This PDF file contains the front matter associated with SPIE Proceedings Volume 13082, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The person can easy to cause ankle injuries in daily activities. Therefore, the demand for ankle rehabilitation treatment is increasing. Due to the long rehabilitation cycle of the ankle joint and there is a shortage of rehabilitation therapists in China, making it difficult to receive timely rehabilitation treatment. Therefore, designing an ankle rehabilitation robot can alleviate the above situation. This thesis first studies the movement space that human ankles can reach. Secondly, determine the robot mechanism as the Stewart mechanism. To calculate the inverse solution of Stewart joint length by Matlab, using Newton method and PSO algorithm to perform forward solution to verify the accuracy of the inverse solution. Finally, the designed Stewart mechanism is imported into Simscape for dynamic simulation and its joint extension is controlled through a PID controller. The simulation results verify that the rehabilitation robot can stably achieve the required posture under PID control.

The thermal management of GIS room directly affects the operation safety and operating cost of substation. The key to the thermal management of GIS room is to adjust and optimize the airflow organization mode of GIS control cabinet. In this paper, CFD model is used to simulate the air flow organization form of GIS control cabinet, the layout and design principles of air supply outlet of GIS control cabinet are discussed, and the design scheme which can effectively reduce the power consumption of air conditioning system and improve the thermal environment in GIS control cabinet is proposed, so as to improve the operating stability of GIS original.

In the radar antenna performance testing system, the system software needs to grasp the azimuth angle of the tested radar in real-time. This article introduces a waveform detection method based on logical judgment of the square wave waveform collected by the DS1102E digital oscilloscope, which effectively converts the radar azimuth code signal into an azimuth angle that can be recognized by the computer, and achieves real-time detection of the radar antenna azimuth angle on a certain type of radar.

In the process of using machine vision technology to detect the edges of circular holes and rectangular slots on furniture panel, the uneven stripes on the panel and the uneven distribution of details in the holes and slots will produce a lot of graphic noise, which will interfere with the edge information of holes and slots and affect the accuracy and stability of the detection results. This article proposes a method based on HSV color space segmentation, which can effectively eliminate unevenly distributed texture and detail noise and deepen edge information, and improve the reliability and accuracy of machine vision edge information. Firstly, the RGB raw image is converted to HSV color space image, and obtain the grayscale image with Hue, Saturation and Value channels. Then the hue channel grayscale image with obvious edge boundary between the hole, slot and the panel is selected, and the appropriate Gaussian kernel is selected for the image to perform Gaussian filtering. Finally, the edge of the filtered image is extracted by adjusting the appropriate upper and lower thresholds and using the Canny operator. The experimental results show that this method can effectively remove the texture of furniture panel and the noise of uneven details in the holes and slots, but also can almost retain the edge of the holes and the whole edge of the panel.

Conventional visual-inertial SLAM(VINS) primarily relying on point features often face challenges in indoor environments characterized by low textures, variable lighting, and fast motions. This is attributed to the difficulty in identifying a substantial number of dependable point features in such scenarios. Considering the abundance of structured features, such as line features in artificial environments, the RPL-VINS is introduced. This system not only harnesses line features to impose additional constraints but also seamlessly integrates them within the loop closure model. Using the Dempster-Shafer evidence theory, the system achieves a tight fusion of point-line loop closure outcomes, dramatically enhancing localization precision. Furthermore, the RGB-D camera's depth information facilitate direct recovery of feature-based 3D information, refining trajectory accuracy. By assimilating point-line features, the RPL-VINS's visual-inertial odometry (VIO) effectively trajectory and localizes the pose of each image frame. Experimental results on public OpenLORIS-Scene dataset reveal that RPL-VINS outperforms VINS-RGBD, PL-VIO, and PL-VINS in terms of performance. While ensuring real-time, it notably enhances trajectory precision and robustness, addressing the performance shortcomings of traditional algorithms in low-texture environments.

The ventilation system of the ship's engine room is a prerequisite for the normal operation of ship equipment, and in order to design a suitable control system, obtaining an accurate theoretical model is particularly important. This article is based on the combination of mechanism method and system identification, improving traditional modeling methods and establishing a more accurate model of the engine room ventilation system. Compared with the improved method, the fitting degree of the model simulation results has been improved from 51.96% to 94.28%, indicating that the improved method produces a higher model accuracy and can better serve the design of control systems.

With the large scale access of distributed photovoltaic, the problem of voltage over limit at the end of low voltage distribution network often occurs, and the traditional centralized voltage over limit management method has too many dependent variables to meet the real time requirements of flexible regulation. In view of the above reasons, this paper proposes a layered and hierarchical flexible control method for grid connection voltage for distributed photovoltaic. Firstly, the voltage overlimit index of different junction points is divided into regions, and the flexible regulation algorithm of reactive power and active power of distributed photovoltaic power generation is proposed. Through the three level governance architecture of voltage overlimit management of junction points, voltage overlimit management of distribution station area and regional voltage overlimit management, the safe and compliant operation of voltage at the end of low voltage distribution network is ensured. Finally, the experimental environment is set up to verify the effectiveness of the layered and hierarchical flexible regulation algorithm on the control of voltage overlimit at the end of the low voltage distribution network.

Aiming at the motion control algorithm of 5-axis industrial robot, this paper establishes a suitable position error analysis model for a KUKA 2700 robot. Based on the variable relationship between the end error of the robot and the parameters of each joint, an approximate compensation method using error mapping is designed based on computer software and numerical simulation tools, which realized the compensation of the position error of the robot and improved the positioning accuracy of the robot. This method is also suitable for error compensation of other mechanism types of robots, and has important application value in robot precision control.

Electric forklifts are becoming widely used for material handling and short distance transportation. Traditional electric forklifts use lead-acid battery packs as the power source, and the hydraulic system has no energy recovery function. a large amount of recyclable potential energy is wasted in the form of overflow loss and heat generation, resulting in low system efficiency. The paper establishes an energy recovery experiment system for heavy electric forklifts with a combination of hydraulic motor and permanent magnet synchronous motor, using lithium iron phosphate batteries for energy storage. The dynamic process of generating current during the energy recovery process is studied. The experimental is shown that the generating current increases with the increase of load and the system becomes more stable.

The paper introduces a small material handling robot system, the system uses Arduino MEGA2560 + NVIDIA Jetson Nano master control to build the whole machine architecture, making full use of its underlying control advantages and arithmetic advantages, which can solve the problem of insufficient arithmetic performance of MCU system and insufficient convenience of the underlying hardware control of ROS system in the traditional robot control scheme. The system uses serial proportional integral derivative(PID) control algorithm to achieve closed-loop control of the robot, and realises self-tuning of PID parameters by particle swarm optimization(PSO) to solve the problems of difficult to guarantee the accuracy of manual parameter adjustment and long parameter adjustment cycle. The paper uses the test vehicle to test 2 kinds of motion control scenarios, and uses MATLAB to track the process of particle swarm parameter self-tuning, and obtains the conclusion that the particle swarm self-tuning is highly efficient and the accuracy is reliable.

With the focus on solar array deployment and latch-up technology for satellite, a solar array deployment mechanism is designed for satellite. This paper introduces its composition and analyses its mechanism. Numerical simulation results given by ADAMS and ANSYS demonstrate that the function and performance of the mechanism is rational. According to the simulation results, deployment time and fundamental frequency of solar array are obtained, and driving torque and latch-up force change trend with time of the mechanism are analyzed. The modeling and simulation methods purposed in this paper can be referenced for further study in designing and manufacturing other solar array deployment mechanisms.

Due to the high voltage electrical equipment's automatic frequency converter speed regulation being easily affected by the control frequency function, the control stability is low. Therefore, a new PLC control method for automatic frequency converter speed regulation of high-voltage electrical equipment is designed. The PLC control protocol of automatic frequency converter speed regulation for high-voltage electrical equipment is designed, and the speed regulation control equation of PLC automatic frequency converter is generated, thus realizing the PLC control of automatic frequency converter speed regulation. The experimental results show that the designed method has good control effect, high control stability, reliability, and certain application value.

Taking a multi-robot production line as the research object, a multi-robot flexible manufacturing production line is established by RobotStudio. The layout of the production line is designed. According to the operation mode of the production line, the signal connection and robot program between the multi-robot and the equipment are studied. The logical relationship between the signals between the systems is established to monitor the collision between the robot and the equipment in real time. Meanwhile, the operation performance parameters of the robot are analyzed The working range of the robot and the position of the wrist joint are analyzed, and the simulation operation and analysis optimization of the multi-robot production line combining die casting, machining, welding and detection are realized. The simulation results show that the production line can be observed in real time, the working performance parameters of the robot can be analyzed and optimized intuitively, the optimal solution of the energy consumption and working time of the robot can be found, and the working range and the position of the wrist joint singular point of the robot can be observed at the same time. The research can provide reference for the establishment and optimization of multi-robot production line.

Aiming at the problems that most of the rotating machinery fault diagnosis algorithms are oriented to labeled data, the cost of label information collection is high and the number of fault samples is far less than that of normal samples, this paper proposes a deep reinforcement learning based rotating machinery fault diagnosis method for unlabeled and imbalanced data. The method leverages the relationship between samples and cluster centers to provide feedback in the form of reward information. It employs mechanical vibration signal samples as model state inputs and fault type selection as selectable actions for the agent. An interactive environment is constructed, allowing the agent to observe, act, and receive rewards in the absence of fault labels. Additionally, a deep neural network is utilized to approximate the Q function, which is then maximized to obtain the optimal policy, enabling fault diagnosis in the absence of labeled data. Through validation with rolling bearing fault data, the proposed method demonstrates a 15% improvement in diagnostic accuracy compared to the K-Means algorithm when dealing with imbalanced data.

In order to explore the fastening scheme of screw sets in electronic components, the workbench of ANSYS finite element analysis software is utilized to establish a simulation model for the process analysis of screw sets. Using the thread preload as the constraint, Workbench is utilized to explore the effects of different tightening sequences and the number of tightening times on the maximum stress of the screws. The simulation results show that 1-3-4-2 can make the screws bear uniformly and the maximum stress is the smallest; the increase in the number of screwing times tends to decrease and then increase the maximum stress of the screws, which can be used by the finite element analysis software to provide a reference for the actual fastening situation.

This paper proposes an improved RRT algorithm based on the cellular decomposition method. In the constructed two-dimensional plane, the space is decomposed into traversable regions and obstacle regions. Subsequently, based on the relationships between adjacent regions, random sampling points are constrained within neighboring regions until expansion reaches the region containing the target node. The planned route is then optimized to effectively address the issue of excessive turning points. Simulation results demonstrate that the improved RRT algorithm enhances path planning accuracy and efficiency in the application of two-dimensional mobile robot navigation, reducing travel distances and lowering cost consumption.

With the rapid development of new power systems mainly based on renewable energy resources, coupled with the increase of seasonal loads, the problems of heavy/overload transformer during peak summer, winter and major holidays are becoming more and more serious every year, which seriously affects the service life of transformers and the reliability of power supply. One of the important means to solve the transformer heavy/overload problem is to adjust and transfer the load in advance by load prediction, so it is crucial to achieve accurate prediction of transformer load. In this paper, A short-term load prediction model based on long and short-term memory recurrent neural network (LSTM) with deep learning is built to predict the load level of transformers in the coming week using the historical load of transformers, holiday information and meteorological data as input. The accuracy of transformer load prediction is verified on Matlab using two 35kV transformers with a capacity of 5000kVA as an example.

Localization is a prerequisite for mobile robots to achieve path planning, autonomous navigation, and decision-making. In localization, maps provide mobile robots with the ability to perceive and model the environment, so the choice of an appropriate map representation has a significant impact on the localization effect of mobile robots. From the perspective of usage matching, this paper divides map representations for mobile robot localization into four categories based on different focuses of describing the environment, which are metric maps, feature maps, topological maps, and semantic maps. The principles, characteristics, and classic cases of these representations are also analyzed in this paper. Furthermore, the applicable working conditions of each type of map representation are summarized to provide effective guidance for mobile robot localization.

In response to the requirements for target identification and tracking in battlefield scenarios, a design has been developed that integrates the control methodologies of hexapod robots with the principles of machine vision. This encompasses the creation of a compact, biomimetic hexapod unmanned combat robot that is based on machine vision principles. The core approach involves the utilization of a high-frame-rate wide-angle camera mounted on the hexapod robot to perform target recognition and tracking on chest ring targets. This is achieved by employing the YOLOv5 and Deepsort algorithms for target detection and tracking, allowing the acquisition of target centroid coordinates. These coordinates are then transmitted to an Arduino development board to govern the hexapod robot's movement. Furthermore, the system has been augmented with an electronic ignition module and firing mechanism, enabling precise firepower upon target locking. By effectively integrating machine vision and hexapod robot motion control technologies, this system provides a comprehensive exposition of the detailed implementation of automated target engagement.

The fault diagnosis method of rotating machinery has always been a research hotspot, and the fault diagnosis method based on deep learning has a great dependence on the sample size, which cannot maintain its advantages in the fault diagnosis of small data industry. Aiming at this problem, this paper applies the method of multi-agent reinforcement learning in the field of image classification to the field of fault diagnosis. Aiming at the disadvantage that the reward function in this method cannot provide timely feedback information for classification, a new reinforce reward is introduced. Under its guidance, the agent can adjust the strategy faster, which significantly improves the learning efficiency and exploration efficiency of the agent. The accuracy of the method on small sample data is improved by more than 6 %, which provides a more practical solution for the field of industrial fault diagnosis.

The valve-controlled and pump-controlled hydraulic technology are both extensively used in hydraulic equipment nowadays, but the valve-controlled hydraulic technology has obvious shortcomings such as the lower power utilization rate due to the inevitable throttling and overflow losses. Pump-controlled hydraulic technology can enhance the efficiency of the entire hydraulic system owing to eliminate these energy losses and overcome the defects of valve-controlled technology. Electro-hydraulic actuator (EHA) is an archetypal pump control system with the huge advantages of high power-to-weight ratio, low energy consumption and compact structure. As a consequence, research on EHA has become a hot topic in the field of fluid power transmission and control by degrees. To date, many predecessors have conducted in-depth exploration on the investigation related to EHA. However, the relevant literatures are extremely scattered, and the research directions of these papers are unequal so that it is quite necessary and meaningful to classify and summarize the whole development history of EHA. This review mainly introduces the evolvement of EHA in the three major fields that include aerospace, engineering machinery and robotics from the origin to the current, aiming at clarifying underlying issues and challenges in the study and application of EHA and discussing the further development tendency of this technology. The outlining content gathered in this document not only will be a valuable comprehensive source of information concerning EHA to scholars, but also provides a forceful reference for future studies with regard to high-power density and energy-efficient hydraulic technique.

The mechanical-electrical-hydraulic systems are developing towards automation and intelligence, which raise higher requirements for accurate and smart fault diagnosis of the core component in these systems. Traditional diagnostic methods not only rely too much on a priori knowledge for feature extraction but also have limited computational ability for massive data, which can’t satisfy the demand for intelligent fault diagnosis. Thanks to the deep network structure, deep learning (DL) can automatically extract the deep implicit feature information from multiple data without a priori knowledge and has an immense advantage in realizing complicated fault diagnosis. As a typical representative of deep learning, Convolutional neural network (CNN) can directly process images and has made significant achievements in image recognition and classification, therefore scholars have conducted extensive research on CNN for fault diagnosis. Based on the above-mentioned content, this review sorts out the current research works employing the 1DCNN model, 2DCNN model and hybrid model of CNN for fault diagnosis in mechanical-electrical-hydraulic systems, and then summarizes the advantages and disadvantages of the three CNN models, respectively. Finally, we discuss the future development directions and challenges of fault diagnosis with CNN.

With the rapid development of VR technology, the accuracy of virtual scene construction has also increased. This article proposes a high-precision virtual scene generation algorithm. On the basis of reducing the low data utilization during the modeling process, we cleverly use programmatic methods to generate the accuracy values of the building. At the same time, the building facade is processed as block units, and the model texture details are fed back to the block units through neural network learning algorithms. Using target detection algorithms for target recognition and related optimization to improve the accuracy of object layout within the model and seek the optimal layout solution. Finally, combined with VR rapid generation technology, the model is transformed into components in the virtual scene, and the virtual scene is constructed using the design of three parts: existing scenes, cross end collaboration, and roaming display in the original model library. The results show that the finished product displayed to users using this algorithm has a higher degree of restoration.

Indoor differential-driven mobile robots play a crucial role in industrial applications such as intelligent inspection and smart transportation. In scenarios with uneven road friction and/or sharp turn, challenges remain for accurate robot localization in indoor environment. When using encoders of the wheel odometry as the sole basis, the robot will lead to significant odometry drift and inaccurate localization. To optimize the wheel odometry data, this paper presents an internal and external combined sensor fusion method for laser simultaneous localization and mapping (SLAM) system. Experimental results demonstrate that the proposed method significantly reduces cumulative localization error by comparing with method using solely wheel odometry. It also effectively corrects an average translational odometry error caused by inherent wheel odometry drift.

Failure of the supporting wheel of the rotary kiln may directly lead to abnormal operating conditions of the kiln. Monitoring the operating status of supporting wheels and providing early warning can greatly reduce the occurrence of rotary kiln failures. This article proposes an online monitoring system for the force on the supporting rollers of a rotary kiln based on the VMD algorithm, which monitors the axial and radial forces on the supporting rollers. This system consists of a laser displacement sensor, ZigBee communication technology and VMD signal processing method to monitor changes in the axial displacement and radial eccentricity of the supporting wheel. This system has been proven effective after actual deployment in a cement plant in Sichuan. It can prevent and reduce possible failures of supporting wheels, extend the operating life of the rotary kiln, and increase economic benefits.

This paper proposes a fire detection algorithm based on improved YOLOv5 to address the issues of delayed and prone to false alarms in traditional fire systems. The proposed algorithm adopts the anchor-free object detection method, which reduces the number of parameters of the deep learning network model to improve reasoning speed. In addition, this proposed algorithm improves the precision of target detection by improving YOLOv5 backbone network structure, neck structure and detection head. The experimental simulation results show that the detection accuracy of proposed algorithm can reach 72.2%, which can effectively realize the intelligent fire detection.

This paper reviews global research on following and obstacle avoidance technology for intelligent robots, examining their current status, types, advantages, and disadvantages. It delves into the AI algorithm landscape, development trends, and challenges worldwide. Additionally, it explores the theoretical background and technical solutions for follow robots, offering an overall system architecture analysis considering hardware and software aspects. In the single-task mode, the service robot has a small application field and a low degree of intelligence. In the case of multitasking, the computing power cost of service robots is high, which leads to a significant increase in energy consumption and shortens the battery life. In view of the above problems, a low-power, multitask follow-up robot system based on the ROS platform is designed in this study, and the system can realize intelligent switching under two tasks of fixed-point cruise and visual follow-up. In terms of hardware, a low-energy heterogeneous computing platform is established to ensure that the same computing power is output while reducing energy consumption. In terms of software, according to the nature of the heterogeneous computing platform, the algorithm framework of the follow-up robot system is designed. Finally, the article proposes a design for an intelligent robot based on visual follow, integrating industrial control, sensing, and data processing technologies.

In the application of vision-guided robotic grasping, 2D position/orientation and 3D depth information are needed. This paper proposes a method for detecting the 4-DoF grasping of unknown objects, which using the combined RGB image and 3D point clouds data by RGB-D camera. The 3-DoF grasp information is obtained by segmenting the target region from the RGB image. Then the depth is converted into a point cloud image by 3D reconstruction. By using an improved RANSAC to fit point cloud planes of the background and object, the height difference between object surface and the planar bottom is determined. The information of Z-axis grasping depth for achieving 4-DoF grasping is determined by RANSAC plane fitting. Experiments are conducted to verify and validate the effectiveness of the proposed method in automated robotic grasping.

To make the mobile robot autonomously plan a collision-free shortest path in an unknown complex environment, a dung beetle optimization algorithm in the swarm intelligence algorithm is applied to the path planning problem. The basic dung beetle optimization technique is not very good at global exploration. Therefore, this paper improves it in two aspects. The first step in initializing the population is to employ an enhanced Sine chaotic mapping, which has a more uniform distribution in phase space, instead of random numbers. Secondly, dung beetles’ dancing locations are updated by using the MSA algorithm. The DBO method's global optimization capacity and convergence accuracy are improved by the nonlinear decreasing control parameters and adaptively varying inertia weight coefficients in the MSA algorithm. Through the creation of a grid map simulation environment in Matlab, it is possible to observe that the enhanced dung beetle optimization algorithm performs better in finding the shortest path than both the DBO algorithm and the GWO algorithm by converging faster and searching for shorter path lengths.

In order to make the State Of Charge(SOC) of lithium batteries in new energy vehicles more accurate, this paper uses the Coati Optimisation Algorithm(COA) to find the optimal noise variance value of the Extended Kalman Filter(EKF) to achieve a more accurate SOC estimation. After establishing the empirical model of the lithium battery, the Recursive Least Squares with Forgetting Factor (FFRLS) is used to identify its parameters, and the COA is used to establish the error correction model, and this is used to find the optimal noise covariance value of the gain matrix, which overcomes the problems of filter dispersion and large SOC estimation error due to real-time variation of battery parameters and uncertainty of filter noise is overcome. The results of the designed simulation experiments show that this optimisation algorithm can effectively solve the dispersion problem of filtering and improve the accuracy of SOC estimation, and has good convergence and robustness with high application value.

Driving intention recognition is one of the key technologies in the development of advanced assisted driving systems (ADAS), which can greatly reduce the occurrence of traffic accidents and thus improve driving safety and comfort. In order to recognize driving intention more effectively and accurately, this paper proposes a method to improve the recognition rate of driving intention based on Long Short-term Memory (LSTM) network optimized by Coati Optimization Algorithm (COA). First, the training dataset and test set based on the road information dataset are established by considering the degree of influence of feature factors on driving intention. Second, the COA-LSTM driving intention recognition model is constructed. Finally, the training and validation evaluation metrics are performed based on the dataset, and the results show that the COA-LSTM-based driving intention recognition model proposed in this paper is better than the LSTM and BP models as a whole, and the accuracy rate and the F_lmacro score are both above 0.95.

Ensuring the reliability of the traction transformer, which is a critical electrical equipment for trains, is crucial for the entire electrified railway. Hence, increasing the precision of fault diagnosis for train traction transformers is necessary. A model using the dung beetle optimization (DBO) algorithm to optimize the deep belief network (DBN) to realize fault diagnosis of traction transformers is presented. Firstly, the DBO is employed to optimize the learning rate and the quantity of neurons in every hidden layer of DBN. Then, the optimized fundamental parameter values are assigned to the DBN to obtain the optimized DBO-DBN fault diagnosis model. Finally, the traction transformer's DGA online monitoring data and the manual oil sample data were used to verify the method. According to experiment findings, the proposed DBO-DBN model can identify faults with up to 95.8% precision. Compared with the basic DBN, SVM, and BPNN approaches, the proposed method's precision for classification rises by 3.3%, 8.3%, and 12.5%, respectively, which verifies the effectiveness of the proposed method. It furnishes an effective tool for the fault diagnosis of traction transformers.

The state of the motor greatly affects the overall performance of the transmission system, and implementing advanced motor fault diagnosis technology can prevent substantial financial losses. Deep learning algorithms, such as convolutional neural networks, are increasingly gaining popularity due to their ability to handle the prominent challenges posed by high feature dimensionality, large datasets, ambiguous labels, and sparse occurrence of motor fault types and causes. This paper extensively examines the usage of convolutional neural networks (CNN) and their different versions in different motor fault diagnosis problems by analyzing a wide range of international journal papers, leading to essential findings.

The Relevance Vector Machine (RVM) which has uncertain expression and management capabilities becomes an effective method for estimating the state of charge (SOC) of Li-ion batteries. However, the algorithm has the problems of low multi-step prediction accuracy and poor online prediction adaptability, which limits its application for battery SOC estimation. So, an improved incremental RVM model is proposed to predict the SOC of Li-ion battery online. Through the ways of dynamic training model and on-line incremental learning to improve the prediction accuracy of the model, and the fast-sequence sparse Bayesian learning algorithm is selected for training to reduce the computational complexity and improve the computational efficiency of the algorithm. The study found that this model can guarantee higher prediction accuracy by adjusting the kernel width automatically. Experimental results show that this method has the characteristics of high prediction accuracy, fast calculation speed, and strong universality, it can provide a reference for Li-ion batteries SOC prediction and application.

Fault diagnosis can effectively improve the power generation of the wind turbines. Deep learning has promoted the intelligent development of wind turbine fault diagnosis. Traditional deep learning usually requires a sufficient amount of labeled data. However, for newly constructed wind turbines, there are problems such as insufficient samples, limited labels, variable operating conditions. Transfer learning provides a new way to solve these problems. Establishing appropriate models to reduce the distribution differences between existing and newly built units is the key to improving unsupervised fault diagnosis accuracy for newly built units. To address these challenges, a novel multi-task transfer model based on improved model agnostic meta learning (MT-TL-MAML) was proposed to realize unsupervised fault diagnosis of newly constructed wind turbines. The proposed model utilizes the advantages of MAML in generalization of new tasks and small sample diagnosis, and can adapt to randomly changing working conditions. By means of iterative learning, the gap between source domain and target domain is further narrowed, and the classifier can realize more accurate diagnosis of target domain data. This article takes the SCADA and CMS data of two wind farms as case studies to conduct unsupervised fault diagnosis and compare it with other literatures. The results validate the advantages of the proposed model in unsupervised fault diagnosis of newly constructed wind turbines.

The theoretical efficiency of class E power amplifier can reach 100 %，it is often used as a power module for magnetically coupled resonant wireless power transmission systems. In practical work, the equivalent load of MCR-WPT system may deviate from the theoretical design value of class E power amplifier, it will affects the operating characteristics of the power amplifier and Causes the system transmission efficiency to drop. To solve this problem, an automatic impedance matching method for tracking the real-time change of load is proposed. First of all, based on Smith chart theory, an L-shaped matching network covering global matching is constructed, and an improved particle swarm optimization algorithm is proposed, It shows that the algorithm is superior to the traditional algorithm in matching accuracy and stability, Perfect matching can be achieved after a few iterations. Finally, it is proved that this method has certain application value in impedance matching design.

This paper introduces the design of a three-degree-of-freedom parallel piezoelectric micro-platform with simple and compact structure, large stroke and no coupling. Firstly, the driving unit of the micro-moving platform is designed by using the flexible bridge amplifier mechanism of double-layer flexible thin plate, and the platform body of the micro-moving platform is designed based on the double-parallelogram flexible mechanism, and then a new configuration of the x-y-θz parallel piezoelectric micro-moving platform with large displacement stroke is designed. Finally, the static and dynamic performance of the platform is tested by finite element simulation. The results show that the developed platform performs well, and the platform along x, y and θz direction is 308.72μm, 404.72μm and 2.79mrad, and the natural frequencies are 101.76 Hz, 119.71 Hz, and 134.53 Hz, respectively.

The digital final assembly of spacecraft uses the three-dimensional model and bill of materials of the spacecraft assembly as the core carrier for design information transmission. The design intent and design parameters are intuitively and structurally reflected in the three-dimensional model and bill of materials. The three-dimensional model is used to directly guide the on-site production work of the spacecraft assembly, while also controlling the technical status. The digital assembly practice of a certain satellite has shown that the digital assembly of spacecraft has overcome the shortcomings of low efficiency, serial operation, and information dispersion in traditional modes, achieving parallelism, collaboration, and integration. The efficiency and quality of design and implementation have been significantly improved.

Aircraft liquid flow test is very important to evaluate the performance and state of aircraft systems, and reasonable liquid flow is the guarantee that aircraft can fly normally. Traditional flow measurement is mostly used by turbine flow meters, while ultrasonic flow measurement has the advantages of non-contact and convenient installation, which is an innovation and progress for aircraft liquid flow measurement. In the article, a time-difference ultrasonic flow measurement system based on high-precision time-to-digital conversion chip TDC-GP2 is designed, the basic principle of improved time-difference measurement is introduced, the hardware and software design of the system are discussed, and the preliminary test of ultrasonic flow measurement system is completed. The test results show that the designed ultrasonic flow measurement system has high time measurement accuracy and good stability, which provides great guidance for the test of aircraft liquid flow.

In order to solve the problem of fatigue failure of the connecting bolts between the integrated subframe and the girder under the continuous high load of the chassis of a light combat vehicle, the rigid strength of the superstructure and the chassis is reduced, which affects the shooting stability. Combined with the structural characteristics of rigid connection between different materials of subframe and beam, the location and cause of bolt failure are analyzed, the "Bolt clearance connection method " is proposed, the finite element calculation model of integrated subframe and girder is established, and the mechanical characteristics of the bolt connection between the original and improved scheme are studied, and the results show that under the continuous high-intensity load of off-road surface, the method can effectively reduce the equivalent force at the bolt joint, and realize the reliable connection between the subframe and the girder in the high and low and lateral directions. Solve the rigid fixing problem of two different materials. It provides a certain reference for the optimization design of light off-road chassis stability.

Undesirable shock vibrations are widely distributed in the mechanical field. Shock damping through bionic structures is a more effective method for vibration suppression. The Elytra structure of the ladybug has the characteristics of buffering and vibration reduction, and it is an efficient structure that can realize bionic vibration reduction. Based on the analysis of the vibration absorption principle of the Elytra structure, this paper adopts the symmetric structure and frictional energy dissipation method to design an Elytra structure like an initial circular beam damping structure. To explore the effect of different features on the vibration reduction performance, the bionic structure is studied by simulation analysis and experimental methods. In order to study the effect of the bionic structure on single and periodic vibrations, mechanical simulation analysis is performed using single impact and periodic continuous vibrations of dropping objects, and an experimental setup is built to collect the corresponding vibration signals, so as to analyze the performance of the vibration reduction structure. The results show that the designed bionic sheath-fin vibration reduction structure not only has a buffering and energy absorption effect on the instantaneous impact but also has a good suppression effect on the low-frequency continuous vibration.

Composite sandwich structures are increasingly widely used in aircraft structures due to their own characteristics, and it is more and more necessary to study the strength performance of composite sandwich structures. In this paper, through the lateral compression test of fiber-reinforced composite sandwich structure of honeycomb and foam sandwich, the test load-displacement curve and failure mode are analyzed, and the finite element analysis is carried out. The calculated failure load and failure mode are also in good agreement with the test results, which provides the test and analysis basis for engineering design and application.

Ensuring the safety state of a product is a crucial consideration during system design, especially during transient periods such as power-up when the logic loading process occurs. Poor design in such cases can often lead to false outputs from the product, causing unintended operation of external loads and posing risks. To guarantee that the product meets the safety requirements during power-up transients, this article proposes an improved hardware configuration design during FPGA loading. The effectiveness of the improved design is verified through implementation and validation, and several key points to be noted in subsequent designs are summarized.

In recent years, additive manufacturing technology (3D printing) has gained widespread popularity across various industries due to its remarkable capacity for producing intricate structures. However, the construction of its manufacturing often suffers from defects, such as warping, shrinkage, and low dimensional accuracy, which reduces the functionality of 3D printed parts. These issues, particularly, impact the production of thin-walled structures, compromising both accuracy and strength. This paper investigates the quality performance of thin-walled 3D printing models. A total of 27 identical models were crafted using polylactic acid (PLA) material on a low-cost 3D printer. We focused primarily on three factors: layer height, temperature, and printing direction, investigating shrinkage and Z-direction strength within varying conditions. The findings reveal that by adopting higher temperatures and lower layer heights under specific conditions, the 3D printed thin-walled structure made of PLA material can be optimized for shrinkage control and enhanced strength. The distinctions in shrinkage and strength between structures printed in different directions are relatively small, while the variances observed at different model heights are significant.

With the increase of elevator operating speed, it is greatly affected by air disturbance, which leads to the increase of elevator cost and energy consumption, and has a huge impact on the safety, reliability and comfort of elevator operation. To improve the aerodynamic characteristics of the cabin flow field, this paper parameterizes the flow guide hoods with a structure similar to an ellipse, selecting eight design parameters. Taking the aerodynamic drag coefficient and the yawing moment coefficient as the optimization objectives, four surrogate models were constructed by using the optimal Latin hypercube design sample points and the prediction accuracy was compared. Finally, the EBF surrogate model with higher fitting accuracy was selected, and combined with the NSGA-II optimization algorithm to carry out multi-objective optimization of the flow guide hood, obtaining a series of Pareto solutions, and finally comparing and analyzing the aerodynamic performance of the flow guide hood before and after optimization. Finally, on the basis of the optimized flow guide hood, the aerodynamic characteristics of the cabin under actual operating conditions were analyzed. The results show that the installation of the flow guide hood can reduce the drag coefficient of the cabin; within a certain range, increasing the total height of the flow guide hood, the vertex offset and the inertia of the flow guide hood in the X direction can improve the aerodynamic performance of the ultra-high speed elevator system. The running scenarios such as start acceleration, smooth running, deceleration and stop will affect the aerodynamic performance of the cabin, and this study provides a reference for the optimization design of the flow guide hood and the operating conditions of the elevator.

In order to enhance the reliability of power operational amplifiers, it is essential to prevent sudden current surges that can lead to an instantaneous increase in circuit temperature and damage the internal transistors of the chip. Through testing its limit current, it was observed that connecting the device to a small load resulted in excessive output current. Therefore, by combining TRIZ theory with ANSYS Q3D simulation software, the resistance of the final protection resistor is approximately 0.13Ω. Aiming at safeguarding the device and significantly improving its life.

Multilayer ceramic substrate is mostly used in electronic packaging substrate because of its high strength, good insulation, excellent thermal conductivity and heat resistance, small thermal expansion coefficient and stable chemical properties. In this paper, solid works is used for 3D modeling, including bare chip, three-layer ceramic substrate, substrate through hole, copper-covered wiring. At the same time, ANSYS workbench software was used for finite element analysis and thermodynamic coupling simulation method was adopted, that is, temperature field data was imported into the structure field. The results showed that the deformation and stress were not large and the thermodynamic performance of the structure was stable under the cyclic test at -65°C-150°C standard temperature.

The wafer carrier structure in semiconductor special device was designed and optimized in this study according to functional requirements of high-temperature heating and low-temperature cooling as well as planeness requirement of vacuum adsorption. The layout of vacuum absorption structure, high-temperature heating unit and low-temperature cooling unit was determined by calculation and simulation. The ultimate structure of wafer carrier was determined through experimental verification. Results showed that surface evenness of this wafer carrier is lower than 30μm in the temperature range of -65 ~ 300 °C and it meets the design requirement of temperature fluctuation lower than ± 5°C.

At present, structural topology optimization in mechanical equipment with excellent performance by optimizing the arrangement and distribution of materials in the design domain, which has important significance in the initial stage of mechanical material design. However, most of existing research on mechanical structure optimization concentrates on planar or simple three-dimensional structures, and can only solve some topology optimization problems with simple initial structure, optimized design domain rules, and single optimization constraints. In this paper, we extract a real mechanical bracket topology information and optimize the topology structure by utilizing the variable density method. After optimizing the topology, we compare our results with existing optimization methods and estimate the performance of different materials. From our extensive experiments, we can conclude that our proposed method can achieve the optimization process for mechanical components and outperform existing methods with acceptable stress and reasonable weights.

Voiceprint recognition is a technology that verifies or identifies individuals by analysing their speech signals. Traditional voiceprint recognition methods have issues like inaccurate feature extraction and weak robustness. To enhance the performance of voiceprint recognition, this paper adopts the triplet loss and its optimization. By employing the optimized triplet loss, we can effectively improve the accuracy and robustness of voiceprint recognition.

The optimization design of energy management strategies for pure electric vehicles holds significant importance. This research aims to design an energy management strategy for pure electric vehicles based on the dynamic programming algorithm and conduct simulation tests and data analysis on a specific model of pure electric vehicle. By comparing the results with real-world data, the following key findings have been obtained: The adoption of the dynamic programming energy management strategy effectively reduces the overall vehicle power demand under the CLTC driving cycle, with a reduction of 4.6% under normal temperature conditions and 2.8% under low temperature conditions. The degradation rate of the electric vehicle's range in low-temperature conditions decreased from 36.2% to 31.9%. These results indicate that through the optimization design of a rational energy management strategy, pure electric vehicles can achieve better performance. Therefore, this research provides valuable insights for further improvement and sustainable development of pure electric vehicle technology.

Real time and stability are crucial requirements in transmission line inspection. Software can quickly process image data and output results while maintaining stability to cope with various complex environments and operating conditions, which is highly challenging. Therefore, this article designs a new X-ray digital imaging software for transmission line inspection robots. The imaging system for robot X-ray defect detection software is composed of a BJI-1X light generator and a Raines digital imager. According to this imaging principle, internal image information of defects is collected using X-ray digital imaging instruments, and defect categories are obtained using image processing software based on its hierarchical recognition model. Using Faster RCNN algorithm to construct defect area localization model, improve digital imaging accuracy, and ultimately output digital imaging results. The experimental results show that when the balance factor is set to 0.30 and the adjustment factor is set to 1.5, the software in this paper has the highest accuracy in digital imaging of defects. The software in this article can accurately locate the defect area, obtain its location boundary box, and has high clarity. It also has excellent digital imaging performance in determining the type of digital imaging defect.

To study the design method of pool centrifugal pumps and the feasibility of drilling balance holes, upon the summary of six excellent hydraulic models, this paper proposed an innovative VCM (velocity-coefficient method)-based hydraulic design method for optimizing cavitation performance of centrifugal pumps. This innovative method has been field-proven with high accuracy and practicability. Based on that, a pool centrifugal pump type was developed with a specific speed of up to 175 rps, and the hydraulic design process and outcomes were elaborated. Moreover, the effect of balance holes on pump performance was discussed, and based on the SST k-ω turbulence model, the performance-axial force curves were plotted under different flow rate conditions of the modeled pumps with and without balance holes upon computations in the numerical simulation models of pool pumps established through the finite volume method (FVM). The analysis shows that balance holes are conducive to a decrease in the axial force by up to 19.6% but greatly affect pump performance due to their hydraulic characteristics. This paper provides a constructive scientific basis for optimizing design and improving the reliability of centrifugal pumps.

This study presents a geometrically parameterized model for the Tesla valve and investigates the factors influencing its flow resistance characteristics. The research demonstrates that increasing the number of internal channels intensifies fluid collisions at intersection points, resulting in heightened pressure losses at bends and intersections in horizontal pipelines. The effectiveness of the modified Tesla valve structure is analyzed using finite element methods. Experimental validation corroborates the research findings. This study not only unveils the intricate mechanisms governing the flow resistance properties of the Tesla valve but also lays a scientific foundation for enhancing its performance. The practical experiments conducted contribute to validating theoretical advancements, underscoring the practical applicability of the research results. Overall, this study deepens the understanding of the complexity of the Tesla valve, providing a scientific basis for its optimization in practical engineering applications.

LPG storage tanks are important equipment for LPG storage and transportation, and the strength design of their supporting structures has a significant impact on the smooth operation of the entire LPG storage tank. This article combines the design and verification methods of stress analysis and strength assessment in the pressure vessel design and manufacturing specifications and GB/T 150 "Pressure Vessels" regulations. By combining rule design and finite element verification, the strength design of LPG storage tanks and their supporting structures is carried out, which can provide reference for the structural design of LPG storage tanks on liquefied petroleum gas tankers.

Aiming at the complexity of the assembly process of the candy pushing mechanism of the BZ350 candy packaging machine and other problems, this paper develops a virtual assembly system based on the BZ350 candy packaging machine. Through SolidWorks to establish a three-dimensional model, with Yixinghe engine and Visual Studio as the system development environment, using the augmented reality device HTC VIVE rich means of human-computer interaction, to realize a set of manual assembly of the virtual assembly system. The experiment shows that: the virtual assembly system reproduces the assembly process and assembly path of the BZ350 candy packaging machine, scores the assembly results as well as saves them, and the time required to complete an assembly experiment of twisted parts is about 9 minutes. The system has good immersion and interactivity, which effectively improves the quality and efficiency of product assembly, and the practical application effect is remarkable, providing users with an intuitive sense of the scene and a new product design mode.

The shape and parameters of hardware are diverse, so the robot needs to have high precision to ensure the correct docking of hardware and apply appropriate force. In order to avoid damaging the hardware fittings, this paper designs an automatic online and offline system for the quality inspection robot of the power transmission line hardware fittings. The hardware structure includes user layer module, decision layer module, execution layer module and equipment layer module. The four functional modules work in coordination to enhance the robot trajectory planning effect. In the software part, the S-shaped trajectory planning method is improved to ensure the shortest planned path distance, and when the robot encounters obstacles, it can quickly plan straight and turning paths to effectively avoid obstacles, thus completing the design of the robot automatic online and offline system. The experimental results show that the trajectory error of the proposed method is less than 0.1rad.

This paper examines the global development of intelligent robots, focusing on remote avatar robots. Some key technologies are researched such as mixed reality and teleoperation by analyzing their status, trends, and challenges. Theoretical background and technical solutions for remote avatar robots are explored, covering hardware and software aspects. A new intelligent robot system for hot-line working with flexible arms, force feedback teleoperation controller and mixed reality technology is established. The robot system in the air can fulfill the working like the wire stripping and removal by human teleoperating with mixed reality scene in the ground, meanwhile a security system of UAV with full perception monitoring and active intervention is cooperated in the air. In the end, the article proposes a prototype design integrating teleoperation, mixed reality, and 5G communication for live working in 10KV high-voltage environments, validated through experiments.

A temperature monitoring system for rotary kilns, based on LoRa technology, has been designed to address challenges such as difficult on-site wiring, high costs, and maintenance and management complexities. The system consists of six distributed terminal collection nodes located on both sides of the various kiln sections, LoRa communication modules, and an upper-level computer system. The collection nodes are composed of STM32L series microcontrollers and infrared sensors, which collect temperature data and transmit it wirelessly using LoRa technology. The temperature data collected by the nodes is transmitted over a LoRaWAN network to a LoRaWAN gateway and further uploaded to the upper-level computer system via RS485 serial communication. Monitoring personnel can observe real-time temperature data on both sides of the rotary kiln at various sections through a PC interface. This system offers advantages such as low power consumption, a simple structure, and ease of maintenance, making it highly applicable in the field of rotary kiln temperature monitoring with broad engineering prospects.

This paper introduces a parametric design system for mortise and tenon structure based on Solid Works. Parametric design is utilized in the design of mortise and tenon structure models, and VB is used as a secondary development tool in solid works modeling software to develop a set of mortise and tenon structure parametric design system, which realizes the rapid and accurate modeling and optimization design of mortise and tenon structure. By controlling the parameterization, users can flexibly adjust the shape, size and connection of the mortise and tenon structure to meet different design requirements. The system has been verified through practical application to have significant advantages in improving design efficiency and quality.

In order to effectively improve the urban and rural environment and promote the recycling of resources, it is imperative to carry out waste classification. Garbage sorting often has problems such as a wide variety of garbage, difficulty in advancing, and inconvenient use of trash cans. Therefore, this paper designs an intelligent garbage sorting system based on the STM32F103C8T6 single-chip microcomputer as the main control core. The HC-SR04 ultrasonic ranging module is used to detect the distance between obstacles (referring to people) and the trash can. In this design, when the distance between the human body and the trash can is detected to be less than 10cm, the entire system will be awakened and started. The LD3320 voice recognition module is combined with the JR6001 voice broadcast module to realize voice-activated opening of the designated trash can without manual opening and closing of the trash can lid. Detect the light intensity of the environment through the photoresistor, and use the low level to automatically control the USB light to realize night lighting. The overflow of the trash can is detected through the infrared tube module, and at the same time, the overflow of a certain trash can is sent to the mobile phone of the cleaning staff through the SIM800C communication module, which is convenient for the cleaning staff to deal with in real time. The results of multiple tests show that the functions of the system are stable and accurate, and can meet the characteristics of high recognition rate, low cost, and strong practicability. It can be applied in the field of garbage classification and has good promotion value.

Due to the small production of aircraft products, the deviation data is small sample sizes, so assembly deviation can’t be calculated by the probability statistics method. In addition, because the aircraft structure is flexible, it is easy to deform during assembly, so assembly deviation can’t be calculated by assembly dimension chains. Therefore, a multi-level assembly deviation prediction method of aircraft structure is proposed based on the grey prediction theory. Firstly, according to deviation detecting data of assembly part, the deviation prediction model is established. Then the deviation prediction data is calculated based on the deviation prediction model. Secondly, integrating prediction data into the next assembly level, the deviation prediction data of the next assembly level is calculated by building the prediction model of the next assembly level. Finally, the prediction data is fused to the next assembly level continuously, until the assembly deviation prediction data of the product is calculated. The application cases show that the accuracy of the deviation prediction method is 96.0%, which verifies the feasibility and accuracy of the prediction method proposed in this paper.

To solve the problem of low efficiency involved in manually inserting power sockets into soft wires, a new system called an automatic insertion wire device of mechanical arm as a part of intelligent agents has been designed. It has a manipulator end lead channel actuator, a two-degree-of-freedom manipulator, a scissor bending mechanism and a control system. A coordinate system has been established for kinematics analyses and inverse kinematics solution. The joint angles of the manipulator when reaching the terminal hole of the power socket are 47.7° and 91.3° for joint angles 1 and 2, respectively. The motions of the scissor bending mechanism are analyzed using a coordinate system, and the rotation angle of support rod 1 is found to be 32.3° after the completion of soft wire bending. A model of the actuator and scissor bending mechanism is created using SolidWorks, and motion simulations are carried out to verify the insertion of soft wire. A prototype is built and tested, which demonstrates that the angle variation range of the soft wire head part due to push block movement is between 58° and 63°, while the angle variation range of the shear fork bending mechanism to other parts of the soft wire is between 168° and 173°. All parameters meet the anticipated goal, effectively resolving the problem of low efficiency.

In order to study the effects of different parameters on the mechanical properties of composite mixed (bolted/bonded) joint structure, this paper built a CFRP/steel single shear double-nail mixed joint structure model based on the known material parameters, Hashin criterion and quade adhesive layer failure criterion, and established a finite element simulation model in Abaqus software. Parameters such as lay-up Angle, lay-up thickness, hole size, bolt end distance and so on were changed respectively. The simulation results show that when the lay-up Angle is [0/45/90/-45]_2s, the lay-up thickness is 0.26mm, the opening size is 5mm, and the end distance is 7.5mm, the overall connection strength of the structure is the highest.

At present, farmers in remote areas of China still rely on traditional methods to raise cattle and sheep, which results in low efficiency and high labor costs. Therefore, most ordinary farmers urgently need a miniature feed mixer to process crop by-products into feed that can be consumed by livestock. Although the micro mixer is small in size, due to the toughness and strength of the grass, it still has the same cutting force of the twisting arm and the kneading wire as the large feed mixer. Therefore, during the operation of the mixing operation, it will produce relatively large impact and vibration noise. In response to the above issues, this article uses the finite element method to model and analyze the vibration characteristics of the silo part of a small fully mixed feed mixer. It is found that the first two natural frequencies of the structure are exactly within its working frequency range, and resonance phenomena will inevitably occur. This will generate noise that causes harm to the human body and also damage the structure of the feed machine, affecting its normal operation and damaging working components, Reduce the service life of the feed mixer. So, based on its first six modal shapes, the structure was optimized and improved, and finally a structure was designed that can effectively avoid the working frequency of a small fully mixed feed mixer.

This paper studies a table tennis picking robot based on robot technology. The ball picking robot can automatically identify the ping-pong ball through CMOS image recognition technology, and pick up the ball through the rotating fan impeller, and then sweep the ball through the conveyor to the storage device. In addition, the robot is also equipped with infrared sensors that can monitor the surrounding environment, so as to achieve automatic obstacle avoidance and avoid collision between the robot and obstacles. This paper mainly studies the structural design principle of the ping pong picking robot, aiming at improving the efficiency and stability of the robot.

This paper designed a pineapple peeling machine which can realize peeling, core, head and tail and push out pineapple. The final product of pineapple is cylindrical hollow pineapple. The process was divided into two parts. First, the outer skin of the pineapple was cut through a rotating knife barrel. Then according to the processing principle of the four-station machine tool, the processing process was designed into five processes, respectively, pushing in, cutting the pineapple front end, cutting the pineapple back end, the core, and pushing out. The processing of pineapple was completed by using intermittent mechanism and connecting rod mechanism.

A closed-loop control system for heavy-duty industrial robots based on indoor infrared positioning technology was proposed to solve the problem of low positioning accuracy and unsatisfactory machining accuracy caused by insufficient stiffness of some heavy-duty industrial robots. The system consists of five parts: infrared emission diode, infrared irradiancy sensors, signal transmission and reception processing device, positioning service device, and heavy-duty robot. The positioning principle and method of the system were analyzed. The infrared emission diode is the most critical electronic component of the system. Due to the inability of ordinary infrared emission diodes to emit infrared rays with circumferential uniform intensity, luminous part of ordinary infrared emission diodes and packaging structure were redesigned to obtain an infrared emission diode which can emit infrared rays with circumferential uniform intensity. The simulation analysis of the light irradiancy intensity of the redesigned infrared emission diode proves that the structure can meet the design requirements. The proposed closed-loop control system for heavy-duty industrial robots can to some extent overcome the problems caused by insufficient stiffness without changing the existing robot structure, maintain the machining accuracy of the robot within an acceptable range, and provide a solution for the implementation of the next heavy-duty industrial robot system.

The system parameter-matching accuracy directly affects the vehicle's comprehensive performance. Achieving the optimal comprehensive performance of the vehicle is a complex problem to be solved in the development of current new energy power systems. This paper proposes a practical parameter-matching method for vehicle power systems based on fuzzy evaluation. The interval ranges of related design variables are calculated. The simulation model of the new energy vehicle is built to obtain dynamic performance and energy economy. The multi-dimensional evaluation indexes and thresholds of dynamic performance and energy economy are determined. The comprehensive performance evaluation method based on compound weight and fuzzy mathematics is adopted to quantitatively evaluate the vehicle's comprehensive performance. Following this, the optimal parameter matching of new-energy vehicle power systems is realized. The transmission ratio matching of the distributed electric drive system is performed following the proposed method, and the practicability and accuracy of the parameter-matching method are verified.

To improve the service reliability and fatigue life of truck-mounted cranes, this paper conducted dynamic analysis and fatigue life evaluation of the crane. The multi-body dynamics model of the crane was established, and the dynamic characteristics of the crane were analyzed. The load-time history of the crane is obtained. Based on the load time history of the crane, the finite element model of the crane is built, and the dynamic stress and maximum stress location of the crane are obtained. Following this, the fatigue life of the crane structure under sequential working conditions was analyzed using the nominal stress method and the load spectrum. The results could support the reliability improvement of the crane's service reliability.

The flying car combines the functions of the aircraft and the car, and its aerodynamic shape satisfies the aerodynamic characteristics of the car and the aircraft. The Catia three-dimensional modeling software is used to draw a ducted flying car shape, and the step-back, fast-back, and square-back type tailback models are established. The CFD software Xflow is used to perform grid-independent experiments on the model to determine the optimal simulation accuracy of the vehicle model. The aerodynamic analysis of the three tailback models is carried out by using the obtained optimal simulation accuracy. Through the analysis and comparison of the aerodynamic characteristics of the three tailback shapes, it is concluded that the aerodynamic parameters of the fast-back tailback are the best for improving aerodynamic performance. By comparing the inclination angle of the fast-back tailback, it is found that when the inclination angle is 30, the aerodynamic parameters improve the aerodynamic performance.

This study focuses on a certain vehicle model and analyzes the noise problem in the edge area of the front cover of the car through wind tunnel tests and Fluent numerical simulation software. Firstly, numerical calculations and analysis were conducted using fluid dynamics theory, acoustic theory, and other methods. Secondly, wind tunnel validation was conducted to analyze the impact mechanism of aerodynamic flow field on the noise of the front cover of automobiles. By comparing the simulation results of different design schemes, a simplified model was used to solve a type of method and solution for eliminating the edge noise of the front cover. Explored the mechanism of reducing noise at the front edge of the front cover of vehicles with through grille lights, studied the structure and position of the front grille light area, and applied it to eliminate wind noise in vehicle models. The simulation and experimental results show that the protruding diversion structure passing through the tail lights can effectively avoid the generation of wind noise at the front of the front cover, reduce the sound pressure value at the front cover, and reduce the noise to a maximum of 19 dB.

Post-rolling cooling is a critical step in the hot rolling production process, and it has a significant impact on the microstructure and mechanical properties of the final product. This paper first introduces three main modules of research on advanced post-rolling cooling system models. Secondly, it analyzes how to establish high-precision predictive models for post-rolling cooling systems and improve temperature control accuracy. The paper summarizes some strategies and solutions proposed by scholars to address identified issues. By utilizing advanced control theory and deep learning, a post-rolling control and cooling predictive model is developed to effectively mine production big data and provide accurate forecasts for the cooling system. In terms of improving temperature control accuracy, scholars have optimized existing self-learning models, resulting in a dual-model parallel system known as VSG+DNN. This system significantly enhances the stability and robustness of the post-rolling cooling system.

In the grinding process of pendulum mills, blade parameter design significantly influences production efficiency. Blades throw the particles to the grinding area for grinding, also the blades design controls the particle movement trajectory. By using discrete element analysis software Rocky DEM, the grinding process is simulated in this paper. A response surface experiment of blade angle and length was conducted. Through analysis of particle number reaching grinding area, the influence laws of particle kinematics and grinding rate were revealed. With increasing blade angle or length, the throwing height and the number of particles in the grinding area increase. However, particles could not be effectively captured under extremely high blade angle and length, which reduced the grinding rate. The response surface results showed that the interaction of blade length and angle was significant, and the ranges of optimal blade angle and length are determined as 35°–38° and 225–245 mm, respectively. At the optimal blade parameters of 36°-227 mm, the grinding rate is 76.7%, 8% higher than that of the industrial blade parameter (32°-205 mm, 68.7%). This study provides a theoretical basis for the optimization design of the blade parameters of pendulum mills.

The forming process of welds involves various factors such as environment, equipment, process, and materials. Among them, the influence of process parameters is the most obvious. Welding process parameters are the basis for affecting the size of the formed part, and each parameter will interact with each other to affect the geometric size of the weld seam. The welding process parameters play a crucial role in the shape of the molten pool, the formation of the weld seam, and the microstructure and properties, as they determine the strength and quality of the welded parts. The welding process parameters of arc welding robots are welding current or wire feeding speed, welding voltage, welding speed, wire diameter, wire extension length, gas flow rate, etc. This article adopts the experimental testing method of secondary universal rotation assembly to establish a secondary regression model between weld bead size and welding voltage, welding current, and welding speed. This model can effectively predict weld bead size, using a reasonable width to improve the quality, fatigue strength, shear strength, etc. of the weld seam.

The power catwalk is the peripheral equipment used in oil drilling rigs to transport various pipe sections, including drill pipes, drill collars, and pipe sleeves. This equipment is responsible for moving pipe sections from the ground up to the drilling platform during drilling and workover operations, as well as lowering unloaded pipe sections from the platform back down to the ground. During the lifting (descending) process, the wire rope pull-type power catwalk may experience significant fluctuations in its pull force, which may result in unstable occurrences such as chattering and impact at certain positions. Using Lagrange equation, a 4-stage dynamic model was established for the power catwalk, taking into account boundary conditions. This model was used to analyze the movement pattern of the catwalk, determine the root cause of its instability, and apply the corresponding control strategy to improve the instability phenomenon, set the stage for further optimization and performance enhancement.

With the rapid development of China's modern industry, the proportion of large-scale equipment in modern enterprises is also increasing. As a kind of large-scale crushing equipment widely used in industry, the intelligent operation of vertical mill has become a research hotspot of scholars at home and abroad. Because the daily maintenance cannot find the faults of the vertical mill equipment in time, it is very necessary to improve the monitoring and fault diagnosis capabilities of the vertical mill to ensure the normal operation of the equipment and reduce the economic losses caused by the equipment faults of the enterprise. This paper will introduce the research methods and research status of intelligent fault diagnosis technology for vertical mill, and put forward the prospects for the future development.

The shrinkage and porosity are common in low pressure casting aluminum alloy wheel hub. Anycast software was used to simulate the filling and solidification process of large aluminum alloy wheel hub. The results show that the location of defects and the volume of defects were predicted. The results show that the position of air entrainment tend to arise in the outer rim of the wheel hub and the inner side of the wheel core during the filling process. During the solidification process, the highest cooling rate of the hub appears at the outer rim, which is 3.202°C/s. The maximum temperature gradient appears at the outer rim, and its value is 64.165 °C/cm. The research can provide practical guidance for reducing casting waste and improving the quality of wheel hub in the casting production of wheel hub.

Steering wheel shimmy often occurs when the vehicle is driving, which affects both riding comfort and driving safety. This article is to find out the reasons through the tests on wheel positioning, wheel dynamic balance, steering gear, and wheelbase parameter adjustment from the perspective of experimental verification. The results show that the dynamic balance that controls the tire assembly is between 0 and 5g. Actions like accurate calibration on the front wheel positioning parameters, adjustment on the free travel of steering gear and steering system, and wheelbase deviation to be controlled within 10mm, can eliminate the steering wheel shimmy.

To alleviate the loss of potentially valuable and discriminative features as the number of networks increases in deep learning (DL). A weighted multi-source information fusion network-based framework is proposed for mechanical fault diagnosis. Firstly, a feature improved Deep Belief Network (FIDBNs) and a feature improved Convolutional Neural Network (FICNNNs) are designed to repetitively extract valuable information from original data. Meanwhile, an attention mechanism is adopted to further extract important fault characteristics Then, a weighted feature fusion module is used to integrate better for more diagnostic performance. Finally, an experimental dataset based on bearing failures is used to prove the effectiveness and superiority of the proposed framework compared with other methods.

In response to the heat dissipation requirements of space optical remote sensor electronics and other heat sources, the characteristics of the orbital heat flux of the high inclination orbit where the remote sensor is located are analyzed. Combined with the position characteristics of the remote sensor platform and the two-dimensional manoeuvring characteristics, the spatial layout position and required area of the heat dissipation radiator are determined. Utilizing heat pipe network to achieve the realization of the heat dissipation radiator groups, achieving effective heat dissipation of the heat source while the high orbital heat flux on the single position of the radiator. Adopting a non-metallic and graphite film composite heat dissipation radiator form, further improving the temperature uniformity of the heat dissipation radiator and effectively enhancing the heat dissipation of the remote sensor. Through this technology, the heat dissipation problem of complex orbit heat flux remote sensors can be solved.

Integrated thermal management system (ITMS) is the most important technology for new energy vehicles, which can significantly impact on thermal performance including driving range, battery safety and passenger comfort. In this paper, an ITMS is designed and constructed based on the principle of thermal load of cabin and heat generation of battery. The simulation model of ITMS is established and with the calibration of components. The influence of ambient temperature on thermal performance of ITMS is investigated. The results show that the cab temperature and battery temperature remain constant and fluctuates within a range of 22~27°C and 24~26°C, respectively. The results demonstrate that the thermal performance of ITMS satisfies well with the heat dissipation requirements under ambient temperature range of 25~40°C. Additionally, the results find that the compressor rational speed varies with cabin and battery temperature to reduce compressor power. The energy consumption of ITMS increases from 3.43 kWh to 15.35 kWh with increasing ambient temperature from 25°C to 40°C.

Oscillating heat pipe (OHP), as a heat transfer element, has a broad application prospect in the conversion and utilization of waste heat generated by mechanical equipment and thermal management of chip in intelligent manufacturing system. How to improve the heat capability of the OHP to enhance its applicability has always been a research hotspot. Liquid metal is used to improve the heat capability of the OHP in this paper. The evaporator, adiabatic and condenser lengths of the OHP are 40 mm, 51 mm and 64 mm, respectively. The effects of liquid metal volume fraction, heating power and angle on the start-up and heat capability of the OHP were studied experimentally. The results show that adding liquid metal will increase the start-up temperature and start-up time. When the heating power is greater than 100W, liquid metal can enhance the heat capability of the OHP, and the thermal resistance first decreases and then increases with the increase of the volume fraction of liquid metal. When the OHP is placed vertically and the heating power is 350W, compared with the pure ammonia OHP, the heat capability of the OHP with liquid metal volume fraction of 2.43% is enhanced by 10.45%.

As a two-phase heat transfer element, the oscillating heat pipe (OHP) holds significant promise for applications in heat management and thermal energy utilization within the medium-temperature range. To investigate the heat transfer properties of medium-temperature OHPs, a stainless steel OHP that uses an azeotropic mixture of kerosene as the working fluid was developed. The impact of tilt angle and operating temperature on the heat transfer performances of the kerosene OHP under different heating power conditions were studied. Results revealed that: (1) The kerosene OHP exhibits the highest heat transfer performance when oriented vertically. As the tilt angle decreases, the heat transfer capacity decreases significantly, and the kerosene OHP cannot be started when placed horizontally. (2) As the operating temperature increases, the working fluid within the OHP transitions from oscillating flow to a stable one-way flow, resulting in a significant enhancement of the heat transfer capacity of the kerosene OHP. (3) When the OHP is oriented vertically with an operating temperature of 80 °C, the minimum thermal resistance is 0.30 °C/W and the maximum equivalent thermal conductivity is 4046.7 W/(m·K).

Due to the lack of analysis on the correlation between the action stages of the overall circuit breaker spring operating mechanism, there is a significant error in the analysis of spring strength and fatigue state. Therefore, a study on the strength and fatigue model of circuit breaker energy storage springs based on SVM algorithm is proposed. Based on the composition of the circuit breaker spring operating mechanism, the stress state of the energy storage spring during the circuit breaker action process and its relationship with various mechanisms were analyzed. On the basis of adaptive improvement of the SVM algorithm, a strength and fatigue model of the circuit breaker energy storage spring was constructed. In the test results, the design model shows that the error in the stress intensity analysis of the spring mechanism used in road vehicles with different spring pull rod outer diameter settings is stable within 8.0MPa, and the error in the fatigue life factor analysis is always stable within 0.3.

Power semiconductor devices have seen a rise in the development of wide bandgap (WBG) semiconductors. WBG devices can be bonded at low temperatures due to the transient liquid phase (TLP) bonding process. Applying Cu porous in TLP has been the subject of relevant studies. The strength of metallic joints created by various solders with Cu porous, however, has received less attention in earlier investigations. In this study, the shear strength of metallic joints made of SAC and Sn58Bi is examined. Cu porous was used as an intermediate metal layer, and a 0.2 mm layer of Sn58Bi / SAC solder paste was applied to its top and bottom surfaces. Research has also looked into the impact of bonding time. It can be inferred that the metal junctions formed with SAC solder are stronger and better suited for transient liquid bonding.

With the rapid development of automobile technology, how to improve the performance of noise, vibration and harshness (NVH) has always been the focus of automotive research and development. In this paper, the installation point of a car air conditioning is used as the excitation source, and the right ear of the driver and rear passenger is used as the response point for NVH researching. The acoustic-solid coupling finite element model of the vehicle is established by using the 3D body model of the vehicle and the finite element model equipped with the passenger compartment. Through the noise transfer function analysis, combined with the modal analysis of the prepared body and the analysis of working deformation, the body components with relatively large contribution to noise transfer are identified and optimized. The optimization results show that the sound pressure value at the driver is reduced by 12.7dB, and the peak sound pressure at the rear passenger is also significantly decreased. Thus, the NVH performance is improved. The analysis method and optimization scheme adopted in this paper are simple and feasible, which has certain reference value for the personnel and manufacturers engaged in automobile design.

In this paper, the flow patterns of flat-plate oscillating heat pipe (FPOHP) at different operation stages were analyzed by infrared thermal imaging. The FPOHP with a working fluid of HFE-347 and a heating power of 20W to 140W was placed vertically. A high speed camera is used to record the flow direction and state of the working fluid in the FPOHP, and the temperature distribution of the FPOHP at different operation stages is recorded by infrared thermal imager. The experimental results show that the flow pattern of the FPOHP can be divided into non-oscillation stage, transition stage and stable operation stage according to the different flow state of working fluid. The temperature distribution presented by infrared thermal image is synchronous with the wall temperature fluctuation of FPOHP and the change of the working fluid flow direction. The flow pattern of the working fluid and the heat transfer performance of FPOHP can be qualitatively judged by infrared thermal imaging.

In order to reduce the vibration of gear transmission system, A new type of gear damping method: flexible damping gear was proposed in this study. a simplified flexible damping gear vibration isolation model was established, and a one-stage open spur gear vibration damping experimental bench was constructed. Based on the test bench, the following tests were carried out:1) flexible damping gear damping experiments; 2) flexible damping gear damping experiments under different torque; 3) flexible damping gear noise reduction experiments. The experimental results shown that the flexible damping gear can effectively reduce the vibration of the gear transmission system in a wide frequency band, and the highest vibration reduction can be achieved; with the increase of torque, the vibration suppression ability of flexible damping gear is also enhanced, and the average vibration reduction reaches 26.70%.

In this study, the performance of the straight-drawn elevator under various working conditions was analyzed by simulation software in the complex environment in the reactor vessel to optimize the design and determine the reasonable operating parameters. Firstly, the multibody dynamics simulation of rigid-flex coupling is carried out during the operation process of the hoist, and the conditions that may affect the operation of the elevators are analyzed, and the influencing factors are analyzed. Secondly, the solid mechanics analysis and modal analysis of the special working conditions that may occur are carried out, and the operating parameters of the elevators are recommended accordingly; Finally, based on the above analysis results, the structure of the elevators is optimized and verified. The research results show that under the material exchange condition, the hanging barrel will have a certain offset and vibration during the expansion and telescopic process of the cantilever of the hoist, and the lifting opportunity will have a certain deformation under special working conditions. By optimizing the structure and limiting the operating conditions, the deformation and vibration can be effectively reduced, and the normal material change of the elevators can be guaranteed.

In this paper the vortex-induced vibration of an underwater robotic arm was simulated using ANSYS-Fluent fluid simulation platform. The effects of water flow direction and the rotational speed of the robotic arm on vortex-excited vibration are discussed. The results indicated that the drag coefficient of the underwater robotic arm in the countercurrent state has a larger range of values and numerical variations compared to the downstream state. The maximum difference in numerical value is 4.84 times. The numerical fluctuation of the lift coefficient of the underwater robotic arm in the downstream state is more significant than that in the upstream state. And when the upstream angle of the underwater robotic arm is 45° there was a significant fluctuation in the lift coefficient. By fitting the change curves of the lift coefficient and drag coefficient, the correlation functions of the lift coefficient and drag coefficient with the displacement of the center of mass were obtained. It also provided a basis for the vortex-excited vibration of the ocean engineering equipment.

Aiming at the life loss and failure of hydrogen storage cylinder caused by repeated charging and discharging of alternating load, based on the fracture mechanics method, the progressive damage model of alternating load was introduced at the interface between fiber layer and liner, and the interface damage was discussed. It was concluded that the interface damage was the most serious, and the main cause of fatigue crack was interface shear.

In order to study the influence of temperature and external load on axle box bearing in high-speed EMUs, on the basis of establishing FAG double row tapered roller bearing pseudo-static analysis model, HyperMesh combined with ANSYS software is applied to establish a reasonable finite element simulation model, and the temperature field and thermal coupling field of double row tapered roller bearing are calculated. The results agree with the theoretical calculation.

For the sake of analyze the dynamic characteristics of the working device of the hydraulic excavator, a three-dimensional model of the working device of a certain type of hydraulic excavator is established, and its four typical working conditions are determined. The finite element model of the working device is established, and the first six natural frequencies and main modal forms of the working device of the hydraulic excavator under four working conditions are calculated, which provides a basis for optimizing the dynamic characteristics of the working device of the hydraulic excavator.

The failure of the operating spring stress in high-voltage circuit breakers, along with fatigue fracture, can result in inadequate opening and closing speeds, exceeding the specified opening and closing times, and the inability to close, seriously affecting the safe and stable operation of equipment and the power grid. In the actual production and maintenance processes, neglecting the operating conditions of the high-voltage circuit breaker spring, such as temperature, loading position, preload, motor vibration, and other factors, leads to poor estimation accuracy of the spring's fatigue state and remaining life. Additionally, the inability to accurately judge the creep and relaxation characteristics of the spring during use results in phenomena such as spring creep deformation and relaxation, leading to problems of missing maintenance opportunities. This paper focuses on studying the influence of external operating conditions, as well as creep and relaxation characteristics, on the properties of the spring. It aims to provide relevant support for the design and operation of springs in subsequent applications.

The dynamic stiffness and impact stiffness of isolators are the core technical indicators for the performance evaluation of isolators. Accurate assessment is necessary to meet the needs of different usage environments. The main methods for testing dynamic stiffness include the ellipse method, vibration excitation method, and self-excited oscillation method. The main techniques for testing impact stiffness are the drop method and the drop hammer method. Choosing the appropriate testing method based on the characteristics of the test piece can greatly improve efficiency. This paper employs the vibration excitation method to conduct dynamic stiffness simulation and experimental analysis on the spring oscillator isolator model, and uses the drop method for impact stiffness simulation and experimental analysis of the same model. Based on a comparison of simulation analysis and experimental analysis, the effectiveness of the tests was clarified. Moreover, the advantages and disadvantages of various testing methods for dynamic and impact stiffness were sorted out based on the relevant experimental data, to serve as a reference for related testing technicians.

In response to the malfunction of "marine diesel engine unable to start", the possible causes of the malfunction were deduced and a fault tree model was established. On this basis, the fault tree model was transformed into a hierarchical analysis model, and the target layer, criterion layer, and solution layer were constructed. Through expert consultation and data collection, a judgment matrix for each layer was constructed, and the effectiveness of the judgment matrix was verified. The impact weights of each base event on the top event were determined, and targeted suggestions were proposed for the management of marine diesel engine systems.

The spiral concentrator is a kind of gravity separation equipment. The structure optimization of mineral processing equipment is the research focus and development direction of today's mineral processing field. In order to improve the sorting efficiency of the spiral concentrator, this paper proposes the optimization method of adding certain structural forms of grooves to the groove surface of the spiral chute. The RNG turbulence model, VOF multiphase flow model, and discrete-phase particle orbital model are used to carry out orthogonal simulation experiments on the sorting process of the spiral chute engraved groove model. The results show that the optimal solution for adding grooves to the spiral chute is 45 grooves, a 30° angle, 5 mm width, and 2 mm depth, which has the most significant sorting effect. In order to verify the feasibility of the optimal scheme, a prototype of the optimal structural scheme was fabricated in this study. Comparison experiments show that the average concentrate grade obtained from the experimental prototype is 2.92% higher, and the average concentrate recovery is 3.08% higher, which verifies the feasibility of the scheme.

In the existing research, the measures to increase the intake air volume of the cabin are usually taken to solve the heat dissipation problem inside the cabin, but these measures will lead to the increase of the internal flow resistance. When evaluating the thermal performance of the engine room, most of the existing studies are based on the specific temperature or ventilation volume of some components, without considering the influence on the whole engine room. When evaluating the flow resistance in the cabin, most of the analysis is based on the flow field cloud image and flow line, but there is a lack of specific quantitative indicators. Taking a passenger car as an example, this paper conducts a systematic study from the aspects of evaluation index establishment, optimization parameter determination, prediction model construction, multi-objective optimization, etc. The purpose is to exchange the best design optimization for a greater improvement in heat dissipation performance. Through experimental comparison, the pressure loss value in the optimal model is reduced by 14.781% compared with the original model, and the temperature efficiency value is increased by 15.163%. The results further verify that the proposed evaluation index can be applied to the multi-objective optimization of engine room heat dissipation performance and inflow resistance, and provide a theoretical basis for the body shape and the general layout of the engine room.

Based on the research background of M701F gas turbine RSS (rotary symmetric tangential support plate) pedestal-bearing rotor system, a dynamic model of the RSS pedestal-bearing rotor system was established, and the global optimal matching theory and algorithm of the dynamic parameters of the pedestal-bearing rotor system were proposed. Then, taking the relevant dynamic parameters of the RSS pedestal-bearing rotor system of M701F gas turbine as reference, the stable, metastable and unstable eccentricity regions of the RSS pedestal-bearing rotor system were defined by considering the best matching relationship between the rotor eccentricity and the stiffness and damping of the pedestal under different bias rates. The stability range of the global matching eccentricity region and the corresponding optimal matching stiffness and damping range are revealed. The theoretical algorithm and evaluation technique are provided for the global optimal matching design of dynamic parameters of pedestal-bearing rotor system in practical engineering.

Lattice transmission towers are typical spatial truss structure, which are commonly composed of equilateral angle steel members using bolts. Different from the bolted joints in beam-column connections of steel frame structures, bolted joints in lattice transmission tower are normally under great axial force and negligible bending moment. Joint slippage will affect the performance of the members under large axial force and even change the behavior of the lattice tower structure system. Therefore, it is very important to establish the joint slippage model for the analysis of lattice transmission towers. Firstly, this study investigates the process of joint slip through a series of tensile tests and analyses the influence of different structural parameters on the slip characteristics of bolted joints. Then, an exponential joint slippage model for the bolted joint of leg member used in steel lattice transmission power is established based on the experimental results. Finally, the finite element model of the transmission tower considering joint slip is established. The influence of different slip models on displacement and axial force of the transmission tower is analyzed.

This paper focuses on the controller in the power transmission auxiliary system of tracked vehicles. Through the process of simplifying the model, initial stiffness calculation, sample set establishment, network training, and parameter identification, a parameter identification model for the power transmission auxiliary system based on the MOGA-LSTM model is established. The analysis results show that the stiffness identification results of the installation structure of the MOGA-LSTM model are reliable. It provides a foundation for further research on the coupling vibration modeling of the dynamic transmission body and the auxiliary system.

Electromagnetic metamaterials applied to wireless power transmission (WPT) systems must be placed between two coils to improve the coupling of the system. This takes up intermediate space and is very inflexible in application. In this paper, a superscatterer based on optical transformation theory can amplify the displacement inside the object to some extent. It only needs to be placed at the transmitter or receiver end of the WPT system to improve the coupling of the system. In this paper, a magnetically coupled resonant wireless power transmission (MCR-WPT) system with the topology of series LC at the transmitter end - series LC at the receiver end (S-S type) is modeled on the COMSOL simulation platform. The modeling simulation verifies that the magnetic field of the transmitting coil is significantly enhanced and the mutual inductance of the two coils is significantly increased by adding the super-scatterer. Thus, the coupling degree of the WPT system is enhanced.

In order to enhance the quality of customized furniture panel processing, avoid information silos between workstations, and promote intelligent manufacturing in customized furniture enterprises, this study constructs a knowledge graph focused on the full lifecycle data of customized furniture panel production. Firstly, the data from the production department of the enterprise is organized and preprocessed, including tokenization, annotation, and other preprocessing techniques, to establish the data layer of the knowledge graph. Secondly, based on real enterprise data, an ontology model is constructed to complete the pattern layer construction of the knowledge graph. Finally, the GPLinker model is utilized for high-precision knowledge extraction of entity relationships. The research results demonstrate that by constructing a knowledge graph focused on the full lifecycle data of customized furniture panel production, interconnectivity and interoperability of data throughout the entire lifecycle of a customized furniture enterprise can be achieved, providing a scientific basis for decision-making in addressing processing anomalies.

After-rolling cooling is a crucial technology for regulating the structure and properties of hot-rolled products, providing vital support for the production and quality improvement of hot-rolled strip products. The after-rolling cooling control system is a core factor limiting the development of after-rolling cooling technology. Therefore, conducting research on the after-rolling cooling control system is of significant importance. This paper first analyzes the basic principles of after-rolling cooling and summarizes the current state of research and applications for after-rolling cooling systems. It provides a comprehensive analysis and summarizes the research status and development trends of the after-rolling cooling control system from two aspects: control strategies and heat transfer mathematical models. Temperature control, as a key component of the after-rolling cooling control system, is essential. Precise control of cooling water pressure, flow rate, and the impact of strip speed fluctuations during the cooling process is an effective control strategy to improve the high-precision temperature control of the after-rolling cooling system. A comprehensive analysis of the application of traditional heat transfer models in strip steel heat transfer processes is presented. A comparative analysis of traditional temperature control models and temperature control models with the addition of intelligent algorithms indicates that conventional afterr-olling cooling control models can no longer meet the requirements of new after-rolling cooling systems under complex conditions. Therefore, it is necessary to develop more practical and intelligent adaptive control models that align with the characteristics of the new after-rolling cooling systems.

Nanshui Reservoir plays a key role in energy production and sustainable development. However, traditional operation and maintenance methods often face the problems of untimely information and low efficiency of data processing. To solve this problem, an automatic inspection method of reservoir area based on edge intelligence and unmanned aerial vehicle was proposed. Firstly, the edge calculation box and flight control system were designed. Then the automatic route planning algorithm and camera linkage control algorithm were studied. Finally, the experimental verification was carried out in Nanshui Reservoir. The results show that this method can improve the operation and maintenance efficiency of the reservoir area.