Wearable sensors for continuous monitoring of vital signs for extended periods of weeks or months are expected to revolutionize healthcare services in the home and workplace as well as in hospitals and nursing homes. This invited paper describes recent research progress in wearable health monitoring technology and its clinical applications, with emphasis on blood pressure and circulatory monitoring. First, a finger ring-type wearable blood pressure sensor based on photo plethysmogram is presented. Technical issues, including motion artifact reduction, power saving, and wearability enhancement, will be addressed. Second, sensor fusion and sensor networking for integrating multiple sensors with diverse modalities will be discussed for comprehensive monitoring and diagnosis of health status. Unlike traditional snap-shot measurements, continuous monitoring with wearable sensors opens up the possibility to treat the physiological system as a dynamical process. This allows us to apply powerful system dynamics and control methodologies, such as adaptive filtering, single- and multi-channel system identification, active noise cancellation, and adaptive control, to the monitoring and treatment of highly complex physiological systems. A few clinical trials illustrate the potentials of the wearable sensor technology for future heath care services.

A flexibility-based distributed computing strategy (DCS) for structural health monitoring (SHM) has recently been proposed which is suitable for implementation on a network of densely distributed smart sensors. In that approach, a hierarchical strategy is proposed in which adjacent smart sensors are grouped together to form sensor communities. Structural health monitoring is done without relying on central data acquisition and processing. The main purpose of this paper is to experimentally verify this flexibility-based DCS approach. The damage locating vector method that forms foundation of the DCS approach is reviewed. An overview of the DCS approach is presented. This flexibility-based approach is then experimentally verified employing a 5.6 m long three-dimensional truss structure. To simulate damage in the structure, the original truss members are replaced by ones with a reduced cross section. Both single and multiple damage scenarios are studied. Experimental results show that the DCS approach can successfully detect the damage at local elements using only locally measured information.

In a collaborative project at Lehigh and Carnegie Mellon, a MEMS acoustic emission sensor was designed and fabricated as a suite of six resonant-type capacitive transducers in the frequency range between 100 and 500 kHz. Characterization studies showed good comparisons between predicted and experimental electro-mechanical behavior. Acoustic emission events, simulated experimentally in steel ball impact and in pencil lead break tests, were detected and source localization was demonstrated. In this paper we describe the application of the MEMS device in structural testing, both in laboratory and in field applications. We discuss our findings regarding housing and mounting (acoustic coupling) of the MEMS device with its supporting electronics, and we then report the results of structural testing. In all tests, the MEMS transducers were used in parallel with commercial acoustic emission sensors, which thereby serve as a benchmark and permit a direct observation of MEMS device functionality. All tests involved steel structures, with particular interest in propagation of existing cracks or flaws. A series of four laboratory tests were performed on beam specimens fabricated from two segments (Grade 50 steel) with a full penetration weld (E70T-4 electrode material) at midspan. That weld region was notched, an initial fatigue crack was induced, and the specimens were then instrumented with one commercial transducer and with one MEMS device; data was recorded from five individual transducers on the MEMS device. Under a four-point bending test, the beam displayed both inelastic behavior and crack propagation, including load drops associated with crack instability. The MEMS transducers detected all instability events as well as many or most of the acoustic emissions occurring during plasticity and stable crack growth. The MEMS transducers were less sensitive than the commercial transducer, and did not detect as many events, but the normalized cumulative burst count obtained from the MEMS transducers paralleled the count obtained from the commercial transducer. Waveform analysis of signals from the MEMS transducers provided additional information concerning arrivals of P-waves and S-waves. Similarly, the analysis provided additional confirmation that the acoustic emissions emanated from the damage zone near the crack tip, and were not spurious signals or artifacts. Subsequent tests were conducted in a field application where the MEMS transducers were redundant to a group of commercial transducers. The application example is a connection plate in truss bridge construction under passage of heavy traffic loads. The MEMS transducers were found to be functional, but were less sensitive in their present form than existing commercial transducers. We conclude that the transducers are usable in their current configuration and we outline applications for which they are presently suited, and then we discuss alternate MEMS structures that would provide greater sensitivity.

Presented in this paper is the environmental testing of Wireless Intelligent Sensor and Actuator Network (WISAN) currently under development at Clarkson University for the use of long-term structural health monitoring of civil infrastructure. The wireless sensor nodes will undergo controlled mechanical vibration and environmental testing in the laboratory. A temperature chamber will be used to perform temperature cycle tests on the sensor nodes. The temperature chamber will also houses a small shaker capable of introducing mechanical loading under the controlled temperature cycle tests. At low temperatures, the resistance of the electronics processing and storage characteristics will be studied. Also, the testing will look at volume expansion and degradation of characteristics due to freezing, degradation of functions and performance, and mechanical characteristics caused by contraction. At high temperatures, temperature-related changes in sensor nodes due to excessively high temperatures will be investigated. Also studied will be the effects of temperature cycles, including the thermal stresses induced in the nodes and housing and the distortion caused due to expansion and contraction, fatigue, cracks, and changes in electrical characteristics due to mechanical displacement. And finally, mechanical vibration loading will be introduced to the WISAN sensor nodes. Mechanical looseness, fatigue destruction, wire disconnection, damage due to harmonic vibration, defective socket contact, joint wear, destruction due to harmonics, lead breakage, occurrence of noise and abnormal vibration, cracking will be monitored. The eventual goal of the tests is to verify WISAN's performance under anticipated field conditions in which the sensors will be deployed.

Since the recognition of the advantages of using Lamb Waves in nondestructive testing (NDT), Lamb Waves and other guided waves have attracted more and more attention nowadays. Unlike waves used in conventional ultrasonic inspection, such as bulk longitudinal and shear waves, which propagate in the region of structure immediately around the transmitting transducer, Lamb Waves can propagate over a long distance. Previously in our work, monolithic interdigitated PVDF transducers for generating surface acoustic waves have been built by using photolithography technology. These sensors have been tested to be able to successfully excite and receive Lamb Waves. As an extension of previous work, this paper focuses on the implementation of interdigitated PVDF sensors on some laminated structures made of carbon fiber composite materials with flaws of different sizes. Experiments have been conducted, and results from PVDF IDTs have been compared with those from PZTs. Efforts have been spent on identifying the components of Lamb waves propagated in these sample structures and evaluating the differences in the received signals.

We examine exploiting the inherent piezoresistivity of a polysilicon compliant mechanism to provide feedback sensing of the mechanism displacement. As the piezoresistive compliant mechanism deflects to produce motion its resistance changes producing a usable signal. The goal of this work is to improve the transient response of a thermal actuator through piezoresistive feedback control. Implementing feedback control significantly improves the actuators transient response. The actuator response time to step inputs is reduced from 800μs to 230μs with proportional control alone. The system bandwidth was increased from 500~Hz to 4~kHz with proportional control. The large overshoot in the step response or the resonant peak in the frequency response can be reduce by an appropriately tuned 2~kHz notch prefilter.

This paper presents the modeling and design optimization of a micromachined floating element piezoresistive shear stress sensor for the time-resolved, direct measurement of fluctuating wall shear stress in a turbulent flow. The sensor structure integrates side-implanted diffused resistors into the silicon tethers for piezoresistive detection. A theoretical nonlinear mechanical model is combined with a piezoresistive model to determine the electromechanical sensitivity. Lumped element modeling (LEM) is used to estimate the resonant frequency. Finite element modeling is employed to verify the mechanical models and LEM results. Two dominant noise sources, 1/f noise and thermal noise, were considered to determine the noise floor. These models were then leveraged to obtain optimal sensor designs for several sets of specifications. The cost function is the minimum detectable shear stress that is formulated in terms of sensitivity and noise floor. This cost function is subjected to the constraints of geometry, linearity, bandwidth, power and resistance. The results indicate the possibility of designs possessing dynamic ranges of greater than 85dB.

Structural health monitoring (SHM) is important for reducing maintenance costs while increasing safety and reliability. Piezoelectric wafer active sensors (PWAS) used in SHM applications are able to detect structural damage using Lamb waves. PWAS are small, lightweight, unobtrusive, and inexpensive. PWAS achieve direct transduction between electric and elastic wave energies. PWAS are essential elements in the Lamb-wave SHM with pitch-catch, pulse-echo, phased array system and electromechanical impedance methods. This paper starts with the state of the art on the impedance method for PWAS applications. Then, finite element impedance model for free and bonded PWAS with different sizes and shapes will be given. Experiments showed that the real part and imaginary part of PWAS had different usage. Applications of impedance-based structural health monitoring indicate impedance method as a good candidate for damage detection and sensor durability verification for SHM smart sensor.

This project investigates the magnetomechanical sensing behavior of iron-gallium alloys in response to applied bending loads in order to provide an experimental and analytic framework for implementing this material in novel sensor applications at the nanoscale. A series of experiments are conducted on millimeter sized cantilevered beams to verify that the material is mechanically sound as well as magnetically active in this loading configuration, with results showing a change in magnetic induction of as much as 0.3 T occurring at twice the frequency of beam vibration. These results agree well with an analytic system model based on nonlinear free energy terms. Initial work has begun on visualizing and characterizing arrays of iron-gallium nanowires, with an atomic force microscope providing preliminary images as well as force and deflection data.

One of the major problems in sensor fusion is that sensors frequently provide spurious observations which are difficult to predict and model. The spurious data from sensors must be identified and eliminated from the sensor fusion since its incorporation in the fusion pool might lead to inaccurate estimation. This paper presents a sensor fusion strategy based on Bayesian approach that can automatically identify the inconsistency in sensor data so that the spurious sensor data can be eliminated from the sensor fusion process. The proposed method adds a term to the commonly used Bayesian technique that represents the probabilistic estimate corresponding to the event that the data is not spurious conditioned upon the data and the true state. This term has the effect of increasing the variance of the posterior distribution when data from one of the sensors is inconsistent with respect to the other. The proposed strategy was verified with the help of extensive computations performed on simulated data from three sensors. A comparison was made between two different fusion schemes: centralized fusion in which data from all sensors were fused at once, and decentralized or sequential Bayesian method which provided opportunity to identify and eliminate spurious data from the fusion process. The simulations verified that the proposed strategy was able to identify spurious data, and its elimination from the fusion process led to better estimation.

We present UV-induced intrinsic Fabry-Perot interferometric (IFPI) fiber sensors and a frequency-division-multiplexing (FDM) scheme for quasi-distributed temperature and strain sensing. We present a spectrum-based measurement system with a swept laser source to measure the fringe patterns of IFPI sensors serially arranged along a single fiber. The FDM scheme is based on the multiplexing of sub-carrier frequencies generated by the frequency-modulation of a continuouswave light source. IFPI sensors with different optical path differences (OPD) will have different sub-carrier frequencies. We use band pass filters to select individual frequency component and use frequency-estimation based signal processing algorithms to determine the OPD of each sensor. Experimental results for multiplexed temperature and strain sensing are demonstrated. The performance of the multiplexing system is discussed.

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

The capability and sensitivity of an electromagnetic (EM) sensor to be used as a non destructive evaluation (NDE) technique to detect and monitor corrosion in structural steels has been evaluated. Three structural carbon steels: AISI 1018, AISI 1045, and Stress Proof, were used for the study. The effect of corrosion on the magnetic properties of the steels was evaluated. Correlation curves and equations relating mass loss due to corrosion at early stages and magnetic property are presented. Based on the results it is established that the EM sensor has the potential to be used as a reliable NDE tool to detect corrosion at early stages based on the variation in magnetic saturation. These results are used to estimate and monitor the degree of damage in terms of mass loss.

A frequency sweep from 50 to 200 kHz of guided mechanical waves have been conducted to detect and assess corrosion damage in steel reinforced mortar specimens with seeded defects and in specimens undergoing accelerated corrosion using impressed current. The sweep was conducted by invoking primarily the fundamental longitudinal mode of propagation, i.e., the L(0,1) mode. The decay of waveform energy (indicative of attenuation) at different frequencies is presented and discussed in terms of corrosion damage. Experimental results indicate that the percentage of corrosion damage can be detected and evaluated invoking the fundamental longitudinal mode of propagation.

A guided wave approach to characterize the evolution of fresh mortar during the first twenty-four hours of hydration is presented. Using a through-transmission system, the method measures the energy leakage of the first torsional wave mode from a circular steel bar to the surrounding mortar. The evolution of mortar properties are discussed and correlated with the attenuation of the guided wave. The study shows that the technique is useful for monitoring the microstructure development and the curing rate of varying water-cement ratios (w/c = 0.40, 0.50, and 0.60). The effects of chemical (accelerant and retardant) and mineral (silica fume and fly ash) admixtures on the guided wave energy leakage are also presented and discussed. The guided wave approach is sensitive to changes in the water-cement ratio and to the addition of admixtures. Mortar compressive strength measurements at 12, 18, and 24 hours of hydration for the different mortar mixtures are presented. A correlation relating the energy leakage of the guided wave the strength development of the mortar is discussed.

At first, two kinds of miniature LRB models are prepared, one model has normal lead damper, the other has abnormal one. And they are scanned by ultrasonic wave using ultrasonic transducers and AE sensors. The output signals obtained through the inside are different from each other. Infinite route is assumed as ultrasonic wave propagation line. But, in this examination, we found that the main route is some layers of steel. Then, the tomography construction is adopted to detect the condition of lead plug in one layer of steel plate. The full acoustic wave solution in an arbitrary two-dimensional object is computed, which is subjected to specified acoustic sources and material parameters. This algorithm is basically a finite difference method. As a result, it is successful to know about ultrasonic wave propagation in one layer of steel and consistent correlation with the output signal. The feature vectors are created by calculation of second power average of the amplitude, and these vectors are used as the data for pattern recognition on the basis of these information. The accuracy of pattern recognition is significantly enhanced in consistent correlation with the condition of lead plug. In this study, active damage detection method to evaluate the status of LRB was proposed. It is possible to evaluate internal states of LRB by using ultrasonic wave.

Many researches have been reported on the condition monitoring of civil infrastructures by means of piezoelectric sensors. Most of them made use of the impedance change of the piezoelectric device in relation to the creation of internal damages to the structure. The impedance measurement is a well accepted method in the piezoelectric sensor area, and has been proved by many authors to be useful for civil structure diagnosis. However, the impedance measurement normally requires sophisticated equipment and analysis technology. For more general and wide application of the piezoelectric diagnosis tool, a new methodology is desired to overcome the limitations of the impedance measurement. This paper presents the feasibility of a piezoelectric oscillator sensor to detect the damages in civil infrastructures. The oscillator sensor is composed of an electronic feedback oscillator circuit and a piezoelectric thickness mode vibrator to be attached to the structure of interest. Damage to the structure causes a change in the impedance spectrum of the structure, which results in a corresponding change of the resonant frequency of the structure. The oscillator sensors can instantly detect the frequency change in a very simple manner. Feasibility of the piezoelectric oscillator sensor was verified in this work with a sample aluminum plate where artificial cracks of different depth were imposed in sequence. Validity of the measurement was confirmed through comparison of the experimental data with the results of finite element analyses of the plate with cracks. Performance of the oscillator sensor was also compared with that of its conventional counterpart, i.e. impedance measurement, to manifest the superiority of the oscillator sensor.

A modified one-sided measurement technique is proposed for Rayleigh wave (R-wave) velocity measurement in concrete. The scattering from heterogeneity may affect the waveforms of R-waves in concrete, which may make the R-waves dispersive. Conventional one-sided techniques do not consider the scattering dispersion of R-waves in concrete. In this study, the maximum energy arrival concept is adopted to determine the wave velocity by employing its continuous wavelet transform. Experimental study was performed to show the effectiveness of the proposed method. The present method is applied to monitor the strength development of early-age concrete. A series of experiments were performed on early-age concrete specimens with various curing conditions. Results reveal that the proposed method can be effectively used to measure the R-wave velocity in concrete structures and to monitor the strength development of early-age concrete.

This paper experiments on each of two control algorithms which are adapted into a unified control algorithm, in order to decide which is better for semi-active control of civil structures using a squeeze mode smart damper. These algorithms are Lyapunov algorithm and a clipped optimal algorithm, both of which are superior in efficiency and reliability to any existing semi-active control algorithms. Such adaptation makes it easier to develop a control algorithm because it accommodates both continuous and discrete time signals at the same time, and to analyze the control characteristics in the case of broadly distributed natural frequency by securing enlarged stable regions. In order to prove its validity, we performed vibration control tests using a prototype steel plate girder bridge. Since the model is a reduced one, we also scaled EI Centro earthquake wave to the same scale as the reduced model bridge. Various performance indexes have been used to see which algorithm is most effective in control. Also, other experiments were performed to define the control characteristics which would enable us to see how all control conditions--displacement control, force control, and acceleration control--work with each control algorithm. Those experiments showed that each control algorithm works differently according to each different control condition. It is found that Lyapunov algorithm of the two is more effective for semi-active control in the unified control system. Therefore, it is necessary to design a control system according to structural conditions and circumstances.

Since the concept of structural control was proposed by J.P.T. Yao, tremendous progress has been made over the last three decades toward making active structural control a viable technology for enhancing structural functionality and safety against natural hazards such as strong earthquakes and high winds. However, because of the high dimensionality and multiple-input-multi-output nature of civil structure model, it is difficult to design a control strategy to achieve desired stability, robustness with centralized control method. Hierarchical decentralized control strategy is employed in this paper in response to this difficulty. In this approach, the structure to be controlled is divided into a set of substructures. A hierarchical decentralized control consists of two levels: the low-level subsystem by which each substructure is controlled independently by local controllers and local information, and the high-level system that we call it global control system, which takes the outputs of every substructure as its input, and eliminates interconnection among substructures. With LQR active control algorithm in Matlab environment, the centralized control and hierarchical decentralized control strategy are implemented on a 20-storey shear building under dynamic excitation. The simulated results show that both the centralized control and hierarchical decentralized control are able to control the vibration of building. Compared with centralized control, hierarchical decentralized control method has a good control effect with preferably suppressed vibration response and less control force. The study in this paper presents a promising technology for structural vibration control.

This paper investigates the feasibility and efficacy of an MR damper-based control system introducing an electromagnetic induction (EMI) part, for suppressing vibration of building structures subjected to seismic loadings. In the proposed control system, the EMI part composed of a permanent magnet and a coil converts the kinetic energy of the relative motion between a building and a damper into the electric energy, which is used for a change in damping characteristics of the MR damper. Since the EMI part can be used as a controller, which determines the command voltage input according to structural responses, as well as a power source, the proposed control system can be much more compact, convenient, and economic than a conventional active/semiactive system that needs a power supply, a controller and sensors. To verify the feasibility and efficacy of the proposed control system, a shaking table test of a small-scale building model employing the MR damper with the EMI part is conducted. The performance of the proposed control system is compared with that of conventional semiactive control systems using an MR damper.

An optimal placement of MR dampers using genetic algorithm (GA) is put forward in this paper in order to reduce the vibration responses of high-rise building under wind load. The shear dynamic model and equation of motion of the structural system are set up and some parameters of the system are determined based on the model considering the torsion effects of the building. Moreover, an optimal installation model for MR dampers based on genetic algorithm is set up. To simulate the vibration procedures under wind load, a 12-story reinforced concrete eccentric frame structure is used as an example to show the optimal steps and response control effect. The results of the simulation show that genetic algorithm can be used effectively and economically in the optimal installation design of MR dampers in high-rise eccentric buildings to decrease the structural vibration responses induced by wind load.

This paper presents a smart passive damping system (SPDS) for reducing stay cable vibrations. Stay cables, such as used in cable-stayed bridges, are prone to vibration due to their low inherent damping characteristics. Recently some studies have shown that semiactive control systems using Magnetorheological(MR) dampers can potentially achieve higher performance levels and adaptability with few of the detractions as compared their passive counterparts. However, most semi-active and active control systems that use MR dampers require additional power supplies, controllers, and sensors, adding complexity into the system. The complexity may not be desirable to effectively control many large civil structures. This paper proposes a novel SPDS with MR dampers. The smart passive device includes an electromagnetic induction (EMI) system to power the MR damper and adjust itself to external loadings. Thus, SPDS dose not require any control system. The numerical study considered 12.56m stay cable to evaluate the dynamic performance of the SPDS for mitigating the vibration of stay cables. Moreover, the performances of the smart passive damping system are compared with those of an equivalent linear viscous damper and an MR damper operated in a pssive-mode. Results showed SPDS has competitive performance with others despite of its simplicity.

An experimental study on vibration control of one stay cable using a magnetorheological fluid (MR) damper is described in the paper. A 14m-long stay cable model, which is a 1:16 scale model of a 220m-long prototype stay cable in the actual structure, is established for the experimental investigation.The planar sinusoidal excitations with the resonant frequencies are generated by the exciter installed perpendicular to the stay cable model at a point near the low anchorage. The modal testing on the unimpeded stay cable is first performed to identify the actual modal properties and the dynamic performances. Then a series of vibration control tests are conducted on the stay cable incorporated with a small-size MR damper near the low anchorage under the sinusoidal excitations with the first two modal resonant frequencies. The control efficacies and the dynamic performances of the combined cable/MR damper system corresponding to the different current inputs to the MR damper and the semi-active MR damper are investigated comparatively. The experimental results of the vibration control of the stay cable model indicate that the semi-active MR damper can achieve much better control efficacy than the passive MR dampers supplied with constant currents, and the reason can be attributed to the pseudo-negative stiffness generated by the semi-active MR damper.

The electromechanical (E/M) impedance method is a powerful technique in active structural health monitoring (SHM). E/M impedance method utilizes as its main apparatus an impedance analyzer that reads the in-situ E/M impedance of piezoelectric wafer active sensors (PWAS) attached to the monitored structure. Present-day impedance analyzer equipments (e.g.HP4194) are bulky, heavy and expensive laboratory equipment that cannot be carried into the field for on-site structural health monitoring. This paper presented the development of a compact and low-cost impedance analyzer system. First, two types of impedance measurement approaches were evaluated in a PC-based simplified impedance analyzer system. It was found that the first approach, which measures impedance frequency by frequency, is very accurate but is not time-efficient and needs more efforts to be implemented. As for the second approach, which measures impedance using broad-band excitation and transfer function method, provides a good compromise among the measurement time-efficient, accuracy and implementation efforts. Experimental results show that this approach can be used for E/M impedance method for structural health monitoring. Second, to eliminate the PC in the measurement system, a DSP-based impedance analyzer system is proposed for further miniaturization. The system hardware configuration and design, software state flow for impedance measurement, and preliminary testing were presented in details.

For some time, the smart materials and structures community has focused on transducer effects, and the closest advance into actually having the "structure" show signs of intelligence is implementing adaptive control into a smart structure. Here we examine taking this a step further by attempting to combine embedded computing into a smart structure system. The system of focus is based on integrated structural health monitoring of a panel which consists of a completely wireless, active sensing systems with embedded electronics. We propose and discuss an integrated autonomous sensor "patch" that contains the following key elements: power harvesting from ambient vibration and temperature gradients, a battery charging circuit, local computing and memory, active sensors, and wireless transmission. These elements should be autonomous, self contained, and unobtrusive compared to the system being monitored. Each of these elements is discussed as a part of an integrated system to be used in structural health monitoring applications.

We show that with a low number of sensors one can estimate, in real time, the full state of distributed parameter systems like the velocity fields of magnetohydrodynamic flows (liquid metals or plasmas in fusion) or the displacement distribution in cantilever beams (as employed in atomic force microscopy). It suffices to place the sensors at the boundary of the domain of the distributed parameter system-for example, electrodes placed at the wall of an MHD flow, or a laser sensor of the beam tip displacement. The estimation of the infinite-dimensional state of the system is performed using observers designed with the method of "backstepping" which guarantees their exponential convergence to the unsteady motion of the true system. The observer design is performed without any spatial discretization-directly on the non-reduced partial differential equation models. The observer gains do not require the solution of any high-dimensional nonlinear equations, like Riccati equations used in Kalman filters. Instead, the observer gains require the solution of a linear hyperbolic PDE, which is readily solvable both numerically and symbolically. We present simulation results that illustrate the use of our observers.

Monitoring the shape of morphing is essential for their effective and safe operation. However, current sensing systems such as fiber optic sensors are expensive, rigid, and unsuitable for monitoring large shape changes without being susceptible to failure or performance degradation. Therefore, a new class of sensors that does not suffer from these serious limitations is presented. The proposed sensor system relies in its operation on a specially configured distributed network of wires that are embedded in the composite fabric of these structures. The output of the sensor network is wirelessly transmitted to a control processor to compute the linear and angular deflections, the shape, and maps of the strain distribution and power flow over the entire surface of the morphing. The deflection and shape information are vital to ascertain that the structure is properly deployed and that its surfaces are operating wrinkle-free. The strain map ensures that the structure is not loaded excessively to adversely affect its service life. While the power flow map provides a metric that uniquely identifies the structural health in a manner that mimics biological systems which tend to redistribute the load and redirect its path away from the injured sites. The equations governing the operation of the sensor network are developed for a beam-like morphing structure using the non-linear theory of finite elements. The resulting equations will provide the sensor with its unique interpolation capabilities that make it possible to map the linear and angular deflection and strain fields as well as the power flow distribution over the entire surface of the morphing structure. The theoretical and experimental characteristics of the sensor network are determined under static and dynamic loading conditions. The results obtained are used to demonstrate the merits and potential of this new class of sensors as a viable means for monitoring the static and dynamic deflections of 1-D morphing structures. Integration of the proposed sensor network with the supporting electronics and with arrays of flexible actuators will enable the development of a self-contained, actively controlled, and autonomously operating new generation of morphing.

This paper presents a new class of piezoelectric based energy harvesting power sources for use in gun-fired munitions or other similar applications requiring high G survivability . These power sources are designed to harvest energy from the firing acceleration as well as vibratory motion and spinning of munitions during their flight and convert it to electrical energy that could be used directly by power consuming electronics onboard munitions or stored. The power sources are designed to withstand firing accelerations in excess of 100,000 G. The power sources have been shown to have the potential of completely eliminating the need for chemical batteries in many fuzing applications, while having the added advantage of providing for considerably more safety and long shelf life. Prototypes of a number of designs of this class of energy harvesting power sources for various power requirements have been constructed and successfully tested in the laboratory and by the U. S. Army (ARDEC) using air guns.

Prototype sensors have been developed to detect the onset of corrosion in steel reinforced concrete using non-invasive techniques. These sensors are designed to be extremely simple and low cost. The sensors are embedded in the concrete and are powered and interrogated through the use of inductively coupled magnetic fields. A new conductivity sensor is proposed, based on the design of the corrosion sensor. The conductivity sensor design is examined using circuit simulations and initial experimental results. Both sensors could be used together in a corrosion monitoring system.

As wireless sensor has emerged as a promising technology in recent years, active sensing which integrates actuation capability in a wireless sensor unit for detecting localized damage has been brought into sight in structural health monitoring. However, the inefficiency of conventional energy conversion system is a major constraint for the utilization of reactive actuator, such as piezoelectric, in the wireless sensor unit since power source is limited. This paper proposes a highly efficient low power switching amplifier to drive piezoelectric disc in the high frequency for wireless sensor applications.

The development of an innovative wireless strain sensing technology has a great potential to extend its applications in manufacturing, civil engineering and aerospace industry. This paper presents a novel wireless and powerless strain sensor with a multi-layer thick film structure. The sensor employs a planar inductor (L) and capacitive transducer (C) resonant tank sensing circuit, and a strain sensitive material of a polarized polyvinylidene fluoride (PVDF) piezoelectric thick film to realize the wireless strain sensing by strain to frequency conversion and to receive radio frequency electromagnetic energy for powering the sensor. The prototype sensor was designed and fabricated. The results of calibration on a strain constant cantilever beam show a great linearity and sensitivity about 0.0013 in a strain range of 0-0.018.

An optimized sensor design and sensor placement strategy will be extremely beneficial to both safety ensuring and cost reduction considerations of structural health monitoring systems. A new framework for structural health monitoring sensor placement optimization was recently developed at Pennsylvania State University based on genetic and evolutionary computation. The formulation of the optimization problem is to minimize the damage misdetection rate as well as to minimize the number of sensors by searching the optimized patterns of sensor placement topology on the feasible region of the structure being monitored. Two types of SHM sensors are considered. One is a single sensor scenario; the other is an actuator-damage-sensor scenario. The program was applied to a sample sensor placement problem of an aging aircraft wing. Optimized sensor placement designs are obtained. The tradeoff relationship between the sensor performance, sensor number, and the overall sensor network performance are also presented in this paper.

We have developed a technique to realize dense sensor/actuator networks that can be deployed on the centimeter to meter-scale in a cost-effective manner. The two-dimensional network is entirely processed in a CMOS foundry before it is "stretched" to the target size and "cut" to the right shape. Our technique therefore combines the maturity of CMOS fabrication techniques with the ability to quickly assemble a fully interconnected 2D sensor network of arbitrary size and shape. Both sensor node placement and network wiring are achieved automatically. The sensor networks are rugged because no wire bonds or solder connections are needed and can be seamlessly integrated into structural materials. The high node count per unit area and large amount of electronic functionality that can be integrated per node will lead to a new class of materials and structures that are truly intelligent.

This paper reports our progress toward development of a unilateral vestibular prosthesis. The sensing element of the prosthesis is a custom designed one-axis MEMS gyroscope. Similarly to the natural semicircular canal, the microscopic gyroscope senses angular motion of the head and generates voltages proportional to the corresponding angular accelerations. Then, voltages are sent to the pulse generating unit where angular motion is translated into voltage pulses. The voltage pulses are converted into current pulses and are delivered through specially designed electrodes, conditioned to stimulate the corresponding vestibular nerve branch. Our preliminary experimental evaluations of the prosthesis on a rate table indicate that the device's output matches the average firing rate of vestibular neurons to those in animal models reported in the literature. The proposed design is scalable; the sensing unit, pulse generator, and the current source can be potentially implemented on a single chip using integrated MEMS technology.

The nondestructive evaluation (NDE) of adhesively bonded structures is a complex process. Earlier work has confirmed that ultrasonic waves are influenced by the properties of the material in which they travel. Acousto-ultrasonic methods have been widely used by previous researchers to generate ultrasonic waves in plates and bonded structures for flaw detection, visualization, and measurements of the local properties of the jointed materials. This paper will present the methods and principles used for generation and propagation of ultrasonic guided waves (Lamb waves) using piezoelectric wafer active sensors (PWAS).

We introduce a technology for robust and low maintenance sensor networks capable of detecting micro-g accelerations in a wide frequency bandwidth (above 1,000 Hz). Sensor networks with such performance are critical for navigation, seismology, acoustic sensing, and for the health monitoring of civil structures. The approach is based on the fabrication of an array of highly sensitive accelerometers, each using a Fabry-Perot cavity with transparent passbands at specific wavelengths that allows for embedded optical detection and serialization. A unique feature of this approach is that no local power source is required for each individual sensor. Instead one global light source is used, providing an optical input signal which propagates through an optical fiber network from sensor to sensor. The information from each sensor is embedded into the transmitted light as a wavelength division multiplexed signal. We present for the first time the preliminary demonstration of a system of two linear serialized wavelength division multiplexed Fabry-Perot sensors of less then 1.5dB loss per device. The sensors are formed using an optical thin film multilayer structure that takes advantage of the natural non-uniformity in deposited thin films to allow serialization.

Structural health monitoring (SHM) technology may be applied to composite bonded repairs to enable the continuous through-life assessment of the repair efficacy. This paper describes an SHM technique for the detection of debonding in composite bonded patches using fibre optic Bragg grating strain sensors. A two sided doubler repair is examined in this paper. A finite element study was conducted which showed that the strain in the debonded region changed significantly compared to the undamaged state. A differential strain approach was used to facilitate the detection of debonds, where two sensors were strategically positioned so that their strain differential increased with the disbond length. With the use of matching gratings, this technique greatly reduces the interrogation equipment requirement by converting spectral information into an intensity-modulated signal, thus allowing a threshold value to be set to indicate imminent critical repair failure. An experimental investigation was conducted, using carbon/epoxy patches to carbon/epoxy substrates, to validate the theoretically predicted results. The experimental measurements agreed well with the numerical findings, indicating that the proposed scheme has great potential as a simple monitoring technique for composite bonded repairs.

Among various optical fiber distance sensing techniques, optical fiber sensors based on white-light Fabry-Perot interferometry offer the simplest configuration, the highest sensitivity, and the most precise distance measurement. Because a whitelight interferometric sensor can overcome the directional ambiguity problem encountered by the other interferometric techniques, it is especially attractive for applications where absolute distance measurement is desired. However, conventional two-fringe matching data demodulation technique can induce a half wavelength error to the distance measurement. In this paper, we present an improved fringe matching data interrogation technique that can overcome this problem. The data interrogation scheme consists of two steps: a rough estimation of the distance and the phase shift using the two fringe matching technique and a more precise estimation of the distance and the phase shift using the correctional terms derived from the fringe difference. Simulation results indicate that the algorithm can converge to the correct distance with sub-Armstrong accuracy over a large dynamic range.

In this paper, a sensor network system based on an active sensing scheme is introduced to identify cracks which may occur at a welded zone of a steel truss member. The active sensing network system offers special potential for real world applications, as it is light, cheap, and useful as a built-in system. Four pairs of pitch-catch Lamb wave signals are utilized from the active sensing network system. In order to extract damage sensitive features from the dispersive Lamb waves, a robust wavelet transform is applied to the original response signals. Peak values in the wavelet coefficients corresponding to the A0 Lamb mode are only considered for application to the damage index. The root-mean-square change of the peak values due to damage is proposed as a damage index. In addition, a least-square curve-fitting algorithm is applied to the damage indices in order to obtain a practical damage indicator with a threshold value that presents the damage tolerance. Finally, damage localization is carried out by investigating the change rates of the damage index according to each damage step. The applicability of the proposed methods has been demonstrated by an experimental study.

Signal processing algorithms for guided wave pulse echo-based SHM must be capable of isolating individual reflections from defects in the structure, if any, which could be overlapping and multimodal. In addition, they should be able to estimate the time-frequency centers, the modes and individual energies of the reflections, which would be used to locate and characterize defects. Finally, they should be computationally efficient and amenable to automated processing. This work addresses these issues with a new algorithm employing chirplet matching pursuits followed by a mode correlation check for single point sensors. Its theoretical advantages over conventional time-frequency representations in all aspects are elaborated and these are demonstrated using numerical simulations and experiments in isotropic plate structures. The issue of in-plane triangulation is then discussed and experimental work done to explore this issue is presented. This work concludes with a description of how the algorithm can be extended to composite plate structures.

The inspection of building structures, especially bridges, is currently made by visual inspection. The few non-visual methodologies make use of wired sensor networks, which are relatively expensive, vulnerable to damage, and time consuming to install. Systems based on wireless sensor networks should be both cost efficient and easy to install, scalable and adaptive to different type of structures. Acoustic emission techniques are an additional monitoring method to investigate the status of a bridge or some of its components. It has the potential to detect defects in terms of cracks propagating during the routine use of structures. However, acoustic emissions recording and analysis techniques need powerful algorithms to handle and reduce the immense amount of data generated. These algorithms are developed on the basis of neural network techniques and - regarding localization of defects - by array techniques. Sensors with low price are essential for such monitoring systems to be accepted. Although the development costs of such a system are relatively high, the target price for the entire monitoring system will be several thousands Euro, depending on the size of the structure and the number of sensors necessary to cover the most important parts of the structure. Micro-Electro-Mechanical-Systems and hybrid sensors form the heart of Motes (network nodes). The network combined multi-hop data transmission techniques with efficient data pre-processing in the nodes. Using this technique, monitoring of large structures in civil engineering becomes very efficient including the sensing of temperature, moisture, strain and other data continuously. In this paper, the basic principles of a wireless monitoring system equipped with MEMS sensors is presented along with a first prototype. The authors work on details of network configuration, power consumption, data acquisition and data aggregation, signal analysis and data reduction is presented.

An extensive program of full-scale ambient vibration testing has been conducted to measure the dynamic response of a 240 meter cable-stayed bridge - Gi-Lu Bridge in Nan-Tou County, Taiwan. A MEMS-based wireless sensor system and a traditional microcomputer-based system were used to collect and analyze ambient vibration data. A total of four bridge modal frequencies and associated mode shapes were identified for cables and the deck structure within the frequency range of 0~2Hz. The experimental data clearly indicated the occurrence of many closely spaced modal frequencies. Most of the deck modes were found to be associated with the cable modes, implying a considerable interaction between the deck and cables. The results of the ambient vibration survey were compared to modal frequencies and mode shapes computed using three-dimensional finite element modeling of the bridge. For most modes, the analytical and the experimental modal frequencies and mode shapes compare quite well. Based on the findings of this study, a linear elastic finite element model for deck structures and beam element with P-Delta effect for the cables appear to be capable of capturing much of the complex dynamic behavior of the bridge with good accuracy.

A novel sensor failure detection method is developed in this paper. Sensor failure considered in this paper can be any type of measurement error that is different from the true structural response. The sensors are divided into two groups, sensors that correctly measure the structural responses, are termed as reference sensors, and sensors that may fail to correctly measure the structural responses, are termed as uncertain sensors henceforth. A sensor error function, one for each uncertain sensor, is formulated to detect the corresponding uncertain sensor failure in real-time, using the measurements from reference sensors and the uncertain sensor being monitored. The sensor error function is derived using the indirect and direct approaches. In the indirect approach, the error function is obtained from the state space model in combination with the inverse model and interaction matrix formulation. The input term is eliminated from the error function by applying inverse model and the interaction matrix is applied to eliminate the state and all uncertain sensor measurement terms excepted the examined uncertain sensor from the error function. In the direct approach, the coe±cients of the error function can be directly calculated from the healthy measurement data from the examined uncertain sensor and all reference sensors without having to know the state-space model of the system. Thus the need to know the state-space model of the plant can be bypassed. The sensor failure detection formulations are investigated numerically using a four degree-of-freedom spring-mass-damper system and experimentally using a 4m long NASA 8-bay truss structure. It is shown by means of numerical and experimental results that the developed sensor failure formulations correctly detect the instants of sensor failure and can be implemented in real structural systems for sensor failure detection.

This paper introduces a heuristic methodology for designing multilayer feedforward neural networks to model the types of nonlinear functions common to many engineering mechanics applications. It is well known that a perfect way to determine the ideal architecture to initialize neural network training has not yet been established. This could be because this challenging issue can only be properly addressed by looking into the features of the function to be approximated and thus might be hard to tackle in a general sense. In this study, the authors do not presume to provide a universal method approximate an arbitrary function, rather the focus is given to modeling nonlinear hysteretic restoring forces, a significant domain function approximation problem. The governing physics and mathematics of nonlinear hysteretic dynamics as well as the strength of the sigmoidal basis function are exploited to determine both an efficient neural network architecture (e.g., the number of hidden nodes) as well as effective initial weight and bias values for those nodes. Training examples are presented to demonstrate and validate the proposed initial design methodology. Comparisons are made between the proposed methodology and the widely used Nguyen-Widrow Initialization. Future work is also identified.

Many damage detection and system identification approaches benefit from the availability of both acceleration and displacement measurements. This is particularly true in the case of suspected nonlinear behavior and permanent deformations. In civil and mechanical structural modeling accelerometers are most often used, however displacement sensors, such as non-contact optical techniques as well as GPS-based methods for civil structures are becoming more common. It is suggested, where possible, to exploit the inherent redundancy in the sensor information and combine the collocated acceleration and displacement measurements in a manner which yields highly accurate motion data. This circumvents problematic integration of accelerometer data that causes lowfrequency noise amplification, and potentially more problematic differentiation of displacement measurements which amplify high-frequency noise. Another common feature of displacement based sensing is that the high frequency resolution is limited, and often relatively low sampling rates are used. In contrast, accelerometers are often more accurate for higher frequencies and thus higher meaningful sampling rates are often available. The fusion of these two data types must therefore combine data sampled at different frequencies. A multi-rate Kalman filtering approach is proposed to solve this problem. In addition, a smoothing step is introduced to obtain improved accuracy in the displacement estimate when it is sampled at lower rates than the corresponding acceleration measurement. Through trials with simulated data the procedure's effectiveness is shown to be quite robust at a variety of noise levels and relative sample rates for this practical problem.

As carbon fiber-reinforced polymer (CFRP) laminates have been widely accepted as valuable materials for retrofitting civil infrastructure systems, an appropriate assessment of bonding conditions between host structures and CFRP laminates becomes a critical issue to guarantee the performance of CFRP strengthened structures. This study attempts to develop a continuous performance monitoring system for CFRP strengthened structures by autonomously inspecting the bonding conditions between the CFRP layers and the host structure. The uniqueness of this study is to develop a new concept and theoretical framework of nondestructive testing (NDT), in which debonding is detected "without using past baseline data." The proposed baseline-free damage diagnosis is achieved in two stages. In the first step, features sensitive to debonding of the CFPR layers but insensitive to loading conditions are extracted based on a concept referred to as a time reversal process. This time reversal process allows extracting damage-sensitive features without direct comparison with past baseline data. Then, a statistical damage classifier will be developed in the second step to make a decision regarding the bonding condition of the CFRP layers. The threshold necessary for decision making will be adaptively determined without predetermined threshold values. Monotonic and fatigue load tests of full-scale CFRP strengthened RC beams are conducted to demonstrate the potential of the proposed reference-free debonding monitoring system.

Base isolation systems have been used in buildings and bridges as protective systems against earthquakes, and the health monitoring of base isolators is of great importance. The ability to detect damages on-line, based on vibration data measured from the health monitoring system, will ensure the reliability and safety of base-isolated structures. When a base-isolated structure is subject to strong earthquakes, it is important to be able to determine the damage of isolators from the seismic response data either on-line or almost on-line. The problem is quite challenging because the restoring force of the base isolator is inelastic, and only a limited number of sensors can be installed in the structural health monitoring system, indicating that the response data may not be available at all degrees of freedom of the structure and that the external excitations may not be measured. In this paper, we propose a new data analysis method, referred to as the sequential nonlinear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO), for the real time on-line identification of structural damages, including the nonlinear base isolators. In this approach, only a limited number of response data are needed and the external excitations may not be measured. Analytical recursive solutions are derived and presented, which are not available in previous literature. The Bou-Wen model is used for the nonlinear base-isolation system, and the accuracy of the new approach is demonstrated using a base-isolated building. Simulation results demonstrate that the proposed approach is capable of tracking on-line the changes of structural parameters, such as the parameters of base isolators, leading to the identification of structural damages.

A new damage detection technique using the roughness profile of structural mode shape is developed in this study. In this method, the spatially distributed signal (e.g., displacements or mode shapes) of a damaged structure is treated as an engineering surface. Irregularity of the surface induced by damage in beam-type structure is then treated as the roughness of the surface. A simple algorithm is developed to extract the roughness profile from the surface. The location and severity of damage is then determined by a sudden change on the roughness profile. This method is then applied to the mode shapes of cracked and delaminated beams obtained analytically, from which the damage location and size are determined successfully. As verifications, the proposed method is further applied on the experimentally measured curvature mode shapes to detect damage in carbon/epoxy composite beams. The successful detection of crack and delamination damage in the composite beams demonstrates that the new technique developed in this study can be used efficiently and effectively in damage identification and health monitoring of beam-type structures.

This paper presents a variety of methodologies that are used to detect the location and amount of structural damage using dynamic measurements of the input and of the structural response. One approach (and its variations) starts from an identified first order model of a structural system and obtain estimation of the structure's mass, damping and stiffness matrices. For these approaches, both the full instrumentation option and the partial instrumentation option are presented. An alternative approach for the identification of the dynamic characteristics of the structure is based on Evolution Strategies. Once these dynamic characteristics have been determined, structural damage is assessed by comparing the undamaged and damaged estimation of such parameters. Both these methodologies are tested on simulated numerical results and their effectiveness in determining structural damage is evaluated.

The long-term reliability of a threshold corrosion sensor is demonstrated using data collected during two series of exposure tests. The sensors were embedded in concrete and interrogated in a wireless manner using inductive coupling. The frequency signature of the sensor changes after a steel sensing wire corrodes, providing a convenient and noninvasive technique for determining when a threshold amount of corrosion has occurred in a reinforced concrete structure. In the first series of exposure tests, the sensors were embedded in concrete prisms, which were exposed to a variety of temperature and moisture conditions over a six-month period. In the second series of tests, the sensors were embedded in reinforced concrete slabs. The slabs have been subjected to sustained loads and alternating wet and dry cycles for the past year. Data from both test series indicate that the threshold sensors are functioning as designed.

A structure is vulnerable if any small damage will trigger disproportionately large consequences, even leads to a cascade of failure events and progressive collapse. The structural vulnerability performance depends upon the properties, locations of damaged components and the way they are connected to the rest of the structure. In this paper, progressive failure analysis method is utilized for the vulnerability study of cable-stayed bridges. The goal of it is to identify various failure scenarios initiated from the sudden damage of some bridge components. Based on the analysis results, assuming that the behaviors of damaged components can be modeled using plastic hinges, the hybrid element model is introduced to derived the modified stiffness matrix considering both of the effects of bending moments and shear forces. Furthermore, the vulnerability index in terms of the nodal stiffness degradation can be analytically quantified, which could be regarded as an index to determine the bridge failure consequences, so that the vulnerability distribution graph for the whole bridge can be sketched to evaluate the bridge performances from vulnerability viewpoints. This quantitative approach is applicable for structural evaluation under unforeseen attack and illustrated on a typical long-span cable-stayed bridge.

Structural Health Monitoring (SHM), the technology to evaluate the health of the structure (such as earthquake resistance), is getting attention recently. The techniques for evaluating earthquake-proof performance in the building are key elements. However, existing techniques are not so practical as they require professional knowledge on structural engineering. The chaos analysis method, recently proposed by Prof. Okada is an attractive method to meet the need. The method evaluates earthquake-proof performance, using chaos analysis. It is clear that there is correlation between chaos theory and physical parameters. This paper proposes a modified version of chaos analysis to make the method stable and reliable. Findings in the course of this study are as follows. (1) The chaos degree rises when attenuation grows. (2) The chaos degree rises by widening the band of the frequency. (3) The ground motion with large power decides the chaos degree. (4) The chaos degree is not unique for the same structure depending on the inputs. These are due to the results of simulation and full-scale experiments. Using these findings, the computational method of the chaos degree without depending on the characteristics of inputs is established. It is a method using the system identification to estimate the parameter model of building from the result of the response due to any inputs. The influence of the input characteristic can be excluded by this method.