Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.
With development of wireless sensor technology, wireless sensor network has shown a great potential for railway health
monitoring. However, how to supply continuous power to the wireless sensor nodes is one of the critical issues in long-term full-scale deployment of the wireless smart sensors. Some energy harvesting methodologies have been available including solar, vibration, wind, etc; among them, vibration-based energy harvester using piezoelectric material showed the potential for converting ambient vibration energy to electric energy in railway health monitoring even for underground subway systems. However, the piezoelectric energy harvester has two major problems including that it could only generate
small amount of energy, and that it should match the exact narrow band natural frequency with the excitation frequency.
To overcome these problems, a wide band piezoelectric energy harvester, which could generate more power on various frequencies regions, has been designed and validated with experimental test. Then it was applied to a full-scale field test using actual railway train. The power generation of the wide band piezoelectric array has been compared to a narrow-band, resonant-based, piezoelectric energy harvester.
Improving the safety and security of civil infrastructure has become a critical issue for decades since it plays a central role in the economics and politics of a modern society. Structural health monitoring of civil infrastructure using wireless smart sensor network has emerged as a promising solution recently to increase structural reliability, enhance inspection quality, and reduce maintenance costs. Though hardware and software framework are well prepared for wireless smart sensors, the long-term real-time health monitoring strategy are still not available due to the lack of systematic interface. In this paper, the Imote2 smart sensor platform is employed, and a graphical user interface for the long-term real-time structural health monitoring has been developed based on Matlab for the Imote2 platform. This computer-aided engineering platform enables the control, visualization of measured data as well as safety alarm feature based on modal property fluctuation. A new decision making strategy to check the safety is also developed and integrated in this software. Laboratory validation of the computer aided engineering platform for the Imote2 on a truss bridge and a building structure has shown the potential of the interface for long-term real-time structural health monitoring.
With the rapid development of electrical circuits, Micro electromechanical system (MEMS) and network technology, wireless smart sensor networks (WSSN) have shown significant potential for replacing existing wired SHM systems due to their cost effectiveness and versatility. A few structural systems have been monitored using WSSN measuring acceleration, temperature, wind speed, humidity; however, a multi-scale sensing device which has the capability to measure the displacement has not been yet developed. In the previous paper, a new high-accuracy displacement sensing system was developed combining a high resolution analog displacement sensor and MEMS-based wireless microprocessor platform. Also, the wireless sensor was calibrated in the laboratory to get the high precision displacement data from analog sensor, and its performance was validated to measure simulated thermal expansion of a laboratory bridge structure. This paper expands the validation of the developed system on full-scale experiments to measure both static and dynamic displacement of expansion joints, temperature, and vibration of an in-service highway bridge. A brief visual investigation of bridges, comparison between theoretical and measured thermal expansion are also provided. The developed system showed the capability to measure the displacement with accuracy of 0.00027 in.
Wireless sensor network is one of the prospective methods for railway monitoring due to the long-term operation and low-maintenance performances. How to supply power to the wireless sensor nodes has drawn much attention recently. In railway monitoring, the idea of converting ambient vibration energy from vibration of railway track induced by passing trains to electric energy has made it a potential way for powering the wireless sensor nodes. Nowadays, most of vibration based energy harvesters are designed at resonance. However, as railway vibration frequency is a wide band range, how to design an energy harvester working at that range is critical. In this paper, the energy consumption of the wireless smart sensor platform, Imote2, at different working states were investigated. Based on the energy consumption, a design of a bimorph cantilever piezoelectric energy harvester has been optimized to generate maximum average power between a wide-band frequency range. Significant power and current outputs have been increased after optimal design. Finally, the rechargeable battery life for supplying the Imote2 for railway monitoring is predicted by using the optimized piezoelectric energy harvesting system.
Wireless sensor network is one of prospective methods for railway bridge health monitoring. It has drawn much attention
due to the long-term operation and low-maintenance performances. However, how to provide power to wireless sensors
is a big issue. In railway health monitoring, the idea of converting ambient vibration energy from the vibration of railway
track induced by passing train to electric energy has made it an efficient way for powering the wireless sensor networks.
In this paper, a bimorph piezoelectric energy harvester from base excitation was investigated in the laboratory, and the
energy output of the bimorph energy harvester was predicted by an equivalent single-degree-of-freedom (SDOF) model.
Reasonable results have been found between the tested and predicted data. Based on the theoretical model, further works
on optimization of the bimorph piezoelectric energy harvester will be performed in future.