Abstract
Wireless sensing systems have been proposed for structural heath monitoring in recent years. While wireless sensors are cost-competitive compared to tethered monitoring systems, their significant merit also lies in their embedded computational capabilities. In this paper, performance of the two embedded engineering algorithms, namely the fast Fourier transform and peak-picking algorithm implemented in the wireless sensing nodes codeveloped at Stanford University and the University of Michigan is investigated through laboratory and field experimental studies. Furthermore, the wireless sensor network embedded with the engineering algorithms is adopted for the identification of structural modal parameters and forces in steel bridge cables. Identification results by the embedded algorithms in the intelligent wireless sensors are compared with those obtained by conventional offline analysis of the measured time-history data. Such a comparison serves to validate the effectiveness of the intelligent wireless sensor network. In addition, it is shown that self-interrogation of measurement data based upon the two embedded algorithms in wireless sensor nodes greatly reduces the amount of data to be transmitted by the wireless sensing network. Thus, the intelligent wireless sensors offer scalable network solutions that are power-efficient for the health monitoring of civil infrastructures.
Highlights
Conventional structural monitoring systems are wire-based systems, which require extensive lengths of cables to transmit recorded data from multiple sensors to a centralized data repository
The academic wireless sensing prototype codeveloped at Stanford University and the University of Michigan has received great attention as it emphasizes the design of a sophisticated computational core that can process measurement data at the wireless sensor level [4,5,6]
Since this paper focuses on studying the performance of the embedded fast Fourier transform (FFT) and PP algorithm in the field experiments on the Wuyuan Bridge, more detailed
Summary
Conventional structural monitoring systems are wire-based systems, which require extensive lengths of cables to transmit recorded data from multiple sensors to a centralized data repository. While wireless monitoring systems offer an economical and feasible technique for data acquisition in SHM, transmitting the lengthy vibration data to the base station can be undesirable due to the limited bandwidth of the wireless communication. The wireless sensors only need to transmit analysis results, which typically have only a fraction of the size of Advances in Civil Engineering raw time history data. Online data processing and analysis results by the two embedded algorithms are compared to those obtained by offline analysis of the measured raw time-history data. This side-by-side comparison validates the accuracy of the embedded algorithms. The two embedded algorithms are employed for identifying the modal parameters of the laboratory building model and the steel arch bridge as well as for estimating cable forces in the steel arch bridge based upon the vibration data
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