Efficient time synchronization for structural health monitoring using wireless smart sensor networks

Abstract

Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (˂50 mu s maximum error) for SHM, even for long sensing duration.