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http://dx.doi.org/10.12989/sss.2022.30.6.583

Wireless sensor network design for large-scale infrastructures health monitoring with optimal information-lifespan tradeoff  

Xiao-Han, Hao (State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau)
Sin-Chi, Kuok (State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau)
Ka-Veng, Yuen (State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau)
Publication Information
Smart Structures and Systems / v.30, no.6, 2022 , pp. 583-599 More about this Journal
Abstract
In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.
Keywords
Bayesian inference; measurement information; multi-type sensor system; network lifespan; system identification; wireless sensor network;
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Times Cited By KSCI : 14  (Citation Analysis)
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