Robust wireless sensor network configuration design for structural health monitoring with optimal information-energy tradeoff

Xiao-Han Hao , Sin-Chi Kuok , Ka-Veng Yuen

Abstract

In this paper, a robust wireless sensor network configuration design method is proposed to develop the optimal configuration under the consideration of sensor failure and energy consumption. A malfunctioned sensor in a wireless sensor network may lead to data transmission failure of the entire sensing cluster, inducing severe deterioration in system identification performance. The proposed method determines a wireless sensor network configuration that is robust against sensor failure. By utilizing Bayesian inference, we introduce a robust indicator to evaluate the impact on estimation accuracy of sensor configurations with various malfunctioned sensors. Moreover, a network formation strategy is proposed to optimize the energy efficiency of the wireless sensor network configuration. Therefore, the resultant robust wireless sensor network configuration can operate with the minimum energy consumption while the measurement information of the sensor network with malfunctioned sensors can be guaranteed. The proposed method is illustrated by designing the robust wireless sensor network configurations of a truss model and a bridge model.

Key Words

Bayesian inference; energy efficiency; multi-type sensing devices; parameter identification; robust wireless sensor network; sensor failure

Address

(1) Xiao-Han Hao — School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
(2) Sin-Chi Kuok, Ka-Veng Yuen — State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering, University of Macau, Macao SAR, China
(3) Sin-Chi Kuok, Ka-Veng Yuen — Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities, University of Macau, Macao SAR, China.

PDF Viewer

Preview is limited to the first 3 pages. Sign in to access the full PDF.

← Back to Volume 33, No. 6