Abstract

Heterogeneous wireless sensor networks (HWSNs) are widely adopted in structural health monitoring systems due to their potential for implementing sophisticated algorithms by integrating a diverse set of devices and improving a network’s sensing performance. However, deploying such a HWSN is still in a challenge due to the heterogeneous nature of the data and the energy constraints of the network. To respond to these challenges, an optimal deployment framework in terms of both modal information quality and energy consumption is proposed in this study. This framework generates a multi-objective function aimed at maximizing the quality of the modal information identified from heterogeneous data while minimizing the consumption of energy within the network at the same time. Particle swarm optimization algorithm is then implemented to seek solutions to the function effectively. After laying out the proposed sensor-optimization framework, a methodology is present to determine the clustering of the sensors to further conserve energy. Finally, a numerical verification is performed on a four-span pre-stressed reinforced concrete box-girder bridge. Results show that a set of strategically positioned heterogeneous sensors can maintain a balanced trade-off between the modal information accuracy and energy consumption. It is also observed that an appropriate cluster-tree network topology can further achieve energy saving in HWSNs.

Highlights

  • Structural health monitoring (SHM) has been widely used to monitor and diagnose the health status of civil structures/infrastructures in real-time [1]

  • We focus on modal identification performance based on vibration information, acquired through two common types of sensors in SHM—Wireless accelerometers and strain gauges

  • The study is aimed to determine the best data transmission path of the Heterogeneous wireless sensor networks (HWSNs) based on the sensor configuration from initial optimization results, and to compare the performance of network topology effects on energy consumption

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Summary

Introduction

Structural health monitoring (SHM) has been widely used to monitor and diagnose the health status of civil structures/infrastructures in real-time [1]. Variance (MV) method [16], and Kinetic Energy (KE) method [17], have been proposed and verified by practical SHM implementations In addition to these existing OSD techniques designed for modal parameter estimation in wired SHM systems, a handful of works have attempted to address the OSD issues for wireless sensor networks. Fu et al [22] performed a study to optimize wireless sensor placement for SHM in terms of both the quality of the modal information and network energy consumption These OSD algorithms were feasible because most WSNs in these studies were homogeneous (sensors have the same type, storage, processing, battery power, sensing, and communication capabilities). A framework is proposed to optimize the layout of multi-type wireless sensors at critical locations of the structure in terms of the modal information quality and network energy consumption.

Optimization Problem Formulation in HWSNs
Heterogeneous Sensor Placement Quality
Modal Clarity Index
Modal Relative Error
Placement Quality Index
Network Model
Objective
Multi-Objective Optimization Function
Particle Swarm Optimization Algorithm
Network Topology Optimization
E RX receiving circuit
Two-Phase Energy Consumption Formulation
Optimal Clustering
Performance Evaluation
Simulation Setup
Bridge
Bearing
Sensor Layout Optimization Results
Clustering Optimization Results
Conclusions
Full Text
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