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考虑传感器失效的鲁棒性结构监测传感器优化布设

周广东 龙伟 沈安斌 张佳宁 杨佳怡

东南大学学报(英文版)2025,Vol.41Issue(3):286-294,9.
东南大学学报(英文版)2025,Vol.41Issue(3):286-294,9.DOI:10.3969/j.issn.1003-7985.2025.03.004

考虑传感器失效的鲁棒性结构监测传感器优化布设

Robustness-oriented optimal sensor placement for structural monitoring considering sensor failures

周广东 1龙伟 2沈安斌 2张佳宁 1杨佳怡1

作者信息

  • 1. 河海大学土木与交通学院,南京 210098
  • 2. 中铁交通投资集团有限公司,南宁 530219
  • 折叠

摘要

Abstract

Conventional optimal sensor placement(OSP)methods employ the premise that all sensors work perfectly during long-term structural monitoring.However,this premise is often difficult to fulfill in real applications due to poor manufacturing and material aging of sensors,human damage,and electromagnetic interference.This paper pres-ents a robustness-oriented OSP method that considers sensor failures.The OSP problem is designed with consideration of sensor failures to ensure that both complete vibration data collected by all sensors and incomplete vibration data caused by individual sensor failures can accurately identify structural modal parameters.A dispersion-aggregation fire-fly algorithm(DAFA),which is derived from the basic fire-fly algorithm,has been proposed to solve this complicated optimization problem.The dispersion and aggregation op-erators are designed to prevent falling into local optima and to rapidly converge to the global optima.The proposed methodology is confirmed by extracting the robust sensor configuration for a long-span cable-stayed bridge.The ro-bustness of the optimal sensor configurations against sensor failure is thoroughly explored,and the performance of the proposed DAFA is extensively examined.

关键词

结构健康监测/传感器优化布设/大跨桥梁/模态参数识别/萤火虫算法

Key words

structural health monitoring(SHM)/optimal sensor placement(OSP)/long-span bridges/modal param-eter identification/firefly algorithm

分类

交通工程

引用本文复制引用

周广东,龙伟,沈安斌,张佳宁,杨佳怡..考虑传感器失效的鲁棒性结构监测传感器优化布设[J].东南大学学报(英文版),2025,41(3):286-294,9.

基金项目

The National Natural Science Foundation of China(No.51978243,52578360). (No.51978243,52578360)

东南大学学报(英文版)

1003-7985

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