Adaptive quadratic sum-squares error with unknown inputs for damage identification of structures

被引:47
作者
Huang, Hongwei [1 ]
Yang, Jann N. [2 ]
Zhou, Li [3 ]
机构
[1] Tongji Univ, Dept Bridge Engn, Shanghai 200092, Peoples R China
[2] Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA 92697 USA
[3] Nanjing Univ Aeronaut & Astronaut, Coll Aerosp Engn, Nanjing 210016, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
structural health monitoring; adaptive quadratic sum-squares error with unknown inputs; adaptive tracking; system identification; damage detection; LEVEL SYSTEM-IDENTIFICATION; ONLINE IDENTIFICATION; FILTER;
D O I
10.1002/stc.318
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The detection of structural damages, either on-line or almost on-line, based on vibration data measured from sensors, is essential for the structural health monitoring system. The problem is quite challenging, in particular when the external excitations are not completely measured. In practical applications, external excitations (inputs), such as seismic excitations, wind loads, traffic loads, etc., may not be measured or may not be measurable. In this paper, we propose a new damage detection method, referred to as the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), for the detection of structural damages. In this approach, external excitations and some structural responses may not be measured. Analytical recursive solution for the proposed AQSSE-UI method will be derived and presented. The accuracy and effectiveness of the proposed approach will be demonstrated by: (1) numerical simulations using both linear and nonlinear structures, and (2) available experimental data. Both the simulation results and experimental data indicate that the proposed approach is a viable damage detection technique capable of: (i) identifying structural parameters, (ii) tracking the changes of parameters leading to the detection of structural damages, and (iii) identifying the unknown external excitations. Copyright (C) 2009 John Wiley & Sons, Ltd.
引用
收藏
页码:404 / 426
页数:23
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