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Adaptive quadratic sum‐squares error with unknown inputs for damage identification of structures
Author(s) -
Huang Hongwei,
Yang Jann N.,
Zhou Li
Publication year - 2010
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.318
Subject(s) - quadratic equation , nonlinear system , identification (biology) , least squares function approximation , structural health monitoring , computer science , recursive least squares filter , algorithm , control theory (sociology) , damages , line (geometry) , engineering , structural engineering , mathematics , physics , adaptive filter , artificial intelligence , statistics , botany , control (management) , quantum mechanics , law , political science , geometry , estimator , biology
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 © 2009 John Wiley & Sons, Ltd.