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Proceedings Paper

Identification of parametric changes for civil engineering structures using an adaptive Kalman filter
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Paper Abstract

An important objective of health monitoring systems for civil infrastructures is to identify the state of the structure and to detect the damage when it occurs. System identification and damage detection based on measured vibration data have received considerable attention recently. Frequently, the damage of a structure may be reflected by a change of some system parameters, such as a degradation of the stiffness. In this paper, we propose an adaptive tracking technique, based on the extended Kalman filter approach, to identify the structural parameters and their changes. The proposed technique is capable of tracking the abrupt change of system parameters from which the event and severity of structural damages can be detected. Our adaptive filtering technique is based on the current measured data to determine the parametric variation so that the residual error of the estimated parameters is contributed only by noises. The proposed technique is applicable to linear and nonlinear structures. Simulation results for tracking the parametric changes of linear and nonlinear hysteretic structures are presented to demonstrate the application and effectiveness of the proposed technique in detecting the structural damages using vibration data from the health monitoring system.

Paper Details

Date Published: 29 July 2004
PDF: 11 pages
Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); doi: 10.1117/12.538325
Show Author Affiliations
Jann N. Yang, Univ. of California/Irvine (United States)
Silian Lin, Univ. of California/Irvine (United States)
Li Zhou, Nanjing Univ. of Aeronautics and Astronautics (China)


Published in SPIE Proceedings Vol. 5391:
Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Shih-Chi Liu, Editor(s)

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