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Proceedings Paper

A time series-based structural damage detection and localization algorithm with implementation in wireless sensing units
Author(s): Ying Lei; J. L. Zhang; J. L. Liu
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Paper Abstract

In this paper, a damage detection and localization algorithm, which is suitable for the implementation of automated damage detection system based on the wireless structural monitoring sensing network, is presented. Vibration signals obtained from sensors are modeled as autoregressive moving average (ARMA) time series. Coefficients of the ARMA models are estimated by a two-stage linear identification process. Stable poles and residues of the ARMA models are extracted based on the stability tolerances on the change in frequency and damping ratios. Then, these stable poles and residues are transmitted to the centralized data server, where structural damage is detected from the change of the poles estimated from undamaged and damaged structural signals, damage locations are identified by the change ratio of the estimated mean values of first vibration mode shape of the undamaged and damaged structure. Implementation of the damage detection and localization algorithm in the wireless structural monitoring sensing system for automated damage detection is illustrated. To test the efficacy of the damage detection and localization methodologies, the algorithm is applied on the benchmark problem designed by the ASCE task group on health monitoring.

Paper Details

Date Published: 11 April 2006
PDF: 12 pages
Proc. SPIE 6174, Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, 61743O (11 April 2006); doi: 10.1117/12.657845
Show Author Affiliations
Ying Lei, Xiamen Univ. (China)
J. L. Zhang, Xiamen Univ. (China)
J. L. Liu, Xiamen Univ. (China)


Published in SPIE Proceedings Vol. 6174:
Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Masayoshi Tomizuka; Chung-Bang Yun; Victor Giurgiutiu, Editor(s)

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