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Structural Damage Detection Based on Autoregressive Spectra Analysis of Time Series

[+] Author Affiliations
Ming-Hui Hu, Shan-Tung Tu, Fu-Zhen Xuan, Shao-Ping Zhou, Chun-Ming Xia

East China University of Science and Technology, Shanghai, China

Er-Ding Cong

Petro-China Jilin Petrochemical Company, Jilin, China

Paper No. IMECE2012-85993, pp. 759-763; 5 pages
  • ASME 2012 International Mechanical Engineering Congress and Exposition
  • Volume 4: Dynamics, Control and Uncertainty, Parts A and B
  • Houston, Texas, USA, November 9–15, 2012
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4520-2
  • Copyright © 2012 by ASME


In this paper, an autoregressive spectral analysis method is proposed for on-line structural damage detection. Firstly, the monitoring strain data are modeled as ARMA models. The power spectral density (PSD) value is directly determining by center-autocorrelation function and statistical autocorrelation function. Structural damage detection is conducted by comparing the values of PSD of the inspected structure. Two experimental applications to the detection of damage in industrial piping structure demonstrate the potential and effectiveness of the new damage detection technique.

Copyright © 2012 by ASME



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