Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

Jing Zhou Lu; Jia Chen Wang; Xu Zhu

doi:10.4028/www.scientific.net/AMM.578-579.1020

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 578-579Research for Structural Damage Identification...

Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

Abstract:

In this paper, we introduce a set of techniques for time series analysis based on principal component analysis (PCA). Firstly, the autoregressive (AR) model is established using acceleration response data, and the root mean squared error (RMSE) of AR model is calculated based on PCA. Then a new damage sensitive feature (DSF) based on the AR coefficients is presented. To test the efficacy of the damage detection and localization methodologies, the algorithm has been tested on the analytical and experimental results of a three-story frame structure model of the Los Alamos National Laboratory. The result of the damage detection indicates that the algorithm is able to identify and localize minor to severe damage as defined for the structure. It shows that the suggested method can lead to less amount of computing time, high suitability and identification accuracy.

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Periodical:

Applied Mechanics and Materials (Volumes 578-579)

Pages:

1020-1023

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.578-579.1020

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Online since:

July 2014

Authors:

Jing Zhou Lu*, Jia Chen Wang, Xu Zhu

Keywords:

Damage Identification, Frameworks, Principal Component, Time Series

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References

[1] S.W. Doebling, C.R. Farrar, and M.B. Prime, The Shock and Vibration Digest Vol. 30(1998), p.91.

Google Scholar

[2] H. Sohn, C. R. Farrar, F. M. Hemez, D. D. Shunk, D. W. Stinemates, and B. R. Nadler, in: Technical Report Annex to SAMCO Summer Academy, Los Alamos National Laboratory, Cambridge, (2003).

Google Scholar

[3] H. Sohn, C.R. Farrar, H.F. Huter, K. Worden, in: Los Alamos National Laboratory Report No. LA-13761-MS, NM 87545(2001).

Google Scholar

[4] Y. Lei, A.S. Kiremidjian, K.K. Nair, J.P. Lynch, K.H. Law, T.W. Kenny, E. Carryer, A. Kottapalli, in: Proceedings of Ninth International Conference on Application of Statistics and Probability in Civil Engineering, San Francisco, CA(2003).

Google Scholar

[5] T.K. Hasselman, M.C. Anderson, G. Wenshui, in: Proceedings of the 16th International Modal Analysis Conference, Santa Barbara, CA, (1998), p.664.

Google Scholar

[6] E. Figueiredo, G. Park, J. Figueiras, C. Farrar, and K. Worden, in: Los Alamos National Laboratory Report No. LA-14393(2009).

Google Scholar