Application of higher order SVD to vibration-based system identification and damage detection

Shu-Hsien Chao; Chin-Hsiung Loh; Jian-Huang Weng

doi:10.1117/12.914617

3 April 2012 Application of higher order SVD to vibration-based system identification and damage detection

Shu-Hsien Chao, Chin-Hsiung Loh, Jian-Huang Weng

Author Affiliations +

Proceedings Volume 8345, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012; 834525 (2012) https://doi.org/10.1117/12.914617
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2012, San Diego, California, United States

Abstract

Singular value decomposition (SVD) is a powerful linear algebra tool. It is widely used in many different signal processing methods, such principal component analysis (PCA), singular spectrum analysis (SSA), frequency domain decomposition (FDD), subspace identification and stochastic subspace identification method ( SI and SSI ). In each case, the data is arranged appropriately in matrix form and SVD is used to extract the feature of the data set. In this study three different algorithms on signal processing and system identification are proposed: SSA, SSI-COV and SSI-DATA. Based on the extracted subspace and null-space from SVD of data matrix, damage detection algorithms can be developed. The proposed algorithm is used to process the shaking table test data of the 6-story steel frame. Features contained in the vibration data are extracted by the proposed method. Damage detection can then be investigated from the test data of the frame structure through subspace-based and nullspace-based damage indices.

Citation Download Citation

Shu-Hsien Chao, Chin-Hsiung Loh, and Jian-Huang Weng "Application of higher order SVD to vibration-based system identification and damage detection", Proc. SPIE 8345, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2012, 834525 (3 April 2012); https://doi.org/10.1117/12.914617

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE