Translator Disclaimer
Paper
9 April 2010 Structural damage detection based on non-negative matrix factorization and relevance vector machine
Author Affiliations +
Abstract
This paper presents a novel approach to detect structural damage combining non-negative matrix factorization (NMF) and relevance vector machine (RVM). Firstly, the time history of acceleration signal are decomposed using the wavelet packet transform to extract wavelet packet node energy as the damage feature, and construct a non-negative matrix using the wavelet packet node energy index of all time history of acceleration data measured by multiple accelerometers installed on the different locations of structure. Secondly, for increasing the damage detection accuracy, the dimension of the feature non-negative matrix is reduced by NMF techniques and new representation of this matrix is obtained. Lastly, RVM, a powerful tool for classification and regression, is used to detect the location of potential damage from the reduced damage feature matrix. Numerical study on the Binzhou Yellow River Highway Bridge is carried out to illustrate the ability of the proposed method in damage detection.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuequan Bao, Hui Li, Yong Huang, and Jinping Ou "Structural damage detection based on non-negative matrix factorization and relevance vector machine", Proc. SPIE 7650, Health Monitoring of Structural and Biological Systems 2010, 76503H (9 April 2010); https://doi.org/10.1117/12.847823
PROCEEDINGS
10 PAGES


SHARE
Advertisement
Advertisement
Back to Top