Multivariate statistical approach to structural damage detection
Wang, Zengrong, and Ong, K.C.G. (2010) Multivariate statistical approach to structural damage detection. Journal of Engineering Mechanics, 136 (1). pp. 12-22.
|PDF (Published Version) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader|
View at Publisher Website: http://dx.doi.org/10.1061/(ASCE)0733-939...
The issue of structural damage detection is addressed through an innovative multivariate statistical approach in this paper. By invoking principal component analysis, the vibration responses acquired from the structure being monitored are represented by the multivariate data of the sample principal component coefficients (PCCs). A damage indicator is then defined based on a multivariate exponentially weighted moving average control chart analysis formulation, involving special procedures to allow for the effects of the estimated parameters and to determine the upper control limits in the control chart analysis for structural damage detection applications. Also, a data shuffling procedure is proposed to remove the autocorrelation probably present in the obtained sample PCCs. This multivariate statistical structural damage detection scheme can be applied to either the time domain responses or the frequency domain responses. The efficacy and advantages of the scheme are demonstrated by the numerical examples of a five-story shear frame and a shear wall as well as the experimental example of the I-40 Bridge benchmark.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||structural health monitoring; statistics; structural dynamics; data analysis; methodology|
|FoR Codes:||09 ENGINEERING > 0905 Civil Engineering > 090506 Structural Engineering @ 100%|
|SEO Codes:||97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 100%|
|Deposited On:||21 Nov 2011 14:07|
|Last Modified:||21 Nov 2011 18:03|
Last 12 Months: 0
Repository Staff Only: item control page