DocumentCode :
3391954
Title :
Visualization of Damage Detection for Circular Arch Based on Stochastic Subspace Identification
Author :
Zhenhua, Nie ; Jun, Zhao ; Hongwei, Ma ; Liangyan, Cheng
Author_Institution :
Key Lab. of Disaster Forecast & Control in Eng., Jinan Univ., Guangzhou, China
Volume :
2
fYear :
2010
fDate :
23-24 Oct. 2010
Firstpage :
127
Lastpage :
130
Abstract :
When performing vibration tests on civil engineering structures, it is often unpractical and expensive to use artificial excitation (shakers, drop weights). Ambient excitation on the contrary is freely available (traffic, wind), but it causes other challenges. The ambient input remains unknown and the system identification algorithms have to deal with output-only measurements. The empirical mode decomposition (EMD) based stochastic subspace identification procedure utilizing operational vibration measurements is presented in this paper. The SSI method is then applied to the decomposed signals to yield the modal parameters of the hinged circular arch which is divided into sixteen elements, and then the strain mode shapes are obtained. In order to let the non-specialist to understand the message of the damages, the strain modes of the arch are presented with visual images. Visualization of damage detection has great potential for development of On-line structure health monitoring.
Keywords :
acoustic signal processing; condition monitoring; data visualisation; dynamic testing; fault location; stochastic processes; structural engineering computing; vibration measurement; ambient excitation; artificial excitation; civil engineering structures; damage detection visualization; decomposed signals; empirical mode decomposition; hinged circular arch; on-line structure health monitoring; output-only measurements; stochastic subspace identification; stochastic subspace identification procedure; strain modes; system identification algorithms; vibration measurements; vibration tests; visual images; Data visualization; Image color analysis; Mathematical model; Matrix decomposition; Stochastic processes; Strain; Visualization; circular arch; damage identification; stochastic subspace identification; strain mode; visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
Type :
conf
DOI :
10.1109/AICI.2010.150
Filename :
5655132
Link To Document :
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