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6. Global-Based Structure Damage Detection Using LVQ Neural Network and Bispectrum Analysis.

Author

Wang, Jun, Liao, Xiaofeng, Yi, Zhang, Dong, Guangming, Chen, Jin, Lei, Xuanyang, Ning, Zuogui, Wang, Dongsheng, and Wang, Xiongxiang

Abstract

In this paper, a new approach for the global-based structure damage detection is proposed, which is based on the combination of bispectrum feature extraction technique and LVQ neural network identification method. A finite element model based on a steel frame structure with various joint damage patterns is analyzed. Results of analysis demonstrate higher damage identification capability in comparison with modal assurance criterion (MAC) method in a noise-contaminated environment. [ABSTRACT FROM AUTHOR]

Published
2005
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