期刊
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷 24, 期 1, 页码 87-92出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2010.08.011
关键词
Wavelet packet decomposition; Frequency band energy; Neural network; Feature fusion; Damage diagnosis
类别
资金
- Natural Science Foundation of Shaanxi Province [2005E205]
A structure damage diagnosis method combining the wavelet packet decomposition, multi-sensor feature fusion theory and neural network pattern classification was presented. Firstly, vibration signals gathered from sensors were decomposed using orthogonal wavelet. Secondly, the relative energy of decomposed frequency band was calculated. Thirdly, the input feature vectors of neural network classifier were built by fusing wavelet packet relative energy distribution of these sensors. Finally, with the trained classifier, damage diagnosis and assessment was realized. The result indicates that, a much more precise and reliable diagnosis information is obtained and the diagnosis accuracy is improved as well. (C) 2010 Elsevier Ltd. All rights reserved.
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