Non-stationary signal combined analysis based fault diagnosis method |
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Authors: | Zhe CHEN Yuqi HU Shiqing TIAN Huimin LU Lizhong XU |
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Affiliation: | 1. College of Computer and Information Engineering,Hohai University,Nanjing 211100,China;2. School of Engineering,Kyushu Institute of Technology,Kyushu 804-8550,Japan |
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Abstract: | Considering the complementarity between the deep learning,spectrum and time frequency analysis methods,a multi-stream framework was designed by combining the convolutional network,Fourier transform and wavelet package decomposition methods,with the aim to analyze the non-stationary signal.Accordingly,a none-stationary signal combined analysis based fault diagnosis method was proposed to extract features in difference aspects.The fault diagnosis experiments demonstrate that the combined analysis method can efficiently and stably depict the fault and significantly improve the performance of fault diagnosis. |
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Keywords: | none-stationary signal fault diagnosis signal processing deep learning feature fusion |
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