Volume 33 Issue 01
Jan.  2007
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Liu Hongmei, Wang Shaoping, Ouyang Pingchaoet al. Fault diagnosis based on wavelet package and Elman neural network for a hydraulic pump[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(01): 67-71. (in Chinese)
Citation: Liu Hongmei, Wang Shaoping, Ouyang Pingchaoet al. Fault diagnosis based on wavelet package and Elman neural network for a hydraulic pump[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(01): 67-71. (in Chinese)

Fault diagnosis based on wavelet package and Elman neural network for a hydraulic pump

  • Received Date: 05 Jan 2006
  • Publish Date: 31 Jan 2007
  • Considering the low signal-to-noise, faint failure characteristics of hydraulic pump, and slow convergence speed and the instability of BP network , a new fault diagnosis method based on the wavelet package analysis and Elman n eural network is presented. The wavelet package analysis is adopted to eliminate the noise in the actual signals and to extract the fault characteristics. Throu gh signal decomposition and single reconfiguration with wavelet package, the noi se can be eliminated from signals to strengthen the failure signal and to extrac t fault feature in every frequency bands effectively. Energy of various frequenc y bands acting as the fault feature vector is input into the improved Elman neural n etwork to realize the mapping between the feature vector and the fault mode. The experiment results verified the effectiveness of the proposed method in the hydraulic pump faul t diagnosis.

     

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