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- W2354528728 abstract "Aiming at the questions of pump-jack fault diagnosis method backward and diagnosis information lack of, it is proposed a kind of wavelet transform based neural network fault diagnosis system. The system first performs discrete wavelet transform for input signals and treats the multi-scale discrete detail signals achieved by Mallat arithmetic as fault characters. Then the transformed signals are sent to the neural network to classify the fault modes. In order to raise the correct rate of fault diagnosis, on one hand the structure of the neural network is optimized, and on the other hand conjugated gradient method is used with learning rate self-adjusting to train the network weight values. In the practice, the system is used to diagnose up to 32 fault pump-jacks, and the correct rate of diagnosis is above 95%. The results show that the proposed scheme is very effective." @default.
- W2354528728 created "2016-06-24" @default.
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- W2354528728 date "2005-01-01" @default.
- W2354528728 modified "2023-09-24" @default.
- W2354528728 title "Wavelet Transform Base Neural Network Fault Diagnosis System and Its Application" @default.
- W2354528728 hasPublicationYear "2005" @default.
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