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Fault diagnosis for reciprocating pump with wavelet neural network.

Yang Qijun( University of Petroleum, Dongying City, Shandong Province ), Sun Hui, Pei Junfeng. , 1999, 27(10): 17~20  
Wavelet analysis, a new technique for signal processing, possesses excellent characteristic of time frequency location and is suitable for analyzing the time varying or transient signals. The authors offer an approach to the feature extraction of reciprocating pumps, and establish a wavelet packet neural network fault diagnosis model of reciprocating pumps, which can carry out signal measuring and fault classification by means of feature extraction of wavelet packat analysis and nonlinear mapping of neural network. Based on this model, a fault identification software system of reciprocating pumps is developed. Diagnosis of faults of fluid end on a reciprocating pump proves the software system being capable of making accurate identification of various kinds of faults with less feature variables.
【CateGory Index】: TE933
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