The new fault diagnosis method of wavelet packet neural network on pump valves of reciprocating pumps

Two key issues of fault diagnosis for the pump valves of reciprocating pump are extracting the fault feature information of nonstationary time variation process efficiently from system feature signals and classifying the faults feature correctly. A new method of fault feature is proposed by ordinary pressure signal (pressure in pump cylinder) as system feature signals. A diagnosis method based on “frequency-energy-fault identification” pattern recognition diagnosis approach is introduced to the fault detection on pump valves of reciprocating pumps. The improved BP neural network is used to diagnose various faults of pump valves by the feature vectors constructed above. This approach deals with the primitive pressure signal simply and acquires fault feature vectors easily. And the pressures in different valve boxes have no influence each other.