The New Fault Diagnosis Method of Wavelet Packet Neural Network on Pump Valves of Reciprocating Pumps

被引：2

作者：

Duan Yu-bo ^{[1
]}

Wang Xing-zhu ^{[1
]}

Han Xue-song ^{[1
]}

机构：

[1] Daqing Petr Inst, Coll Elect & Informat Engn, Daqing 163318, Peoples R China

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

关键词：

Reciprocating Pumps; Pressure Signal; Wavelet Packet; Neural Network; Fault Diagnosis;

D O I：

10.1109/CCDC.2009.5192650

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：3285 / 3288

页数：4