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计算机工程 ›› 2007, Vol. 33 ›› Issue (08): 199-200,. doi: 10.3969/j.issn.1000-3428.2007.08.070

• 人工智能及识别技术 • 上一篇    下一篇

基于BP神经网络与专家系统的故障诊断系统

巩文科1,李心广1,赵 洁2   

  1. (1. 广东外语外贸大学信息科学技术学院,广州 510006;2. 广东药学院医药信息工程学院,广州 510006)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-04-20 发布日期:2007-04-20

Fault Diagnosis System Based on BP Neural Network and Expert System

GONG Wenke 1, LI Xinguang 1, ZHAO Jie 2   

  1. (1. School of Computer Science & Technology, Guangdong University of Foreign Studies, Guangzhou 510006; 2. College of Pharmaceutical Information Engineering, Guangdong Pharmaceutical University, Guangzhou 510006)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-04-20 Published:2007-04-20

摘要: 针对目前国内油田压缩机故障诊断存在的效率低、自动化程度不高的问题,设计了一种基于BP神经网络和专家系统的油田压缩机故障诊断系统,利用专家先验知识和神经网络的数值推理、自学习能力,对油田压缩机的故障进行分析处理,与以往油田压缩机故障诊断方法相比,该系统自动化程度高,诊断可靠准确。

关键词: 专家系统, 神经网络, 故障诊断

Abstract: The fault diagnosis for oil field compressor is not efficienct and not automatic, so a type of fault diagnosis system for oil field compressor is designed, the system is constructed by an expert system and a BP neural network, the expert knowledge and the numeric reasoning capacity of the neural network are applied to analyze the compressor fault. Contrast to the old method, the system is automatic and diagnosises accurately and credibly.

Key words: Expert system, Neural network, Fault diagnosis

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