Fault Diagnosis Method for Nuclear Power Plants Based on Integrated Neural Networks and Logical Fusion

摘要：

　　A new fault diagnosis method based on integrated neural networks (INNs) and logical fusion for nuclear power plants (NPPs) is presented to improve the reliability of fault diagnosis.In this method, multiple neural networks that the types of neural networks are different were applied to the fault diagnosis of NPP simultaneously.The logical fusion method was employed to fuse the diagnosing results of different neural networks.The final results of fault diagnosis for NPP are obtained from the results of logical fusion.The typical operation patterns of NPP are diagnosed to demonstrate the effectivity of the proposed method.The comparison between the methods of logical and D-S evidence theory fusion was implemented.The results reveal that employing the proposed method can improve the reliability of fault diagnosis results over the diagnosis method based on single neural network; the method of logical fusion is a simple, convenient and fast fusion method and suit for the fusion of multiple variables comparing with D-S evidence theory.

关键词： nuclear power plant integrated neural networks logical fusion fault diagnosis

作者: Zhou Gang Han Long Yang Li

作者单位: College of Power Engineering,Naval University of Engineering Wuhan 430033,China

会议类型: 国际会议

会议名称: 2013 IEEE 11th International Conference on Electronic Measurement & Instruments(第十一届IEEE国际电子测量与仪器学术会议)

会议地点: 哈尔滨

会议语种:英文

页码: 857-861

在线出版日期: 2013-08-16（万方平台首次上网日期，不代表论文的发表时间）