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Research on Fault Diagnosis Expert System Based on Neural Network

Abstract— Aiming at the singleness and inexperience of expert system in fault diagnosis field, this paper puts forward a method of applying neural network to fault diagnosis expert system. This method introduces the overall framework, reasoning mechanism and implementation method of fault diagnosis expert system based on neural network, and focuses on analyzing the functional requirements of the expert system, the implementation methods of main functional modules, the design criteria of knowledge base and the reasoning mechanism of the system. The method of expert system has some problems in fault diagnosis, such as difficulty in obtaining diagnosis experience and insufficient reasoning. The learning function, associative memory function and distributed parallel information processing function of neural network are used to solve the problems of knowledge representation, acquisition and parallel reasoning in expert

Index Terms— neural network, fault diagnosis, expert system, knowledge base.

Xiaomin Xie, Yong Zeng, Changkai Li
Institute of Electronic Communication Engineering, Anhui Xinhua University, CHINA
Fan Zhang
Research Department, Anhui Xinhua University, CHINA

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Cite: Xiaomin Xie, Fan Zhang, Yong Zeng, Changkai Li, "Research on Fault Diagnosis Expert System Based on Neural Network," Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, pp. 166-170, Bangkok, 28-30 June, 2018.