A fault diagnosis expert system based on knowledge matrix

Tianshu Wang; Ren Yu; Qiao Peng; Di Wang; Xiaosen Song

doi:10.1117/12.2661211

9 December 2022 A fault diagnosis expert system based on knowledge matrix

Tianshu Wang, Ren Yu, Qiao Peng, Di Wang, Xiaosen Song

Proceedings Volume 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022); 124920I (2022) https://doi.org/10.1117/12.2661211
Event: International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 2022, Wuhan, China

Abstract

The expression of fault diagnosis expert knowledge and its reasoning method is the main content of fault diagnosis expert system design and is also an important factor that affects its performance. The traditional expression method of fault diagnosis expert knowledge is more complicated, and its reasoning machine is serial reasoning using the combined rules. When the reasoning logic becomes more complex and the number of rules grows larger, the search efficiency and reasoning speed get lower. This paper defines a new method of knowledge expression and proposes an expert knowledge expression system based on meta-propositional knowledge network model and knowledge matrix. At the same time, a parallel reasoning algorithm based on matrix operation is designed. It is convenient for the expression and storage of expert knowledge in the computer, as well as the detection of rule conflict and dead loop. Using this method can greatly improve the reasoning speed of expert system. And the number of rules grows larger, the effect gets more significant.

Citation Download Citation

Tianshu Wang, Ren Yu, Qiao Peng, Di Wang, and Xiaosen Song "A fault diagnosis expert system based on knowledge matrix", Proc. SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 124920I (9 December 2022); https://doi.org/10.1117/12.2661211

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