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A novel cause analysis approach of grey reasoning Petri net based on matrix operations

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Abstract

Cause analysis makes great contributions to identifying the priorities of the causes in fault diagnosis system. A fuzzy Petri net (FPN) is a preferable model for knowledge representation and reasoning and has become an effective fault diagnosis tool. However, the existing FPN has some limitations in cause analysis. It is criticized for the inability to fully consider incomplete and unknown knowledge in uncertain situations. In this paper, an enhanced grey reasoning Petri net (EGRPN) based on matrix operations is presented to address the limitations and improves the flexibility of the existing FPN. The proposed EGRPN model uses grey numbers to handle the greyness and inaccuracy of uncertain knowledge. Then, the EGRPN inference algorithm is executed based on the matrix operations, which can express the relevance of uncertain events in the form of grey numbers and improve the reliability of the knowledge reasoning process. Finally, industrial examples of cause diagnosis are used to illustrate the feasibility and reliability of the EGRPN model. The experimental results show that the new EGRPN model is promising for cause analysis.

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Acknowledgements

This project is partly supported by the National Natural Science Foundation of China (Grant Nos. 61725306, 61751312, 61773405 and 61533020), the Fundamental Research Funds for the Central Universities of Central South University (2019zzts063), and the Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan, China under the Grant No. MADT0F2019B01.

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Authors and Affiliations

  1. School of Automation, Central South University, Changsha, 410083, China

    Li Li, Yongfang Xie, Lihui Cen & Zhaohui Zeng

  2. Peng Cheng Laboratory, Shenzhen, 518000, China

    Li Li

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  1. Li Li
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Correspondence to Lihui Cen.

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Li, L., Xie, Y., Cen, L. et al. A novel cause analysis approach of grey reasoning Petri net based on matrix operations. Appl Intell 52, 1–18 (2022). https://doi.org/10.1007/s10489-021-02377-4

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