Abstract
In this paper, a Simulation Research on Fault Diagnosis of CNC Machine Tools Based on Fuzzy Petri Net is proposed. According to the fault information of the CNC machine tool electrical system, the Petri net and fuzzy reasoning are combined to establish the fuzzy Petri net model of the CNC machine tool electrical system. Describes the relationship between CNC machine faults. The fuzzy generation rule is represented by FPN. The fault diagnosis rule of Petri net is used for fault diagnosis reasoning. A fuzzy Petri net model combining reverse reasoning and forward excitation is proposed to analyze the causal relationship between abnormal behavior processes. Combining the feasibility of the occurrence relationship between faults and the frequency of faults, reverse reasoning and forward excitation can accurately and quickly find the root cause of the fault, and can find the fault cause more quickly than the traditional fault diagnosis method. The maintenance time is reduced. The fault diagnosis of the electrical system of CNC machine tools is taken as an example. The diagnostic model based on fuzzy Petri net is established. The correctness of the model and the effectiveness of the algorithm are verified by simulation analysis. Improve the usability of CNC machine tools.
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Lu, N., Xu, B., Chen, Z., Ren, D., Yang, Y., Bian, P. (2020). Simulation Research on Fault Diagnosis of CNC Machine Tools Based on Fuzzy Petri Net. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2019 Chinese Intelligent Systems Conference. CISC 2019. Lecture Notes in Electrical Engineering, vol 593. Springer, Singapore. https://doi.org/10.1007/978-981-32-9686-2_6
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DOI: https://doi.org/10.1007/978-981-32-9686-2_6
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