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Semigroup of fuzzy automata and its application for fast accurate fault diagnosis on machine and anti-fatigue control

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Abstract

In order to carry out machine fault diagnosis earlier and more accurately such as the automatic detection for the ship’s level scale, and the existing literatures didn’t discuss these until now. However, for solving the problem, this paper presents a semigroup of fuzzy automata and its properties, constructs a fuzzy inference system on the semigroup of fuzzy automata, and discusses its application on machine fault diagnosis and the anti-fatigue driving reminder device. At the same time, the comparison between this inference model and the existing diagnosis methods is discussed. The experimental results show that the diagnosis speed and the average precision of the proposed inference model are faster and higher than those of traditional methods, which their maximum diagnosis precision is 95.98%.

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Acknowledgements

This work is supported by Center Plain Science and Technology Innovation Talents (194200510016); Science and Technology Innovation Team Project of Henan Province University (19IRTSTHN013); Zhengzhou Science and Technology Innovation Talents (192101059006); National Natural Science Foundation of China (61973104, U1604151); Key Science and Technology Program of Henan Province (172102310447), respectively.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Qing E Wu, Mengke Guang & Hu Chen

  2. Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou, 450001, China

    Lijun Sun

  3. Zhengzhou Key Laboratory of Machine Perception and Intelligent System, Henan University of Technology, Zhengzhou, 450001, China

    Lijun Sun

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  1. Qing E Wu
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  2. Mengke Guang
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  3. Hu Chen
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  4. Lijun Sun
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Correspondence to Qing E Wu or Lijun Sun.

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Wu, Q.E., Guang, M., Chen, H. et al. Semigroup of fuzzy automata and its application for fast accurate fault diagnosis on machine and anti-fatigue control. Appl Intell 50, 1542–1557 (2020). https://doi.org/10.1007/s10489-019-01611-4

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