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A Fault Diagnosis Method of the Shearer Hydraulic Heightening System Based on a Rough Set and RBF Neural Network

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  • Min Liu

    (College of Intelligent Manufacturing Engineering, Shanxi Institute of Science and Technology, Jincheng 048000, China
    College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Zhiqi Liu

    (College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Jinyuan Cui

    (College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China)

  • Yigang Kong

    (College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China)

Abstract

The hydraulic heightening system is the core component of the shearer, and its stable operation directly affects the safety and reliability of the equipment, so it is of great significance to realize an efficient and accurate fault diagnosis. This paper proposes a fault diagnosis method combining a rough set and radial basis function neural network (RS-RBFNN). Firstly, the RS is used to discretize the original fault data set and attribute reduction, remove the redundant information, and mine the implicit knowledge and potential rules. Then, the topology structure of the RBFNN is determined. The mapping relationship is established between the fault symptom and category. The fault diagnosis is carried out with Python language. Finally, the method is compared with two diagnostic methods including a back propagation neural network (BPNN) and RBFNN. The research results show that the RS-RBFNN has the highest fault diagnosis accuracy, with an average of 98.68%, which verifies the effectiveness of the proposed fault diagnosis method.

Suggested Citation

  • Min Liu & Zhiqi Liu & Jinyuan Cui & Yigang Kong, 2023. "A Fault Diagnosis Method of the Shearer Hydraulic Heightening System Based on a Rough Set and RBF Neural Network," Energies, MDPI, vol. 16(2), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:956-:d:1036014
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    References listed on IDEAS

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    1. Łukasz Bołoz & Zbigniew Rak & Jerzy Stasica, 2022. "Comparative Analysis of the Failure Rates of Shearer and Plow Systems—A Case Study," Energies, MDPI, vol. 15(17), pages 1-17, August.
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