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A New State Assessment Method for Hydrodynamic Journal Bearings under Different Assembly Characteristics

Author

Listed:
  • Hong Lu

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Jiashun Dai

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Qi Liu

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Jiangnuo Mei

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Jiji He

    (School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China)

Abstract

As the transmission component in mechanical systems, hydrodynamic journal bearing is widely used in large electromechanical equipment. The instability of the hydrodynamic journal bearing often results in mechanical wear and damage, which may cause maintenance shutdowns and significant financial losses. Accordingly, assessing the hydrodynamic journal bearing online is a highly effective approach to guaranteeing reliability. To analyze oil film thickness distribution under various assembly characteristics, this paper proposes a Fluid–Solid coupling analysis method based on hydrodynamic lubrication theory and Hertzian elastic deformation theory. The novelty is that the difference between the oil film thicknesses at the same measuring angle within the two opposing faces of the bearing shell is taken as the assessment parameter, which can directly indicate the deviation degree of the stator axis. Comparison of simulation and experimental results validated that the proposed method exhibits exceptional accuracy in practical applications.

Suggested Citation

  • Hong Lu & Jiashun Dai & Qi Liu & Jiangnuo Mei & Jiji He, 2024. "A New State Assessment Method for Hydrodynamic Journal Bearings under Different Assembly Characteristics," Mathematics, MDPI, vol. 12(15), pages 1-21, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2400-:d:1447849
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