Volume 50 Issue 8
Aug.  2024
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ZHANG Wenhao, WU Juan, RUAN Kaiyi. Structural performance monitoring of mine hoist head sheave based on digital twins[J]. Journal of Mine Automation，2024，50（8）：69-75.  doi: 10.13272/j.issn.1671-251x.2024050086
Citation: ZHANG Wenhao, WU Juan, RUAN Kaiyi. Structural performance monitoring of mine hoist head sheave based on digital twins[J]. Journal of Mine Automation，2024，50（8）：69-75.  doi: 10.13272/j.issn.1671-251x.2024050086
shu

Structural performance monitoring of mine hoist head sheave based on digital twins

doi: 10.13272/j.issn.1671-251x.2024050086
  • 1.

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

  • 2.

    Shanxi Mine Fluid Control Engineering Laboratory, Taiyuan University of Technology, Taiyuan 030024, China

  • 3.

    National-local Joint Engineering Laboratory of Mining Fluid Control, Taiyuan University of Technology, Taiyuan 030024, China

  • 4.

    School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China

  • Received Date: 2024-05-30
  • Rev Recd Date: 2024-08-11
    • Available Online: 2024-08-02
    Abstract
  • Currently, most of the monitoring research on the head sheave of mine hoists focuses on monitoring the vibration, temperature, and deflection of the head sheave, while there is relatively little research on monitoring the structural performance of the head sheave. In order to solve the above problems, a structural performance monitoring method of mine hoist head sheave based on digital twins is proposed. Based on the actual conditions during the operation of the mine hoist head sheave, a digital twin monitoring system for the mine hoist head sheave is designed. The system consists of an object entity layer, a twin model layer, a twin data layer, an application layer, and connections between each layer. The predicted data in the twin data layer is the real-time head sheave structural performance data predicted by the head sheave structural performance prediction model during the operation of the mine hoist head sheave, including stress and strain data. The structural performance prediction model of the mine hoist head sheave is constructed using a combined surrogate model. A single surrogate model of radial basis function (RBF) is trained using processed finite element data. The weight of the single surrogate model in the combined surrogate model is obtained based on generalized mean square error, thus obtaining the head sheave structural performance prediction model. Taking the five rope friction lifting system of the vertical shaft as the experimental object, based on the Unity3D platform, a digital twin monitoring system for the mine hoist head sheave is established through the construction of virtual space, data transmission, and application modules. The experimental results show that during the operation of the head sheave, the average determination coefficient of the measured strain and predicted strain at the four test points is 0.973 98, indicating a high correlation between the predicted strain and the measured strain. This verifies that the designed prediction model can meet the needs of monitoring the structural performance of the head sheave.

     

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