Affiliation:
1. School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang China
2. Hebei Key Laboratory of Mechanical Power and Transmission Control Shijiazhuang Tiedao University Shijiazhuang China
3. School of Civil Engineering Shijiazhuang Tiedao University Shijiazhuang China
4. Taiyuan Vehicle Depot, Daqin Railway Co., Ltd. Taiyuan China
Abstract
AbstractWith the rapid advancements in high‐speed train technology, the importance of ensuring the safety of train operations has become paramount. Bearings, being a critical component of train bogies, have garnered significant attention for their role in maintaining safety standards. Monitoring the temperature of bearings to evaluate their motion state is a common practice in high‐speed trains, emphasizing the need for further research into temperature fluctuations. In this study, a dynamic model is developed for the bearing rotor system of high‐speed trains. By considering the contact points between raceways and rolling elements, the power loss in the bearing is obtained and a transient temperature‐field model of the system is established. The relationship between node temperature and factors such as ambient temperature, train running speed, and load is illustrated, with a detailed presentation of the influence of bearing fault type and size on node temperature. The analysis results reveal that the node temperature increases with higher values corresponding to those quantifiable factors and is most affected by rolling element fault. Additionally, it is observed that the temperature rises rapidly in the initial stage and gradually flattens out over time. The comparative analysis of temperature under different fault conditions shows that the node temperature is most affected by the rolling element fault. Experiments and actual line temperature data are used to verify the validity of the model. The comparison results show that the simulation aligns well with experimental and line data. The transient temperature‐field model of the bearing rotor system in high‐speed trains can effectively simulate and predict the temperature change process of each node of the system. The simulation results hold certain theoretical guiding significance for further research and practical applications in ensuring train operation safety.
Funder
National Natural Science Foundation of China
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