Analysis of temperature characteristics of high-speed train wheelset system under complex operating conditions

Abstract

With 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.

Keywords

high-speed train / dynamic model / transient temperature field / bearing fault / line data

References

[1] Tarawneh CM, Fuentes AA, Kypuros JA, Navarro LA, Vaipan AG, Wilson BM. Thermal modeling of a railroad tapered-roller bearing using finite element analysis. J Therm Sci Eng Appl. 2012;4:1-11.

[2] Xu J, Zhang JJ, Huang ZQ, Wang LP. Calculation and finite element analysis of the temperature field for high-speed rail bearing based on vibrational characteristics. J Vibroeng. 2015;17(2):720-732.

[3] Ye Z, Wang L, Chen G, Tang D. Analysis of thermo-mechanical coupling of high-speed angular-contact ball bearings. Adv Mech Eng. 2017;9(6):1687814017702812.

[4] Than VT, Wang CC, Ngo TT, Huang JH. Estimating time-varying heat sources in a high-speed spindle based on two measurement temperatures. Int J Therm Sci. 2017;111:50-65.

[5] Hadden GB, Kleckner RJ, Ragen MA, Shaberth L. Steady-state and transient thermal analysis of a shaft bearing system including ball, cylindrical and tapered roller bearing. NASA Tech Paper. 1981;254:NAS3-22690.

[6] Harris TA. Rolling Bearing Analysis. 4th ed. Wiley; 2001.

[7] Pouly F, Changenet C, Ville F, Velex P, Damiens B. Power loss predictions in high-speed rolling element bearings using thermal networks. Tribol Trans. 2010;53:957-967.

[8] Niel D, Changenet C, Ville F, Octrue M. Thermomecanical study of high speed rolling element bearing: a simplified approach. Proc Inst Mech Eng Part J J Eng Tribol. 2019;233(4):541-552.

[9] Ai S, Wang W, Wang Y, Zhao Z. Temperature rise of double-row tapered roller bearings analyzed with the thermal network method. Tribol Int. 2015;87:11-22.

[10] Gao P, Chen Y, Hou L. Nonlinear thermal behaviors of the inter-shaft bearing in a dual-rotor system subjected to the dynamic load. Nonlinear Dyn. 2020;101:191-209.

[11] Zhou C, Xing M, Wang H, Hu B. A novel thermal network model for predicting the contact temperature of spur gears. Int J Therm Sci. 2021;161:106703.

[12] Winer WO, Bair S, Gecim B. Thermal resistance of a tapered roller bearing. ASLE Trans. 1986;29(4):539-547.

[13] Bossmanns B, Tu JF. A thermal model for high-speed motorized spindles. Int J Mach Tools Manuf. 1999;39(9):1345-1366.

[14] Ma F, Li Z, Qiu S, Wu B, An Q. Transient thermal analysis of grease-lubricated spherical roller bearings. Tribol Int. 2016;93:115-123.

[15] Zheng D, Chen W. Thermal performances on angular contact ball bearing of high-speed spindle considering structural constraints under oil-air lubrication. Tribol Int. 2017;109:593-601.

[16] Yang Y, Du Z, Feng X, Yang J. Real-time thermal modelling approach of a machine tool spindle based on bond graph method. Int J Adv Manuf Technol. 2021;113:99-115.

[17] Brossier P, Niel D, Changenet C, Ville F, Belmonte J. Experimental and numerical investigations on rolling element bearing thermal behaviour. Proc Instit Mech Eng Part J: J Eng Tribol. 2021;235(4):842-853.

[18] Zheng Z, Song D, Zhang W, Zhang W, Zhao M, Lei L. Research on temperature of high-speed train axle box bearing considering lubrication state evolution and vehicle dynamics response. Veh Syst Dyn. 2023;12:1-31.

[19] Harris TA, Kotzalas MN. Advanced Concepts of Bearing Technology: Rolling Bearing Analysis. 5th ed. CRC Press; 2006.

[20] Liu Y, Wang B, Zhang B, Yang S. Establishment of dynamic model for axle box bearing of high-speed trains under variable speed conditions. Chin J Mech Eng. 2022;35(04):47.

[21] Wang B, Liu Y, Zhang B, Yang S. Development and stability analysis of a high-speed train bearing system under variable speed conditions. Int J Mech Syst Dyn. 2022;2(4):352-362.

[22] Sun Y, Li F, Lin G, Xu J, He Z. Adaptive fault-tolerant control of high-speed maglev train suspension system with partial actuator failure: design and experiments. J Zhejiang Univ Sci A. 2023;24(3):272-283.

[23] Cao H, Niu L, Xi S, Chen X. Mechanical model development of rolling bearing-rotor systems: a review. Mech Syst Signal Proc. 2018;102:37-58.

[24] Sun X, Wang T, Zhang R, Gu F, Ball AD. Numerical modelling of vibration responses of helical gears under progressive tooth wear for condition monitoring. Mathematics. 2021;9(3):213.

[25] Shi J, Zhao B, He T, Tu L, Lu X, Xu H. Tribology and dynamic characteristics of textured journal-thrust coupled bearing considering thermal and pressure coupled effects. Tribol Int. 2023;180:108292.

[26] Stein JL, Tu JF. A state-space model for monitoring thermally induced preload in anti-friction spindle bearings of high-speed machine tools. J Dyn Syst Meas Control. 1994;116:372-386.

[27] Liu Y, Wang B, Yang S, Liao Y, Guo T. Characteristic analysis of mechanical thermal coupling model for bearing rotor system of high-speed train. Appl Math Mech. 2022;43(9):1381-1398.

RIGHTS & PERMISSIONS

2024 The Author(s). International Journal of Mechanical System Dynamics published by John Wiley & Sons Australia, Ltd on behalf of Nanjing University of Science and Technology.