Rapid prediction of brake disc temperature of high-speed train based on back propagation neural network

Mingchen Xia; Jianyong Zuo; Xueping Wang

doi:10.1117/12.2689489

7 September 2023 Rapid prediction of brake disc temperature of high-speed train based on back propagation neural network

Mingchen Xia, Jianyong Zuo, Xueping Wang

Author Affiliations +

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127906I (2023) https://doi.org/10.1117/12.2689489
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

Due to the time-consuming shortcomings of the current brake disc temperature prediction method, this paper studies the rapid prediction method of the maximum temperature of the brake disc based on BP neural network. The finite element model of the brake disc is constructed by using ANSYS software, and the error between the simulation results of the finite element model and the test results is verified to be less than 5%, which verifies the accuracy of the simulation model. Based on the simulation data of the finite element model, a BP neural network temperature prediction model is constructed to realize rapid prediction of the maximum temperature of the brake disc. The results show that using the trained neural network model to predict multiple sets of test samples, the maximum relative error is about 1%, and the average relative error is only 0.6%. The model shows a good prediction effect.

Citation Download Citation

Mingchen Xia, Jianyong Zuo, and Xueping Wang "Rapid prediction of brake disc temperature of high-speed train based on back propagation neural network", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127906I (7 September 2023); https://doi.org/10.1117/12.2689489

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