Optimisation of hardness profiles in high-speed train axlebox bearings

Abstract

To produce bearings with more reasonable hardness profiles, a finite element model was established to simulate different heat treatment processes. Based on the simulated hardness profiles, an artificial neural network model was established to fit the relationship between the heat treatment process parameters and the hardness profiles. Genetic algorithm was used to optimise the hardness profiles and the confirmation test was conducted. The results showed that the optimised hardness profile was closer to the optimisation target. The mean absolute error of hardness was reduced by 68.16% and the root mean square error was reduced by 66.72% after optimisation. This method can be used for hardness profile optimisation and provides a reference for the optimisation of the bearing heat treatment process.

KEYWORDS:

• Hardness profiles
• G20CrNi2MoA
• carburised bearings
• artificial neural network
• genetic algorithm

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Development Project of China Railway [grant number N2022J017], the Fund of China Academy of Railway Sciences Corporation Limited [grant number 2022YJ161].