Rolling Contact Fatigue Performance Prediction and Surface Integrity Optimization of Aviation Gear Steel

doi:10.3901/JME.2024.08.081

Abstract

Abstract: Rolling contact fatigue of gear is an important bottleneck for high-end equipment such as aviation, aerospace, new energy vehicles and ships. High surface integrity is an vital guarantee to determine the service performance of gears, and the quantitative correlation between surface integrity and gear contact fatigue performance has become a research focus in engineering and academia. In this work, the effects of conventional shot peening, double shot peening, fine particle peening, barrel finishing, barrel finishing after shot peening, etc., on the surface integrity and service properties of AISI 9310 carburized and quenched aviation gear steel are discussed, and it is expected to give an anti-fatigue design method. It is the third part of this series of research. Based on the obtained surface integrity and fatigue performance data, the research on fatigue property prediction and surface integrity design are carried out. The importance of surface integrity parameters to rolling contact fatigue life is determined by random forest algorithm. Taking the contact stress, surface roughness, surface residual stress, surface hardness, effective residual stress depth and fatigue life reliability as input and rolling contact fatigue life as output, the rolling contact fatigue life prediction model is established using GA-BP neural network and SVM machine learning methods. The influence of surface integrity parameters on rolling contact fatigue life is explored. The prediction formula of rolling contact fatigue life based on multiple regression is proposed. The predicted fatigue life is within 1.5 times dispersion band. Genetic algorithm is used to optimize the surface integrity parameters under a given design life, which serves the anti-fatigue design of transmission components.

Key words: rolling contact fatigue, surface integrity, fatigue performance, data-driven, life prediction

CLC Number:

TG156

WU Jizhan, WEI Peitang, WU Shaojie, LIU Huaiju, ZHU Caichao. Rolling Contact Fatigue Performance Prediction and Surface Integrity Optimization of Aviation Gear Steel[J]. Journal of Mechanical Engineering, 2024, 60(8): 81-93.

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