• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2024, Vol. 60 ›› Issue (8): 81-93.doi: 10.3901/JME.2024.08.081

• 材料科学与工程 • 上一篇    下一篇

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航空齿轮钢滚动接触疲劳性能预测与表面完整性优化

吴吉展, 魏沛堂, 吴少杰, 刘怀举, 朱才朝   

  1. 重庆大学机械传动国家重点实验室 重庆 400044
  • 收稿日期:2023-03-11 修回日期:2023-09-16 出版日期:2024-04-20 发布日期:2024-06-17
  • 作者简介:吴吉展,男,1995年出生,博士研究生。主要研究方向为齿轮抗疲劳设计制造。E-mail:1356645469@qq.com;魏沛堂(通信作者),男,1984年出生,博士,副教授,博士研究生导师。主要研究方向为抗疲劳设计制造。E-mail:peitangwei@cqu.edu.cn
  • 基金资助:
    国家重点研发计划(2022YFB3402801)和国家自然科学基金(52275050)资助项目。

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

WU Jizhan, WEI Peitang, WU Shaojie, LIU Huaiju, ZHU Caichao   

  1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044
  • Received:2023-03-11 Revised:2023-09-16 Online:2024-04-20 Published:2024-06-17

摘要: 齿轮滚动接触疲劳是限制航空、航天、新能源汽车、舰艇等高端装备的重要瓶颈。高表面完整性是决定齿轮服役性能的重要保障,表面完整性与齿轮接触疲劳性能的定量关联规律成为工程及学术界的研究重点。该系列研究讨论了常规喷丸、二次喷丸、微粒喷丸、滚磨光整、喷丸光整等加工工艺对AISI 9310渗碳淬火航空齿轮钢表面完整性参数及服役性能的影响,并给出齿轮抗疲劳设计方法。针对获得的表面完整性与疲劳性能数据,开展疲劳性能预测与表面完整性设计研究。采用随机森林算法确定了表面完整性参数对滚动接触疲劳寿命的重要度;以接触应力、表面粗糙度、表面残余应力、表面硬度、有效残余应力深度、疲劳寿命可靠度为输入,滚动接触疲劳寿命为输出,采用GA-BP神经网络和SVM机器学习方法建立了滚动接触疲劳寿命预测模型,探究了表面完整性参数对滚动接触疲劳寿命的影响规律;提出了基于多元回归的滚动接触疲劳寿命预测公式,疲劳寿命预测值在1.5倍分散带以内;并在给定设计寿命下采用遗传算法对表面完整性参数进行优化,服务于传动构件抗疲劳设计。

关键词: 滚动接触疲劳, 表面完整性, 疲劳性能, 数据驱动, 寿命预测

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

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