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Experimental investigation of the relation between the surface integrity and bending fatigue strength of carburized gears

Experimental investigation of the relation between the surface integrity and bending fatigue strength of carburized gears

作     者:CHEN DiFa ZHU JiaZan LIU HuaiJu WEI PeiTang MAO TianYu 

作者机构:State Key Laboratory of Mechanical TransmissionsChongqing UniversityChongqing 400044China China Gas Turbine EstablishmentChengdu 710025China 

出 版 物:《Science China(Technological Sciences)》 (中国科学(技术科学英文版))

年 卷 期:2023年第66卷第1期

页      面:33-46页

核心收录:

学科分类:0810[工学-信息与通信工程] 08[工学] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程(可授工学、理学学位)] 0802[工学-机械工程] 0702[理学-物理学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 080201[工学-机械制造及其自动化] 

基  金:supported by the National Key R&D Program (Grant No.2020YFB2008200) the National Science and Technology Major Project(Grant No. 2019-VII-0017-0158) 

主  题:carburized gear surface integrity bending fatigue design formula 

摘      要:Bending fatigue is an essential parameter that needs to be considered in the improvement process of the power density and reliability of gear drives. Quantitative relations among the manufacturing parameters, surface integrities, and fatigue performance are not clear, which seriously limits the effectiveness of an anti-fatigue design. For this work, tooth-bending fatigue tests of carburized gears with different surface integrities were performed using a pulsator. The effects of the manufacturing parameters and surface integrities on the gear fatigue, such as surface hardness and residual stress, were investigated. The experimental results revealed that due to the improvement of surface integrities after shot peening, the nominal bending stress number(fatigue limit) increased by 6.3%–31.1%, with an amplitude range of 39–143 MPa. A supervised learning algorithm of a random forest was implemented to determine the contribution of the surface hardness and surface residual stress to the nominal stress number. An empirical formula was proposed to predict the nominal stress number considering the surface integrities. The prediction error was less than 7.53%, as verified by several gear-bending fatigue tests. This provided theoretical support for the modern, anti-fatigue design of the gears.

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