摘要
42CrMo属于超高强度钢,其具备较高的强度,材料淬透性能好,淬火后的变形量小,大量地应用于牵引用的大齿轮、承压主轴、连杆等传动件材料,弯曲疲劳试验对齿轮疲劳寿命预测具有重要意义。首先,通过齿轮弯曲疲劳试验,获得了应力比R=0.1时交变载荷作用下的齿轮弯曲疲劳试验数据,得到了齿轮弯曲疲劳强度P-S-N曲线和拟合曲线关系式,以及不同可靠度下齿轮所能承受弯曲的疲劳极限值。随后,采用有限元方法对齿轮弯曲疲劳试验进行了数值模拟,得到了齿轮齿根处的静力学强度和理论计算值对比,分析表明数值模拟所得结果与理论分析结果基本一致,可以作为弯曲疲劳试验疲劳寿命仿真的基础。最后,通过弯曲疲劳寿命试验试验值与数值模拟结果对比,结果表明,疲劳寿命试验值与可靠度在84.1%时数值模拟得到的弯曲疲劳寿命基本一致,验证了数值模拟的准确性,因此能够有效预测42CrMo齿轮的弯曲疲劳寿命。
42CrMo is a kind of ultra-high strength steel,which has high strength,good hardenability and small deformation after quenching.It is widely used in driving materials such as large gears,bearing spindle and connecting rod used in traction.Bending fatigue test is of great significance for fatigue life prediction of gears.First of all,the bending fatigue test data of gear under alternating load at stress ratio R=0.1 were obtained,the P-S-N curve of gear bending fatigue strength and the fitting curve relation were obtained,and the fatigue limit value of gear under different reliability was obtained.Then the finite element method was used to simulate the bending fatigue test of gear.The static strength at the root of the gear tooth is compared with the theoretical value,and the analysis shows that the numerical simulation results are basically consistent with the theoretical analysis results,which can be used as the basis of fatigue life simulation of bending fatigue test.Finally,the experimental values of the bending fatigue life test are compared with the numerical simulation results.The results show that the fatigue life test values are basically consistent with the numerical simulation results when the reliability is 84.1%,which verifies the accuracy of the numerical simulation and can effectively predict the bending fatigue life of 42CrMo gear.
作者
王嘉军
裴未迟
纪宏超
龙海洋
王志涛
WANG JiaJun;PEI WeiChi;JI HongChao;LONG HaiYang;WANG ZhiTao(College of Mechanical Engineering,North China University of Technology,Tangshan 063210,China)
出处
《机械强度》
CAS
CSCD
北大核心
2023年第2期474-480,共7页
Journal of Mechanical Strength
基金
河北省高等学校科学技术研究项目(QN2019203)
唐山市科技创新团队培养计划项目(18130216A,20130204D)
唐山市科技重大专项(19140203F)资助。
