基于Gamma过程的金属材料剩余强度退化模型

兰州理工大学学报 ›› 2022, Vol. 48 ›› Issue (4): 36-42.

基于Gamma过程的金属材料剩余强度退化模型

韦尧兵^*, 赵成, 张震, 刘俭辉

兰州理工大学机电工程学院, 甘肃兰州 730050

收稿日期:2021-06-07 出版日期:2022-08-28 发布日期:2022-10-09
通讯作者: 韦尧兵(1965-),男,甘肃靖远人,研究员.Email:ybwei0730@163.com
基金资助:
国家自然科学基金青年基金(51605212),甘肃省自然科学基金(20JR10RA161)

Residual strength degradation model of metal material based on gamma process

WEI Yao-bing, ZHAO Cheng, ZHANG Zhen, LIU Jian-hui

School of Mechanical and Electronical Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China

Received:2021-06-07 Online:2022-08-28 Published:2022-10-09

摘要/Abstract

摘要： 针对多级载荷作用下零件剩余强度未考虑加载次序的问题,基于Schaff模型,引入载荷次序影响因子,对Schaff模型进行修正,建立考虑载荷加载次序影响的等损伤比剩余强度预估模型.借助Gamma函数的形状参数和尺寸参数对零件的强度退化过程进行描述.采用45^#钢和30CrMnSiA的疲劳试验数据验证模型的准确性.结果表明:修正的等损伤比剩余强度模型预测精度要优于Schaff模型,且Gamma过程与零部件强度退化过程相吻合.

关键词: 多级载荷, 等损伤比, 剩余强度, 强度退化, Gamma过程

Abstract: Aiming at the problem of the residual strength of parts under multi-level loading not considering the loading sequence, the Schaff model is revised by introducing the loading sequence influence factor based on the Schaff model, and an equal damage ratio residual strength prediction model considering the effect of the loading sequence is established. With the aid of the shape parameter and size parameter of the Gamma function, the strength degradation process of the part is described. The fatigue test data of 45^# steel and 30CrMnSiA are used to verify the accuracy of the model. The results show that the prediction accuracy of the modified equal damage ratio residual strength model is better than that of the Schaff model, and the Gamma process is consistent with the strength degradation process of the parts.

Key words: multi-level loading, equal damage ratio, residual strength, strength degradation, Gamma process

中图分类号:

TB114.3

韦尧兵, 赵成, 张震, 刘俭辉. 基于Gamma过程的金属材料剩余强度退化模型[J]. 兰州理工大学学报, 2022, 48(4): 36-42.

WEI Yao-bing, ZHAO Cheng, ZHANG Zhen, LIU Jian-hui. Residual strength degradation model of metal material based on gamma process[J]. Journal of Lanzhou University of Technology, 2022, 48(4): 36-42.

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