中国机械工程

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基于焊缝品质参数区间模型的疲劳寿命预测方法

安兴强1;谷正气1,2;马骁骙1;张沙1;米承继3   

  1. 1.湖南大学汽车车身先进设计制造国家重点实验室,长沙,410082
    2.湖南文理学院,常德,415000 
    3.湖南工业大学机械工程学院,株洲,412007
  • 出版日期:2017-11-10 发布日期:2017-11-07
  • 基金资助:
    国家高技术研究发展计划(863计划)资助项目(2012AA041805);
    中央财政支撑地方高校发展专项资金资助项目(0420036017);
    汽车车身先进设计与制造国家重点实验室自主课题(734215002)
    National High Technology Research and Development Program of China (863 Program)(No. 2012AA041805)

Fatigue Life Prediction Method Based on Weld Quality Parameter Interval Model

AN Xingqiang1;GU Zhengqi1,2;MA Xiaokui1;ZHANG Sha1;MI Chengji3   

  1. 1.State Key Laboratory of Advanced Design and Manufacture for Vehicle Body,Hunan University,Changsha,410082 
    2.Hunan University of Arts and Science,Changde,Hunan,415000
    3.College of Mechanical Engineering,Hunan University of Technology,Zhuzhou,Hunan,412007
  • Online:2017-11-10 Published:2017-11-07
  • Supported by:
    National High Technology Research and Development Program of China (863 Program)(No. 2012AA041805)

摘要:

疲劳寿命预测中,焊缝品质参数如材料弹性模量E、疲劳强度系数σ'f和指数b、疲劳延性系数ε'f和指数c往往存在不确定性。运用随机-遗传算法对焊缝品质参数进行区间估计,并结合Manson-Coffin公式构建上述不确定因素的区间模型,提出了一种疲劳寿命区间预测方法。首先,在双轴疲劳试验机上进行了基于应变控制的焊接试件疲劳寿命试验。其次,针对疲劳寿命试验数据,运用随机-遗传算法构建了焊缝品质参数区间求解模型,并结合Manson-Coffin公式建立了疲劳寿命区间预测模型。最后通过模型预测数据与试验数据对比证实了预测模型的精确性以及考虑焊缝品质参数不确定性的合理性。

关键词: 随机-遗传算法, 焊缝品质参数, 疲劳寿命区间预测, 区间不确定性

Abstract: Weld quality parameter—elastic modulus E, fatigue strength coefficient σ'f and exponent b, fatigue ductility coefficient ε'f and exponent c were always of uncertainty in fatigue life prediction. A method of fatigue life prediction was proposed by interval model which combined random-GA method with Manson-Coffin formula. Firstly, the fatigue life tests of welding specimen were carried out on biaxial fatigue testing machines based on strain control. Then , for fatigue life test data, fatigue life interval prediction method was constructed by combining weld quality parameter interval solving model which was constructed by random-GA method with Manson-Coffin formula. Finally, the accuracy of this method and the rationality of considering the uncertainty of weld quality parameters were verified by the comparisons between the interval model predictive data and fatigue life test data.

Key words: random-genetic algorithm(GA), weld quality parameter, fatigue life interval prediction, interval uncertainty

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