基于神经网络与蒙特卡洛方法的疲劳寿命可靠性分析

Fatigue Life Prediction and Reliability Analysis Based on the Neural Network and Monte Carlo Method

摘要:

通过加速腐蚀试验以及疲劳试验数据,对腐蚀损伤表征因子(腐蚀坑最大宽度、腐蚀坑最大深度、点蚀率)进行统计分析,应用神经网络和蒙特卡洛法对6A02铝合金试验件的疲劳寿命进行可靠性分析,分析结果与实验结果的相对误差在工程上可以接受。

Abstract:

In this paper, the distribution of the corrosion damage characterization factors was analyzed through the accelerated corrosion test and fatigue test date. The methods of application of neural network and Monte Carlo in material fatigue life prediction and reliability analysis provided a reference for an engineering problem result from the randomicity in corrosion fatigue of high strength aluminum alloy. The relative error between the analysis results and the experimental results could be accepted in the project.