基于样本信息聚集原理的小子样疲劳特性分析

Analysis of fatigue characteristics of small samples based on the principle of sample information aggregation

为了对小样本疲劳试验做出指导以及寻求小样本下S-N曲线最优拟合方法,对经典样本信息聚集方法进行了改进。基于不同应力水平下试样疲劳寿命概率分位点的一致性,采用数据共享与融合方法,实现不同应力水平下样本数据信息聚集应用。根据应力-疲劳寿命的线性关系,利用改进后的样本信息聚集方法,对小样本数据中各个应力水平下的疲劳寿命均值进行参数化逐步搜索,得到不同应力水平下疲劳寿命最优值,然后根据最小二乘法拟合出S-N曲线。对不同应力水平作为基准进行了S-N曲线的疲劳特性对比分析,算例结果表明,以低应力水平为基准结合改进后的方法拟合出的曲线与传统成组法拟合结果最大相对误差不到5%,预测出的疲劳寿命误差范围最小。由此可见,改进后的方法提高了小样本疲劳特性分析的可靠性。

In order to guide the fatigue test of small samples and find the best fitting method of S-N curve under small samples,an improved classical sample information aggregation method is proposed.Based on the consistency of the fatigue life probability quantiles of the specimens under different stress levels,data sharing and fusion methods are adopted to realize the application of sample data information aggregation under different stress levels.According to the linear relationship between stress and fatigue life,the improved sample information aggregation method is used to parameterize and gradually search the average fatigue life under each stress level in the small sample data to obtain the optimal value of fatigue life under different stress levels.The least squares method is used to fit the S-N curve.The fatigue characteristics of the S-N curve are compared and analyzed with different stress levels as the benchmark.The comparison and analysis results show that the maximum relative error of the curves fitted with the improved method and the traditional group method is less than 5%,and the range of predicted fatigue life error is the smallest,which shows that the improved method promotes the reliability of fatigue analysis of small samples.