极小子样下基于GM-Bootstrap方法的装载机驱动桥可靠性评估

Reliability Evaluation of Loader Drive Axle Based on GM-Bootstrap Method Under Extreme Small Samples

装载机驱动桥作为大型复杂结构件,进行足尺疲劳试验成本高且子样数少,无法满足经典统计方法样本容量的要求。为此,提出一种针对极小子样试验的GM-Bootstrap组合评估方法。先利用GM预测模型对小子样试验的试验样本进行扩充,再采用Bootstrap方法对扩充后的样本进行评估,得到未知参数的估计。通过GM-Bootstrap方法对装载机驱动桥可靠性评估结果与半经验法的结果对比,验证了该方法的可行性和评估结果的可靠性,为成本昂贵的大型复杂结构件的可靠性评估问题提供了一种新的途径。

As a large scale complicated structural component, it is difficult to do full-scale-fatigue test on the loader driving axle due to high cost, so the extreme small sample size can hardly meet the statistical requirements of traditional methods. In this paper, a GM-Bootstrap combined method was proposed to estimate the extremely small scale sample fatigue test. First, the sample size was expanded by using the GM prediction model, and then Bootstrap method was used to evaluate the fatigue reliability of the expanded sample. The reliability evaluation of loader drive axle was conducted by the proposed method and semi empirical method. The results verify the feasibility and reliability of the proposed method. Moreover, it provides a new way for reliability evaluation of high cost large scale complicated structural component.