Weibull分布下绕线联轴器双应力加速寿命试验研究

针对绕线联轴器具有较长的工作寿命，其可靠性很难快速评定的问题，采用恒加试验方法，进行了绕线联轴器双应力加速寿命试验及其失效寿命数据的统计分析；在加速寿命试验中，通过对绕线联轴器的失效机理进行分析，确定了加速应力及加速模型，采用Escobar-Meeker（E-M）法确定了加速寿命试验的条件矩阵；失效寿命数据的统计分析中，假设绕线联轴器的寿命服从威布尔分布，利用威布尔概率纸检验和巴特利特检验相结合的方式对绕线联轴器的寿命分布进行检验；利用极大似然估计法（MLE）和最佳线性无偏估计法（BLUE）确定分布模型的形状参数和特征寿命，并对参数估计方法进行了分析比较；对绕线联轴器双应力恒加试验数据的统计分析表明：绕线联轴器的寿命可用双应力逆幂律-Weibull精确描述，获得了加速应力-寿命模型，某型绕线联轴器在正常转速水平1000r／min，正常扭矩水平0.6Nm下可靠性指标的最佳线性无偏估计。

Research on Double Stress Accelerated Life Test of Winding Coupling under Weibull Distribution

The winding coupling has a long working life, but it is difficult to quickly assess its reliability. To solve the above problem,the double stress accelerated life test and the statistical analysis of the failure life data of the winding coupling were carried out by the method of constant accelerated life test. In the accelerated life test, through the analysis of the failure mechanism of the winding coupling, the acceleration stress and acceleration model were determined. The condition matrix of the accelerated life test was determined by Escobar-Meeker (E-M) method. In the statistical analysis of failure life data, it was assumed that the life of the winding coupling obeyed Weibull distribution, and the Weibull probability paper test and Bartlett test were combined to test the life distribution of the winding coupling. Maximum likelihood estimation (MLE) and optimal linear unbiased estimation (BLUE) were used to determine the shape parameters and characteristic life of the distribution model, and the parameter estimation methods were analyzed and compared. The statistical analysis of the data of the double stress constant accelerated life test of the winding coupling showed that the life of the winding coupling could be accurately described by the double stress inverse power law-Weibull, and the accelerated stress-life model was obtained. Under the normal speed level of 1 000 r/min and the normal torque level of 0.6 Nm, the reliability index of a type of winding coupling was obtained by the optimal linear unbiased estimation method.