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提出一种Weibull分布定时无失效数据疲劳寿命分散系数修正方法,定义了定时无失效数据情形下分散系数的修正系数,推导了其计算公式.定时无失效数据与完全数据截然不同,因此其疲劳寿命分散系数明显不同,从疲劳分散系数的定义出发,分别对定时无失效数据情形下基于平均寿命、特征寿命、中位值寿命、最小寿命及最大寿命的两参数Weibull分布疲劳寿命分散系数进行了修正.最后对完全数据与定时无失效数据条件下分散系数计算数值进行了对比分析,结果表明分散系数的修正充分利用了产品的寿命信息,提高了产品安全寿命的预测精度,且修正系数易于计算,便于工程应用.
A method to correct the fatigue life distribution coefficient of Weibull distribution-based time-invariant data is proposed, and the correction coefficient of dispersion coefficient under the condition of no-failure data is defined. The calculation formula of the dispersion coefficient is deduced. Timing failure-free data is completely different from the complete data, Based on the definition of fatigue dispersion coefficient, the two-parameter Weibull distribution fatigue life distribution coefficient based on mean life, characteristic life, median life, minimum life and maximum life are respectively revised .Finally, the calculated values of dispersion coefficient under the condition of complete data and timed zero failure data are compared and analyzed. The results show that the correction of dispersion coefficient makes full use of product life information and improves the prediction accuracy of product safety life, and the correction coefficient is easy to calculate, Facilitate engineering applications.