Storage life evaluation method based on segmented nonlinear Arrhenius model
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摘要: 针对对数线性阿伦尼斯模型适用于温度在较小范围内变化的情况,给出了一种阿伦尼斯模型的修正方法.结合步退应力加速寿命试验失效率高、样本量少、试验设备简单的优点,给出了一种在工程实践中利用分段非线性阿伦尼斯模型对步退应力加速贮存试验进行评估的方法.首先,基于分段非线性阿伦尼斯模型建立步退应力下失效数据折算的数学模型.其次,建立了基于全样本的极大似然函数.最后利用遗传算法解非线性方程组,得到分段非线性阿伦尼斯模型的参数估计.以雷达高度表的步退应力加速贮存试验进行实例分析,将基于分段非线性阿伦尼斯模型、基于对数线性阿伦尼斯模型的加速贮存寿命评估方法得到的计算结果与产品外场得到的平均寿命、失效率以及可靠度函数进行对比分析,基于分段非线性阿伦尼斯模型的加速贮存寿命评估方法得到的结果误差在5%范围内.验证了论文中基于分段非线性阿伦尼斯模型的步退应力加速贮存试验评估方法的有效性以及准确性.
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关键词:
- 分段非线性阿伦尼斯模型 /
- 步退应力 /
- 加速贮存试验 /
- 寿命评估 /
- 极大似然函数
Abstract: Considering that logarithm linear Arrhenius model is only suitable for a small temperature range, a correction method for the Arrhenius model was given. As the step-down-stress accelerated life testing has the advantages of higher failure rate, less sample size, and simpler testing equipment, an evaluation method used in engineering practice for step-down-stress accelerated storage life testing was provided based on the segmented nonlinear Arrhenius model. A mathematical model for failure data conversion under step down stress based on the segmented nonlinear Arrhenius model was first established. The maximum likelihood function of the whole samples was given. The segmented nonlinear Arrhenius model parameter estimation could then be obtained by employing the genetic algorithm to solve nonlinear equations. Taking the step-down-stress accelerated storage life testing of radar altimeter as an example for analysis, the results of average life expectancy, the failure rate and reliability function based on logarithm linear Arrhenius model accelerated storage life evaluation method, the results based on segmented nonlinear Arrhenius model accelerated storage life evaluation method, and the results from field data were compared. The relative error of the results based on the segmented nonlinear Arrhenius model accelerated storage life evaluation method is within 5%. The efficiency and accuracy of the step-down-stress accelerated storage life evaluation method based on the segmented nonlinear Arrhenius model is verified. -
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