卡方加速可靠性增长模型

A. Feinberg
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引用次数: 3

摘要

卡方加速可靠性增长(CARG)模型是单应力水平和多应力水平可靠性增长寿命数据分析的一种新方法。该模型比较容易应用,具有很强的实用性。当可以假设指数分布时,CARG方法是合适的。卡方分布已被用作确定组件、组件和系统的指数失效寿命行为的可靠性置信限的传统方法,并经常扩展到加速寿命试验数据分析。当在统计显著性水平上的可靠性估计的加速测试中观察到很少甚至零故障时,分布是评估的关键。因此,考虑在可靠性加速增长数据分析的应用中使用卡方方法是很自然的。利用统计量,在由单加速应力和多加速应力测试组成的制造数据集上对该模型进行了验证。可靠性增长预测与产品的现场数据非常吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chi-Squared Accelerated Reliability Growth model
A Chi-Squared Accelerated Reliability Growth (CARG) model has been developed as a new method for single- and multi-stress level reliability growth life data analysis. The model is relatively easy to apply and is very practical. The CARG method is appropriate when an exponential distribution can be assumed. The chi-squared distribution has been used as a traditional method of identifying reliability confidence bounds for the exponential failure lifetime behavior of components, assemblies, and systems and is often extended to accelerated life test data analysis. The distribution is key for assessment when observance of few or even zero failures occur in accelerated testing for estimates on reliability at a statistical significance level. It is therefore natural to consider using the chi-squared method in the application of accelerated reliability growth data analysis. Using the statistic, the model is demonstrated on a manufacturing data set consisting of single accelerated stress and multi-accelerated stress tests. Reliability growth predictions show good agreement with the product's field data.
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