Evaluation method for accelerated degradation testing with interval analysis
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摘要: 传统的加速退化试验(ADT)评估方法基于精确退化数据进行可靠性和寿命评估,然而考虑到测量中人的不确定因素,试验数据可能是区间型而非精确数据.针对此类问题,基于维纳过程提出一种采用区间分析的加速退化试验寿命评估方法,区间分析方法包括可能性模型和必要性模型.首先基于区间回归将各加速应力条件下的区间退化数据的建模分析问题转化为二次规划问题,利用可能性模型获取各应力条件下的漂移系数区间和扩散系数.然后利用必要性模型结合加速模型,外推得到正常工作应力条件下的漂移系数区间,进而分析测量不确定性与可靠性和寿命评估结果的关系.最后通过数值案例对提出的方法进行阐述和验证,并进行不确定性敏感性分析.结果表明,可靠性和寿命评估结果受测量中认知不确定性的影响,降低该不确定性水平能够保证评估结果的合理性.Abstract: Traditional evaluation methods of accelerated degradation testing (ADT) are based on precise degradation data to conduct reliability and lifetime assessment. However, with interfere of the uncertainties from human factors, the test data can be imprecise represented by interval rather than precise data. Under this consideration, an interval analysis method for ADT evaluation was proposed based on Wiener process, which included possibility and necessity models. Interval regression method was firstly used to transfer the problems of modeling interval degradation data under different accelerated stress levels into quadratic programming problems. The interval drift coefficients under different stress levels with possibility model and diffusion coefficient were obtained. Then the interval drift coefficients were extrapolated to normal stress condition with accelerated model under necessity model, and further to analyze the relationship between measurement uncertainty and reliability and lifetime evaluation results. Finally, the numerical study was used to present and verify the proposed methodology, and conduct uncertainty sensitivity analysis. The results show that both reliability and lifetime evaluation results are effected by epistemic uncertainty of measurement, and their correctness can be ensured with decreasing epistemic uncertainty.
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