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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.
Traditional methods for assessing accelerated degradation (ADT) rely on accurate degeneration data for reliability and life assessment, however, given the human uncertainties in the measurement, the test data may be interval-based rather than exact data.For such problems, This paper presents a method to estimate the life of accelerated degradation tests using interval analysis, and the interval analysis method includes the possibility model and the necessity model.First, based on the interval regression, the problem of modeling and analysis of interval degeneration data under various accelerating stress conditions is transformed into two Sub-planning problem, using the probabilistic model to get the drift coefficient interval and diffusion coefficient under various stress conditions.And then using the necessity model combined with the acceleration model, we can extrapolate the drift coefficient interval under the normal working stress, and then analyze the relationship between the measurement uncertainty and Reliability and life assessment results.Finally, the numerical examples are used to illustrate and verify the proposed method and carry out uncertainty sensitivity analysis.The results show that the reliability and life assessment results are affected by the cognitive uncertainty in the measurement , Reducing the level of uncertainty to ensure the validity of the assessment results.