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Modeling of degradation data via wiener stochastic process based on acceleration factor constant principle

机译：基于加速因子恒定原理的维纳随机过程模拟降解数据

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摘要

This paper proposes a systematic method of modeling accelerated degradation data based on the acceleration factor constant principle. Wiener stochastic process is considered because it is the most extensively used for degradation modeling. For the Wiener stochastic processes with three different time functions, the parameter relationships, which should be satisfied under any two different stress levels, are deduced according to the acceleration factor constant principle. The deduced parameter relationships indicate the stress-related parameters, which are applied to establish accurate accelerated degradation models. In addition, the deduced parameter relationships provide a guidance to test the consistency of the degradation mechanisms under different stress levels. A hypothesis method based on Analysis of Variance is adopted to identify the accelerated stress levels with different degradation mechanism. The degradation data under these stress levels should not be used to assess the product's reliability. The methods of validating accelerated degradation models and reliability assessments are also proposed. The simulation results prove the feasibility and effectiveness of the proposed methods. From the numerical example, it is concluded that the accelerated degradation model established based on the acceleration factor constant principle is more credible and accurate.
机译：本文提出了一种基于加速因子恒定原理建模加速降解数据的系统方法。考虑了维纳随机过程，因为它是最广泛用于降解建模的。对于具有三种不同时间函数的维纳随机过程，根据加速度因子恒定原理推断出在任何两个不同的应力水平下进行参数关系。推断的参数关系表明应力相关参数，用于建立准确的加速下降模型。另外，推断的参数关系提供了测试不同应力水平下的降解机制的一致性的指导。采用基于差异分析的假设方法来鉴定具有不同降解机制的加速应力水平。不应使用这些应力水平下的劣化数据来评估产品的可靠性。还提出了验证加速降级模型和可靠性评估的方法。仿真结果证明了所提出的方法的可行性和有效性。从数值示例中，得出结论，基于加速度因子恒定原理建立的加速降解模型更可信和准确。

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