Abstract

A multi-objective optimization method for the accelerated degradation test based on Wiener process is proposed in this article in order to solve the problem that a single objective optimization cannot solve the difficulty or even conflicting test configurations caused by different optimization objective functions. An accelerated degradation model is established based on Wiener process, and the unknown parameters are solved by a two-step maximum likelihood estimation method. Considering both the accuracies of life estimation and the model parameter estimation, a multi-objective optimization model is established with the optimization goals of the minimum asymptotic variance of P-quantile of lifetime and the maximum determinant of Fisher information matrix. The Pareto solutions are set by the multi-objective genetic algorithm, and the test configurations for multi-objectives are obtained. Under the step stress accelerated degradation test and the constant stress accelerated degradation test, the effectiveness of the proposed method is verified by an optimization example of LEDs accelerated degradation test.

摘要

针对单一目标优化无法解决优化目标函数不同导致的测试配置困难甚至冲突的问题，本文提出了一种基于维纳过程的加速退化测试多目标优化方法。基于维纳过程建立加速退化模型，通过两步最大似然估计法求解未知参数。综合考虑寿命估计精度和模型参数估计，建立了以寿命P分位数渐近方差最小、Fisher信息矩阵行列式最大为优化目标的多目标优化模型。帕累托解由多目标遗传算法设定，并获得多目标的测试配置。在阶跃应力加速退化试验和恒应力加速退化试验下，通过一个LED加速退化试验的优化实例验证了所提方法的有效性。