固体力学与飞行器总体设计

综合应力加速贮存试验方案优化设计

  • 周洁 ,
  • 姚军 ,
  • 苏泉 ,
  • 胡洪华
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  • 1. 北京航空航天大学 可靠性与系统工程学院, 北京 100191;
    2. 桂林航天工业学院 自动化系, 桂林 541004
周洁 女, 硕士研究生。主要研究方向: 可靠性与环境试验技术。Tel: 010-82316473 E-mail: zhouj90@126.com;姚军 男, 博士, 副教授, 硕士生导师。主要研究方向: 可靠性与环境试验技术。Tel: 010-82316473 E-mail: yao2jun1@sina.com;苏泉 男, 硕士, 助教。主要研究方向: 可靠性与环境试验技术。Tel: 010-82316473 E-mail: quanyouyou@guat.edu.cn;胡洪华 男, 硕士研究生。主要研究方向: 可靠性与环境试验技术。Tel: 010-82316473 E-mail: huhzihua@163.com

收稿日期: 2014-06-19

  修回日期: 2014-08-27

  网络出版日期: 2014-09-03

Optimum design of accelerated storage test plan under multiple stresses

  • ZHOU Jie ,
  • YAO Jun ,
  • SU Quan ,
  • HU Honghua
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  • 1. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;
    2. College of Automation, Guilin University of Aerospace Technology, Guilin 541004, China

Received date: 2014-06-19

  Revised date: 2014-08-27

  Online published: 2014-09-03

摘要

针对电子产品在贮存过程中受到的复杂环境应力及现阶段主要采用单应力加速贮存试验的现状,提出一种基于累积损伤理论的温度-湿度步降加速贮存试验方案的优化设计方法。以电子设备正常应力水平下中位寿命估计值的最小渐近方差为目标,以各加速应力水平为设计变量,结合极大似然估计理论,建立了温度-湿度综合应力加速贮存试验方案优化设计的数学模型。对某电度表的综合应力加速贮存试验进行优化设计,利用遗传算法解得k=5时的方案为最优方案。利用Monte Carlo仿真进一步证明k=5时的方案为最优方案。经优化后的试验方案不仅可以满足小样本综合应力加速贮存试验的优化设计,而且能够保证试验数据的估计精度,减少试验次数,缩短试验时间和节约费用。

本文引用格式

周洁 , 姚军 , 苏泉 , 胡洪华 . 综合应力加速贮存试验方案优化设计[J]. 航空学报, 2015 , 36(4) : 1202 -1211 . DOI: 10.7527/S1000-6893.2014.0201

Abstract

In allusion to the complexity of environmental stresses electronic products encountered in the process of storage and the phenomenon that single stress is being used to conduct accelerated storage test currently, an optimum design method of temperature and humidity step-down-stress accelerated storage test based on the cumulative damage method is proposed. The minimum asymptotic variance of product's medium life estimated value at normal working stresses is taken as optimum target, each accelerated stress level as design variable. Meanwhile, combined with maximum likelihood estimation theory for parameter estimation, the mathematic model for multiple stresses accelerated storage test plan's optimal design is built. When genetic algorithm is employed to solve the optimum design result of accelerated storage test plan under multiple stresses of a meter, it is determined that the scheme is best when k equals 5. To improve the credibility, the Monte Carlo simulation is employed to compare the volatility of each scheme about minimum asymptotic variance and mean minimum asymptotic variance, which further proves that the scheme is optimal when k equals 5. The optimized test plan can not only solve optimization design for small sample accelerated storage test, but also ensure the accuracy of evaluation, reduce test times, shorten test time and save cost.

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