作者：罗赓¹, 穆希辉², 牛跃听², 杜峰坡², 陈建华¹, 王琦¹

作者单位：1. 军械工程学院, 河北 石家庄 050003;
2. 军械技术研究所, 河北 石家庄 050003

关键词：竞争失效;加速试验;优化设计;步降应力;BP神经网络;蒙特卡洛仿真

摘要：

针对解析方法难以得到竞争失效产品步降加速试验最优方案和仿真法仿真规模大的难题,该文提出一种基于BP神经网络拟合的竞争失效产品步降加速试验优化方法。采用Monte-Carlo对加速试验进行模拟仿真,以最佳应力水平和试样分配比例为设计变量,以正常应力水平下各失效机理的对数特征寿命渐近方差作为目标函数,建立竞争失效产品步降加速试验优化设计模型。通过仿真实例,验证该方法有效可行。

Study on optimal design of step-down-stress accelerated life test of competing risk products

LUO Geng¹, MU Xihui², NIU Yueting², DU Fengpo², CHEN Jianhua¹, WANG Qi¹

1. Ordnance Engineering College, Shijiazhuang 050003, China;
2. Ordnance Technological Research Institute, Shijiazhuang 050003, China

Abstract: Aiming at the problems including great difficulty of finding out the optimal plan for the step-down-stress accelerated life test of competing risk products and large simulation scale with the simulation method, the paper puts forward an optimization method for the step-down-stress accelerated life test of competing risk products based on BP neural network fitting. The method applies Monte-Carlo to have an analog simulation for the accelerated life test and establishes a model for the optimal design of step-down-stress accelerated life test of competing risk products by taking the optimal stress level and sample distribution proportion as design variables and the asymptotic variance of logarithmic characteristic life of failure mechanisms under normal stress level as objective function. The effectiveness and feasibility of the method are verified through case simulation.

Keywords: competing failure;accelerated life test;optimal design;step-down-stress;BP neural network;Monte-Carlo simulation

2016, 42(6): 95-99  收稿日期: 2015-08-20;收到修改稿日期: 2015-10-19

基金项目: 国家自然科学基金项目(61471385)

作者简介: 罗赓(1990-),男,陕西咸阳市人,硕士研究生,专业方向为弹载机电系统分析与评估。

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