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加速试验技术是开展寿命评估的重要手段,它能够在短时间内得到大量的寿命信息,弥补了外场信息稀缺的问题.然而实验室环境并不能完全代表外场使用环境,它们之间存在一定的差异,其结果也往往不能反应产品的实际情况.针对上述问题,提出一种能够综合加速寿命试验、加速退化试验和外场信息的贝叶斯建模评估方法,利用修正因子对实验室和外场的差异进行修正,利用马尔科夫蒙特卡洛方法进行统计推断,从而得到更为精确的外场可靠寿命及可靠性评估结果.最后通过仿真案例对该方法的实施过程进行了说明及验证,并对其精度和敏感性进行了分析.
Accelerated test technology is an important means to carry out life assessment, which can get a lot of life information in a short time and make up for the problem of scarcity of field information.However, the laboratory environment does not completely represent the external use environment, there is a certain difference between them , The results often can not reflect the actual situation of the product.Aiming at the above problems, this paper proposes a Bayesian modeling and evaluation method that can comprehensively accelerate the life test, accelerated degradation test and field information, and use the correction factor to test the difference between laboratory and field And make use of Markov-Monte-Carlo method to make statistical inference, so as to obtain more accurate field reliability reliability and reliability assessment results.Finally, the simulation process illustrates and verifies the implementation of this method, and its accuracy And sensitivity was analyzed.