Lifetime evaluation method with integrated accelerated testing and field information
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摘要: 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.Abstract: Accelerated testing is an important method in lifetime prediction. It can obtain enough lifetime information in short time. Sometimes, the lifetime information from the laboratory condition and the one from actual condition are different. To solve the problem above, a Bayesian evaluation method was proposed to integrate the accelerated life testing(ALT) data, accelerated degradation testing(ADT) data and field data together. Calibration method was introduced to calibrate the difference between the different conditions, to evaluate the product's real lifetime more accurately. The statistical inference method was carried out through Markov chain Monte Carlo methods. The proposed method was demonstrated through an example, and relevant analyses were implemented.
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