基于系统性能退化数据的可靠性增长研究

Reliability Growth Analysis Based on System Degradation Data

性能退化表征的是产品的工作能力随时间逐渐降低的现象。对于试验费用昂贵的高可靠性产品,失效时间数据难以得到,此时性能退化数据是进行可靠性增长分析的重要信息。文章提出用线性随机过程模型来描述产品性能参数逼近临界值的过程,并根据失效机理进行产品可靠性评估;再根据产品研制试验分阶段进行的特点,引进增长因子反映各阶段间的改进程度,并用ML Ⅱ方法得到该参数的估计;最后用线性回归方法得到失效率随研制阶段进展而下降的可靠性增长模型。文中推导的寿命分布函数中的参数因物理含义明确而易于通过实时测量特性参数输出数据估计得到。文中还给了一个数值例说明该方法在工程上应用的有效性。

Degradation is a phenomenon where certain measurements of quality characteristics deteriorate over time.Degradation data can provide us with useful information about the reliability growth for highly reliable and tests expense products.In this paper, the degradation process are described as a simple linear stochastic model, then reliability can be assessed based on failure physical analysis.At the same time,the growth factor is proposed to reflect the improvement between adjacent periods, and the factor is assessed by ML-Ⅱ method.At last,the reliability growth model,which is represent by the descending of instant failure rate with time, was got by linear regression.The parameters of the failure time distribution educed from failure physical analysis can be estimated easily from the degradation data collected.A numerical example is given to illustrate the efficiency of this method.