基于条件分布的陆军装备系统分析中心模型可靠性增长预测  

Reliability Growth Prediction of Army Materiel System Analysis Activity Model Based on Conditional Distribution

作　　者：郭建英[1] 孙永全[1] 陈洪科[1] 丁喜波[1] 

机构地区：[1]哈尔滨理工大学传感器与可靠性研究所,哈尔滨150080

出　　处：《机械工程学报》2012年第4期188-192,共5页Journal of Mechanical Engineering

基　　金：国家自然科学基金(60072002);国家高技术研究发展计划(863计划;2009AA042407)资助项目

摘　　要：针对可靠性增长试验中未来故障发生时间的预测问题,提出基于条件分布的陆军装备系统分析中心模型可靠性增长预测建模方法。基于Weibull过程理论和可靠性增长预测理论,在故障截尾和时间截尾两种情况下,根据系统已发生故障时间的联合概率密度函数和未来故障发生时间的联合条件概率密度函数,建立未来故障发生时间的边缘条件概率密度函数,给出未来故障发生时间的预测子和预测区间。通过引入方差系数,分析未来故障发生时间的预测精度。并利用某型风力发电机组变桨系统在现场试运行中伴随维修而获取的可靠性增长试验数据,验证本方法的可行性和有效性。不仅克服传统预测方法的局限性,而且预测精度较高。研究结果对于动态分析系统可靠性增长变化趋势,科学调整增长试验时间,合理确定设备交付时间、制定维修策略等都有明显的指导意义。Army materiel system analysis activity（AMSAA） model reliability growth prediction modeling method based on conditional distribution is proposed for the prediction of next failure time during reliability growth testing.According to Weibull process theory and reliability growth prediction theory,marginal conditional probability density function of the future failure time is established through obtaining joint probability density function of the failure time and joint conditional probability density function of the future failure time in the cases of failure censor and time censor,and then predictor and prediction intervals of the future failure time are given.By introducing the coefficient of variance,prediction accuracy of the future failure time is analyzed.Feasibility and effectiveness of this method are verified through a certain type of wind turbine pitch system reliability growth test data in the filed trial operation,not only overcame the limitations of traditional prediction method,but also improved the prediction accuracy.The research results is beneficial to dynamic analyzing system reliability growth trend,science adjusting reliability growth test time,reasonable determining the equipment delivery time,and developing maintenance strategies.

关 键 词：可靠性增长预测 条件分布 预测精度 方差系数 风力发电机组 

分 类 号：TB114[理学—概率论与数理统计]