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作 者:彭宝华[1] 周经伦[1] 冯静[1] 刘学敏[1]
机构地区:[1]国防科学技术大学信息系统与管理学院,湖南长沙410073
出 处:《电子学报》2011年第11期2674-2679,共6页Acta Electronica Sinica
基 金:国家自然科学基金(No.60701006;60804054;71071158)
摘 要:金属化膜脉冲电容器是惯性约束聚变激光装置的重要元器件之一,其寿命预测是激光装置维护和备件决策制定的依据.在分析金属化膜脉冲电容器退化失效机理的基础上,采用Wiener过程描述其性能退化过程.进一步考虑到各电容器之间的差异,将Wiener过程的漂移参数和扩散参数看成随机变量,提出了随机效果Wiener过程模型,由同一批电容器的历史性能退化数据拟合其分布.在对单个电容器进行寿命预测时,采用Bayes方法融合电容器总体信息与该电容器自身的性能退化信息,得到其剩余寿命参数的验后估计,因而在电容器性能退化数据较少时采用该方法能提高剩余寿命预测精度.The metallized film capacitor is one of the most important types of components of the laser driver in inertial fusion facility.The residual lifetime of the capacitor is of great value in maintenance and spare parts decision making.We used the Wiener process to model the degradation process based on an analysis of the capacitance degradation mechanism of the metallized film capacitor.Taking the inherent difference of each capacitor into consideration,we proposed to use the Wiener process with random effect,where the drift and diffusion parameters of the Wiener process were treated as random variables,whose distribution were estimated using the degradation data from other capacitors from the same batch.When predicting the residual lifetime of a particular capacitor,a Bayesian method was used to integrate its degradation data and the batch information.Posterior distribution of the residual lifetime parameters were deduced.The proposed method can improve the precision of prediction when its degradation data are few.
关 键 词:金属化膜脉冲电容器 剩余寿命预测 BAYES方法 WIENER过程 信息融合
分 类 号:TP114.3[自动化与计算机技术—控制理论与控制工程]
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