全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
电子学报  2015 

基于随机退化数据建模的设备剩余寿命自适应预测方法

DOI: 10.3969/j.issn.0372-2112.2015.06.013, PP. 1119-1126

Keywords: 寿命预测,退化,Bayesian方法,期望最大化

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对现有剩余寿命预测研究中需要多个同类设备历史数据离线估计模型参数的问题,本文提出了一种基于退化数据建模的服役设备剩余寿命自适应预测方法.该方法,利用指数随机退化模型来建模设备的退化过程,基于退化监测数据运用Bayesian方法更新模型的随机参数,进而得到剩余寿命的概率分布函数及点估计.区别于现有方法,本文方法基于设备到当前时刻的监测数据,利用期望最大化算法对模型中的非随机未知参数进行在线估计,由此无需多个同类设备历史数据.最后,通过数值仿真与实例分析,验证了本文方法在剩余寿命预测时的有效性.

References

[1]  Wu C F.On the convergence property of the EM algorithm[J].Annals of Statistics, 1983, 11(1):95-103.
[2]  彭宝华, 周经伦, 冯静, 刘学敏.金属化膜脉冲电容器剩余寿命预测方法研究[J].电子学报, 2011, 39(11):2674-2679. Peng B H, Zhou J L, Feng J, Liu X M.Residual lifetime prediction of metallized film pulse capacitors[J].Acta Electronica Sinica, 2011, 39(11):2674-2679.(in Chinese)
[3]  王小林, 郭波, 程志君.融合多源信息的维纳过程性能退化产品的可靠性评估[J].电子学报, 2012, 40(5):977-982. Wang X L, Guo B, Cheng Z J.Reliability assessment of products with Wiener process degradation by fusing multiple information[J].Acta Electronica Sinica, 2012, 40(5):977-982.(in Chinese)
[4]  钟强晖, 张志华, 李大伟.基于性能退化的电子产品筛选试验设计[J].电子学报, 2013, 41(9):1788-1793. Zhong Q H, Zhang Z H, LI D W.Screening test design for electronics based on performance degradation[J].Acta Electronica Sinica, 2013, 41(9):1788-1793.(in Chinese)
[5]  Saha B, Goebel K, Poll S, Christophersen J.Prognostics methods for battery health monitoring using a Bayesian framework[J].IEEE Transactions on Instrumentation Measurement, 2009, 58(2):291-296.
[6]  Si X S, Wang W B, Hu C H, et al.Remaining useful life estimation—A review on the statistical data driven approaches[J].European Journal of Operational Research, 2011, 213(1):1-14.
[7]  Meeker W Q, Escobar L A.A review of recent research and current issues in accelerated testing[J].International Statistical Review, 1993, 61(1):147-168.
[8]  司小胜, 胡昌华, 周东华.带测量误差的非线性退化过程建模与剩余寿命估计[J].自动化学报, 2013, 39(5):590-601. Si X S, Hu C H, Zhou D H.Nonlinear degradation process modeling and remaining useful life estimation subject to measurement error[J].Acta Automatica Sinica, 2013, 39(5):590-601.(in Chinese)
[9]  Gertsbackh I B, Kordonskiy K B.Models of Failure[M].New York:Springer-Verlag, 1969.
[10]  Nelson W.Accelerated Testing:Statistical Models, Test Plans and Data Analyses[M].New York:Wiley, 1990.
[11]  Lu C J, Meeker W Q.Using degradation measures to estimate a time-to-failure distribution[J].Technometrics, 1993, 35(2):161-174
[12]  周东华, 魏慕恒, 司小胜.工业过程异常检测、寿命预测与维修决策的研究进展[J].自动化学报, 2013, 39(6):711-722. Zhou D H, Wei M H, Si X S.A survey on anomaly detection, life prediction and maintenance decision for industrial processes[J].Acta Automatica Sinica, 2013, 39(6):711-722.
[13]  Gebraeel N Z, Lawley M A, Li R, et al.Residual-life distributions from component degradation signals:A Bayesian approach[J].IIE Transactions, 2005, 37(6):543-557.
[14]  N Gebraeel.Sensory-updated residual life distributions for components with exponential degradation patterns[J].IEEE Transactions on Automation Science and Engineering, 2006, 3(4):382-393.
[15]  Gebraeel N Z, Elwany A, Pan J.Residual life predictions in the absence of prior degradation knowledge[J].IEEE Transactions on Reliability, 2009, 58(1):106-117.
[16]  Elwany A, Gebraeel N Z, Maillart L.Structured replacement policies for systems with complex degradation processes and dedicated sensors[J].Operations Research, 2011, 59(3):684-695.
[17]  Si X S, Wang W B, Hu C H, Zhou D H, Pecht M.Remaining useful life estimation based on a nonlinear diffusion degradation process[J].IEEE Transactions on Reliability, 2012, 61(1), 50-67.
[18]  Park C, Padgett W J.Stochastic degradation models with several accelerating variables[J].IEEE Transactions on Reliability, 2006, 55(2):379-390.
[19]  Tseng S T, Tang J, Ku L H.Determination of optimal burn-in parameters and residual life for highly reliable products[J].Naval Research Logistics, 2003, 50(1):1-14.
[20]  程龙, 冯静, 孙权, 周经伦, 蔡永超.非连续运行设备贮存-工作联合退化模型及其应用[J].电子学报, 2012, 40(12):2549-2552. Cheng L, Feng J, Sun Q, Zhou J L, Cai Y C.Storage-work joint degradation model for discontinuous-working devices and its application[J].Acta Electronica Sinica, 2012, 40(12):2549-2552.(in Chinese)
[21]  司小胜, 胡昌华, 李娟, 陈茂银.Bayesian更新与EM算法协作下退化数据驱动的剩余寿命估计方法[J].模式识别与人工智能, 2013, 26(4):357-365. Si X S, Hu C H, Li J, Chen M Y.Degradation data-driven remaining useful life estimation approach under collaboration between Bayesian updating and EM algorithm[J].Pattern Recognition and Artificial Intelligence, 2013, 26(4):357-365.(in Chinese)
[22]  周鑫.基于EM算法的G0分布参数最大似然估计[J].电子学报, 2013, 41(1):178-184. Zhou X.An EM algorithm based maximum likelihood parameter estimation method for the GO distribution[J].Acta Electronica Sinica, 2013, 41(1):178-184.(in Chinese)
[23]  Dempster A P, Laird N M, Rubin D B.Maximum likelihood from incomplete data via the EM algorithm[J].Journal of the Royal Statistical Society Series B, 1977, 39(1):1-38.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133