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基于贝叶斯模型的装备剩余寿命预测研究 被引量:7

Bayesian Model for Predicting Residual Life of Equipment
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摘要 为了解决武器装备日益复杂及维修工作日趋繁重的问题,运用贝叶斯模型预测装备修理后的剩余寿命,为合理安排其修理计划提供依据。替代传统的指数分布,用威布尔分布描述系统寿命特征,并运用极大似然方法和贝叶斯方法估计威布尔分布的两个未知参数,给出其置信区间。在此基础上,对先验样本和后验样本两种不同情况,分别运用贝叶斯模型预测装备修理后的剩余寿命,并给出实例。结果表明了该方法的有效性。 To solve the problem of weapon equipment is the growing complexity and themaintenance work becoming heavy daily,the Bayesian model is applied to predicting residual life ofequipment after repair,the foundation was proposed for reasonably arranging repair plan. Thetraditional exponential distribution is replaced,then Weibull distribution is used for describing lifecharacteristic of system,furthermore,and the methods of Maximum likelihood and Bayesian areapplied to estimating the two parameters of Weibull distribution,and the credible intervals are given.On the basis,according to the two situations that prior sample and posterior sample,the residual lifeafter repair is predicted by Bayesian model respectively. The illustrative example is given in paper,and the proposed method is proved to be effective.
作者 刘刚 黎放
出处 《火力与指挥控制》 CSCD 北大核心 2016年第5期19-24,共6页 Fire Control & Command Control
关键词 威布尔分布 贝叶斯 剩余寿命 预测 weibull distribution,bayesian,residual life,predict
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参考文献16

  • 1杨志波,董明.动态贝叶斯网络在设备剩余寿命预测中的应用研究[J].计算机集成制造系统,2007,13(9):1811-1815. 被引量:12
  • 2孙绍辉,王华伟,李伟.潜在故障期内航空发动机的剩余寿命预测[J].航空计算技术,2012,42(1):8-11. 被引量:5
  • 3WANG W B.A two-stage prognosis model in conditionbased maintenance [J].European Journal of OperationalResearch,2007,12(182):1177-1187.
  • 4NAGI G.Mark lawley residual life predictions fromvibration-based degradation signals:a neural networkapproach a neural network approach[J].IEEE Transactionson Industrial Electronics,2004,51(3):694-700.
  • 5YUEN H K,TSE S K. Parameters estimation for weibulldistributed lifetimes under progressive censoring with randomremovals[J]. Statist Comput Simul,1996,3(55):57-71.
  • 6FERNáNDEZ A J. On estimating exponential parameterswith general type II progressive censoring[J]. Statist PlannInference,2004,1(121):135-147.
  • 7SOLIMAN A A. Estimation of parameters of life fromprogressively censored data using burr-XII model[J]. IEEETrans Reliab,2005,5(54):34-42.
  • 8ASGHARZADEH A. Point and interval estimation for ageneralized logistic distribution under progressive type IIcensoring[J]. Commun Statist Theory Meth,2006,3(35):1685-1702.
  • 9KUS C,KAYA M F. Estimation for the parameters of thepareto dsitribution under progressive censoring[J]. CommunStatist Theory Meth. 2007,2(36):1359-1365.
  • 10MOUSA M A,SAGHEER S A. Bayesian prediction forprogressively type-II censored data from the rayleigh model[J]. Commun Statist Theory Meth, 2005, 1(34):2353-2361.

二级参考文献25

  • 1刘洪亮,王蓓.浅议武器装备全寿命管理[J].军事经济学院学报,2005,12(4):51-52. 被引量:2
  • 2左洪福,张海军,戎翔.基于比例风险模型的航空发动机视情维修决策[J].航空动力学报,2006,21(4):716-721. 被引量:50
  • 3Todd D Batzel,David C Swanson.Prognostic Health Manage-ment of Aircraft Power Generators[J].IEEE Transactions onAerospace and Electronic Systems,2009,45(2):473-482.
  • 4Wenbin Wang.A Two-stage Prognosis Model in Conditionbased Maintenance[J].European Journal of Operational Re-search,2007,182:1177-1187.
  • 5Wang Ying,Wang Wen-bin,Fang Shu-fen.Research on a Model of the Residual Life Prediction for Condition-basedMaintenance[J].Management Science and Engineering,2006,10:536-539.
  • 6Feng Xue,Piero Bonissone,Anil Varma.An Instance-BasedMethod for Remaining Useful Life Estimation for Aircraft En-gines[J].Journal of Failure Analysis and Prevention,2008,8(2):199-206.
  • 7Nagi Gebraeel.Mark Lawley Residual Life Predictions FromVibration-Based Degradation Signals:A Neural Network Ap-proach A Neural Network Approach[J].IEEE Transactionson Industrial Electronics,2004,51(3):694-700.
  • 8BUNKS C, MCCARTHY D, TARIK A. Condition based maintenance of machines using hidden Markov models[J]. Mechanical Systems and Signal Processing, 2000,14(4) :597-612.
  • 9CAMCI F. Process monitoring, diagnostics and prognostics using support vector machines and hidden Markov models[D]. Detroit, Mich. , USA: Wayne State University,2005.
  • 10JARDINE A K S, LIN D, BANJEVIC D. A review on machinery diagnostics and prognostics implementing condition-based maintenance[J]. Mechanical Systems and Signal Processing, 2005,20(1) :1483-1510.

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