›› 2016, Vol. 36 ›› Issue (4): 58-.doi: 10.16708/j.cnki.1000-758X.2016.0044

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LifetimepredictionofaerospaceequipmentbasedonDSevidencetheory

DING  Rui, LU  Ning-Yun, CHENG  Yue-Hua, JIANG  Bin, XING  Yan   

  1. 1CollegeofAutomationEngineering,NanjingUniversityofAeronautics&Astronautics,Nanjing211016,China
    2CollegeofAerospaceEngineering,NanjingUniversityofAeronautics&Astronautics,Nanjing211016,China
    3BeijingInstituteofControlEngineering,Beijing100191,China
    4StateKeyLaboratoryofSpaceIntelligentControl,Beijing100191,China
  • Received:2015-11-26 Revised:2015-12-30 Online:2016-08-25 Published:2016-05-11

Abstract: AninformationfusionmethodwasproposedbasedonDSevidencetheoryandBayestheoryforlifetimepredictionofimportantaerospaceequipment,momentumwheel.Firstly,multisourcelifeinformationwerecollectedandminedtoobtainthepriordistributionofthemomentumwheel′slifetime,inordertobuildDSevidencecollections.Secondly,DScombinationrulewasusedtoobtainreasonableweightallocationforpriordistributions.Afterthat,fusionposteriordistributionwasfiguredoutandthevaluesoflifeparameterswerealsoestimated.Finally,accordingtoparameters′estimation,thelifetimepredictionformomentumwheelwasderived.Simulationresultshowsthatthepredictionusingtheproposedmethodisclosertothereallifetimemeasurements.

Key words: lifetimeprediction, multisourceinformationfusion, DSevidencetheory, Bayesmethod, Momentumwheel