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1、表明了该方法的优越性。(2)提岀了一种新的基于相对粒度的属忡约简算法，用于约去决策表中的冗余属性，该算法不但时间复杂度低，而且同时适用于相容决策表和不相容决策表，并对除氧器的故障诊断决策表进行了约简。(3)提出了一种基于相似度的搜索推理算法，通过计算最大相似度寻找现场釆集信息对应的决策，这种方法可以有效减少甚至避免推理中结杲冲突的概卒，提高分辨率，将其用于除氧器系统的故障诊断决策推理中。(4)提岀了-科基于粒计算的SDG故障诊断方法，以65t/h蒸汽锅炉系统为例，搭建其snG模型，获取snG故障珍断的决策衰，约简后生成粒]1
2、F,利用搜索推理方法，適汁算最大相似度寻找故障源，并在Matlab仿真平台上，对算法的可行性进行了验证。仿真结果表明，该方法在保留SDa故院诊断诸多优点的前提札提高了诊断的速率和分辨率。关键词：故障KE断，符号有句图，粒计算，属性约简，搜索推理RESEARCHONGRANULARCOMPUTING-BASEDSDGFAULTDIAGNOSISOFSTEAMBOILERSYSTEMABST孔生CTSignedDirectedGraph(SOG)modelasanimportantbranchofqualitativemodel
3、scanbeusedtoexpresscomplicatedcause-e:ffectrelationship，andhasthecapacityo[containinglarge-scalepotentia1information・Whenusedforfaultdiagnosis,itnotonlyhasgoodcompleteness,strongadaptabilityandexcellentrobustness,butalsocanprovidefaultpropagationpathsandfaultexplan
4、ation.Inrecentyears,SOGfaultdiagnosisgetstheextensiveattentionofscholars,developsrapidly，andhasachievedgoodapplicationeffectinpetroleurnandchemicalindustry.ButthefaultdiagnodismethodbasedonSDGmodelinevitablyhasthedisadvantageofrnulti-meaningsreasoninginqualitativem
5、ethod,whichcanresultinlowresolution,andthereisotherproblemstobesolved:relyingonthemodeltoomuch,slowdiagnosisrateoflargesystems,badreal-timeandsoon.GranularComputing(GrC)whichisproposedbyprofessorT.Y.Linin1996,isanewwayofhumanthink,ingsimulatingandsolvingcomplexprob
6、lemsinthecuqentareasofcomputerintelligence,anditisaneffectivetoolforsolvingcomplexproblem,massivedatamining,andfuzzyinformationprocessing.AttributereductionalgorithmsinGrCcanreduceredundantattributesunderthepremiseofensuringtheabilityofnotchangingclassification,and
7、derivetheminimalattributeset.AndsearchreasoningmethodcanJargelyreduceevenavoidtheconflictprobabiJityofresultsUhusimprovethereasoningresoJution.InordertosolvetheproblemsexsitinSDGfaultdiagnosis,theattributereductionandsearchreasoningofGrCisintroducedinSDGfaujtdiagno
8、sisinthispaper,anddiefollowingworkisdone:(1)Toimprovethediagnosisreal-time,avoidmultiplereasoningfortbesamefaultmodeandthepossiblecombinationexpl
