基于贝叶斯网络(BayesianNetworks)方法的高炉故障诊断分析

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1、AbstractThesmeltinginblastfurnaceplaysanimportantpartinironandsteelindustrywhichisstanchionindustryofcountryeconomic.Thesmeltinginblastfurnaceisacomplicatedprocessincludingalotofphysicalchangeandchemicalchange.Thesmeltinginblastfurnacecarriesonundertheclosedstateandtheprocessparameter

2、mostlyisunabledirectlytoobserve.Sopeoplecanonlyindirectlydeterminethesmeltingprocesstounderstandthesmeltinginblastfurnaceprocess.Thefaultdiagnosisofthestateonblastfurnaceisveryimportanttosmeltinginblastfurnace,andthestateofblastfurnaceisoftenundulate.Soifwecancomprehensivelyunderstand

3、thestatewhichisgoingonwellandtheunusualsituationofthesmeltinginblastfurnaceandmakeafastaccurateisolationandrecognizestoitsbreakdown,sowemayhaveabetterdirectionwiththediagnoses.Thuspeoplecanreducethemaintenancecostvastly,enhancetheenterprisebenefit,andeffectivelyavoidthesignificantacci

4、dentoccurrence.ThisarticlemainlydiscussestheapplicationofBayesiannetworkinblastfurnacefaultdiagnosis.Themethodisusedtodiagnosismodelandproposedasystemdesign.ThedesignincludethecausalityandsimpleBayesiannetworkdiagnosticmodel,applythecompletesamplesettotraintheinitialnetworkparamete匚In

5、ordertoimprovethefunctionofmodel,thepaperresearchtheMonte-Carlomethod,GaussianandEMalgorithmintrainingtheincompletedata,andanalysethereasonsforthedifferences.BayesianNetworkisadirectedacyclicgraph.Eachnodeinthenetworkexpressthedegreeofcorrelationbytheconditionalprobability.BayesianNet

6、workisamathematicalinferencemodelbasedonprobabilitytheory.Itcanincorporatethepriorknowledgeeffectivelyandgetaeffectivetrainingandreasoning.Keywords：Thesmeltinginblastfurnace;faultdiagnosis;BayesianNetworks摘要IAbstractII第1章绪论11」论文研究背景及意义11.2设备诊断技术的重要意义21.3智能故障诊断方法的研究现状及发展3131智能故障诊断的研究现状

7、41.3.2几种智能故障诊断模型的比较41.3.3智能故障诊断的发展趋势61.4论文主要工作及章节安排7第2章高炉冶炼系统研究82.1高炉工艺82.1.1高炉生产的工艺流程82.1.2高炉木体控制工艺92.2高炉牛产的特点92.2.1炉内状况描述102.2.2高炉炉况判断的意义102.2.3高炉异常炉况122.3本章小结14第3章贝叶斯网络方法的研究153.1贝叶斯方法的概述153.1.1贝叶斯方法的基本观点153.1.2基本贝叶斯分类模型163.2贝叶斯网络的综述18321贝叶斯网络的基本规则183.2.2贝叶斯网络的定义193.2.3单连通和多连通的贝叶斯网络

8、213.2