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ID:36465010
大小:2.37 MB
页数:82页
时间:2019-05-10
《振动压路机智能故障诊断系统的研究与开发》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、分类号:—业!!一长安大学硕士学位论文握麴匿竖扭蟹筵垫睦趁堑丕缝鳇硒塞皇珏筮业指导敦师姓名巨巫暨熬篮申请学位级别—唑±一学科名称窑煎篮盛王程翌蕉劐论文提交日期j墅礁驵论文答辩日期z鲤§至≥且:2旦学位授予单位—————————盏盘墨竖———————一答辩委员会主席:煎量壁—熬握学位论文讦阅人:武直差—蓝握型埋照—鼓援AbstractThispaperderivesfromtheresearchanddevelopmentofcontrolsystemofintelligentroadrollerin“86
2、3”project.Sometimes,intelligentroadrollerintegrateshydraulictechnique,computertechnique,microelectronictechnique,andsensingandtestingtechniques,sotheadvancedtechnologyandthecomplexstructureaddgreatlytothedifficultyofrepair.Mostofthetime,airmadaworktogethe
3、rontheconstructionsite。iftheroadrolleroccursfault,theotherconstructionmachinerycooperatewithitalsomuststopworking,which,illdelayconstructionperiodandyieldhugefinanciallosses.Thepurposeoftheresearchofthispaperisjusttoachievestatemonitoring,guardingagainsta
4、nddiagnosingfault,anddecreasinglossescausedbyroadroller’sfaults.Intelligentfaultdiagnosissystemofvibratoryroadrollerwhichconsistsofneuralnetworkandexpertsystemisbuiitinthispaperbydetailedanalysisofstructureandprincipleofvibratoryroadrollerandcomparisonofm
5、ainmethodsofbuildingfaultdiagnosissystem,thissystemcandiagnoseusualfaultofvibratoryroadroller.Inthispaper,analysisanddiagnosisoffaultmechanismofYZCl2Zintelligentroadroller,overalldesignoftheintelligentfaultdiagnosissystem,realizationofcriticaltechnologyof
6、theintelligentfaultdiagnosissystem,andloadinganddebuggingoftheintelligentfaultdiagnosissystemarediscussedinthispaper.Therearesomekeytechnologies,suchasknowledge1ibrary,ratiocinativemechanism,learningmechanism,expositorymechanism,databaseandtheinter-import
7、ingmechanismofneuralnetworkandexpertsysteminthisintelligentfaultdiagnosissysteIILTheknowledgelibrary,ratiocinativemechanismandlearningmechanisma11eonsistofneuralnetworkandexpertsystem,andtheyshouldbetreatedseparately.Inknowledge1ibrary。neuralnetworkisused
8、toindicatethesurfaceknowledge,soastoinstinctivelyassociatewithfaults,whileframeworksareusedtoindicatedeep-seatedknowledgetologicallyconfirmthediagnosis.Inratiocinativemechanism,neuralnetworkadoptrightdirectionalreas
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