预览加载中,请您耐心等待几秒...
1/2
2/2

在线预览结束,喜欢就下载吧,查找使用更方便

如果您无法下载资料,请参考说明:

1、部分资料下载需要金币,请确保您的账户上有足够的金币

2、已购买过的文档,再次下载不重复扣费

3、资料包下载后请先用软件解压,在使用对应软件打开

基于机器视觉的电机转子质量在线检测系统研究 Title:ResearchonOnlineMassInspectionSystemforElectricMotorRotorsBasedonMachineVision Abstract: Thequalityofelectricmotorrotorsplaysacrucialroleintheoverallperformanceandefficiencyofelectricmotors.Traditionalmethodsforrotormassinspectionaretime-consuming,labor-intensive,andlackaccuracy.Toaddressthesechallenges,thisresearchaimstodevelopanonlinemassinspectionsystemforelectricmotorrotorsbasedonmachinevision.Theproposedsystemutilizesmachinevisiontechniquestodetectandmeasurethemassoftherotor,providingreal-timefeedbackonthequalityoftherotor.Thispaperpresentsanin-depthanalysisoftheresearchonmachinevision-basedmassinspectionsystems,highlightingtheiradvantages,challenges,andpotentialapplications.Theexperimentalsetupandproceduresaredescribedindetail,followedbytheperformanceevaluationandcomparisonwithtraditionalmethods.Theresultsindicatethatthedevelopedonlinemassinspectionsystembasedonmachinevisionoffershighaccuracy,efficiency,andreliabilityforrotorqualityassessment.Thefindingsofthisresearchcontributetoenhancingthequalitycontrolandproductionefficiencyofelectricmotorrotors,therebypromotingtheoveralldevelopmentoftheelectricmotorindustry. 1.Introduction 1.1Background 1.2ResearchObjectives 1.3ScopeoftheStudy 2.LiteratureReview 2.1MassInspectionTechniquesforElectricMotorRotors 2.2MachineVisionTechniques 2.3ApplicationsofMachineVisioninQualityControl 3.Methodology 3.1SystemOverview 3.2ImageAcquisition 3.3ImagePre-processing 3.4ImageSegmentation 3.5MassMeasurementAlgorithm 3.6SystemIntegrationandDevelopment 4.ExperimentalSetup 4.1HardwareComponents 4.2SoftwareTools 4.3ExperimentalProcedures 5.ResultsandDiscussion 5.1PerformanceEvaluationMetrics 5.2ComparisonwithTraditionalMethods 5.3AnalysisofExperimentalResults 5.4DiscussiononSystemPerformance 6.Conclusion 6.1SummaryoftheStudy 6.2ContributionsandPotentialApplications 6.3FutureResearchDirections 7.References Thefullpaperwillprovideanin-depthunderstandingoftheresearchonmachinevision-basedmassinspectionsystemsforel