基于视频端AI算法实现的矿井斜巷联动联控系统研究

基于视频端AI算法实现的矿井斜巷联动联控系统研究摘要：

在煤炭等矿井斜巷联动联控系统中，视频端算法作为一种新型的技术手段，可以在矿井生产过程中，对矿井内部的安全状况、设备状态、作业流程等情况进行实时监控，并对异常情况进行智能预警和预测分析，从而提高斜巷的安全性和生产效率。本文基于视频端算法，研究并实现了矿井斜巷联动联控系统的智能监控和控制功能。首先，对视频图像进行处理和分析，实现对矿井内部设备状态和作业流程的实时监控；然后，通过深度学习和数据挖掘等技术手段，对监测数据进行处理和分析，实现对矿井内部异常情况的自动识别和预测。最后，将监控结果传输到联动联控系统，实现对斜巷的自动调节和控制。实验结果表明，本算法可以有效地监控矿井斜巷的生产安全和生产效率，具有较好的应用前景和推广价值。

关键词：视频端算法；矿井斜巷联动联控系统；智能监控；深度学习；数据挖掘

Abstract:

Inthemininginclinedroadwaylinkagecontrolsystem,videoendalgorithmasanewtechnology,canbeintheminingproductionprocess,thesafetysituationinsidethemine,equipmentstatus,theoperationprocesssuchasreal-timemonitoring,andintelligentpredictionanalysisofabnormalsituation,thusimprovingthesafetyandproductionefficiencyofinclinedroadway.Inthispaper,basedonthevideoendalgorithm,westudiedandimplementedtheintelligentmonitoringandcontrolfunctionofthemininginclinedroadwaylinkagecontrolsystem.First,thevideoimageisprocessedandanalyzedtoachievereal-timemonitoringofequipmentstatusandoperationprocessinsidethemine;then,throughdeeplearninganddataminingandothertechnicalmeans,themonitoringdataisprocessedandanalyzedtoachieveautomaticidentificationandpredictionofabnormalsituationsinsidethemine.Finally,themonitoringresultistransmittedtothelinkagecontrolsystemtoachieveautomaticadjustmentandcontroloftheinclinedroadway.Theexperimentalresultsshowthatthisalgorithmcaneffectivelymonitortheproductionsafetyandproductionefficiencyofmininginclinedroadway,andhasgoodapplicationprospectandpromotionvalue.

Keywords:Videoendalgorithm;mininginclinedroadwaylinkagecontrolsystem;intelligentmonitoring;deeplearning;datamininMiningisahigh-riskindustrythatrequiresconstantmonitoringtoensurethesafetyofworkersandtheefficientoperationofmachinery.Inparticular,inclinedroadwaysplayacriticalroleinundergroundmining,astheyprovideaccesstodeepandremoteareasofthemine.However,thecomplexgeologyandharshworkingconditionsofinclinedroadwaysmaketheirmonitoringandmaintenanceachallengingtask.

Inrecentyears,videomonitoringsystemshaveemergedasaneffectivetoolforthereal-timemonitoringofminingoperations.However,thevastamountofvideodatageneratedbythesesystemspresentsanotherchallenge.Toaddressthis,researchershaveproposedtheuseofvideoendalgorithms,whichcanautomaticallyanalyzeandinterpretvideodatatoextractactionableinformation.

Inthispaper,weproposeanintelligentmonitoringsystemformininginclinedroadwaysbasedonvideoendalgorithms.Thesystemconsistsofavideomonitoringsystem,alinkagecontrolsystem,andanintelligentmonitoringmodule.Thevideomonitoringsystemcapturesandrecordsthereal-timevideodataoftheinclinedroadway,whicharethentransmittedtotheintelligentmonitoringmodule.

Theintelligentmonitoringmoduleusesacombinationofdeeplearninganddataminingtechniquestoanalyzethevideodataandextractrelevantinformationsuchasthespeedanddirectionoftheminingequipment,thevolumeoforebeingextracted,andtheconditionoftheroadway.Thisinformationisthenprocessedandtransmittedtothelinkagecontrolsystem,whichcanautomaticallyadjustandcontroltheinclinedroadwaytoensurebothsafetyandefficiency.

Ourexperimentalresultsdemonstratethatourproposedalgorithmiseffectiveinmonitoringtheproductionsafetyandefficiencyofmininginclinedroadways.Moreover,thisalgorithmhassignificantapplicationprospectsandpromotionalvalueintheminingindustry.

Inconclusion,theintegrationofintelligentvideomonitoringsystemsandadvanceddataanalyticstechniqueshasenormouspotentialtotransformtheminingindustrybyimprovingthesafetyofworkers,optimizingproductionefficiency,andminimizingdowntime.WehopethatourproposedsystemcancontributetotheseeffortsandinspirefurtherresearchinthisfieldTheminingindustryhasbeenknownforitshazardousandphysicallydemandingworkingconditions.However,withtheintegrationofintelligentvideomonitoringsystemsandadvanceddataanalyticstechniques,miningoperationscanbemadesafer,moreefficient,andmoreproductive.

Oneareawhereintelligentvideomonitoringsystemscanbeincorporatedisinthesafetyofworkers.Miningsitescanbeequippedwithcamerasthatcandetectpotentialsafetyhazardsandalertworkersviawearabledevices.Forinstance,camerasmountedondronescanbeusedtomonitorminingsitesinreal-time,whichcanhelppreventaccidentsandimprovesafetyprotocols.Wearablessuchassmarthelmetscanalsoprovideminerswithpertinentsafetydata,suchastemperature,airquality,andradiationlevels,whichcanhelppreventaccidentsandillness.

Anotherareawheredataanalyticscanbeusefulisintheoptimizationofproductionefficiency.Bymonitoringkeyperformanceindicators(KPIs)suchasmachineutilization,downtime,andcycletimes,miningoperationscanbeoptimizedtorunmoreefficiently,resultinginshorterproductionleadtimes,lowercosts,andhigherprofits.Additionally,dataanalyticscanhelpidentifyandpredictequipmentfailures,improvingmaintenanceschedulesandminimizingdowntime.

Lastly,dataanalyticscanbeusedtoanalyzethegeologyofmines.Byintegratinggeologicaldatawithvideomonitoring,minescanbemappedin3Dmodels,allowingforexplorationandextractionplanning.Additionally,computervisioncanbeusedtoidentifymineralsandrocks,makingoreprocessingmoreefficient.

Overall,theintegrationofintelligentvideomonitoringsystemsanddataanalyticshasenormouspotentialtotransformtheminingindustry.Theuseofcameras,wearables,anddataanalyticscanmakeminingoperationssafer,moreefficient,andmoreproductive.However,furtherresearchanddevelopmentareneededtofullyharnessthepotentialoftheseinnovativetechnologiesOneareawhereintelligentvideomonitoringsystemsanddataanalyticscanplayamajorroleintheminingindustryisinassetmanagement.Equipmentfailurecanleadtocostlydowntime,aswellassafetyhazardstoworkers.Bymonitoringtheperformanceofmachinerythroughsensors,cameras,andwearables,dataanalyticscanhelppredictwhenmaintenanceisneeded,preventingcatastrophicfailuresandsubsequentlyavoidingdowntime.Additionally,dataanalyticscanhelpidentifypatternsinequipmentfailures,enablingcompaniestomakechangestotheirmaintenanceandrepairschedulestooptimizeefficiency.

Anotherareawhereintelligentvideomonitoringsystemsanddataanalyticscanbeusefulisinpredictingandpreventingaccidentsintheminingindustry.Byanalyzingpatternsinworkermovementsandbehavior,dataanalyticscanflaghigh-riskactivitiesandalertsupervisorstopotentialsafetyhazards.Wearabletechnologycanalsobeusedtomonitorvitalsignsanddetectearlysignsoffatigueorstress,enablingcompaniestotakepreventativemeasuresbeforeaccidentsoccur.

Intelligentvideomonitoringsystemsanddataanalyticscanalsohelpreducetheenvironmentalimpactofminingoperations.Bycollectingdataonairquality,waterquality,andnoiselevels,companiescanmonitortheirimpactontheenvironmentandtakestepstoreducetheirfootprint.Additionally,byanalyzingdataonenergyconsumptionandemissions,companiescanidentifyopportunitiestoreducetheircarbonfootprintandimprovesustainability.

However,theimplementationofintelligentvideomonitoringsystemsanddataanalyticsintheminingindustryisnotwithoutchallenges.Onemajorissueisdataprivacyandsecurity.Withtheincreasinguseofconnecteddevicesandsensors,vastamountsofdataarebeinggeneratedandstored.Keepingthisdatasecureandensuringthatitisnotmisusedorstolenisasignificantconcern.Additionally,thehighcostofimplementingthesetechnologiesmaybeabarrierforsmallerminingoperations.

Inconclusion,theintegrationofintel