溫度影響下空心板橋鉸接縫損傷識別方法研究

溫度影響下空心板橋鉸接縫損傷識別方法研究摘要：

本文在考慮溫度影響下，運用激光掃描等技術，研究了空心板橋的鉸接縫損傷識別方法。該方法通過數(shù)字化的方式獲取鉸接縫的高清三維模型，從而實現(xiàn)對其缺陷及損傷的檢測與識別。首先，本文總結了現(xiàn)有損傷識別方法的不足之處，提出了完善的針對高清三維模型的損傷識別方法。其次，針對激光掃描之后獲取的鉸接縫數(shù)據進行了預處理和優(yōu)化，以便更好地分析其結構特性。加權最小二乘算法被用于計算并擬合出可以準確描述缺陷與損傷的曲面，進而利用曲面和其法向量求出特征點。最后，根據特征點對缺陷類型進行了分類，并進行了實驗驗證。結果表明，所提出的方法能夠有效地發(fā)現(xiàn)鉸接縫的各種損傷，準確地識別缺陷類型與位置。

關鍵詞：空心板橋、鉸接縫、損傷識別、激光掃描、三維模型。

Abstract:

Thispaperstudiesthedamageidentificationmethodforthehingejointsofhollowslabbridgesundertheinfluenceoftemperatureusinglaserscanningtechnology.Thismethoddigitizesandobtainsthehigh-definitionthree-dimensionalmodelofthehingejoint,thusachievingdetectionandidentificationofitsdefectsanddamages.Firstly,thispapersummarizestheshortcomingsofexistingdamageidentificationmethodsandproposesimproveddamageidentificationmethodsforhigh-definitionthree-dimensionalmodels.Secondly,thehingejointdataobtainedafterlaserscanningwerepreprocessedandoptimizedtobetteranalyzetheirstructuralcharacteristics.Theweightedleastsquaresalgorithmwasusedtocalculateandfitthesurfacethataccuratelydescribesthedefectsanddamages,andthenthefeaturepointswereobtainedusingthesurfaceanditsnormalvector.Finally,thedefecttypeswereclassifiedaccordingtothefeaturepoints,andtheexperimentalverificationwascarriedout.Theresultsshowthattheproposedmethodcaneffectivelydetectvariousdamagesofthehingejoint,accuratelyidentifythetypesandpositionsofdefects.

Keywords:hollowslabbridge,hingejoint,damageidentification,laserscanning,three-dimensionalmodel。Additionally,theproposedmethodalsohastheadvantagesofhighefficiencyandaccuracy,asthelaserscanningandthree-dimensionalmodelingprocesscanbecompletedquicklyandaccurately,andthefeaturepointscanbepreciselyextractedtoclassifythedefecttypeswithhighaccuracy.Comparedwithtraditionalinspectionmethods,suchasvisualinspectionandultrasonictesting,theproposedmethodavoidsthesubjectiveinfluenceofhumanjudgmentandcanprovidemoredetailedandreliableinformationabouttheconditionofthehingejoint.

Furthermore,theproposedmethodcanalsobeusedforthelong-termhealthmonitoringofthehingejoint,asthethree-dimensionalmodelcanbeupdatedregularlytotracktheconditionchangesofthehingejointovertime.Thiscanprovideearlywarningofpotentialdefectsandhelptopreventcatastrophicfailures.

Inconclusion,theproposedlaserscanningandthree-dimensionalmodelingmethodprovidesaneffectiveandaccurateapproachforthedetectionandclassificationofvariousdamagesinhollowslabbridgehingejoints.Themethodhasgreatpotentialforpracticalapplicationsinbridgemaintenanceandmanagement,andcancontributetothesafetyandreliabilityofbridgestructures。Moreover,themethodcanalsobeappliedtoothertypesofbridgesorstructureswithsimilarhollowslabhingejoints.Forinstance,jackedboxculverts,undergroundtunnels,andburiedpipelinescanallbeinspectedusingthisapproach.

Itisworthnotingthatthismethodrequiresspecializedequipmentandskilledprofessionalstoperformthelaserscanningand3Dmodeling.Therefore,itmaynotbefeasibleforsmallerbridgeownersorcontractorstoadoptthistechnique.However,astechnologyadvancesandbecomesmoreaccessible,itislikelythatthismethodwillbecomemorewidelyadoptedandcost-effective.

Inaddition,thedataobtainedfromthelaserscanningand3Dmodelingcanalsobeusedtogeneratedetailedreportsandvisualizationsforbridgeownersandmanagers.Thiscanaidinthedecision-makingprocessforrepairs,refurbishmentsorreplacements.

Overall,thisproposedmethodisapromisingapproachfortheinspectionandmaintenanceofhollowslabbridgehingejoints.Byprovidingaccurateandreliabledata,itcanhelpbridgeownersandmanagersefficientlydetectandclassifyvariousdamagesandpreventcatastrophicfailures.Withfurtherresearchanddevelopment,thismethodmaybecomeastandardandessentialtoolinthebridgemaintenanceandmanagementindustry。Inadditiontotheproposedmethodforinspectinghollowslabbridgehingejoints,thereareothertechniquesandtechnologiesthatcanbeusedtoassesstheconditionandperformanceofbridges.Someoftheseinclude:

1.Non-destructivetesting(NDT):NDTisagroupoftestingmethodsthatcandetectdefects,corrosion,andotherdamagesinmaterialsandstructureswithoutcausinganyharmtothem.ExamplesofNDTmethodsthatcanbeusedforbridgeinspectionsincludeultrasonictesting,magneticparticletesting,acousticemissiontesting,andvisualinspection.

2.Structuralhealthmonitoring(SHM):SHMisasystemforcontinuouslymonitoringthestructuralbehaviorofabridgeduringitsoperation.Itusessensorstomeasurevariousparameterssuchasstrain,vibration,temperature,anddeformation,andtransmitsthedatatoacentraldatabaseforanalysis.SHMcanprovideearlywarningofpotentialfailuresandhelpoptimizemaintenanceactivities.

3.Remotesensing:Remotesensingreferstotheuseofaerialphotography,LiDAR(LightDetectionAndRanging),andotherimagingtechnologiestoobtaininformationaboutthephysicalcharacteristicsandconditionofabridge.Thiscanhelpidentifyareasofconcernthatmaynotbevisiblefromthegroundandprioritizemaintenanceactivities.

4.Finiteelementanalysis(FEA):FEAisacomputersimulationtechniquethatcanbeusedtoanalyzethestructuralbehaviorofabridgeundervariousloadingconditions.Itcanhelppredicttheperformanceofabridgeovertimeandidentifyareasofconcernthatmayrequiremaintenanceorrepair.

Bycombiningthesetechniquesandtechnologies,bridgeownersandmanagerscangainacomprehensiveunderstandingoftheconditionandperformanceoftheirbridgesandmakeinformeddecisionsaboutmaintenanceandrepairactivities.Asthedemandforinfrastructuregrowsandexistingbridgescontinuetoage,theuseofadvancedinspectionandmonitoringmethodswillbecomeevenmorecriticalforensuringthesafetyandreliabilityofourtransportationsystem。Furthermore,theuseofadvancedinspectionandmonitoringmethodscanalsohelptoextendthelifespanofbridges,ultimatelysavingmoneyinthelong-term.Bydetectingandaddressingpotentialissuesearlyon,bridgeownersandmanagerscanavoidmorecostlyrepairsoreventheneedforreplacement.Thisproactiveapproachcanalsoleadtofewerdisruptionstotransportationservices,asrepairsormaintenanceactivitiescanbescheduledatconvenienttimestominimizeimpactontravelers.

Inadditiontotraditionalinspectionmethods,technologicaladvancementssuchasdrones,sensors,andartificialintelligencearerevolutionizingbridgeinspectionandmonitoring.Dronescanprovideabird's-eyeviewofbridges,allowinginspectorstoidentifyissuesthatmaynotbevisiblefromgroundlevel.Sensorsembeddedinbridgecomponentscandetectchangesintemperature,strain,andhumidity,providingreal-timedataontheconditionofthebridge.Artificialintelligencecanthenanalyzethegathereddata,providinginsightsandpredictionsforfuturemaintenanceneeds.

Despitethebenefitsofadvancedinspectionandmonitoringmethods,therearestillchallengestobeaddressedinwidespreadimplementation.Onekeychallengeisthecostofthesetechnologies,whichmaybeprohibitiveforsmallerorganizations.Thereisalsoaneedforstandardizedprotocolstoensureconsistencyandaccuracyininspectionsacrossdifferentjurisdictionsandorganizations.Additionally,theremaybeconcernsarounddataprivacyandcybersecurity,asthetechnologyusedforbridgeinspectionsandmonitoringmaycollectsensitiveinformation.

Inconclusion,bridgesareacriticalcomponentofourtransportationinfrastructure,andensuringtheirsafetyandreliabilityrequiresamultifacetedapproach.Advancedinspectionandmonitoringmethodscanprovidevaluableinsightsintotheconditionandper