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developmentofpartialdischargesinvarioustypesofconstructionsofinsulationsys-
temswithdifferentnominalparametersaswellastheimpactofoperationalexposures;
inparticular,multi-stresses(e.g.,electrical,thermal,andmechanical),whoseinfluence
acceleratestheprocessesofphysicalandchemicalchangesindielectricstructures.
Partialdischargesareoftennotevendetectableduringthemanufacturingand
testprocessesofpowerequipment;theycandevelopduringoperationinthefield.
Thus,thediagnosticsofpowerequipmentisparticularlyimportantinthiscontext
duetobothoperationalmulti-stressesandthestrivingforhigherandhighervoltage
levelsaswellasduetoincreasingrequirementswithrespecttothesafetyandreliability
ofelectricpower.Inthisaspect,exploitationstrategiesconsiderpartialdischargesas
oneofthekeyparametersofnon-invasiveandnon-destructivediagnosticandmonitor-
ingsystems.
Partialdischargeshaveintriguedresearchersformorethanacentury,yetsome
underlyingphysicalmechanismsarestillnotfullyunderstoodandrequireamulti-
-physicalresearchapproach.Thebookpresentsselectedaspectsrelatedtothepartial
dischargemechanism,itsprocessing,anditsanalyticsinhigh-voltageinsulatingsys-
tems.Thefirstblockthatcomprisesapartialdischargemechanismstartswiththeun-
derlyingphysicalphenomenainastrongelectricfieldthatleadtoionizationeffects
aswellasdischargedevelopmentandpropagation.Then,variouspartialdischarge-
-detectionmethodsareconsidered,withaspecialfocusonelectricalmeasurements
andopticalimaging.Withrespecttohigh-voltagestimuli,differentwaveformsarein-
vestigated,suchasAC(includingitsharmoniceffects),DC,PWM,andimpulsevoltag-
es.Theseparateclassreferstonon-continuousPDsequencingcalledPDchoppingand
thediscoveredassociatedphenomenoncalledPDEcho.Thisnovelmethodologyis
presentedintermsofpartialdischargemeasurement,detection,andinterpretation.
Thesecondpartpresentspartialdischargeprocessing(i.e.,fromacquisitiontodigital
signalandimageprocessing),includingphysicalaspectssuchasthemappingofdis-
chargeclustersandthemorphologyofdeteriorationcausedbydischarges.Themain
domainoftheanalysisconcernsthephase-resolvedPDpatternsthatreflectdifferent
formsofdischarges.Thisestablishedmethodofdischarge-formvisualizationisusedin
bothlaboratoryexperimentsandon-sitemeasurementsonhigh-voltagepowerequip-
ment.Theharshindustrialenvironmentanddisturbancesoftenrequirethedenoising
ofanyacquiredsignalsandimages.Inthiscontext,theapplicationofwaveletsispre-
sentedinthisbook.Thethirdpart(calledpartialdischargeanalytics)referstotheap-
plicationofartificialintelligencetopartialdischarges;forexample,tofeatureextrac-
tion,clustering,orsegmentationaswellasclassificationbasedondeepconvolutional
neuralnetworks.Inthecaseoffuturemonitoringsystems,theautonomoustrackingof
partialdischargepatternevolutionshowsacertainnewdirection.
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