UHF Partial Discharge Pattern Recognition for GIS with Support Vector Machine


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Abstract


As partial Discharge (PD) can reflect the type of insulation defect and different types of PD do harm to gas insulated switchgear (GIS) in different ways, identifying the type of discharge correctly is of significant value to help ensure the safe and reliable operation, assess the insulation condition and make sensible maintenance strategy for GIS. In order to research the features of PD excited by different insulation defect models in GIS, four kinds of typical PD models are designed to simulate the actual insulation defects occurred during GIS operation. To describe the typical characteristics of PDs, eight feature parameters are extracted from the UHF signals acquired by experiments. A four-type Support Vector Machine Classifier is constructed based on Support Vector Machine (SVM) Algorithm, and then the PD type is identified by voting method. Experimental results show that the proposed method possesses a high recognition rate and can effectively identify these four types of GIS PD
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Keywords


Partial Discharge (PD); Gas Insulated Switchgear (GIS); Insulation Defect; Support Vector Machine (SVM); Pattern Recognition

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References


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