Partial discharge source discrimination using a support vector machine

IEEE Transactions on Dielectrics and Electrical Insulation

Volumn 17, Issue 1, 2010, Pages 189-197

  Hao, L ^a   Lewin, P L ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Clustering methods; Correlation analysis; Partial discharges; Pattern recognition; Radio frequency current transducer; Signal processing; Support vector machine; Wavelet analysis

Indexed keywords

CLUSTERING METHODS; CONVENTIONAL MEASUREMENTS; CORRELATION ANALYSIS; DIFFERENT EFFECTS; DIGITAL STORAGE OSCILLOSCOPES; DISCHARGE SOURCE; EQUIPMENT MANUFACTURERS; FIELD MEASUREMENT DATA; HIGH-PERFORMANCE PERSONAL COMPUTERS; INSULATION PERFORMANCE; LABORATORY EXPERIMENTS; MACHINE LEARNING TECHNIQUES; MEASUREMENT DATA; ON LINE MEASUREMENT SYSTEM; P-D MODEL; PARTIAL DISCHARGE MEASUREMENTS; PARTIAL DISCHARGE SOURCES; POWER APPARATUS; POWER EQUIPMENT; POWER SYSTEMS; PROCESS MEASUREMENTS; RADIO FREQUENCY CURRENT TRANSDUCER; ROBUST PERFORMANCE; SOURCE IDENTIFICATION; WIDE BANDWIDTH;

CATHODE RAY OSCILLOSCOPES; CLUSTER ANALYSIS; COMPUTER CRIME; CORRELATION METHODS; DIGITAL RADIO; DIGITAL STORAGE; IMAGE RETRIEVAL; LEARNING ALGORITHMS; LIGHT MEASUREMENT; PARTIAL DISCHARGES; PATTERN RECOGNITION; PERSONAL COMPUTERS; RADIO; RADIO WAVES; SENSORS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; TRANSDUCERS; VECTORS; WAVELET ANALYSIS; WAVELET TRANSFORMS;

MEASUREMENTS;

EID: 77249107870     PISSN: 10709878     EISSN: None     Source Type: Journal    
DOI: 10.1109/TDEI.2010.5412017     Document Type: Article

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