Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network

IET Science, Measurement and Technology

Volumn 4, Issue 3, 2010, Pages 177-192

  Evagorou, D ^a   Kyprianou, A ^a   Lewin, P L ^b   Stavrou, A ^c   Efthymiou, V ^c   Metaxas, A C ^d   Georghiou, G E ^a  

^a UNIVERSITY OF CYPRUS   (Cyprus)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c Electricity Authority of Cyprus   (Cyprus)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPLIED VOLTAGES; CHARACTERISATION; CORONA DISCHARGES; FEATURE EXTRACTION AND CLASSIFICATION; FEATURE SPACE; FEATURE VECTORS; HIGH VOLTAGE LABORATORIES; HIGH-FREQUENCY CURRENT TRANSFORMERS; HIGH-VOLTAGE EQUIPMENTS; PARTIAL DISCHARGE SIGNAL; PD CLASSIFICATION; POWER CABLES; PROBABILISTIC NEURAL NETWORKS; PROBABILITY DENSITY FUNCTION (PDF); WAVELET COEFFICIENTS; WAVELET PACKET; WAVELET PACKET TRANSFORMS;

ALGORITHMS; ELECTRIC CORONA; ELECTRIC TRANSFORMERS; FEATURE EXTRACTION; PARTIAL DISCHARGES; PROBABILITY DENSITY FUNCTION; WAVELET TRANSFORMS;

NEURAL NETWORKS;

EID: 78651500131     PISSN: 17518822     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-smt.2009.0023     Document Type: Article

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