A novel extension neural network based partial discharge pattern recognition method for high-voltage power apparatus

Expert Systems with Applications

Volumn 39, Issue 3, 2012, Pages 3423-3431

  Chen, Hung Cheng ^a   Gu, Feng Chang ^a   Wang, Meng Hui ^a  

^a NATIONAL CHIN YI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Extension distance; Extension neural network; Fractal feature; Partial discharge; Pattern recognition

Indexed keywords

CLUSTERING PROBLEMS; COMPARATIVE STUDIES; CONTINUOUS INPUT; DEFECT MODEL; DEFECT TYPE; ELECTRICAL APPARATUS; EUCLIDEAN DISTANCE; EXTENSION DISTANCE; EXTENSION NEURAL NETWORKS; EXTENSION THEORY; FRACTAL FEATURE; HIGH-VOLTAGES; K-MEANS; LACUNARITY; NOISE TOLERANCE; PARTIAL DISCHARGE PATTERN RECOGNITION; PATTERN RECOGNITION METHOD; PD DETECTOR; PD PATTERN; POWER APPARATUS; THREE-DIMENSION;

DEFECTS; ELECTRIC TRANSFORMER TESTING; FEATURE EXTRACTION; FRACTAL DIMENSION; MULTILAYER NEURAL NETWORKS;

PARTIAL DISCHARGES;

EID: 80255124876     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.09.030     Document Type: Article

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