Partial discharge pattern recognition of power cable joints using extension method with fractal feature enhancement

Expert Systems with Applications

Volumn 39, Issue 3, 2012, Pages 2804-2812

  Gu, Feng Chang ^a   Chang, Hong Chan ^a   Chen, Fu Hsien ^a   Kuo, Cheng Chien ^b  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b ST JOHN'S UNIVERSITY   (Taiwan)

Author keywords

Extension method; Fractal theory; Neural network; Partial discharge; Pattern recognition

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; DEFECT TYPE; DEGREE OF CORRELATIONS; EXTENSION METHOD; FAST RECOGNITION; FEATURE PARAMETERS; FRACTAL FEATURE; FRACTAL THEORY; LACUNARITY; MATTER-ELEMENT; MATTER-ELEMENT MODEL; PARTIAL DISCHARGE PATTERN RECOGNITION; PD DETECTOR; PD PATTERN; POWER CABLE JOINTS; RANDOM NOISE; RECOGNITION ACCURACY; XLPE POWER CABLES;

CABLE JOINTING; CABLES; DEFECTS; ELECTRIC TRANSFORMER TESTING; FRACTAL DIMENSION; INDUCTIVE SENSORS; NEURAL NETWORKS; PARTIAL DISCHARGES; SENSORS; TELECOMMUNICATION CABLES; THREE DIMENSIONAL;

FEATURE EXTRACTION;

EID: 80255123396     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.08.140     Document Type: Article

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