Application of information fusion to recognition of partial discharge in transformer

Gaodianya Jishu/High Voltage Engineering

Volumn 38, Issue 3, 2012, Pages 553-559

  Chen, Xingang ^a,b   Tian, Xiaoxiao ^a   Zhao, Yangyang ^a   Zhang, Chaofeng ^a  

^a CHONGQING UNIVERSITY OF TECHNOLOGY   (China)

^b CHONGQING UNIVERSITY   (China)

Author keywords

Correspondence relationship; Dissolved gas analysis(DGA); Information fusion; Neural network; Partial discharge(PD); Pattern recognition

Indexed keywords

BOOST PRESSURE; BP NEURAL NETWORKS; CHARACTERISTIC PARAMETER; CORRESPONDENCE RELATIONSHIP; DEVELOPMENT PROCESS; DEVELOPMENT TRENDS; DISCHARGE CAPACITIES; DISCHARGE FREQUENCY; DISCHARGE MODELS; DISCHARGE PROPERTIES; DISCHARGE TYPES; DISSOLVED GAS; DISSOLVED GAS ANALYSIS; DISSOLVED GASES IN OIL; EXPERIMENTAL MODELS; GAS FEATURES; INFORMATION FUSION METHOD; INTERNAL INSULATION; LATENT DEFECTS; OIL PAPER INSULATION; PARTIAL DISCHARGE CHARACTERISTICS; PARTIAL DISCHARGE SIGNAL; RBF NEURAL NETWORK; RELIABLE OPERATION; SPECTROGRAMS; STATISTICAL CHARACTERISTICS;

DISSOLUTION; ELECTRIC PROPERTIES; GASES; INFORMATION FUSION; NEURAL NETWORKS; PATTERN RECOGNITION;

PARTIAL DISCHARGES;

EID: 84859737388     PISSN: 10036520     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1003-6520.2012.03.006     Document Type: Article

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