Partial discharge classification using deep learning methods - Survey of recent progress

Energies

Volumn 12, Issue 13, 2019, Pages

  Barrios, Sonia ^a   Buldain, David ^b   Comech, María Paz ^b   Gilbert, Ian ^a   Orue, Iñaki ^a  

^a Ormazabal Corporate Technology   (Spain)

^b UNIVERSITY OF ZARAGOZA   (Spain)

Author keywords

Deep learning; Deep neural network; Fault diagnosis; Fault recognition; Machine learning; Partial discharges

Indexed keywords

AUTOMATION; DATA ACQUISITION; DATA MINING; DEEP LEARNING; DIGITAL STORAGE; FAILURE ANALYSIS; LEARNING SYSTEMS; MACHINE LEARNING; PARTIAL DISCHARGES; STRUCTURAL OPTIMIZATION;

AUTOMATED FEATURES; AUTOMATED IDENTIFICATION; CLASSIFICATION AND RECOGNITION; ELECTRICAL EQUIPMENT; FAULT RECOGNITION; LEARNING METHODS; OPERATIONAL CONDITIONS; PARTIAL DISCHARGE CLASSIFICATION;

DEEP NEURAL NETWORKS;

EID: 85068444913     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en12132485     Document Type: Review

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