Comparison of the performance of artificial neural networks and Fuzzy logic for recognizing different partial discharge sources

Energies

Volumn 10, Issue 7, 2017, Pages

  Mas'ud, Abdullahi Abubakar ^a   Ardila Rey, Jorge Alfredo ^b   Albarracín, Ricardo ^c   Muhammad Sukki, Firdaus ^d   Bani, Nurul Aini ^e  

^a JUBAIL INDUSTRIAL COLLEGE   (Saudi Arabia)

^b DEPARTAMENTO DE FÍSICA   (Chile)

^c School of Industrial Engineering   (Spain)

^d ROBERT GORDON UNIVERSITY   (United Kingdom)

^e UTM RAZAK SCHOOL OF ENGINEERING AND ADVANCED TECHNOLOGY   (Malaysia)

Author keywords

Artificial neural network; Fuzzy logic; Partial discharge; Polyethylene terephthalate

Indexed keywords

COMPUTER CIRCUITS; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; NEURAL NETWORKS; PARTIAL DISCHARGES; PLASTIC BOTTLES; POLYETHYLENE TEREPHTHALATES; SURFACE DISCHARGES;

ANGULAR POSITIONING; DEFECT CLASS; DIFFERENT VOLTAGES; PARTIAL DISCHARGE SOURCES; PD CLASSIFICATION; PD DETECTIONS; POLYETHYLENE TEREPHTHALATES (PET); TRAINING AND TESTING;

FUZZY LOGIC;

EID: 85029061428     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en10071060     Document Type: Article

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