Fault diagnosis of insulators from ultrasound detection using neural networks

Author:

Frizzo Stefenon Stéfano1,Silva Marcelo Campos1,Bertol Douglas Wildgrube1,Meyer Luiz Henrique2,Nied Ademir1

Affiliation:

1. Department of Electrical Engineering, Santa Catarina State University (UDESC), Paulo Malschitzki 200 (Zona Industrial Norte), Joinville SC, Brazil

2. Department of Electrical Engineering, Regional University of Blumenau (FURB), São Paulo 3250 (Itoupava Seca), Blumenau SC, Brazil

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference39 articles.

1. Ilhan S. , Ozdemir A. , Jayaram S. and Cherney E. , Simulations of pollution and their effects on the electrical performance of glass suspension insulators, in Electrical Insulation and Dielectric Phenomena, Montreal, Canada: (CEIDP), 2012, 803–806.

2. Detection and classification of defects in ceramic insulators using RF antenna;Anjum;IEEE Transactions on Dielectrics and Electrical Insulation

3. Stefenon S.F. , Meyer L.H. and Molina F.H. , Real Time Automated Diagnosis of Insulating System Employng Ultrasound Inspection, in XXIII International Conference on Electricity Distribution, Lyon, France: CIRED, 2015.

4. Patel B. , Paranjape R. , Mehrandezh M. and Zhang L. , Ultrasonic inspection of underwater guy wires with applications to floating oil platforms, in IEEE Canadian Conference on Electrical and Computer Engineering, Vancouver, Canada: CCECE, 2016.

5. RF-Based Monitoring and Classification of Partial Discharge on Wet Silicone Rubber Surface;Shurrab;IEEE Transactions on Dielectrics and Electrical Insulation,2013

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