Power transformers internal fault diagnosis based on deep convolutional neural networks

• Published in: Journal of intelligent & fuzzy systems Vol. 37; no. 1; pp. 1165 - 1179
• Main Authors: Afrasiabi, Mousa, Afrasiabi, Shahabodin, Parang, Benyamin, Mohammadi, Mohammad
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2019; Sage Publications Ltd
• Subjects: Artificial neural networks; Computer simulation; Current limiters; Dependence; Discrimination; Error compensation; Fault diagnosis; Feature extraction; Inrush current; Neural networks; Noise sensitivity; Reliability analysis; Spectrum analysis; System reliability; Transformers; Power transformer protection; Convolutional neural network (CNN); Inrush current; Differential protection

Differential protection of power transformers, as the fundamental protection, plays an important role in power system reliability and security. The main challenge in differential protection is discrimination between internal faults of power transformers and inrush current. Development of differentia...