Convolutional Neural Network and Transfer Learning for High Impedance Fault Detection

Rui Fan; Tianzhixi Yin

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arXiv · 1904.08863

Convolutional Neural Network and Transfer Learning for High Impedance Fault Detection

Rui Fan·Tianzhixi Yin

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Abstract

This letter presents a novel high impedance fault (HIF) detection approach using a convolutional neural network (CNN). Compared to traditional artificial neural networks, a CNN offers translation invariance and it can accurately detect HIFs in spite of variance and noise in the input data. A transfer learning method is used to address the common challenge of a system with little training data. Extensive studies have demonstrated the accuracy and effectiveness of using a CNNbased approach for HIF detection.

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BibTeX RIS

Rui Fan, Tianzhixi Yin. 2019-04-18. Convolutional Neural Network and Transfer Learning for High Impedance Fault Detection. https://arxiv.org/abs/1904.08863

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