Transmission Power Line Fault Detection using Convolutional Neural Networks

Abstract

: In an electrical power system, most of the faults occurs in overhead transmission lines because of most of the conductor exposure to the atmosphere. Therefore, Insulated Overhead Conductors (IOCs) are widely used. To overcome this, a robust real-time PD fault analysis system is required. To analyze and classify the raw voltage signal for detection of PD's in IOC's a Convolutional Neural Network (CNN) based fault classification algorithm is proposed in this paper. The CNN is implemented using popular pre-trained CNN architectures such as AlexNet, VGG16 & ResNet are applied to the voltage signals in the dataset. From the values of Precision, Recall & F1-Score it is observed that ResNet architecture provides the best prediction and classification results.