Recognition and Classification of Incipient Cable Failures Based on Variational Mode Decomposition and a Convolutional Neural Network

Jiaying Deng,Wenhai Zhang,Xiaomei Yang

doi:10.3390/en12102005

Jiaying Deng, Wenhai Zhang + Show 1 more

Open Access

https://doi.org/10.3390/en12102005

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Abstract

To avoid power supply hazards caused by cable failures, this paper presents an approach of incipient cable failure recognition and classification based on variational mode decomposition (VMD) and a convolutional neural network (CNN). By using VMD, the original current signal is decomposed into seven modes with different center frequencies. Then, 42 features are extracted for the seven modes and used to construct a feature vector as input of the CNN to classify incipient cable failure through deep learning. Compared with using the original signals directly as the CNN input, the proposed approach is more efficient and robust. Experiments on different classifiers, namely, the decision tree (DT), K-nearest neighbor (KNN), BP neural network (BP) and support vector machine (SVM), and show that the CNN outperforms the other classifiers in terms of accuracy.

Highlights

The development process of cable failure is usually divided into three stages: the partial discharge period, incipient failure period and permanent failure period [1]
This paper presents a new approach for incipient cable failure recognition and classification on feature extraction and variational mode decomposition (VMD), features of each decomposed based on VMD feature extraction and convolutional neural network (CNN) classification (Figure 1)
Applies the softmax function as Figure 3 shows the flowchart of recognition and classification of incipient cable failure based on VMD and and CNN

Summary

Introduction

The development process of cable failure is usually divided into three stages: the partial discharge period, incipient failure period and permanent failure period [1]. Due to defect formation, corrosion or aging of the insulating layer, a series of partial discharge pulses first appear in the cable, forming electrical or water branches. With further deterioration, these branches would evolve into incipient failures accompanied by arcing. Because of the similarity with other disturbances, e.g., overcurrents caused by transformer inrush current, constant impedance and capacitor switching failures, it is relatively difficult to recognize incipient cable failures accurately. It is of great significance for the stable operation of power grid to achieve an approach that can effectively recognize and classify incipient cable failures and to complete cable maintenance in time before incipient failures become permanent failures

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Discussion

Conclusion