Recognition of Fused Partial Discharge Patterns in High Voltage Insulation Systems: A Hybrid DCNN and SVM Based Approach

Abstract

The performance assessment of insulation materials within the components of a high voltage power system depends upon effective condition monitoring techniques of the insulation. One of the important phenomena to be considered in the diagnostics and performance assessment of high voltage insulation materials is the Partial Discharge (PD) measurement. The improved Deep learning techniques help in the effective identification and classification of various sources of PD mechanism. In this work, Deep Convolution Neural Network (DCNN) technique is proposed for the fusion of several features that are extracted from the PD signals. Three-dimensional Phase Resolved patterns of PD images can be used for training the DNN. For the classification of PD patterns, linear and non-linear type of multi-class support vector machine has been proposed. The results obtained are compared with linear SVM and non-linear SVMs with the polynomial kernel, Radial Basis Function (RBF) kernel, and Sigmoidal kernel. The SVM type with a higher pattern recognition rate is identified to be effective in PD pattern recognition and classification. The results of the proposed work show that the fusion approach of PD patterns supports applying huge PD data sets as input, generated by multiple faults, for effective PD pattern recognition.

KEYWORDS:

• Deep learning
• Edge detection techniques
• Feature extraction
• Fuseddeep convolution neural network
• Image fusion
• Partial discharge
• Pattern recognition

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

I. Aruna Devi

I Aruna Devi received her BE degree in electrical and electronics engineering and ME in high voltage engineering from National Engineering College, Kovilpatti, affiliated to Anna University, Chennai, Tamilnadu, India. She works as a senior lecturer in the Department of Electrical and Electronics Engineering, Sri Ramana Institute of Polytechnic College, Tirunelveli, Tamilnadu, India. She has comprehensive publications in Scopus indexed journals & conferences. Currently, she is carrying research in the areas of partial discharge, dielectrics, and soft computing.

R.V. Maheswari

R V Maheswari was born in Tirunelveli District, Tamilnadu, India in March 1977. She received BE in electrical and electronics engineering in 2000 at Government College of Engineering, Tirunelveli and ME (High Voltage Engineering) in 2008 at National Engineering College, Kovilpatti. She completed her PhD degree in the faculty of Electrical Engineering, Anna University, Chennai. She is currently working as a professor in EEE Department of the National Engineering College, Kovilpatti. She has more than two decades of teaching experience in Engineering Institutions and has published twenty papers in international conferences and more than ten papers in well reputed international journals. She is a life member of Indian Society for Technical Education and associate member of Institution of Engineers (India). Her research interests are characteristics of partial discharge, numerical analysis, pattern recognition and modeling of partial discharge. Email: [email protected]

R. Rajesh

R Rajesh was born in Coimbatore District, Tamil Nadu, India, in March 1994. He received BE in instrumentation and control engineering from PSG College of Technology, Coimbatore, India in 2015, and the ME in control and instrumentation engineering from Anna University Regional Campus, Coimbatore, India in 2018. Currently pursuing PhD at Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India. His research area includes naturally inspired algorithms, linear control theory, nonlinear control system, adaptive control system, optimal control theory, advanced process control, vehicle dynamics, electrical systems  testing and measurements. Email: [email protected]