Abstract

Optical detection and ultrahigh frequency (UHF) detection are two significant methods of partial discharge (PD) detection in the gas-insulated transmission lines (GIL), however, there is a phenomenon of signals loss when using two types of detections to monitor PD signals of different defects, such as needle defect and free particle defect. This makes the optical and UHF signals not correspond strictly to the actual PD signals, and therefore the characteristic information of optical PD patterns and UHF PD patterns is incomplete which reduces the accuracy of the pattern recognition. Therefore, an image fusion algorithm based on improved non-subsampled contourlet transform (NSCT) is proposed in this study. The optical pattern is fused with the UHF pattern to achieve the complementarity of the two detection methods, avoiding the PD signals loss of different defects. By constructing the experimental platform of optical-UHF integrated detection for GIL, phase-resolved partial discharge (PRPD) patterns of three defects were obtained. After that, the image fusion algorithm based on the local entropy and the phase congruency was used to produce the photoelectric fusion PD pattern. Before the pattern recognition, 28 characteristic parameters are extracted from the photoelectric fusion pattern, and then the dimension of the feature space is reduced to eight by the principal component analysis. Finally, three kinds of classifiers, including the linear discriminant analysis (LDA), support vector machine (SVM), and k-nearest neighbor (KNN), are used for the pattern recognition. The results show that the recognition rate of all the photoelectric fusion pattern under different classifiers is higher than that of optical and UHF patterns, up to the maximum of 95%. Moreover, the photoelectric fusion pattern not only greatly improves the recognition rate of the needle defect and the free particle defect, but the recognition accuracy of the floating defect is also slightly improved.

Highlights

  • In recent years, gas-insulated transmission lines (GIL) are widely used in the power transmission of hydropower stations and nuclear power plants because of their high efficiency, large transmission capacity, high reliability, and small footprint [1,2,3].In the operation of GIL, partial discharge (PD) is a precursor in the deterioration of insulation performance, which is the main cause of a breakdown

  • In order to improve the accuracy of PD pattern recognition in the GIL, this study proposes an image fusion algorithm based on improved non-subsampled contourlet transform (NSCT) [9], which can gain the photoelectric fusion phase-resolved partial discharge (PRPD) pattern by fusing the optical PRPD pattern with the ultrahigh frequency (UHF) PRPD pattern

  • In order to verify the applicability of the photoelectric fusion PD pattern proposed in this study, the above three classifiers were used to test the photoelectric fusion PD pattern samples, comparing with the recognition results of optical patterns and UHF patterns

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Summary

Introduction

Gas-insulated transmission lines (GIL) are widely used in the power transmission of hydropower stations and nuclear power plants because of their high efficiency, large transmission capacity, high reliability, and small footprint [1,2,3]. In the operation of GIL, partial discharge (PD) is a precursor in the deterioration of insulation performance, which is the main cause of a breakdown. PD detection and pattern recognition are important in the GIL [4,5]. In order to improve the reliability of PD detection and pattern recognition, Energies 2019, 12, 4120; doi:10.3390/en12214120 www.mdpi.com/journal/energies. Energies 2019, 12, 4120 some scholars have proposed a method of combining the fluorescent fiber detection and the ultrahigh frequency (UHF) detection in the PD detection of gas-insulated equipment, which has the characteristics of high sensitivity, strong anti-interference ability, and wide application range [6].

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