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Open AccessArticle

Multi-Scale Analysis and Pattern Recognition of Ultrasonic Signals of PD in a Liquid/Solid Composite of an Oil-Filled Terminal

1
Key Laboratory of Engineering Dielectrics and its Application, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China
2
College of Rongcheng, Harbin University of Science and Technology, Rongcheng 264300, China
3
State Grid Corporation of Yantai, Yantai 264001, China
*
Author to whom correspondence should be addressed.
Energies 2020, 13(2), 366; https://doi.org/10.3390/en13020366
Received: 9 December 2019 / Revised: 3 January 2020 / Accepted: 9 January 2020 / Published: 11 January 2020
In order to analyze the partial discharge (PD) characteristics of a liquid/solid composite medium in an oil-filled submarine cable terminal; we have designed five discharge models including needle-plate, plate-to-plate air gap, surface, slide-flash and suspension potential. At the same time, the ultrasonic signals of PD have been extracted through the typical fault model research platform of oil-filled submarine cable equipment. First, we use SureShrink threshold wavelet denoising to suppress the ultrasonic signal noise. Secondly, through the multi-scale analysis of the signal, the energy distribution maps of five different types of PD are obtained; the analysis found that needle-plate discharge, suspension discharge, and slide-flash discharge have better resolution; and plate-to-plate air gap discharge and creeping discharge have similar characteristics and are not easy to distinguish. Finally, we designed six characteristic parameters of the ultrasound signal, and screened three feature quantities by a back propagation (BP) neural network to distinguish between plate-to-plate air gap discharge and surface discharge. In summary, the method of combining multi-scale analysis and neural networks is used to distinguish the five discharge types by extracting the characteristic values of the characteristic signals. View Full-Text
Keywords: high voltage oil-filled cable terminal; multiscale analysis; BP neural network; PD pattern recognition high voltage oil-filled cable terminal; multiscale analysis; BP neural network; PD pattern recognition
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MDPI and ACS Style

Wang, Y.; Zhang, X.; Li, Y.; Li, L.; Gao, J.; Guo, N. Multi-Scale Analysis and Pattern Recognition of Ultrasonic Signals of PD in a Liquid/Solid Composite of an Oil-Filled Terminal. Energies 2020, 13, 366.

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