{"title":"Examination of insulation diagnosis in substation by neural network with phase-resolved partial discharge pattern reconstruction","authors":"Shunya Fujioka, Hideaki Kawano, Masahiro Kozako, Masayuki Hikita, Osamu Eda, Shuhei Yaguchi, Yasuharu Shiina","doi":"10.1002/ecj.12360","DOIUrl":null,"url":null,"abstract":"<p>Several studies for partial discharge (PD) pattern recognition using artificial neural network (ANN) were reported in the early 1990s. Usually, in an actual field such as a substation, data on partial discharge is scarcely available, or even rare. In many cases, the power supply phase required for the PRPD pattern cannot be easily obtained. We propose an ANN method that shifts the phase in which the maximum signal intensity detected with PD sensors is generated and used it as training and input data, even for the few phases resolved PD data available in the field. This ANN method was applied to the PRPD pattern obtained in a practical field. As a result, it was shown that the discrimination rate between PD and noise was improved, and therefore the proposed ANN method was found to be effective.</p>","PeriodicalId":50539,"journal":{"name":"Electronics and Communications in Japan","volume":"105 4","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics and Communications in Japan","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ecj.12360","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Several studies for partial discharge (PD) pattern recognition using artificial neural network (ANN) were reported in the early 1990s. Usually, in an actual field such as a substation, data on partial discharge is scarcely available, or even rare. In many cases, the power supply phase required for the PRPD pattern cannot be easily obtained. We propose an ANN method that shifts the phase in which the maximum signal intensity detected with PD sensors is generated and used it as training and input data, even for the few phases resolved PD data available in the field. This ANN method was applied to the PRPD pattern obtained in a practical field. As a result, it was shown that the discrimination rate between PD and noise was improved, and therefore the proposed ANN method was found to be effective.
期刊介绍：
Electronics and Communications in Japan (ECJ) publishes papers translated from the Transactions of the Institute of Electrical Engineers of Japan 12 times per year as an official journal of the Institute of Electrical Engineers of Japan (IEEJ). ECJ aims to provide world-class researches in highly diverse and sophisticated areas of Electrical and Electronic Engineering as well as in related disciplines with emphasis on electronic circuits, controls and communications. ECJ focuses on the following fields:
- Electronic theory and circuits,
- Control theory,
- Communications,
- Cryptography,
- Biomedical fields,
- Surveillance,
- Robotics,
- Sensors and actuators,
- Micromachines,
- Image analysis and signal analysis,
- New materials.
For works related to the science, technology, and applications of electric power, please refer to the sister journal Electrical Engineering in Japan (EEJ).
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