Shaosheng Geng, Min Li, Chunxin Wang, Qianqian Zhang, Qi Liu, Jun Xie
{"title":"Determination of partial discharge development stage of oil-paper insulation based on sparse decomposition considering the effect of aging","authors":"Shaosheng Geng, Min Li, Chunxin Wang, Qianqian Zhang, Qi Liu, Jun Xie","doi":"10.1007/s00202-024-02689-x","DOIUrl":null,"url":null,"abstract":"<p>To realize the accurate determination of the partial discharge development stage of an oil-immersed power transformer by a method based on sparse decomposition is proposed in the insulation system of an oil-immersed power transformer. First, statistical parameters are extracted from the PD pulse signals to construct a complete atomic library. According to the sparse representation principle, the preliminary determination of the discharge stage can be realized by ignoring the influence of aging; secondly, to solve the influence of feature parameter correlation on the determination result, the statistical feature parameters are sparsely reconstructed to realize the ordering of the effectiveness of the statistical feature parameters; lastly, to take into account the influence of the aging of the insulating cardboard, the plausible weights of the aging factor are calculated, and the number of votes for the development stage of partial discharge is determined according to the Borda voting mechanism. Two typical discharge defect models are designed so that the PDs on which the work focuses are superficial, and the measured signals are used to verify the validity of this paper's method. The results show that the highest accuracy is 56.2% when ignoring the influence of insulation cardboard aging, and the accuracy of the decision is less than 75% when considering the influence of aging without sparse reconstruction of statistical feature parameters; the method in this paper has good recognition effect, and the recognition accuracy is improved by 38.6% compared with that of ignoring the influence of aging of the insulation cardboard, and the average can reach 94.2%.</p>","PeriodicalId":50546,"journal":{"name":"Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electrical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00202-024-02689-x","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
To realize the accurate determination of the partial discharge development stage of an oil-immersed power transformer by a method based on sparse decomposition is proposed in the insulation system of an oil-immersed power transformer. First, statistical parameters are extracted from the PD pulse signals to construct a complete atomic library. According to the sparse representation principle, the preliminary determination of the discharge stage can be realized by ignoring the influence of aging; secondly, to solve the influence of feature parameter correlation on the determination result, the statistical feature parameters are sparsely reconstructed to realize the ordering of the effectiveness of the statistical feature parameters; lastly, to take into account the influence of the aging of the insulating cardboard, the plausible weights of the aging factor are calculated, and the number of votes for the development stage of partial discharge is determined according to the Borda voting mechanism. Two typical discharge defect models are designed so that the PDs on which the work focuses are superficial, and the measured signals are used to verify the validity of this paper's method. The results show that the highest accuracy is 56.2% when ignoring the influence of insulation cardboard aging, and the accuracy of the decision is less than 75% when considering the influence of aging without sparse reconstruction of statistical feature parameters; the method in this paper has good recognition effect, and the recognition accuracy is improved by 38.6% compared with that of ignoring the influence of aging of the insulation cardboard, and the average can reach 94.2%.
期刊介绍：
The journal “Electrical Engineering” following the long tradition of Archiv für Elektrotechnik publishes original papers of archival value in electrical engineering with a strong focus on electric power systems, smart grid approaches to power transmission and distribution, power system planning, operation and control, electricity markets, renewable power generation, microgrids, power electronics, electrical machines and drives, electric vehicles, railway electrification systems and electric transportation infrastructures, energy storage in electric power systems and vehicles, high voltage engineering, electromagnetic transients in power networks, lightning protection, electrical safety, electrical insulation systems, apparatus, devices, and components. Manuscripts describing theoretical, computer application and experimental research results are welcomed.
Electrical Engineering - Archiv für Elektrotechnik is published in agreement with Verband der Elektrotechnik Elektronik Informationstechnik eV (VDE).
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
