909 / 2022-08-18 10:54:25
Research on oil-paper insulation state diagnosis and life prediction method based on Shuffle-SVM
oil-paper insulation,time-domain dielectric,Shuffle-SVM algorithm,Multi-source information
全文录用
Dixing Wu / Harbin University of Science and Technology;College of Electrical and Electronic Engineering
Mingze Zhang / Harbin University of Science and Technology;College of Electrical and Electronic Engineering
骥 刘 / 哈尔滨理工大学
Kunhan Wang / State Grid East Inner Mongolia Electric Power Research Institute
守明 王 / HUST
Power transformer plays an important role in the process of transmission and distribution, so it is necessary to diagnose the insulation and predict the service life of the power transformer. Support vector machine (SVM) is widely used in the field of multi-source information fusion for data prediction. The traditional SVM algorithm projects the data into high-dimensional space and constructs a hyperplane for classification. The new data is projected as the prediction set when building the model, and the prediction value is obtained according to the hyperplane classification. The Recovery voltage method (RVM) is a non-destructive test method. Its test characteristic quantity can reflect the aging and moisture of oil-paper insulation from many aspects. In this paper, the improved SVM algorithm called Shuffle-SVM is used to train multi-source data obtained from the RVM test are put into model training to predict the polymerization degree (DP) to detect the insulation state and calculate the service life of the transformer.

 
重要日期
  • 会议日期

    09月25日

    2022

    09月29日

    2022

  • 08月15日 2022

    提前注册日期

  • 09月10日 2022

    报告提交截止日期

  • 11月10日 2022

    注册截止日期

  • 11月30日 2022

    初稿截稿日期

  • 11月30日 2022

    终稿截稿日期

主办单位
IEEE DEIS
承办单位
Chongqing University
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