基于逻辑回归的高压电缆交叉互联接地系统缺陷分类识别方法

Translated title of the contribution: Classification and identification method of grounding system defects in cross-bonded HV cables based on logistic regression

Gen Li*, Hang Wang, Haikang Liu, Xinyou Cui, Chengke Zhou*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Many researches have focused on grounding system defects in cross-bonded high voltage (HV) cables in recent years, but the results in previous efforts have not been satisfactory when only using the amplitude of grounding current as indicators. In this paper, the 27 common grounding system states were divided into 3 categories from the perspective of circuit topology, the grounding current calculation method under various defect states was given, and a comprehensive feature extraction based on grounding current amplitude ratio and phase angle difference method was proposed. The linear binary classification logistic regression algorithm was introduced into the intelligent identification model of cross-connected high-voltage cable grounding system defects through polynomial feature expansion and multi-class voter construction, and the classification algorithm was evaluated using the data generated by the grounding current calculation model. The evaluation results show that the grounding system defect classification method based on the circuit topology can be adopted to effectively distinguish various types of defects, and the comprehensive grounding current characterization method based on the amplitude ratio and the phase angle difference can be adopted to effectively reflect the abnormal circuit topology of the grounding system. The system grounding defect classification model based on logistic regression can be adopted to effectively identify 27 common high-voltage cable grounding system states. The total evaluation indicators such as algorithm accuracy, precision, recall and F1 value are all above 95%. The recognition accuracy of the model for various states is above 89%. The research results verify the effectiveness of the proposed method. © 2021, High Voltage Engineering Editorial Department of CEPRI. All right reserved.
Translated title of the contributionClassification and identification method of grounding system defects in cross-bonded HV cables based on logistic regression
Original languageChinese (Simplified)
Pages (from-to)3674-3683
Number of pages10
JournalGaodianya Jishu/High Voltage Engineering
Volume47
Issue number10
DOIs
Publication statusPublished - 31 Oct 2021

Keywords

  • Condition monitoring
  • Defects classification
  • Grounding system
  • High voltage cable
  • Logistic regression
  • Metallic sheath
  • Sheath current

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Classification and identification method of grounding system defects in cross-bonded HV cables based on logistic regression'. Together they form a unique fingerprint.

Cite this