您当前的位置:
首页 >
文章列表页 >
Study of GIS insulation defect identification method using LSTM-CNNfeature fusion and BO-SVM
更新时间:2026-10-18
    • Study of GIS insulation defect identification method using LSTM-CNNfeature fusion and BO-SVM

    • Electric Machines and Control   Vol. 29, Issue 12, Pages: 182-194(2025)
    • DOI:10.15938/j.emc.2025.12.016    

      CLC: TM85
    • Received:26 August 2024,

      Published:2025-12

    移动端阅览

  • XIE Zuibing, MA Longtao, WANG Jili, et al. Study of GIS insulation defect identification method using LSTM-CNNfeature fusion and BO-SVM[J]. Electric Machines and Control, 2025, 29(12): 182-194. DOI: 10.15938/j.emc.2025.12.016.

  •  
  •  

0

Views

955

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Partial discharge ultrasound localization based on super-resolution generalized cross-correlation estimation algorithm
Simulation study on effect of temperature on partial discharge inside void defects under closed conditions
Combined simulation model for partial discharge considering air-gap discharge, electromagnetic propagation and antenna response
Monitoring and type identification with fiber optic sensors and intelligent algorithm for partial discharge in high-voltage generators
Multi-physical signal evolution law of partial discharge in inter-turn oil-paper insulation

Related Author

DONG Ming
WANG Hao
LIU Yinkang
WANG Bin
ZHANG Chongxing
REN Ming
GUAN Yu
LUO Lingen

Related Institution

State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University
Department of Electrical Engineering, Shanghai Jiao Tong University
(School of Electrical Engineering, Shanghai Jiao Tong University,,)
云南电力试验研究院(集团)有限公司
0