Thermal Fault Diagnosis of Power Equipment through Improved Instance Segmentation Algorithm and Deep Neural Network Temperature Fitting
Author:
Affiliation:
1. State Grid Zhengzhou Power Supply Company of Henan Electric Power Company,Zhengzhou,Henan,China,450000
2. Guangxi University,Guangxi Key Laboratory of Power System Optimization and Energy Technology,Nanning,Guangxi,China,530004
Funder
National Natural Science Foundation of China
Specific Research Project of Guangxi for Research Bases and Talents
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10428934/10429048/10429092.pdf?arnumber=10429092
Reference19 articles.
1. Temperature Compensation Method for Infrared Detection of Live Equipment under the Interferences of Wind Speed and Ambient Temperature
2. Infrared Image Detection of Substation Insulators Using an Improved Fusion Single Shot Multibox Detector
3. An Infrared Image Detection Method of Substation Equipment Combining Iresgroup Structure and CenterNet
4. An Insulator in Transmission Lines Recognition and Fault Detection Model Based on Improved Faster RCNN
5. DefGAN: Defect Detection GANs With Latent Space Pitting for High-Speed Railway Insulator
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