山东电力技术2023，Vol.50Issue(12)：1-10,10.DOI:10.20097/j.cnki.issn1007-9904.2023.12.001
基于深度视觉的GIS内部金属微粒运动特性分析
Analysis of Metal Particles Motion Characteristics in GIS Based on Depth Vision
摘要
Abstract
In order to study the motion characteristics of the moving metal particles inside the gas insulated substation(GIS)cavity,a real and reasonable simulation model was established.A visual analysis method based on deep learning was proposed.The video of the motion process was obtained by high-speed camera,and the YOLOv5 model and DeepSort model were used to detect and track the moving metal particles.The motion state of metal particles in the cavity was obtained.On the basis of test data,the motion characteristics were analyzed,such as the trajectory distribution of metal particles,the velocity distribution histogram and distribution law,and the correlation between the velocity and the passing position.The experimental results show that the particle motion range is wide and the velocity is small,and the velocity of the particle has different degrees of correlation with different positions.The results of the research and analysis can provide some theoretical and methodological guidance for the detection and motion characteristics analysis of metal particles in GIS.关键词
GIS/运动金属微粒/视觉分析/运动特性Key words
GIS/moving metal particles/visual analysis/motion characteristics分类
动力与电气工程引用本文复制引用
刘宝林,熊永平,李杰,师伟..基于深度视觉的GIS内部金属微粒运动特性分析[J].山东电力技术,2023,50(12):1-10,10.基金项目
国家电网有限公司科技项目"融合高速光学成像与局放信号检测的GIS设备内部金属异物检测技术研究"(5500-202116132A-0-0-00).Science and Technology Project of State Grid Corporation of China"Research on Detection Technology of Metal Foreign Body in GIS Equipment Integrating High-speed Optical Imaging and Local Emission Signal Detection"(5500-202116132A-0-0-00). （5500-202116132A-0-0-00）
