电测与仪表2026，Vol.63Issue(4)：73-81,9.DOI:10.19753/j.issn1001-1390.2026.04.008
基于深度学习的新型电力系统作业风险预警研究
Research on operation risk warning in novel power system based on deep learning method
摘要
Abstract
Regarding the safety risks caused by improper wearing of safety helmets,smoking,and illegal entry into hazardous areas during the operation of power system,this paper studies an intelligent warning method for safety risks in operations based on improved YOLO(you only look once)v7 deep learning model.Firstly,the architec-ture for training and using a deep learning-based operation risk warning model is discussed.Then,the object recog-nition and detection method based on the YOLO v7 deep learning model is analyzed,and convolutional block atten-tion module(CBAM)and k-means++methods are introduced to improve the model.Finally,the improved YOLO v7 model is used to analyze and verify its effectiveness in the aforementioned safety risk warning.Experimental re-sults show that compared to the previous YOLO series detection methods,the improved YOLO v7 model has better performance in detecting operational safety risks in power system,and can meet the real-time detection and risk warning needs of the novel power system for operational risks.关键词
新型电力系统/作业风险/预警/目标识别Key words
novel power system/operation risk/warning/object recognition分类
信息技术与安全科学引用本文复制引用
李强,刘超,梁懿,王秋琳,丘志强..基于深度学习的新型电力系统作业风险预警研究[J].电测与仪表,2026,63(4):73-81,9.基金项目
国家电网有限公司总部科技项目(5700-202319302A-1-1-ZN) （5700-202319302A-1-1-ZN）
