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大模型时代:电力视觉技术新起点 被引量:1

The Era of Large Models:A New Starting Point for Electric Power Vision Technology
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摘要 随着无人机、巡检机器人和远程监控系统在输电、变电、配电、安监等电力场景中的广泛应用,利用电力视觉技术完成对海量巡检图像的自动处理,能够进一步提升电力系统智能化运维水平,对我国源网荷储一体化进程的快速推进具有至关重要的作用。随着通用视觉大模型的兴起,电力视觉技术正处于从传统深度学习时代向大模型时代跨越的重要节点。该文首先综述了电力视觉技术和通用视觉大模型的最新研究进展,结合视觉大模型在多种公共场景的应用先例,探讨视觉大模型在电力视觉领域将面临的3重能力边界问题。从初步探索通用视觉大模型的潜力,到逐步构建电力视觉大模型的过程,提出4种模型应用范式以突破视觉大模型能力边界。最后分析了视觉大模型对电力视觉研究者的影响,并对大模型浪潮下电力视觉技术的发展方向进行了展望。 With the widespread applications of drones,inspection robots,and remote monitoring systems in power scenarios such as transmission,transformation,distribution,and safety supervision,the power vision technology is utilized to automatically process massive inspection images,thus the intelligent operation and maintenance level of power systems can be further enhanced,playing a crucial role in the rapid advancement of China’s source-grid-load-storage integration process.With the rise of general-purpose large vision models,the electric power vision technology is embarking on an important transition from the traditional deep learning era to the era of large models.In this paper,the latest research progress in electric power vision technology and general-purpose large vision models is summarized.Combined the precedents of large vision models’applications in various public scenarios,three main capability boundary issues that large vision models will face in the field of power vision are investigated.From initially attempting to apply general-purpose large vision models to establishing power-specific large vision models,the four model application paradigms to break through the capability boundaries of large vision models are proposed.Finally,the impact of large vision models on electric power vision researchers is analyzed,and prospects in the development direction of electric power vision technology under the wave of large models are put forward.
作者 赵振兵 冯烁 席悦 张靖梁 翟永杰 赵文清 ZHAO Zhenbing;FENG Shuo;XI Yue;ZHANG Jingliang;ZHAI Yongjie;ZHAO Wenqing(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China;Engineering Research Center of Intelligent Computing for Complex Energy Systems of Ministry of Education,North China Electric Power Uni-versity,Baoding 071003,China;Hebei Key Laboratory of Power Internet of Things Technology,North China Electric Power University,Baoding 071003,China;School of Control and Computer Engineering,North China Electric Power University,Bao-ding 071003,China)
出处 《高电压技术》 EI CAS CSCD 北大核心 2024年第5期1813-1825,共13页 High Voltage Engineering
基金 国家自然科学基金(U21A20486,62373151,62371118,62303184) 河北省自然科学基金(F2021502008,F2021502013) 中央高校基本科研业务费专项资金(2023JC006)。
关键词 电力视觉 视觉大模型 目标检测 图像分割 深度学习 图像处理 electric power vision large vision models object detection image segmentation deep learning image pro-cessing
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