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电力视觉技术的概念、研究现状与展望 被引量:25

Concept,Research Status and Prospect of Electric Power Vision Technology
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摘要 随着我国新一代电力系统建设的快速发展,发输变电设备作为电力系统的重要组成部分,实现其缺陷的智能检测与分析变得愈发重要。紧跟国家新一代人工智能的步伐,与当今较热的计算机视觉相结合,提出电力视觉技术的概念,分析其研究对象和难点问题,在电力系统、计算机视觉和人工智能等领域之间建立了桥梁,并系统地总结了电力视觉技术在发电、输电和变电3大场景中的研究现状。最后从泛在电力物联网、少样本或零样本学习、生成式对抗网络、电力知识图谱和视觉推理等方面来分析电力视觉技术及其应用的未来发展趋势。 With the rapid development of China's new generation power system construction,power generation,transmission and transformer equipments are an important part of the power system,and intelligent detection and analysis of their defects has become increasingly important.Keeping pace with China's new generation of artificial intelligence and combining with today's hot computer vision,this article proposes the concept of electric power vision technology,analyzes its research objects and difficult problems,and establishes a bridge among power system,computer vision,and artificial intelligence fields.This paper systematically summarizes the research status of electric power vision technology in the three major scenarios of power generation,transmission and transformation.Finally,it analyzes the future development trend of electric power vision technology and its applications from the aspects of Ubiquitous power Internet of Things,few or zero shot learning,generative adversarial networks,power knowledge graph,and visual reasoning.
作者 赵振兵 张薇 翟永杰 赵文清 张珂 孔英会 戚银城 ZHAO Zhenbing;ZHANG Wei;ZHAI Yongjie;ZHAO Wenqing;ZHANG Ke;KONG Yinghui;QI Yincheng(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China;School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,China)
出处 《电力科学与工程》 2020年第1期1-8,共8页 Electric Power Science and Engineering
基金 国家自然科学基金项目(61871182,61773160) 北京市自然科学基金项目(4192055) 河北省自然科学基金项目(F2017502016) 中央高校基本科研业务费专项资金项目(2018MS095,2018MS094) 模式识别国家重点实验室开放课题基金项目(201900051) 国家留学基金项目(201906735011)。
关键词 电力视觉 新一代电力系统 机器学习 模式识别 图像处理 electric power vision new generation power system machine learning pattern recognition image processing
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