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作 者:康恺 毛一凡 周钢泉 KANG Kai;MAO Yifan;ZHOU Gangquan(Hangzhou Science and Technology Development Branch,Zhejiang Dayou Industrial Co.,Ltd.,Hangzhou Zhejiang 310000,China)
机构地区:[1]浙江大有实业有限公司杭州科技发展分公司,浙江杭州310000
出 处:《信息与电脑》2024年第16期95-97,共3页Information & Computer
摘 要:随着电力设施安全的重要性日益凸显,电力变电站的图像识别与入侵检测系统的研发已成为一项紧迫的技术需求。图像识别技术通过分析摄像头捕获的图像,能识别和跟踪场景中的对象;而入侵检测技术则专注于监测和响应未授权的入侵行为。将这两项技术结合起来,可以有效提高变电站的安全防范能力,防止非法入侵和设备损害事件的发生。本文设计了一个电力变电站图像识别与入侵检测系统,包括系统总体架构的构建、图像采集与处理模块的实施,以及入侵检测算法的设计与优化。同时,文章展示了系统的实现过程和实验测试结果,验证了所提出系统的有效性与可行性。As the importance of power facility security becomes increasingly prominent,the development of image recognition and intrusion detection systems for power substations has become an urgent technical need.Image recognition technology analyzes images captured by cameras to identify and track objects in the scene;while intrusion detection technology focuses on monitoring and responding to unauthorized intrusions.Combining these two technologies can effectively enhance the security prevention capabilities of substations and prevent illegal intrusions and equipment damage.This paper designs an image recognition and intrusion detection system for power substations,including the construction of the overall system architecture,the implementation of image acquisition and processing modules,and the design and optimization of intrusion detection algorithms.At the same time,the article shows the system implementation process and experimental test results,verifying the effectiveness and feasibility of the proposed system.
分 类 号:TM63[电气工程—电力系统及自动化]
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