Research on the stability and security of image recognition detection technology for electrical equipment based on cloud-side-end collaboration

Fei Wu, Jianguo Qian, Jianye Huang, Yangdi Li, Yan Yang, Deming He, Zhou Zheng
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引用次数: 0

Abstract

The digital construction process of power grid often uses image intelligent recognition technology in the transmission and substation system for equipment environment monitoring, unmanned inspection and other scenarios, and this process generates massive data, and the existing centralized data processing model is limited by the lack of storage resources and computing power, and cannot meet the massive data processing requirements and frequent interaction needs. In this regard, this paper proposes a framework for the application of image recognition data of side electrical equipment based on cloudside - end collaboration, and builds an online intelligent diagnosis and analysis model of electrical equipment based on image recognition algorithm, so as to achieve real-time tracking of the operation status of electrical equipment. To further verify the stability and safety of the built model, Matlab simulation software is applied to conduct a targeted case analysis of the model, and the superiority of the proposed cloud-side synergy in the image recognition model of electrical equipment is verified through the comparative analysis of data synergy efficiency curves, which proves the feasibility of the proposed design scheme.
基于云端协作的电气设备图像识别检测技术的稳定性和安全性研究
电网数字化建设过程中经常在输变电系统中使用图像智能识别技术进行设备环境监测、无人巡检等场景,该过程产生海量数据,现有的集中式数据处理模式受到存储资源和计算能力不足的限制,无法满足海量数据处理需求和频繁交互需求。对此,本文提出了基于云端协同的侧电设备图像识别数据应用框架,构建了基于图像识别算法的电气设备在线智能诊断分析模型,实现了对电气设备运行状态的实时跟踪。为了进一步验证所建模型的稳定性和安全性,应用Matlab仿真软件对模型进行了有针对性的案例分析,并通过数据协同效率曲线的对比分析验证了所提出的云侧协同在电气设备图像识别模型中的优越性,证明了所提出设计方案的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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