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作 者:李邦源 常荣 Li Bangyuan(Yunnan Power Grid Co.,Ltd.,Yuxi Power Supply Bureau,Yuxi 653100,Yunnan,China)
机构地区:[1]云南电网有限责任公司玉溪供电局,云南玉溪653100 [2]云南电网有限责任公司玉溪供电局科技创新与数字化中心
出 处:《云南电力技术》2025年第1期52-56,共5页Yunnan Electric Power
摘 要:电流二次回路设计复杂的线路,导致其故障检测效率低下。提出变电站现场定检中电流二次回路通断测试,采用双端口稳压调控技术,采集电流二次回路状态数据。利用模糊均值聚类算法,对状态数据进行分类处理。结合实时频谱分析技术和高斯分布特性,构建了故障检测模型。基于深度学习,进行电流二次回路故障定位。实验结果显示,该方法在通断速度上具有显著优势,最快通断时间仅为0.5 s,相较于其他传统方法,效率更高,性能更优。本文的研究成果为变电站现场定检中电流二次回路通断测试提供了新的思路和方法,有助于电力系统的智能化发展。The complex design of current secondary circuits results in low fault detection efficiency.Propose research on the on/off testing of current secondary circuits during on-site inspection of substations.Adopting dual port voltage regulation technology to collect current secondary circuit status data.Using fuzzy mean clustering algorithm to classify and process state data.A fault detection model was constructed by combining real-time spectrum analysis technology and Gaussian distribution characteristics.Based on deep learning,perform fault location in current secondary circuits.The experimental results show that this method has significant advantages in on-off speed,with the fastest on-off time being only 0.5 seconds.Compared with other traditional methods,it has higher efficiency and better performance.The research results of this article provide new ideas and methods for the on/off testing of current secondary circuits in on-site inspection of substations,which is helpful for the intelligent development of power systems.
关 键 词:电流二次回路 通断测试 故障检测 实时频谱分析 深度学习
分 类 号:TM74[电气工程—电力系统及自动化]
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