环网柜智能识别与故障诊断算法研究  

Research on Intelligent Recognition and Fault Diagnosis Algorithms for Ring Main Units

作　　者：卢其亮 唐宏成 林乐强 LU Qiliang;TANG Hongcheng;LIN Leqiang(China-One Power Electric Co.,Ltd.,Wenzhou Zhejiang 325000,China;Zhejiang NEDQ Electric Technology Co.,Ltd.,Wenzhou Zhejiang 325000,China;Honghao Electric Power Equipment Co.,Ltd.,Wenzhou Zhejiang 325000,China)

机构地区：[1]一能电气有限公司,浙江温州325000 [2]浙江迪能电气科技有限公司,浙江温州325000 [3]鸿皓电力设备有限公司,浙江温州325000

出　　处：《信息与电脑》2025年第5期180-182,共3页Information & Computer

摘　　要：在电力系统运行中,环网柜的稳定至关重要,但传统方式难以满足其高效运维需求。鉴于此,开展了环网柜智能识别与故障诊断算法研究。通过在环网柜中安装传感器来采集多源数据,并利用数据清洗和标准化技术,构建了深度学习特征提取和多模态数据融合模型。另外,研发了故障分类与时间序列预测算法。优化实验后,该技术显著提高了故障诊断的准确性和可靠性,从而推动了电力系统的智能化进程。In the operation of power system,the stability of ring network cabinet is crucial,but the traditional way is difficult to meet the demand of its efficient operation and maintenance.In view of this,the research on intelligent identification and fault diagnosis algorithm of ring network cabinet is carried out.A deep learning feature extraction and multimodal data fusion model is constructed by installing sensors in ring network cabinets to collect multi-source data,and using data cleaning and standardization techniques.In addition,fault classification and time series prediction algorithms are developed.After optimization experiments,the technique significantly improves the accuracy and reliability of fault diagnosis,thus promoting the intelligent process of power system.

关 键 词：环网柜 智能识别 故障诊断 数据分析 电力系统 

分 类 号：P315.69[天文地球—地震学]