变电站综合自动化设备运检中的故障诊断技术研究  

Research on Fault Diagnosis Technology in Operation and Inspection of Substation Integrated Automation Equipment

作　　者：校淑佩 刘成泊 XIAO Shupei;LIU Chengbo

机构地区：[1]国网新疆电力有限公司巴州供电公司,新疆库尔勒841000

出　　处：《今日自动化》2024年第9期83-84,160,共3页Automation Today

摘　　要：随着电力系统的不断发展,变电站综合自动化设备在电网中的作用日益突出。然而,设备故障给电网运行带来了严重的影响,所以提高对设备故障的诊断效率成为当务之急。传统的故障诊断方法存在着局限性,而基于机器学习的技术为解决这一问题提供了新的思路。文章分析了变电站综合自动化设备运检中的故障诊断技术,探讨了基于特征提取的故障诊断模型,旨在提高变电站运检的准确性和效率。With the continuous development of the power system,the role of comprehensive automation equipment in substations in the power grid is becoming increasingly prominent.However,equipment failures have had a serious impact on the operation of the power grid,so improving the efficiency of diagnosing equipment failures has become an urgent task.Traditional fault diagnosis methods have limitations,and machine learning based techniques provide new ideas to solve this problem.The article analyzes the fault diagnosis technology in the operation and inspection of comprehensive automation equipment in substations,and explores the fault diagnosis model based on feature extraction,aiming to improve the accuracy and efficiency of substation operation and inspection.

关 键 词：变电站综合自动化设备 故障诊断技术 特征提取 机器学习 

分 类 号：TM63[电气工程—电力系统及自动化]