基于数字孪生技术的电力设备故障诊断仿真系统构建研究  

Research on the Construction of Power Equipment Fault Diagnosis Simulation System Based on Digital Twin Technology

作　　者：房雪雷[1] 马娟[1] 徐结红 丁津津 彭勃 FANG Xuelei;MA Juan;XU Jiehong;DING Jinjin;PENG Bo(State Grid Anhui Electric Power Company Training Center,Hefei 230022,China;State Grid Anhui Electric Power Co.,Ltd.Electric Power Science Research Institute,Hefei 230071,China)

机构地区：[1]国网安徽省电力公司有限公司培训中心,合肥230022 [2]国网安徽省电力有限公司电力科学研究院,合肥230071

出　　处：《自动化与仪器仪表》2024年第10期233-236,共4页Automation & Instrumentation

基　　金：安徽省自然科学基金《柔性互联配电网形态结构与运行控制关键技术研究》(2208085UD11)。

摘　　要：变压器是电力系统中的重要设备,为了提高电力系统运行的稳定性与安全性,研究构建了一个基于数字孪生技术的变压器故障诊断模型,该模型通过一维卷积神经网络,对变压器故障进行诊断分析。结果显示,在变压器处于低温过热故障状态时,模型能够实现100%的诊断正确率,在变压器发生中温过热故障时,故障诊断正确率降至97%。研究构建的电力设备故障诊断模型,有效提高了二次设备变压器的故障诊断准确率,实现了电力系统变压器故障诊断的实时检测,保障了电力系统的稳定安全运行。通过二次设备变压器故障诊断的模拟分析,可帮助电力系统维修人员更好地了解变压器故障发生机理及应对措施。Transformers are important equipment in the power system.In order to improve the stability and safety of power system operation,a transformer fault diagnosis model based on digital twin technology was studied and constructed.This model uses one-dimensional convolutional neural networks to diagnose and analyze transformer faults.The results show that the model can achieve 100%diagnostic accuracy when the transformer is in a low-temperature overheating fault state,and the diagnostic accuracy drops to 97%when the transformer experiences a medium temperature overheating fault.The power equipment fault diagnosis model constructed through research has effectively improved the accuracy of secondary equipment transformer fault diagnosis,achieved real-time detection of power system transformer fault diagnosis,and ensured the stable and safe operation of the power system.Through the diagnosis of transformer faults in secondary equipment,your simulation analysis can help power system maintenance personnel better understand the mechanism of transformer faults and corresponding measures.

关 键 词：数字孪生 电力设备 故障诊断 二次设备 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]