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基于大数据与物联网的输变电设备故障诊断研究 被引量:11

Research on Substation Fault Detection and Operation Optimization Based on Data Mining and IoT
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摘要 针对输变电设备运行过程中各种因素导致的电网故障,提出了新型的故障诊断方法。该方法以大数据技术和物联网技术为基础,构建出包含数据采集层、数据传输层、数据分析层和数据监控层的物联网检测系统,实现了底层设备的物联网信息通讯。在故障诊断过程中,还融合了行波定位方法和BP神经网络算法模型,通过波定位方法能够使用户实时获取输变电设备中不同监测节点的暂态电压、暂态电流数据,进而迅速、精确地定位出输变电设备故障发生位置。通过BP神经网络算法模型对行波定位后的故障信息进行进一步地优化,对定位到的输变电设备故障位置信息进行更精确地学习和训练,以提高输变电设备的故障数据处理能力。试验表明,该方案误差率较低,大大提高了输变电设备故障诊断能力,从而提高了系统整体运行的效率。 Aiming at the power grid failure caused by various factors during the operation of transmission and transformation equipment,a new fault diagnosis method is proposed.Based on the big data technology and the Internet of Things technology,this method builds an IoT detection system including data acquisition layer,data transmission layer,data analysis layer and data monitoring layer,and realizes the IoT information communication of the underlying equipment.In the process of fault diagnosis,the traveling wave positioning method and BP neural network algorithm model are also integrated.Through the wave positioning method,users can obtain the real-time transient voltage and transient current data of different monitoring nodes in power transmission and transformation equipment,and then quickly,accurately locate the fault occurrence location of transmission and transformation equipment.The BP neural network algorithm model is used to further optimize the fault information after traveling wave localization,and more accurately learn and train the fault location information of the located transmission and transformation equipment to improve the fault data processing capability of the transmission and transformation equipment.Experiment shows that the error rate of the proposed scheme is low,which greatly improves the fault diagnosis capability of transmission and transformation equipment,thereby improving the overall system operation efficiency.
作者 邓燕山 赵凯利 吕文超 白杰 董杰 高岭 DENG Yan-shan;ZHAO Kai-li;LYU Wen-chao;BAI Jie;DONG Jie;GAO Ling(Tangshan Power Supply Company of State Grid Jibei Electric Power Co.,Ltd.,Tangshan 063000,China)
出处 《计算机技术与发展》 2021年第7期193-197,208,共6页 Computer Technology and Development
基金 河北省重点科技计划项目(052200HJ52170019)。
关键词 输变电设备 电网故障 大数据 物联网技术 行波定位方法 BP神经网络算法模型 transmission and transformation equipment grid faults big data internet of things technology traveling wave positioning method BP neural network algorithm model
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