The special transformer is the key equipment connecting different voltage levels in the power system.In order to en-sure the safe and stable operation of the transformer,this paper designs a special transformer abnormal power consumption de-tection system to monitor and collect transformer operation parameters in real time.The STM32F103RBT6 chip is used as the main control unit as the special transformer monitoring terminal,and the infrared temperature sensor is used to collect environ-mental parameters and transformer temperature.The system builds an anomaly detection model based on graph convolutional neural network,and uses the directed horizontal visualizable algorithm to transform the time series data.Feature vectors of di-rected level graph are extracted through feature pooling,and anomaly detection results are obtained after operation of convolu-tion layer and pooling layer.Experimental results show that the maximum accuracy of anomaly detection is 97.5％,the shor-test running time is 812 ms,and the fastest detection time is 1224 ms.
关键词
专用变压器/异常用电检测/监测终端设计/红外温度传感器/图卷积神经网络/有向水平可视图
Key words
special transformer/abnormal power consumption detection/monitoring terminal design/infrared temperature sen-sor/graph convolutional neural network/directed horizontal viewable
维普
万方数据