Research on Real-Time Monitoring of Power Equipment Status Based on Artificial Neural Network Technology
To improve the management level of the power system and timely grasp the operation status of power equipment,a real-time monitoring method for power equipment status based on artificial neural network technology is proposed.This method is based on the operation data of power equipment collected by sensors.The data module processes the noise data in the equipment operation status data through the variational mode decomposition method.The processed data is output to a BP neural network model,which learns and trains data to output the abnormal state detection results of power equipment.The detection results are visualized using a recursive graph structure.The results show that this method has good application effects and can reliably achieve real-time monitoring of the status of power equipment,determine the abnormal operation results of the equipment,and provide a certain reliable basis for power system management.
artificial neural network technologypower equipmentreal-time monitoring of statusvisual presentation
NETL
NSTL
万方数据
