电能计量互感器二次回路故障远程诊断方法

为保障电量计量设备平稳运行，提高二次回路故障诊断准确率，提出了电能计量互感器二次回路故障远程诊断方法，提高不同原因导致的二次回路故障诊断效果。在电能计量二次侧的电压、电流二次回路上布置各检测点，通过远程诊断设备的PT监测单元、CT监测单元、多路模拟采集器采集各检测点的电参量数据，传输至远程诊断设备的故障诊断单元，故障诊断单元综合处理接收的各数据信息，利用基于改进粒子群优化的BP神经网络故障诊断模型诊断互感器二次回路故障，并输出故障诊断结果。实验结果表明：该方法经80次迭代后，适应度曲线达到最佳收敛效果，获得最小MSE值，可有效识别电流信号的波形变化，实现不同原因导致的互感器二次回路故障的远程诊断，且故障诊断准确度高。

Remote Diagnosis Method of Secondary Circuit Fault of Electric Energy Metering Transformer

In order to ensure the smooth operation of electric energy metering equipment and improve the accuracy of secondary circuit fault diagnosis, a remote diagnosis method of secondary circuit fault of electric energy metering transformer is proposed to improve the effect of secondary circuit fault diagnosis caused by different reasons. Each detection point is arranged on the voltage and current secondary circuit at the secondary side of the electric energy metering. The electrical parameter data of each detection point is collected through the PT monitoring unit, CT monitoring unit and multi-channel analog collector of the remote diagnosis equipment and transmitted to the fault diagnosis unit of the remote diagnosis equipment. The fault diagnosis unit comprehensively processes the received data information, The fault diagnosis model of BP neural network based on improved particle swarm optimization is used to diagnose the fault of transformer secondary circuit, and the fault diagnosis results are output. The experimental results show that after 80 iterations, the fitness curve achieves the best convergence effect, obtains the minimum MSE value, can effectively identify the waveform change of current signal, realize the remote diagnosis of transformer secondary circuit fault caused by different reasons, and the fault diagnosis accuracy is high.