Design of Three-Phase Energy Meter Measurement Error Atuomatic Calibration Method
To improve the effectiveness of the three-phase energy meter measurement error calibration method and avoid the interference of redundant data to the calibration process,an three-phase energy meter measurement error automatic calibration method based on clustering optimization is proposed.Fuzzy C-mean(FCM)clustering algorithm is utilized to extract the core features of the calibration data of three-phase energy meters and construct the core feature data set of the calibration data.The kernel function is utilized to divide the original feature space,which is mapped to the higher dimensional Hilbert space.A support vector machine(SVM)model is established,and the core feature data set is input into the model to realize the automatic calibration of three-phase energy meter measurement error with less data,to improve the accuracy of calibration.The test results show that the calibration time of this method is lower,which is all below 2.5 s;the detection rate of three-phase energy meter measurement error all reaches more than 90％,which can effectively improve the calibration efficiency.The method has an important role in the measurement error verification.
Three-phase energy meterData processingError calibrationFuzzy C-mean(FCM)clustering algorithmSupport vector machine(SVM)Automatic calibration
万方数据
维普
