Research on Abnormal State Monitoring Method of Electric Energy Metering Device
During the metering process of electric energy metering device,affected by the power spectrum harmonic tremor strength,its state index data presents a highly chaotic state,resulting in poor monitoring performance.For this reason,the abnormal state monitoring method of electric energy metering device based on improved cluster analysis is proposed.By constructing the state assessment system of electric energy metering device,selecting the technical indicators with assessment value and their corresponding parameter indicators,and considering the relevant indicators parameter as objects to be categorized,the chaotic sample data of the operating state of electric energy metering device are obtained.Ant colony algorithm is used to optimize the clustering index data of K-Means clustering method to realize the state monitoring of electric energy metering device.The test results show that the detection rate of abnormal state of electric energy metering device after the application of this method is high,the fitting rate and accuracy of the predicted value and the actual value are high.The method has good monitoring performance.
Electric energy metering deviceHarmonic tremor intensityTransformerPower spectrumState monitoringMultivariate phase space reconstructionEigenvectorsK-Means clustering
NETL
NSTL
万方数据
