Abstract: Aiming at the problem of the complex  harmonic components in the current harmonic measurement of electronic current transformers, which  led to interference from noise and outliers in actual measurement, resulting in a decrease in the accuracy of harmonic measurement results. By introducing DBSCAN (density-based spatial clustering of applications with noise) clustering, we proposed a harmonic measurement algorithm for electronic current transformers based on DBSCAN clustering to effectively identify and eliminate noise points and outliers in the dataset, thereby improving the accuracy of harmonic component detection. Firstly, we collected the current signals of the electronic current transformer and obtained the peak frequency of each current signal in 
the transformer based on the time-frequency energy peak value. Secondly, by using the DBSCAN clustering algorithm, we calculated the distance between the peak frequencies of each current signal, and determined noise signals, non harmonic signals, and different types of harmonic signals based on the distance to eliminate noise points and outliers in the dataset. Finally, we  used the least squares method to measure the amplitude and phase of various harmonic signals, and obtained the harmonic measurement results of the current transformer. The experimental results show that when the time is 2 s, the actual value of harmonic phase is 18°, and the harmonic phase of the proposed algorithm is 18°, which is consistent with the actual results. The measurement  accuracy of harmonic  amplitude and phase is high,  indicating that the proposed algorithm  can effectively improve the accuracy of harmonic measurement and avoid interference from noise and outliers.

Key words: DBSCAN clustering, electronic current transformer, quadratic difference, harmonic measurement, least squares method