Performance Evaluation of Ultra‐Fast Frequency Detection Method Based on MUSIC and its Improved Scheme
Yaru Sheng, Bin Li, Jiawei He, Ye Li, Chenyang Ma, Yalin Li · IEEJ Transactions on Electrical and Electronic Engineering · 2025
Abstract The electrical transients contain rich frequency components due to the system disturbances or faults. In order to extract characteristic information and further analyze them, the ultra‐fast frequency detection method is crucial. In this paper, an ultra‐fast frequency detection method based on multiple signal classification (MUSIC) is researched. First, the frequency detection speed of MUSIC algorithm is discussed, and its minimum time window for frequency detection is obtained. Then, the frequency detection performance of the MUSIC algorithm is analyzed in detail by varying the time window, the frequencies, amplitudes, phases of the estimated signal, and the set number of frequencies in the algorithm. As for the false spectral peak phenomenon of the MUSIC algorithm, the paper proposes the improved method by combining the MUSIC algorithm with K‐means clustering to identify false spectral peaks. Finally, the effectiveness of the proposed improved method is validated through case studies. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.