Frequency Measurement of Electrical Signal Based on Variable Step Size Lms Adaptive Notch Algorithm
Frequency is an important parameter for the operation of the power system, and the accuracy of frequency measurement directly affects the safe and reliable operation of the power system. At present, the commonly used frequency measurement methods include spectrum analysis method, Fourier transform method, frequency domain method and mixed frequency measurement method. Among them, the mixed frequency measurement method has the characteristics of simple algorithm and high accuracy, and is widely used in the power system. According to the different frequency components in the signal, the mixed frequency measurement method uses different filtering methods for signal processing, and then uses the Fourier transform to convert the signal into a spectrum. Due to the introduction of a large number of harmonics in the process of mixing measurement, the spectrum is distorted and the accuracy of the measurement results is affected. In this paper, an electrical signal frequency measurement method based on variable step size LMS adaptive notch algorithm is proposed, which realizes the adaptive adjustment of the structural parameters of the notch filter by changing the step size coefficient. This method can effectively suppress harmonic and noise interference, improve the accuracy of frequency measurement, and has strong anti-interference ability. Experimental results show that the algorithm can effectively suppress noise interference and harmonic interference, and has good frequency measurement accuracy, with a frequency measurement error of less than 0.2% in the range of 10~20 Hz and less than 0.15% in the range of 100 Hz. Therefore, the algorithm is suitable for electrical signal frequency measurements.
Authors
- Shanshan Cao (ORCID: https://orcid.org/0000-0001-9614-3249)
Institutions
- Heilongjiang Institute of Technology (CN)
Publication Details
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1109/gccit63234.2024.10862608
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00