Research on harmonic detection based on wavelet threshold and FFT algorithm

• Main Authors: Shuaishuai Zhao, Chuanjiang Wang, Xiaoxue Bian
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2018-09-01
• Series: Systems Science & Control Engineering
• Subjects: Wavelet threshold; FFT algorithm; polynomial fitting; harmonic detection
• Online Access: http://dx.doi.org/10.1080/21642583.2018.1558420

The fast Fourier transform (FFT) algorithm with window interpolation is the most commonly used and most effective method in harmonic analysis. However, the fast Fourier transform has a great dependence on the quality of the signal, and the existence of noise makes the detection result error. A harmonic detection method based on wavelet threshold preprocessing noise elimination and windowed interpolation FFT algorithm is proposed in this thesis. Firstly, de-noising the selected signals, and the wavelet coefficients are used to select the wavelet threshold to eliminate the noise in the signal. Then the signal after the de-noising is analysed by the Nuttall window interpolate FFT algorithm, and the calculation formula is derived by using the amplitude information content of four spectral lines. The simulation results show that the proposed method is more accurate and effective to detect the signal after de-noising.