Electronic Science and Technology ›› 2023, Vol. 36 ›› Issue (1): 60-66.doi: 10.16180/j.cnki.issn1007-7820.2023.01.009

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Harmonic Detection Technology Based on Improved Wavelet Threshold Denoising and CEEMDAN-HT Fusion

WANG Yumei,ZHENG Yi   

  1. School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454000,China
  • Received:2021-06-17 Online:2023-01-15 Published:2023-01-17
  • Supported by:
    National Natural Science Foundation of China(U1804143)

Abstract:

In view of the low accuracy of CEEMDAN harmonic detection of adaptive noise caused by power grid environmental noise, a harmonic detection technology based on improved wavelet threshold denoising and CEEMDAN-HT fusion is proposed in this study. The threshold value is adaptively adjusted by the correction factor Tj, the soft and hard characteristics of the threshold function are adjusted by the adjustable parameter τ, and the improved wavelet threshold denoising method is applied to the preprocessing of harmonic signals. The preprocessed signal is decomposed by CEEMDAN, which can effectively suppress the mode aliasing binding. Relatedness criterion is used to remove false components, and the Hilbert transform is used to demodulate the components containing harmonic characteristics, and the amplitude-frequency information is accurately extracted. MATLAB simulation results show that the fusion algorithm of improved wavelet threshold denoising and CEEMDAN-HT controls the average error of steady-state harmonic detection below 1%, and the average error of transient harmonic detection below 2.1%, showing good anti-noise performance.

Key words: improved wavelet threshold denoising, CEEMDAN, modal aliasing, correction factor, false component, correlation criterion, harmonic detection, Hilbert transform

CLC Number: 

  • TN911