Journal of Jilin University (Information Science Edition) ›› 2021, Vol. 39 ›› Issue (2): 142-151.

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Research on Improved Method for Denoising of PSO-VMD-SVD

DU Ying1a, LI Hong1a, LIU Qingqiang1a, LU Jingyi1b,1c, LI Fu2   

  1. 1a. School of Electrical Engineering and Information; 1b. Artificial Intelligence Energy Research Institute;1c. Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing 163318, China;2. Drilling Company 1, Daqing Drilling Engineering Company, Daqing 163318, China
  • Received:2020-10-10 Online:2021-04-19 Published:2021-04-26

Abstract: According to VMD(Variational Mode Decomposition) in processing the signal, the selection of mode number K and parameter α will affect the signal decomposition results, an optimized VMD(Variational Mode Decomposition) algorithm improving PSO(Particle Swarm Optimization) (PSO-VMD) was proposed. Based on the analysis of signal, high frequency noise is reconstructed by singular value denoising. Experiments on simulation signal and pipeline leakage signal, by selecting multiple K and combined with proposed the correlation method to select mode and reconstruct signal, compare SNR ( Signal to Noise Ratio ), correlation CC (Coefficient), SAE(Square Absolute Error), MSE(Mean Square Error) of reconstructed signal of different K and original signal, proved the reliability of optimizing VMD by improved PSO. The proposed method is compared with PSO-VMD combined with HD-SVD(Haussteff Distance and Singular Value), MI-SVD(Mutual Information and Singular Values), CC-WT(Correlation Coefficient and Wavelet Transform) and other methods.The proposed denoising method has the best effect.

Key words: VMD algorithm, particle swarm optimization, correlation coefficient, singular value, denoising

CLC Number: 

  • TN911