Application of a noise reduction method combining AVMD and SVD in natural gas pipeline leakage signal

Abstract

Due to the large amount of noise in pipeline leakage signal, the accuracy of the leakage detection device's judgment will be reduced by direct leakage detection. Therefore, the noise reduction of pipeline leakage signal is critical for preprocessing technology of pipeline leakage detection. A denoising method combining adaptive variational mode decomposition (AVMD) and singular value decomposition (SVD) is proposed in this paper. First, the mode number and the penalty factor of VMD are searched automatically by AVMD. The AVMD algorithm is coupled to a fitness function based on improved refine composite multiscale dispersion entropy (RCMDE). Subsequently, a time–frequency matrix which obtains time–frequency subspace after SVD is constructed for all mode components decomposed by VMD, and the number of effective time–frequency subspaces is determined by the relative change rate of singular values, thereby the denoised signal is achieved. Finally, the experimental results show that the AVMD-SVD method proposed in this paper has the significant denoising effect and strong robustness.

Keywords

• variational mode decomposition
• parameter optimization
• signal denoising
• pipeline leakage