Denoising Method of Pipeline Leakage Signal Based on VMD and Hilbert Transform

Abstract

In order to solve the problem of low localization accuracy of water supply pipeline leakage detection using acoustic emission signals, a noise reduction algorithm based on variational mode decomposition (VMD) and Hilbert transform is proposed in this paper. Firstly, the leakage signal is decomposed into several intrinsic mode functions (IMF) using VMD, and the number of decomposition layers is determined, and the IMF component is transformed by Hilbert to get the marginal spectrum, and the noise are preliminarily filtered according to the marginal spectrum characteristics and the cross-correlation coefficient. Secondly, the signal denoising is realized by using filtering technology and cross-correlation coefficient. Finally, the time delay estimation of the denoised signal is estimated and the location of the leakage point is calculated based on the positioning principle. In order to verify the performance of the algorithm, a water supply pipeline experiment platform for leakage simulation and leak location experiment was conducted. The cross-correlation algorithm, VMD-correlation coefficient algorithm, and the proposed algorithm are analyzed through simulation and experiment. The results show that compared with the other two algorithms, the proposed algorithm can effectively remove the noise in the leakage signal and improve the accuracy of leakage location.