An Improved VMD Method for Use with Acoustic Impact Response Signals to Detect Corrosion at the Underside of Railway Tracks

Variational Mode Decomposition (VMD) is widely used for inspection purposes. The initial parameters are usually set manually, which is a limitation of this technique. In this paper, a method to automatically select these parameters through a combination of Singular Value Decomposition (SVD) and Improved-VMD (IVMD) is proposed. VMD is applied multiple times with a varying K-value parameter. The original signal and its sub-signals arising from VMD decomposition are all subjected to SVD. An index representing the relevance between sub-signals and the original signal is obtained by comparing eigenvalues, which are calculated by SVD. The result shows the effectiveness of VMD with different initial K-value parameters. SVD is then further applied to the VMD result for the selected K-value parameter to obtain Shannon entropy, which can be used in the detection and classification of corrosion on the underside of the rail. Comparing with current energy-based methods, the Shannon entropy obtained by IVMD-SVD has the advantage of reducing environmental interference to obtain more uniform energy results. The proposed method can improve the effectiveness of VMD for the impact response signal. The classification of underside corrosion of rails can be realised according to the results obtained from the proposed method.

Automated summary

In this paper, a method combining Singular Value Decomposition (SVD) and Improved-VMD (IVMD) is proposed to automatically select parameters for Variational Mode Decomposition (VMD). The results show the effectiveness of VMD with different initial K-value parameters. The Shannon entropy obtained by IVMD-SVD has the advantage of reducing environmental interference and obtaining more uniform energy results compared to current energy-based methods.