An improved variational mode decomposition method based on the optimization of salp swarm algorithm used for denoising of natural gas pipeline leakage signal

Abstract

Natural gas pipeline leak detection is susceptible to environmental noise, which leads to low detection accuracy. Denoising of natural gas pipeline leak signals is of great significance for improving the accuracy of pipeline leak detection. Variational mode decomposition (VMD) has the function of signal denoising. However, the inaccurate setting of VMD parameters will affect the result of signal decomposition. Therefore, an improved VMD adaptive signal denoising method is proposed in this paper. First, the control parameters of VMD, i.e. decomposition layer number K and penalty factor α, are optimized by using the salp swarm algorithm (SSA). The ratio of the mean and variance of the permutation entropy (PE) is used as the fitness function of SSA. Then, the optimized VMD is used to decompose the pipeline leakage signal to obtain several intrinsic mode functions (IMFs). Finally, the PE is used to select IMFs containing leakage features for reconstruction so as to obtain the denoised signal. The comparative experimental analysis shows that the improved VMD method after SSA optimization has stronger denoising robustness than other denoising methods.