Application of the SCSSA-VMD Denoising Method in Natural Gas Pipeline Leakage Detection

The decomposition performance of variational mode decomposition (VMD) on natural gas pipeline leakage pressure signals is highly sensitive to the subjective selection of its key parameters: the number of modes K and the penalty factor α. To address this issue, this paper proposes an enhanced sparrow search algorithm (SSA) that integrates sine/cosine searching and Cauchy mutation strategies, referred to as SCSSA, for optimizing the VMD parameter combination. Experimental results demonstrate that the SCSSA-optimized VMD method significantly outperforms denoising approaches based on the standard SSA and particle swarm optimization (PSO) in optimizing VMD parameters. Specifically, the proposed method achieves a higher signal-to-noise ratio (SNR) and a lower root mean square error (RMSE) in the denoised signal, effectively enhancing the denoising performance.