Keywords
Leakage detection
Sparrow search algorithm (SSA)
Variational mode decomposition (VMD)
Signal denoising
Submitted : 2026-01-14
Accepted : 2026-01-29
Published : 2026-02-13
Abstract
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.
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