Denoising method for interfacial damage signals of marine composite pipelines based on improved PSO-VMD

Marine composite pipelines are critical infrastructure for offshore oil and gas transportation, and accurate damage detection is essential for maintaining structural integrity. However, interfacial damage signals are easily affected by underwater noise, including hydrodynamic disturbances, flow-induced turbulence, and mechanical vibrations, which introduce broadband interference and reduce detection reliability. To address this challenge, an adaptive denoising framework is proposed by integrating variational mode decomposition (VMD) with an improved particle swarm optimization (IPSO) algorithm. The IPSO algorithm incorporates linearly decreasing inertia weights, adaptive acceleration coefficients, and minimum envelope entropy to optimize VMD parameters automatically. Furthermore, a dual-feature IMF selection strategy combining correlation coefficient, envelope entropy, and K-means clustering is developed to distinguish effective signal components for reconstruction. The proposed method is validated using simulated signals and experimental signals acquired under flow-induced noise generated by a laboratory-scale recirculating water system. Experimental results show that IPSO-VMD achieves an SNR of 14.08 dB and a correlation coefficient of 0.98, corresponding to relative improvements of 65.06% and 7.69%, respectively, compared with conventional VMD. The proposed method effectively suppresses underwater noise while preserving damage-related features, providing a reliable signal preprocessing framework for marine pipeline interfacial damage detection under controlled experimental conditions.