@Article{sdhm.2025.071278,
AUTHOR = {Weichen Wang, Shaofeng Wang, Wenjing Liu, Luncai Zhou, Erqing Zhang, Ting Gao, Grigory Petrishin},
TITLE = {Suppression of Dry-Coupled Rubber Layer Interference in Ultrasonic Thickness Measurement: A Comparative Study of Empirical Mode Decomposition Variants},
JOURNAL = {Structural Durability \& Health Monitoring},
VOLUME = {20},
YEAR = {2026},
NUMBER = {1},
PAGES = {0--0},
URL = {http://www.techscience.com/sdhm/v20n1/65360},
ISSN = {1930-2991},
ABSTRACT = {In dry-coupled ultrasonic thickness measurement, thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy. Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise. This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference. By decomposing A-scan signals into Intrinsic Mode Functions (IMFs), the framework employs energy contribution thresholds (>85%) and kurtosis indices (>3) to autonomously select IMFs containing valid specimen echoes. Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing. Experimental results demonstrate the framework’s robustness, achieving 92.3% thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling, outperforming conventional methods by up to 18.7%. The dual-criterion approach reduces operator dependency by 37% and maintains ΔT < 0.03 mm under surface roughness up to 6.3 μm, offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.},
DOI = {10.32604/sdhm.2025.071278}
}