复合材料科学与工程Issue(4)：44-54,11.DOI:10.19936/j.cnki.2096-8000.20260428.006
基于自适应聚类与语义加权的空气耦合兰姆波无基准损伤成像方法
A baseline-free damage imaging method for air-coupled lamb waves based on adaptive clustering and semantic weighting
摘要
Abstract
This paper proposes a baseline-free probability imaging method integrating density clustering and se-mantic weighting to overcome the reliance on defect-free reference signals and boundary artifacts in traditional air-coupled Lamb wave imaging.Full-path response signals are collected via orthogonal scanning.A joint feature vector is constructed using wavelet low-frequency approximation coefficients and a normalized symmetric difference factor,followed by density-based spatial clustering of applications with noise(DBSCAN)to unsupervisedly classify scan paths into"healthy"or"damaged"states.The resulting semantic labels are embedded as adaptive weights into an improved reconstruction algorithm for probabilistic inspection of damage(RAPID)model,suppressing artifact paths and dynamically constructing a soft baseline.Experiments on CFRP delamination defects show that the method,requi-ring no prior baseline,reduces the average size measurement error by 50.5%compared to traditional RAPID.For a 40 mm×20 mm×0.05 mm defect,measurement accuracy in the X/Y directions has improved by 81.7%and 65.5%,respectively,while effective identification of a 20 mm×20 mm×0.05 mm defect is achieved.Stable imaging perform-ance is maintained even at a 5 dB SNR.This method effectively eliminates the baseline dependency and enhances de-tection accuracy and robustness,demonstrating significant engineering potential.关键词
无基准成像/密度聚类/语义加权/空气耦合兰姆波/碳纤维增强复合材料/边界伪影抑制Key words
baseline-free imaging/density clustering/semantic weighting/air-coupled Lamb waves/CFRP/boundary artifact suppression分类
通用工业技术引用本文复制引用
秦塬,周进节,彭志康..基于自适应聚类与语义加权的空气耦合兰姆波无基准损伤成像方法[J].复合材料科学与工程,2026,(4):44-54,11.基金项目
中央引导地方科技发展资金(YDZJSX2024B006) （YDZJSX2024B006）
