The guided wave is an efficient and reliable tool for the structural health monitoring (SHM) of the composite laminates. In the guided wave-based SHM methods, extracting the dispersion curves is essential for integrity evaluation. In this study, a sparse wavenumber analysis based on hybrid least absolute shrinkage and selection operator (Lasso) regression is proposed to extract the dispersion curves in the frequency–wavenumber distribution (FKD) for the composite laminate. The hybrid Lasso regression model is constructed based on the guided wave propagation mechanism. Considering that responses of some wave modes are very weak at specific frequencies due to the guided wave attenuation in the composite laminates, the group-sparsity and continuity regularizations are imposed in this model to improve frequency–wavenumber resolution and remove noises. Only few sensors are required for the proposed method to extract the dispersion curves. Both the simulation and the experiment are used to verify the effectiveness of the proposed method. Furthermore, the material property of the composite laminate in the experiment is non-destructively estimated by using the dispersion curves extracted by the proposed method.

导波是用于复合材料层压板结构健康监测 (SHM) 的有效且可靠的工具。在基于导波的 SHM 方法中，提取色散曲线对于完整性评估至关重要。在这项研究中，提出了一种基于混合最小绝对收缩和选择算子 (Lasso) 回归的稀疏波数分析，以提取复合材料层压板的频率 - 波数分布 (FKD) 中的色散曲线。混合Lasso回归模型是基于导波传播机制构建的。考虑到由于复合材料层压板中的导波衰减，某些波模式在特定频率下的响应非常弱，因此在该模型中强加了群稀疏性和连续性正则化以提高频率 - 波数分辨率并去除噪声。所提出的方法只需要很少的传感器来提取色散曲线。仿真和实验均用于验证所提出方法的有效性。此外，实验中复合材料层压板的材料特性是通过使用所提出的方法提取的色散曲线来无损估计的。