Delamination is the most common and dangerous failure mode for multilayered structures. Delamination defects of different shapes and sizes have different sensitivity to guided wave of different frequencies and modes. So that it is necessary to study the application of multi-frequency methods for achieving detection. In this study, the algorithm of multi-frequency localized wave energy is present using laser ultrasonic guided waves for delamination identification. Localized wave energy is acoustic energy in space under specific wavenumber. New wavenumber components occur in damaged composite plates and its localized wave energy can be used for delamination identification. The localized wave energy is not only related to mode conversion caused by the decrease of structural thickness above the delamination, but also the scattering waves in delamination region. The scattering waves make acoustic energy redistributed and it is enhanced at specific spatial position. The discovery has been verified in simulation and experiment. Multi-frequency experimental results show lower noises and more discernible profile of delamination region in two specimens, including medial and non-medial delamination. In the case of medial delamination, the actual dispersion curve is closer to the dispersion curve of upper laminate at high frequency; in the case of non-medial delamination, the actual dispersion curve is similar to the ideal situation ignoring the effect of epoxy resin. Based on the actual dispersion curves, two critical parameters of proper frequencies and filter threshold are selected for delamination identification using laser ultrasonic guided wave.

分层是多层结构最常见和最危险的失效模式。不同形状和尺寸的分层缺陷对不同频率和模式的导波具有不同的敏感性。因此有必要研究应用多频方法实现检测。在本研究中，提出了使用激光超声导波进行分层识别的多频局域波能量算法。局域波能是空间中特定波数下的声能。损坏的复合板中出现新的波数分量，其局部波能可用于分层识别。局域波能量不仅与分层以上结构厚度减小引起的模式转换有关，还有分层区域的散射波。散射波使声能重新分布并在特定空间位置增强。该发现已在模拟和实验中得到验证。多频实验结果表明，两个样本中的分层区域具有更低的噪声和更可辨别的轮廓，包括内侧和非内侧分层。在中间分层的情况下，实际的色散曲线更接近于上层层压板高频时的色散曲线；在非中间分层的情况下，实际色散曲线与忽略环氧树脂影响的理想情况相似。根据实际频散曲线，选取合适的频率和滤波阈值两个关键参数进行激光超声导波分层识别。