When using Lamb wave for damage detection in plate-like structures, factors such as unknown material properties, anisotropy and iterative operation for solving nonlinear equations make it difficult to accurately localize damages. This problem becomes even more difficult when multiple damages exist in the plate. To overcome these difficulties, a rapid technique for localizing multiple damages in plate-like structures without any prior knowledge of direction-dependent velocity profile is proposed in this paper. The time difference of arrival is obtained by performing cross-correlation processing on the damage features extracted from the received signal. Damage artifacts are removed using relative location determination and relative probability density analysis. Multi-damage localization at different locations were simulated. The proposed technique is validated experimentally for steel plates. Simulation and experimental results show that the proposed technique can realize multiple damage localization in plate-like structures with unknown material properties. With the help of L-shaped sensor clusters, damage locations for isotropic and anisotropic materials can be quickly predicted without solving nonlinear equations and without taking into account the dispersion effects. The results suggest that a suitable threshold range is set to 0.5–0.7 to remove damage artifacts.

在利用兰姆波对板状结构进行损伤检测时，由于未知的材料特性、各向异性以及求解非线性方程的迭代运算等因素，难以准确定位损伤。当板中存在多处损坏时，这个问题变得更加困难。为了克服这些困难，本文提出了一种快速定位板状结构中多重损伤的技术，而无需事先了解与方向相关的速度剖面。到达时间差是通过对接收信号中提取的损伤特征进行互相关处理得到的。使用相对位置确定和相对概率密度分析去除损伤伪影。模拟了不同位置的多损伤定位。所提出的技术在钢板上进行了实验验证。仿真和实验结果表明，该技术可以在材料特性未知的板状结构中实现多重损伤定位。借助 L 形传感器集群，可以快速预测各向同性和各向异性材料的损伤位置，而无需求解非线性方程，也无需考虑色散效应。结果表明，将合适的阈值范围设置为 0.5–0.7 以消除损坏伪影。可以快速预测各向同性和各向异性材料的损伤位置，而无需求解非线性方程，也无需考虑色散效应。结果表明，将合适的阈值范围设置为 0.5–0.7 以消除损坏伪影。可以快速预测各向同性和各向异性材料的损伤位置，而无需求解非线性方程，也无需考虑色散效应。结果表明，将合适的阈值范围设置为 0.5–0.7 以消除损坏伪影。