Page 123 - 《应用声学》2021年第5期

第 40 卷 第 5 期 Vol. 40, No. 5
2021 年 9 月 Journal of Applied Acoustics September, 2021

⋄ 研究报告 ⋄

小样本字典学习的兰姆波模态识别方法 ∗

李娟娟 1,2†

(1 山西师范大学 太原 030031)
(2 中北大学 信息探测与处理山西省重点实验室 太原 030051)

摘要：针对兰姆波多模态识别问题，提出了基于小样本字典学习的模态识别方法。将多层复合板的频散特性
看作一个线性时不变系统。首先，根据频散知识模拟各个模态传播特定距离后的信号，提取走时和能量特征创
建字典；其次，获取待测信号的走时特征，通过查询字典来识别兰姆波模态；最后，根据能量参数估计结果，实现
待测信号中各模态信号的分离和重构。通过对 3 层粘接的 AAA 板 (铝板 -亚克力板 -铝板，每层厚度为 2 mm)
中传播距离为 0.3 m、0.5 m 的直达波和反射波的仿真验证，结果显示该方法对 A 0、S 0 模态的有效识别和各个
波包信号的准确重建。
关键词：兰姆波；频散特性；模态识别；走时特征
中图法分类号: TB55; TP18 文献标识码: A 文章编号: 1000-310X(2021)05-0767-07
DOI: 10.11684/j.issn.1000-310X.2021.05.016

Lamb mode identification method based on small samples
dictionary learning

LI Juanjuan 1,2

(1 Shanxi Normal University, Taiyuan 030031, China)
(2 Shanxi Key Laboratory of Signal Capturing & Processing, North University of China, Taiyuan 030051, China)

Abstract: In this paper, a Lamb mode identification method based on small samples dictionary learning is
proposed. Firstly, according to the dispersion characteristics of multi-layer plate, Lamb waves of each mode
propagating at specific distances are simulated, and the signal features (time of flight, energy distribution) are
extracted to create a dictionary; secondly, the traveling time of the signal to be identified is extracted, then
Lamb modes are identified by searching the dictionary; finally, the energy parameters are estimated, and signal
separation and reconstruction is realized. Through the experimental verification of direct wave and reflected
wave with propagation distance of 0.3 m and 0.5 m in AAA plate (aluminum-acrylic-aluminum plate, thickness
of each layer is 2 mm), A 0 and S 0 modes can be identified and reconstruction effectively.
Keywords: Lamb wave; Dispersion characteristic; Mode identification; Time of flight

2020-12-22 收稿; 2021-03-14 定稿
山西省高等学校科技创新计划项目 (2020L0699), 中北大学信息探测与处理重点实验室基金项目 (ISPT2020-8)
∗
作者简介: 李娟娟 (1987– ), 女, 山西太原人, 博士, 研究方向: 复合层叠结构的超声导波检测方法。
† 通信作者 E-mail: lijj0921@163.com1