Ultrasonic Lamb waves multimodal separation through independent component analysis in the time-frequency domain

被引:0
|
作者
Lou, Sijia [1 ]
Liu, Zhenli [1 ]
Xu, Kailiang [1 ,2 ]
Zhou, Chang [3 ]
Le, Lawrence H. [4 ]
Ta, Dean [1 ,2 ]
机构
[1] Department of Electronic Engineering, Fudan University, Shanghai,200433, China
[2] Zhuhai Fudan Innovation Institute, Zhuhai,519000, China
[3] Ningbo Marvoto Intelligent Technology, Ningbo,315300, China
[4] Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton,AB,T6G2R3, Canada
来源
Shengxue Xuebao/Acta Acustica | 2021年 / 46卷 / 01期
关键词
Ultrasonic waves - Independent component analysis - Fourier series - Frequency domain analysis - Thickness measurement - Finite difference time domain method - Light velocity - Modal analysis - Signal to noise ratio;
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学科分类号
摘要
To facilitate Lamb waves signal analysis and mode characterization, a multimodal Lamb waves identification method combining Short-Time Fourier Transform (STFT) and Independent Component Analysis (ICA) was proposed. Temporal signals were first projected into the time-frequency domain using STFT. Since different modes were relatively independent in the time-frequency domain, ICA was then introduced to realize the multimodal separation. The group velocity curve of each mode was extracted according to its time-frequency energy ridge. Thus, the plate thickness can be further estimated. The proposed method was applied to the Finite-Difference Time-Domain (FDTD) simulation and the steel plate experiment, with A0, S0 and A1 mode being separated. The average error of group velocity estimation in simulation and experiment was about 1.5% and 2.0%, with that of plate thickness estimation being 0.3% and 2.0% approximately. The simulation results show that, as the Signal-to-Noise Ratio (SNR) is not less than 0 dB, the timefrequency independent component analysis method can be used for Lamb waves multimodal separation, group velocity curves extraction and plate thickness estimation. © 2021 Acta Acustica.
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页码:103 / 110
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