An approach based on expectation-maximization algorithm for parameter estimation of Lamb wave signals

•Develop a model function with five parameters to model the Lamb wave signal.•Adopt EM algorithm to obtain the parameters.•Study the convergence property using synthetic signals.•Experimentally study the effectiveness of mode identification and time locating. In the structural health monitoring or n...

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Published in:Mechanical systems and signal processing Vol. 120; pp. 341 - 355
Main Authors: Jia, Hongbo, Zhang, Zhichun, Liu, Hongwei, Dai, Fuhong, Liu, Yanju, Leng, Jinsong
Format: Journal Article
Language:English
Published: Berlin Elsevier Ltd 01.04.2019
Elsevier BV
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ISSN:0888-3270, 1096-1216
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Abstract •Develop a model function with five parameters to model the Lamb wave signal.•Adopt EM algorithm to obtain the parameters.•Study the convergence property using synthetic signals.•Experimentally study the effectiveness of mode identification and time locating. In the structural health monitoring or nondestructive examination system based on the Lamb wave technology, the accurate and valid characteristics of wave packet extracted from the signal are critical factors to evaluate damage. However, the dispersion effect and the multi-mode characteristic in the elastic wave make the data extraction difficult and degrade the resolution, and therefore further prevent the effectiveness of Lamb wave for damage detection. In this study, we proposed a model-based approach for extracting effective characteristics from the noisy signals. By taking the narrow band Gabor pulse as the incident pulse and considering the general non-linear frequency dispersion (quadratic dispersion), we developed a model with five parameters to model the dispersive wave packet and obtained the parameter vector of each wave packet by the expectation-maximization (EM) algorithm. The parameters in the model present the characteristics of signals, which can be further applied to locate and evaluate the structure’s damage. To study the convergence property, synthetic signals with different sampling rates and noise intensities were considered. Furthermore the developed approach is also verified by the experimental data from an isotropic aluminum plate.
AbstractList •Develop a model function with five parameters to model the Lamb wave signal.•Adopt EM algorithm to obtain the parameters.•Study the convergence property using synthetic signals.•Experimentally study the effectiveness of mode identification and time locating. In the structural health monitoring or nondestructive examination system based on the Lamb wave technology, the accurate and valid characteristics of wave packet extracted from the signal are critical factors to evaluate damage. However, the dispersion effect and the multi-mode characteristic in the elastic wave make the data extraction difficult and degrade the resolution, and therefore further prevent the effectiveness of Lamb wave for damage detection. In this study, we proposed a model-based approach for extracting effective characteristics from the noisy signals. By taking the narrow band Gabor pulse as the incident pulse and considering the general non-linear frequency dispersion (quadratic dispersion), we developed a model with five parameters to model the dispersive wave packet and obtained the parameter vector of each wave packet by the expectation-maximization (EM) algorithm. The parameters in the model present the characteristics of signals, which can be further applied to locate and evaluate the structure’s damage. To study the convergence property, synthetic signals with different sampling rates and noise intensities were considered. Furthermore the developed approach is also verified by the experimental data from an isotropic aluminum plate.
In the structural health monitoring or nondestructive examination system based on the Lamb wave technology, the accurate and valid characteristics of wave packet extracted from the signal are critical factors to evaluate damage. However, the dispersion effect and the multi-mode characteristic in the elastic wave make the data extraction difficult and degrade the resolution, and therefore further prevent the effectiveness of Lamb wave for damage detection. In this study, we proposed a model-based approach for extracting effective characteristics from the noisy signals. By taking the narrow band Gabor pulse as the incident pulse and considering the general non-linear frequency dispersion (quadratic dispersion), we developed a model with five parameters to model the dispersive wave packet and obtained the parameter vector of each wave packet by the expectation-maximization (EM) algorithm. The parameters in the model present the characteristics of signals, which can be further applied to locate and evaluate the structure’s damage. To study the convergence property, synthetic signals with different sampling rates and noise intensities were considered. Furthermore the developed approach is also verified by the experimental data from an isotropic aluminum plate.
Author Liu, Hongwei
Leng, Jinsong
Jia, Hongbo
Dai, Fuhong
Liu, Yanju
Zhang, Zhichun
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  organization: Center for Composite Materials and Structures, Harbin Institute of Technology, Harbin 150080, PR China
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Keywords Lamb wave
Parameter estimation
Gabor pulse
Multi-mode characteristic
EM algorithm
Dispersion effect
Language English
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SSID ssj0009406
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Snippet •Develop a model function with five parameters to model the Lamb wave signal.•Adopt EM algorithm to obtain the parameters.•Study the convergence property using...
In the structural health monitoring or nondestructive examination system based on the Lamb wave technology, the accurate and valid characteristics of wave...
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SubjectTerms Algorithms
Aluminum
Damage assessment
Damage detection
Dispersion effect
Elastic waves
EM algorithm
Gabor pulse
Lamb wave
Lamb waves
Mathematical models
Maximization
Metal plates
Multi-mode characteristic
Nondestructive testing
Parameter estimation
Structural damage
Structural health monitoring
Wave dispersion
Title An approach based on expectation-maximization algorithm for parameter estimation of Lamb wave signals
URI https://dx.doi.org/10.1016/j.ymssp.2018.10.020
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Volume 120
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