Identification of Elastic Properties of Composites by Inversion of Ultrasonic Guided Wave Data

Cui, Ranting; Scalea, Francesco Lanza di

doi:10.1007/s11340-021-00700-1

Cited by 11 publications

(10 citation statements)

References 36 publications

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“…This study suggests experimental verification of numerical studies for future works. Cui and Scalea [121] 2021 The central objective of this article is the experimental validation of the recently published methodology [120] based on the SA algorithm and ultrasonic guided waves for the nondestructive identification of elastic properties of composite plates.…”

Section: VImentioning

confidence: 99%

A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

Ghannadi

Kourehli

Mirjalili

2023

Frattura Ed Integrità Strutturale

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In recent years, many innovative optimization algorithms have been developed. These algorithms have been employed to solve structural damage detection problems as an inverse solution. However, traditional optimization methods such as particle swarm optimization, simulated annealing (SA), and genetic algorithm are constantly employed to detect damages in the structures. This paper reviews the application of SA in different disciplines of structural health monitoring, such as damage detection, finite element model updating, optimal sensor placement, and system identification. The methodologies, objectives, and results of publications conducted between 1995 and 2021 are analyzed. This paper also provides an in-depth discussion of different open questions and research directions in this area.

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Section: VImentioning

confidence: 99%

A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

Ghannadi

Kourehli

Mirjalili

2023

Frattura Ed Integrità Strutturale

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“…The application of the method based on slowness residuals with initial value θ (j) signal and some noise is removed as described in Section 2. Before starting the loop at 13 the next step, the bandwidth of filter δ (1) , the coefficient of filter bandwidth compression 14 α ∈ (0, 1) and bounds Θ, where the solution is allowed, are chosen. Also, initial values 15 Ω (1) = R 2 , g(1) = g and j = 0 necessary for the first stage of the identification procedure 16 are determined at this step.…”

Section: Exitmentioning

confidence: 99%

“…Noninvasive characterization of material mechanical properties is vital for condition monitoring to control the quality of samples and to identify possible damage or structural degradation during its service period [1]. Vibration-based techniques have proven their efficiency for the evaluation of elastic properties of small-scale samples [2].…”

Section: Introductionmentioning

confidence: 99%

Improved Unsupervised Learning Method for Material Properties Identification Based on Mode Separation of Ultrasonic Guided Waves

Golub¹,

Doroshenko²,

Arsenov³

et al. 2022

Preprint

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Numerical methods, including machine learning methods, are now actively used in the applications related to guided wave propagation. The method proposed in this study for material properties characterization is based on the algorithm of the clustering of multivariate data series obtained as a result of the application of the matrix pencil method to the experimental data. In the proposed technique, multi-objective optimization is employed to improve the accuracy of particular parameter identification. At the first stage, the computationally efficient method based on the calculation of the Fourier transform of Green's matrix is employed iteratively and the obtained solution is used for the filter construction with decreasing bandwidth, which allows us to obtain nearly noise-free classified data (with mode separation). The filter provides data separation between all guided waves in a natural way, which is needed at the second stage, where the slower method based on the minimization of the slowness residuals is applied to the data. The method might be applied for material properties identification in plates with thin coatings/interlayers, multi-layered anisotropic laminates etc.

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“…And frequency points in the frequency-wavenumber spectra with wavenumber being zero are called cutoff frequency points 1,2 . Local resonances formed by zero-group velocity and cutoff frequency points will show sharp resonance peaks in the frequency spectrum, which can be utilized for non-destructive evaluation (NDE) applications, including damage detection 3,4 and material characterization 5,6 . The existence and application of those local resonances have been extensively reported in plate and pipe structures 2,7 .…”

Section: Introductionmentioning

confidence: 99%

Generating local resonances in free rails with piezoelectric elements

Zhang

et al. 2023

Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII

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Local resonances formed by zero-group velocity (ZGV) and cutoff frequency points usually demonstrate sharp resonance peaks in frequency spectra, which can be utilized for nondestructive evaluation (NDE) and Structural Health Monitoring (SHM). The existence and application of those local resonances have been extensively reported in plate and pipe structures. However, local resonances in rails are rarely studied. The team recently reported that impulse dynamic tests can promote the local resonances in rails up to 40 kHz, and the results were verified using both semi-analytical finite element (SAFE) analysis and frequency-domain fully discretized finite element analysis. In this work, we present the discovery of ZGV modes and cutoff frequency resonances in free rails up to 80 kHz using piezoelectric elements. A miniature low-cost PZT patch works as a consistent excitation source compared with the impulse dynamic testing method. First, we implement the SAFE analysis to compute dispersion curves of a standard AREMA 115RE rail and to identify potential ZGV and cutoff frequency points up to 80 kHz. Then, to understand the existence and detectability of identified ZGV and cutoff points in a free rail, we install one PZT patch on the side of the rail head. A chirp signal covering 20 to 120 kHz is selected as the excitation to cover the desired frequency range. Finally, we perform a spatial sampling of wave propagation using three receivers along the wave propagation direction to calculate the dispersion relations experimentally via two-dimensional Fourier Transforms (2D-FFT). This study verifies the existence of ZGV modes in free rail up to 80 kHz and demonstrates the feasibility of using piezoelectric elements to generate local resonances.

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Identification of Elastic Properties of Composites by Inversion of Ultrasonic Guided Wave Data

Cited by 11 publications

References 36 publications

A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

Improved Unsupervised Learning Method for Material Properties Identification Based on Mode Separation of Ultrasonic Guided Waves

Generating local resonances in free rails with piezoelectric elements

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