Simulated Lamb wave propagation method for nondestructive monitoring of matrix cracking in laminated composites

Mardanshahi, Ali; Shokrieh, M.M.; Kazemirad, Siavash

doi:10.1177/14759217211008620

Cited by 18 publications

(10 citation statements)

References 60 publications

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“…At the cost of significant computational power requirements, numerical methods allow for complex real case scenario simulation. Recent advances covers in particular: Guided waves scattering on impact damage of composite structures [ 43 , 47 ] or delaminations [ 48 ]; Transmission of guided waves across partially-closed cracks [ 49 ]; Wave damage interaction coefficients for lightweight structures [ 10 ]; Damage of reinforced concrete beams [ 50 ]; Looseness of joint structures in cylindrical waveguides [ 51 ]; Matrix cracking in laminated composites [ 52 ]. …”

Section: Materials and Methodsmentioning

confidence: 99%

Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks

Heesch

Dziendzikowski

Mendrok

et al. 2022

Sensors

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Guided waves are a potent tool in structural health monitoring, with promising machine learning algorithm applications due to the complexity of their signals. However, these algorithms usually require copious amounts of data to be trained. Collecting the correct amount and distribution of data is costly and time-consuming, and sometimes even borderline impossible due to the necessity of introducing damage to vital machinery to collect signals for various damaged scenarios. This data scarcity problem is not unique to guided waves or structural health monitoring, and has been partly addressed in the field of computer vision using generative adversarial neural networks. These networks generate synthetic data samples based on the distribution of the data they were trained on. Though there are multiple researched methods for simulating guided wave signals, the problem is not yet solved. This work presents a generative adversarial network architecture for guided waves generation and showcases its capabilities when working with a series of pitch-catch experiments from the OpenGuidedWaves database. The network correctly generates random signals and can accurately reconstruct signals it has not seen during training. The potential of synthetic data to be used for training other algorithms was confirmed in a simple damage detection scenario, with the classifiers trained exclusively on synthetic data and evaluated on real signals. As a side effect of the signal reconstruction process, the network can also compress the signals by 98.44% while retaining the damage index information they carry.

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Section: Materials and Methodsmentioning

confidence: 99%

Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks

Heesch

Dziendzikowski

Mendrok

et al. 2022

Sensors

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“…Lamb waves are typical ultrasonic guided waves propagating in plate-like structures and are capable of propagating long distances. It has been confirmed that Lamb waves are sensitive to both surface and internal defects, such as crack, 1 corrosion, 2 matrix cracking, 3 and delamination. 4 Lamb wave-based structural health monitoring (SHM) and nondestructive testing (NDT) methods are efficient because these methods can monitor or detect the area of the whole Lamb wave propagation path.…”

Section: Introductionmentioning

confidence: 91%

Waveform covariance imaging for Lamb wave phased array

Deng

2022

Structural Health Monitoring

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The amplitude and the phase information are both important for damage localization in Lamb wave–based structural health monitoring and non-destructive testing. Most previous studies in Lamb wave imaging are only based on either the amplitude or phase of the signal at the time of flight. In this study, a post-processing technique for Lamb wave phased array imaging is proposed for isotropic plates, which simultaneously utilizes both the amplitude and phase information within a small neighborhood centered at the time of flight. In the proposed imaging algorithm, a modified virtual time reversal is firstly implemented to compensate for dispersion and the amplitude decrease caused by wave diffusion. Then the waveform covariance between any two processed wave packets, which contains information of both amplitude and phase, is used as the indicator of the presence of damage. Finally, adaptive weights based on minimum variance are introduced to weight and sum the waveform covariance for damage imaging. Based on a uniform circular array, experimental results on an aluminum plate with three defects verify that the proposed algorithm is capable of localizing multiple defects, suppressing background noise and main lobe width.

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“…Many researchers have used finite element (FE) simulations to investigate the wave propagation problems. [34][35][36][37][38][39][40][41][42] For example, Alleyne and Cawley 35 assessed the interaction of the Lamb waves and defects in plate-like structures using FE simulations. They showed that different parameters affect the sensitivity of Lamb waves to defects, including the geometry of the plate, wave mode, wave frequency-thickness, and the type of the notch defect.…”

Section: Introductionmentioning

confidence: 99%

“…The finite element method (FEM) is the most stable numerical solution technique to study the characteristics of wave propagation in different structures. Many researchers have used finite element (FE) simulations to investigate the wave propagation problems 34–42 . For example, Alleyne and Cawley 35 assessed the interaction of the Lamb waves and defects in plate‐like structures using FE simulations.…”

Section: Introductionmentioning

confidence: 99%

Detection and characterization of matrix cracking in fiber‐metal laminates using Lamb wave propagation

Fattahi

Ramezani

Shokrieh

et al. 2022

Structural Contr & Hlth

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The purpose of the present study was to assess the capability of finite element (FE) simulations of guided Lamb wave propagation for the characterization of the modulus of fiber-metal laminates (FMLs) and detection of the matrix cracking in them. An FE model of an FML specimen with a [Al/90 2 /Al/ 90 2 /Al] layup was developed. The matrix cracking with different densities was also induced in the fiber-reinforced composite layers of the FML model. The fundamental antisymmetric Lamb wave mode was propagated on the developed model at frequencies from 50 to 300 kHz. The Lamb wave velocity was obtained from the FE models at different frequencies. Then, the inverse Lamb wave propagation problem was solved and the elastic modulus of the simulated FML specimen was estimated. An experimental program was conducted to evaluate the results of FE simulations. The FML specimens with the same layup and materials were fabricated and underwent the tensile and Lamb wave propagation tests. The average elastic moduli of the specimens obtained from the tests, classical lamination theory, and FE simulations were in good agreement, especially at low frequencies. It was observed that the sensitivity of the Lamb wave velocity to matrix cracks was higher at high frequencies.

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Simulated Lamb wave propagation method for nondestructive monitoring of matrix cracking in laminated composites

Cited by 18 publications

References 60 publications

Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks

Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks

Waveform covariance imaging for Lamb wave phased array

Detection and characterization of matrix cracking in fiber‐metal laminates using Lamb wave propagation

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