Effects of temperature variations on guided waves propagating in composite structures

Shoja, Siavash; Berbyuk, Viktor; Boström, Anders E

doi:10.1117/12.2218791

Cited by 6 publications

(7 citation statements)

References 14 publications

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“…The variations of temperature affect the propagation of guided waves in laminated composites, as confirmed by the previous studies, [70][71][72][73][74] and the same phenomenon is observed in the current work. The data clusters showing the effect of temperature variation on the healthy state of the composite plate are shown in the red elliptical boundary of Figure 9.…”

Section: Resultssupporting

confidence: 91%

Damage assessment of laminated composites using unsupervised autonomous features

Khan,

Kim

2023

Journal of Thermoplastic Composite Materials

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This article proposes a framework for the damage assessment of and effect of temperature variations in laminated composites using Lamb waves and unsupervised autonomous features. A network of piezoelectric transducers is employed to generate data for 18 health states of a laminated composite plate. The data is processed with sparse autoencoder (SAE) for unsupervised autonomous features. The discriminative capabilities of the extracted features are confirmed by processing the feature space in the supervised and unsupervised frameworks of machine learning. The confusion matrices of supervised learning provided physical insights into the problem. The feature space was also visualized in two dimensions in an unsupervised manner through principal component analysis (PCA), which revealed physically consistent results for the effect of temperature variations, damage of different severity levels, and the undamaged paths between the actuator and sensors. The healthy state data and information on the paths between the actuator and sensors was processed via SAE for damage localization. The proposed approach can be employed for the autonomous assessment of composite structures for the presence of damage and variations of operating temperatures while using both supervised and unsupervised machine learning algorithms.

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Section: Resultssupporting

confidence: 91%

Damage assessment of laminated composites using unsupervised autonomous features

Khan,

Kim

2023

Journal of Thermoplastic Composite Materials

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“…where α and β are the temperature-dependent stretch factors of symmetric and asymmetric wave modes and are obtained by calibrating the model with experimental data. Previous work by the authors described BSS with mode decomposition in detail (Shoja et al, 2016). The method is applied to the results obtained by the FE model in this study in order to handle the effects of temperature on GW propagating in composite structures.…”

Section: Effects Of Temperaturementioning

confidence: 99%

“…In this method, a signal in the time domain is stretched or compressed in such a way that it matches to another signal. Although BSS is a simple method with reasonable accuracy, it is previously shown (Shoja et al, 2016) that the method needs to be modified when it comes to composite materials.…”

Section: Computational Modelmentioning

confidence: 99%

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Guided wave–based approach for ice detection on wind turbine blades

2018

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An efficient ice detection system is an important tool to optimize the de-icing processes in wind turbines operating in cold climate regions. The aim of this work is to study the application of guided wave for ice detection on wind turbine blades. Computational model is developed to simulate guided wave propagation on composite structures. The model has been validated with experimental data obtained in cold climate laboratory. Effect of ice accretion on composite structures is studied in the time, frequency and wavenumber domains. In each case, post-processing algorithms as well as icing index are introduced which are sensitive to accumulated ice on the composite structure. The algorithms and icing index are applied to both simulation results and experimental data. Analysis of the obtained results has shown that the guided wave-based approach can be used for developing ice detection systems for wind turbine blades.

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“…Results verify that BSS with mode decomposition (MD) shows slightly better performance than BSS with one stretch factor. 26 Despite numerous methodologies in literature, however, it has been summarized that it is not possible to completely manipulate the effect of temperature in SHM, and there is still need of further improvements and authentic model to identify and estimate the thermal sensitivity of ultrasonic guided waves. Therefore, the interpretation of temperature effect on the guided wave propagation in real-time practical inspections through an authentic model is necessary to achieve optimum results.…”

Section: Introductionmentioning

confidence: 99%

Optimization of ultrasonic guided wave inspection in structural health monitoring based on thermal sensitivity evaluation

Abbas

Qiu

et al. 2020

Journal of Low Frequency Noise, Vibration and Active Control

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Damage detection in a mechanical structure using ultrasonic guided waves becomes even more problematic when the effect of variation in environmental and operating conditions, such as mechanical noise, temperature, flow rate, inner pressure, etc. is taken into account. The variation in these environmental and operating conditions can degrade the accuracy of the damage inspection process. The basic purpose of current research work is to propose a finite element model–based simulation model to identify and estimate the influence of environmental temperature on the measured signal and meanwhile perceive the temperature invariant points to provide an optimal baseline for thermal attenuation in real-time ultrasonic guided wave inspections. This model signifies the variation in material elastic properties, thermal sensitivities, and the abrupt changes in group and phase velocities of S0 wave mode with temperature. A low bandpass filter is used to keep the excitation frequency in a certain range and remove the noise from it. The numerical investigation is achieved in [Formula: see text] on the basis of six parameters, including variation in strain rate and stress, the amplitude of displacement, symmetric and anti-symmetric dispersion curves, time of flight, group velocity, and natural frequency of the beam. A wave velocity function has been generated in the Matlab® environment to calculate the group velocity of guided waves considering the effect of both temperature and excitation frequency. A linear fit curve (first-degree polynomial) is utilized in this function to analyze the effect of temperature on group velocity. An analytical estimation has also been applied to evaluate the impact of temperature on the material properties and damage detection. The simulation model is validated against the analytical group velocity results and experimental wave amplitude results. The comparison with minute percentage error is achieved in a convincing manner. The proposed thermal sensitivity simulation model is more efficient and reliable as compared to optimal baseline selection and baseline signal stretch. It detects not only the occurrence of damage but also examines the influence of environmental temperature on ultrasonic guided wave propagation and perceives the temperature invariant points to provide an optimal baseline for thermal attenuation in real-time ultrasonic guided wave inspections. This model can also be implemented practically in transportation and industrial applications to ensure structural reliability.

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Effects of temperature variations on guided waves propagating in composite structures

Cited by 6 publications

References 14 publications

Damage assessment of laminated composites using unsupervised autonomous features

Damage assessment of laminated composites using unsupervised autonomous features

Guided wave–based approach for ice detection on wind turbine blades

Optimization of ultrasonic guided wave inspection in structural health monitoring based on thermal sensitivity evaluation

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