Guided wave-based detection of delamination and matrix cracking in composite laminates

Wandowski, Tomasz; Malinowski, Paweł; Kudela, Paweł; Ostachowicz, Wiesław

doi:10.1243/09544062jmes1907

Cited by 16 publications

(10 citation statements)

References 26 publications

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“…7 Due to the advantages of low cost and the ability to rapidly measure large areas, testing technology based on the guided wave has drawn more and more attention. 8,9 Moreover, with the laser ultrasonic testing system, the guided wave propagating in composite structures can be measured in a convenient and flexible way. 10,11 The wavefield data provides a rich source of fatigue-related features, including group velocity, phase velocity, and attenuation of wave amplitude.…”

Section: Introductionmentioning

confidence: 99%

Fatigue evolution prediction for fiber‐reinforced plastics based on frequency‐wavenumber wavefield of guided wave using deep‐learning model

Huang,

Zhang,

Tao

et al. 2023

Fatigue Fract Eng Mat Struct

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Employing the laser ultrasonic system, information on fatigue evolution can be captured and explicitly stored in the frequency‐wavenumber wavefield of the guided wave. This paper presents a deep‐learning architecture for processing the frequency‐wavenumber wavefield, which comprises two distinct steps: fatigue characterization and evolution prediction. Firstly, the fatigue characterization step employs a convolutional autoencoder (CAE) for compressing the frequency‐wavenumber wavefield and a fully connected network (FCN) for obtaining the fusion fatigue characteristic. Due to the high cost of experimental samples, extensive simulation‐generated wavefields are used to pre‐train the network. Subsequently, the fatigue evolution prediction model based on the latent ordinary differential equation (Latent‐ODE) is trained for the step‐by‐step prediction of fatigue evolution with a small amount of composite fatigue test data. The results validate the effectiveness of the deep‐learning architecture in characterizing fatigue and predicting its evolution, as well as the feasibility of the frequency‐wavenumber wavefield compression of guided wave.

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Section: Introductionmentioning

confidence: 99%

Fatigue evolution prediction for fiber‐reinforced plastics based on frequency‐wavenumber wavefield of guided wave using deep‐learning model

Huang,

Zhang,

Tao

et al. 2023

Fatigue Fract Eng Mat Struct

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show abstract

“…Both costly in monetary terms and down time, these operations can be replaced with a new genre of inspection techniques called active structural health monitoring [1]. This new technology requires the placement of sensors in the structure permanently that can be interrogated continuously or periodically or as the need arises.…”

Section: Introductionmentioning

confidence: 99%

The Continuous Monitoring of the Health of Composite Structure

Masango

Philander

Msomi

2018

Journal of Engineering

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Currently nondestructive testing techniques for composite aircraft structures are disadvantaged when compared to instant structural health monitoring (SHM) systems that monitor the structure while being in-service and give real-time data. This paper reports on the use of Polyvinylidene Fluoride (PVDF) sensors in sensing (or monitoring) and locating the defect of a flexible composite structure. The samples used for the tests were manufactured through the use of vacuum infusion process. The threepoint bending test was performed to determine the material properties. The vertical sample deflection was measured through the use of vertical height Vernier. It should be noted that the samples were analyzed as cantilever beam due to limited availability of test equipment. The sample health was monitored through the use of PVDF sensor. The sensor data was logged and recorded through the use of Fluke-View scopemeter. The 50 g mass pieces were used as a mode of subjecting the structure to the vertical load. The experiment was performed on samples with defects (drilled 3 mm hole) sample and no-defected sample. The deflection and output voltage from the PVDF sensor of all the samples were comparatively studied.

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“…The second general approach is the guided wave approaches, which used the propagation of the wave in the structure to detect and characterize the damage state of structures. [23][24][25] The wave analysis tool like WFEM has been used to identify the damage in the framework of guided waves techniques. Kharrat et al [26][27][28][29] used a torsional wave to detect damage in a pipe and determine its size based on a database of reflection.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of damage detection in plate-like structure using combined energetic approaches

Samet

Hui

Souf

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this paper, an experimental investigation of damage detection in plate-like structure using energetics approaches is presented. Two energetics approaches are developed to localize the damage in structure at low-, medium-, and high-frequency range. The first one is the inverse simplified energy method, which is used for the identification of the excitation source and the detection of damage in medium and high frequencies. The second one is the curvature method, which is used for the damage detection in the low and medium frequencies. The main novelty of this paper is to combine these energetics approaches in order to localize the damage in all frequency bands. Experimental examples with different characteristics of plate were performed for the validation purpose. Results show that the presented methods can detect precisely the defects location in plate-like structures.

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Guided wave-based detection of delamination and matrix cracking in composite laminates

Cited by 16 publications

References 26 publications

Fatigue evolution prediction for fiber‐reinforced plastics based on frequency‐wavenumber wavefield of guided wave using deep‐learning model

Fatigue evolution prediction for fiber‐reinforced plastics based on frequency‐wavenumber wavefield of guided wave using deep‐learning model

The Continuous Monitoring of the Health of Composite Structure

Experimental investigation of damage detection in plate-like structure using combined energetic approaches

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