Investigation of multiple cracking in glass/epoxy 2D woven composites by vibrothermography

Bai, Gabriele; Lamboul, B.; Roche, Jean‐Michel; Baste, Stéphane

doi:10.1080/17686733.2015.1079013

Cited by 7 publications

(5 citation statements)

References 30 publications

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“…Vavilov et al stated that friction between defect surfaces or plastic deformation are the main source of defect detection in composites [9]. Bai et al stated that crack frictions and viscoelasticity are main contributions to the heat generation in vibrothermography [69].…”

Section: Principle Of Heat Generation In Vibrothermographymentioning

confidence: 99%

Recent developments in vibrothermography

Gülcan¹

2021

Res. Eng. Struct. Mater.

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Due to the sensitivity of fluorescent penetrant inspection to surface roughness of the inspected material, researchers have been investigating alternative inspection methods. Vibrothermography is one of the contactless nondestructive testing methods in which vibration pulses with high frequencies (typically 20-40 kHz) are used in a part for a short period of time to produce thermal gradient at the defect. In this technique, thermographic or infra-red cameras are used for radiation detection due to thermal gradient in the range of 0.9-14 µm electromagnetic spectrum. This paper focuses on the recent developments in vibrothermography. It covers basics, history, equipments used, types, materials, probability of detection, principle of heat generation mechanism and factors that affect detectability in vibrothermography.

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Section: Principle Of Heat Generation In Vibrothermographymentioning

confidence: 99%

Recent developments in vibrothermography

Gülcan¹

2021

Res. Eng. Struct. Mater.

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“…Since then, the range of application of UET has spread out over different types of materials such as polymers, fiber reinforced polymers, metals, ceramics, or timber. Regarding polymers and carbon fiber reinforced plastic laminates, UT has been used to detect cracks and impact damage [1][2][3][4][5][7][8][9][10][11], delaminations, disbonds [12], and heat damage [13], as well as to assess the overall damage in composites [14] (fibers ruptures and intra/inter yarn decohesion in glass/epoxy woven composites [15]) after mechanical loading. Other fields of application are the detection of corrosion [16] and cracks [6,[17][18][19][20] in metallic plates and timber [21], the identification of microcracks in plasma sprayed coatings [22] (being the only non-destructive technique capable of identifying such flaws), or the assessment of defective adhesion in bondlines [13].…”

Section: Ultrasound Excited Thermography: An Efficient Tool For the C...mentioning

confidence: 99%

“…The method involves calculation of first order temporal and second order spatial partial derivatives of the image sequence, which amplifies noise, and thus requires the use of low-pass spatial and/or temporal filtering to avoid the ill-posedness of the calculation of numerical derivatives. In this work, the authors also apply the processing described by equation (15) to the case of 3D heat propagation, when heat sources are buried a certain distance below the sample surface. The resulting 'heat source estimate' provides better spatial and temporal resolution than the raw image sequence but the resulting processed images do not correspond to a physical intensity, neither are they quantitative, as a 2D model is applied to heat sources that are actually buried below the surface.…”

Section: Inverse Problemmentioning

confidence: 99%

Ultrasound excited thermography: an efficient tool for the characterization of vertical cracks

Mendioroz

Celorrio

Salazar

2017

Meas. Sci. Technol.

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Ultrasound excited thermography has gained a renewed interest in the last two decades as a nondestructive testing technique aimed at detecting and characterizing surface breaking and shallow subsurface discontinuities. It is based on measurement of the IR radiation emitted by the specimen surface to detect temperature rises produced by the heating of defects under high amplitude ultrasound excitation and is primarily addressed to flaws with contacting faces, such as kissing cracks or tight delaminations. The simplicity of application and the ability to detect small cracks in challenging media makes it an attractive emerging technology, which is still in a development stage. However, it has proven to provide an opportunity for the quantitative characterization of defects, mainly of vertical cracks. In this review, we present the principles of the technique and the different experimental implementations, we put it in context with other nondestructive tests and we summarize the work done in order to improve defect detectability and test reliability, with the final goal of determining the probability of detection. Then we review the contributions aimed at characterizing vertical cracks, i.e. retrieving the geometry and location of the crack from surface temperature data, generated by ultrasonic excitation.

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“…Banaszczyka et al [ 5 ] showed that using infrared imaging, the contact resistance of the fabric can be measured. Bai et al [ 6 ] showed that vibrothermography can be used study the multiple micro cracks in the woven fabric. The goal is to find the sensitivity of the vibrothermography effect to crack density.…”

Section: Introductionmentioning

confidence: 99%

Automated Optical Inspection for Defect Identification and Classification in Actual Woven Fabric Production Lines

Kuo

Wang

Barman

2022

Sensors

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This paper presents a turnkey integrated system that can be operated in real time for real textile manufacturers. Eight types of defects in woven fabric, including stain, broken end, broken weft, hole, nep, double pick, kinky weft and float can be recognized and classified. First, an image is captured by a CMOS industrial camera with a pixel size of 4600 × 600 above the batcher at 20 m/min. After that, the four-stage image processing procedure is applied to detect defects and for classification. Stage 1 is image pre-processing; the filtration of the image noise is carried out by a Gaussian filter. The light source is corrected to reduce the uneven brightness resulting from halo formation. The improved mask dodging algorithm is used to reduce the standard deviation of the corrected original image. Afterwards, the background texture is filtered by an averaging filter, and the mean value is corrected for histogram shifting, so that this system is robust to the texture and color changes of woven fabric. The binary segmentation threshold is determined using the mean value and standard deviation of an image with a normal sample. Stage 2 uses adaptive binarization for separation of the background and defects and to filter the noise. In Stage 3, the morphological processing is used before the defect contour is circled, i.e., four features of each block, including the defect area, the aspect ratio of the defect, the average gray level of the defect and the defect orientation, which are calculated according to the range of contour. The image defect recognition dataset consists of 2246 images. The results show that the detection success rate is 96.44%, and the false alarm rate is 3.21%. In Stage 4, the defect classification is implemented. The support vector machine (SVM) is used for classification, 230 defect images are used as training samples, and 206 are used as test samples. The experimental results show that the overall defect recognition rate is 96.60%, providing that the software and hardware equipment designed in this study can implement defect detection and classification for woven fabric effectively.

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Investigation of multiple cracking in glass/epoxy 2D woven composites by vibrothermography

Cited by 7 publications

References 30 publications

Recent developments in vibrothermography

Recent developments in vibrothermography

Ultrasound excited thermography: an efficient tool for the characterization of vertical cracks

Automated Optical Inspection for Defect Identification and Classification in Actual Woven Fabric Production Lines

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