Comparison of different non-destructive testing techniques for bonding quality evaluation

Yılmaz, Bengisu; Ba, Abdoulaye; Jasiūnienė, Elena; Bui, Huu Kien; Berthiau, Gérard

doi:10.1109/metroaerospace.2019.8869692

Cited by 9 publications

(13 citation statements)

References 28 publications

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“…The single-lap joints with different bonding qualities have been investigated with induction (eddy current stimulated active) thermography. As described in an earlier study [ 3 ], the induction coil frequency plays a significant role in the experiment performance. Hence the design of the coil is selected as a helical coil inductor (inner diameter 15 mm, outer diameter 25 mm, height 30 mm, five turns, manufactured at IREENA institute, Saint-Nazaire, France) to achieve 105 kHz frequency.…”

Section: Methodsmentioning

confidence: 99%

“…The induction thermography data have been evaluated with singular value decomposition-based principal component analysis (PCA). As described in the previous work [ 3 ], PCA allows to eliminate the nonuniform heating patterns and increase the defect contrast in thermography results. Since PCA calculates the eigenvectors within data and sorts them in ascending order; the first few principal components carry the most information [ 30 ].…”

Section: Methodsmentioning

confidence: 99%

“…To maximize defect detection, each recorded defected sample thermography data and perfect bonding sample thermography data was differentiated after alignment according to the bondline. As described in the previous study, the recorded surface temperature data was separated for heating part and cooling part with the novel separation algorithm, which depends on the constant rate of change (derivative) of the sample temperature to be reached ( Figure 5 a) [ 3 ].…”

Section: Methodsmentioning

confidence: 99%

“…In order to expand the application of adhesive joints, the geometry, size and position of these inclusions have to be identified via nondestructive testing (NDT) techniques [ 1 ]. In our recent studies, interface defects in adhesive-bonded structures are inspected with ultrasonic and thermography nondestructive testing techniques [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…The nondestructive evaluation of bonding quality is a challenging task because adhesive bonding is an interfacial phenomenon involving a thin layer of material, usually less than 10 microns [ 35 ]. Although adhesive bonding evaluations with different nondestructive testing techniques have been performed over the past decades, the challenges continue to rise to establish the ultimate reliable NDT technique [ 3 ]. Each NDT technique is limited to deliver a reliable evaluation of bonding quality due to its methodological and physical capabilities.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Bonding Quality with Advanced Nondestructive Testing (NDT) and Data Fusion

Yılmaz

Jasiūnienė

et al. 2020

Sensors

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This work aims to compare quantitatively different nondestructive testing (NDT) techniques and data fusion features for the evaluation of adhesive bonding quality. Adhesively bonded composite-epoxy single-lap joints have been investigated with advanced ultrasonic nondestructive testing and induction thermography. Bonded structures with artificial debonding defects in three different case studies have been investigated: debonding with release film inclusion, debonding with brass film-large, debonding with brass film-small. After completing preprocessing of the data for data fusion, the feature matrices, depending on the interface reflection peak-to-peak amplitude and the principal component analysis, have been extracted from ultrasonic and thermography inspection results, respectively. The obtained feature matrices have been used as the source in basic (average, difference, weighted average, Hadamard product) and statistical (Dempster–Shafer rule of combination) data fusion algorithms. The defect detection performances of advanced nondestructive testing techniques, in addition to data fusion algorithms have been evaluated quantitatively by receiver operating characteristics. In conclusion, it is shown that data fusion can increase the detectability of artificial debonding in single-lap joints.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of Bonding Quality with Advanced Nondestructive Testing (NDT) and Data Fusion

Yılmaz

Jasiūnienė

et al. 2020

Sensors

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Full-view in vivo skin and blood vessels profile segmentation in photoacoustic imaging based on deep learning

Nguyen

et al. 2022

Photoacoustics

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Photoacoustic (PA) microscopy allows imaging of the soft biological tissue based on optical absorption contrast and spatial ultrasound resolution. One of the major applications of PA imaging is its characterization of microvasculature. However, the strong PA signal from skin layer overshadowed the subcutaneous blood vessels leading to indirectly reconstruct the PA images in human study. Addressing the present situation, we examined a deep learning (DL) automatic algorithm to achieve high-resolution and high-contrast segmentation for widening PA imaging applications. In this research, we propose a DL model based on modified U-Net for extracting the relationship features between amplitudes of the generated PA signal from skin and underlying vessels. This study illustrates the broader potential of hybrid complex network as an automatic segmentation tool for the in vivo PA imaging. With DL-infused solution, our result outperforms the previous studies with achieved real-time semantic segmentation on large-size high-resolution PA images.

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Estimation of the size and location of an artificial weld seam defect based on the actual ultrasonic welding phenomenon for online inspection

et al. 2023

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A series of research has been conducted to analyze the quality of weld seams by non-destructive testing methods. Research on defect analysis using the actual ultrasonic welding phenomenon has not been addressed yet. To ensure a comprehensive quality evaluation, this research estimates the size and location of artificial weld seam defects by the actual ultrasonic welding phenomenon without conventional inspection systems. The welding parameters (power, pressure force, and speed) were carefully selected to ensure optimal bond strength. A superimposed type of seam was produced longitudinally by PVC-coated hybrid textiles in rough to smooth surface contact for two welding groups, using a welding width of 10 mm with an activated cooling air effect. Artificial defects were introduced across the weld seam at five different locations spaced 50 mm apart using Teflon films of 3 and 5 mm width. The actual weld phenomenon of ultrasonic welding process parameters was determined after the recorded machine parameters were converted. The effect of welding process parameters on the seam quality was also analyzed, comparing the weld seam quality between different welding groups and Teflon widths. Based on the discovered graph of the actual welding phenomenon, the location and extent of artificial weld seam defects were estimated. The artificial weld seam defect with a thickness of 0.059 mm at a width of 3.85 mm was estimated at an interval of 50.77 mm using 275 N welding pressure force and 120 W welding power at 2 m/min welding speed for 3 mm Teflon width. The results showed that the estimated values closely align with the actual size and position of defects. Overall, this research contributes to the development of a non-destructive testing approach for detecting weld seam defects in ultrasonic welding, emphasizing the importance of these techniques for online inspection and control of weld seam quality.

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Comparison of different non-destructive testing techniques for bonding quality evaluation

Cited by 9 publications

References 28 publications

Evaluation of Bonding Quality with Advanced Nondestructive Testing (NDT) and Data Fusion

Evaluation of Bonding Quality with Advanced Nondestructive Testing (NDT) and Data Fusion

Full-view in vivo skin and blood vessels profile segmentation in photoacoustic imaging based on deep learning

Estimation of the size and location of an artificial weld seam defect based on the actual ultrasonic welding phenomenon for online inspection

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