| Title |
Non-destructive evaluation of the quality of adhesive joints using ultrasound, X-ray, and feature-based data fusion / |
| Authors |
Jasiūnienė, Elena ; Yilmaz, Bengisu ; Smagulova, Damira ; Bhat, Gawher Ahmad ; Cicėnas, Vaidotas ; Žukauskas, Egidijus ; Mažeika, Liudas |
| DOI |
10.3390/app122412930 |
| Full Text |
|
| Is Part of |
Applied sciences.. Basel : MDPI. 2022, vol. 12, iss. 24, art. no. 12930, p. 1-20.. ISSN 2076-3417 |
| Keywords [eng] |
data fusion ; ultrasonics ; radiography ; adhesive joints ; adhesive bond ; non-destructive evaluation ; interface defects ; multiple reflections ; signal modeling |
| Abstract [eng] |
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future. |
| Published |
Basel : MDPI |
| Type |
Journal article |
| Language |
English |
| Publication date |
2022 |
| CC license |
|
