Automated Quality Characterization for Composites Using Hybrid Ultrasonic Imaging Techniques
| Autor: | Tat-Hean Gan, Alvin Yung Boon Chong, Guojin Feng, Jamil Kanfoud, Jiangtao Sun, Siamak Tavakoli, Cem Selcuk |
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| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
Materials science Mechanical Engineering Delamination Composite number Ultrasonic testing Carbon-fibre-reinforced polymer Image processing Fibre-reinforced plastic Condensed Matter Physics 01 natural sciences Thresholding Glass-fibre-reinforced polymer Mechanics of Materials 0103 physical sciences General Materials Science Ultrasonic sensor Segmentation Composite material 010301 acoustics |
| Zdroj: | Research in Nondestructive Evaluation. 30:205-230 |
| ISSN: | 1432-2110 0934-9847 |
| DOI: | 10.1080/09349847.2018.1459989 |
| Popis: | An enhanced technique using image processing has been developed for automated ultrasonic inspection of composite materials, such as glass/carbon-fibre-reinforced polymer (GFRP or CFRP), to ascertain their structural healthiness. The proposed technique is capable of identifying the abnormality features buried in the composite by image filtering and segmentation applied to ultrasonic C-Scan images. This work presents results performed on two composite samples with simulated delamination defects. A local gating scheme is applied to raw A-Scan data for improved contrast between defective and healthy regions in the produced C-Scan image. In this test campaign, different filtering and thresholding algorithms are evaluated and compared in terms of their effectiveness on defect identification. The accuracies of less than 3 mm and 1.11 mm were attained for the defect size and depth, respectively. The results demonstrates the applicability of the proposed technique for accurate defect localization and chara... |
| Databáze: | OpenAIRE |
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