Using Laser Point Scanning Thermography for Quality Monitoring of Products Made of Composite Materials
| Autor: | Aleksandr G. Divin, Sergey V. Karpov, Yuriy A. Zakharov, Nataliya A. Karpova, Aleksandr A. Samodurov, Dmitriy Yu. Golovin, Aleksandr I. Tyurin |
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| Jazyk: | English<br />Russian |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Инженерные технологии и системы, Vol 34, Iss 1, Pp 145-163 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2658-4123 2658-6525 |
| DOI: | 10.15507/2658-4123.034.202401.145-163 |
| Popis: | Introduction. Control of the presence of subsurface defects in products from composite materials is necessary for verification of products after release from production and in the process of operation. Aim of the Study. The purpose of the presented work is to estimate the parameters of subsurface defects using local laser thermography, suitable for quality control of both small objects and suspicious areas of large objects with curved surfaces. Materials and Methods. The laboratory setup on which this work was carried out includes a robotic arm, a COX CG640 thermal imager and a 3 W laser. The method was tested on a fiberglass sample with introduced delamination defect simulations located at different depths below the surface. By means of computer modeling rational parameters of thermographic control were selected, providing reliable detection of the defect at a depth of up to 3 mm under the surface of the composite sample. Results. Numerical modeling of surface temperature field induced by moving focused laser beam was carried out using COMSOL software package. It showed that laser beam with 3 W power moving at 5 mm/s provided the thermal contrast sufficient to detect the defects at the depth up to 3 mm. The obtained experimental data are in satisfactory agreement with numerical modeling both qualitatively and quantitatively. Experimental data were used to construct a regression model for determining defect depth based on the maximal thermal contrast and the time interval between heating and the contrast maximum. Discussion and Conclusion. The results obtained in this work allow us to propose a technique for detecting defects in fiberglass plastics and estimating their depth. The coefficient of determination for the obtained regression model was found to be equal to 0.95, and the mean square error of the metric was no more than 0.016 mm2. The use of a robotic arm to scan objects will make it possible to investigate objects with complex curved surfaces. |
| Databáze: | Directory of Open Access Journals |
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