Browsing by Author "Maldague, Xavier"
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Item Open Access Fusion insights from ultrasonic and thermographic inspections for impact damage analysis(AIAA, 2023-06-08) Torbali, M. Ebubekir; Alhammad, Muflih; Zolotas, Argyrios; Avdelidis, Nicolas Peter; Ibarra-Castanedo, Clemente; Maldague, XavierLow energy impact damage in composite materials may be more concerning than it appears visually, often requiring a detailed examination for accurate assessment to ensure safe and sustainable operation. Non-destructive testing (NDT) methods provide such inspection techniques, and in this paper, NDT-based fusion is explored for enhanced identification of defect size and location compared to indepdently using individual NDT methods separately. Three Carbon Fiber Reinforced Polymer (CFRP) specimens are examined, each with an impact damage of a given energy level, using pulsed thermography (PT) and phased array (PA) ultrasonic methods. Following the extraction of binary defect shapes from source images, a decision-level fusion approach is performed. The results indicate that combining ultrasonic and infrared thermography (IRT) inspections for CFRP composite materials is promising to achieve enhanced and improved detection traceability.Item Open Access Multi-label classification algorithms for composite materials under infrared thermography testing(Taylor and Francis, 2022-10-14) Alhammad, Muflih; Avdelidis, Nicolas Peter; Ibarra Castanedo, Clemente; Maldague, Xavier; Zolotas, Argyrios; Torbali, M. Ebubekir; Genestc, MarcThe key idea in this paper is to propose multi-labels classification algorithms to handle benchmark thermal datasets that are practically associated with different data characteristics and have only one health condition (damaged composite materials). A suggested alternative approach for extracting the statistical contents from the thermal images, is also employed. This approach offers comparable advantages for classifying multi-labelled datasets over more complex methods. Overall scored accuracy of different methods utilised in this approach showed that Random Forest algorithm has a clear higher performance over the others. This investigation is very unique as there has been no similar work published so far. Finally, the results demonstrated in this work provide a new perspective on the inspection of composite materials using Infrared Pulsed Thermography.Item Open Access Non-destructive imaging of marqueteries based on a new infrared-terahertz fusion technique(Elsevier, 2022-06-29) Hu, Jue; Zhang, Hai; Sfarra, Stefano; Gargiulo, Gianfranco; Avdelidis, Nicolas Peter; Zhang, Mingli; Yang, Dazhi; Maldague, XavierDetection of subsurface defects has hitherto been regarded as an important element in the course of preserving cultural heritage. To do so, non-destructive imaging approaches for viewing and determining the location of splitting inside the sample under test are required, which constitute the subject of the present study. Both active thermography and terahertz imaging have demonstrated their potential in providing non-destructive inspection on cultural heritage objects. Conventionally, active thermography has been used to retrieve details on the defects as well as morphological data from the surface and subsurface, whereas pulsed terahertz imaging has been applied to record the internal material distribution. Here, the feature extraction, selection and fusion framework is extended to design a fusion process to merge the information obtained by both active thermography and terahertz imaging; in this way, the technique naturally inherits the strengths of both aforementioned imaging technologies. The fusion technique is able to produce images with high-contrast defect information located at different depths. To demonstrate the efficacy of the suggested technique, an experiment has been conducted on an ancient marquetry.Item Open Access Non-invasive inspection for a hand-bound book of the 19th century: numerical simulations and experimental analysis of infrared, terahertz, and ultrasonic methods(Elsevier, 2024-05-24) Jiang, Guimin; Zhu, Pengfei; Gai, Yonggang; Jiang, Tingyi; Yang, Dazhi; Sfarra, Stefano; Waschkies, Thomas; Osman, Ahmad; Fernandes, Henrique; Avdelidis, Nicolas P.; Maldague, Xavier; Zhang, HaiDue to fungal growth and mishandling in the book, there are various types of defects as they age such as foxing, tears, and creases. It is important to develop novel non-invasive inspection techniques and defect recognition algorithms. In this work, three non-invasive inspection techniques, including infrared thermography (IRT), terahertz time-domain spectroscopy (THz-TDS), and air-coupled ultrasound (ACU), were employed for the detection of defects in an ancient book cover. To improve the image quality and defect contrast, principal component analysis, fast Fourier transform, and partial least squares regression algorithms are used as the post-processing methods. Furthermore, the YOLOv7 network is deployed for defect automatic detection. Finite element analysis and finite-difference time-domain methods were employed for generating training dataset of YOLOv7 network. Experimental results demonstrate that IRT and THz-TDS has excellent detection capability for surface and subsurface defects, respectively. By employing YOLOv7 network with simulation datasets, defects can be effectively identified.