Browsing by Author "Torbali, M. Ebubekir"

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    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, Xavier
    Low 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.
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    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, Marc
    The 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.