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Enhancement of Damage Detectability in Aircraft Structures Using the Fusion of NDT Results

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Following the damage tolerance philosophy in aircraft design and operation, one of the most significant stages of maintenance is non-destructive testing of structures. It is, therefore, essential to use testing methods sensitive to particular damage types occurring in aircraft structures during operation. In this paper, the authors present a study on selection and comparison of methods of information fusion applied to testing the results of inspection of composite structures used in aircraft elements, obtained using various ultrasonic methods. The presented approach of fusion of ultrasonic scans allows for enhancement of damage detection and identification due to the presence of different parts of information about detected damage obtained from different initial information sources in a single resulting set. Such an approach can be helpful at the decision-making stage during inspection of aircraft elements and structures. Besides the methodology, the GUI-based software for performing fusion of various types of ultrasonic data is presented.
Rocznik
Tom
Strony
55--74
Opis fizyczny
Bibliogr. 14 poz., rys., tab., wzory
Twórcy
autor
  • Institute of Fundamentals of Machinery Design, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland
autor
  • Institute of Fundamentals of Machinery Design, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland
autor
  • Air Force Institute of Technology, Ks. Bolesława 6, 01-494 Warsaw, Poland
Bibliografia
  • [1] Goshtasby A.A., Nokolov S., Image fusion: Advances in the state of the art, Information Fusion, 8(2), 114–118, 2007.
  • [2] Piella G., A general framework for multiresolution image fusion: from pixels to regions, Information Fusion, 4(4), 259–280, 2003.
  • [3] Li S., Kang X., Fang L., Hu J., Yin H., Pixel-level image fusion: A survey of the state of the art, Information Fusion, 33, 100–112, 2017.
  • [4] Nirmala D.E., Vaidehi V., Comparison of Pixel-level and feature level image Fusion methods, Proc. of the 2nd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, 743–748, 2015.
  • [5] Burt P., Adelson E., The Laplacian Pyramid as a compact image code, IEEE Transactions on Communications, 31(4), 532–540, 1983.
  • [6] Zapłotny M., Damage identification in aircraft composite structures using information fusion methods, Master Thesis, Silesian University of Technology, Faculty of Mechanical Engineering, Gliwice, 2017.
  • [7] Katunin A., Kostka P., Characterisation of impact damage of composite structures using wavelet-based fusion of ultrasonic and optical images, Advanced Composites Letters 23(5), 123-130, 2014.
  • [8] Yang B., Li S., Multifocus image fusion and restoration with sparse representation, IEEE Transactions on Instrumentation and Measurement, 59(4), 884-892, 2010.
  • [9] Al-Wassai F.A., Kalyankar N.V., Al-Zuky A.A., The IHS transformations based image fusion, arXiv:1107.4396, 2011.
  • [10] LLC Black Ice Software. HSI color space – color space conversion. www.blackice.com, accessed at 11.07.2017.
  • [11] Choi M., A new Intensity-Hue-Saturation fusion approach to image fusion with a tradeoff parameter, IEEE Transactions on Geoscience and Remote Sensing, 44(6), 1672–1682, 2006.
  • [12] Amolins K., Zhang Y., Dare P., Wavelet based image fusion techniques – An introduction, review and comparison, ISPRS Journal of Photogrammetry and Remote Sensing, 62(4), 249–263, 2007.
  • [13] Piella G., New quality measure for image fusion. Proc. of the 7th International Conference on Information Fusion, Stockholm, 2004.
  • [14] Wang Z., Borovick A.C., A universal image quality index, IEEE Signal Processing Letters, 9, 81-84, 2002.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e0b0e9c1-bfb4-4816-a15e-11c4fb18564f
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