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Methodology of classification of internal damage the steels during creep service

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: of this publication is to present the methodology of computer assisted method for analysis of the metallographic images obtained in the scanning electron microscope (SEM) from the elements after long time creep service. Design/methodology/approach: Stages in development of internal damage involving intercrystalline cavitation cracking were discussed and illustrated with micrographs. The method based on analysis of images, shape coefficients and neural networks was proposed as a tool to evaluate the internal damage classes of materials used for the high-pressure installations elements working in creep conditions. Findings: Combining of several methods making use of the image analysis, shape coefficients, and neural networks will make it possible to achieve the better efficiency of class recognition of damages developed in the material. Practical implications: The presented method can be use in industrial practice for evaluation and qualification of creep-damage of power station boiler components operating in creep regime (e.g., steam boilers, chambers, pipelines, and others). Originality/value: Original value of the work is applying the artificial intelligence method for the classification of internal damage in the steel during creep service.
Rocznik
Strony
263--266
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wykr.
Twórcy
  • Institute for Ferrous Metallurgy, ul. K. Miarki 12/14, 44-100 Gliwice, Poland
autor
  • Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland
  • Institute for Ferrous Metallurgy, ul. K. Miarki 12/14, 44-100 Gliwice, Poland
Bibliografia
  • [1] L.A. Dobrzański, J. Dobrzański, J. Madejski, J. Zacłona, The conception of a computer aided decision making system connected with the residual life of the elements of power installations in the conditions of creep, J. Mat. Proc. Tech., Vol. 56, pp. 718-728, 1996
  • [2] J. Dobrzański, Internal damage processes in low alloy chromium-molybdenum steels during high-temperature creep service, J. Mat. Proc. Tech., Vol. 157-158, pp. 197-303, 2004
  • [3] J. Dobrzański, The classification method and the technical condition evaluation of the critical elements’ material of power boilers in creep service made from the 12Cr-1Mo-V, J. Mat. Proc. Tech., Vol. 164-165, pp. 785-794, 2005
  • [4] J. Dobrzański, Material diagnostics in evaluation of the state and extended service time forecast in addition to the computational life of pipelines in creep service, Power Engineering, 12, 2002, pp. 937-943 (in Polish).
  • [5] L.A. Dobrzański, Fundamentals of Materials Science and Physical Metallurgy Engineering Materials with Fundamentals of Materials Design, WNT, Warszawa, 2002 (in Polish).
  • [6] L.A. Dobrzański, M. Krupinski, J.H. Sokolowski, Computer aided classification of flaws occurred during casting of aluminum, J. of Mat. Proc. Techn., Vol. 167, Is. 2-3, 2005, pp. 456-462.
  • [7] L.A. Dobrzański, M. Kowalski, J. Madejski: Methodology of the mechanical properties prediction for the metallurgical products from the engineering steels using the artificial intelligence methods, J. of Mat. Proc. Tech., Vol. 164-165, 2005, pp. 1500–1509.
  • [8] L. A. Dobrzański, W. Sitek, M. Krupiński, J. Dobrzański, Computer aided method for evaluation of failure class of materials working in creep conditions, J. Mat. Proc. Tech., Vol. 157-158, pp. 102-106, 2004.
  • [9] B. Tyler, App. Surf. Sci., Interpretation of TOF-SIMS images: multivariate and univariate approaches to image denoising, image segmentation and compound identification, Vol. 203-204, pp. 825-831, 2003.
  • [10] H. Zheng, L.X. Kong, S. Nahavand, Automatic inspection of metallic surface defects using genetic algorithms, J. Mat. Proc. Tech., Vol. 125-126, pp. 427-433, 2002.
  • [11] L.A. Dobrzański, W. Sitek, Application of neural network in modeling of hardenability of constructional steels, Journal of Materials Processing Technology, 78 (1998) 59-66.
  • [12] L. Miaoquan, Ch. Dunjun, X. Aiming, Li. Long, An adaptive prediction model of grain size for the forging of Ti-6Al-4V alloy based on fuzzy neural networks, Journal of Materials Processing Technology, 123 (2002) 377-381.
  • [13] R. Tadeusiewicz, P. Korohoda, Computer assisted image analysis and processing, Development in telecommunication Press, Cracow 1997 (in Polish).
  • [14] A. Hernas, J. Dobrzański, Life-time and Damage of Boilers and Steam Turbines Elements, Silesian University of Technology, Gliwice, 2003 (in Polish).
  • [15] J. Dobrzański, A. Hernas, Relationship between microstructure and remanent life-time of low alloy Cr–Mo steels, in: Proceedings of the Sixth International Conference on Creep and Fatigue, London, 1996, 451-461.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f10af601-0249-4fe9-86e7-0835948a9723
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