Application of neural networks to classification of internal damages in steels working in creep service

• Autorzy: Dobrzański L. A. , Sroka M. , Dobrzański J.
• Konferencja: 12th International Scientific Conference CAM3S'2006, 27-30th November 2006, Gliwice-Zakopane
• Języki publikacji: EN

Abstrakty

EN

Purpose: The goal of the paper is the presentation of computer assisted method for analysis of the metallographic images obtained in the scanning electron microscope (SEM) from the low alloyed steel 13CrMo4-5 elements in different states of internal damages after long time creep service. Design/methodology/approach: Investigations of the structure and morphology of internal damages resulting from creep were made by the use of light microscope and scanning electron microscope. Their topography were observed by the use of confocal laser scanning microscope. There was proposed a method based on analysis of images, shape coefficients and neural networks as a tool to evaluate the internal damage classes of materials used for the high-pressure installations elements working in creep conditions. Findings: The better efficiency of class recognition of damages developed in the material can be achieved as a combining of several methods making use of the image analysis, shape coefficients, and neural networks. 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: Applying of the artificial intelligence method for the classification of internal damage in the steel during creep service.

Słowa kluczowe

EN

images analysis; neural networks; steels

PL

analiza obrazów; sieci neuronowe; stale

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2007
• Tom: Vol. 20, nr 1-2
• Strony: 303--306
• Opis fizyczny: Bibliogr. 18 poz., fot., tab.

Twórcy

autor

Dobrzański L. A.

autor

Sroka M.

autor

Dobrzański J.

• Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18 a, 44-100 Gliwice, Poland,

Bibliografia

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• [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) 937- 943 (in Polish).
• [5] J. Dobrzański, M. Sroka, A. Zieliński, Methodology of classification of internal damage the steels during creep service, Journal of Achievements in Matrials and Manufacturing Engineering, 18 (2006) 263-266.
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• [16] 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.
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