Computer aided method for quality control of automotive Al-Si-Cu cast components

• Autorzy: Dobrzański L. A. , Krupiński M. , Maniara R. , Sokolowski J. H.
• Języki publikacji: EN

Abstrakty

EN

Purpose: The technological progress in material engineering causes the continuous need to develop product testing methods providing comprehensive quality evaluation. In material engineering it is the images obtained by various methods that have become the source of information about materials. Design/methodology/approach: The presented methodology, making it possible to determine the types and classes of defects developed during casting the elements from aluminium alloys, making use photos obtained with the flaw detection method with the X-ray radiation. The tests indicate to the applicability of neural networks for this task. It is very important to prepare the neural network data in the appropriate way, including their standardization, carrying out the proper image analysis and correct selection and calculation of the geometrical coefficients of flaws in the X-ray images. Findings: In classical computer algorithms even a slight rotation or change in lighting can binder the proper interpretation and alternation of variable input data. To eliminate this hindrance the programming can be converted by specifying such features of the structure element that remain most significant and effect the similarities of the analysed images. In neural networks this particular feature needs not to be specified - if necessary, the neural network spots it automatically. Practical implications: The computer aided methodology of the quality control of the light Al and Mg based alloys may be used by manufacturers of subassemblies and elements of car engines. Originality/value: The value of the applied methodology was to correct identify the casting effects that occurred during the casting process.

Słowa kluczowe

EN

technological process; Al-Si-Cu; image analysis; neural networks; cast defects; quality

PL

proces technologiczny; Al-Si-Cu; analiza obrazu; sieci neuronowe; wady odlewów; jakość

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2007
• Tom: Vol. 24, nr 2
• Strony: 151--154
• Opis fizyczny: Bibliogr. 21 poz., fot., rys., tab.

Twórcy

autor

Dobrzański L. A.

autor

Krupiński M.

autor

Maniara R.

autor

Sokolowski J. H.

• 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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