A method of object-oriented symbolical description and evaluation of machine elements using antipatterns

• Autorzy: Kacalak W. , Majewski M. , Tucholka A.
• Języki publikacji: EN

Abstrakty

EN

Authors propose a method of normalizing and analyzing structures, enabling automated cross-comparison of features observed in tested structures against predefined ones (both correct and incorrect reference elements). Application of this method, enables usage of numerical methods and neural networks for rapid classification of elements, while maintaining high level of flexibility, uncertainty and variety of input data. Additionally, a language, enabling symbolic representation of mechanical elements is presented and used in the demonstration of the proposed method applied to mechanical shafts. Authors explore one simple, and two more complex calculation models aimed at automation of the evaluation and rating of mechanical elements, with a purpose of improving the design and quality monitoring processes. Increase in efficiency of these processes results from applying proposed method as a tool for reducing common mistakes, faults, quality assessment time of large amounts of similar elements, or automatic suggesting of possible solutions.

Słowa kluczowe

EN

machine design; automated design system; structural feature language; antipattern

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2016
• Tom: Vol. 16, No. 4
• Strony: 49--69
• Opis fizyczny: Bibliogr. 14 poz., tab., rys.

Twórcy

autor

Kacalak W.

• Koszalin University of Technology, Faculty of Mechanical Engineering, Koszalin, Poland

autor

Majewski M.

• Koszalin University of Technology, Faculty of Mechanical Engineering, Koszalin, Poland

autor

Tucholka A.

• Koszalin University of Technology, Faculty of Mechanical Engineering, Koszalin, Poland

Bibliografia

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• [4] KACALAK W., MAJEWSKI M., TUCHOLKA A., 2015, Intelligent Assessment of Structure Correctness Using Antipatterns, International Conference on Computational Science and Computational Intelligence CSCI2015, Las Vegas, USA. IEEE Xplore Digital Library, 559-564.
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