Application of the Hamming network to the classification of surfaces after abrasive machining

• Autorzy: Lipinski D. , Tomkowski R. , Kacalak W.

Identyfikatory

DOI

10.5604/01.3001.0012.7722

• Języki publikacji: EN

Abstrakty

EN

The use of artificial neural networks for modelling and inference about surface parameters is a more and more often undertaken research topic. Based on the analysis of the ranges of suitability of surface topography parameters, a variety of different parameters can be observed to identify surfaces with different features and different conditions of use. The issues of surface topography analysis and determination of surface condition after abrasive machining are of fundamental importance. Currently, when assessing the surface intended for interaction with the other surface, it is possible to use many surface evaluation parameters. Assigning the machined surface to the appropriate assessment group, especially in automated quality control systems, requires a preliminary surface classification. In this article Hamming's network was used for the surface classification along with modification of Hamming distance.

Słowa kluczowe

EN

classification; surface topography; abrasive machining; neural network

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2018
• Tom: Vol. 18, No. 4
• Strony: 114--126
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Lipinski D.

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

autor

Tomkowski R.

• KTH Royal Institute of Technology, Industrial Engineering and Management, Department of Prod. Eng., Sweden

autor

Kacalak W.

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

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).