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

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.

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