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- Haluzíková, B., et al.
(författare)
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Identification of Surface Quality of Plastic Electrodes after Blasting
- 2013
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Ingår i: Diffusion in Solids and Liquids VIII. - : Trans Tech Publications. ; , s. 71-76
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Konferensbidrag (refereegranskat)abstract
- Nowadays, plastics have become one of the most demanded materials, replacing the traditional ones such as metals. Therefore, many companies are concerned with the production of plastics, with their distribution and innovation development. Plastics have found utility in a wide range of applications, we use them every day. Measurement of surface roughness of plastic moldings produced by the injection molding process was carried out by a contact profilometer Mitutoyo Surftest SJ401. A reason for this measurement is to obtain information about surface roughness. For further technical adjustment is required to have higher surface roughness what helps to increase electrical conductivity of plastic moldings. This involves determination of a ratio between Ra/Rz (the ratio between the arithmetic average of the roughness profile Ra and the average maximum height of the profile Rz) in order to satisfy customer demand for achieving better surface characteristics leading to an increase in electrical conductivity.
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| 3. |
- Lipinski, D., et al.
(författare)
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Application of the hamming network to the classification of surfaces after abrasive machining
- 2018
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Ingår i: Journal of Machine Engineering. - : Editorial Institution of Wrocaw Board of Scientific. - 1895-7595 .- 2391-8071. ; 18:4, s. 114-126
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Tidskriftsartikel (refereegranskat)abstract
- 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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