Technological information extraction of free form surfaces using neural networks
Korošec, Marjan (Author)

URLURL - Presentation file, Visit http://dx.doi.org/10.1007/s00521-006-0071-9 This link opens in a new window

The aim of this paper is to show how to predict the accurate machining technology for the particular free form NURBS or B-spline surface. Since that kind of a surface is very hard to describe in an analytical manner, the topological and geometrical information about the surface was acquired with the help of self-organized neural networks (NNs) and first- or second-order statistic parameters. It is proved that the most significant parameter in thisprocess is the curvature, especially when rapid changes of curvature on a free form surface occurred. As the Gaussian distribution of surface curvaturesand slope gradient data were presumed, the mean and variance was used for one-dimensional data presentation, and the Hebbian output data vectorwas used to assess probability, density function and distribution of thepresented data. For collecting the maximum amount of surface information, the principal component analysis method inside the Hebbian NN was used.

Keywords:nevronalne mreže, obdelovalne tehnologije, B-spline površine, Gaussove porazdelitve, anlizne metode, verjetnostne funkcije, analize variance, proste oblike, neural network, self-organized map, probability density function, variance, free form surface, shape distribution function
Work type:Not categorized (r6)
Tipology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Number of pages:str. 453-463
Numbering:Letn. 16, št. 4/5
ISSN on article:0941-0643
COBISS.SI-ID:9749275 Link is opened in a new window
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Record is a part of a journal

Title:Neural computing & applications
Shortened title:Neural comput. appl.
COBISS.SI-ID:1607958 This link opens in a new window

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