Deformed lattice analysing using neural networks

Author

Leopold, Jürgen ; Günther, Holger

Author_Institution

Gessellschaft fur Fertigungtech. und Entwicklung e.V., Tech. Univ. Chemnitz, Germany

Volume

5

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

3094

Abstract

The image analysis of deformed grids may help for development and investigation of pairs of workpiece and cutting material, optimised technological conditions and new tool material which may allow cutting without coolants and lubricants or with less use of coolants and lubricants. However, for a comprehensive and economical industrial use of these methods it is necessary to automate the recognition of grid points and the analysis of deformations. For the processing of given points there exist some programs and software systems like the system VISIO, developed by the Society for Production Engineering and Development (GFE) Chemnitz, but the analysis of large or extremely deformed grid structures continues to be only practicable manually (using microscopes,digitizers etc.). The paper proposes a solution for recognising points in large deformed and damaged lattices using digital image processing in combination with neural networks

Keywords

cutting; image processing; learning (artificial intelligence); metalworking; neural nets; plastic deformation; quality control; cutting material; deformed lattice analysis; digital image processing; grid points recognition; neural networks; workpiece; Coolants; Image analysis; Image recognition; Industrial economics; Lattices; Lubricants; Microscopy; Neural networks; Production engineering; Software systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374727

Filename

374727