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The application of image processing techniques in the tool wear estimation / Anna Zawada-Tomkiewicz, Borys Storch.

Autor:

ZAWADA-TOMKIEWICZ, Anna. Politechnika Koszalińska - Wydział Mechaniczny, Zakład Zarządzania i Marketingu w Budowie i Eksploatacji Maszyn, 1996 -

Współtwórca(-y):

STORCH, Borys. Politechnika Koszalińska - Wydział Mechaniczny, Zakład Zarządzania i Marketingu w Budowie i Eksploatacji Maszyn, 1996 -

Rodzaj materiału:

ArtykułJęzyk: angielski Praca zawiera:

International Conference on Computational Methods in Contact Mechanics (6 ; 2003 ; Crete, Grecja). Contact Mechanics 2003

Rodzaj/forma:

Materiały konferencyjne.

W: Computational methods in contact mechanics VI / ed. C.A. Brebbia. - s. 201-210Streszczenie: The assumptions for a monitoring system of a tool flank wear the basis of a machined surface digital image acquired from a computer vision system are presented. Yhe method of a VB parameter estimation is based on a texture analysis of a digital image of a machined surface. This method is an indirect mrthod. One directional three-layer artificial neural network with an optimized number of neurons in each layer and time of training acts as an estimator. The settlement of the estimator parameters is nased on error minimization between the reference values and the output values from an estimator. Input values for an estimator are the mathematical indexes of a machined surface digital image. The method presented solves the problem of applying a machined surface image for tool flank wear monitoring during cutting.

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Wstecz								Dalej
Wstecz	Classifying the wear of turning tools with neural networks /	Classifying the wear of turning tools with neural networks /	Estimation of perception of visional press advertisement and schema in frames of practices with ergonomics /	The application of image processing techniques in the tool wear estimation /	Machine vision - a novel quality in monitoring systems /	Estimation of surface roughness parameters on a base of machined surface image /	Machined surface generated in sliding using a modified cutting edge /	Dalej

Dane z autopsji.

The assumptions for a monitoring system of a tool flank wear the basis of a machined surface digital image acquired from a computer vision system are presented. Yhe method of a VB parameter estimation is based on a texture analysis of a digital image of a machined surface. This method is an indirect mrthod. One directional three-layer artificial neural network with an optimized number of neurons in each layer and time of training acts as an estimator. The settlement of the estimator parameters is nased on error minimization between the reference values and the output values from an estimator. Input values for an estimator are the mathematical indexes of a machined surface digital image. The method presented solves the problem of applying a machined surface image for tool flank wear monitoring during cutting.