Verifikace prediktoru vstupních parametrů laserového mikroobrábění

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Verification of the predictor of laser micro-machining input parametrs

Popis výsledku v původním jazyce

The laser micro-machining is process which has several input parameters. These input parameters have to be set very carefully in order to obtain desired product. Main product quality characteristics are surface quality and depth of the groove. The examined input parameters of used laser machine were two - power of laser beam and feed. Influences of this two input parameters are contradictory. The higher the power is, the deeper the groove is and higher surface roughness is obtained. Nevertheless, the higher the feed is, the shallower the groove is and the lower surface roughness is. It is difficult to find good combination of these two parameters for desired output product quality. Moreover, dependence between single input parameter and single output characteristic is nonlinear what makes modelling by classical approaches even more complicated. In this paper artificial multilayer feed-forward neural network is used for modelling of behaviour between input and output parameters of laser

Název v anglickém jazyce

Verification of the predictor of laser micro-machining input parametrs

Popis výsledku anglicky

The laser micro-machining is process which has several input parameters. These input parameters have to be set very carefully in order to obtain desired product. Main product quality characteristics are surface quality and depth of the groove. The examined input parameters of used laser machine were two - power of laser beam and feed. Influences of this two input parameters are contradictory. The higher the power is, the deeper the groove is and higher surface roughness is obtained. Nevertheless, the higher the feed is, the shallower the groove is and the lower surface roughness is. It is difficult to find good combination of these two parameters for desired output product quality. Moreover, dependence between single input parameter and single output characteristic is nonlinear what makes modelling by classical approaches even more complicated. In this paper artificial multilayer feed-forward neural network is used for modelling of behaviour between input and output parameters of laser

Druh

D - Stať ve sborníku

CEP obor

JJ - Ostatní materiály

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2007

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

microCAD 2007

ISBN

978-963-661-753-0

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

149-154

Název nakladatele

University of Miskolc

Místo vydání

Miskolc

Místo konání akce

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Datum konání akce

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Typ akce podle státní příslušnosti

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Kód UT WoS článku

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