778 KB0 KB200620252014Babič, MatejBalič, JožeBelič, IgorKokol, PeterKovačič, MihaPanjan, Peterštevilka:3letnik:81str. 143-147ISSN:2232-3236COBISSID_HOST:78906369URN:URN:NBN:SI:doc-A1H7Y8S6enElektrotehniška zveza SlovenijeElektrotehniški vestnikcomplex geometry structureengineeringgenetic programminggensko programiranjekompleksna geometrijaUsing of genetic programming in engineering|Intelligent systems are process coupled with robotics in industrial usually settings, though they may be used as diagnostic systems connected only to passive sensors. In this paper we use a new method which combines an intelligent genetic algorithm and multiple regression to predict the hardness of hardened specimens. The hardness of a material is an important mechanical property affecting mechanical properties of materials. The Microstructures of the hardened specimens are very complex and cannot be described them with the classical Euclidian geometry. Thus, we use a new method, i.e. fractal geometry. By using the method intelligent-system, genetic programming and multiple regression, improved production the process laser-hardening increases because of the decreased time of the process and, the improved increased topographical property of the used materials. The genetic-programming modelling results show a good agreement with teh measured hardness of the hardened specimensInteligentni sistemi naj bi se po navadi povezali skupaj z robotiko v nastavitvah industrijskih procesov, čeprav so lahko sistemi za diagnostiko povezani samo za pasivne senzorje. V tem članku bomo uporabili metodo, ki združuje inteligentne genetske algoritme in multiplo regresijo za napoved trdote kaljenih vzorcev. Trdota materiala je pomembna mehanska lastnost, ki vpliva na mehanske lastnosti materialov. Mikrostrukture kaljenih vzorcev so zelo kompleksne in jih ne moremo opisati s klasično evklidsko geometrijo. Zato smo uporabili novo metodo, fraktalno geometrijo. Z metodo inteligentnega sistema, genetskim programiranjem in multiplo regresijo smo povečali proizvodnjo pri laserskem kaljenju, saj smo skrajšali čas procesa in povečali topografsko lastnost materiala. Rezultati modeliranja genetskega programiranja se dobro ujemajo z izmerjenimi vrednostmi trdote kaljenih vzorcevTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaElektrotehniška zveza Slovenije