Miran Brezočnik (Avtor), Miha Kovačič (Avtor), Mirko Ficko (Avtor)

Povzetek

In this paper we propose genetic programming to predict surface roughness in end-milling. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Spindle speed, feed rate,depth of cut, and vibrations are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by genetic programming. Accuracy of the best model was proved with the testing data. It was established that the surface roughness is most influenced by the feed rate, whereas the vibrations increase the prediction accuracy.

Ključne besede

čelno frezanje;površinska hrapavost;napoved hrapavosti;genetsko programiranje;end milling;surface roughness;prediction of surface roughness;genetic programming;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UM FS - Fakulteta za strojništvo
UDK: 621.914:004.89
COBISS: 9026582 Povezava se bo odprla v novem oknu
ISSN: 0924-0136
Št. ogledov: 1453
Št. prenosov: 109
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarne ključne besede: čelno frezanje;površinska hrapavost;napoved hrapavosti;genetsko programiranje;
URN: URN:SI:UM:
Strani: str. 28-36
Zvezek: ǂVol. ǂ157/158
Čas izdaje: 20. dec. 2004
ID: 8718714