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INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING

U. Zuperl
Franci Čuš
E. Kiker

Puni tekst: engleski, pdf (3 MB) str. 15-22 preuzimanja: 1.876* citiraj
APA 6th Edition
Zuperl, U., Čuš, F. i Kiker, E. (2006). INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING. Tehnički vjesnik, 13 (1,2), 15-22. Preuzeto s https://hrcak.srce.hr/8842
MLA 8th Edition
Zuperl, U., et al. "INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING." Tehnički vjesnik, vol. 13, br. 1,2, 2006, str. 15-22. https://hrcak.srce.hr/8842. Citirano 17.11.2019.
Chicago 17th Edition
Zuperl, U., Franci Čuš i E. Kiker. "INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING." Tehnički vjesnik 13, br. 1,2 (2006): 15-22. https://hrcak.srce.hr/8842
Harvard
Zuperl, U., Čuš, F., i Kiker, E. (2006). 'INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING', Tehnički vjesnik, 13(1,2), str. 15-22. Preuzeto s: https://hrcak.srce.hr/8842 (Datum pristupa: 17.11.2019.)
Vancouver
Zuperl U, Čuš F, Kiker E. INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING. Tehnički vjesnik [Internet]. 2006 [pristupljeno 17.11.2019.];13(1,2):15-22. Dostupno na: https://hrcak.srce.hr/8842
IEEE
U. Zuperl, F. Čuš i E. Kiker, "INTELLIGENT ADAPTIVE CUTTING FORCE CONTROL IN END-MILLING", Tehnički vjesnik, vol.13, br. 1,2, str. 15-22, 2006. [Online]. Dostupno na: https://hrcak.srce.hr/8842. [Citirano: 17.11.2019.]

Sažetak
In this article, an adaptive neural controller for the ball end-milling process is described. Architecture with two different kinds of neural networks is proposed, and is used for the on-line optimal control of the milling process. A BP neural network is used to identify the milling state and to determine the optimal cutting inputs. The feedrate is selected as the optimised variable, and the milling state is estimated by the measured cutting force. The adaptive controller is operated by a PC and the adjusted feedrates are sent to the CNC. The purpose of this article is to present a reliable, robust neural controller aimed at adaptively adjusting feed-rate to prevent excessive tool wear, tool breakage and maintain a high chip removal
rate. The goal is also to obtain an improvement of the milling process productivity by the use of an automatic regulation of the cutting
force. Numerous simulations are conducted to confirm the efficiency of this architecture. The proposed architecture for on-line determining of optimal cutting conditions is applied to ball end-milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.

Ključne riječi
end-milling; adaptive force control; neural controller

Hrčak ID: 8842

URI
https://hrcak.srce.hr/8842

Posjeta: 2.149 *