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  • Load control in high speed milling
    Župerl, Uroš ; Kiker, Edvard ; Čuš, Franc, 1953-
    The paper describes a neural controller with optimization for the ball end-milling process. An architecture with two different kinds of neural networks is proposed. It is used for on-line optimal ... control of the milling process. A BP neural network is used to identify the milling state and to learn the appropriate mappings between the input and output variables of the machining orocess. The feedrate is selected as the optimised variable, and the milling state is estimated by the measured cutting forces. The goal is also to obtain an improvement of the milling process productivity by the use of an automatic regulation of the milling cutting force. Numerous simulations are conducted toconfirm the efficiency of this architecture.
    Vir: Annals of DAAAM for 2005 & proceedings of the 16th International DAAAM symposium "Intelligent manufacturing & Automation: "Focus on young researchers and scientsts", University of Rijeka, 19-22nd October 2005, Opatija, Croatia (Str. 401-402)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2005
    Jezik - angleški
    COBISS.SI-ID - 9959190

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