Uroš Župerl (Author), Franc Čuš (Author), Edvard Kiker (Author), Matjaž Milfelner (Author)

Abstract

V prispevku je prikazana uporaba združevanja metod nevronskih mrež in mehke logike pri modeliranju in prilagodnem krmiljenju postopka oblikovnega frezanja. Izdelan je celovit postopek hibridnega modeliranja postopka odrezovanja (sistem ANfis), ki ga uporabimo pri izdelavi simulatorja frezanja RNK. S hibridnim modeliranjem postopka, ločeno optimizacijo ter usmerjeno nevronsko krmilno shemo (UNKS) je zgrajen kombiniran sistem za posredno optimiranje in prilagodno nastavljanje rezalnih parametrov. To je prilagodni sistem krmiljenja, ki z digitalno prilagodljivostjo rezalnih parametrov nadzoruje rezalno silo in ohranja stalno hrapavost obdelane površine med frezanjem. Tako uravnotezi vse motnje postopka odrezovanja: obrabo orodja, nehomogenost obdelovanega materiala, vibracije, drdranje itn. Poglavitno načelo vodenja je izvedeno s krmilno shemo (UNKS), ki jo sestavljata dve nevronski razpoznavali dinamike postopka in primarni krmilnik. Simulator frezanja RNK testira stabilnost sistema in uglasi parametre krmilne sheme. Postopek je bil uspešno uporabljen na RNK frezalnem stroju Heller. S preizkusi je potrjena učinkovitost prilagodnega sistema krmiljenja, ki se kaze v izboljšani kakovosti površine in manjši obrabi orodja.

Keywords

frezanje oblikovno;krmiljenje sil;odrezovanje;optimiranje;sistemi prilagoditveni

Data

Language: Slovenian
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FS - Faculty of Mechanical Engineering
Publisher: Association of Mechanical Engineers and Technicians of Slovenia et al.
UDC: 621.914:681.51
COBISS: 8511259 Link will open in a new window
ISSN: 0039-2480
Parent publication: Strojniški vestnik
Views: 295
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Other data

Secondary language: English
Secondary title: ǂA ǂcombined system for off-line optimization and adaptive adjustment of the cutting parameters during a ball-end milling process
Secondary abstract: This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feed-forward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness ofthe surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.
Secondary keywords: machining;force control;adaptive control systems;optimization;ball-end mill;odrezovanje;krmiljenje sil;sistemi prilagoditveni;optimiranje;frezanje oblikovno;
URN: URN:NBN:SI
Type (COBISS): Not categorized
Pages: str. 542-559
Volume: ǂLetn. ǂ51
Issue: ǂšt. ǂ9
Chronology: 2005
ID: 1743131