Model based reconstruction of milled surface topography from measured cutting forces

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • B. Denkena
  • M. Krüger
  • D. Bachrathy
  • G. Stepan

Externe Organisationen

  • Hungarian Academy of Sciences
  • Budapest University of Technology and Economics
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)25-33
Seitenumfang9
FachzeitschriftInternational Journal of Machine Tools and Manufacture
Jahrgang54-55
Frühes Online-Datum23 Dez. 2011
PublikationsstatusVeröffentlicht - März 2012

Abstract

This paper presents a method for the reconstruction of surface topographies of peripheral milled surfaces based on measured cutting forces. Even under stable process conditions, machine tool vibrations occur due to the milling tools dynamic excitation. In order to estimate the influence of tool vibrations on surface degradation, a dynamic tool model is developed and applied to a material removal model. The proposed tool model is able to reconstruct the accurate shape and roughness of machined surfaces. The developed method is verified by comparing the reconstructed and the measured surface topographies. The results demonstrate that the method is able to reconstruct the surface topography of the machined workpiece from measured resultant cutting forces and it can be used also for the online monitoring of milling processes.

ASJC Scopus Sachgebiete

Zitieren

Model based reconstruction of milled surface topography from measured cutting forces. / Denkena, B.; Krüger, M.; Bachrathy, D. et al.
in: International Journal of Machine Tools and Manufacture, Jahrgang 54-55, 03.2012, S. 25-33.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Denkena B, Krüger M, Bachrathy D, Stepan G. Model based reconstruction of milled surface topography from measured cutting forces. International Journal of Machine Tools and Manufacture. 2012 Mär;54-55:25-33. Epub 2011 Dez 23. doi: 10.1016/j.ijmachtools.2011.12.007
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N1 - Funding information: The results presented in this paper were obtained within the Collaborative Research Center 653 “Gentelligent Components in their Lifecycle” (TP-K2). The authors would like to thank the German Research Foundation for its financial and organizational support. The article are result of the activities performed within DYNXPERTS project, funded by the European Commission—FP7 Factories of the Future with the Grant Number 260073 and it is connected to the scientific program of the “Development of quality-oriented and harmonized R+D+I strategy and functional model at BME” project. This project is supported by the New Hungary Development Plan (Project ID: TÁMOP-4.2.1/B-09/1/KMR-2010-0002 ).

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