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Retrofittable vibration-based monitoring of milling processes using wavelet packet transform

Barton, David; Federhen, Jens; Fleischer, Jürgen

Abstract (englisch):
An important aspect of the overall quality of machined parts is surface roughness, which depends on cutting parameters, tool condition, and machine vibrations. Online surface roughness prediction in milling operations can reduce set up time and assist in determining economic cutting parameters. However, the adoption of existing solutions in industrial production is inhibited by lacking integration in an open and retrofittable architecture. In this contribution, a solution for surface roughness estimation by vibration monitoring is developed as part of a retrofitting kit. Wavelet packet transform is used to filter the vibration signal, then the roughness of the generated surface is estimated. The approach is tested in milling experiments.

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Verlagsausgabe §
DOI: 10.5445/IR/1000129650/pub
Veröffentlicht am 12.02.2021
Originalveröffentlichung
DOI: 10.1016/j.procir.2021.01.099
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 11.01.2021
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000129650
Erschienen in Procedia CIRP
Verlag Elsevier
Band 96
Seiten 353–358
Nachgewiesen in Dimensions
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