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.
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
Bemerkung zur Veröffentlichung
8th CIRP Global Web Conference (CIRPe 2020) : Flexible Mass Customisation, 14-16 October 2020, Online