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A defect-driven diagnostic method for machine tool spindles

Published

Author(s)

Gregory W. Vogl, M A. Donmez

Abstract

Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition.
Citation
CIRP Annals-ManufacturingTechnology
Volume
64
Issue
1

Keywords

Spindle, Condition monitoring, Vibration, Machine tools

Citation

Vogl, G. and Donmez, M. (2015), A defect-driven diagnostic method for machine tool spindles, CIRP Annals-ManufacturingTechnology, [online], https://doi.org/10.1016/j.cirp.2015.04.103 (Accessed October 31, 2024)

Issues

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Created December 31, 2015, Updated November 10, 2018