title: A defect-driven diagnostic method for machine tool spindles.
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.
authors.affiliation: Engineering Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, Maryland 20899-8220, USA.
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Vogl
authors.affiliation: Engineering Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, Maryland 20899-8220, USA.
authors.forename: M Alkan
authors.initials: MA
authors.lastname: Donmez
keywords: Condition monitoring; Machine tools; Spindle; Vibration