Gao, R.
, Yan, R.
, Zhang, L.
and Lee, K.
(2007),
Condition Monitoring of Operating Spindle Based on Stochastic Subspace Identification, 2007 ASME International Mechanical Engineering Congress and Exposition, Seattle, WA, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=823019
(Accessed October 6, 2024)
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Condition Monitoring of Operating Spindle Based on Stochastic Subspace Identification
Published
Author(s)
Robert Gao, , Li Zhang,
Abstract
Accurate identification of spindle modal parameters is critical to realizing a new generation of "smart" machine tools with built-in self-diagnosis capability. This paper describes a new approach to extracting spindle modal parameters from the output measured during operation, based upon stochastic subspace identification. The technique accounts for structural dynamic behavior associated with the spindle rotation that is not present when the spindle remains stationary. Experimental results conducted on a customized spindle test bed under different speed-load combinations confirm the effectiveness of the new technique for on-line spindle condition monitoring.Conference Dates
November 11-15, 2007
Conference Location
Seattle, WA, USA
Conference Title
2007 ASME International Mechanical Engineering Congress and Exposition
Pub Type
Conferences
Download Paper
Keywords
Condition monitoring, non-intrusive testing, spindle, structural dynamics, subspace identification.
Citation
Issues
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Created November 10, 2007, Updated October 12, 2021