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Condition Monitoring of Operating Spindle Based on Stochastic Subspace Identification

Published

Author(s)

Robert Gao, Ruqiang Yan, Li Zhang, Kang B. Lee

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

Keywords

Condition monitoring, non-intrusive testing, spindle, structural dynamics, subspace identification.

Citation

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 May 30, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created November 10, 2007, Updated October 12, 2021