Condition Monitoring of Operating Spindle Based on Stochastic Subspace Identification

Published

November 11, 2007

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

Pub Type

Conferences

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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 October 9, 2025)