@inproceedings{48cb88640f1a4901aeb30bf926ad2333,
title = "Condition monitoring of operating spindle based on stochastic subspace identification",
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.",
keywords = "Condition monitoring, Non-intrusive testing, Spindle, Structural dynamics, Subspace identification",
author = "Gao, \{Robert X.\} and Ruqiang Yan and Li Zhang and Lee, \{Kang B.\}",
year = "2008",
doi = "10.1115/IMECE2007-41988",
language = "英语",
isbn = "0791843033",
series = "ASME International Mechanical Engineering Congress and Exposition, Proceedings",
publisher = "American Society of Mechanical Engineers (ASME)",
pages = "1129--1136",
booktitle = "Mechanical Systems and Control",
note = "ASME International Mechanical Engineering Congress and Exposition, IMECE 2007 ; Conference date: 11-11-2007 Through 15-11-2007",
}