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|Author(s):||Ruqiang Yan; Robert Gao; Zhang Li; Kang B. Lee;|
|Title:||Modal Parameter Identification from Output-only Measurement Data: Application to Operating Spindle Condition Monitoring|
|Published:||September 23, 2008|
|Abstract:||This paper presents an experimental investigation of the dynamics of a custom-designed spindle test system under different operation conditions and at various stages of its service life. Unlike classical modal analysis techniques where known input excitation from hammer strikes are employed to excite the spindle, the presented output-only modal analysis method applies the stochastic subspace identification algorithm to the spindle response measured during its operation such that the modal parameters of the spindle as well as their variation are identified. This method accounts for the structural excitations during the spindle operation, which are not considered if the spindle remains stationary in the experiment. The obtained modal parameters provide insight into structural changes of the spindle during its service life, and can be used as indictor for enhanced spindle condition monitoring.|
|Proceedings:||Proceedings of the 8th International Conference on Frontiers of Design and Manufacturing|
|Dates:||September 23-26, 2008|
|Keywords:||Spindle Dynamics, Output-only Modal Analysis, Stochastic Subspace Identification, Condition monitoring|
|Research Areas:||Lean Manufacturing, Manufacturing|
|PDF version:||Click here to retrieve PDF version of paper (318KB)|