Paper
2 February 2001 Experimental analysis and modeling of the dynamic performance of machine tool spindle-bearing systems
Author Affiliations +
Proceedings Volume 4191, Sensors and Controls for Intelligent Manufacturing; (2001) https://doi.org/10.1117/12.417240
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
In this paper, an analysis of the dynamic characteristics of machine tool spindle-bearing systems is presented. The research utilized the force impact-response testing method. The results are applied to the analysis and modeling of the dynamic performance of machine tool spindle-bearing systems. As an indicator of dynamic performance, the impulse response matrices are experimentally obtained. Two types of impulse response matrices are considered: (1) with respect to (wrt) acceleration; which describes the space-coupled relationship between the vectors of the force (impact) and measured acceleration (response) and (2) wrt displacement; which describes the space-coupled relationship between vectors of the force and simulated displacement. The results indicate an interrelation between different directions of displacements, and lay a foundation for the dynamic modeling of spindle-bearing systems in view of the transfer matrix with nonzero non-diagonal elements. From an engineering point of view, the transfer function matrix can be considered a `dynamic imprint', or `signature' of system performance. As a practical example, the dynamic properties (the impulse and frequency response matrices) of the spindle-bearing system of a Barer-Proteo D/94 high precision machining center are obtained, identified and investigated. The developed approach for modeling and parameter identification appears promising for a wide range of industrial applications, including rotary systems.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evgueni V. Bordatchev, Peter E. Orban, and Adam Rehorn "Experimental analysis and modeling of the dynamic performance of machine tool spindle-bearing systems", Proc. SPIE 4191, Sensors and Controls for Intelligent Manufacturing, (2 February 2001); https://doi.org/10.1117/12.417240
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Spindles

Modeling

Systems modeling

Data modeling

Mathematical modeling

Matrices

Performance modeling

Back to Top