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Proceedings Paper

Vibration-based machine condition monitoring with attention to the use of time-frequency methods
Author(s): Adam G. J. Rehorn; Peter E. Orban; Jin Jiang
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Paper Abstract

To enable lightly staffed or fully autonomous machining operations, it is essential that both the condition of the cutter and the health of the machine tool system be known. In this paper, the health of the spindle positioning drive (Z axis) on a Proteo D/94 precision machining center is investigated using time, frequency and time-frequency techniques. Investigated is a cogging phenomenon produced as a result of the DC servomotor brushes sticking due to poor design. This incipient fault reduces the accuracy and controllability of the machine tool, and always leads to total drive failure. Thus, it is important to determine the fault signature of the drive so that corrective action may be taken before failure can occur, permanently damaging both the motor and the workpiece. The vibratory signatures of both a healthy and a faulty spindle during translation are analyzed. It is shown that a spindle under fault conditions behaves differently from a healthy one, and that time and time-frequency domain methods provide useful information on the status of the system. This paper lays the groundwork for the development of a future machine condition monitoring system, which can be easily retrofitted to any machine tool system.

Paper Details

Date Published: 4 March 2004
PDF: 12 pages
Proc. SPIE 5263, Intelligent Manufacturing, (4 March 2004); doi: 10.1117/12.515899
Show Author Affiliations
Adam G. J. Rehorn, Univ. of Western Ontario (Canada)
National Research Council (Canada)
Peter E. Orban, National Research Council (Canada)
Jin Jiang, Univ. of Western Ontatrio (Canada)


Published in SPIE Proceedings Vol. 5263:
Intelligent Manufacturing
Bhaskaran Gopalakrishnan; Angappa Gunasekaran; Peter E. Orban, Editor(s)

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