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Automatic bearing fault classification combining statistical classification and fuzzy logic
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| Author(s) |
T. Lindh; J. Ahola; P. Spatenka; A-L Rautiainen |
| Abstract |
In this paper, a new automatic analysis method for the detection of cyclic bearing faults is introduced. The method uses a multivariate statistical fault classification
and fuzzy logic. Features are extracted from an envelope
spectrum of the frame acceleration of a motor frame. Qualitative and quantitative measures of the features are utilized. |
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| Filename: | Unnamed file |
| Filesize: | 65.09 KB |
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| Type |
Members Only |
| Date |
Last modified 2006-01-24 by System |
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