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Details van artikel 29 van 124 gevonden artikelen
| Titel: |
Bearing fault detection using multi-scale fractal dimensions based on morphological covers |
| Auteur: |
Zhang, Pei-Lin Li, Bing Mi, Shuang-Shan Zhang, Ying-Tang Liu, Dong-Sheng |
| Verschenen in: |
Shock and vibration |
| Paginering: | Jaargang 19 (2012) nr. 6 pagina's 1373-1383 |
| Jaar: |
2012-03-07 |
| Inhoud: |
Vibration signals acquired from bearing have been found to demonstrate complicated nonlinear characteristics in literature. Fractal geometry theory has provided effective tools such as fractal dimension for characterizing the vibration signals in bearing faults detection. However, most of the natural signals are not critical self-similar fractals; the assumption of a constant fractal dimension at all scales may not be true. Motivated by this fact, this work explores the application of the multi-scale fractal dimensions (MFDs) based on morphological cover (MC) technique for bearing fault diagnosis. Vibration signals from bearing with seven different states under four operations conditions are collected to validate the presented MFDs based on MC technique. Experimental results reveal that the vibration signals acquired from bearing are not critical self-similar fractals. The MFDs can provide more discriminative information about the signals than the single global fractal dimension. Furthermore, three classifiers are employed to evaluate and compare the classification performance of the MFDs with other feature extraction methods. Experimental results demonstrate the MFDs to be a desirable approach to improve the performance of bearing fault diagnosis. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 29 van 124 gevonden artikelen
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