DOI | Trouver le DOI : https://doi.org/10.4028/www.scientific.net/AMM.197.124 |
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Auteur | Rechercher : Liu, Jie; Rechercher : Yang, Chunsheng1; Rechercher : Lou, Qingfeng |
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Affiliation | - Conseil national de recherches du Canada. Technologies de l'information et des communications
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Format | Texte, Article |
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Conférence | International Conference on Mechanical Science and Engineering, ICMSE 2012, July 20-22 2012, Beijing, China |
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Sujet | Bearing fault detection; Bearing fault signature; Catastrophic failures; Health condition; Nonstationary; Performance degradation; Research efforts; Rolling Element Bearing; Rotary machine; Bearings (structural); Condition monitoring; Fault detection; Rotating machinery; Signal processing; Vibration analysis; Feature extraction |
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Résumé | Rolling element bearings are widely used in various rotary machines. Most rotary machine failures are attributed to unexpected bearing faults. Accordingly, reliable bearing fault detection is critically needed in industries to prevent these machines' performance degradation, malfunction, or even catastrophic failures. Feature extraction plays an important role in bearing fault detection and significant research efforts have thus far been devoted to this subject from both academia and industry. This paper intends to provide a brief review of the recent developments in feature extraction for bearing fault detection, and the focus will be placed on the advances in methods for dealing with the nonstationary characteristics of bearing fault signatures. © (2012) Trans Tech Publications, Switzerland. |
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Date de publication | 2012-09-26 |
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Dans | |
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Série | |
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Langue | anglais |
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Publications évaluées par des pairs | Oui |
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Numéro NPARC | 21270040 |
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Exporter la notice | Exporter en format RIS |
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Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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Identificateur de l’enregistrement | f121dc26-853b-4076-9c19-aac5f434ae1f |
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Enregistrement créé | 2013-12-16 |
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Enregistrement modifié | 2020-04-21 |
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