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| Natura: | Artículo científico |
| Lingua: | en |
| Pubblicazione: |
Universidad Nacional de Colombia
2013
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| Accesso online: | https://www.redalyc.org/articulo.oa?id=49629318022 |
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Sommario:
- OUTLIER DETECTION IN ROTATING MACHINERY UNDER NON-STATIONARY OPERATING CONDITIONS USING DYNAMIC FEATURES AND ONE-CLASS CLASSIFIERS OSCAR CARDONA MORALES DIEGO A. ÁLVAREZ MARÍN GERMAN CASTELLANOS-DOMINGUEZ Ingeniería One Dynamic features Data description class classification The main goal of condition-based maintenance is to describe the machine state under current operating regimes, which can be non-stationary depending of load/speed changes. Besides, damaged machine data are not always available in real-world applications. This paper proposes a methodology of outlier detection in time-varying mechanical systems based on dynamic features and data description classifiers. Dynamic features set is formed by spectral sub-band centroids and linear frequency cepstral coefficients extracted from time-frequency representations. One-class classification is carried out to validate performance of the dynamic features as descriptors of machine behavior. The methodology is tested with a data set coming from a test-rig including different machine states with variable speed conditions. The proposed approach is validated on real recordings acquired from a ship driveline. The results outperform other time-frequency features in terms of classification performance. The methodology is robust to minimal changes in the machine state and/or time-varying operational conditions. 2013 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49629318022 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.182 Vol.80