OUTLIER DETECTION IN ROTATING MACHINERY UNDER NON-STATIONARY OPERATING CONDITIONS USING DYNAMIC FEATURES AND ONE-CLASS CLASSIFIERS

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...

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Bibliographic Details
Published inDyna (Medellín, Colombia) Vol. 80; no. 182; pp. 173 - 181
Main Authors OSCAR CARDONA MORALES, ÁLVAREZ MARÍN, DIEGO A, Castellanos-Dominguez, German
Format Journal Article
LanguageSpanish
English
Published Bogota Universidad Nacional de Colombia 01.01.2013
Subjects
características dinámicas
clasificación de una clase
class classification
data description
descripción de datos
dynamic features
one
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Summary: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.
ISSN:0012-7353
2346-2183