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Bearing fault detection by a novel condition-monitoring scheme based on statistical-time features and neural networks
Delgado Prieto, Miquel; Cirrincione, Giansalvo; García Espinosa, Antonio; Ortega Redondo, Juan Antonio; Henao, Humberto
Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica; Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. MCIA - Centre MCIA Innovation Electronics
Bearing degradation is the most common source of faults in electrical machines. In this context, this work presents a novel monitoring scheme applied to diagnose bearing faults. Apart from detecting local defects, i.e., single-point ball and raceway faults, it takes also into account the detection of distributed defects, such as roughness. The development of diagnosis methodologies considering both kinds of bearing faults is, nowadays, subject of concern in fault diagnosis of electrical machines. First, the method analyzes the most significant statistical-time features calculated from vibration signal. Then, it uses a variant of the curvilinear component analysis, a nonlinear manifold learning technique, for compression and visualization of the feature behavior. It allows interpreting the underlying physical phenomenon. This technique has demonstrated to be a very powerful and promising tool in the diagnosis area. Finally, a hierarchical neural network structure is used to perform the classification stage. The effectiveness of this condition-monitoring scheme has been verified by experimental results obtained from different operating conditions.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria mecànica::Processos de fabricació mecànica::Màquines i mecanismes
Àrees temàtiques de la UPC::Enginyeria mecànica::Motors::Motors elèctrics
Àrees temàtiques de la UPC::Energies::Energia elèctrica::Electricitat
Ball-bearings
Electric motors, Induction
Neural networks (Computer science)
Electric fault location
Vibration--Control
Ball bearings classification algorithms condition monitoring fault diagnosis feature extraction induction motors neural networks vibrations
Rodaments de boles
Motors elèctrics d'inducció
Xarxes neuronals (Informàtica)
Energia elèctrica -- Transmissió
Vibració -- Control
info:eu-repo/semantics/publishedVersion
Article
Institute of Electrical and Electronics Engineers (IEEE)
         

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