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Electrical Engineering
Erschienen in: Electrical Engineering 1/2017

30.09.2016 | Original Paper

Single point bearing fault diagnosis using simplified frequency model

verfasst von: Mohamed Lamine Masmoudi, Erik Etien, Sandrine Moreau, Anas Sakout

Erschienen in: Electrical Engineering | Ausgabe 1/2017

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Abstract

The time synchronous averaging (TSA) is a well-known technique used for early detection of bearing failure in electrical machines. This method is very efficient if the characteristic default frequency is perfectly known. In this article, a reduced frequency model, derived from ESPRIT algorithm, is used to provide a very accurate estimation of the fault frequency. The precision obtained on this frequency allows to apply TSA algorithm under optimal conditions. The proposed method is tested on simulated and real vibration signals for inner and outer ring faults. Finally, a fault indicator is proposed to discriminate the healthy case from the faulty one.
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Metadaten
Titel
Single point bearing fault diagnosis using simplified frequency model
verfasst von
Mohamed Lamine Masmoudi
Erik Etien
Sandrine Moreau
Anas Sakout
Publikationsdatum
30.09.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 1/2017
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-016-0441-y

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