Title :
Rolling element bearing fault diagnosis in rotating machines of oil extraction rigs
Author :
Mendel, E. ; Rauber, T.W. ; Varejao, F.M. ; Batista, R.J.
Author_Institution :
Dept. of Comput. Sci., Fed. Univ. of Espirito Santo, Vitoria, Brazil
Abstract :
This paper presents vibration analysis techniques for fault detection in rotating machines. Rolling element bearing defects inside a motor pump are the subject of study. Signal processing techniques, like frequency filters, Hilbert transform, and spectral analysis are used to extract features used later as a base to classify the condition of machines. Also, pattern recognition techniques are applied to the obtained features to improve the classification precision. In a previous work, a graphic simulation was used to produce signals to illustrate the idea of the method. In this work we examine the performance of this method for monitoring bearing condition when applied to rotating machines of oil rigs, that is, when applied to real problems.
Keywords :
Hilbert transforms; electric machines; fault diagnosis; feature extraction; oil drilling; pumps; rolling bearings; signal classification; spectral analysis; Hilbert transform; fault detection; feature extraction; frequency filters; motor pump; oil extraction rigs; pattern recognition techniques; rolling element bearing fault diagnosis; rotating machines; signal processing techniques; spectral analysis; vibration analysis techniques; Abstracts; Accuracy; Amplitude modulation; Demodulation; Monitoring; Offshore installations; Vibrations;
Conference_Titel :
Signal Processing Conference, 2009 17th European
Conference_Location :
Glasgow
Print_ISBN :
978-161-7388-76-7