Title :
New method of data Treatment related to induction machine bearing fault using Axial Vibration Analytic Signal
Author :
Bouguerne, A. ; Lebaroud, Abdesselam ; Boukadoum, Aziz
Author_Institution :
Dept. of Electr. Eng., Univ. of Constantine, Constantine, Algeria
Abstract :
This paper deals with a new method called Axial Vibration Analytic Signal applied to Treatment of data for diagnosis the bearing faults of induction motor. This method consists a extracting vibration vectors forms by time-frequency representation. The calculation method based on the cloud points dispersion parameter has two main parts; the first part is the Hilbert transform of axial vibration signals. The second part is the normalization compared to module of AVAS. This method has been applied on the vibration data of a 5.5-kW induction motor test bench.
Keywords :
Hilbert transforms; fault diagnosis; induction motors; machine bearings; power engineering computing; signal processing; vibrations; AVAS; Hilbert transform; axial vibration analytic signal; bearing faults diagnosis; cloud points dispersion parameter; data treatment; induction machine bearing fault; induction motor; induction motor test bench; normalization; power 5.5 kW; time-frequency representation; vibration data; vibration vectors; Ball bearings; Dispersion; Feature extraction; Induction motors; Transforms; Vectors; Vibrations; axial vibration analytic signal; dispersion parameter; hilbert transform; time-frequency representation;
Conference_Titel :
Ecological Vehicles and Renewable Energies (EVER), 2013 8th International Conference and Exhibition on
Conference_Location :
Monte Carlo
Print_ISBN :
978-1-4673-5269-7
DOI :
10.1109/EVER.2013.6521521
