Title :
Using the Cyclostationarity of Electrical Signal for Bearing Fault Detection in Induction Machine
Author :
Ibrahim, Ali ; El Badaoui, Mohamed ; Guiller, F. ; Zoaeter, Mohamed
Author_Institution :
IUT de Roanne, Roanne
Abstract :
We present in this paper the detection of a rolling defect in an asynchronous machine by analysis of the electric signals. For this purpose, we used a Wiener filter to decrease the dynamics of the 50 Hz and to increase the frequencies associated to the mechanical load. Thus, we could detect the presence of a ball defect. This result is corroborated by an envelope analysis of the vibratory signals. The suggested method exploits the cyclostationarity of electrical signals (voltage and current) via their cyclic statistics to resynchronization the signals according to the electrical cycle (50 Hz) in order to recover frequency fluctuations. We then estimate the Wiener filter which is highly adapted to our application in order to obtain a signal corresponding to the electrical part only, which allows extracting the mechanical part on the measured current. An experimental result, in the presence of fault in rolling element bearings, illustrates the high performance of the proposed method.
Keywords :
Wiener filters; asynchronous machines; fault location; machine bearings; Wiener filter; asynchronous machine; bearing fault detection; cyclic statistics; electrical signal cyclostationarity; induction machine; mechanical load; rolling element bearings; signal resynchronization; vibratory signals; Current measurement; Electrical fault detection; Fluctuations; Frequency; Induction machines; Mechanical variables measurement; Signal analysis; Statistics; Voltage; Wiener filter; Asynchronous machine; Wiener filter; cyclostationarity; diagnosis; electrical signals; envelope analysis; rolling defect;
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
DOI :
10.1109/ICIT.2006.372654