Isolation and identification of dry bearing faults in induction machine using wavelet transform

Any vibration signal obtained from electromechanical systems contains a level of random changes. These random changes in the measured signal may be due to the random vibrations that can be related to the health of the machine for some faults such as dry bearing fault or bearing ageing. The presence of dry bearing fault, which is caused by the lack of lubricant, increases the level of random vibrations as compared to those obtained in healthy bearing machine. If these random vibrations could be isolated from the measured signal, useful information about bearing health may be obtained. Therefore, in this paper, signals (three line to line voltages, three currents, two vibration signals, four temperatures and one speed signal) obtained from the monitoring system are treated and analyzed using wavelet transform to correlate it to the dry bearing faults in induction machine. In this study, on-line analysis of the acquired signals has been performed using C⁺⁺, while MATLAB has been used to perform the off-line analysis.