Comprehensive bearing condition monitoring algorithm for incipient fault detection using acoustic emission
Amit R. Bhende, Gajanan K. Awari, Sachin P. Untawale
The bearing reliability plays major role in obtaining the desired performance of any machine. A continuous condition monitoring of machine is required in certain applications where failure of machine leads to loss of production, human safety and precision. Machine faults are often linked to the bearing faults. Condition monitoring of machine involves continuous watch on the performance of bearings and predicting the faults of bearing before it cause any adversity. This paper investigates an experimental study to diagnose the fault while bearing is in operation. An acoustic emission technique is used in the experimentation. An algorithm is developed to process various types of signals generated from different bearing defects. The algorithm uses time domain analysis along with combination low frequency analysis technique such as fast Fourier transform and high frequency envelope detection. Two methods have adopted for envelope detection which are Hilbert transform and order analysis. Experimental study is carried out for deep groove ball bearing cage defect. Results show the potential effectiveness of the proposed algorithm to determine presence of fault, exact location and severity of fault.