Bearing fault severity estimation using time–based descriptors for rotating electric machines
This paper evaluates the bearing fault severity in rotating electric machines based on the time–based descriptors derived from machine vibration signal. Time–based descriptors are independent of bearing dimensions and machine dynamics. To establish the relationship between the time–based descriptor and bearing fault severity, a wide range of defective bearings are examined on an experimental set–up and the factors contributing to the value of time–based descriptor are determined. The application of this technique to the bearing faults such as rolling element, inner–race and outer–race fault, has confirmed that time–based descriptor successfully measures the severity of faults. The significance of time–based descriptors has been evaluated and tested by developing online bearing failure situation via shaft current. Since the time–based descriptors are independent of dimensions and characteristic frequencies of the bearing, the severity estimation is less sensitive to operating conditions for data acquisition. The laboratory investigations on 10–hp cage induction motor are presented.
Keywords: condition monitoring, vibration analysis, bearing faults, fault diagnosis, fault severity estimation, rotating electric machines, time–based descriptors, defective bearings