Projects

Rolling element bearings are widely used in rotating machinery including mining, aerospace, manufacturing and rail vehicles such as passenger and freight wagons and locomotives engines. The failure of rolling element bearing is one of the common reasons for machinery breakdowns. While this causes major repair costs, bearing failure could be life threatening. With condition monitoring systems in place, the unnecessary costs due to scheduled maintenance can be reduced by only addressing bearings that have been identified as potentially faulty. Effective bearing condition monitoring systems should be able to detect and estimate the size of defects in bearings at early stages of a defect development to either enable remedial action to be taken, or schedule the replacement of the bearing at a convenient time. The typical vibro-acoustic condition monitoring process involves the measuring vibro-acoustic level on a bearing housing and trending the level over time. When the level exceeds a nominated threshold, the bearing is flagged for replacement. Alternatively, the philosophy of this research project is to determine the geometric arc length and the geometry shape of a bearing defect from the vibro-acoustic signal, without using historical data. This research involves experimental and modelling analysis of various defective bearings with various defect geometries, and developing sophisticated signal processing methods to reliably detect and categorise defects in bearing by monitoring the vibro-acoustic signature.