Operating machinery generates noise and vibration that can be used to determine if there is a fault with it. By analysing the vibration or acoustic signature of a bearing, fault types and the severity can be determined.
Examples of research projects include:
- ARC Linkage Project with TrackIQ to develop an acoustic based method to detect bearing faults in moving rail vehicles.
- Analysis of the vibration signatures of faulty bearings.
- Finite element analysis of defective bearings.
- Estimation of the defect size in a bearings from the vibration signature.
- Numerical modelling of defective bearings.
- Online condition monitoring of induction motors.
Contact Associate Professor Carl Howard for more information.