Vibration-based health monitoring of aero-engine bearings . This project will develop new vibration-based techniques to greatly improve the detection and diagnosis of faults in aero engine bearings from in-flight measurements. To achieve this goal, advances will be made on source separation algorithms to extract the weak bearing signals, and signal processing techniques to extract features for diagnosing bearing fault severity and lubrication conditions, under a wide range of operating condition ....Vibration-based health monitoring of aero-engine bearings . This project will develop new vibration-based techniques to greatly improve the detection and diagnosis of faults in aero engine bearings from in-flight measurements. To achieve this goal, advances will be made on source separation algorithms to extract the weak bearing signals, and signal processing techniques to extract features for diagnosing bearing fault severity and lubrication conditions, under a wide range of operating conditions. A bearing degradation model will estimate the remaining useful life. Since rolling element bearings are among the most critical components in most machines, the results of this research will also provide massive benefits in other sectors such as mining, transportation, energy production and manufacturing.Read moreRead less
A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allo ....A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allow estimation of relatively weak friction forces, previously neglected, as an important prognostic tool. This would allow detailed root cause analysis and prediction of remaining useful life. Improvements in gear prognosis would have safety and economic benefits by eliminating unforeseen catastrophic failures and optimising maintenance schedules.Read moreRead less