Formal modelling and analysis of software requirements for air traffic management systems for improved integrity assurance. This project will significantly reduce the time and cost of developing software for critical applications such as aviation and air traffic management. As well as improving the trustworthiness of safety-critical computer-based systems, this project will also enable system improvements to be deployed faster and more reliably.
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
Temporal and spatial Bayesian network modelling for improved fog forecasting. This project aims to improve the accuracy of fog forecasting by explicitly modelling the spatial and temporal uncertainties surrounding fog formation. It is expected weather forecast services will adopt our approach to improve their predictions of fog, which will in turn help transport companies save costs, cut emissions and improve safety.
Discovery Early Career Researcher Award - Grant ID: DE120100802
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Developing novel concepts for improved safety in aircraft emergency situations. The outcomes of this project will enable the creation of an emergency system that can improve visual situation awareness in emergency landing scenarios by investigating novel detection, control and planning algorithms. The project will contribute significantly to Australia's share in technologies for aircraft automation.