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
Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patter ....Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patterns of brain activity that predict a lapse of attention. The results should contribute to theories of vigilance and improve performance in real-world monitoring situations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101747
Funder
Australian Research Council
Funding Amount
$354,216.00
Summary
Mechanism and control of water droplets from condensation to defrosting. The deposition of frost/ice is inevitable and negatively impacts many fields and industries, such as the frosting of air source heat pumps and liquid natural gas vaporizers, and icing of aircraft and power cables. On the other hand, ice slurry is widely deployed for cold storage and transportation of food and organs. To accurately predict and control the frosting/icing process, this project aims to study and understand the ....Mechanism and control of water droplets from condensation to defrosting. The deposition of frost/ice is inevitable and negatively impacts many fields and industries, such as the frosting of air source heat pumps and liquid natural gas vaporizers, and icing of aircraft and power cables. On the other hand, ice slurry is widely deployed for cold storage and transportation of food and organs. To accurately predict and control the frosting/icing process, this project aims to study and understand the interrelated heat, mass and momentum transport phenomena of water droplets from condensation to defrosting. Outcomes of this project should contribute to the development of new material, such as applicable anti-icing/anti-frosting surfaces, and relative technology and equipment, and thus benefit a number of fields.Read moreRead less
Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/S ....Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/SAR missions. It will exploit recent advances in Partially Observable Markov Decision Processes (POMDPs) to recommend robust, safe, and pilot-aware mission and manoeuvring strategies to make HEMS/SAR operations safer for helicopter crews, and more effective for those in need of the service.Read moreRead less
When every second counts: Multi-drone navigation in GPS-denied environments. The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localizatio ....When every second counts: Multi-drone navigation in GPS-denied environments. The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localization and Mapping (SLAM) algorithms with Partially Observable Markov Decision Processes (POMDP) and Deep Reinforcement learning. This should provide significant benefits, such as more responsive search and rescue inside collapsed buildings or underground mines, as well as fast target detection and mapping under the tree canopy. Read moreRead less