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
High-fidelity simulations for new models that reduce noise pollution. This project aims to develop a method for accurate and affordable prediction and mitigation of flow-induced noise. The innovative approach, based on recent developments in simulation and data-driven modelling, expects to reduce environmental noise pollution, improve public health and ease the impact of urbanisation. To date methodological limitations have hampered our ability to predict noise reliably and hence control it. Thi ....High-fidelity simulations for new models that reduce noise pollution. This project aims to develop a method for accurate and affordable prediction and mitigation of flow-induced noise. The innovative approach, based on recent developments in simulation and data-driven modelling, expects to reduce environmental noise pollution, improve public health and ease the impact of urbanisation. To date methodological limitations have hampered our ability to predict noise reliably and hence control it. This project, exploiting proven high-fidelity simulation and machine-learning techniques to overcome limitations to produce the scientific knowledge required for practical noise mitigation. Benefits include quieter aerospace, marine and renewable energy technologies, creating more pleasant communities.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100067
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Wind profiler network for planetary boundary layer research. Understanding winds in the lower atmosphere is of great fundamental and practical importance. This new wind monitoring network will help Australian scientists to better predict propagation of tropical cyclones, to improve the efficiency of wind energy production, and to better understand atmosphere-ocean interactions affecting weather and climate.