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Scheme : Linkage Projects
Status : Active
Research Topic : vibration
Australian State/Territory : NSW
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Dynamics vibration and vibration control (3)
Dynamics, Vibration and Vibration Control (3)
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  • Funded Activities (7)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP220200934

    Funder
    Australian Research Council
    Funding Amount
    $406,838.00
    Summary
    Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely .... Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely diagnostics and prognostics and innovative proactive control measures that mitigate their impact on autonomous driving quality and safety. The expected benefits for the automotive industry and end-users include increased safety and reliability of steering systems, and higher confidence in autonomous driving.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP220100389

    Funder
    Australian Research Council
    Funding Amount
    $348,406.00
    Summary
    An intelligent condition-monitoring system for mineral screening machines. This project aims to develop an intelligent condition-monitoring system for screening machines which are widely used for classifying mineral particles in the mining industry. This project will develop new vibration-based methodologies and techniques for fault diagnostics and remaining useful life prediction of bearings and gears in situations with multiple complex sources and interferences. The monitoring system, as the e .... An intelligent condition-monitoring system for mineral screening machines. This project aims to develop an intelligent condition-monitoring system for screening machines which are widely used for classifying mineral particles in the mining industry. This project will develop new vibration-based methodologies and techniques for fault diagnostics and remaining useful life prediction of bearings and gears in situations with multiple complex sources and interferences. The monitoring system, as the expected outcomes of this project, will modernise the current maintenance practices towards condition-based predictive maintenance, reducing unplanned downtime, increasing productivity and reducing maintenance costs for the Australian mining industry. It will also add more value to the Australian manufactured products.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180101161

    Funder
    Australian Research Council
    Funding Amount
    $194,546.00
    Summary
    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.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210301054

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings a .... Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings and outcomes of this research will advance the knowledge and practice of hard-rock mining machines in Australia. The success of this project will significantly increase mining productivity and reduce human injury
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    Active Funded Activity

    Linkage Projects - Grant ID: LP230100456

    Funder
    Australian Research Council
    Funding Amount
    $371,499.00
    Summary
    Dynamic model assisted fault diagnostics of wind turbine gearbox. This project aims to develop novel condition monitoring methodologies for the gearbox of large horizontal-axis wind turbines which are widely installed in wind farms for generating renewable energy. This project expects to generate a new diagnostic framework by integrating dynamic model assisted simulations and digital twin-based approaches. Expected outcomes of this project include new vibration-based methods for fault diagnostic .... Dynamic model assisted fault diagnostics of wind turbine gearbox. This project aims to develop novel condition monitoring methodologies for the gearbox of large horizontal-axis wind turbines which are widely installed in wind farms for generating renewable energy. This project expects to generate a new diagnostic framework by integrating dynamic model assisted simulations and digital twin-based approaches. Expected outcomes of this project include new vibration-based methods for fault diagnostics and predictions of the remaining useful life of turbine gearboxes. This should provide significant benefits to the Australian Wind Industry by ensuring reliable operation of wind turbines, reducing turbine downtime and reducing operation and maintenance costs; ultimately lowering the cost of energy from wind.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200100382

    Funder
    Australian Research Council
    Funding Amount
    $302,000.00
    Summary
    Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities fo .... Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities for frequent, low-cost track monitoring; 3) novel inspection and maintenance optimisation methods to efficiently allocate resources. The knowledge generated by this project is expected to decrease maintenance costs, safety risk, and track closures and therefore enhance the affordability and reliability of rail travel.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210200285

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    Development of Novel Concrete Noise Walls Incorporating Recycled Materials. This project will develop high-performance, lightweight, concrete noise walls and acoustic barriers that use recycled tyre and glass products to improve sound absorption, and address environmental problems associated with the mining of river sands, and stockpiling of waste tyre and glass products. Innovation in noise wall technology consists in developing low-carbon concrete mixes (using less cement) with a maximum amoun .... Development of Novel Concrete Noise Walls Incorporating Recycled Materials. This project will develop high-performance, lightweight, concrete noise walls and acoustic barriers that use recycled tyre and glass products to improve sound absorption, and address environmental problems associated with the mining of river sands, and stockpiling of waste tyre and glass products. Innovation in noise wall technology consists in developing low-carbon concrete mixes (using less cement) with a maximum amount of recycled product, together with reducing wall thickness, while maintaining the necessary engineering properties such as acoustics, strength, and durability. In addition to higher acoustic insulation, the novel low-carbon, lightweight, panels will improve material handling and affordability of noise barriers.
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    Showing 1-7 of 7 Funded Activites

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