Guaranteeing the safety of short welds in automotive applications. Most safety-critical welds in the automotive and related industries are of short duration (less than three seconds). We will develop a unified theoretical model of short welds which accounts for all important phenomena. Using this model, we will create the first system to check every safety-critical weld in real time, with 3D data objects that use all the data available from the non-stationary process. The outcomes will be a comp ....Guaranteeing the safety of short welds in automotive applications. Most safety-critical welds in the automotive and related industries are of short duration (less than three seconds). We will develop a unified theoretical model of short welds which accounts for all important phenomena. Using this model, we will create the first system to check every safety-critical weld in real time, with 3D data objects that use all the data available from the non-stationary process. The outcomes will be a comprehensive understanding of short welds, which will be an essential step towards the development of more reliable welding procedures, and a weld fault monitor ready for industrial application.Read moreRead less
Gas metal arc welding process monitoring with acoustic sensing. This project aims to investigate the physical mechanisms of Gas Metal Arc Welding (GMAW) sound generation, and establish an acoustic model that correlates the acoustic signal with other wielding parameters. Key acoustic features and identification algorithms for process monitoring will be explored, and a prototype GMAW process monitoring system developed. GMAW is an arc welding process that is widely used in industry and well suited ....Gas metal arc welding process monitoring with acoustic sensing. This project aims to investigate the physical mechanisms of Gas Metal Arc Welding (GMAW) sound generation, and establish an acoustic model that correlates the acoustic signal with other wielding parameters. Key acoustic features and identification algorithms for process monitoring will be explored, and a prototype GMAW process monitoring system developed. GMAW is an arc welding process that is widely used in industry and well suited to automatic welding. The proposed monitoring method is an urgent need identified by industries for improving process control and quality. Auditory cues have been found to be critical for expert welders to adjust the weld process and to maintain quality, but the mechanisms underpinning the process are not well understood. The project will provide significant benefit to the Australian manufacturing industry’s productivity and innovation.Read moreRead less
A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced n ....A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced noise and other interference noise are further filtered out by a specific adaptive noise cancellation algorithm based on the spherical and differential microphone array structure. With the proposed system, the measurement configuration size is expected to be reduced from the current few metres to less than 10 centimetres, and with better accuracy.Read moreRead less
Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vecto ....Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.Read moreRead less
Vector quantization approaches to nonlinear stochastic estimation. Many problems in health, economics, telecommunications and industrial control can be formulated as estimation problems with uncertain data. This project is aimed at developing a novel class of algorithms aimed at high complexity estimation problems. If successful, the project will provide new approaches to these problems.
Joint modelling and recognition of linguistic and paralinguistic speech information. A new modelling framework will be developed exploiting interdependence between linguistic and paralinguistic cues to improve automatic recognition of emotion-related information. Applications in the high-tech industry include automatic routing of angry telephone customers or pre-suicidal crisis centre callers to specialist operators/clinicians.
Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet ....Automated Diagnosis of Faults in Rotating Machinery using Adaptive Network Based Fuzzy Inference. The long-term integrity of engineering assets depends on the quality of their maintenance which runs into billions of dollars per year in Australia. This project aims to develop a new fundamental automated technique for the detection and diagnosis of machinery faults. The innovation lies in the ability of this technique to not depend on knowledge of fault components in the discrete wavelet packet analysis. All other work conducted to date depends on knowledge of these components and their location. The results of this work will vastly improve the costly manually based diagnostics procedures in the maintenance of plant and industrial assets.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102210
Funder
Australian Research Council
Funding Amount
$350,333.00
Summary
Feedback control as a tool for enhanced neuroprosthetic stimulation. The aim is to use control theory tools to find optimal stimulation parameters to use in a bionic implant. This project will lead to improvements in understanding of mechanisms underlying electrical stimulation and to improvements in medical bionics technologies.
Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to ....Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to solve inverse problems is expected to advance technology toward lower power, lower cost solutions for MRI scanners in healthcare and industrial applications, including materials science and mineral processing.Read moreRead less
New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.Read moreRead less