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2026 ARDC Annual Survey is now open!

The Australian Research Data Commons (ARDC) invites you to participate in a short survey about your interaction with the ARDC and use of our national research infrastructure and services. The survey will take approximately 5 minutes and is anonymous. It’s open to anyone who uses our digital research infrastructure services including Reasearch Link Australia.

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  • Funded Activity

    Linkage - International - Grant ID: LX0212065

    Funder
    Australian Research Council
    Funding Amount
    $63,191.00
    Summary
    Development of an Automated Control System for Selection of Optimal Process Parameters in Welding Using Solar Energy Concentration. The objective of this proposed research is to develop an intelligent control system for selection of optimal process parameters in welding using solar energy concentration. This investigation endeavours to address the complex interaction between welding process parameters and quality of weld. The results of the work will lead to signicant advancement of knowledge .... Development of an Automated Control System for Selection of Optimal Process Parameters in Welding Using Solar Energy Concentration. The objective of this proposed research is to develop an intelligent control system for selection of optimal process parameters in welding using solar energy concentration. This investigation endeavours to address the complex interaction between welding process parameters and quality of weld. The results of the work will lead to signicant advancement of knowledge in automation of the welding process and will generate global interest due to its innovation and applications in automotive manufacturing and steel fabrication industries. The research activity proposed in this application is expected to further strengthen the links between QUT and Mokpo National University and will enhance the capabilities of both universities in attracting funding from local manufacturing industries.
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    Funded Activity

    Linkage - International - Grant ID: LX0346793

    Funder
    Australian Research Council
    Funding Amount
    $74,711.00
    Summary
    Studies on the Weld Characterstics and Weldability of Welded Joints with Alternate Supply of Shileding Gases in Welding. In today's dynamic changing environment, for industries to remain internationally competitive, traditional manufacturing techniques used for welding have to become more flexible and intelligent to attain better adaptability and higher productivity. In industrial applications of MIG/MAG welding processes, various types of shielding gases are used based on type of work material .... Studies on the Weld Characterstics and Weldability of Welded Joints with Alternate Supply of Shileding Gases in Welding. In today's dynamic changing environment, for industries to remain internationally competitive, traditional manufacturing techniques used for welding have to become more flexible and intelligent to attain better adaptability and higher productivity. In industrial applications of MIG/MAG welding processes, various types of shielding gases are used based on type of work material and weld quality required. In this proposed research, experimental studies will be conducted on welding productivity by using different shielding gas combinations. The aim of this project is to conduct experimental analysis on weld arc phenomenon, weld pool behavior, and weld quality and to build an intelligent system for the selection of optimum combination shielding gas mixtures. In addition this study also aims to examine how the microstructure and mechanical properties of different welds are influenced by the use of different shielding gases combinations.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211387

    Funder
    Australian Research Council
    Funding Amount
    $222,932.00
    Summary
    Smart CMOS Vision Sensors in Deep Sub-0.25um CMOS Technologies. This research project aims to develop a new generation of smart vision sensors featuring on-chip and pixel-level implementation of human vision based algorithms. Built in state-of-the-art deep sub-0.25um CMOS technologies, these imagers will feature extensive in-pixel processing power in contrast to the currently commercially available CMOS vision sensors. This will enable on-chip vision-based decision making but also increased on-c .... Smart CMOS Vision Sensors in Deep Sub-0.25um CMOS Technologies. This research project aims to develop a new generation of smart vision sensors featuring on-chip and pixel-level implementation of human vision based algorithms. Built in state-of-the-art deep sub-0.25um CMOS technologies, these imagers will feature extensive in-pixel processing power in contrast to the currently commercially available CMOS vision sensors. This will enable on-chip vision-based decision making but also increased on-chip image processing. These innovative system-on-chip features will contribute towards the positioning of CMOS imaging technology as the technology of choice for most digital imaging applications, in place of the existing, and so far unchallenged, CCD technology.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211809

    Funder
    Australian Research Council
    Funding Amount
    $142,000.00
    Summary
    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.
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