• Data-driven modeling and control for mineral preparation processes
    編號:497 訪問權限:僅限參會人 更新:2022-05-20 15:27:11 瀏覽:431次 特邀報告

    報告開始:2022年05月27日 09:10 (Asia/Shanghai)

    報告時間:20min

    所在會議:[S5] Intelligent Equipment and Technology [S5-2] Intelligent Equipment and Technology-2

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    摘要
    The deep integration of new generation information technology and manufacturing is triggering far-reaching industry transformation. Coal separation, as an important part of the clean utilization of coal resources, is gradually moving from automation and informatization to intelligence, to comply with national “dual-carbon” development strategic plan. However, in the actual production, it is often faced with the problems, such as difficult detection of operation indices in the product quality and output, time-varying working conditions, unclear mechanism, difficult design of control methods, complex control structures and difficult verification of control systems, which pose new challenges for intelligent coal separation. This report focuses on the actual demand for intelligent coal separation, takes the heavy medium separation process as the background, combines data and knowledge, integrates intelligent behaviour and intelligent methods, modelling and control, and introduces them into the intelligent coal separation process. Additionally, the intelligent modelling method of coal separation process, the operation optimization structure and design methods, and the hardware-in-the-loop experimental research platform are introduced, and the opportunities and challenges brought by the next industrial Internet are discussed.
     
    關鍵字
    industry transformation;coal separation;heavy medium separation
    報告人
    Wei DAI
    Dr China University of Mining and Technology

    Wei Dai is currently working as a Professor in the School of Information and Control Engineering, China University of Mining and Technology (CUMT), China. His research focuses on industrial big data analytics, machine learning, data mining and knowledge discovery from complex industrial processes. Dr. Dai is serving as an Associate Editor of Industrial Artificial Intelligence (Springer), Editorial board member of Journal of China University of Mining & Technology, Editorial board member of Journal of Mine Automation, he is an IEEE Senior Member and Technical Committee member of Big Data (CAA). Dr. Dai won the Second Prize of Natural Science Award of the Ministry of Education of China in 2020, the First Prize of Natural Science Award of Chinese Association of Automation in 2021, and the Third Prize of Science and Technology Award of Jiangsu Province in 2019. He also received the Best Paper Award of IEEE International Conference on Real-time Computing and Robotics in 2020. He was a recipient of the Top Young Talents Award of the National Ten Thousand Talents Plan of China in 2021.
     

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