首期我和优博有个约会活动成功举办

日期:2022-01-28 10:43

2022年1月28日,中国自动化学会首期“我和优博有个约会”活动正式启动。加拿大阿尔伯塔大学陈宏田博士做客活动,为大家带来精彩分享。

陈宏田博士首先介绍了自己所在团队的研究方向,即“数据驱动高速列车牵引系统故障诊断”。从研究背景、理论角度下和应用角度下这项研究的内容及创新点、相关成果以及获得的奖励进行了分享。随后,陈博士通过自己的科研历程阐述了在“科研创新”方面的一些心得,强调理论和应用的结合。在科研创新中要从实际工程问题出发,提炼成理论问题,最后采用数学工具去解决。在这个过程中需要有强大的知识储备和思维能力,高瞻远瞩、勤于思考、一步一个脚印,通过80%的勤奋+20%的选择,最终才能得到想要的成果。参与本期活动的听众非常活跃,围绕“自身科研历程中的具体问题”、“瓶颈期如何客服”“未来研究方向”等方面进行了提问,陈博士结合自身经历一一作答。

本次“我和优博有个约会”活动在中国自动化学会官方视频号、钉钉群同步直播,总观看量超过千余人次,讨论量近百条。


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https://www.bilibili.com/video/BV1YS4y1V7mp/


【报告人】陈宏田,现为加拿大阿尔伯塔大学博后,IEEE会员,中国自动化学会会员,江苏青工委会员,中国人工智能学会会员及其智能检测与运动控制委员会委员。本硕毕业于南师大,博士毕业于南京航空航天大学。2018年在德国先进控制与复杂系统研究所做访问学者。主要研究方向为数据驱动技术、人工智能、量子计算、分布式系统等及其在高速列车牵引系统的故障诊断应用。


【报告摘要】Recently, to ensure the reliability and safety of high-speed trains, detection and diagnosis of faults (FDD) in traction systems have become an active issue in the transportation area over the past two decades. Among these FDD methods, data-driven designs, that can be directly implemented without a logical or mathematical description of traction systems, have been receiving special attention because of their overwhelming advantages. Based on the existing data-driven FDD methods for traction systems in high-speed trains, the first objective of this paper is to systematically recall and categorize most of the mainstream methods. By analyzing the characteristic of observations from sensors equipped in traction systems, great challenges which may prevent successful FDD implementations on practical high-speed trains are then summarized in detail. Benefiting from theoretical developments of data-driven FDD strategies, instructive perspectives on this topic are further elaborately conceived by the integration of model-based FDD issues, system identification techniques, and new machine learning tools, which provide several promising solutions to FDD strategies for traction systems in high-speed trains.