Activities
2022年1月28日，中國自動化學(xué)會首期“我和優(yōu)博有個(gè)約會”活動正式啟動。加拿大阿爾伯塔大學(xué)陳宏田博士做客活動，為大家?guī)砭史窒怼?
陳宏田博士首先介紹了自己所在團(tuán)隊(duì)的研究方向，即“數(shù)據(jù)驅(qū)動高速列車牽引系統(tǒng)故障診斷”。從研究背景、理論角度下和應(yīng)用角度下這項(xiàng)研究的內(nèi)容及創(chuàng)新點(diǎn)、相關(guān)成果以及獲得的獎(jiǎng)勵(lì)進(jìn)行了分享。隨后，陳博士通過自己的科研歷程闡述了在“科研創(chuàng)新”方面的一些心得，強(qiáng)調(diào)理論和應(yīng)用的結(jié)合。在科研創(chuàng)新中要從實(shí)際工程問題出發(fā)，提煉成理論問題，最后采用數(shù)學(xué)工具去解決。在這個(gè)過程中需要有強(qiáng)大的知識儲備和思維能力，高瞻遠(yuǎn)矚、勤于思考、一步一個(gè)腳印，通過80%的勤奮+20%的選擇，最終才能得到想要的成果。參與本期活動的聽眾非常活躍，圍繞“自身科研歷程中的具體問題”、“瓶頸期如何客服”“未來研究方向”等方面進(jìn)行了提問，陳博士結(jié)合自身經(jīng)歷一一作答。
本次“我和優(yōu)博有個(gè)約會”活動在中國自動化學(xué)會官方視頻號、釘釘群同步直播，總觀看量超過千余人次，討論量近百條。
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【報(bào)告人】陳宏田，現(xiàn)為加拿大阿爾伯塔大學(xué)博后，IEEE會員,中國自動化學(xué)會會員，江蘇青工委會員，中國人工智能學(xué)會會員及其智能檢測與運(yùn)動控制委員會委員。本碩畢業(yè)于南師大，博士畢業(yè)于南京航空航天大學(xué)。2018年在德國先進(jìn)控制與復(fù)雜系統(tǒng)研究所做訪問學(xué)者。主要研究方向?yàn)閿?shù)據(jù)驅(qū)動技術(shù)、人工智能、量子計(jì)算、分布式系統(tǒng)等及其在高速列車牽引系統(tǒng)的故障診斷應(yīng)用。
【報(bào)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.
