学术报告第201847期-自动化学院

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学术报告第201847期

发布时间:2018-07-16 编辑:李增宇 来源:

报告题目:Applications of Computational Intelligence to Condition-Based Maintenance

报告人: Kay Chen Tan, 香港城市大学教授

报告时间:2018723日(周一)上午10:00-11:00

报告地点:南一楼中311

报告摘要:

Condition-based maintenance (CBM) is known as an important tool for running a plant or factory in an optimal manner. Although developments in recent years have allowed some types of equipment to be observed by measuring simple values such as temperature, pressure etc., it is often not trivial to turn this measured data into actionable knowledge about the health of the equipment. This talk will discuss various challenges to the use of CBM and present our recent work on applying data-driven based computational intelligence technologies to CBM without the need of relying on physical domain knowledge. Experimental results obtained from a few case studies, such as robust prognostic, tool condition monitoring and automated surface inspection, will also be analyzed and discussed.

报告人简介:

Kay Chen Tan is a full Professor with the Department of Computer Science, City University of Hong Kong, Hong Kong. He is the Editor-in-Chief of IEEE Transactions on Evolutionary Computation, was the EiC of IEEE Computational Intelligence Magazine (2010-2013), and currently serves on the Editorial Board member of 15+ international journals. He is an elected member of IEEE CIS AdCom (2017-2019) and was an IEEE Distinguished Lecturer (2015-2017). He has published 200+ refereed articles and 5+ books. He is a Fellow of IEEE.