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7月23 日学术报告(千人计划 Kay Chen Tan, City University of Hong Kong, Fellow of IEEE)
2018年07月20日14时 人评论

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

报告时间:  2018723日(周一)下午3:00

报告地点:  计算机学院E202

报告人:    Kay Chen Tan

报告人单位:City University of Hong Kong

 

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 and tool condition monitoring 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 10+ 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.

 

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