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学术报告预告:2016.6.20宾夕法尼亚州立大学杨徽博士
发布者:实验室管理员 日期:2016-06-20

    学术报告预告:2016.6.20宾夕法尼亚州立大学杨徽博士

  • 讲座题目:Mining Dynamic Recurrences in Nonlinear and Nonstationary Systems for Feature Extraction, Process Monitoring and Fault Diagnosis

    主讲人:杨徽(博士,博士生导师,宾夕法尼亚州立大学)

    时 间:2016 年6月20日10:00

    地 点:机械传动国家重点实验室219会议室

    内容简介:

    Nonlinear dynamics arise whenever multifarious entities of a system cooperate, compete, or interfere. Effective monitoring and control of nonlinear dynamics will increase system quality and integrity, thereby leading to significant economic and societal impacts. In order to cope with system complexity and increase information visibility, modern industries are investing in a variety of sensor networks and dedicated data centers. Real-time sensing gives rise to “big data”. Realizing the full potential of “big data” for advanced quality control requires fundamentally new methodologies to harness and exploit complexity. This talk will present novel nonlinear methodologies that mine dynamic recurrences from in-process big data for real-time system informatics, monitoring, and control. Recurrence (i.e., approximate repetitions of a certain event) is one of the most common phenomena in natural and engineering systems. For examples, the human heart is near-periodically beating to maintain vital living organs. Stamping machines are cyclically forming sheet metals during production. Process monitoring of dynamic transitions in complex systems (e.g., disease conditions or manufacturing quality) is more concerned about aperiodic recurrences and heterogeneous recurrence variations. However, little has been done to investigate heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. This talk will present the state of art in nonlinear recurrence analysis and a new heterogeneous recurrence methodology for monitoring and control of nonlinear stochastic processes. Specifically, the developed methodologies will be demonstrated in both manufacturing and healthcare applications. The proposed methodology is generally applicable to a variety of complex systems exhibiting nonlinear dynamics, e.g., precision machining, sleep apnea, aging study, nanomanufacturing, biomanufacturing. In the end, future research directions will be discussed.

    报告人简介:

    杨徽,博士,博士生导师,副教授,Department of Industrial and Manufacturing Engineering, The Pennsylvania State University。杨徽博士在2015年被评为美国自然基金会杰出青年科学家(NSF CAREER Award),现担任INFORMS质量统计和可靠性学会主席,INFORMS数据挖掘学会,和IIE计算机与信息系统学会理事会成员,2014界INFORMS年会人工智能分会主席,2014界IIE年会计算机与信息系统分会主席,2015界IIE年会过程控制分会主席。杨徽博士现为Springer信息系统和电子商务杂志和IEEE智能系统杂志特约编委,多家学术杂志论文评审人,美国国家自然科学基金项目评审人。承担美国国家自然科学基金研究项目5项(累计达两百万美元),大学自主科研基金研究项目两项,申请发明专利2项,发表学术杂志论文50多篇,专著章节3篇,和通用汽车研发中心技术报告2篇。杨徽博士指导的博士生多次在国际学术会议获奖,4次荣获国际IIE年会最佳论文奖(2009,2010, 2014 和 2015),1次荣获IEEE国际生物医学工程年会IBM最佳论文奖(2011)。

    主办单位:重庆大学机械传动国家重点实验室

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