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新西兰 奥克兰大学 Jaspreet S. Dhupia副教授 学术讲座

发布时间:2024-07-04 点击数:

讲座题目:Modelling, Control and Diagnostics to Improve Reliability of Energy Generation and Transfers

讲座时间:2024/7/8(星期一)15:00-16:30

讲座地点:创新港巨构2-2072会议室

讲座学者:Jaspreet S. Dhupia副教授

讲座人简介:

Jaspreet S. Dhupia is a Senior Lecturer in the Department of Mechanical and Mechatronics Engineering, The University of Auckland (UoA), New Zealand since July 2015. Prior to joining UoA, he was an academic staff member in the School of Mechanical and Aerospace Engineering in Nanyang Technological University, Singapore (2008-2015) and a Research Fellow at The University of Michigan, Ann Arbor, USA (2007-2008). He received his M.S. and PhD from The University of Michigan and B.Tech from Indian Institute of Technology, Delhi. He is Senior Member with IEEE, and served as a Technical Editor for the IEEE/ASME Transactions of Mechatronics, and an Associate Editor with the ASME’s Dynamic Systems and Control Division. He has worked with USA Food and Drug Administration, ABB, Roll-Royce and oDocs Eye Care on funded research projects. In 2015 and 2016, he was a visiting professor to the University of Michigan- Shanghai Jiao Tong University’s Joint Institute.

讲座简介:

Failures in gearboxes, bearing and motor/ generators are the common reasons for extended downtime of many energy generating systems,such as wind turbine. These failures, which also have potential to cause structural damage and catastrophic system failure, are often the most expensive. The detection of such failure is challenged due to changes in speed and load, high background noise and often limited measurement availability. This seminarwillcoverwork onhigh fidelity modeling of drivetrain systems, robust fault detection and diagnosis in presence of varying operating conditions, and control methods that not only maintain good system performance but also improve its reliability by reducing structural loads. Additionally, thisseminar will address leveraging interconnected device capabilities within the internet-of-things (IoT) framework and usingmachine learning techniques to provide robust maintenance support for such systems.

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