Prof Ning Hu, Hebei University of Technology, China
Recent Progress in Damage Inspection Techniques Based on Linear and Nonlinear Lamb Waves
Professor Ning Hu finished his education from undergraduate to PhD in Chongqing University, China from 1981-1991. After graduation, he has been working at Nanjing University of Aeronautics and Astronautics (China), Tohoku University (Japan), Tsinghua University (China), The Johns Hopkins University (USA), Chiba University (Japan), Hunan University (China) and Chongqing University (China) as Post-doctoral researcher, Assistant Professor, Associate Professor and Full Professor. Before his back to China in 2013, he was a Full Professor, the Chairman of Department of Mechanical Engineering, and the Head of Division of Artificial System Science, Chiba University (Japan). From the end of 2013, he founded College of Aerospace Engineering in Chongqing University (China) and worked as the first Dean. From April, 2019, he started his work as a Vice-President of Hebei University of Technology (China).
His main research interests include: solids mechanics, functional and structural nanocomposites and conventional fiber reinforced composites, analysis and design of metal and composite structures, computational materials science (e.g., multi-scale simulations), on-line structural health monitoring and off-line non-destructive evaluation techniques, sensing/energy harvesting techniques, etc. To date, in the above fields, he has published 3 books in English, 1 textbook in Chinese, and generated around 470 peer-reviewed journal articles in Chinese, English and Japanese (including 360 SCI English journal papers). These articles have been cited over 10000 times with H-Index=50. Also, he has obtained over 20 Japanese and Chinese patents. He is now working as Associate Editor and an Editorial Board Member of 13 academic journals including 11 international academic journals.
He has also received some important awards, e.g., “Outstanding Young Scholar from NSF (Type B), China, 2007”, “National Distinguished Experts (Thousand Talents Plan ), China, 2013”, etc. He was also selected by Elsevier as one of “The Most Highly Cited Chinese Researcher” from 2014 to 2020 in the field of mechanics of materials and mechanical engineering. He was also continuously selected as World’s Top 2% Scientists (Career Scientific Impact and Single year Scientific Impact) from 2019-2020.
Prof Yuchun Xu, Aston University, United Kingdom
Towards Smart Remanufacture and Asset Management Using Multi-Disciplinary Technologies
Professor Yuchun Xu is a Chair of Manufacturing in the College of Engineering and Physical Sciences at Aston University. He’s the leader of two interdisciplinary research themes at Aston University, namely Digital Engineering, and Circular Economy.
He studied in Harbin Institute of Technology during 1989 – 1999 receiving his BEng in Automotive Engineering and PhD in Manufacturing degrees in 1993 and 1999, respectively. He then did his postdoctoral research in Tianjin University for two years and worked in IT industry for a year in Shanghai before he moved to UK in 2002. He worked in Cardiff University, Queens University Belfast and Cranfield University, respectively, before he joined Aston University in 2017.
Prof Xu’s research is primarily on smart manufacturing, life cycle engineering, cost modelling, and decision making. He has close collaboration with industry, his industrial partners include High Value Manufacturing Catapult, Airbus, Rolls-Royce, QinetiQ and Network Rail etc. Prof Xu’s research is sponsored by UK Engineering and Physical Science Research Council (EPSRC), Innovate UK, Department for Education, and EU H2020, FP7 etc. with total funding profile over £25M.
Professor Xu has published about 70 research papers mainly in leading peer reviewed international journals and conferences. He is the member of UK EPSRC & STFC Peer Review College and received recognition of his significant contribution in that role. He’s the editorial board member of Chinese Journal of Mechanical Engineering, and regularly serves as the technical and programme committee member and sessions chair of leading international conferences. Prof. Xu has international collaboration with leading universities worldwide mainly through international collaboration funding schemes such as EU Marie Skłodowska-Curie Actions Innovative Training Networks (MSCA ITN) scheme and ERASMUS+ scheme, but also through his external examiner’s roles such as in Tunku Abdul Rahman University College, Malaysia and Xi’an Jiaotong-Liverpool University (XJTLU) etc.
Dr Changming Cheng, Shanghai Jiao Tong University, China
Variable selection in nonlinear non-parametric system Identification
Dr Changming Cheng is currently an associate professor in the State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, doctoral supervisor, the winner of Pujiang Talent Program. His research interests include system identification, machine learning, signal processing, mechanical vibration, machine health diagnosis and prognostics.
He developed a theoretical framework of the parameterized and nonparametric system identification, and based on the framework, proposed a variety of system identification methods, which can effectively reduce the effect of the curse of dimensionality in nonlinear system identification and improve the accuracy of system identification. He also developed a variety of machine learning and signal processing methods, and successfully applied them to the characterization and feature extraction of the rotor rubbing, gear fault, rolling bearing fault and other mechanical faults.
He has published more than 20 SCI papers on the internationally famous Journals in the system identification and signal processing communities, such as IEEE Transactions on Automatic Control, Automatica, Mechanical Systems and Signal Processing，International Journal of Nonlinear Mechanics，IEEE Transactions on Instrumentation and Measurement, Nonlinear Dynamics. He won the Best Paper Award of the 6th International Conference on Control Dynamic Systems, and Robotics. His work has been in part supported by the National Natural Science Foundation of China projects with the reference numbers of 12072188, 11702171, and in part supported by Natural Science Foundation of Shanghai, and in part supported by Shanghai Pujiang Program, and in part supported by the Key project of State Key Laboratory of Ministry of Science and Technology.
Dr Xiaoxi Ding, Chongqing University, China
Convolutional Sparse Self-learning for Monitoring Rotating Machinery under Varying Operating Conditions
Dr Xiaoxi Ding is an assistant professor of mechanical design and theory, Chongqing University and the director of the Key Laboratory of Intelligence and System. He received B.S. and PhD degree in mechanical engineering from the University of Science and Technology of China, Hefei, China, in 2012 and 2017, respectively. He served as a Post-Doctoral Research Associate with the State Key Laboratory of Mechanical Transmission, Chongqing University, China, in 2020.
His current research interests include signal processing, data mining, and intelligent monitoring system for health monitoring and fault diagnosis in machines. His research accomplishments are mainly in five subjects: transient structure extraction with time-frequency manifold sparse theory; periodic feature enhancement with convolution shift invariant modal learning; robust condition representation under complex operating conditions with dynamic interpolation ConvNet architecture; big data monitoring system platform; Edge intelligence technology for smart bearings.
He has Published 26 SCI/EI papers as the first author/corresponding author), including 16 SCI papers including IEEE TII, MSSP, IEEE TIM, SMS, JSV and etc. , 1 ESI paper with 1% high citation rate. Up to now, the total citation is nearly 500 times, with the highest citation of a single paper exceeding 200 times.
Dr Wolfgang Hahn, GN power, Philippines
Optimising maintenance in a flexible power market
Dr Wolfgang Hahn has been working in the power generation industry UK for over 20 years. His experience covers operations, commissioning, maintenance, projects and asset management with most of the last 10 years dedicated to engineering safety cases, business risk and technical asset management. Currently he works for GN power in the Philippines in the technical services department.
His collaboration involves a number of areas internal and external to the power industry, interacting on a professional level with a number of institutes, professional bodies and universities to progress best practice and promote benchmarking in the power industry. He was chair of the generator safety and integrity programme (GENSIP), member of the IMECHE safety and reliability team and worked with ASME & the P65 programme in EPRI. His experience in operations, maintenance and engineering ensures that plant operations, maintenance and the overall asset management programme for each power plant is optimised from a people, plant and processes. He engages in the UK government sponsored R&D programmes on a regular basis to research new approaches to power plant problems & challenges using innovation.
He is also under part time teaching by lecturing and supervising students at University of Manchester. He has published various conference and journal papers in ASME, EPRI, Vetomac and Maintec.
Prof Lingli Cui, Beijing University of Technology, China
Quantitative and intelligent diagnosis of mechanical equipment
Dr WProf. Lingli Cui has managed four projects of the National Natural Science Foundation of China, as principal investigator. Three projects are excellent, and one is “Ten Excellent project”. She received award of the Youth Beijing Scholar in 2020, Beijing “Great Wall Scholar” in 2018, Beijing Million Talent Project in 2018 and so on. She has published more than 60 publications, including 21 patents, 1 book and 40 journal papers, which are included by SCI.
As first finisher, she also received the second award of Natural Science Award of Ministry of education in 2019, the second award of Natural Science Award of Beijing in 2020, and the second award of Science and Technology of China Society of Vibration Engineering in 2020, the Mao Yisheng Beijing Youth Science and Technology Award in 2018, and the Youth Science and Technology award of China Society of Vibration Engineering in 2018.