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Asoke K. Nandi PhD 教授学术报告
编辑:【机器人研究所】     加入时间:【2017-5-17】

Rotating machine condition classification using vibration signals

 

 

Professor Asoke K. Nandi PhD FREng FIEEE FIET FIMA FInstP FRSA FIMechE FBCS

Department of Electronic and Computer Engineering

Brunel University London, Uxbridge, UB8 3PH, United Kingdom

Personal website: http://www.brunel.ac.uk/people/asoke-k.-nandi

Email: asoke.nandi@brunel.ac.uk

 

 

Abstract: Rotating machines and ball bearings are very common. Accurate determinations of their current condition allow the possibility of taking corrective actions before failures, leading to severe loss of production or catastrophic accidents. Successful condition monitoring can reduce costs, increase productivity, and save lives. This seminar will bring together signal processing and machine learning to highlight our latest research. There will be discussions about feature extraction, feature selection, feature generation, classifiers, evolutionary computation, compressive sampling, and deep neural network, followed by classification of rolling element bearings.

 

Bio-Sketch: Professor Asoke K. Nandi received the degree of Ph.D. in Physics from the University of Cambridge (Trinity College), Cambridge (UK). He held academic positions in several universities, including Oxford (UK), Imperial College London (UK), Strathclyde (UK), and Liverpool (UK) as well as Finland Distinguished Professorship in Jyvaskyla (Finland). In 2013 he moved to Brunel University (UK), to become the Chair and Head of Electronic and Computer Engineering. Professor Nandi is a Distinguished Visiting Professor at Tongji University (China) and an Adjunct Professor at University of Calgary (Canada).

In 1983 Professor Nandi contributed to the discovery of the three fundamental particles known as W+, Wand Z0 (by the UA1 team at CERN), providing the evidence for the unification of the electromagnetic and weak forces, for which the Nobel Committee for Physics in 1984 awarded the prize to two of his team leaders for their decisive contributions. His current research interests lie in the areas of signal processing and machine learning, with applications to condition monitoring, communications, gene expression data, functional magnetic resonance data, and biomedical data. He has made many fundamental theoretical and algorithmic contributions to many aspects of signal processing and machine learning. He has much expertise in “Big Data”, dealing with heterogeneous data, and extracting information from multiple datasets obtained in different laboratories and different times. He has authored over 500 technical publications, including 200 journal papers as well as four books, entitled Automatic Modulation Classification: Principles, Algorithms and Applications (Wiley, 2015), Integrative Cluster Analysis in Bioinformatics (Wiley, 2015),Blind Estimation Using Higher-Order Statistics (Springer, 1999), and Automatic Modulation Recognition of Communications Signals (Springer, 1996). Recently he published in Blood, International Journal of Neural Systems, BMC Bioinformatics, IEEE TWC, NeuroImage, PLOS ONE, and Royal Society Interface. The h-index of his publications is 63 (Google Scholar) and ERDOS number is 2.

 

Professor Nandi is a Fellow of the Royal Academy of Engineering (UK) and also a Fellow of seven other institutions including the IEEE and the IET. Among the many awards he received are the Institute of Electrical and Electronics Engineers (USA) Heinrich Hertz Award in 2012, the Glory of Bengal Award for his outstanding achievements in scientific research in 2010, the Water Arbitration Prize of the Institution of Mechanical Engineers (UK) in 1999, and the Mountbatten Premium, Division Award of the Electronics and Communications Division, of the Institution of Electrical Engineers (UK) in 1998.

 

 

 

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