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Research Seminar:A Robust detector for Bearing Condition Monitoring and Fault diagnosis

Translator: International Office Editor: release date :2017-03-15
Research Seminar


Date and Time: March,17, 2017,Friday,9:00am-11:00am
Venue::Eastern Campus  Teaching Building  7D-101

Topic One:A Robust detector for Bearing Condition Monitoring and Fault diagnosis
Experts Biography:

Andrew Ball is Professor of Diagnostics Engineering at the University of Huddersfield. He is the head of the University’s Centre for Efficiency and Performance Engineering, created at the University of Manchester, which is the largest independent diagnosis research and development organisation in the world. In addition, he has held positions

Jan 1991 – June 1999 – Lecturer in Maintenance Engineering, University of Manchester
July 1999 to date – Professor of Diagnostics and Maintenance Engineering, University of Manchester
Sept 2003 to Feb 2004 – Head of School, Manchester School of Engineering, University of Manchester
Feb 2004 – Sept 2007 - Graduate Dean, Faculty of Science and Engineering, University of Manchester
Sept 2007 to date Pro-Vice-Chancellor (Research and Enterprise) at University of Huddersfield

Professor Ball is one of the UK’s foremost experts in the fields of machinery diagnostics, dynamic modelling, intelligent computation and vibro-acoustics analysis, with over 30 years of maintenance engineering experience. He is the author of over 300 technical and professional publications in machine diagnosis, non-destructive measurement and related fields, and he spends much of his time lecturing and consulting to industry in all parts of the world. He has been the organizer of several international conferences in condition monitoring and maintenance. He has performed consultancy work for numerous companies, in over 30 countries and across 5 continents. In addition, he acts as an expert witness in court cases and litigations involving machine and structural deterioration or failure

Topic Two:Gear Condition Monitoring and Fault Diagnosis Based on Demodulation Analysis
Experts Biography:

Dr Fengshou Gu is currently working as the Principle Research Fellow and the Head of Measurement and Data Analysis Research Group (MDARG) at the Centre for Efficiency and Performance Engineering (CEPE), the University of Huddersfield. He has been worked in the field of machine monitoring and diagnostic for more than 30 years in developing an advanced diagnostic laboratory and numerical simulation methods which have facilities to simulate various faults for majority machines. He is supervising over 40 PhD students and undertaking more than 5 contracts funded from UK and Chinese government and industries.

Jan 1985 – June 1991 – Lecturer in Vibration and Acoustics, Taiyuan University of Technology, China
July 1991 – Oct 1996– Research Engineer at University of Manchester, U.K
Nov 1996 – Sept. 2007 Senior Research Engineer at University of Manchester, U.K
Sept. 2007 - to date Principle Research Fellow, Head of MDARG at University of Huddersfield, U.K.

Fengshou Gu is one of experts in the fields of machinery performance diagnostics/prognostics over 20 years of research experience. To improve operational efficiency and reliability of different machines, he has worked in multiple disciplines including electrical, mechanical and thermal dynamics, vibration, acoustics and tribology for modelling, advanced measurements, signal processing and information optimization. He is the author of over 200 technical and professional publications in machinery diagnosis, signal processing, measurement system and related fields. He has undertaken vibro-acoustic research projects of turbine machines, electric motors, internal combustion engines, reciprocating compressors, centrifugal pumps, hydraulic power systems, gearboxes and bearings. He has experienced in system modeling, various physical parameter measurements, advanced signal processing techniques including time-frequency analysis, wavelet transforms, adaptive signal decompositions, neural network algorithms and statistical analysis. Recent research interests are mainly focusing on power supply data based system diagnostics and performance monitoring, and tribological behavior of engines running with alternative fuels.