International network of efficiency and performance engineering researchers

International network of efficiency and performance engineering researchers | School of Computing and Engineering

The University of Huddersfield’s International Collaborative Fund (ICF) allowed Professors Andrew Ball and Fengshou Gu to develop, sustain and extend The Efficiency and Performance Engineering Network (TEPEN), which brings together institutions worldwide to collaborate on research, and has resulted in numerous international papers being published.

The Project

TEPEN was established in 2017 as an international network of world leading researchers in the field of efficiency and performance engineering. Its mission, to facilitate collaborative research across the globe and influence innovation in efficiency and performance engineering.

Since it was founded, TEPEN now comprises over 50 institutions and over 500 individual researchers. Each year it hosts an annual conference and steering meeting, the latest being held at the University of Huddersfield in August 2023 with over 150 international papers presented and over 200 attendees.

TEPEN also has its own open access international journal, The Journal of Dynamics, Monitoring and Diagnostics, JDMD, that was first released in March 2022 and is edited by Prof Andrew Ball and Fulei Chu (Tsinghua).

Partner Institutions

• Tsinghua University
• Shanghai Jiaotong University
• Zhejiang University
• University of Pretoria
• City University Hong Kong
• Indian Institute of Technology Ropar
• University of Malaya
• Further 50+ worldwide institutions

International Partnerships

TEPEN includes the majority of researchers and institutions from around the world working in the fields of machinery condition monitoring, sensor systems and dynamic modelling. Fourteen of the remaining institutions who work in this field will join the network in the next year.

A key benefit to TEPEN membership is having access to other members’ research facilities and data sets.  The 14 additional members will significantly increase the range and scope of collaborative research facilities at members’ disposal.

Over the years, TEPEN has also driven overseas recruitment with over 20 registered full-time and part-time post-graduates at the University of Huddersfield, as a direct consequence of TEPEN activities. More than 15 of these post-graduate students are now undertaking their studies at the extensive CEPE / TEPEN Laboratory at Beijing Institute of Technology in Zhuhai.

Projects that have come out of TEPEN, include:

• Wind turbine health management with remote visions and physics-informed deep learning technologies.
• Machine Learning Based Condition Monitoring for Industrial Collaborative Robots.
• Online Condition Monitoring and Health Management of Batteries

based on Digital Twin (DT) Technologies.

• Characterising Acoustic Emission of Additive Manufacturing for Online Quality Control.

More information about TEPEN can be found here.

TEPEN is the largest independent plant maintenance and diagnostics research group in the world. Collectively, we aim to develop and nurture those within the network to advance the scope and sensitivity of machinery fault detection, diagnosis and emissions monitoring, and improve plant performance. Our goal is to be the world’s most comprehensive and influential body in this subject area.

Professor Andrew Ball, University of Huddersfield.

About the Researchers

Prof Andrew Ball is Pro Vice-Chancellor (Research Innovation and Knowledge Exchange) and Prof of Diagnostic Engineering at the University of Huddersfield. He specialises in the detection and diagnosis of faults in mechanical, electrical and electro-hydraulic machines, in data analysis and signal processing. He acts as external examiner at over 30 institutions, holds visiting and honorary positions at six overseas universities and sits on three large corporate scientific advisory boards. He is also author of over 400 technical and professional publications.

Find out more about Prof Andrew Ball.

Prof Fengshou Gu is Professor Emeritus in the Department of Engineering at the University of Huddersfield. He has over 30 years’ research experience in vibro-acoustics analysis and machinery diagnosis. He is the author of over 500 technical and professional publications in machine dynamics, signal processing, tribology dynamic responses, condition monitoring and related fields.

Find out more about Prof Fengshou Gu.