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Research Expertise and Interests

  • Machinery condition monitoring
  • Vibration analysis
  • Signal processing
  • Fault detection
  • Acoustics


Professor Andrew Ball is Pro Vice-Chancellor for Research and Enterprise and Professor of Diagnostic Engineering at the University of Huddersfield.

Graduating from the University of Leeds in 1987, Andrew attained a first class honours in Mechanical Engineering, his degree having been sponsored by BICC Electronic Cables. Andrew went on to work for Ruston Gas Turbines and then gained a sponsorship from WM Engineering and the Royal Navy, enabling him to join the Total Technology Scheme at the University of Manchester, from which he graduated in 1991 with a PhD in Machinery Condition Monitoring.

Andrew then took the Shell sponsored lectureship in Maintenance Engineering at the University of Manchester; he was promoted to Professor of Maintenance Engineering in 1999, and was the Head of School of the Manchester School of Engineering from 2003 to 2004. In 2005 he became Dean of Graduate Education and in late-2007 he moved to the University of Huddersfield as Professor of Diagnostic Engineering and Pro-Vice-Chancellor for Research and Enterprise.

Over the 25 years that he has been an academic, Andrew has established the largest independent plant maintenance and diagnostics research group in the world. The Centre for Efficiency and Performance Engineering aims to advance the scope and sensitivity of machinery fault detection and diagnosis and of plant performance and emissions monitoring. The philosophy is to use routine instrumentation where possible, to apply sophisticated signal processing, to develop non-intrusive on-line techniques and to focus upon incipient faults with the intention of predicting future behaviour. The group is recognised internationally for its specialism in:

  • Machinery condition monitoring, fault detection and diagnosis
  • Signal processing, feature extraction and pattern recognition
  • Vibro-acoustic and vibro-impact analysis
  • Model based and predictive methods
  • Sensor development & novel measurement
  • Non-intrusive parameter estimation

Andrew’s personal research expertise is in the detection and diagnosis of faults in mechanical, electrical and electro-hydraulic machines, in data analysis and signal processing, and in measurement systems and sensor development. He is the author of over 300 technical and professional publications, and he has spent a large amount of time lecturing and consulting to industry in all parts of the world.

Andrew has to date graduated more than 60 research degrees, in the fields of Mechanical, Electrical and Diagnostic Engineering. He has acted as external examiner at over 30 institutions, he holds visiting and honorary positions at 4 overseas universities, he sits on 3 large corporate scientific advisory boards, and he is also a Registered Expert Witness in 3 countries.


  • Machinery condition monitoring
  • Vibration analysis
  • Signal Processing
  • Fault Detection
  • Fault Diagnosis
  • Acoustics

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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2011 2021

Research Output 2000 2018

2 Citations
Bearings (structural)
Condition monitoring
Fault detection
Frequency bands

A Sparse Modulation Signal Bispectrum Analysis Method for Rolling Element Bearing Diagnosis

Wang, G., Gu, F., Rehab, I., Ball, A. & Li, L. 19 Apr 2018 In : Mathematical Problems in Engineering. 2018, 12 p., 2954094

Research output: Contribution to journalArticle

Open Access
Bearings (structural)
Signal analysis
fault detection
acoustic emission
Condition monitoring
Acoustic emissions
Fault detection

A comparative study of gravitational acceleration cancellation from on-rotor MEMS accelerometers for condition monitoring

Mones, Z., Feng, G., Tang, X., Haba, U., Gu, F. & Ball, A. 2017 Proceedings of the 24th International Congress on Sound and Vibration, ICSV 2017. Gibbs, B. (ed.). International Institute of Acoustics and Vibration, IIAV

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
rotor dynamics

A Dynamic Deformation based Lubrication Model between the Piston Rings and Cylinder Liner

Li, G., Gu, F., Wang, T., Lu, X., Zhang, R. & Ball, A. 26 Oct 2017 Proceedings of the 23rd International Conference on Automation & Computing (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
Piston rings
Engine cylinders
Shear stress

Activities 2004 2019

International Conditioning Monitoring and Diagnostic Engineering Management Conference 2019

Ball, A. (Chair)
2019 → …

Activity: Participating in a conference, workshop, ...

Research Journal of Applied Sciences (Journal)

Ball, A. (Member of editorial board)
2016 → …

Activity: Editorial work

A Robust Fault Detection Method of Rolling Bearings Using Modulation Signal Bispectrum Analysis

Gu, F. (Contributor to Paper or Presentation), Ball, A. (Contributor to Paper or Presentation), Xiange Tian (Speaker), Ibrahim.A.M Rehab (Speaker), Gaballa Abdalla (Speaker)
1 Dec 2015

Activity: Oral presentation

John Crane PLC (External organisation)

Ball, A. (Member)
2014 → …

Activity: Membership of board