Centre for Efficiency and Performance Engineering

  • United Kingdom

Organization profile

Profile Information

The Centre for Efficiency and Performance Engineering (CEPE) aims to scope and sensitivity of machinery fault detection and diagnosis and of plant performance and emissions monitoring. Headed by Professor Andrew Ball, the CEPE at the University of Huddersfield is the largest independent group of its type in the world. Its mission is to tackle real-world problems using the most practical and accessible means possible. 

The Centre specialises in vibro-acoustics, vibro impacts, instantaneous angular speed and instantaneous electric current analysis, dagnostic model development, signal processing, feature extraction, pattern recognition, sensor development, non-intrusive parameter estimation and model based fault diagnosis. Internationally recognised as one of the world's leading research organisations in the field of plant condition and performance monitoring, our researchers have been developing capabilities for various machines since 1991.

Fingerprint The fingerprint is based on mining the text of the scientific documents related to the associated persons. Based on that an index of weighted terms is created, which defines the key subjects of research unit

Bearings (structural) Engineering & Materials Science
Condition monitoring Engineering & Materials Science
Failure analysis Engineering & Materials Science
Fault detection Engineering & Materials Science
Signal analysis Engineering & Materials Science
Reciprocating compressors Engineering & Materials Science
Modulation Engineering & Materials Science
Monitoring Engineering & Materials Science

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Research Output 2008 2019

An Approach to Reducing Input Parameter Volume for Fault Classifiers

Smith, A., Gu, F. & Ball, A., Apr 2019, In : International Journal of Automation and Computing. 16, 2, p. 199-212 14 p.

Research output: Contribution to journalArticle

Open Access
Fault
Classifiers
Classifier
Naive Bayes Classifier
Harmonic

An Introduction of a Robust OMA Method: CoS-SSI and Its Performance Evaluation through the Simulation and a Case Study

Liu, F., Wu, J., Gu, F. & Ball, A. D., 31 Jan 2019, In : Shock and Vibration. 2019, p. 1-14 14 p., 6581516.

Research output: Contribution to journalArticle

Open Access
Correlation methods
Modal analysis
set theory
evaluation
Structural health monitoring

An Investigation into the Acoustic Emissions of Internal Combustion Engines with Modelling and Wavelet Package Analysis for Monitoring Lubrication Conditions

Wei, N., Gu, J. X., Gu, F., Chen, Z., Li, G. & Ball, A., 16 Feb 2019, In : Energies. 12, 4, 19 p., 640.

Research output: Contribution to journalArticle

Open Access
Internal Combustion Engine
Acoustic Emission
Lubrication
Acoustic emissions
Internal combustion engines

Projects 2015 2021