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An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches.

Angelov, Plamen and Giglio, V and Guardiola, C and Lughofer, Edwin and Lujan, J M (2006) An Approach to Model-based Fault Detection in Industrial Measurement Systems with Application to Engine Test Benches. Measurement Science and Technology, 17 (7). pp. 1809-1818. ISSN 1361-6501

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Abstract

An approach to fault detection (FD) in industrial measurement systems is proposed in this paper which includes an identification strategy for early detection of the appearance of a fault. This approach is model based, i.e. nominal models are used which represent the fault-free state of the on-line measured process. This approach is also suitable for off-line FD. The framework that combines FD with isolation and correction (FDIC) is outlined in this paper. The proposed approach is characterized by automatic threshold determination, ability to analyse local properties of the models, and aggregation of different fault detection statements. The nominal models are built using data-driven and hybrid approaches, combining first principle models with on-line data-driven techniques. At the same time the models are transparent and interpretable. This novel approach is then verified on a number of real and simulated data sets of car engine test benches (both gasoline—Alfa Romeo JTS, and diesel—Caterpillar). It is demonstrated that the approach can work effectively in real industrial measurement systems with data of large dimensions in both on-line and off-line modes.

Item Type: Article
Journal or Publication Title: Measurement Science and Technology
Uncontrolled Keywords: measurement systems ; model-based failure detection ; data-driven and hybrid modelling ; data quality ; combustion engines ; engine test benches ; DCS-publications-id ; art-766 ; DCS-publications-credits ; dsp-fa ; DCS-publications-personnel-id ; 82
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 890
Deposited By: Dr. Plamen Angelov
Deposited On: 08 Jan 2008 13:25
Refereed?: Yes
Published?: Published
Last Modified: 21 Mar 2014 10:08
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/890

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