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The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system

Shi, John Z., Gu, Fengshou, Lennox, Barry and Ball, Andrew (2005) The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system. Control Engineering Practice, 13 (11). pp. 1357-1367. ISSN 0967-0661

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Abstract

This paper presents a practical approach to combine model-based fault detection with an adaptive threshold. The suitability of the proposed technique is illustrated through its application to the condition monitoring of a nonlinear electro-hydraulic plant. The paper begins by outlining the difficulties associated with modelling the plant and the steps taken to identify the uncertain factors that influence the accuracy of the resulting model. A linearised model is applied in this study. The reason for this is because of the availability of many well-developed model-based approaches and model parameter estimation techniques for linear systems. The errors due to the linearisation and stochastic factors are studied both experimentally and theoretically and are compensated for by using an adaptive threshold. The combined linearised model-based approach and adaptive threshold is not only easy for on-line implementation but also takes into account the unknown influences such as model errors, measurement noise, temperature fluctuation and hence leads to a reliable fault detection scheme. The performance of the proposed fault detection scheme is demonstrated in detecting several different fault types associated with the control components, actuator and sensor.

Item Type: Article
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > Informatics Research Group
School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
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Depositing User: Sharon Beastall
Date Deposited: 20 Jan 2010 14:12
Last Modified: 08 Dec 2010 13:30
URI: http://eprints.hud.ac.uk/id/eprint/6811

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