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Multimodal Human Spacecraft Interaction in Remote Environments Read chapter Read first chapter

2010 | OriginalPaper | Chapter

22. A Hybrid Framework for Servo-Actuated Systems Fault Diagnosis

Authors : Seraphin C. Abou, Manali Kulkarni, Marian Stachowicz

Published in: Machine Learning and Systems Engineering

Publisher: Springer Netherlands

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Abstract

A hybrid fault diagnosis method is proposed in this paper which is based on analytical and fuzzy logic theory. Analytical redundancy is employed by using statistical analysis. Fuzzy logic is then used to maximize the signal- to-threshold ratio of the residual and to detect different faults. The method was successfully demonstrated experimentally on hydraulic actuated system test rig. Real data and simulation results have shown that the sensitivity of the residual to the faults is maximized, while that to the unknown input is minimized. The decision of whether ‘a fault has occurred or not?’ is upgraded to ‘what is the severity of that fault?’ at the output. Simulation results show that fuzzy logic is more sensitive and informative regarding the fault condition, and less sensitive to uncertainties and disturbances.

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Metadata
Title
A Hybrid Framework for Servo-Actuated Systems Fault Diagnosis
Authors
Seraphin C. Abou
Manali Kulkarni
Marian Stachowicz
Copyright Year
2010
Publisher
Springer Netherlands
Book
Machine Learning and Systems Engineering

Print ISBN: 978-90-481-9418-6

Electronic ISBN: 978-90-481-9419-3

Copyright Year: 2010

DOI
https://doi.org/10.1007/978-90-481-9419-3_22

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