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Journal of Control Science and Engineering
Volume 2017 (2017), Article ID 1763934, 10 pages
https://doi.org/10.1155/2017/1763934
Research Article

Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations

1Laboratory of Intelligent Vehicles (LIV), Sherbrooke University, Sherbrooke, QC, Canada
2IFSTTAR-IM-LIVIC, Versailles-Satory, France

Correspondence should be addressed to Nicolas Pous

Received 11 August 2016; Accepted 6 December 2016; Published 16 January 2017

Academic Editor: Gang Li

Copyright © 2017 Nicolas Pous et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This work proposes a fault detection architecture for vehicle embedded sensors, allowing to deal with both system nonlinearity and environmental disturbances and degradations. The proposed method uses analytical redundancy and a nonlinear transformation to generate the residual value allowing the fault detection. A strategy dedicated to the optimization of the detection parameters choice is also developed.