Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations. (16th January 2017)

• Record Type: Journal Article
• Authors: Pous, Nicolas; Gingras, Denis; Gruyer, Dominique
• Other Names: Li Gang Academic Editor.
• Is Part Of: Journal of control science and engineering. Volume 2017(2017)
• Publication Date: 2017-01-16
• Subjects: Control theory -- Periodicals; 629.831205
• DOI: 10.1155/2017/1763934
• Languages: English
• ISSNs: 1687-5249

Abstract

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.