Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations
Joint Authors
Gingras, Denis
Pous, Nicolas
Gruyer, Dominique
Source
Journal of Control Science and Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Pous, Nicolas& Gingras, Denis& Gruyer, Dominique. 2017. Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations. Journal of Control Science and Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1173396
Modern Language Association (MLA)
Pous, Nicolas…[et al.]. Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations. Journal of Control Science and Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1173396
American Medical Association (AMA)
Pous, Nicolas& Gingras, Denis& Gruyer, Dominique. Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations. Journal of Control Science and Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1173396
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1173396
