Intelligent Vehicle Embedded Sensors Fault Detection and Isolation Using Analytical Redundancy and Nonlinear Transformations-Reference-Cited by-同舟云学术

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

Published:2017 Issue: Volume:2017 Page:1-10
ISSN:1687-5249
Container-title:Journal of Control Science and Engineering
language:en
Short-container-title:Journal of Control Science and Engineering

Author:

Pous Nicolas¹^ORCID,Gingras Denis¹^ORCID,Gruyer Dominique²

Affiliation:

1. Laboratory of Intelligent Vehicles (LIV), Sherbrooke University, Sherbrooke, QC, Canada

2. IFSTTAR-IM-LIVIC, Versailles-Satory, France

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.

Funder

National Science and Engineering Research Council

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://downloads.hindawi.com/journals/jcse/2017/1763934.pdf

Reference13 articles.

1. Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data

2. A new approach to robust fault detection and identification

3. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors