By Topic

A pattern recognition approach for anomaly detection on buses brake system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Nicolas Cheifetz ; University Paris-Est, IFSTTAR, GRETTIA, F-93166 Noisy-le-Grand, France ; Allou Samé ; Patrice Aknin ; Emmanuel de Verdalle

Diagnosis of complex systems refers to the problem of identifying a breakdown or a failure based on an inspection, a control or a test. Monitoring such industrial complex systems is essential to schedule relevant maintenance actions. We consider an automotive subsystem to monitor: the brake system, because of its impact on the vehicles availability. Through a European project [1], data are acquired via in-vehicle communication protocols and additional sensors. This work aims at developing remote diagnostic and maintenance support tools driven by these data. Our approach combines an analytic model and detection techniques in order to monitor the brake system. We provide experimental results on vehicle data using two multivariate detection methods.

Published in:

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

Date of Conference:

5-7 Oct. 2011