Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
710473 | IFAC-PapersOnLine | 2016 | 6 Pages |
Abstract
This paper lies in the domain of Fault Detection and Isolation (FDI). A Bayesian Naïve Classifier (BNC) structure is selected and used as a first attempt to use Bayesian Belief Networks (BBNs) for DC/DC power converter FDI. In order to highlight the BNC capabilities, it is compared to the well known and used FDI method based on Proportional Observer (PO). This comparative study is based on real data collected from a Zero Volt Switch (ZVS) Full Bridge Isolated Buck converter.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Abbass Zein Eddine, Iyad Zaarour, Francois Guerin, Abbas Hijazi, Dimitri Lefebvre,