Bond Graph for Online Robust Diagnosis Application: hydraulic system

被引：2
|
作者：
Abdallah, Ibrahim [1 ]
Gehin, Anne-Lise [1 ]
Bouamama, Belkacem Ould [1 ]
机构：
[1] Univ Lille, CNRS, Ctr Rech Informat Signal & Automat Lille, CRIStAL,Cent Lille,UMR 9189, F-59000 Lille, France
来源：
IFAC PAPERSONLINE | 2017年 / 50卷 / 01期
关键词：
Supervision; Diagnosis; Bond Graph; Linear Fractional Transformation; FAULT-DIAGNOSIS;
D O I：
10.1016/j.ifacol.2017.08.2350
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper concerns the online quantitative Fault Detection and Isolation (FDI) in uncertain systems using the Analytical Redundancy Relations (ARR). It proposes a pure graphical robust diagnosis using Bond Graph (BG) model. The proposed diagnoser directly generates online residuals with dynamical thresholds. The innovative interest is the use of only one tool (BG) for the behavioral modeling and for the FDI without expressing the analytical form of the model nor the thresholds. A hydraulic system is presented for the demonstration. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：13538 / 13543
页数：6
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