Version 1
: Received: 4 March 2019 / Approved: 5 March 2019 / Online: 5 March 2019 (12:03:53 CET)
How to cite:
Sallami, A.; Mzoughi, D.; Allegui, A.; Mami, A. Robust Supervision by Integration External and Bond Graph Models of a Desalination System. Preprints2019, 2019030059. https://doi.org/10.20944/preprints201903.0059.v1
Sallami, A.; Mzoughi, D.; Allegui, A.; Mami, A. Robust Supervision by Integration External and Bond Graph Models of a Desalination System. Preprints 2019, 2019030059. https://doi.org/10.20944/preprints201903.0059.v1
Sallami, A.; Mzoughi, D.; Allegui, A.; Mami, A. Robust Supervision by Integration External and Bond Graph Models of a Desalination System. Preprints2019, 2019030059. https://doi.org/10.20944/preprints201903.0059.v1
APA Style
Sallami, A., Mzoughi, D., Allegui, A., & Mami, A. (2019). Robust Supervision by Integration External and Bond Graph Models of a Desalination System. Preprints. https://doi.org/10.20944/preprints201903.0059.v1
Chicago/Turabian Style
Sallami, A., Allegui Allegui and Abdelkader Mami. 2019 "Robust Supervision by Integration External and Bond Graph Models of a Desalination System" Preprints. https://doi.org/10.20944/preprints201903.0059.v1
Abstract
This article aims to solve the problem of robust supervision of a reverse osmosis desalination system (RO-DS) with two models, external model and bond graph model. The structure of an industrial system from the point of view of the external model operates according to several modes of operation (degraded and normal). For this external model, we cannot locate the faults since we are talking about a global operation of the system. The possible solution for the development of research was to use the multidisciplinary model called bond graph. This model by its graphic nature and using a unified language makes it possible to model the industrial system element by element from where it helps the user not only to detect the faults but also to locate them when they appear in the system. The results suggest that the use of the bond graph model for alarm 02 is a reverse osmosis error (RO1); these phenomena are readable on the bond graph model and can be quantified by equations. The equation of the model of this reverse osmosis (RO1) is found in the residual equations (r5, r6 and r7), so that these residues will be sensitive to this rupture. The possible solution during research development was to use the bond graph model to supplement information with physical knowledge and to locate faults. This article also describes the operating safety (by minimizing false alarms and non-detections as well as delays in fault detection) of the desalination system by using the bond graph model described in Linear Fractional Transformation (LFT) form for enable it to manage the robust supervision of a desalination system. An approach based on (LFT-BG) is developed to monitor tank leakage (Cu) and reverse osmosis (RO1 and RO2) faults or valve level (V1 and V2) closures and membrane clogging reverse osmosis (Rm1 and Rm2) that can occur in the reverse osmosis desalination system (RO-DS).
Keywords
Robust Supervision, Bond Graph model, External model, Desalination unit, Reverse osmosis, Linear Fractional Transformation.
Subject
Engineering, Control and Systems Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
