Implementation of a Cascade Fault Tolerant Control and Fault Diagnosis Design for a Modular Power Supply

The main objective of this research work was to develop reliable and intelligent power sources for the future. To achieve this objective, a modular stand-alone solar energy-based direct current (DC) power supply was designed and implemented. The converter topology used is a two-stage interleaved boost converter, which is monitored in closed loop. The diagnosis method is based on analytic redundancy relations (ARRs) deduced from the bond graph (BG) model, which can be used to detect the failures of power switches, sensors, and discrete components such as the output capacitor. The proposed supervision scheme including a passive fault-tolerant cascade proportional integral sliding mode control (PI-SMC) for the two-stage boost converter connected to a solar panel is suitable for real applications. Most model-based diagnosis approaches for power converters typically deal with open circuit and short circuit faults, but the proposed method offers the advantage of detecting the failures of other vital components. Practical experiments on a newly designed and constructed prototype, along with simulations under PSIM software, confirm the efficiency of the control scheme and the successful recovery of a faulty stage by manual isolation. In future work, the automation of this reconfiguration task could be based on the successful simulation results of the diagnosis method.This research was funded by the Tunisian Ministry of Higher Education and Scientific Research

Online Implementation of Inequality Constraints Monitoring in Dynamical Systems

This paper deals with fault detection in dynamical systems where the state variables evolutions are constrained by inequality constraints. The latter corresponds either to physical limitations or to safety specification. Two classical residual generation approaches are studied, namely, parity space and unknown input observer approaches, and are extended to monitor the inequality constraints. A practical implementation on a real process is performed and permits to validate the relevance of the proposed methods

Online Implementation of Inequality Constraints Monitoring in Dynamical Systems

This paper deals with fault detection in dynamical systems where the state variables evolutions are constrained by inequality constraints. The latter corresponds either to physical limitations or to safety specification. Two classical residual generation approaches are studied, namely, parity space and unknown input observer approaches, and are extended to monitor the inequality constraints. A practical implementation on a real process is performed and permits to validate the relevance of the proposed methods

Design of a polarimetric imager for complex surface analysis.

Cette thèse est consacrée à la conception et au développement d’un capteur polarimétrique destiné à l'analyse d’objets métalliques spéculaires tels que les bains de soudure.Nous présentons une étude basée sur l'imagerie polarimétrique du rayonnement thermique émis par la surface du bain de fusion pour accéder à d'autres paramètres physiques présents dans la scène observée.Notre objectif est de proposer une technique permettant un contrôle en temps réel de la surface du bain liquide au cours de la soudure. Dans ce manuscrit nous abordons tout d'abord la mise en place du dispositif d'imagerie et son étalonnage afin de recueillir une donnée polarimérique fiable.Enfin, plusieurs problématiques sont développées, telles que la segmentation automatique des images de polarisation, la détection de la présence de particules flottantes telles que l’alumine et la caractérisation du changement de concavité sans avoir recours à l’évaluation de la topographie du bain.This thesis is devoted to the design and development of a polarimetric sensor intended for the analysis of specular metallic objects such as weld pools.We present a study based on polarimetric imaging of thermal radiation emitted by the surface of the molten pool to access other physical parameters present in the observed scene.Our objective is to propose a technique allowing real-time control of the surface of the liquid pool during welding. In this manuscript, we first discuss the setting up of the imaging device and its calibration in order to collect reliable polarimetric data.Finally, several issues are developed, such as the automatic segmentation of polarization images, the detection of the presence of floating particles such as alumina and the characterization of the change in concavity without resorting to the assessment of the topography of the weld pool

Mode Identification and Fault Detection for Hybrid Dynamical Systems using Luenberger Observers

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Distinguishability and Similarity between modes in Hybrid System Monitoring

International audienceThe general principle of model-based Fault Detection and Isolation (FDI) algorithms aims to compare the expected behavior of the system, given by a model, with its actual behavior, known through on-line observations. Accordingly, this paper considers Hybrid Dynamical Systems (HDS), since the behavior is determined by the interaction between continuous and discrete dynamics. The proposed FDI method is based on Luenberger observers. The resulting faults indicators allow detecting both continuous and discrete faults. The property of distinguishability will be considered to guarantee modes identification and the similarity between modes is given in order to reduce residuals calculation

Behavior graphs for hybrid systems monitoring

International audienceHybrid Dynamical Systems (HDS) constitute a wide class of common industrial applications, where the behavior is determined by the interaction between continuous and discrete dynamics, i.e. behavioral modes succession. The general principle of model-based Fault Detection and Isolation (FDI) algorithms is to compare the expected behavior of the system, given by a model, with its actual behavior, known through on-line observations. Faults in HDS may corrupt the two dynamics. In that paper, we propose to limit the set of possible mode candidates by using a priori information on the discrete evolution under normal and faulty hypothesis. Two kinds of graphs are derived from the initial hybrid model, namely Normal Behavior Graphs (NBG), Faulty Behavior Graphs (FBG). Using these graphs allows us not only to identify efficiently the actual mode but also to directly interpret (diagnose) the discrete faulty evolution in terms of faults. The whole FDI methodology is described and applied to a two tanks system example