Bond Graph model of a vertical U-tube steam condenser coupled with a heat exchanger.

International audienceA simulation model for a vertical U-tube steam condenser in which the condensate is stored at the bottom well is developed in this paper. The U-tubes carrying the coolant are partially submerged in the stored condensate and thus the bottom well acts as a heat exchanger. The storage of hydraulic and thermal energies is represented using a coupled pseudo-bond graph model. Advection effects are modelled by considering reticulated segments of the tubes carrying coolant, over which condensation takes place. The developed model is of intermediate complexity and it is intended for use in observer based real time process supervision, which works by comparing the process behaviour to the reference model outputs. The simulation results obtained from the bond graph model are validated with experimental data from a laboratory set-up

Fault detection and isolation of PEM fuel cell system based on nonlinear analytical redundancy

This paper presents a procedure dealing with the issue of fault detection and isolation (FDI) using nonlinear analytical redundancy (NLAR) technique applied in a proton exchange membrane (PEM) fuel cell system based on its mathematic model. The model is proposed and simplified into a five orders state space representation. The transient phenomena captured in the model include the compressor dynamics, the flow characteristics, mass and energy conservation and manifold fluidic mechanics. Nonlinear analytical residuals are generated based on the elimination of the unknown variables of the system by an extended parity space approach to detect and isolate actuator and sensor faults. Finally, numerical simulation results are given corresponding to a faults signature matrix

Model builder for diagnosis and simulation of hybrid dynamic systems: Application to railway rolling stock

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A dynamic fuzzy model for a drum–boiler–turbine system

A nonlinear dynamic fuzzy model for natural circulation drum–boiler–turbine is presented. The model is derived from Åström–Bell nonlinear dynamic system and describes the complicated dynamics of the physical plant. It is shown that the dynamic fuzzy model gives in some appropriate sense accurate global nonlinear prediction and at the same time that its local models are close approximations to the local linearizations of the nonlinear dynamic system. This closeness is illustrated by simulation in various condition

Robust FDI based on LFT BG and relative activity at junction

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Modelling and estimation of tire-road longitudinal impact efforts using bond graph approach

Tireroad interface dynamics is due to the interaction of several physical phenomena (mechanical, thermal, hydrodynamic, etc.). Modelling of such a system needs a unified approach to represent the nonlinear behavior model in a generic and systematic way. Bond graph modelling is well suited for this task. The developed model allows to estimate the longitudinal impact forces at tireroad contact in interaction with its environment. A simulation model in modular and hierarchical form is developed in Symbols 2000 software and used for model integration and validation. Finally, comparison with experimental results are presented

Structural diagnosability analysis. Application to an induction motor

International audience—The presented research is carried out within the framework of a global industrial project " Electro-Mechanical Actuator Health Management " with french company CERTIA. The objective is the realization of an auto-diagnosis embedded module for health monitoring and reconfiguration of Electro-Mechanical Actuator (EMA) including two operating modes: Test checking before taking off (evaluation and health management, i.e evaluation of the rate of degradation) and online supervision including (i)fault detection and isolation (to avoid the irreversible jamming default for instance) and (ii) fault tolerant control and/or reconfiguration in faulty situation (how to continue to control the system en degraded mode ?). The present paper concerns the first part of the project. The innovative interest concerns use of bond graph model as unified and multidisciplinary tool not only for modeling but also for structural diagnosability analysis (which faults which may affect component including sensors can be detected an isolated ?) and sensor placement proposition to make the system diagnosable Without any need of numerical calculation. An application to an induction motor as main component in an EMA is used for illustration

Particle Filter based Integrated Health Monitoring in Bond Graph Framework

International audienceThis chapter presents a holistic method to addresses the issue of health monitoring of system parameters in Bond Graph (BG). The advantages of BGs are integrated with Bayesian estimation techniques for efficient diagnostics and prog-nostics of faults. In particular, BG in Linear fractional transformations (LFT) are used for modelling the global uncertain system and sequential Monte Carlo method based Particle filters (PF) are used for estimation of state of health (SOH) and subsequent prediction of the remaining useful life (RUL). In this work, the method is described with respect to a single system parameter which is chosen as prognos-tic candidate. The prognostic candidate undergoes progressive degradation and its degradation model is assumed to be known a priori. The system operates in control feedback loop. The detection of degradation initiation is achieved using BG LFT based robust fault detection technique. The latter forms an efficient diagnostic module. PFs are exploited for efficient Bayesian inference of SOH of the prog-nostic candidate. Moreover, prognostics is achieved by assessment of RUL in probabilistic domain. The issue of prognostics is formulated as joint state-parameter estimation problem, a hybrid prognostic approach, wherein the fault model is constructed by considering the statistical degradation model of the prog-nostic candidate. The observation equation is constructed from nominal part of the BG-LFT derived Analytical Redundancy Relations (ARR). Various uncertainties which arise because of noise on ARR based measurements, degradation process, environmental conditions etc. are effectively managed by PF. This allows the production of effective predictions of the RUL of the prognostic candidate with suitable confidence bounds. The method is applied over a mechatronic system in real time and performance is assessed using suitable metrics

Backlash fault detection in mechatronic system.

International audienceIn this paper, a fault detection and isolation model based for backlash phenomenon is presented. The aim of this contribution is to be able to detect then distinguish the undesirable backlash from the useful one inside an electromechanical test bench. The dynamic model of the real system is derived, using the bond graph approach, motivated by the multi-energy domain of such mechatronic system. The innovation interest of the use of the bond graph tool, resides in the exploitation of one language representation for modelling and monitoring the system with presence of mechanical faults. Fault indicators are deduced from the analytical model and used to detect and isolate undesirable backlash fault, including the physical system. Simulation and experimental tests are done on electromechanical test bench which consists of a DC motor carrying a mechanical load, through a reducer part containing a backlash phenomenon