78 research outputs found

    Bond Graph Model Based and Fuzzy Logic For Robust FDI of Mechatronic Systems

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    Robust fault decision : Contribution to Omni directional Mobile Robot

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    Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems and avoiding the execution of an unsafe behaviour. This chapter deals with Robust Decision Making (RDM) for fault detection of electromechanical systems by combining the advantages of Bond Graph (BG) modeling and Fuzzy logic reasoning. A fault diagnosis method implemented in two stages is proposed. In the first stage, the residuals are deduced from the BG model allowing the building of a Fault Signature Matrix (FSM) according to the sensitivity of residuals to different parameters. In the second stage, the result of FSM and the robust residual thresholds are used by the fuzzy reasoning mechanism in order to evaluate a degree of detectability for each set of components. Finally, in order to make robust decision according to the detected fault component, an analysis is done between the output variables of the fuzzy system and components having the same signature in the FSM. The performance of the proposed fault diagnosis methodology is demonstrated through experimental data of an omni directional robot. - See more at: http://www.eurekaselect.com/102039/chapter/robust-fault-decision%3A-appl...

    SBG for Health Monitoring of Fuel Cell System

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    To guarantee the safe operation of the Fuel Cell (FC) systems, it is necessary to use systematic techniques to detect and isolate faults for diagnosis purposes. The problematic for Fault Detection and Isolation (FDI) model-based of fuel cell consists in that such system is bad instrumented, its model is complex (because of coupling of multi-physical phenomena such as electrochemical, electrical, thermo fluidic
) and the numerical values related to it are not always known. This is why qualitative model (based on existence or not of the links between variables and the relations) is well suited for fuel cell diagnosis. In this paper, we propose a new graphical model (named Signed Bond Graph) allowing to combine both qualitative and quantitative features for health monitoring (in terms of diagnosis and prognosis) of the fuel cell. The innovative interest of the presented paper is the use of only one representation for not only structural model but also diagnosis of faults which may affect the fuel cell. The developed theory is illustrated by an application to a Proton Exchange Membrane Fuel Cell (PEMFC).

    Addressing decision making for remanufacturing operations and design-for-remanufacture

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    Remanufacturing is a process of returning a used product to at least original equipment manufacturer original performance specification from the customers' perspective and giving the resultant product a warranty that is at least equal to that of a newly manufactured equivalent. This paper explains the need to combine ecological concerns and economic growth and the significance of remanufacturing in this. Using the experience of an international aero-engine manufacturer it discusses the impact of the need for sustainable manufacturing on organisational business models. It explains some key decision-making issues that hinder remanufacturing and suggests effective solutions. It presents a peer-validated, high-level design guideline to assist decision-making in design in order to support remanufacturing. The design guide was developed in the UK through the analysis of selections of products during case studies and workshops involving remanufacturing and conventional manufacturing practitioners as well as academics. It is one of the initial stages in the development of a robust design for remanufacture guideline

    Functional and Behavior Models for the Supervision of an Intelligent and Autonomous System

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    The graphical approaches often have different backgrounds and view a system or an algebraic model from different perspectives in order to facilitate the communication and the understanding. These graphical approaches satisfy the modeling needs and give a clear and easily understandable overview of the behavioral and functional models and make easier to see what the process is, which vulnerabilities and asset that are involved and how the system works. The main goal of this paper is to develop and implement a methodology which combines the functional analysis and the bond graph (BG) tool for intelligent and autonomous systems. As a result, a supervisory interface is obtained, given under a finite automaton, displaying to the operators the possibilities the system has to achieve or not, its objectives. Each operating mode, corresponding to a vertex of the automaton, is associated with a set of services from a functional point-of-view and is defined accurately by a behavioral BG model. Furthermore, the service availability (associated to the BG elements) and the conditions for switching from one mode to another one are analyzed by fault detection and isolation algorithms generated on the basis of the structural and causal properties of the BG tool. Moreover, when a fault is not completely isolable some results can nevertheless be expressed in terms of available or unavailable services

    Human Endogenous Retrovirus and Neuroinflammation in Chronic Inflammatory Demyelinating Polyradiculoneuropathy.

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    Human endogenous retroviruses HERV-W encode a pro-inflammatory protein, named MSRV-Env from its original identification in Multiple Sclerosis. Though not detected in various neurological controls, MSRV-Env was found in patients with chronic inflammatory demyelinating polyradiculoneuropathies (CIDPs). This study investigated the expression of MSRV in CIDP and evaluated relevant MSRV-Env pathogenic effects. 50 CIDP patients, 19 other neurological controls (ONDs) and 65 healthy blood donors (HBDs) were recruited from two different countries. MSRV-env and -pol transcripts, IL6 and CXCL10 levels were quantified from blood samples. MSRV-Env immunohistology was performed in distal sensory nerves from CIDP and neurological controls biopsies. MSRV-Env pathogenic effects and mode of action were assayed in cultured primary human Schwann cells (HSCs). In both cohorts, MSRV-env and -pol transcripts, IL6 positivity prevalence and CXCL10 levels were significantly elevated in CIDP patients when compared to HBDs and ONDs (statistically significant in all comparisons). MSRV-Env protein was detected in Schwann cells in 5/7 CIDP biopsies. HSC exposed to or transfected with MSRV-env presented a strong increase of IL6 and CXCL10 transcripts and protein secretion. These pathogenic effects on HSC were inhibited by GNbAC1, a highly specific and neutralizing humanized monoclonal antibody targeting MSRV-Env. The present study showed that MSRV-Env may trigger the release of critical immune mediators proposed as instrumental factors involved in the pathophysiology of CIDP. Significant MSRV-Env expression was detected in a significant proportion of patients with CIDP, in which it may play a role according to its presently observed effects on Schwann cells along with previously known effects on immune cells. Experimental results also suggest that a biomarker-driven therapeutic strategy targeting this protein with a neutralizing antibody such as GNbAC1 may offer new perspectives for treating CIDP patients with positive detection of MSRV-Env expression. Geneuro-Innovation, France
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