Dissertations / Theses on the topic 'Modélisation non paramétrique'
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Chikhi, Mohamed. "Modélisation non paramétrique des processus stochastiques : analyse non paramétrique de la non linéarité de l'indice CAC40." Montpellier 1, 2001. http://www.theses.fr/2001MON10024.
Full textIn this work, we are interested in the nonparametric dynamic modelling of the stochastic processes. We try to exceed the traditional vision treating the observed fluctuations on the Parisian stock exchange market while seeking to identify the stock exchange CAC 40 series while holding account of the kernel method. In chapter 1, we specify the informational efficiency theory of the stock exchange markets by distinguishing the three usual categories of efficiency and study the anomalies in the stock exchange markets. In chapter 2, we test the weak from efficiency hypothesis by the various traditional tests of random walk and autocorrelation. Then, we apply two more powerful nonparametric tests : Mizrach and BDS tests. In a last time, we test if there is a type of long-term dependence by testing the fractional coefficient of integration and the long memory. .
Taramasco, Ollivier. "Modélisation non paramétrique du comportement des cours boursiers." Grenoble 1, 1993. http://www.theses.fr/1993GRE10038.
Full textRivoirard, Vincent. "Estimation bayésienne non paramétrique." Phd thesis, Université Paris-Diderot - Paris VII, 2002. http://tel.archives-ouvertes.fr/tel-00002149.
Full textFischer, Richard. "Modélisation de la dépendance pour des statistiques d'ordre et estimation non-paramétrique." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1039/document.
Full textIn this thesis we consider the modelling of the joint distribution of order statistics, i.e. random vectors with almost surely ordered components. The first part is dedicated to the probabilistic modelling of order statistics of maximal entropy with marginal constraints. Given the marginal constraints, the characterization of the joint distribution can be given by the associated copula. Chapter 2 presents an auxiliary result giving the maximum entropy copula with a fixed diagonal section. We give a necessary and sufficient condition for its existence, and derive an explicit formula for its density and entropy. Chapter 3 provides the solution for the maximum entropy problem for order statistics with marginal constraints by identifying the copula of the maximum entropy distribution. We give explicit formulas for the copula and the joint density. An application for modelling physical parameters is given in Chapter 4.In the second part of the thesis, we consider the problem of nonparametric estimation of maximum entropy densities of order statistics in Kullback-Leibler distance. Chapter 5 presents an aggregation method for probability density and spectral density estimation, based on the convex combination of the logarithms of these functions, and gives non-asymptotic bounds on the aggregation rate. In Chapter 6, we propose an adaptive estimation method based on a log-additive exponential model to estimate maximum entropy densities of order statistics which achieves the known minimax convergence rates. The method is applied to estimating flaw dimensions in Chapter 7
Duchereau, Jérôme. "Modélisation non paramétrique des incertitudes en dynamique transitoire des systèmes complexes avec incertitudes non homogènes." Paris, CNAM, 2004. http://www.theses.fr/2004CNAM0479.
Full textThis paper is devoted to numerical models for prediction of transient dynamical response induced by shocks upon structures with inhomogeneous random uncertainties. The usual numerical methods for analyzing such structures in the low- and medium- frequency ranges employ reduced matrix models based on the use of the elastic modes. The contribution of the higher modes is very sensitive to the modelling and data errors. Here, a recent nonparametric probabilistic method is applied to construct the random matrix model allowing modelling and data errors to be taken into account. The paper presents an extension of the nonparametric method for the case of inhomogeneous uncertainties in the structures. A dynamic substructuring method is used and every substructure gets its own uncertainty level. Experiments have been developed in order to validate the nonparametric probabilistic approach of random uncertainties for such dynamical systems
Raoux, Jean-Jacques. "Modélisation non-linéaire des composants électroniques : du modèle analytique au modèle tabulaire paramétrique." Limoges, 1995. http://www.theses.fr/1995LIMO0006.
Full textMoreau, Sandrine. "Contribution à la modélisation et à l'estimation paramétrique des machines électriques à courant alternatif : application au diagnostic." Poitiers, 1999. http://www.theses.fr/1999POIT2327.
Full textAgbodan, Dago. "Nomination persistante dans un modèle paramétrique : identification non-ambigue͏̈ et appariement générique d'entités topologiques." Poitiers, 2002. http://www.theses.fr/2002POIT2313.
Full textParametric models have a dual structure where an abstract representation (the parametric specification) references an explicit representation (the geometry). The persistent naming problem is to maintain the references between these two representations in order to be able to reevaluate the second starting from the first, in spite of modifications. The problem is to identify an entity in an initial model, then to find it in a reevaluated model. We propose to represent evolutions of the shells and faces of the modeled objects in a graph. Each entity referenced by the specification is characterized in terms of the graph nodes, and by a link to the current geometry. Matching the initial graph and a reevaluated graph throughout a revaluation, and then, searching common elements in these graphs, allows us to interpret the references and thus to maintain the link between the parametric specification and the geometry in the reevaluated object, ensuring a persistent naming
Villemur, Charles. "Modélisation paramétrique et classification automatique de signaux de forme transitoire : application au contrôle non-destructif." Toulouse, INPT, 1988. http://www.theses.fr/1988INPT082H.
Full textBoitard, Philippe. "Dynamique des véhicules industriels : modélisation non-linéaire pour l'application à la sécurité active et à l'identification paramétrique." Lyon, INSA, 1999. http://www.theses.fr/1999ISAL0081.
Full textIn a context of shortening the times of development, it becomes essential for the car manufacturers, to use data-processing simulation like prediction and development tools. In order to study the heavy vehicle handling, a modeling was developed. A mathematical translation of the model was carried out thanks to a program especially developed for this application. This tool is based on symbolic mathematical software called Maple. A data processing environment of simulation was conceived. It uses the modularity of the Matlab / Simulink environment. From an experimental point of view, a parametric identification method is presented. This one is used to parameterise and contribute to the correlation of the models. A comparison between calculation and measurement is carried out on a vehicle of the Renault Midliner type. An example of simulation is presented in the case of a braking in curve and rollover maneuvers
Pugsley, Gareth. "Modélisation paramétrique non linéaire des machines asynchrones et démarche d'optimisation associée : application au dimensionnement dans les véhicules hybrides." Phd thesis, Grenoble INPG, 2004. http://tel.archives-ouvertes.fr/tel-00408322.
Full textRhaiem, Mehdi. "Efficience de la recherche dans les écoles de gestion au Canada : modélisation par des approches paramétriques et non-paramétriques." Doctoral thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/36193.
Full textThe production of knowledge is of great importance to governments, universities and researchers. For the latter, today more than ever, research is becoming more and more important in their portfolios of activities. A number of factors are driving this new trend, including the introduction of productivity-driven research funding systems in a number of countries, global competition for research, the proliferation of standardized tools for assessing scientific excellence, and the importance of research performance and productivity in researchers’ career path success. However, the performance of university researchers varies greatly between disciplines and within the same discipline. These findings reinforce the relevance of questioning the allocation and management of resources in the field of university research. This study addresses this issue in the specific context of research in Canadian Business Schools. Its aims, on the one hand, to draw a detailed portrait of the advancement of knowledge on the concept of the efficiency of academic research and to identify the main milestones that have marked its evolution over the last two decades and, on the other hand, to evaluate the efficiency of academic research of Canadian Business Schools’ scholars and to identify the determinants that may explain the differences in efficiency between them. The thesis allowed the production of three articles. The first one used the systematic review of the literature and the method of vote counting to build an integrative conceptual framework of inputs, outputs, and determinants of the efficiency of academic research. It has also identified several research opportunities to contribute to the advancement of knowledge in this field of study. The second article used a new method, The Reference Publication Year Spectroscopy, to study in depth the concept of the efficiency of academic research by identifying its historical roots as well as the contributions that marked its evolution. These first two articles made it possible to satisfy the first part of the general objective of this research: “to draw a detailed portrait of the advancement of knowledge on the concept of the efficiency of academic research and to identify the main milestones that have marked its evolution over the last two decades”. Taking advantage of the findings and potential contributions to the advancement of knowledge identified in the first two articles, the third article estimated parametric and non-parametric frontiers of efficiency of scholars’ publications and citations in eight research disciplines in Canadian Business schools. It also allowed to identify several levers of efficiency gaps among researchers affiliated with these schools. Among other things, the results of this third article showed that efficiency scores differ significantly from one disciplinary field to another, and even within disciplinary fields, and that AACSB accreditation, affiliation to prestigious universities, size of institution, sources of funding and seniority are positively associated with high levels of efficiency. The findings of the three articles devised some lines of action that might improve the efficiency of academic research for researchers in general and those affiliated with Canadian Business schools, in particular.
Jabloun, Meryem. "Modélisation de signaux fortement non stationnaires à phase et à amplitude locales polynomiales." Phd thesis, Grenoble INPG, 2007. http://tel.archives-ouvertes.fr/tel-00176079.
Full textet de reconstruction de signaux fortement non-stationnaires, modulés non-linéairement à la fois
en amplitude et en fréquence. L'estimation de tels signaux dans un contexte trés bruité est un problème
délicat et les méthodes existantes de la littérature présentent plusieurs inconvénients dans ce cas.
Nous avons montré comment une approche locale permet une meilleure adaptabilité du modèle à la
nature des variations locales des amplitudes et des fréquences instantanées. Les résultats de l'estimation
sont par conséquent améliorés. L'originalité de la méthode proposée tient à l'application de modèles paramétriques bien adaptés sur des segments temporels de courtes durées extraits du signal étudié. Nous
avons proposé une stratégie de segmentation puis une stratégie de fusion des segments estimés permettant
la reconstruction du signal dans la totalité de sa durée. L'approche proposée permet de s'affranchir d'un
modèle global du signal requérant un ordre d'approximation élevé.
La validation de l'efficacité de l'estimation a été effectuée au préalable sur un segment temporel court.
Le modèle considéré localement consiste en une approximation polynomiale de la fréquence et de l'amplitude
exprimée dans une base polynomiale discrète et orthonormale que nous avons calculée. Cette base
permet de réduire le couplage entre les paramètres du modèle. Nous proposons et comparons deux techniques
différentes pour estimer ces derniers. La première est fondée sur la maximisation de la fonction
de vraisemblance en utilisant la technique d'optimisation stochastique le recuit simulé. Tandis que la
deuxième se base sur une approche Bayésienne employant les méthodes MCMC simulées par l'algorithme
de Metroplois-Hastings.
Nous montrons, sur des simulations et également sur des signaux réels, que l'approche proposée fournit
de bons résultats d'estimation par comparaison à celles de la HAF.
Jabloun, Meryem. "Modélisation de signaux fortement non stationnaires à phase et à amplitude locales polynomiales." Phd thesis, Grenoble INPG, 2007. http://www.theses.fr/2007INPG0077.
Full textThis work concentrates on the estimation and reconstruction of highly non-stationary signals having both non-linear amplitude and frequency modulations. We propose a new method for estimating the above mentioned signals with high additive noises. Most of the previously published work in this domain is plagued by shortcomings and at times even fails to address the problem of estimation. We have shown that by using a local approach, which provides flexibility to fit to the local variations of the instantaneous amplitude and frequency, the estimation results are improved significantly. The novelty of the presented work consists in the use of parametric models well-adapted and defined on short time segments. We have also proposed a new technique for obtaining short time segments from the entire signal. Finally, we propose a merging strategy to reconstruct the entire signal along with its modulations. The proposed estimation approach is great interest as it does not require a higher order model to estimate the entire signal. Initially, we validate the estimation effeciency of the local model considering a short time segment. This local model uses polynomial approximations of both local instantaneous amplitude and frequency, decomposed using a discrete orthonormal base which we derived. We also affirm that this base reduces the coupling of model parameters. Hence, the estimation accuracy is enhanced. Furthermore, we have compared two techniques to estimate the model parameters. The first approach is based upon the maximization of the likelihood function by means of an optimization stochastique technique named Simulated Annealing. The second approach uses the MCMC methods with Metropolis-Hastings algorithm. We demonstrate using simulations and real applications that the proposed approach improves both performance and robustness of signal estimation as compared to the existing Higher Ambiguity function based technique
Poilleux-Milhem, Hélène. "Test de validation adaptatif dans un modèle de régression : modélisation et estimation de l'effet d'une discontinuité du couvert végétal sur la dispersion du pollen de colza." Paris 11, 2002. http://www.theses.fr/2002PA112297.
Full textThis thesis framework is the spread of genetically modified organisms in the environment. Several parametric models of the individual pollen dispersal distribution have already been proposed for homogeneous experiments (plants emitting marked pollen surrounded by the same unmarked plants). In order to predict the "genetic pollution" in an agricultural landscape, a discontinuity effect on pollen flows in a cultivated area (e. G. A road crosses a field) has to be taken into account. This effect was modelled and estimated: according to the size of the discontinuity, it may correspond to a significant acceleration of the pollen flow. Graphical diagnosis methods show that the modelling of the individual pollen dispersal distribution and of the discontinuity effect, is best fitting the data when using constant piecewise functions. Prior to using parametric models to predict genetic pollution, goodness-of-fit tools are essential. We therefore propose a goodness-of-fit test in a nonlinear Gaussian regression model, where the errors are independent and identically distributed. This test does not require any knowledge on the regression function and on the variance of the observations. It generalises the linear hypothesis tests proposed by Baraud et al (Ann. Statist. 2003, Vol. 31) to the nonlinear hypothesis. It is asymptotically of level α and a set of functions over which it is asymptotically powerful is characterized. It is rate optimal among adaptive procedures over isotropic and anisotropic Hölder classes of alternatives. It is consistent against directional alternatives that approach the null hypothesis at a rate close to the parametric rate. According to a simulation study, this test is powerful even for fixed sample sizes
Ben, Salah Hanene. "Gestion des actifs financiers : de l’approche Classique à la modélisation non paramétrique en estimation du DownSide Risk pour la constitution d’un portefeuille efficient." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10249/document.
Full textThe DownSide Risk (DSR) model for portfolio optimization allows to overcome the drawbacks of the classical Mean-Variance model concerning the asymmetry of returns and the risk perception of investors. This optimization model deals with a positive definite matrix that is endogenous with respect to the portfolio weights and hence leads to a non standard optimization problem. To bypass this hurdle, we developed a new recursive minimization procedure that ensures the convergence to the solution and gives a smooth portfolio efficient frontier. Our method consists in replacing all the returns by their nonparametric estimators counterpart using kernel mean or median regressions. This technique provides an effect similar to the case where an infinite number of observations is available. We also develop a new portfolio optimization model where the risks are measured through conditional variance or semivariance. This strategy allows us to take advantage from returns prediction which are obtained by nonparametric univariate methods. The prediction step uses kernel estimation of the conditional mean. Data from different markets are used to test and validate the proposed approaches, and results indicate better overall performance
Mesnil, Florence. "Extension d'une méthode non paramétrique d'estimation dans les modèles mixtes pour l'analyse de données répétées : exemples en pharmacocinétique et en épidémiologie." Paris 11, 1999. http://www.theses.fr/1999PA11T037.
Full textBoulanger, Jérôme. "Estimation non-paramétrique et contributions à l'analyse de séquences d'images : modélisation, simulation et estimation du trafic intra-cellulaire dans les séquences de vidéo-microscopie." Rennes 1, 2007. ftp://ftp.irisa.fr/techreports/theses/2007/boulanger.pdf.
Full textIn this document, the problem of the restauration of videomicroscopy image sequences is first analyzed using an adaptive non-parametric estimation approach. A sequence of growing neighborhoods is thus design to control the bias-variance tradeoff of our estimator based on a weighted average of the data in a adapted neighborhood at the considered location. This procedure allows us to minimize the local quadratic risk in order to select the optimal extent of the neighborhood. The estimator selects points in this neighborhood using a similarity measure based on a distance computed between patches provides a way to better preserve the structures of the image. The analysis and the modelisation of the intracellular membrane trafficking is latter discussed distinguishing the slowy moving component and fast moving component of the sequence. A model based on the analogy between intracellular traffic and communication networks is used to capture the dynamic of the transport intermediates
Victori, Stéphane. "Etude de l'affinement spectral d'un oscillateur paramétrique optique (OPO) en régime nanoseconde par insertion d'un cristal photoréfractif : Modélisation des OPO monomodes." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2001. http://pastel.archives-ouvertes.fr/pastel-00714252.
Full textBelhedi, Amira. "Modélisation du bruit et étalonnage de la mesure de profondeur des caméras Temps-de-Vol." Thesis, Clermont-Ferrand 1, 2013. http://www.theses.fr/2013CLF1MM08/document.
Full text3D cameras open new possibilities in different fields such as 3D reconstruction, Augmented Reality and video-surveillance since they provide depth information at high frame-rates. However, they have limitations that affect the accuracy of their measures. In particular for TOF cameras, two types of error can be distinguished : the stochastic camera noise and the depth distortion. In state of the art of TOF cameras, the noise is not well studied and the depth distortion models are difficult to use and don't guarantee the accuracy required for some applications. The objective of this thesis is to study, to model and to propose a calibration method of these two errors of TOF cameras which is accurate and easy to set up. Both for the noise and for the depth distortion, two solutions are proposed. Each of them gives a solution for a different problem. The former aims to obtain an accurate model. The latter, promotes the simplicity of the set up. Thereby, for the noise, while the majority of the proposed models are only based on the amplitude information, we propose a first model which integrate also the pixel position in the image. For a better accuracy, we propose a second model where we replace the amplitude by the depth and the integration time. Regarding the depth distortion, we propose a first solution based on a non-parametric model which guarantee a better accuracy. Then, we use the prior knowledge of the planar geometry of the observed scene to provide a solution which is easier to use compared to the previous one and to those of the litterature
Dumont, Thierry. "Contributions à la localisation intra-muros. De la modélisation à la calibration théorique et pratique d'estimateurs." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00795685.
Full textChentouf, Sid-Ahmed. "Simulation et essais dynamiques sur stators de moteurs de traction." Phd thesis, Université de Franche-Comté, 2011. http://tel.archives-ouvertes.fr/tel-00776475.
Full textFernandez, Charles. "Modélisation et validation expérimentale des complexes insonorisants pour la prévision vibroacoustique numérique basse et moyenne fréquences des automobiles." Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00470535.
Full textTernynck, Camille. "Contributions à la modélisation de données spatiales et fonctionnelles : applications." Thesis, Lille 3, 2014. http://www.theses.fr/2014LIL30062/document.
Full textIn this dissertation, we are interested in nonparametric modeling of spatial and/or functional data, more specifically based on kernel method. Generally, the samples we have considered for establishing asymptotic properties of the proposed estimators are constituted of dependent variables. The specificity of the studied methods lies in the fact that the estimators take into account the structure of the dependence of the considered data.In a first part, we study real variables spatially dependent. We propose a new kernel approach to estimating spatial probability density of the mode and regression functions. The distinctive feature of this approach is that it allows taking into account both the proximity between observations and that between sites. We study the asymptotic behaviors of the proposed estimates as well as their applications to simulated and real data. In a second part, we are interested in modeling data valued in a space of infinite dimension or so-called "functional data". As a first step, we adapt the nonparametric regression model, introduced in the first part, to spatially functional dependent data framework. We get convergence results as well as numerical results. Then, later, we study time series regression model in which explanatory variables are functional and the innovation process is autoregressive. We propose a procedure which allows us to take into account information contained in the error process. After showing asymptotic behavior of the proposed kernel estimate, we study its performance on simulated and real data.The third part is devoted to applications. First of all, we present unsupervised classificationresults of simulated and real spatial data (multivariate). The considered classification method is based on the estimation of spatial mode, obtained from the spatial density function introduced in the first part of this thesis. Then, we apply this classification method based on the mode as well as other unsupervised classification methods of the literature on hydrological data of functional nature. Lastly, this classification of hydrological data has led us to apply change point detection tools on these functional data
Andrieu, Cindie. "Modélisation fonctionnelle de profils de vitesse en lien avec l'infrastructure et méthodologie de construction d'un profil agrégé." Phd thesis, Université Paul Sabatier - Toulouse III, 2013. http://tel.archives-ouvertes.fr/tel-00915420.
Full textKhemane, Firas. "Estimation fréquentielle par modèle non entier et approche ensembliste : application à la modélisation de la dynamique du conducteur." Thesis, Bordeaux 1, 2011. http://www.theses.fr/2010BOR14282/document.
Full textThis thesis deals with system identification and modeling of fractional transfer functions using bounded and uncertain frequency responses. Therefor, both of fractional differentiation and integration definitions are extended into intervals. Set membership approaches are then applied to estimate coefficients and derivative orders as intervals. These methods are applied to estimate certain Linear Time Invariant systems (LTI), uncertain LTI systems and Linear Parameter Varying systems (LPV). They are notably adopted to model driver's dynamics, since most of studies on one or several individuals shave shown that the collected reactions are not identical and are varying from an experiment to another
Viallefont, Valérie. "Analyses bayesiennes du choix de modèles en épidémiologie : sélection de variables et modélisation de l'hétérogénéité pour des évènements." Paris 11, 2000. http://www.theses.fr/2000PA11T023.
Full textThis dissertation has two separated parts. In the first part, we compare different strategies for variable selection in a multivariate logistic regression model. Covariate and confounder selection in case-control studies is often carried out using either a two-step method or a stepwise variable selection method. Inference is then carried out conditionally on the selected model, but this ignores the madel uncertainty implicit in the variable selection process, and so underestimates uncertainty about relative risks. It is well known, and showed again in our study, that the ρ-values computed after variable selection can greatly overstate the strength of conclusions. We propose Bayesian Model Averaging as a formal way of taking account of madel uncertainty in a logistic regression context. The BMA methods, that allows to take into account several models, each being associated with its posterior probability, yields an easily interpreted summary, the posterior probability that a variable is a risk factor, and its estimate averaged over the set of models. We conduct two comparative simulations studies : the first one has a simple design including only one risk factor and one confounder, the second one mimics a epidemiological cohort study dataset, with a large number of potential risk factors. Our criteria are the mean bias, the rate of type I and type II errors, and the assessment of uncertainty in the results, which is bath more accurate and explicit under the BMA analysis. The methods are applied and compared in the context of a previously published case-control study of cervical cancer. The choice of the prior distributions are discussed. In the second part, we focus on the modelling of rare events via a Poisson distribution, that sometimes reveals substantial over-dispersion, indicating that sorme un explained discontinuity arises in the data. We suggest to madel this over-dispersion by a Poisson mixture. In a hierarchical Bayesian model, the posterior distributions of he unknown quantities in the mixture (number of components, weights, and Poisson parameters) can be estimated by MCMC algorithms, including reversible jump algothms which allows to vary the dimension of the mixture. We focus on the difficulty of finding a weakly informative prior for the Poisson parameters : different priors are detailed and compared. Then, the performances of different maves created for changing dimension are investigated. The model is extended by the introduction of covariates, with homogeneous or heterogeneous effect. Simulated data sets are designed for the different comparisons, and the model is finally illustrated in two different contexts : an ecological analysis of digestive cancer mortality along the coasts of France, and a dataset concerning counts of accidents in road-junctions
Hafidi, Ghizlane. "Application de la commande prédictive non-linéaire à la commande de culture de bactéries escherichia coli." Phd thesis, Université Paris Sud - Paris XI, 2008. http://tel.archives-ouvertes.fr/tel-00345850.
Full textChentouf, Sid-Hamed Benabdallah. "Simulation et essais dynamiques sur stators de moteurs de traction." Thesis, Besançon, 2011. http://www.theses.fr/2011BESA2002/document.
Full textMastering numerical simulations of the behaviour of railway stators remains an important challenge for designers. This allows both the understanding of some physical phenomena and the improvement of design in presence of different sources of uncertainties. The approach proposed in this work consists firstly on building and validating a numerical model of a typical design stator. By carrying out numerical-experimental confrontations and updating models, this first step allowed us to characterize the mean behavior of this heterogeneous assembling and mainly to establish generic modeling rules for other design stators. The second part of this work deals with the investigation of uncertainties affecting the structure or its model. In order to take into account all uncertainties types while performing a calculation of uncertainties propagation, a stochastic hybrid method, combining parametric and non-parametric models, was proposed. Because of the large sizes of finite element models of stators, the problem is treated in a component mode synthesis context. It amounts to carry out an approach reanalysis. In order to ensure a good compromise between reasonable calculation times and an acceptable precision, a generalized variant of the Combined Approximations method (VCA) has been introduced and adapted to component mode synthesis. The VCA method allows both a significant gain in computation time, comparing to an exact calculation, and a high robustness performance comparing to a standard reduction method or an improved method by static residual vectors
Benadjaoud, Mohamed Amine. "Modélisation flexible du risque d’événements iatrogènes radio-induits." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA11T017/document.
Full textRadiotherapy plays a major role in the therapeutic arsenal against cancer. Despite significant advances in technology for nearly twenty years, healthy tissues near or away from the target tumor remain inevitably irradiated at very different levels of doses. These doses are at the origin of early side effects (edema, radiation necrosis, dysphagia, cystitis) or late (rectal bleeding, telangiectasia, carcinogenic, cerebrovascular diseases). It is therefore essential to quantify and prevent these side effects to improve the patient quality of life after their cancer treatment.The objective of this thesis was to propose modelling methods able to answer specific questions asked in both aspects, dosimetry and statistics, involved in the modeling risk of developing radiation-induced iatrogenic pathologies.Our purpose was firstly to assess the out-of-field dose component related to head scatter radiation in high-energy photon therapy beams and then derive a multisource model for this dose component. For measured doses under out-of-field conditions, the average local difference between the calculated and measured photon dose is 10%, including doses as low as 0.01% of the maximum dose on the beam axis. We secondly described a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding for In the flexible Cox model context, we proposed a new dimension reduction technique based on a functional principal component analysis to estimate a dose-response relationship. A two-stage knots selection scheme was performed: a potential set of knots is chosen based on information from the rotated functional principal components and the final knots selection is then based on statistical model selection. Finally, a multilevel functional principal component analysis was applied to radiobiological data in order to quantify the experimental Variability for replicate measurements of fluorescence signals of telomere length
Jemeï, Samir. "Modélisation d'une Pile à Combustible de type PEM par Réseaux de Neurones." Phd thesis, Université de Franche-Comté, 2004. http://tel.archives-ouvertes.fr/tel-00777611.
Full textRagot, Nicolas. "Conception d'un capteur de stéréovision omnidirectionnelle : architecture, étalonnage et applications à la reconstruction de scènes 3D." Phd thesis, Université de Rouen, 2009. http://tel.archives-ouvertes.fr/tel-00417963.
Full textRagot, Nicolas. "Conception d'un capteur de stéréovision omnidirectionnelle : architecture, étalonnage et applications à la reconstruction de scènes 3D." Phd thesis, Rouen, 2009. http://www.theses.fr/2009ROUES035.
Full textThe work presented in this thesis deals with the design and the evaluation of a vision sensor made of two catadioptric sensors, one above the other. To obtain a 3D model, it is necessary to calibrate the sensors, that is to say to estimate the relationships between the 3D space and the image plane. A parametric method has been implemented. It uses an ad hoc model and a cylindrical 3D pattern whose points of interest are light-emetting diodes. This method is based on the assumption that the sensor respects the single effective viewpoint constraint, but which is difficult to put into practice. Thus, we propose a non-parametric method which eliminate the problem of model restrictions. The relationships are defined for a finite number of points and numerical interpolation algorithms allow us to approximate the projection and back-projection functions for all pairs of 3D points-2D points. Then, we propose the implementation and the evaluation of a 3D volumetric reconstruction method which models the scene by a 3D array whose cells are voxels. A colorimetric similarity measure of the voxel projections estimate whether or not the voxel is an object in 3D. This method is evaluated on a 3D static reconstruction, that is a simultaneous image acquisition. Then, this method is studied for sensor displacements. This is a 3D dynamic reconstruction which is defined as the intersection of 3D static reconstructions made at successive times
Fall, Mame Diarra. "Modélisation stochastique de processus pharmaco-cinétiques, application à la reconstruction tomographique par émission de positrons (TEP) spatio-temporelle." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112035.
Full textThe aim of this work is to develop new statistical methods for spatial (3D) and space-time (3D+t) Positron Emission Tomography (PET) reconstruction. The objective is to propose efficient reconstruction methods in a context of low injected doses while maintaining the quality of the interpretation. We tackle the reconstruction problem as a spatial or a space-time inverse problem for point observations in a \Bayesian nonparametric framework. The Bayesian modeling allows to regularize the ill-posed inverse problem via the introduction of a prior information. Furthermore, by characterizing the unknowns with their posterior distributions, the Bayesian context allows to handle the uncertainty associated to the reconstruction process. Being nonparametric offers a framework for robustness and flexibility to perform the modeling. In the proposed methodology, we view the image to reconstruct as a probability density in(for reconstruction in k dimensions) and seek the solution in the space of whole probability densities in . However, due to the size of the data, posterior estimators are intractable and approximation techniques are needed for posterior inference. Most of these techniques are based on Markov Chain Monte-Carlo methods (MCMC). In the Bayesian nonparametric approach, a major difficulty raises in randomly sampling infinite dimensional objects in a computer. We have developed a new sampling method which combines both good mixing properties and the possibility to be implemented on a parallel computer in order to deal with large data sets. Thanks to the taken approach, we obtain 3D spatial reconstructions without any ad hoc space voxellization and 4D space-time reconstructions without any discretization, neither in space nor in time. Furthermore, one can quantify the error associated to the statistical estimation using the credibility intervals
Avalos, Marta. "Modèles additifs parcimonieux." Phd thesis, Université de Technologie de Compiègne, 2004. http://tel.archives-ouvertes.fr/tel-00008802.
Full textTran, Gia-Lac. "Advances in Deep Gaussian Processes : calibration and sparsification." Electronic Thesis or Diss., Sorbonne université, 2020. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2020SORUS410.pdf.
Full textGaussian Processes (GPs) are an attractive specific way of doing non-parametric Bayesian modeling in a supervised learning problem. It is well-known that GPs are able to make inferences as well as predictive uncertainties with a firm mathematical background. However, GPs are often unfavorable by the practitioners due to their kernel's expressiveness and the computational requirements. Integration of (convolutional) neural networks and GPs are a promising solution to enhance the representational power. As our first contribution, we empirically show that these combinations are miscalibrated, which leads to over-confident predictions. We also propose a novel well-calibrated solution to merge neural structures and GPs by using random features and variational inference techniques. In addition, these frameworks can be intuitively extended to reduce the computational cost by using structural random features. In terms of computational cost, the exact Gaussian Processes require the cubic complexity to training size. Inducing point-based Gaussian Processes are a common choice to mitigate the bottleneck by selecting a small set of active points through a global distillation from available observations. However, the general case remains elusive and it is still possible that the required number of active points may exceed a certain computational budget. In our second study, we propose Sparse-within-Sparse Gaussian Processes which enable the approximation with a large number of inducing points without suffering a prohibitive computational cost
Diouf, Cherif El Valid. "Modélisation comportementale de drivers de ligne de transmission pour des besoins d'intégrité du signal et de compatibilité électromagnétique." Thesis, Brest, 2014. http://www.theses.fr/2014BRES0040/document.
Full textIntegrated circuits miniaturization, high operating frequencies, lower supply voltages, high-density integration make digital signals propagating on interconnects highly vulnerable to degradation. Assessing EMC and signal integrity in the early stages of the design flow requires accurate interconnect models allowing for efficient time-domain simulations. In this context, our work addressed the issue of behavioral modeling of transmission line buffers, and particularly that of drivers. The main result is an original modeling approach partially based on Volterra-Laguerre series. The black box models we developed have a fairly simple implementation in SPICE thus allowing a very good portability. They are easy to identify and have a parametric complexity allowing a large gain in simulation time with respect to transistor driver models. In addition, the developed methods allow a more accurate output port nonlinear dynamics modeling, and a more general management of inputs. A very good reproduction of driver behaviour in overclocking conditions provides a significant advantage over standard IBIS models
Andrieu, Cindie. "Modélisation fonctionnelle de profils de vitesse en lien avec l'infrastructure et méthodologie de construction d'un profil agrégé." Phd thesis, Toulouse 3, 2013. http://thesesups.ups-tlse.fr/2057/.
Full textThe knowledge of the actual vehicle speeds is an essential characteristic of drivers behavior and their road usage. This information become available with the generalization of connected vehicles, but also smartphones, which increase the number of "tracers" likely to refer their position and speed in real time. In this thesis, we propose to use these digital traces and to develop a methodology, based on a functional approach, to produce several reference speed profiles. In a first part, we propose a functional modeling of space-speed profiles (i. E. Speed vs position) and we study their properties (continuity, differentiability). In a second part, we propose a methodology to construct an estimator of a space speed profile from noisy measurements of position and speed, based on smoothing splines and the theory of reproducing kernel Hilbert spaces (RKHS). The third part is devoted to the construction of several aggregated profiles (average, median). In particular, we propose a landmark-based registration of profiles at stops, and we propose the construction of speed corridors reflecting the dispersion of actual speeds
Bassene, Aladji. "Contribution à la modélisation spatiale des événements extrêmes." Thesis, Lille 3, 2016. http://www.theses.fr/2016LIL30039/document.
Full textIn this thesis, we investigate nonparametric modeling of spatial extremes. Our resultsare based on the main result of the theory of extreme values, thereby encompass Paretolaws. This framework allows today to extend the study of extreme events in the spatialcase provided if the asymptotic properties of the proposed estimators satisfy the standardconditions of the Extreme Value Theory (EVT) in addition to the local conditions on thedata structure themselves. In the literature, there exists a vast panorama of extreme events models, which are adapted to the structures of the data of interest. However, in the case ofextreme spatial data, except max-stables models, little or almost no models are interestedin non-parametric estimation of the tail index and/or extreme quantiles. Therefore, weextend existing works on estimating the tail index and quantile under independent ortime-dependent data. The specificity of the methods studied resides in the fact that theasymptotic results of the proposed estimators take into account the spatial dependence structure of the relevant data, which is far from trivial. This thesis is then written in thecontext of spatial statistics of extremes. She makes three main contributions.• In the first contribution of this thesis, we propose a new approach of the estimatorof the tail index of a heavy-tailed distribution within the framework of spatial data. This approach relies on the estimator of Hill (1975). The asymptotic properties of the estimator introduced are established when the spatial process is adequately approximated by aspatial M−dependent process, spatial linear causal process or when the process satisfies a strong mixing condition.• In practice, it is often useful to link the variable of interest Y with covariate X. Inthis situation, the tail index depends on the observed value x of the covariate X and theunknown fonction (.) will be called conditional tail index. In most applications, the tailindexof an extreme value is not the main attraction, but it is used to estimate for instance extreme quantiles. The contribution of this chapter is to adapt the estimator of the tail index introduced in the first part in the conditional framework and use it to propose an estimator of conditional extreme quantiles. We examine the models called "fixed design"which corresponds to the situation where the explanatory variable is deterministic. To tackle the covariate, since it is deterministic, we use the window moving approach. Westudy the asymptotic behavior of the estimators proposed and some numerical resultsusing simulated data with the software "R".• In the third part of this thesis, we extend the work of the second part of the framemodels called "random design" for which the data are spatial observations of a pair (Y,X) of real random variables . In this last model, we propose an estimator of heavy tail-indexusing the kernel method to tackle the covariate. We use an estimator of the conditional tail index belonging to the family of the estimators introduced by Goegebeur et al. (2014b)
Cazenove, Jean de. "Développement des méthodes numériques et expérimentales pour la certification vibratoire des disques aubagés monoblocs." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2017.
Full textUnder operating conditions, turbomachinery blisks are subject to static and dynamic loads which mayresult in High-Cycle Fatigue situations when excited at the neighbourhood of resonant frequencies.Random mistuning, which affects blisks due to machining deviations, turns this issue even morecritical. The objective of the current study is to introduce a numerical-Experimental strategy allowingthe dynamic characterization of an experimental bladed disk with regard to the statistics representingthe simulated behaviour for a population of operating blisks. A high-Fidelity numerical model basedon the optical acquisition of an experimental blisk has been set up. Test series performed in labconditions allowed to verify its coherence. The comparison of the response amplitudes measuredunder operating conditions to the model predictions revealed an acceptable matching between testand simulation data. Finally, a non-Parametric probabilistic approach has been used to predict thetheoretical maximal amplification factor. The maximum amplification factor obtained by means ofsimulation was compared to the amplification factor of the test specimen. The strategy proposed inthis study allows maximum amplification factor predictions for a population of blisks
Chiron, Guillaume. "Système complet d’acquisition vidéo, de suivi de trajectoires et de modélisation comportementale pour des environnements 3D naturellement encombrés : application à la surveillance apicole." Thesis, La Rochelle, 2014. http://www.theses.fr/2014LAROS030/document.
Full textThis manuscript provides the basis for a complete chain of videosurveillence for naturally cluttered environments. In the latter, we identify and solve the wide spectrum of methodological and technological barriers inherent to : 1) the acquisition of video sequences in natural conditions, 2) the image processing problems, 3) the multi-target tracking ambiguities, 4) the discovery and the modeling of recurring behavioral patterns, and 5) the data fusion. The application context of our work is the monitoring of honeybees, and in particular the study of the trajectories bees in flight in front of their hive. In fact, this thesis is part a feasibility and prototyping study carried by the two interdisciplinary projects EPERAS and RISQAPI (projects undertaken in collaboration with INRA institute and the French National Museum of Natural History). It is for us, computer scientists, and for biologists who accompanied us, a completely new area of investigation for which the scientific knowledge, usually essential for such applications, are still in their infancy. Unlike existing approaches for monitoring insects, we propose to tackle the problem in the three-dimensional space through the use of a high frequency stereo camera. In this context, we detail our new target detection method which we called HIDS segmentation. Concerning the computation of trajectories, we explored several tracking approaches, relying on more or less a priori, which are able to deal with the extreme conditions of the application (e.g. many targets, small in size, following chaotic movements). Once the trajectories are collected, we organize them according to a given hierarchical data structure and apply a Bayesian nonparametric approach for discovering emergent behaviors within the colony of insects. The exploratory analysis of the trajectories generated by the crowded scene is performed following an unsupervised classification method simultaneously over different levels of semantic, and where the number of clusters for each level is not defined a priori, but rather estimated from the data only. This approach is has been validated thanks to a ground truth generated by a Multi-Agent System. Then we tested it in the context of real data
Li, Shuxian. "Modélisation spatio-temporelle pour l'esca de la vigne à l'échelle de la parcelle." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0313/document.
Full textEsca grapevine disease is one of the incurable dieback disease with the etiology not completely elucidated. It represents one of the major threats for viticulture around the world. To better understand the underlying process of esca spread and the risk factors of this disease, we carried out quantitative analyses of the spatio-temporal development of esca at vineyard scale. In order to detect the spatial correlation among the diseased vines, the non-parametric statistical tests were applied to the spatio-temporal data of esca foliar symptom expression for 15 vineyards in Bordeaux region. Among vineyards, a large range of spatial patterns, from random to strongly structured, were found. In the vineyards with strongly aggregated patterns, no significant increase in the size of cluster and local spread from symptomatic vines was shown, suggesting an effect of the environment in the explanation of this aggregation. To model the foliar symptom occurrence, we developed hierarchical logistic regression models by integrating exogenous covariates, covariates of neighboring symptomatic vines already diseased, and also a latent process with spatio-temporal auto-correlation. The Bayesian inferences of these models were performed by INLA (Inverse Nested Laplace Approximation) approach. The results confirmed the effect of environmental factors on the occurrence risk of esca symptom. The secondary locally spread of esca from symptomatic vines located on the same row or out of row was not shown. A two-step centered auto-logistic regression model, which explicitly integrated the spatio-temporal neighboring structure, was also developed. At last, a geostatistical method was proposed to interpolate data with a particular anisotropic structure. It allowed interpolating the ancillary variable, electrical resistivity of soil, which were used to estimate the available soil water content at vine-scale. These geostatistical methods and spatio-temporal statistical methods developed in this thesis offered outlook to identify risk factors, and thereafter to predict the development of esca grapevine disease in different agronomical contexts
Inou, Allal. "Modélisations numériques d'oscillateurs paramétriques optiques, en régime de fortes conversions, à l'échelle nanoseconde." Limoges, 1998. http://www.theses.fr/1998LIMO0013.
Full textBendjoudi, Aniss. "Contrôle non destructif ultrasonore de tubes métalliques : modélisation, simulation, confrontation à l'expérience et études paramétriques." Paris 7, 2013. http://www.theses.fr/2013PA077002.
Full textNon destructive testings play an essential role in industrial production, in particular in the areas where products quality is critical to safety, such as nuclear. Numerical modeling is one of the means used to understand and master controls. The company CEZUS pursues a project of modeling of its ultrasonic testing for metal tubes used in nuclear fuel assembly. The experimental study of the control is necessary to establish the influence of the various parameters on variability and accuracy. This study also guides the choices made for modeling. To accomplish this, an experimental reproduction of the factory control is realised in the laboratory. Modeling of ultrasonic testing must be sufficiently precise while retaining reasonable computation time. For this, a hybrid model combining a semi-analytical method using the Rayleigh integral with a finite difference method is developed. Finally, the hybrid model is implemented in an operational industrial simulation plaltform. The validation process of simulation results is based on the confrontation with experimental measurements in specific configurations. Signals comparisons show a good qualitative prediction but an incomplete quantitative prediction, especially concerning the relative amplitudes. Finally, the simulation platform allows the exploration of control configurations experimentally incaccessible
Laurain, Vincent. "Contributions à l'identification de modèles paramétriques non linéaires. Application à la modélisation de bassins versants ruraux." Phd thesis, Université Henri Poincaré - Nancy I, 2010. http://tel.archives-ouvertes.fr/tel-00550515.
Full textFontaine, Charles. "Utilisation de copules paramétriques en présence de données observationnelles : cadre théorique et modélisations." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTT009/document.
Full textObservational studies (non-randomized) consist primarily of data with features that are in fact constraining within a classical statistical framework. Indeed, in this type of study, data are rarely continuous, complete, and independent of the therapeutic arm the observations are belonging to. This thesis deals with the use of a parametric statistical tool based on the dependence between the data, using several scenarios related to observational studies. Indeed, thanks to the theorem of Sklar (1959), parametric copulas have become a topic of interest in biostatistics. To begin with, we present the basic concepts of copulas, as well as the main measures of association based on the concordance founded on an analysis of the literature. Then, we give three examples of application of models of parametric copulas for as many cases of specific data found in observational studies. We first propose a strategy of modeling cost-effectiveness analysis based essentially on rewriting the joint distribution functions, while discarding the use of linear regression models. We then study the constraints relative to discrete data, particularly in a context of non-unicity of the copula function. We rewrite the propensity score, thanks to an innovative approach based on the extension of a sub-copula. Finally, we introduce a particular type of missing data: right censored data, in a regression context, through the use of semi-parametric copulas
Sandu, Leontina. "Inversion de modèles paramétriques : application aux mesures indirectes de températures." Paris 11, 1996. http://www.theses.fr/1996PA112343.
Full textThe general context of this work is the non-linear reconstruction of a mesurand or so-called the non-linear inverse problem with a very small data set. We are concerned with an inverse problem of heat conduction that deals with the determination of the internaI temperature from measured temperatures outside a heat conducting body. Ln order to solve this measurement problem, we propose different modelling techniques: analytical, numerical and the tehnique using external parametric models. Good existing results obtained from parametric estimation of temperature profiles lead us to study more deeply the external parametric models. Previous work has also demonstrated the interest of parametric functions as forward model for other applications. Those functions are simple to implement and result in good pelformance of the inversion process. We study the problem of construction of some candidates for parametric models. The discrimination between candidates is studied. Some theoretical notions for construction of parametric functions are advanced. We demonstrate that the choice of the parametric function depends on the significant quantity to estimate. This quantity could be the parameter vector, the model function in some points "inaccessible" to observation or an other parametric function. The proposed criteria choose the "best" function with respect to the inversion goal using the information gained in the experiment. The best model will be specific to the measurement goal and must be "sufficiently" close to real observations. Instruments for temperature measurement or other physical quantities measurement could include this type of model
Argoul, Pierre. "Identification des structures vibrantes." Marne-la-vallée, ENPC, 1990. https://hal-enpc.archives-ouvertes.fr/tel-04010926.
Full textThe study of the identification of mechanical structures under vibration involves a double approach : the search for mechanical models representative of the observed phenomena and the search for identification techniques for these models from adapted vibratory tests. The first part of this work gives the definition of the external and internal representations of the behaviour of structures. If the external representation is based on basic mathematical theorems, which precise the form of the operator of the behaviour, the internal representation is linked to the rules of the continuum media dynamics which are recalled in a continuous form and then discretized within the frame of a variational formulation. The modelization of the linear dissipative effects is then studied using linear viscoelasticity theory. We note that the model with constant quality factor and the hysteretic one can be defined with the basic element of models using fractionnal derivatives. The second part gives an overview of some identification procedures which are classified according to the properties of the model and particularly the distinction made between parametric and non-parametric. The causality of identified systems and the risk of linking the loss of causality for a mechanical system to the possible presence of a non-linearity are amphasized. Two new identification methods are presented and tested on numerical example. The first, suitable for linear strongly damped systems, is based on the property of dynamic ampliciation of a weighted integral transform. Its computation allows an estimation of the poles and zeros of a transfer function without making any assumption on the type of real damping. The second one seeks for the best approximation of the restoring forces as a double sum of Chebyshev polynomials. This technique doesn’t make any « a priori » assumption on the structural behaviour. The proposed improvements of the interpolation and extrapolation procedures in the space yield good results when the expression of the restoring forces contains displacements-velocity or modal coupling terms
Das Studium der vibrierenden mechanischen Strukturen beinhaltet zwei Forschungsrichtungen : Die Suche nachden die beobachteten Phänomene repräsentierenden mechanischen Modellen, und die Suche nach Identifikationstechniken dieser Modelle ausgehend von experimentellen Tests. Im ersten Teil dieser Arbeit werden die externen un internen Repräsentationsformen des Strukturverhaltens definiers. Die externe Darstellung basiers auf mathematischen Grundsätzen, die die Form der Verhaltensfunktion bestimmen : wohingegen sich die interne Darstellund durch die Gesetze der Dynamik kontinuierlicher Système ausdrückt, die im Rahmen der Variationstheorie in diskretisierter Form angewendet werden. Dis Modellisierung der Streuungseffekte wird in der Form von linear Viskoelastizität studiert. Es wird gezeigt, daß hysteretische Modelle und Modelle, die konstante Qualitätsfaktoren benutzen, auf der Basis von Modellen definiert werder können, die gebrochenrationale Ableitungsfunktionen benutzen. Der zweite Teil bietet einen Überblick über die Menge der Identifikationsprozeduren. Die Klassifizierung wird gemäß der Eigenschaften der Modelle und der Unterscheidung zwischen parametrisierten und nicht parametrisierten Modellen vorgenommen. Der Schwerpunkt liegt auf den kausalen Zusammenhängen der identifizierten Systeme und auf dem Risiko der Verbindung eines Kausalitätsverlustes mit einer evtl. Vorhandenen Nichtlinearität. Zwei neue Identifikationsmethoden werden vorgestellt und an numerischen Beispielen getestet. Das erste Beispiel, der Fall eines stark gedämpften linearen Systems, basiert auf der Verstärkungseigenschaft einer integralen gewichteten Transformation. Seine Berechnung ermöglicht die Abschätzung der Pole und Nullstellen einer Übertragungsfunktion, ohne daß eine Hypothese des Dämpfungsmodells der Struktur benötiget wird. Die zweite Methode sucht nach der besten zweidimensionalen Approximation der inneren Kräfte durch Tchebyscheff Polynome. Diese Technik macht keine a priori Annahme über das Verhalten der Struktur. Die vorgeschlagenen Verbesserungen des Glättungsprozesses der inneren Kräfte im Zustandsraum ergeben gute Resultate, wenn die Beschreibung dieser Kräfte Terme enthält, die Geschwindigkeit une Deplazierung verbinden
Laouti, Nassim. "Diagnostic de défauts par les Machines à Vecteurs Supports : application à différents systèmes mutivariables nonlinéaires." Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00985437.
Full textBoumegoura, Tarek. "Recherche de signature électromagnétique des défauts dans une machine synchrone et synthèse d'observateurs en vue du diagnostic." Ecully, Ecole centrale de Lyon, 2001. http://www.theses.fr/2001ECDL0008.
Full textElectrical traction use more and more the asynchronous machines because of their robustness, their power weight ratio. Their maintenance as well as their diagnosis then became an economic state. It is important to early detect the faults likely to appear in those motors and therefor to implement a preventive maintenance. Thus, a detailed model of the machine was developed in order to analyse the impact of those faults on the machine performance. We could then get specific signatures for electrical faults and foresee their evolution. Our approach is based on keeping a close watch over parameters of the performance model of the machine perticularly sensitive to faults : the rotor resistances of three phase model, the magetising inductance and the rotoric resistance of a two phase model. Some tools for detecting motor faults, based on extended Kalman and High Gain observes adapted to non-linear systems, were workout to record these parameters. They were successfully tested on data from a motor bench as well as on data from finite element model