44 results on '"Aknin, Patrice"'
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2. Confiance.ai Days 2022. Booklet of articles & posters
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Aknin, Patrice, Braunschweig, Bertrand, Cantat, Loic, Chamroukhi, Faïcel, Hebrail, Georges, Jurie, Frédéric, Loesch, Angelique, Mattioli, Juliette, Oller, Guillaume, IRT SystemX, Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), SAFRAN Group, Département Intelligence Ambiante et Systèmes Interactifs (DIASI), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, THALES [France], and IRT Saint Exupéry - Institut de Recherche Technologique
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ODD ,[STAT.ML]Statistics [stat]/Machine Learning [stat.ML] ,trustworthy ,AI-based systems ,V&V ,[INFO]Computer Science [cs] ,Robust AI ,Explainability ,Embedded AI ,critical systems - Abstract
Conférence: Confiance.ai Days, 4 au 6 octobre 2022, CentraleSupélec, Gif-sur-Yvette (France); This booklet gathers 52 papers, either in the form of articles or posters, presented during the secondedition of the Confiance.ai Days held in Saclay on October 4-6, 2022. Altogether they give a good snapshotof the research and development work done in the Confiance.ai program, an industrial and academicinitiative of the national Grand Challenge on provable and certifiable AI, launched in support of the France2030 strategy.Among these papers, a dozen are presented as « external contributions » that were selected by an ad-hoccommittee following a call for papers. All other communications belonged to one of five so-called « villages» with physical implementation in the conference hall, distributing the work done in Confiance.ai intofive topics : « End-to-end approach » ; « from Operational Design Domain to Data » ; « Explainabilityand Understanding» ; « Robustness and Monitoring » ; « Embedded AI ».After two years of activity, and complementing the Confiance.ai white paper, this document shows thediversity and the quality of the work done in the programme. Some important and up-to-date subjects areaddressed, such as – only to name a few - out-of-distribution detection, adversarial robustness, semi- orself-supervised learning, explainability by design, verification and validation, embedded AI etc. We hopethat you will enjoy reading parts of this document as much as we enjoyed preparing and attending the 2022Confiance AI days.
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- 2023
3. Dynamic bayesian networks for reliability analysis: from a Markovian point of view to semi-markovian approaches
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Foulliaron, Josquin, Bouillaut, Laurent, Barros, Anne, and Aknin, Patrice
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- 2015
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4. A hidden process regression model for functional data description. Application to curve discrimination
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Chamroukhi, Faicel, Samé, Allou, Govaert, Gérard, and Aknin, Patrice
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- 2010
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5. A dynamic Bayesian network to represent discrete duration models
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Donat, Roland, Leray, Philippe, Bouillaut, Laurent, and Aknin, Patrice
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- 2010
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6. Time series modeling by a regression approach based on a latent process
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Chamroukhi, Faicel, Samé, Allou, Govaert, Gérard, and Aknin, Patrice
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- 2009
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7. Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints
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Côme, Etienne, Oukhellou, Latifa, Denœux, Thierry, and Aknin, Patrice
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- 2012
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8. Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis
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Cherfi, Zohra L., Oukhellou, Latifa, Côme, Etienne, Denœux, Thierry, and Aknin, Patrice
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- 2012
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9. Model-based clustering and segmentation of time series with changes in regime
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Samé, Allou, Chamroukhi, Faicel, Govaert, Gérard, and Aknin, Patrice
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- 2011
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10. Mixture-model-based signal denoising
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Samé, Allou, Oukhellou, Latifa, Côme, Etienne, and Aknin, Patrice
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- 2007
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11. DESIGNING THE MISSING LINK BETWEEN SCIENCE AND INDUSTRY: ORGANIZING PARTNERSHIP BASED ON DUAL GENERATIVITY
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Chen, Milena, Aknin, Patrice, Lagadec, Lilly-Rose, Laousse, Dominique, Masson, Pascal, Weil, Benoit, IRT SystemX (IRT SystemX), Innovation & Research, SNCF, Centre de Gestion Scientifique i3 (CGS i3), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-MINES ParisTech - École nationale supérieure des mines de Paris, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
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[SHS.GESTION]Humanities and Social Sciences/Business administration - Abstract
International audience; Industry-academic research partnerships are mostly considered interesting to increase industrial innovativeness, and its benefits have been discussed in the flourishing open innovation literature. However, how to create mutually beneficial partnerships seems to be a question that has not been sufficiently studied. Through this article, we discuss the goals of these partnerships by modelling different types of collaboration. We defend that their real value has to be evaluated not only by looking at the knowledge created, but also at the increase of generativity we observe, due to interactions between academia and industry. Furthermore, we propose a model based on C-K theory that can be used to design a research collaboration that increases generativity, going beyond problem solving and knowledge transfer logics. We illustrate it through a case study, which shows that value creation in an industry-research partnership is increased by a model of co-generation, instead of considering these relations as a one-way transfer. Furthermore, we show that conflicts in a partnership can be solved through a C-K based tool.
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- 2017
12. A specific semi-markovian dynamic bayesian network estimating residual useful life
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FOULLIARON, Josquin, Bouillaut, Laurent, Aknin, Patrice, Barros, Anne, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, SNCF : Innovation & Recherche, SNCF, Department of Computer and Information Science [Trondheim] (IDI), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU)-Norwegian University of Science and Technology (NTNU), and ANR - Diadem
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MODELE MATHEMATIQUE ,MODELE GRAPHIQUE PROBABILISTE ,DUREE DE VIE ,FIABILITE ,GRAPHICAL DURATION MODEL ,RESIDUAL USEFUL LIFE ESTIMATION ,DYNAMIC BAYESIAN NETWORK ,RESEAU BAYESIEN ,SEMI MARKOVIAN DEGRADATION PROCESS MODELLING ,CYCLE DE VIE ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation - Abstract
16th ASMDA Conference, LE PIREE, GRECE, 30-/06/2015 - 04/07/2015; Degradation processes modelling is a key problem to perform any type of reliability study. Indeed, the quality of the computed reliability indicators and prognosis estimations directly depends on this modelling. Mathematical models commonly used in reliability (Markov chains, Gamma processes...) are based on some assumptions that can lead to a loss of information on the degradation dynamic. In many studies, Dynamic Bayesian Networks (DBN) have been proved relevant to represent multicomponent complex systems and to perform reliability studies. In a previous paper, we introduced a, degradation model based on DBN named graphical duration model (GDM) in order to represent a wide range of duration models. This paper will introduce a new degradation model based on GDM integrating the concept of conditional sojourn time distributions in order to improve the degradation modelling. It integrates the possibility to take into account several degradation modes together and to adapt the degradation modelling in respect of some new available observations of either the current operation state or the estimated degradation level, to take into account an eventual dynamic change. A comparative study on simulated data between the presented model and the GDM will be performed to show the interest of this new approach.
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- 2015
13. Spatio-temporal Analysis of Dynamic Origin-Destination Data Using Latent Dirichlet Allocation: Application to Vélib' Bike Sharing System of Paris
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COME, Etienne, RANDRIAMANAMIHAGA, Njato Andry, Oukhellou, Latifa, Aknin, Patrice, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, and Cadic, Ifsttar
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[SHS.STAT]Humanities and Social Sciences/Methods and statistics ,[SHS.STAT] Humanities and Social Sciences/Methods and statistics ,BASE DE DONNEES - Abstract
This paper deals with a data mining approach applied on Bike Sharing System Origin-Destination data, but part of the proposed methodology can be used to analyze other modes of transport that similarly generate Dynamic Origin-Destination (OD) matrices. The transportation network investigated in this paper is the Vélib’ Bike Sharing System (BSS) system deployed in Paris since 2007. An approach based on Latent Dirichlet Allocation (LDA), that extracts the main features of the spatio-temporal behavior of the BSS is introduced in this paper. Such approach aims to summarize the behavior of the system by extracting few OD-templates, interpreted as typical and temporally localized demand profiles. The spatial analysis of the obtained templates can be used to give insights into the system behavior and the underlying urban phenomena linked to city dynamics.
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- 2014
14. How to keep optimal maintenance strategies with a dynamic optimization approach?
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ROZAS, Rony, Bouillaut, Laurent, Aknin, Patrice, BRANGER, Guillaume, Cadic, Ifsttar, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, and Bombardier Transportation
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[SPI.OTHER]Engineering Sciences [physics]/Other ,MAINTENANCE ,OPTIMUM ,[SPI.OTHER] Engineering Sciences [physics]/Other ,OPTIMISATION ,DEGRADATION ,MATERIEL ROULANT ,ENTRETIEN - Abstract
The optimization of maintenance strategies has become a key issue in the railway industry but also in most industrial fields. To address this challenge, many studies dealt with the estimation of optimal maintenance parameters. But what commonly happens when the degradation process suddenly changes? The operator has to face an unexpected, increasing number of severe defects (and then a strong drop of its availability). These changes are generally due to either: a new component, introduced in the system for obsolescence reasons; or changing operating conditions. Based on the dynamic Bayesian networks (DBN), formalism that has been proved relevant to perform reliability analysis can easily represent complex system behaviors. This paper introduces a dynamic maintenance strategy, able to detect these drifts and to evaluate their impacts on the rolling stock doors system’s behavior.
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- 2014
15. Mod\'ele \'a processus latent et algorithme EM pour la r\'egression non lin\'eaire
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Chamroukhi, Faicel, Samé, Allou, Govaert, Gérard, and Aknin, Patrice
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Statistics::Machine Learning ,Computer Science - Learning ,Statistics - Machine Learning ,Statistics::Methodology ,Mathematics - Statistics Theory ,Statistics - Methodology - Abstract
A non linear regression approach which consists of a specific regression model incorporating a latent process, allowing various polynomial regression models to be activated preferentially and smoothly, is introduced in this paper. The model parameters are estimated by maximum likelihood performed via a dedicated expecation-maximization (EM) algorithm. An experimental study using simulated and real data sets reveals good performances of the proposed approach.
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- 2013
16. A rollingstock door system’s dynamic maintenance strategies based on a sensitivity analysis through bayesian networks
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Rozas, Rony, Bouillaut, Laurent, Aknin, Patrice, Same, Allou, Francois, Olivier, Branger, Guillaume, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Bombardier Transportation, and Cadic, Ifsttar
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[SPI.OTHER]Engineering Sciences [physics]/Other ,MAINTENANCE ,[SPI.OTHER] Engineering Sciences [physics]/Other - Abstract
In most industrial fields, and particularly in the railway industry, the optimization of maintenance policies has become a key issue. Dynamic Bayesian networks (DBN) have been proved as relevant to perform reliability analysis as they can easily represent complex systems behaviors. Based on this formalism, graphical duration models (GDM) were developed by (Donat, et al., 2009) to set all kind of sojourn time distributions for each state of the system. Unlike to some Markovian approaches that impose exponential behavior, this approach could better model the exact degradation dynamic of real industrial systems. But, what commonly happens when the degradation process suddenly changes? The operator has to face with an unexpected increasing number of severe defects (and then a strong drop of its availability). These changes are generally due to either new component, introduced in the system for obsolescence reasons, or to changing operating conditions. The aim of the study introduced in this paper, focusing on Dynamic Maintenance Strategies, is to detect these drifts and to evaluate their impacts on the system’s behavior.
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- 2013
17. Online predictive diagnosis of electrical train door systems
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Han, Yufei, Francois, Olivier, Same, Allou, Bouillaut, Laurent, Oukhellou, Latifa, Aknin, Patrice, Branger, Guillaume, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, BOMBARDIER TRANSPORT FRANCE SAS, and Cadic, Ifsttar
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DIAGNOSTIC ,MAINTENANCE ,TRAIN - Abstract
Considering availability purposes for train transportation, passenger accesses (doors and steps) are often designated as critical systems. To improve global availability of its rolling stock, Bombardier Transportation (BT) aims at reinforcing its maintenance procedure by introducing predictive diagnosis. The SURFER project has been initiated to develop online and in-cars tools to early detect and prevent faults. In this paper, an overview of achieved progress with respect to online predictive diagnosis will be introduced. For this purpose, many signals are recorded using a test bench by BT: electrical motor intensity current, door displacement, binary indicators as door closed and locked. The paper focuses on designing a semi-Supervised discriminative probabilistic model that take into account contextual variables (train inclination or constraints due to passengers affluence) to perform a robust predictive diagnosis. The main steps of the proposed method are the followings: the segmentation of the provided signals into opening and closing phases, the extraction of relevant features from opening/closing phases, the setting of the discriminative diagnosis model based on statistical semi-supervised learning. The proposed approach is tested on signals collected from regional trains fleeting around Paris. It allows the earlier detection of anomalies, for instance, those due to maladjustments. The practical implementation of this approach will be detailed together with its preliminary results.
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- 2013
18. State-space modeling of a sequence of curves application to the condition condition monitoring of railway switches
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Same, Allou, EL ASSAAD, Hani, Aknin, Patrice, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, and Cadic, Ifsttar
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[SPI.OTHER]Engineering Sciences [physics]/Other ,[SPI.OTHER] Engineering Sciences [physics]/Other ,SURVEILLANCE - Abstract
This article introduces a state-space model for the dynamic modeling of curve sequences within the framework of railway switches online monitoring. In this context, each curve has the peculiarity of being subject to multiple changes in regime. The proposed model consists of a specific latent variable regression model whose coefficients are supposed to evolve dynamically in the course of time. Its parameters are recursively estimated across a sequence of curves through an online Expectation-Maximization (EM) algorithm. The experimental study conducted on two real power consumption curve sequences from the French high speed network has shown encouraging results.
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- 2013
19. A mixture of Kalman filters for online monitoring of railway switches
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Same, Allou, EL ASSAAD, Hani, Aknin, Patrice, Govaert, Gérard, Antoni, Marc, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), SNCF, Direction Contrats et Services Clients, Pôle Technique Ingénierie de Maintenance, and Cadic, Ifsttar
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[SPI.OTHER]Engineering Sciences [physics]/Other ,DIAGNOSTIC ,[SPI.OTHER] Engineering Sciences [physics]/Other ,SURVEILLANCE - Abstract
International audience; Assessing the operating state of the railway infrastructure and rolling stock using condition measurements acquired through embedded sensors has become a powerful decision-making support for preventive maintenance strategies. This article introduces a dynamic approach for the online monitoring of railway switch operations. The method is based on modeling the power consumption curves acquired during successive switch operations using conjointly five polynomial regression models whose coefficients are dynamically estimated across a sequence of curves. The experimental study conducted on two real power consumption curve sequences from the French high speed network has shown encouraging results in terms of characterization of the temporal evolution of railway switch operations.
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- 2013
20. A Probabilistic Graphical Models approach for rail prognosis based maintenance in a periodic observations context
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FOULLIARON, Josquin, Bouillaut, Laurent, Barros, Anne, Aknin, Patrice, ROZAS, Rony, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Laboratoire Modélisation et Sûreté des Systèmes (LM2S), Institut Charles Delaunay (ICD), and Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)
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[SPI.OTHER]Engineering Sciences [physics]/Other ,MAINTENANCE - Abstract
In most industrial fields, and particularly in the railway industry, the optimization of maintenance policies has become a key issue. To address this problem, predictive maintenance seems to be one of the most effective known approaches. It consists of driving the maintenance process anticipating the evolution of the system state. A prediction process, called "prognosis" could also be introduced and it lays on the online estimation of the remaining useful life (RUL). Dynamic Bayesian networks (DBN) have been proved as relevant to perform reliability analysis as they can easily represent complex systems behaviors. Based on this formalism, graphical duration models (GDM) were developed by (Donat 2009) to set all kind of sojourn time distributions for each state of the system. Unlike to some Markovian approaches that impose exponential behavior, this approach could better model the exact degradation dynamic of real industrial systems. In our study, where time and states space are discretized, we consider rail degradation whom process is assumed to be monotone increasing. The real state of rails is unknown but periodically observed by an ultrasonic vehicle, characterized by its good detections rates, false alarms rates and non detection rates. This paper introduces an online RUL estimation algorithm based on the use of graphical duration models. The objective is both to evaluate the RUL and to adjust it, in real time, when a new observation is available. Then, the algorithm is applied to the rail degradation example to evaluate the quality of the RUL estimations. This paper will also provide some comparative results in respect of the considered degradation model (Markovian approach vs GDM). Finally, these RUL computations, and the associated estimations of the future system behavior, will be subsequently used to optimize the rail maintenance strategy and its diagnosis schedule.
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- 2013
21. Fuel Cell Health Monitoring Using Self Organizing Maps
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ONANENA, Raissa, Oukhellou, Latifa, COME, Etienne, Jemei, Samir, Candusso, Denis, Hissel, Daniel, Aknin, Patrice, Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Direction scientifique (IFSTTAR/DS), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Laboratoire Commun de Belfort : Hydrogène et Pile à Combustible pour les applications au transport (FC LAB), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Laboratoire Transports et Environnement (IFSTTAR/AME/LTE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-Université de Lyon-Laboratoire des Technologies Nouvelles (IFSTTAR/COSYS/LTN), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Technologie de Belfort-Montbeliard (UTBM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Laboratoire des Technologies Nouvelles (IFSTTAR/COSYS/LTN), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Laboratoire Transports et Environnement (IFSTTAR/AME/LTE), and Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-Université de Lyon
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lcsh:Computer engineering. Computer hardware ,DUREE DE VIE ,[PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Mechanics of the fluids [physics.class-ph] ,SURVEILLANCE ,[SPI.NRJ]Engineering Sciences [physics]/Electric power ,[PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph] ,lcsh:TP155-156 ,lcsh:TK7885-7895 ,lcsh:Chemical engineering ,[SPI.AUTO]Engineering Sciences [physics]/Automatic - Abstract
International audience; The problem of durability of fuel cell technology is central for its spreading and commercialization. There is therefore a growing need to build accurate diagnosis tools which can give the operating state of the fuel cell during their use. When supervised machine learning approaches are used to build such diagnosis tools, they generally require a large amount of labeled data. Collection and annotation of data can be either difficult to perform or time consuming. In this paper, authors are interested in the monitoring of fuel cells in an unsupervised framework, meaning that no labels are required to learn the diagnosis model. The aim is to build a monitoring tool able to easily visualize the State Of Health of full cells fromelectrochemical impedance spectroscopy measures, showing thus its evolution from fault free case ("normal" behaviour) to defective classes such as drying or flooding. The proposed approach is based on Self Organizing Maps (SOM) which have shown their performance to solve fault detection and prediction in many industrial systems. By automatically visualizing the data into a two-dimensional space, the interpretation of the results have become easy and instinctive. The approach also allows the clustering of the data into different groups of classes, thus enabling the classification of new observations. Experimental results carried out on real data sets have shown the efficiency of the proposed approach with respect to standard supervised and unsupervised classification approaches.
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- 2013
22. A dynamic probabilistic modeling of railway switches operating states
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Same, Allou, Chamroukhi, Faicel, Aknin, Patrice, Antoni, Marc, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Laboratoire des Technologies Nouvelles (IFSTTAR/LTN), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), SNCF Direction de l'infrastructure, and parent
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[SPI.OTHER]Engineering Sciences [physics]/Other ,MAINTENANCE ,COMMUTATEUR ,VOIE FERREE ,TELESURVEILLANCE - Abstract
WCRR 2011 - 9th World Congress on Railway Research, LILLE, FRANCE, 22-/05/2011 - 26/05/2011; The remote monitoring of the railway infrastructure and particularly the switch mechanism is of great interest for railway operators. The problem consists in detecting earlier the presence of defects in order to alert the concerned maintenance service before a breakdown occurs. For this purpose, this paper introduces a new probabilistic-based approach to dynamically modeling the evolution of condition measurements acquired during switch operations. It consists of two steps. The feature extraction from the electrical power consumption signals which aims at summarizing each signal by a low dimensional feature vector. Then, a specific autoregressive model is proposed to model the dynamical behavior of the switch mechanism.
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- 2011
23. A regression model with a hidden logistic process for feature extraction from time serie
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Chamroukhi, Faicel, Samé, Allou, Govaert, Gérard, Aknin, Patrice, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Technologies Nouvelles (INRETS/LTN), and Institut National de Recherche sur les Transports et leur Sécurité (INRETS)
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[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH] - Abstract
International audience; A new approach for feature extraction from time series is proposed in this paper. This approach consists of a specific regression model incorporating a discrete hidden logistic process. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The parameters of the hidden logistic process, in the inner loop of the EM algorithm, are estimated using a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm. A piecewise regression algorithm and its iterative variant have also been considered for comparisons. An experimental study using simulated and real data reveals good performances of the proposed approach.
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- 2009
24. Réseaux bayésiens dynamiques pour la représentation de modèles de durée en temps discret
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Donat, Roland, Leray, Philippe, Bouillaut, Laurent, Aknin, Patrice, Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), Laboratoire d'Informatique de Nantes Atlantique (LINA), Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN), Laboratoire des Technologies Nouvelles (INRETS/LTN), and Institut National de Recherche sur les Transports et leur Sécurité (INRETS)
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modèles graphiques de durée ,[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] ,Modèles graphiques probabilistes ,fiabilité - Abstract
12 pages; Originally devoted to specific applications such as biology, medicine and demography, the duration models are now widely used in economy, finance or reliability. Some recent works in reliability analysis have been proved relevant the use of bayesian networks. In this paper, we describe a specific dynamic bayesian network, named graphical duration model (GDM), to represent generic duration model adapted to multi-state systems featuring complex sojourntime distributions and context dependencies
- Published
- 2008
25. A dynamic graphical model to represent complex survival distributions
- Author
-
Donat, Roland, Bouillaut, Laurent, Aknin, Patrice, Leray, Philippe, Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), Laboratoire des Technologies Nouvelles (INRETS/LTN), Institut National de Recherche sur les Transports et leur Sécurité (INRETS), Laboratoire d'Informatique de Nantes Atlantique (LINA), and Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN)
- Subjects
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] ,Graphical duration models ,Reliability ,Probabilistic graphical models - Abstract
Reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks. Moreover, recent works in reliability involving the use of probabilistic graphical models, also known as bayesian networks, have been proved relevant. This paper describes a specific dynamic graphical model, named graphical duration model (GDM), to represent complex stochastic degradation processes with any kind of state sojourn time distributions. We give qualitative and quantitative descriptions of the proposed model and detail a simple algorithm to estimate the system reliability. Finally, we illustrate our approach with a three-states system subjected to one context variable and non-exponential sojourn time distributions.
- Published
- 2008
26. A generic approach to model complex system reliability using graphical duration models
- Author
-
Donat, Roland, Bouillaut, Laurent, Aknin, Patrice, Leray, Philippe, Levy, D., Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), Laboratoire des Technologies Nouvelles (INRETS/LTN), Institut National de Recherche sur les Transports et leur Sécurité (INRETS), Laboratoire d'Informatique de Nantes Atlantique (LINA), and Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN)
- Subjects
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] - Abstract
Nowadays, reliability analysis has become an integral part of system design and operating. This is especially true for systems performing critical tasks. Moreover, recent works in reliability involving the use of probabilistic graphical models, also known as bayesian networks, have been proved relevant. This paper aims to describe a general methodology to model the stochastic degradation process of a complex system, allowing any kind of state sojourn distributions along with an accurate context description. We meet these objectives using a specific dynamic graphical model, namely a graphical duration model. In this article, we give qualitative and quantitative descriptions of the proposed model and describe a simple algorithm to estimate the system reliability and some of its related metrics. Finally, we illustrate this approach by applying our methodology to a three-states system subjected to one context variable and with non exponential duration distributions.
- Published
- 2007
27. Pattern recognition approach for the prediction of infrequent target events in floating train data sequences within a predictive maintenance framework.
- Author
-
Sammouri, Wissam, Come, Etienne, Oukhellou, Latifa, Aknin, Patrice, and Fonlladosa, Charles-Eric
- Published
- 2014
- Full Text
- View/download PDF
28. Floating train data systems for preventive maintenance: A data mining approach.
- Author
-
Sammouri, Wissam, Come, Etienne, Oukhellou, Latifa, Aknin, Patrice, and Fonlladosa, Charles-Eric
- Published
- 2013
29. Mining Floating Train Data Sequences for Temporal Association Rules within a Predictive Maintenance Framework.
- Author
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Sammouri, Wissam, Côme, Etienne, Oukhellou, Latifa, and Aknin, Patrice
- Published
- 2013
- Full Text
- View/download PDF
30. A Sequential Testing Procedure for Multiple Change-Point Detection in a Stream of Pneumatic Door Signatures.
- Author
-
Cheifetz, Nicolas, Same, Allou, Aknin, Patrice, Verdalle, Emmanuel De, and Chenu, Damien
- Published
- 2013
- Full Text
- View/download PDF
31. Model-Based Clustering of Temporal Data.
- Author
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El Assaad, Hani, Samé, Allou, Govaert, Gérard, and Aknin, Patrice
- Published
- 2013
- Full Text
- View/download PDF
32. A sequential testing approach for change-point detection on bus door systems.
- Author
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Cheifetz, Nicolas, Same, Allou, Aknin, Patrice, and de Verdalle, Emmanuel
- Abstract
Detecting change-points and anomalies on sequential data is common in various domains such as fraud detection for credit cards, intrusion detection for cyber-security or military surveillance [1]. This study is motivated by the predictive maintenance of pneumatic doors in transit buses. For this purpose, buses are instrumented and data are collected through embedded sensors. Inspired by the CUSUM and GLR approaches, this paper deals with on-line change-point detection on sequential data where each observation consists in a bivariate curve. The system is considered out of control when a change occurs in the curves probability distribution. A specific regression model is used to describe the curves. The unknown parameters of this model are estimated using the maximum likelihood principle. Experimental studies performed on realistic data demonstrate the promising behavior of the proposed method. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
33. Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis.
- Author
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Côme, Etienne, Oukhellou, Latifa, Denœux, Thierry, and Aknin, Patrice
- Abstract
In Independent Factor Analysis (IFA), latent components (or sources) are recovered from only their linear observed mixtures. Both the mixing process and the source densities (that are assumed to be generated according to mixtures of Gaussians) are learned from observed data. This paper investigates the possibility of estimating the IFA model in its noiseless setting when two kinds of prior information are incorporated: constraints on the mixing process and partial knowledge on the cluster membership of some examples. Semi-supervised or partially supervised learning frameworks can thus be handled. These two proposals have been initially motivated by a real-world application that concerns fault diagnosis of a railway device. Results from this application are provided to demonstrate the ability of our approach to enhance estimation accuracy and remove indeterminacy commonly encountered in unsupervised IFA such as source permutations. [ABSTRACT FROM AUTHOR]
- Published
- 2009
- Full Text
- View/download PDF
34. Railway device diagnosis using sparse Independent Component Analysis.
- Author
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Cherfi, Zohra L., Come, Etienne, Oukhellou, Latifa, and Aknin, Patrice
- Published
- 2009
35. A subspace method for detection and classification of rail defects.
- Author
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Mehel-Saidi, Zineb, Bloch, Gerard, and Aknin, Patrice
- Published
- 2008
36. A new decision criterion for feature selection application to the classification of non destructive testing signatures.
- Author
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Oukhellou, Latifa, Aknin, Patrice, Stoppiglia, Herve, and Dreyfus, Gerard
- Published
- 1998
37. A new approach for the modelling of track geometry recording vehicles and the deconvolution of versine measurements.
- Author
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Aknin, Patrice and Chollet, Hugues
- Subjects
- *
DECONVOLUTION (Mathematics) , *GEOMETRIC modeling , *MATHEMATICAL regularization , *SIGNAL-to-noise ratio , *CURVATURE , *RAILROAD tracks - Abstract
This article deals with railway track geometry in horizontal and vertical directions, and its measurement by means of track recording vehicle. The first part of the article introduces the mathematics tools for describing planar curves, mainly the "transformed curve" defined as the double integration of the algebraic local curvature, function of the curvilinear abscissa. The complete non linear model of the non-centered versine apparatus has been calculated in this space, as well as its simplification in the case of low local angular values. The main contribution of this article lies in the choice of algebraic local curvature as system input for the further inversion of experimental data. The following part describes the deconvolution procedure using the Wiener approach; therefore the optimal inverse filter becomes the multiplication of the direct inversion by a regularization function linked to the signal-to-noise ratio. Then, the direct modelling of the French Mauzin measurement system and the adapted inverse numerical filtering (in horizontal and vertical directions) are calculated. It is shown that the inverse procedure allows the deconvolution of track irregularities of up to 150m wavelengths. [ABSTRACT FROM AUTHOR]
- Published
- 1999
- Full Text
- View/download PDF
38. Dedicated Sensor and Classifier of Rail Head Defects for Railway Systems
- Author
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Oukhellou, Latifa, Aknin, Patrice, and Perrin, Jean-Paul
- Published
- 1997
- Full Text
- View/download PDF
39. Eddy current sensor for the measurement of a lateral displacement. Applications in the railway domain
- Author
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Aknin, Patrice, Placko, Dominique, and Ayasse, Jean-Bernard
- Published
- 1992
- Full Text
- View/download PDF
40. Adaptive mesh refinement in level set based body-fitted topology optimization
- Author
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Nardoni, Chiara, Danan, David, Ferro, Nicola, Perotto, Simona, Sekourane, Amine, and Aknin, Patrice
- Subjects
[SPI.MECA.SOLID] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Solid mechanics [physics.class-ph] ,level set method ,adaptive remeshing ,topology optimization ,anisotropic remeshing - Abstract
Topology optimization is devoted to the optimal design of structures. It aims at finding the best materialdistribution inside a working domain in order to satisfy mechanical, geometrical or manufacturingspecifications. The need for lighter and efficient structural solutions has made topology optimizationa vigorous research field in both academic and industrial structural engineering communities. In thepresent setting the level set method is coupled with a remeshing routine which enables the reconstructionof a body-fitted mesh at each step of the underlying optimization process. Since thestructural interface is known explicitely at each step of the iterative procedure, the body-fitted approachsimplifies the evaluation of the mechanical quantities of interest. The body-fitted remeshing strategy is driven by global user-defined parameters such as the minimal/maximal mesh size or thegradation of the desired mesh. In this contribution we propose to couple the body-fitted approach withadaptative remeshing techniques involving an anisotropic recovery-based a posteriori error analysis. Thegradient-recovery Zienkiewicz-Zhu-type error estimator is applied to drive isotropicor anisotropic mesh adaptation at each step of the underlying optimization process. The proposed errorestimator is used from one hand to control the accuracy of the discretization of the structural interface,from the other hand to control the discretization error linked to the numerical evaluation of mechanicalcriteria and sensitivities in order to speed up the overall optimization routine. All the proposed numericalexamples are realized using PISCO, a Research and Development software platform for shape andtopology optimization in active development at IRT SystemX. We rely on a gradient-flow optimizationalgorithm designed to decrease both the value of the objective function and the violation of the constraints.Several
- Published
- 2022
41. Physically based bead topology model coupled with electro-mechanical power source model applied for wire and arc additive manufacturing
- Author
-
C. Mang, X. Lorang, R. Tami, F. Rouchon, and Aknin, Patrice
- Subjects
Condensed Matter::Soft Condensed Matter ,Electro-mechanical power source ,Wire and arc additive manufacturing ,[SPI] Engineering Sciences [physics] ,Bead topology ,Young-Laplace equation ,[SPI.MECA.MEMA] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph] - Abstract
Metal additive manufacturing (MAM) has grown, in recent years, very strong interest in academic researches as well as industrial applications. Among MAM processes, wire and arc additive manufacturing (WAAM) became very popular through its advantages in manufacturing of medium and large-scale components.The present work is carried out in the framework of the WAS project which deals with WAAM process. The process relies on an automatized welding process in which a part is built by successively deposed metal bead.We propose a physically based bead topology model using the equilibrium between the hydrostatic pressure and the capillarity force, under two-dimensional hypothesis. This equilibrium can be described by the Young-Laplace equation. The proposed model can also estimate a bead topology which is deposed on a complex support such as an inclined or a curved one. To do so, the Young equation is used to balance the forces at tri-phase point. Moreover, a deposed melted metal volume is necessary for the bead topology model. By modelling a gas metal arc welding (GMAW) power source system, the volume can be estimated and be used as a physical parameter for the bead topology model. Combining the topology and the power source models, the coupling model allows to simulate the topology of a part made of deposed beads via WAAM. In addition to the modelling, experimental profiles of the beads are used to validate the model.
- Published
- 2022
42. Towards the engineering of trustworthy AI applications for critical systems - The Confiance.ai program
- Author
-
Morvan, Michel and Aknin, Patrice
- Subjects
[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] ,[INFO.INFO-PF] Computer Science [cs]/Performance [cs.PF] ,[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG] ,[STAT.ML] Statistics [stat]/Machine Learning [stat.ML] - Published
- 2022
43. Equilibre d’une goutte métallique liquide déposée sur un support quelconque dans le cadre de la fabrication additive arc-fil métallique
- Author
-
Mang, Chetra, Rouchon, François, Lorang, Xavier, and Aknin, Patrice
- Subjects
angle de contact hystérésis ,équation de Young- Laplace ,tension superficielle ,phénomène de humping ,[SPI.MECA] Engineering Sciences [physics]/Mechanics [physics.med-ph] - Abstract
Une goutte liquide peut adhérer sur une surface inclinée non-plane lorsque les angles de contacts avant et arrièrede la goutte sont différents (angle de contact hystérétiques). L’adhésion de cette goutte est liée aux forcescapillaires qui s’équilibrent avec la pression hydrostatique de la goutte. [Guéré 98] a proposé une formulationanalytique du critère d’équilibre d’une goutte d’eau sur un plan incliné (hypothèse de goutte sphérique).Cette communication présente l’extension du travail de Guéré pour l’équilibre de la goutte liquide sur unsupport quelconque. Ce travail réalisé dans le cadre du projet WAS SystemX est motivé par le procédé de fabricationadditive WAAM (Wire Arc Additive Manufacturing). Ce procédé se base sur le procédé de soudage automatisé,où une pièce est construite par dépôt de cordons successifs. Un cordon est généré par dépôt de gouttes métalliquesissu de fil fondu.Nous proposons un modèle géométrique de cordon déposé. Le profil du cordon est obtenu grâce à la résolution del’équation de Young-Laplace sous l’hypothèse de rayon de courbure sphérique. Dans le cadre de cette hypothèse, la méthode des volumes finis est utilisée pour l’évaluation numérique du critère d’équilibre d’une goutte surun support 3D quelconque. Le critère d’équilibre est ensuite validé par l’expression analytique de Guéré dansle cas du support plan incliné. Enfin, en utilisant le critère d’équilibre de la goutte sphérique, nous évaluons lecritère de humping en déterminant une taille limite de goutte, garantissant un cordon rectiligne sans défautsgéométriques.
- Published
- 2021
44. Fault diagnosis in railway track circuits using Dempster–Shafer classifier fusion
- Author
-
Oukhellou, Latifa, Debiolles, Alexandra, Denœux, Thierry, and Aknin, Patrice
- Subjects
- *
DEMPSTER-Shafer theory , *ARTIFICIAL neural networks , *PATTERN recognition systems , *DECISION trees , *CAPACITORS , *SHORT circuits , *LARGE scale systems - Abstract
Abstract: This paper addresses the problem of fault detection and isolation in railway track circuits. A track circuit can be considered as a large-scale system composed of a series of trimming capacitors located between a transmitter and a receiver. A defective capacitor affects not only its own inspection data (short circuit current) but also the measurements related to all capacitors located downstream (between the defective capacitor and the receiver). Here, the global fault detection and isolation problem is broken down into several local pattern recognition problems, each dedicated to one capacitor. The outputs from local neural network or decision tree classifiers are expressed using the Dempster–Shafer theory and combined to make a final decision on the detection and localization of a fault in the system. Experiments with simulated data show that correct detection rates over 99% and correct localization rates over 92% can be achieved using this approach, which represents a major improvement over the state of the art reference method. [Copyright &y& Elsevier]
- Published
- 2010
- Full Text
- View/download PDF
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