Tesis sobre el tema "Machine Diagnostic"
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Kříž, Petr. "Online vibrační diagnostika vřetene frézovacího stroje DATRON". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402508.
Texto completoZhong, Binglin. "Model building and machine fault diagnosis". Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340889.
Texto completoTcheeko, Lot. "Didacticiel d'apprentissage du diagnostic d'erreurs en langage machine". Paris 6, 1990. http://www.theses.fr/1990PA066332.
Texto completoRaoult, Olivier Lux Augustin Mossière Jacques Demogeot Jacques. "Diagnostic de pannes des systèmes complexes". S.l. : Université Grenoble 1, 2008. http://tel.archives-ouvertes.fr/tel-00332209.
Texto completoSOAVE, Elia. "Diagnostics and prognostics of rotating machines through cyclostationary methods and machine learning". Doctoral thesis, Università degli studi di Ferrara, 2022. http://hdl.handle.net/11392/2490999.
Texto completoNegli ultimi decenni, l’analisi vibrazionale è stata sfruttata per il monitoraggio di molti sistemi meccanici per applicazioni industriali. Nonostante molte pubblicazioni abbiano dimostrato come la diagnostica vibrazionale possa raggiungere risultati soddisfacenti, lo scenario industriale odierno è in profondo cambiamento, guidato dalla necessità di ridurre tempi e costi produttivi. In questa direzione, la ricerca deve concentrarsi sul miglioramento dell’efficienza computazionale delle tecniche di analisi del segnale applicate a fini diagnostici. Allo stesso modo, il mondo industriale richiede una sempre maggior attenzione per la manutenzione predittiva, al fine di stimare l’effettivo danneggiamento del sistema evitando così inutili fermi macchina per operazioni manutentive. In tale ambito, negli ultimi anni l’attività di ricerca si sta spostando verso lo sviluppo di modelli prognostici finalizzati alla stima della vita utile residua dei componenti. Tuttavia, è importante ricordare come i due ambiti siano strettamente connessi, essendo la diagnostica la base su cui fondare l’efficacia di ciascun modello prognostico. Su questa base, questa tesi è stata incentrata su queste due diverse, ma tra loro connesse, aree al fine di identificare e predire possibile cause di cedimento su macchine rotanti per applicazioni industriali. La prima parte della tesi è concentrata sullo sviluppo di un nuovo indicatore di blind deconvolution per l’identificazione di difetti su organi rotanti sulla base della teoria ciclostazionaria. Il criterio presentato vuole andare a ridurre il costo computazionale richiesto dalla blind deconvolution tramite l’utilizzo della serie di Fourier-Bessel grazie alla sua natura modulata, maggiormente affine alla tipica firma vibratoria del difetto. L’indicatore proposto viene accuratamente confrontato con il suo analogo basato sulla classica serie di Fourier considerando sia segnali simulati che segnali di vibrazione reali. Il confronto vuole dimostrare il miglioramento fornito dal nuovo criterio in termini sia di minor numero di operazioni richieste dall’algoritmo che di efficacia diagnostica anche in condizioni di segnale molto rumoroso. Il contributo innovativo di questa parte riguarda la combinazione di ciclostazionarietà e serie di Furier-Bessel che porta alla definizione di un nuovo criterio di blind deconvolution in grado di mantenere l’efficacia diagnostica della ciclostazionarietà ma con un minor tempo computazionale per venire incontro alle richieste del mondo industriale. La second parte riguarda la definizione di un nuovo modello prognostico, appartenente alla famiglia degli hidden Markov models, costruito partendo da una distribuzione Gaussiana generalizzata. L’obbiettivo del metodo proposto è una miglior riproduzione della reale distribuzione dei dati, in particolar modo negli ultimi stadi del danneggiamento. Infatti, la comparsa e l’evoluzione del difetto comporta una modifica della distribuzione delle osservazioni fra i diversi stati. Di conseguenza, una densità di probabilità generalizzata permette la modificazione della forma della distribuzione tramite diversi valori dei parametri del modello. Il metodo proposto viene confrontato con il classico hidden Markov model di base Gaussiana in termini di qualità di riproduzione della distribuzione e predizione della sequenza di stati tramite l’analisi di alcuni test di rottura su cuscinetti volventi e sistemi complessi. L’innovatività di questa parte è data dalla definizione di un algoritmo iterativo per la stima dei parametri del modello nell’ipotesi di distribuzione Gaussiana generalizzata, sia nel caso monovariato che multivariato, partendo dalle osservazioni sul sistema fisico in esame.
Keuneke, Anne Marie. "Machine understanding of devices causal explanation of diagnostic conclusions /". The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487671640057361.
Texto completoAbed, Aïcha. "Contribution à l'étude et au diagnostic de la machine asynchrone". Nancy 1, 2002. http://www.theses.fr/2002NAN10020.
Texto completoUsed in the majority of the electric drives, the asynchronous machine tends to supplant the machine with D. C. Current as well as the synchronous machine because of its many qualities, and mainly of its low cost and its robustness. Thus, a general reflexion is committed in modeling and diagnostic of induction machine defects. More particularly, we propose to study the rotor defects (broken bars in the rotor). In the first time, we develop two models of the asynchronous machine for the simulation of broken bars. We present in the continuation three methods to detect this fault. The principle of detection is based on the spectral analysis of the stator current in order to follow the evolution of the frequencies which are related to the fault. Lastly, a study of the defect in the presence of a classical vector control is presented, opening a new way towards a diagnostic in the case of speed variation. An experimental part is carried out to validate the exactitude of the theoretical results and to show the effectiveness of the developed methods
Bachir, Smaïl. "Contribution au diagnostic de la machine asynchrone par estimation paramétrique". Poitiers, 2002. http://www.theses.fr/2002POIT2306.
Texto completoKass, Souhayb. "Diagnostic vibratoire autonome des roulements". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI103.
Texto completoThe industrial and transportation sectors require more and more efficient and complex machines and installations increasing the risk of failure and disruption. This can lead to the immediate shutdown of a machine and disrupts the proper functioning of the entire production system. The diagnosis of industrial machines is essentially based on the monitoring of symptoms related to different degradation conditions. These symptoms can be derived from various sources of information, including vibration and acoustic signals. Nowadays, many effective techniques are well established, based on powerful tools offered by the theory of cyclostationary processes. The complexity of these tools requires an expert to use them and to interpret the results based on his/her experience. The continuous presence of the expert is expensive and difficult to achieve in practice. Condition indicators for rotating machines exist in the literature but they are conceived under the assumption of perfect operating conditions. They are limited, dispersed and generally not supported by theoretical frameworks. The main objective of this thesis is to reduce the use of human intervention by proposing strategies to design two optimal indicators that summarize diagnostic information into a scalar value. A distinction is made between two families in diagnosis: the case where prior information on the faults is known and the case where it is unknown. These indicators are designed to be used in an autonomous process without requiring human intervention, using statistical hypothesis tests. The capacity of these indicators is validated on real data and compared with other indicators from the literature in terms of detection performance
Hrbáček, Vlastimil. "Návrh provozních mezí pro diagnostický systém obráběcího stroje". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417438.
Texto completoCeban, Andrian. "Méthode globale de diagnostic des machines électriques". Thesis, Artois, 2012. http://www.theses.fr/2012ARTO0202/document.
Texto completoThe work described in this thesis proposes new procedures to diagnose faults in AC machines. The diagnostic procedures described are reliable, original, inexpensive and simple to implement. They have the advantage of being noninvasive and just get rid from the main drawback presented by other diagnostic methods based on a comparison with a healthy state assumed to be known. The analysis focuses on the magnetic field dispersion in the vicinity of the machine, especially its radial an axial distribution which presents different sensitivity according to various faults. To this end, the phenomena due to inter-turn short-circuit faults in the stator winding, rotor eccentricity and broken rotor bars, are studied in the case of an induction machine and a synchronous machine. For each fault, specific signatures are identified and justified by analytical modeling and numerical method of analysis including coupled electric circuit and finite element methods. Defects have been created in the rotor and stator on different machines in order to validate experimentally the suggested diagnostic procedures
Kohutek, Tomáš. "Diagnostika vibrací strojů při kusových zkouškách". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318531.
Texto completoDa, Cunha Joao Paulo. "Diagnostic thermique de la machine à courant continu par identification paramétrique". Poitiers, 1999. http://www.theses.fr/1999POIT2353.
Texto completoJouglet, David. "Coopération homme-machine pour le diagnostic technique : Application aux dérangements téléphoniques". Valenciennes, 2000. https://ged.uphf.fr/nuxeo/site/esupversions/e3848e7b-293c-4dff-b8ef-a980ab1a7abe.
Texto completoDidier, Gaëtan. "Modélisation et diagnostic de la machine asynchrone en présence de défaillances". Nancy 1, 2004. http://www.theses.fr/2004NAN10163.
Texto completoIn this study, we move on to the broken rotor bar diagnosis of squirrel-cage induction machines. The first part is devoted to the development of a model which is based on the magnetically coupled electric circuits. We present three methods allowing detection of a rotor defect of an induction machine. The first method is based on the evaluation of several indexes calculated starting from the amplitude of the components present in the spectra of the instantaneous power and the line current. The second method of detection suggested uses the stator current spectrum phase calculated starting from a Fourier Transform. To improve the detection, we use the Hilbert transform phase calculated starting from the stator current spectrum module. These approaches have the characteristic to be based on any threshold of reference to establish the presence of a broken rotor bar
Protzer, Eric(Eric Sean McMurtrie). "Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence". Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122211.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 74-76).
Over the course of the 2 0 th century numerous economies have leveraged export-driven industrialization strategies to grow wealthier. The advent of automation technology, however, threatens to disrupt the low-cost manufacturing models which have characterized this process; the future may see factories resituated to high-income, high-skill countries which can successfully deploy automation. This thesis consequently evaluates how developing countries could navigate automation by either innovating abreast of it or specializing away from its impact. It is broadly divided into three sections. First, the stage is set by examining the political economy of industrial policy to highlight how political incentives constrain feasible strategies for economic readjustment of any sort. It is shown that even in a setting with few corruption problems - the European Union - industrial policy is guided by politicians' incentives to maintain power, and thus one ought to be cognizant of such incentives in any context. Second, possible barriers to greater productivity and innovation in developing countries are explored through a case study analysis of Vietnam, which is considered by some to be highly exposed to automation risk. Growth diagnostic tools are applied to identify the binding constraints which prevent it from shifting towards more complex, value-added economic activities. Structural economic reform is found to be critical to greater innovation, as opposed to technocentric solutions that aim to leapfrog to the technological frontier. Third, product space and machine learning methodology are used to simulate how countries' export diversification paths could respond to automation. By conducting sensitivity analysis across a range of automation scenarios it provides insight on how developing countries may be able to respecialize their economies to maintain growth.
by Eric Protzer.
S.M. in Technology and Policy
S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society
Soukup, Patrik. "Diagnostika točivých elektrických strojů". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-377107.
Texto completoGiap, Quang Huy. "Sur le diagnostic interactif". Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENT105/document.
Texto completoThis PhD thesis studies the iterative diagnosis problems and provides thecomputer-aided diagnostic tool for interactive diagnosis. Different diagnosis processes wherethe tool to support human-machine interaction are useful, are presented. These tools help totackle difficulties related to the representation of a large number of elements in a system,difficulties related to the representation of the behavior functioning of a system and difficultiesencountered while expliciting the expertise. Our work led to the design of different interactivetools to support the diagnosis process. The first tool allows to exploit the structural-functionalmodeling to build and solve progressively a diagnosis problem. The second interactive toolallows to exploit the behavioral models built step by step in the diagnosis process and tosolve the diagnosis problem. The final tool was proposed to show that it is possible to takeinto account the implicit knowledge of an expert in order to solve the diagnosis problem.A diagnosis problem is therefore presented as an iterative process with human-machineinteractions
Baskaya, Elgiz. "Détection & diagnostic de pannes pour les drones utilisant la machine learning". Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30043.
Texto completoThis new era of small UAVs currently populating the airspace introduces many safety concerns, due to the absence of a pilot onboard and the less accurate nature of the sensors. This necessitates intelligent approaches to address the emergency situations that will inevitably arise for all classes of UAV operations as defined by EASA (European Aviation Safety Agency). Hardware limitations for these small vehicles point to the utilization of analytical redundancy, rather than to the usual practice of hardware redundancy in manned aviation. In the course of this study, machine learning practices are implemented in order to diagnose faults on a small fixed-wing UAV to avoid the burden of accurate modeling needed in model-based fault diagnosis. A supervised classification method, SVM (Support Vector Machines) is used to classify the faults. The data used to diagnose the faults are gyro and accelerometer measurements. The idea to restrict the data set to accelerometer and gyro measurements is to check the method's classification ability, with a small and inexpensive chip set and without the need to access the data from the autopilot, such as the control input information. This work addresses the faults in the control surfaces of a UAV. More specifically, the faults considered are the control surface stuck at an angle and the loss of effectiveness.First, a model of an aircraft is simulated. This model is not used for the design of Fault Detection and Diagnosis (FDD) algorithms, but is instead utilized to generate data. Simulated data are used instead of flight data in order to isolate the probable effects of the controller on the diagnosis, which may complicate a preliminary study on FDD for drones. The results show that for simulated measurements, SVM gives very accurate results on the classification of the loss of effectiveness faults on the control surfaces. These promising results call for further investigation so as to assess SVM performance on fault classification with flight data. Real flights were arranged to generate faulty flight data by manipulating the open source autopilot, Paparazzi. All data and the code are available in the code sharing and versioning system, Github. Training is held offline due to the need for labeled data and the computational burden of the tuning phase of the classifiers. Results show that from the flight data, SVM yields an F1 score of 0.98 for the classification of control surface stuck faults. For the loss of efficiency faults, some feature engineering, involving the addition of past measurements is needed in order to attain the same classification performance. A promising result is discovered when spinors are used as features instead of angular velocities. Results show that by using spinors for classification, there is a vast improvement in classification accuracy, especially when the classifiers are untuned. Using spinors and a Gaussian Kernel, an untuned classifier gives an F1 score of 0.9555, which was 0.2712 when gyro measurements were used as features. In summary, this work shows that SVM gives a satisfactory performance for the classification of faults on the control surfaces of a drone using flight data
Fedida, Vincent. "Etude des défauts des machines électriques tournantes par analyse du champ magnétique de fuite : Application au diagnostic de machines de faibles puissances dans un contexte de production en grande série". Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAT023.
Texto completoDiagnostic and identification of defaults providing in electrical machines (mainly single phased asynchrone motors) by stray flux measurement
Ondel, Olivier. "Diagnostic par reconnaissance des formes : Application à un ensemble convertisseur-machine asynchrone". Phd thesis, Ecole Centrale de Lyon, 2006. http://tel.archives-ouvertes.fr/tel-00113102.
Texto completoLa maintenance et la surveillance de ces deux systèmes permettent de rentabiliser les installations. Il est donc important de développer des outils de diagnostic pour détecter de manière précoce les défauts pouvant apparaître aussi bien sur le convertisseur que sur la machine.
Notre approche est basée sur l'utilisation des méthodes de reconnaissance des formes. Un vecteur de paramètres, appelé vecteur forme, est extrait de chacune des mesures effectuées sur la machine. Les règles de décisions utilisées permettent de classer les observations, décrites par le vecteur forme, par rapport aux différents modes de fonctionnement connus avec ou sans défaut.
Des défauts ont été créés au rotor et au stator de la machine asynchrone, alimentée soit à partir du réseau, soit par le biais d'un onduleur de tension.
La procédure de décision, basée sur la règle des k - plus proches voisins, associée à une fonction d'appartenance, permet de détecter l'évolution des modes de fonctionnements ainsi que les défauts avérés. Par la suite, le suivi d'évolution de ces modes est réalisé par une approche de type Kalman : un estimateur récursif de Kalman est utilisé pour déterminer les paramètres du modèle dynamique rendant compte de l'évolution d'un mode et un prédicteur de Kalman pour prévoir une évolution vers de nouvelles zones de l'espace. Ces algorithmes ont montré l'efficacité de l'application de la reconnaissance des formes au diagnostic.
Ondel, Olivier Clerc Guy. "Diagnostic par reconnaissance des formes Application à un ensemble convertisseur-machine asynchrone /". [S.l.] : [s.n.], 2006. http://bibli.ec-lyon.fr/exl-doc/oondel.pdf.
Texto completoAndriamalala, Rijaniaina Njaksasoa. "Modélisation du défaut d'excentration dans une machine asynchrone : application au diagnostic et à la commande de deux machines spécifiques". Thesis, Nancy 1, 2009. http://www.theses.fr/2009NAN10064/document.
Texto completoThis thesis investigates various fault and detection issues in a Dual-Stator Winding Induction Machine Drive including rotor eccentricity problems and inverter switch faults. In addition, the control of six-phase series-connected two-motor drives and the related fault detection and fault tolerant strategy issues are studied as well. The work starts with new modeling methods for an eccentric multiphase induction machine. The first proposed method considers only the winding harmonics and neglects the slotting effects. Then, a second method is proposed, considering the first winding harmonic and the slotting ones. From both modeling techniques, eccentricity signatures are extracted. Simulation results show that both modeling techniques provide identical spectra at low frequency; however, the second technique gives additional high frequency sidebands. These sidebands are the results of the interaction between the eccentricity and the slot harmonics. Eccentricity and inverter faults in a Dual-Stator Winding Induction Machine Drive are subsequently investigated. The inverter topology and the control algorithm are reconfigured to deal with short-circuit and open circuit faults on the inverter side so that the stator currents become balanced again and reach their pre-fault magnitude. Simulation results show promising results. The speed is stabilized after a short disturbance due to the fault. Besides, analytical method has been successfully used to predict eccentricity fault, although the machine was inverter fed. Control variables have been effectively used as diagnosis tools for eccentricity fault in a vector controlled machine. Additionally, decoupled control of six-phase and three-phase machines connected in series has been investigated. Firstly, decoupling control using analytical method is predicted. Several simulations are then carried out to confirm the decoupling effectiveness. For this special drive, elimination of the disturbances due to a switch fault is also possible thanks to an appropriate converter topology and adaptation of the control algorithm. Most of simulation predictions are confirmed by experimental results
Vu, Hoang Giang. "Estimation and diagnostic of doubly-fed asynchronous wind generator". Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10151.
Texto completoThis doctoral thesis presents a methodology for the online condition monitoring of the electrical power drive in wind energy systems based on the local measurement of the DC-bus magnetic field. The work is divided into two complementary parts. In the first part, some contributions related to the estimation of the state and parameters for certain classes of nonlinear systems are provided. The estimators have been validated in simulation and on test benches. The second part focuses on the implementation and control design of two benchmarks used to study defects in a doubly-fed induction generator (DFIG) system and an induction motor power drive. In the former benchmark, the parameters identification of the induction machine and the controller design of the DFIG system are carried out. For the latter test bench, the notable work is to build an induction machine drive for the purpose of fault investigation, in which a PWM generator is developed to control and create the fault of the converter. Furthermore, virtual sensors are designed to estimate mechanical speed that is used to calculate the characteristic frequencies, and mechanical torque signal that has influence on the amplitude of some typical fault signatures. Finally, based on the theoretical aspect of the selected faults, the relevant simulations are developed and experiments are implemented on the benchmarks in order to validate the proposed technique. It has been shown that the diagnostic relying on the magnetic field measurement is feasible and offers various advantages such as simplicity and cost-effectiveness
Xue, Yang. "Physically-Aware Diagnostic Resolution Enhancement for Digital Circuits". Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/720.
Texto completoAndriamalala, Rijaniaina Njaksasoa Sargos François-Michel. "Modélisation du défaut d'excentration dans une machine asynchrone Application au diagnostic et à la commande de deux machines spécifiques /". S. l. : S. n, 2009. http://www.scd.uhp-nancy.fr/docnum/SCD_T_2009_0064_ANDRIAMALALA.pdf.
Texto completoSalles, Gaël. "Surveillance et diagnostic des défauts de la charge d'un entraînement par machine asynchrone". Lyon 1, 1997. http://www.theses.fr/1997LYO10017.
Texto completoLegrand, Claude. "Contribution à l'avancement des techniques de diagnostic pour l'intégration d'automates de traitement rapide d'images". Paris 11, 1985. http://www.theses.fr/1985PA112239.
Texto completoPetropol, Siana-Elena. "Ondelettes et diagnostic : application aux défauts diélectriques et électriques des machines tournantes". Grenoble INPG, 2001. http://www.theses.fr/2001INPG0077.
Texto completoThe purpose of this work is the diagnosis of dielectric and electric faults of electrical drives, more precisely, the diagnosis of changes or anomalies in the measured signals. By its time-frequency localization, the Multiresolution Analysis is adaptable to fault diagnosis. He choices of the mother wavelet and of the number of decomposition levels are the freedom degrees, which allow this method to extract relevant information from the analyzed signals. Its implementation by numerical filters reduces the computations cost. The fault detection method computes on-line the wavelet coefficients. A gradual alarm rate is delivered function of the fault type and persistency. The fault isolation and identification methods take into account the spectral contents of the coefficients vector at each decomposition level to determine the fault membership of a class of known fault types and further to estimate the fault amplitude. New classes of faults may be created. The fault detection method has been initially conceived to detect the insulation quick aging and has been further validated for the asynchronous motor parameter fault detection. The fault isolation and identification methods have been developed and verified only for the asynchronous motor application. The Multiresolution Analysis freedom degrees confer flexibility to the developed methods with regard to different applications
Perez, Daniel Antonio. "Performance comparison of support vector machine and relevance vector machine classifiers for functional MRI data". Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34858.
Texto completoGiap, Quang-Huy. "Sur le diagnostic interactif". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00766997.
Texto completoAlameh, Kawthar. "Contribution au diagnostic et a l'analyse de défauts d'une machine synchrone à aimants permanents". Thesis, Normandie, 2017. http://www.theses.fr/2017NORMR072/document.
Texto completoThe advent of new magnetic materials and recent advances in power electronics have played a major role in the progress of hybrid electric vehicles. Nowadays, permanent magnet synchronous machines (PMSM) thanks to their performances, especially their energy efficiency, are considered as ideal candidates for the traction chains of hybrid and electric vehicles. However, due to material aging, manufacturing defects or severe operating conditions, different types of faults are capable to occur in the machine components, its control or measuring devices. In order to ensure safety, reliability and availability, the integration of a fault diagnosis and condition monitoring approach in the automotive electrical powertrain system is becoming more and more important. In this context, the aim of the thesis is to contribute to the diagnosis and characterization of faults in the PMSM based on a vibration analysis. First, analytical modeling approaches for the PMSM and inter-turn short-circuits, eccentricity and rotor demagnetization faults will be proposed. The major interest of such models, in a diagnosis context, is to study the behavior of the machine in the presence of studied faults in order to deduce the most suitable detection methods. In addition, numerical models will be developed in order to validate the analytical magnetic and mechanical parts of the machine as well as the demagnetization fault. In the phase of fault impact analysis, we will focus on the cases of rotor eccentricity and demagnetization. The fault indicators will be extracted from the vibratory signal representations in time and space domains and their Fourier transforms, in the cases of single faults and the cases of two combined faults. For single fault cases, two diagnosis approaches will be proposed: the first uses the principle of statistical tests and fault signature tables, inspired by model-based diagnosis methods, while the second relies on a set of three neural networks, such as each one is with a single input and a single output and dedicated to isolate one type of fault. Finally, the performance of these two approaches, in terms of robustness and adaptability, will be compared for the same training and test sets
Obry, Tom. "Apprentissage numérique et symbolique pour le diagnostic et la réparation automobile". Thesis, Toulouse, INSA, 2020. http://www.theses.fr/2020ISAT0014.
Texto completoClustering is one of the methods resulting from unsupervised learning which aims to partition a data set into different homogeneous groups in the sense of a similarity criterion. The data in each group then share common characteristics. DyClee is a classifier that performs a classification based on digital data arriving in a continuous flow and which proposes an adaptation mechanism to update this classification, thus performing dynamic clustering in accordance with the evolution of the system or process being followed. Nevertheless, the only consideration of numerical attributes does not allow to apprehend all the fields of application. In this generalization objective, this thesis proposes on the one hand an extension to nominal categorical data, and on the other hand an extension to mixed data. Hierarchical clustering approaches are also proposed in order to assist the experts in the interpretation of the obtained clusters and in the validation of the generated partitions. The presented algorithm, called Mixed DyClee, can be applied in various application domains. In the case of this thesis, it is used in the field of automotive diagnostics
Hanych, Libor. "Vliv vibrací brousícího vřetene brusky na chvění obrobku při broušení". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-377655.
Texto completoZidat, Farid. "Sur la conception d'une cellule de suivi des performances d'éco-efficacité énergétique des machines électriques tournantes à courants alternatifs". Thesis, Artois, 2012. http://www.theses.fr/2012ARTO0203/document.
Texto completoThe energetic performance increase of industrial processes using AC electrical rotating machines is nowadays of great concern. The developments presented in this thesis are situated in this context and are about the design of an energy monitoring tool (cell). The main scientific barrier to lift is the estimation of the electromagnetic torque of AC machines without dismounting their terminal box or measuring their shaft speed. Non invasive methods have been developed; they are based on the measurement of the phase current and/or the external flux in the immediate vicinity of the machine. Analyses of the external flux distribution around the external housing were made : the magnetic flux is attenuated and phase shifted because of the eddy current effect. Then, the analysis has made it possible to distinguish the contribution of the wires placed in the slots from the effect of the end-windings in the external flux emission. The work explains how to determine an image of the external flux, as well as the way to measure it. That leads to the definition of protocols for determining the electromagnetic torque, which, for some of them use current measurements or its estimation from the external flux. The proposed methods have been applied to induction machines with rated powers between 3 to 200 kW. The cell structure is described, in particular the wireless transmission of the measured information. The autonomy of the cell is a factor taken into account troughout the study, leading to the development of little-intensive computing algorithms. It is also shown that the external flux can be used as an additional energy source
Menexiadis, Dimitri. "Conception d'un système expert d'aide au diagnostic pour les machines tournantes". Valenciennes, 1988. https://ged.uphf.fr/nuxeo/site/esupversions/04ba5d72-dc25-461d-8efd-ab79aeeefb8f.
Texto completoHuang, Ke. "Modélisation de fautes et diagnostic pour les circuits mixtes/RF nanométriques". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00670338.
Texto completoKothiyal, Prachi. "Detection and Classification of Sequence Variants for Diagnostic Evaluation of Genetic Disorders". University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1275922297.
Texto completoOumaamar, Mohamed El Kamel. "Surveillance et diagnostic des défauts rotoriques et mécaniques de la machine asynchrone avec alimentation équilibrée ou déséquilibrée". Thesis, Université de Lorraine, 2012. http://www.theses.fr/2012LORR0022/document.
Texto completoThe research presented in this thesis concerns the diagnosis of rotor and mechanical defaults of the induction machine. First, there is provided a summary of the diagnostic methods supported by experiments with defects created in the rotor and stator of the asynchronous machine fed from the network. And in the same vein, an experimental study on the comparison in amplitude and phase signatures of defects in bar in the spectra between the stator current and neutral voltage was discussed. In a second step, the induction motor is fed by a converter mounted directly onto the motor. We introduced a new diagnostic technique based on spectral analysis of the currents of the network (upstream of the converter-machine). Finally, in order to simulate the behavior of the machine, it was necessary to develop an accurate model taking into account the space harmonics, and neutral voltage. To corroborate the frequency induced by rotor defects in the neutral voltage, a theoretical study was presented which gave interesting results
Younsi, Mohamed Omar. "Analyse, diagnostic et optimisation énergétiques d'un parc de machines électriques sur site industriel". Thesis, Artois, 2017. http://www.theses.fr/2017ARTO0211/document.
Texto completoIn the industry, electrical motors are responsible for 67% of electricity consumption. Replacing installed motors by more efficient ones requires the knowledge of their suitability with the loads that they drive. Analyzing the load variations without intrusive measurements or installations consignments is a strong constraint.That is why this thesis has a threefold purpose. Firstly, a “noninvasive” diagnostic device has been developed with four methods for evaluating the load of grid-connected induction motors. Two of these methods, based on the measurement of the current and the magnetic stray flux, have been significantly improved up to TRL7. The two other methods exploit only the measurement of the stray flux. Their applicability is checked for balanced and unbalanced supply voltage systems with permanent or random variations. A more exploratory study shows that the noninvasive estimation of the current for inverter-fed induction machines is possible using the radiated external flux. Secondly, the energy diagnosis device and search algorithms adapted to an operating cycle motorization have been applied to practical examples of energy optimization in an electro-intensive industrial plant, an aluminum smelter. Thirdly, a reflection on the management of a motor fleet is proposed, in particular, on the performance analysis between new motors and rewounded ones
Cuevas, Salvatierra Mauricio Andrés. "Méthodes non-invasives de diagnostic de défauts et d'analyse thermique des machines synchrones à pôles saillants". Thesis, Artois, 2017. http://www.theses.fr/2017ARTO0209/document.
Texto completoThis work aims to develop non-invasive monitoring techniques on AC rotating machines so that their implementation is easy in an industrial environment. For this purpose, two independent methods are described: a fault diagnosis in alternators connected to the local power gird and an exploratory study to evaluate the internal temperature of AC rotating machines.The first method relies on the analysis of two physical magnitudes: the stray magnetic field radiated outside from the external frame and the vibrations content of machine structure. Mathematical models have been developed in order to correlate magnetic and mechanical phenomena which occur in three different machine states: healthy and in two winding short-circuit faults both in the stator and in the rotor. These results were then validated experimentally in laboratory as well as on large machines in industrial environment. A first diagnostic prototype is presented capable to be implemented in industrial environment in order to detect short-circuit faults in larges alternators.In a second time, a temperature estimation method is proposed based on observations concerning variations in material characteristics of windings as temperature increases. Thus, the localizations of impedance resonant frequencies are impacted, which was verified experimentally as well.This thesis work allowed to verify diagnostic feasibility and on-line monitoring methods in rotating machines in a non-invasive way in industrial environments
Féré, Michael. "M3S – Développement de la spectroscopie Raman en cytopathologie : Application au diagnostic de la leucémie lymphoïde chronique". Thesis, Reims, 2018. http://www.theses.fr/2018REIMM202/document.
Texto completoCurrently, there are few new "Label free" technologies to facilitate and improve early diagnosis. These technologies could be powerful tools to better diagnose patients. Many studies have shown the potential of Raman spectroscopy to help clinicians. The work carried out during this thesis aimed to develop an autonomous tool for the diagnosis of CLL, using Raman data acquired under different experimental and instrumental conditions during multicentric measurement campaigns. However, these changes have a significant impact on Raman data, which poses transferability issues. The appearance of this technology at the bedside is therefore hindered, it is necessary to correct this lack of transferability. In this thesis, various lines of research were conducted. As a first step, it was proposed to evaluate a solution consisting in the application of a specifically developed pre-treatment to eliminate the spectral variability induced by the different changes in conditions. Pre-treatment based on EMSC has shown strong performance in homogenizing this multicentric data. The second research axis was to evaluate different strategies, in order to create and optimize models for the diagnosis of CLL. 100 classification models were therefore created through repeated double crossvalidation. The combination of the predictions of these models allowed, through a majority vote, to predict with great accuracy whether a patient was healthy or sick
Derrhi, Mostafa. "Modélisation de la machine asynchrone par la méthode des réseaux de perméances : validation par le diagnostic". Amiens, 2000. http://www.theses.fr/2000AMIE0114.
Texto completoVervier, Kevin. "Méthodes d’apprentissage structuré pour la microbiologie : spectrométrie de masse et séquençage haut-débit". Thesis, Paris, ENMP, 2015. http://www.theses.fr/2015ENMP0081/document.
Texto completoUsing high-throughput technologies is changing scientific practices and landscape in microbiology. On one hand, mass spectrometry is already used in clinical microbiology laboratories. On the other hand, the last ten years dramatic progress in sequencing technologies allows cheap and fast characterization of microbial diversity in complex clinical samples. Consequently, the two technologies are approached in future diagnostics solutions. This thesis aims to play a part in new in vitro diagnostics (IVD) systems based on high-throughput technologies, like mass spectrometry or next generation sequencing, and their applications in microbiology.Because of the volume of data generated by these new technologies and the complexity of measured parameters, we develop innovative and versatile statistical learning methods for applications in IVD and microbiology. Statistical learning field is well-suited for tasks relying on high-dimensional raw data that can hardly be used by medical experts, like mass-spectrum classification or affecting a sequencing read to the right organism. Here, we propose to use additional known structures in order to improve quality of the answer. For instance, we convert a sequencing read (raw data) into a vector in a nucleotide composition space and use it as a structuredinput for machine learning approaches. We also add prior information related to the hierarchical structure that organizes the reachable micro-organisms (structured output)
Boumegoura, 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.
Texto completoElectrical 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
Mynář, Josef. "Vliv frekvenčního měniče na životnost ložisek a jejich poškození". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-378018.
Texto completoMahyob, Amin. "Modélisation des machines électriques tournantes défectueuses par la méthode des réseaux de perméances : application à la machine asynchrone". Le Havre, 2009. http://www.theses.fr/2009LEHA0017.
Texto completoFault diagnosis in electrical machines needs a modelling approach reliable and as close to the reality as possible. It is shown that by proper modelling of the electrical machines it is possible to detect the effect of the different faults on the different machine quantities. This work proposes a robust modular model based on Permeance Network Method (PNM) for the diagnosis of induction machine stator and rotor faults. The proposed model allows taking into account the local magnetic saturation of the magnetic circuit due to heavy fault currents, especially in the case of inter-turn short circuit fault, and remains moderately time consuming. In this model, the magnetic circuit of the machine was represented by a set of permeances (reluctances); their values vary as functions of the magnetic state of the machine. Firstly, the system of algebraic equations describing the developed permeance network is written. Then, this magnetic model is coupled to the electrical and mechanical differential equations describing the induction machine operation in presence of different faults to achieve a final system of algebro-differential equations of first order with variable coefficients whose numerical solution is provided by the iterative Newton-Raphson method. The comparison between the experimental results and simulation results obtained by the proposed model in the presence of inter-turn short circuit fault shows the relevance of the chosen method to identify the signature of this fault in the measurable quantities
Daghustani, Sara Hussain. "USING AUTOENCODER TO REDUCE THE LENGTH OF THE AUTISM DIAGNOSTIC OBSERVATION SCHEDULE (ADOS)". CSUSB ScholarWorks, 2018. https://scholarworks.lib.csusb.edu/etd/620.
Texto completoRaoult, Olivier. "Diagnostic de pannes des systèmes complexes". Phd thesis, Grenoble INPG, 1989. http://tel.archives-ouvertes.fr/tel-00332209.
Texto completoVirkkala, Linda y Johanna Haglund. "Modelling of patterns between operational data, diagnostic trouble codes and workshop history using big data and machine learning". Thesis, Uppsala universitet, Datalogi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-279823.
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