This thesis takes place in the field of Ambient Intelligence (AmI). AmI Systems are interactive systems composed of many heterogeneous components. From a hardware perspective these components can be divided into two main classes: sensors, using which the system observes its surroundings, and actuators, through which the system acts upon its surroundings in order to execute specific tasks.From a functional point of view, the goal of AmI Systems is to activate some actuators, based on data provided by some sensors. However, sensors and actuators may suffer failures. Our motivation in this thesis is to equip ambient systems with self fault detection capabilities. One of the particularities of AmI systems is that instances of physical resources (mainly sensors and actuators) are not necessarily known at design time; instead they are dynamically discovered at run-time. In consequence, one could not apply classical control theory to pre-determine closed control loops using the available sensors. We propose an approach in which the fault detection and diagnosis in AmI systems is dynamically done at run-time, while decoupling actuators and sensors at design time. We introduce a Fault Detection and Diagnosis framework modeling the generic characteristics of actuators and sensors, and the physical effects that are expected on the physical environment when a given action is performed by the system's actuators. These effects are then used at run-time to link actuators (that produce them) with the corresponding sensors (that detect them). Most importantly the mathematical model describing each effect allows the calculation of the expected readings of sensors. Comparing the predicted values with the actual values provided by sensors allows us to achieve fault-detection.

The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown considerably since their introduction during the 1970s. The majority of the early knowledge-based systems incorporated shallow knowledge, which sought to define simple cause and effect relationships between a symptom and a fault, that could be encoded as a set of rules. Though such systems enjoyed much success, it was recognised that they suffered from a number of inherent limitations such as inflexibility, inadequate explanation, and difficulties of knowledge elicitation. Many of these limitations can be overcome by developing knowledge-based systems which contain deeper knowledge about the device being diagnosed. Such systems, now generally referred to as model-based systems, have shown much promise, but there has been little evidence to suggest that they have successfully made the transition from the research centre to the workplace. This thesis argues that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex devices, and that both deep and shallow knowledge have their part to play in this process. More specifically this thesis demonstrates how a wide-ranging knowledge-based system for quality assurance, based upon shallow knowledge, can be developed, and implemented. The resultant system, named DIPLOMA, not only diagnoses faults, but additionally provides advice and guidance on the assembly, disassembly, testing, inspection and repair of a highly complex hydro-mechanical device. Additionally it is shown that a highly innovative modelbased system, named MIDAS, can be used to contribute to the provision of diagnostic, explanatory and training facilities for the same hydro-mechanical device. The methods of designing, coding, implementing and evaluating both systems are explored in detail. The successful implementation and evaluation of the DIPLOMA and MIDAS systems has shown that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex hydro-mechanical devices, and that they make a beneficial contribution to the business performance of the host organisation. Furthermore, it has been demonstrated that the most effective and comprehensive knowledge-based approach to fault diagnosis is one which incorporates both deep and shallow knowledge, so that the distinctive advantages of each can be realised in a single application. Finally, the research has provided evidence that the model-based approach to diagnosis is highly flexible, and may, therefore, be an appropriate technique for a wide range of industrial applications.

With growing demands for reliability, availability, safety and cost efficiency in modern machinery, accurate fault diagnosis is becoming of paramount importance so that potential failures can be better managed. Although various methods have been applied to machinery condition monitoring and fault diagnosis, the diagnostic accuracy that can be attained is far from satisfactory. As most machinery faults lead to increases in vibration levels, vibration monitoring has become one of the most basic and widely used methods to detect machinery faults. However, current vibration monitoring methods largely depend on signal processing techniques. This study is based on the recognition that a multi-parameter data fusion approach to diagnostics can produce more accurate results. Fuzzy measures and fuzzy integral data fusion theory can represent the importance of each criterion and express certain interactions among them. This research developed a novel, systematic and effective fuzzy measure and fuzzy integral data fusion approach for machinery fault diagnosis, which comprises feature set selection schema, feature level data fusion schema and decision level data fusion schema for machinery fault diagnosis. Different feature selection and fault diagnostic models were derived from these schemas. Two fuzzy measures and two fuzzy integrals were employed: the 2-additive fuzzy measure, the fuzzy measure, the Choquet fuzzy integral and the Sugeno fuzzy integral respectively. The models were validated using rolling element bearing and electrical motor experiments. Different features extracted from vibration signals were used to validate the rolling element bearing feature set selection and fault diagnostic models, while features obtained from both vibration and current signals were employed to assess electrical motor fault diagnostic models. The results show that the proposed schemas and models perform very well in selecting feature set and can improve accuracy in diagnosing both the rolling element bearing and electrical motor faults.

In this thesis two different problems in distributed sensor networks are considered. Part I involves optimal quantiser design for decentralised estimation of a two-state hidden Markov model with dual sensors. The notion of optimality for quantiser design is based on minimising the probability of error in estimating the hidden Markov state. Equations for the filter error are derived for the continuous (unquantised) sensor outputs (signals), which are used to benchmark the performance of the quantisers. Minimising the probability of filter error to obtain the quantiser breakpoints is a difficult problem therefore an alternative method is employed. The quantiser breakpoints are obtained by maximising the mutual information between the quantised signals and the hidden Markov state. This method is known to work well for the single sensor case. Cases with independent and correlated noise across the signals are considered. The method is then applied to Markov processes with Gaussian signal noise, and further investigated through simulation studies. Simulations involving both independent and correlated noise across the sensors are performed and a number of interesting new theoretical results are obtained, particularly in the case of correlated noise. In Part II, the focus shifts to the detection of faults in helicopter transmission systems. The aim of the investigation is to determine whether the acoustic signature can be used for fault detection and diagnosis. To investigate this, statistical change detection algorithms are applied to acoustic vibration data obtained from the main rotor gearbox of a Bell 206 helicopter, which is run at high load under test conditions.

La sûreté de fonctionnement est devenue indispensable pour tous les systèmes critiques où des vies humaines sont en jeu (comme l’aéronautique, le ferroviaire, etc.). Ceci a conduit à la conception et au développement des architectures tolérantes aux fautes, l’objectif de ces architectures étant de maintenir un service correct délivré par le système malgré la présence de fautes, et en particulier de garantir la sécurité-innocuité et la fiabilité du système. La tolérance aux fautes sur les drones aériens multirotors a récemment reçu une attention importante de la part de la communauté scientifique. En particulier, plusieurs travaux ont été développés sur la tolérance aux fautes des quadrirotors suite à des fautes partielles sur les actionneurs, et récemment des recherches ont abordé le problème de panne totale de l’un des actionneurs. D’après ces études, il a été montré qu’une défaillance totale d’un actionneur dans un quadrirotor rend le système non complètement contrôlable. Une solution proposée est de considérer des multirotors avec des actionneurs redondants (hexarotors ou octorotors). La redondance inhérente disponible dans ces véhicules est exploitée, en cas de défaillance sur les actionneurs, pour redistribuer les efforts de commande sur les moteurs sains de façon à garantir la stabilité et la contrôlabilité complète du système. Dans ce travail de thèse, des approches pour la conception de systèmes de commande tolérants aux fautes des drones multirotors sont étudiées et appliquées au contrôle des octorotors. Toutefois, les algorithmes sont conçus de manière à être applicables sur les autres types de multirotors avec des modifications mineures. D’abord, une analyse de contrôlabilité de l’octorotor après l’occurrence de défaillances sur les actionneurs est présentée. Ensuite, un module de détection et d’isolation de pannes moteurs basé sur un observateur non-linéaire et les mesures de la centrale inertielle est proposé. Les mesures des vitesses et des courants de moteurs fournis par les contrôleurs de vitesse sont également utilisées dans un autre algorithme de détection pour détecter les défaillances des actionneurs et distinguer les pannes moteurs des pertes des hélices. Un module de rétablissement basé sur la reconfiguration du multiplexage est proposé pour redistribuer les efforts de commande d’une manière optimale sur les actionneurs sains après l’occurrence de défaillances dans le système. Une architecture complète, comprenant la détection et l’isolation des défauts suivie par le rétablissement du système est validée expérimentalement sur un octorotor coaxial puis elle est comparée à d’autres architectures basées sur l’allocation de commande et la tolérance aux fautes passive par mode glissant. / With growing demands for safety and reliability, and an increasing awareness about the risks associated with system malfunction, dependability has become an essential concern in modern technological systems, particularly safety-critical systems such as aircrafts or railway systems. This has led to the design and development of fault tolerant control systems (FTC). The main objective of a FTC architecture is to maintain the desirable performance of the system in the event of faults and to prevent local faults from causing failures. The last years witnessed many developments in the area of fault detection and diagnosis and fault tolerant control for Unmanned Aerial rotary-wing Vehicles. In particular, there has been extensive work on stability improvements for quadrotors in case of partial failures, and recently, some works addressed the problem of a quadrotor complete propeller failure. However, these studies demonstrated that a complete loss of a quadrotor motor results in a vehicle that is not fully controllable. An alternative is then to consider multirotors with redundant actuators (octorotors or hexarotors). Inherent redundancy available in these vehicles can be exploited, in the event of an actuator failure, to redistribute the control effort among the remaining working actuators such that stability and complete controllability are retained. In this thesis, fault-tolerant control approaches for rotary-wing UAVs are investigated. The work focuses on developing algorithms for a coaxial octorotor UAV. However, these algorithms are designed to be applicable to any redundant multirotor under minor modifications. A nonlinear model-based fault detection and isolation system for motors failures is constructed based on a nonlinear observer and on the outputs of the inertial measurement unit. Motors speeds and currents given by the electronic speed controllers are also used in another fault detection and isolation module to detect actuators failures and distinguish between motors failures and propellers damage. An offline rule-based reconfigurable control mixing is designed in order to redistribute the control effort on the healthy actuators in case of one or more motors failures. A complete architecture including fault detection and isolation followed by system recovery is tested experimentally on a coaxial octorotor and compared to other architectures based on pseudo-inverse control allocation and a robust controller using second order sliding mode.

Les récents développements des systèmes technologiques ont mené à une complexification des comportements des systèmes actuels. Une solution pour gérer cette complexité croissante consiste à les considérer comme un ensemble de sous-systèmes hétérogènes et à développer des techniques distribuées pour les contrôler et les gérer. Cette solution soulève plusieurs problèmes. Tout d’abord, l’augmentation de la taille et du nombre de composants entraîne immanquablement l’augmentation du nombre de fautes qui peuvent conduire le système dans un état de défaillance critique. De fait, parmi les fonctions opérationnelles, les tâches de détection et d’isolation des fautes (Fault Detection and Isolation ou FDI), de maintenance et de réparation sont devenues prédominantes et elles influent considérablement sur le coût total des produits finaux.Cette thèse porte sur la détection et l’isolation de fautes. Parmi les différentes méthodes pour générer des tests de diagnostic utilisant la redondance analytique, cette thèse adopte l’approche par espace de parité qui utilise les relations de redondance analytique (RRA). Étant donné un modèle du système sous la forme d’un ensemble d’équations différentielles, les RRA sont des relations obtenues à partir du modèle en éliminant les variables non mesurées. Ceci peut être effectué dans un cadre analytique en utilisant la théorie de l’élimination. Une autre solution consiste à utiliser l’analyse structurelle. L’analyse structurelle est basée sur une abstraction du modèle qui ne conserve que les liens entre variables et équations. Malgré son apparente simplicité, l’analyse structurelle fournit un ensemble d’outils puissants, s’appuyant sur la théorie des graphes, pour analyser et inférer des informations sur le système. Par ailleurs, elle a l’avantage de s’appliquer indifféremment sur les systèmes linéaires ou non linéaires.L’objectif de cette thèse est de développer des techniques efficaces basées sur l’analyse structurelle pour le diagnostic des systèmes continus distribué. Dans ce cadre, le système se décompose en un ensemble de sous-systèmes en fonction de contraintes fonctionnelles, géographiques ou de confidentialité. La thèse se divise principalement en deux parties :• la première partie cherche à mettre à lumière, à partir des modèles structurels obtenus au niveau des sous-systèmes, les redondances qui généreront des tests de diagnostic pertinents au niveau du système global,• la deuxième partie vise à formuler et résoudre le problème d’optimisation lié au choix d’un sous-ensemble de tests de diagnostic au niveau des sous-systèmes permettant une diagnosticabilité maximale pour le système global.La première partie utilise le concept d’ensemble minimal structurellement surdéterminé guidé par les fautes (Fault-Driven Minimal Structurally Overdetermined Set ou FMSO set). Ce concept est introduit dans la thèse. Il s’agit d’un sousensemble d’équations du modèle avec une redondance minimale à partir de laquelle une RRA sensible à un ensemble de fautes peut être obtenu. Deux solutions pour générer des ensembles FMSO pour le système global sont présentées, d’une part dans un cadre décentralisé avec des superviseurs imbriqués suivant une hiérarchie; d’autre part dans un cadre totalement distribué. Ces solutions sont basées sur les propriétés des ensembles FMSO au niveau des sous-systèmes qui sont présentées dans la thèse. La deuxième partie pose un problème d’optimisation dans le cadre d’une recherche heuristique et propose trois solutions basées sur un algorithme A* itératif combiné avec une fonction capable d’évaluer si un ensemble FMSO au niveau global peut être obtenu à partir des ensembles FMSO locaux sélectionnés. Les concepts introduits dans la thèse et les résultats sont appliqués à deux cas d’étude industriels. Le premier est une usine de désalinisation. Le second est un système de détermination et de contrôle d’attitude pour un satellite en orbite basse. / The recent development of technological systems implies a high complexity of behaviors for today’s systems. An answer to the increased system’s complexity is to look at them as a multitude of heterogeneous subsystems and develop distributed techniques to control and manage them. This raises a number of problems. Firstly, as the size and number of components increase, so does the number of fault occurrences that may drive the system to undergo critical failures. Fault detection and isolation (FDI), maintenance and repair are an increasing part of the operational everyday’s tasks and they impact drastically the total cost of final products.This thesis focuses on fault detection and isolation. Among the different methods to generate diagnosis tests by taking advantage of analytical redundancy, this thesis adopts the so-called parity space approach based on analytical redundancy relations (ARRs). Given a model of the system in the form of a set of differential equations, ARRs are relations that are obtained from the model by eliminating non measured variables. This can be performed in an analytical framework using elimination theory but another way of doing this is to use structural analysis. Structural analysis is based on a structural abstraction of the model that only retains a representation of which variables are involved in which equations. Despite the rusticity of the abstract model, structural analysis provides a set of powerful tools, relying on graph theory, to analyze and infer information about the system. Interestingly, it applies indifferently to linear or nonlinear systems. The goal of this thesis is to develop effective techniques based on structural analysis for diagnosis of distributed continuous systems. In this framework, the system is decomposed into a set of subsystems according to functional, geographical or privacy constraints. The thesis is organized in two parts:• highlighting the redundancies that are built into the global structural model and that can be used to generate diagnosis tests starting from the redundancies existing in the subsystem’s models,• formulating and solving the optimization problem linked to the choice of a subset of diagnosis tests at the subsystems level that can lead to a set of diagnosis tests achieving maximum diagnosability for the global system.The first part takes benefit of the concept of Fault-Driven Minimal Structurally Overdetermined Set (FMSO set) that is introduced in the thesis. An FMSO set determines a subset of equations of the model with minimal redundancy from which an ARR sensitive to a set of faults can be obtained. Two solutions for generating FMSOs for the global system are presented, in a decentralized framework with supervisors at each level of a hierarchy and in a totally distributed framework.These are based on the properties of the FMSO sets for the subsystems in relation to those of the global system derived in the thesis.

Orientador: Prof. Dr. Jesus Franklin Andrade Romero. / Tese ( doutorado)- Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2016.

Poussés par les réglementations « anti-pollution », les industriels automobiles sont incités à développer des véhicules plus propres et sobres en consommation. Ces dernières années, la dépollution des véhicules n'a cessée d'être améliorée, en optimisant le traitement des polluants des moteurs actuels, mais aussi en développant des solutions alternatives. C'est dans ce contexte que les deux études ont étés menées. Cette étude s'est d'abord intéressée à l'optimisation du fonctionnement du catalyseur trois voies. Ce système est le principal organe de dépollution des motorisations essence, il est capable de convertir les trois principaux polluants réglementés (oxydes d'azote, monoxyde de carbone et hydrocarbures imbrûlés) en gaz non nocifs pour la santé. On s'est intéressé à la modélisation orientée contrôle de ce réacteur chimique, le modèle développé à permis d'élaborer les outils nécessaires au contrôleur pour lui permettre de prendre en compte les dynamiques internes du catalyseur trois voies. L'étude s'est ensuite focalisée sur le contrôle multivariable robuste d'une chaîne d'air turbocompressée d'un moteur essence selon les approches des systèmes linéaires à commutation et à paramètres variant. Le contrôle robuste permet au système de chaîne d'air d'admettre au plus juste la quantité d'air admis dans la chambre de combustion en prenant en compte les éventuelles perturbations. / Forced by more and more severe normative, automotive industrials have to develop clean and energy-efficient vehicles. During the last decades, after-treatment system has been improved and alternative solutions have been found. The two presented studies have been lead in this context. The first study has been focused on the performance optimization of the three ways catalyst. This after-treatment system is able to convert the three main pollutants limited by the normative (nitrogen oxides, carbon monoxide and unburned hydrocarbon) into harmless gases. The purpose of this study is to develop a mathematical reduced order model for the three ways catalyst focused on the oxygen storage-release dynamics. From this model, an observer for the oxygen storage rate estimation has been developed. Based on this tool, three ways catalyst converter controller will be able to take into account the internal dynamics. The second study deals with the multivariable robust control of a supercharged air path system for a spark ignition engine according to two approaches: the switched linear system and the linear parameter varying system. With robust control, the air path system will inject the right amount of air entering the combustion chamber by taking into account possible disruptions.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-05-04T18:35:38Z No. of bitstreams: 1 CECÍLIA ALVES BURITI DA COSTA – DISSERTAÇÃO (PPGEE) 2016.pdf: 2848486 bytes, checksum: eb2cfb57825ecee909a3560f654a3038 (MD5) / Made available in DSpace on 2018-05-04T18:35:38Z (GMT). No. of bitstreams: 1 CECÍLIA ALVES BURITI DA COSTA – DISSERTAÇÃO (PPGEE) 2016.pdf: 2848486 bytes, checksum: eb2cfb57825ecee909a3560f654a3038 (MD5) Previous issue date: 2016-08-25 / Capes / Este trabalho apresenta o processo de modelagem de um relé de distância em um simulador digital em tempo real. O modelo inclui: i) as principais funcionalidades da arquitetura de um relé digital, incluindo filtro anti-aliasing e estimação fasorial; ii) as características de operação do tipo mho e quadrilateral, ambas com duas zonas de atuação; iii) a etapa de diagnóstico de falta, que informa as principais características do distúrbio. Para o diagnóstico da falta, foram avaliados métodos de detecção, classificação e localização por meio de simulação em massa de diferentes cenários de falta em uma linha de transmissão. Dos resultados obtidos, os melhores métodos de cada etapa foram escolhidos para compor o relé. Ao final, a atuação e o diagnóstico do relé modelado foram comparados com os resultados fornecidos pelo relé de distância disponível no próprio simulador e por um relé digital real. / This work presents the modeling process of a distance relay in a real-time digital simulator. The model contains: i) the main features of a digital relay architecture, including anti-aliasing filter and phasor estimation; ii) mho and quadrilateral operating characteristics, with two protection zones; iii) fault diagnosis, which informs the main features of the disturbance. For the fault diagnosis, detection, classification and location methods were evaluated using batch mode simulation of different fault scenarios in a transmission line. From the obtained results, the best methods were selected to be part of the modeled relay. At the end, the operation and diagnosis of the modeled relay were compared with the results presented by the distance relay model provided by the simulator manufacturer and by a digital relay.

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / A análise de gases dissolvidos tem sido aplicada há décadas como a principal técnica de manutenção preditiva para diagnosticar defeitos incipientes em transformadores de potência, tendo em vista que a decomposição do óleo mineral isolante produz gases que permanecem dissolvidos na fase líquida. Entretanto, apesar da importância desta técnica, os métodos de diagnóstico mais conhecidos são baseados em constatações de modelos termodinâmicos e composicionais simplificados para a decomposição térmica do óleo mineral isolante, em conjunto com dados empíricos. Os resultados de simulação obtidos a partir desses modelos não reproduzem satisfatoriamente os dados empíricos. Este trabalho propõe um modelo termodinâmico flexível aprimorado para mimetizar o efeito da cinética de formação de sólidos como restrição ao equilíbrio e seleciona, entre quatro modelos composicionais, aquele que apresenta o melhor desempenho na simulação da decomposição térmica do óleo mineral isolante. Os resultados de simulação obtidos a partir do modelo proposto apresentaram uma melhor adequação a dados empíricos do que aqueles obtidos a partir dos modelos clássicos. O modelo propostofoi, ainda, aplicado ao desenvolvimento de um método de diagnóstico com base fenomenológica.Os desempenhos desta nova proposta fenomenológica e de métodos clássicos de diagnóstico por análise de gases dissolvidos foram comparados e discutidos; o método proposto alcançou desempenho superior a vários métodos usualmente empregados nessa área do conhecimento. E, ainda, um procedimento geral para a aplicação do novo método de diagnóstico é descrito / The dissolved gas analysis has been applied for decades as the main predictive maintenance technique for diagnosing incipient faults in power transformers since the decomposition of the mineral insulating oil produces gases that remain dissolved in the liquid phase. Nevertheless, the most known diagnostic methods are based on findings of simplified thermodynamic and compositional models for the thermal decomposition of mineral insulating oil, in addition to empirical data. The simulations results obtained from these models do not satisfactorily reproduce the empirical data. This work proposes a flexible thermodynamic model enhanced to mimic the kinetic effect of solid formation as a restriction to equilibrium and selects, among four compositional models, the one offering the best performance on the simulation of the thermal decomposition of mineral insulating oil. The simulation results obtained from the proposed model showed better adequacy to reported data than the results obtained from the classical models. The proposed model was also applied in the development of a diagnostic method with a phenomenological basis. The performances of this new phenomenological proposition and of classical dissolved gas analysis diagnostic methods are compared and discussed; the proposed method achieved a performance superior to several methods usually employed in this area of knowledge.Also, a general procedure for the application of the new diagnostic method is described