Given the importance of diagnosing internal combustion engines and their expandingmarket, it is crucial to investigate the complex dynamics of these engines and developa model to detect and localize component and sensor faults, independent of operatingconditions. This master’s thesis explores capturing dynamic relationships in engine signalsto detect faults. Internal combustion engines have highly nonlinear dynamics that arenot easy to capture with basic system identification methods. Consequently, some newlydeveloped methods, such as Sparse Identification of Nonlinear Dynamics (SINDy) andAuto Regressive (AR) models, have been implemented to address the governing equations.Following previous research in this field, some analytical relations between the sensorswere known. Additionally, these equations provide the sensitivity of residuals based onthe input sensor fault. By implementing the mentioned methods and using informationfrom the analytical equations, some relationships between the sensor values and the inputfault have been identified.After finding these dynamic relationships between the sensor values, a classificationalgorithm was selected to classify the sensor faults. Additionally, to estimate the faultseverities (sensor inaccuracies), some regression models have been implemented. Further-more, it was desired to evaluate the isolability of the faults, and in this regard, some newconstraints have been considered to reconstruct the relations with the desired isolability.Finally, through several evaluations, it was shown that the proposed method is not af-fected by the driving cycle. However, this research established these methods based on aspecific case study, which is a specific turbocharged internal combustion engine.

Aujourd'hui, les réseaux de communications sont largement utilisés pour relier les points de ressources, qui permettent la transmission de données à distance, de réduire la complexité dans le cadre de câblage et les coûts de support et de fournir l'aide dans la maintenance. En raison de ces avantages, les réseaux ont été introduits dans les systèmes automatiques au cours de ces dernières décennies et de nouveaux protocoles de réseau industriel ont été également développés pour assurer le contrôle à distance. Les systèmes contrôlés en réseau SCR (Networked Control System NCS) sont des systèmes automatiques traditionnels où les actionneurs, les capteurs, les contrôleurs et des autres composants sont distribués autour d'un réseau de communication, qui peut être partagé ou non avec d'autres applications. Les données de commande et de diagnostic sont échangées entre les composants du système (capteur, contrôleur, actionneur) via ce réseau partagé. Cette nouvelle architecture de système de contrôle introduit des problèmes originaux, en termes de retard variable affectant la transmission, des pertes de paquets, etc. Dans l'objectif de maintenir de bonnes performances du module de diagnostic face à des éventuelles variations introduites par le réseau, il est intéressant d'introduire des nouvelles approches. Nous avons rapporté les résultats relatifs aux techniques d'estimation optimale à base de filtre de Kalman, de façon à constituer un document aussi complet que possible traitant la génération de résidus et l'isolation des défauts dans SCR. Notre contribution consiste, dans un premier temps, à développer un modèle d'état d'un système contrôlé via un réseau. En deuxième temps, nous proposons un générateur de résidus en se basant sur les hypothèses simulant le retard induit par le réseau. Finalement, nous développons un filtre isolateur pour identifier directement les défauts affectant les actionneurs dans un SCR / Today's communications networks are widely used to connect the resources, enabling the remote data transmission, reducing the cabling complexity, minimizing costs and providing easy maintenance. Because of these advantages, the networks have been introduced in automatic systems during recent decades and new industrial network protocols were also developed for the remote control. The systems controlled by networks, the term "Networked Control Systems (NCS)" are automatic traditional systems where the actuators, the sensors, the controllers and other components are distributed around a communication network that can be shared or not with other applications. The data of both control and diagnostic are exchanged between system components (sensor, controller and actuator) via the shared network. This new architecture of control system introduces new problems in terms of variable delay affecting the transmission, the packet loss, etc. With the aim to maintain good performance of diagnostic module face of possible changes introduced by the network, it is interesting to introduce new approaches. We have reported results for the optimal estimation techniques based on Kalman filter, thus creating a report as complete as possible, treating the residual generation and fault isolation in NCS. Our contribution consists, firstly, to develop a state space model of a system controlled via a network. Secondly, we propose a residual generator based on the delay models induced by the network. Finally, we develop a isolation filter in order to directly identify in the actuators faults in a SCR

Orientador: Robson Pederiva / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-07-23T22:28:49Z (GMT). No. of bitstreams: 1 Chiarello_AndreGarcia_D.pdf: 7903318 bytes, checksum: cd3f513a26e60d59ef55edbb6453d942 (MD5) Previous issue date: 1998 / Resumo: Este trabalho aborda o problema de detecção e localização de falhas em sistemas mecânicos através de modelos matemáticos. Considera-se que o sistema mecânico seja representado por um modelo dinâmico na forma de variáveis de estado, com parâmetros constantes e entradas estacionárias. Definindo-se, apropriadamente, funções de correlação e explorando as propriedades inerentes aos sistemas estacionários, consegue-se obter funções analíticas envolvendo parâmetros físicos do sistema. Posteriormente, demonstra-se que estas funções analíticas podem ser utilizadas para monitorar parâmetros físicos do modelo, ou ainda, identificar parâmetros físicos relacionados a uma falha no sistema. Duas abordagens diferentes para o problema de localização de falhas são desenvolvidas: uma utiliza a estimação de parâmetros e outra utiliza funções de resíduo. Visando uma aplicação em sistemas reais, foram simulados sistemas mecânicos em diversas condições de operação. Os resultados numéricos comprovaram que a metodologia proposta pode ser utilizada no monitoramento de sistemas mecânicos / Abstract: This work deals with the problem of fault detection and location in mechanical systems through mathematical models. It is considered that the mechanical system is represented in a state space form, with constant parameters and stationary inputs. Some correlation functions are appropriately defined involving physical parameters of the stationary system. It is demonstrated that these correlation functions can be transformed to appropriate analytical form (redundancy equations) for fault detection and isolation purposes. Two different approaches are considered: one based on physical parameters estimation and the other based on residuaIs generation. Three different mechanical systems were numerically simulated with conditions (or restrictions) usually found in practical situations. The results showed that the proposed approach is a promising methodology for monitoring stationary mechanical systems / Doutorado / Projeto Mecanico / Doutor em Engenharia Mecânica