The purpose of this study is to investigate the flue gas fan in Mälarenergi’s Unit 6 and try to find what is causing the vibrations increase. The Fast Fourier transform (FFT) method was used for this degree project. A comparison was made with previous studies using FFT in order to pinpoint the source of the problem with vibrations. After a possible source had been identified, a computational fluid dynamics (CFD) simulation was performed using ANSYS to visualize the problem. Two cases were simulated using two different turbulence models: the K-epsilon model and the Large-eddy simulation (LES) model. The result from the CFD simulations was compared with previous studies that used similar turbulence models. The flue gas fan’s high vibrations are most likely flow-induced. The simulation result indicates that LES model performed better than the Kepsilon model. The lack of validation in this degree work means that it is hard to know the accuracy of the model. Based on the simulation results the most promising solution seems to be inlet straighteners. / Syftet med studien är att undersöka rökgasfläkten i Mälarenergis Unit 6 och att försöka hitta vad som orsakar vibrationsökningarna. Fast Fourier transform metoden har används i detta examensarbete. En jämförelse har gjorts med tidigare studier som använt FFT metoden för att kunna urskilja källan till vibrationsproblemet. Efter en rimlig källa hittades så utfördes en CFD-simulering i ANSYS för att visualisera problemet. Två fall simulerades med två olika turbulensmodeller: K-epsilon modellen och Largeeddy simulation modellen. Resultatet från CFD-simuleringarna jämfördes med tidigare studier som använt liknande metoder.  Rökgasfläktens höga vibrationer är med störst sannolikhet flödesinducerad. Simuleringsresultatet indikerar att LES modellen utfördes bättre än Kepsilon modellen. Då det saknas en validering i form av flödesmätningar så är det svårt att säga hur lik modellen är med verkligheten. Baserat på resultatet från simuleringarna så verkar inloppsgaller vara den mest lovande lösningen.

Orientador: Eurípedes Guilherme de Oliveira Nóbrega / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-16T17:08:16Z (GMT). No. of bitstreams: 1 AlvesJunior_MarcoAntoniodeOliveira_D.pdf: 2426154 bytes, checksum: bc1d1ecd78ca881b519a4e56c9383c8f (MD5) Previous issue date: 2010 / Resumo: Esta monografia apresenta uma arquitetura para aplicação de Controle Tolerante a Falhas, seguindo uma abordagem de dupla malha de realimentação. A primeira malha apresenta um controlador regular, e a segunda segue uma estratégia de controle adaptativa baseada em rede neural, que faz uso de um mecanismo de ajustes de pesos em tempo real. O primeiro controlador foi escolhido como um projeto de controlador baseado em norma H?, objetivando estabilizar o sistema e garantir o bom desempenho na presença de erros de modelagem e distúrbios externos. O controlador tolerante a falhas, que atua complementarmente à malha externa, é o controlador que usa a técnica neuroadaptativa. A rede neural possui estados internos recorrentes, usando uma superfície de deslizamento para adaptar os seus pesos, de modo a acomodar as possíveis falhas. Também apresenta robustez contra as perturbações externas, além da capacidade do controlador regular. Uma nova topologia de dinâmica da rede neural, com estados internos recursivos e aprendizado em tempo-real, é proposta, e a estabilidade do sistema é provada com base em uma função de Lyapunov e em requisitos predefinidos. Para avaliar o método, foi usado um modelo matemático de um veículo aéreo não tripulado do tipo quadrirrotor. Os resultados simulados, com o sistema submetido a vários tipos de condições de falha, são apresentados, mostrando o bom desempenho da configuração proposta / Abstract: This monograph presents an architecture scheme for Fault Tolerant Control applications, following a dual-loop controller design approach, where the first closed loop is a regular controller and the second one is based on a neural network adaptive control strategy, with on-line adjustment of the weights. The first controller, which was here chosen as an H? norm designed controller, aims stabilize the system, and guarantee a good performance in presence of modeling errors and external disturbances. The fault tolerant controller, acting complementarily to the external loop, is the one using the neuro-adaptive technique. Its design is based on recurrent internal states, using a sliding surface to adapt the weights of the neural network, in order to accommodate the system faults, but also with a robust effect which includes correcting all external perturbations, beyond the capacity of the regular controller. A new neural network dynamic topology, with internal recursive states and on-line learning algorithm, is proposed, and its stability is proved based on a Lyapunov function and predefined requirements. To assess the method, an unmanned quad rotor flying vehicle is modeled, and the respective controllers designed. Results based on numerical simulation, with the system submitted to several different fault conditions, are presented, showing a good performance of the proposed configuration / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica