Orientador: Vicente Lopes Júnior / Banca: Paulo Carlos Kaminski / Banca: Walter Katsumi Sakamoto / Resumo: A tecnologia de materiais inteligentes se tornou uma área de crescente interesse para o desenvolvimento de estruturas que podem incorporar atuadores e sensores capazes de detectar falhas. Extensivas investigações têm sido focadas na tecnologia que integra materiais inteligentes no monitoramento das condições de sistemas. Vários estudos têm sido realizados na área de identificação de sistemas mecânicos e há uma tendência de introduzir otimização em projetos de monitoramento de sinais que permitirá automatização do processo e caracterização de falhas para sistemas complexos. O problema de identificação de variáveis ou detecção de falhas em sistemas mecânicos é uma classe de problemas inversos e, portanto, não apresenta uma solução única. O problema inverso consiste em determinar as causas baseando-se na observação dos efeitos. Nos problemas inversos os parâmetros de falha (comprimento de trinca e/ou localização) podem ser calculados no domínio da freqüência ou do tempo. A metodologia proposta neste trabalho utiliza dados no domínio da freqüência, e utiliza, em uma primeira etapa, o método da impedância elétrica para se determinar a localização das falhas. Numa segunda etapa é realizada a quantificação da intensidade de falhas, usando algoritmos genéticos. Algoritmos genéticos (AG) são processos de otimização baseados nos princípios de evolução natural. Um AG simula um processo de adaptação em uma população inicial de indivíduos através de operadores genéticos artificiais em cada geração. Em condições de otimização, cada indivíduo da população é codificado em um cromossomo, que representa uma solução genérica para o problema, enquanto a adaptação individual é avaliada por uma função de aptidão. / Abstract: Smart material technology has become an area of increasing interest for the development of structures that are able to incorporate actuator and sensor capabilities for fault detection. Extensive investigations have been focused on integrating smart material technology into health monitoring systems. Several studies have been accomplished in the area of identification of mechanical systems and there is a tendency of introducing optimization in projects of signals monitoring, which would allow automation in the process and characterization of faults, even for complex systems. The problem of variables identification or damage detection in mechanical systems is a class of inverse problem and, therefore, it doesn't present a unique solution. The inverse problem consists in determining the causes based on some observation of their effects. In inverse problems the damaged parameters (crack length and/or location) can be calculated in frequency or time domain. The proposal methodology is based on frequency domain, and it uses, in a first stage, the method of electric impedance to determine the location of the faults. Later on takes place the quantification of the fault intensities, in a second stage, by using genetic algorithms. Genetic algorithms (GA) are optimization processes based on principles of natural evolution. A GA simulates an adaptation process taking an initial population of individuals and applying artificial genetic operators in each generation. In optimization conditions, each individual of the population is coded in a string or chromosomes, which represents a trial solution for a certain problem, while the individual adaptation is evaluated through a fitness function. / Mestre

O problema da tolerância a falhas em robôs manipuladores cooperativos conectados rigidamente a um objeto indeformável é estudado nesta tese. A tolerância a falhas é alcançada através de reconfiguração do sistema de controle. Primeiro, a falha é detectada e isolada. Então, o sistema de controle é reconfigurado de acordo com a falha isolada. As falhas em robôs manipuladores são primeiramente estudadas de acordo com suas consequências no sistema cooperativo. Quatro tipos de falhas são identificados: juntas com balanço livre (sem atuadores ativos), bloqueadas, com informação incorreta de posição e com informação incorreta de velocidade. A detecção e a isolação dos dois primeiros tipos de falhas são alcançadas através de um sistema utilizando redes neurais artificiais. Redes do tipo MLP são empregadas para mapear a dinâmica dos robôs cooperativos sem falhas e uma rede RBF é utilizada para a classificação do vetor de resíduos. As falhas do tipo informação incorreta de posição ou velocidade das juntas são detectadas e isoladas através do uso das restrições impostas pela cadeia cinemática fechada presente no sistema cooperativo. Quando falhas do tipo juntas com balanço livre ou bloqueadas são isoladas, as leis de controle são reconfiguradas. Para estes casos, controladores híbridos de movimento e esmagamento do objeto são deduzidos. Quando falhas do tipo informação incorreta de posição ou velocidade das juntas são isoladas, as medidas afetadas são substituídas por valores estimados. Resultados obtidos em simulações e em robôs cooperativos reais mostram que a metodologia proposta é viável. / The problem of fault tolerance in cooperative manipulators rigidly connected to an undeformable load is addressed in this work. Fault tolerance is reached by reconfiguration of the control system. The faults are firstly detected and isolated. Then, the control system is reconfigured according to the isolated fault. Four faults are considered: free-swinging joint faults, locked joint faults, incorrectly measured joint position faults, and incorrectly measured joint velocity faults. Free-swinging and locked joint faults are detected and isolated by artificial neural networks. MLP’s are utilized to reproduce the dynamics of the fault-free system and an RBF is used to classify the residual vector. Incorrectly measured joint position and velocity faults are detected and isolated based on the kinematic constraints imposed on the cooperative system. When free-swinging and locked joint faults are isolated, the control laws are reconfigured. Control laws for motion and squeeze of the object are developed in these cases. When incorrectly measured joint position faults and incorrectly measured joint velocity faults are isolated, the faulty measurements are replaced by their estimates. Results obtained in simulations and in real cooperative robots indicate that the proposed methodology is viable.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-24T15:00:02Z No. of bitstreams: 1 Ronnie.pdf: 3320281 bytes, checksum: 56be4f928c1366ece428d2ae6caf9627 (MD5) / Made available in DSpace on 2017-08-24T15:00:02Z (GMT). No. of bitstreams: 1 Ronnie.pdf: 3320281 bytes, checksum: 56be4f928c1366ece428d2ae6caf9627 (MD5) Previous issue date: 2012-08-31 / This work aims to monitor and analyze the data from the instrumentation system of a substation as a way to identify false alarms, which can result in a decision by the mistaken maintenance and operation. This project was conceived because of the need for a research and development project which is called Maintenance Management Center (MMC) whose overall objective is to assist in the maintenance of their equipment operational intervention. Data is extracted from the automation system that has digital relay protection function and measurement of the electric grid, passing through a sequence of data processing to achieve the results that will serve for the detection and diagnosis of faults. We applied methods based on quantitative model by transforming the data system of continuous variables (SVC) and qualitative data by transforming the system of discrete event (SDE) applying analytical redundancy techniques and neural networks respectively, thus aiming a simplified model for detection and diagnosis fault (DDF). The model has been designed taking into account the characteristics DDF due to its stages, thereby providing a good system failure recovery. Know filter if certain event is real or a false alarm is not an easy task, but this system will have to meet this purpose. Technological resources are used fairly consolidated in the industrial process for the integration of the solution, because the time factor and information processing are critical in the results generated by the system recovery. Another key point of this trial was to have developed a system based on experiential knowledge, because it has higher robustness in results. / Este trabalho tem como objetivo monitorar e analisar os dados provenientes do sistema de instrumentação de uma subestação como forma de identificar falsos alarmes, que pode acarretar em uma tomada de decisão equivocada por parte da manutenção e operação. Este projeto foi concebido devido à necessidade de um projeto de pesquisa e desenvolvimento que se intitula Centro de Gestão da Manutenção (CGM) cujo objetivo global é auxiliar a manutenção na intervenção operacional de seus equipamentos. Os dados são extraídos do sistema de automação provenientes dos reles digitais que tem função de proteção e medição da rede elétrica, passando por um sequencia de transformação dos dados até chegar aos resultados, que servirá para detecção e diagnostico de falhas. Foram aplicados métodos baseados no modelo quantitativo através da transformação dos dados do sistema de variáveis contínuas (SVC) e qualitativo através da transformação dos dados do sistema de eventos discretos (SED) aplicando técnicas de redundância analítica e redes neurais respectivamente, objetivando assim um modelo simplificado para detecção e diagnóstico da falha (DDF). O modelo foi concebido levando em consideração as características DDF decorrente de suas etapas, propiciando assim um bom sistema de recuperação de falha. Saber filtrar se determinado evento é real ou um falso alarme não é uma tarefa fácil, porém este sistema terá que atender este propósito. Foram utilizados recursos tecnológicos bastante consolidados no processo industrial para garantir a integração da solução, pois o fator tempo e o processamento da informação são decisivos nos resultados gerados pelo sistema de recuperação. Outro ponto fundamental neste trabalho foi ter desenvolvido um sistema baseado no conhecimento experimental, pois se tem maior robustez nos resultados.

O trabalho proposto tem por objetivo avaliar a viabilidade de localização de falhas elétricas, por meio da análise de assinaturas magnéticas resultantes do sistema elétrico. Assim, diversos algoritmos - descritos na literatura científica atual e aplicáveis ao processamento de sinais conduzidos - foram analisados com o objetivo de verificar a possibilidade de complementar as metodologias já desenvolvidas para a detecção e classificação de falhas, de uma maneira não invasiva e via análise de assinaturas magnéticas resultantes. Diferentemente do processo de monitoração tradicional, cujos sensores precisam estar fisicamente conectados aos circuitos analisados, propõe-se estudar a viabilidade da análise dos sinais provenientes da assinatura magnética dos distúrbios para localizar falhas. Ressalta-se, assim, a característica não invasiva desse processo. A avaliação da metodologia proposta foi realizada através da escolha de casos de sensibilidade, cujos resultados teóricos e provenientes de simulações foram utilizados na análise de sua viabilidade. / The proposed study aims to evaluate the feasibility of determinig the fault location in electrical systems, by analyzing the resulting magnetic signatures. Thus, several algorithms - described in the current scientific literature and for the processing of conducted signals - will be analyzed in order to verify the possibility of complementing the methodologies already developed for fault detection and classification, a non-invasive way and by analysis magnetic signatures resulting. Differently from traditional monitoring process, in which the sensors need to be physically connected to the analyzed circuits. It should be noted, the characteristic of this methodology as a non-invasive procedure. The evaluation of the proposed methodology will be carried out through the choice of sensitivity cases, which theoretical results obtained from simulations will be used to analyze its viability.

<p>U disertaciji je predložena metoda za pouzdano otkrivanje kvara rotora<br />trofaznog kaveznog asinhronog motora. Metoda je zasnovana na<br />identifikaciji obeležja kvara rotora iz signala terminalnih veličina<br />jednofazno napojenog trofaznog kaveznog motora u stacionarnom stanju<br />pogona. Predložena metoda eliminiše potrebu za postojanja opterećenja<br />motora, što je osnovna prednost u odnosu na rešenja iz literature. Sva<br />teorijska razmatranja su praćena odgovarajućim rezultatima računarskih<br />simulacija, da bi se potom sprovela eksperimentalna verifikacija i<br />potvrdila efikasnost predložene metode. Takođe, predstavljen je<br />postupak za kvantitativnu procenu oštećenja štapnih provodnika rotora.</p> / <p>In this Doctoral dissertation, a novel method for broken rotor bar fault detection<br />in a three-phase squirrel-cage induction motor (IM) is introduced. The proposed<br />method is non-invasive and it is based on the analysis of the IM terminal<br />quantities in a single-phase steady-state operating condition. Compared to<br />conventional fault detection techniques, the developed method does not require<br />any loading on the motor, which is the main benefit of the method. The faulty<br />condition of broken rotor bars was investigated analytically, while the<br />effectiveness of the proposed method was proven by the variety of computer<br />simulations and experimental results. Based on these results, a methodology for<br />the quantification of broken rotor bars in the IM has been presented.</p>

Ces dernières années, la fiabilité et la continuité de service des chaînes de traction sont devenus des défis majeurs afin que les véhicules électriques puissent accéder au marché grand public de l’automobile. En effet, la présence de défauts dans les chaînes de traction peut conduire à des dysfonctionnements dans les véhicules et ainsi réduire ses performances par rapport aux véhicules conventionnels. Dans l’hypothèse où des défauts électriques se produisaient, les chaînes de traction des véhicules électriques à pile à combustible devraient inclure des topologies et/ou contrôles tolérants aux défauts pour les différents convertisseurs DC/DC et DC/AC. Dans le cadre de ce travail de recherche, un focus est fait sur le convertisseur DC/DC associé à la pile à combustible de la chaine de traction. Ce dernier doit répondre aux problématiques majeures des applications véhicule électrique à pile à combustible à savoir : faible masse et petit volume, haute efficacité énergétique, réduction de l’ondulation de courant d’entrée et fiabilité. A la base d’une recherche bibliographique poussée sur les structures non-isolées et isolées appropriées pour des applications PàC, une topologie de convertisseur DC/DC entrelacé a été choisie permettant de respecter les contraintes des véhicules électriques à pile à combustible.Ce travail de thèse a ensuite consisté à dimensionner et contrôler la structure de convertisseur DC/DC tolérante aux défauts choisie pour les véhicules à PàC. Des algorithmes de gestion des modes dégradés de ce convertisseur ont été développés et implémentés expérimentalement. A ce titre, l’interaction PàC-convertisseur DC/DC a été étudiée. Une approche théorique, de simulation et expérimentale a été mise en oeuvre pour mener à bien ce travail. / Over the last years, reliability and continuity of service of powertrains have become major challenge so that the fuel cell electric vehicles (CFEV) can access to the mass automotive market. Indeed, the presence of faults in powertrains can lead up to malfunctions in the vehicle and consequently reduce its performances compared with conventional vehicles. In the case of electrical faults, powertrains of FCEV have to include fault tolerant topology and/or control for the different DC/DC and DC/AC converters. Within the framework of this research work, the study is focused on DC/DC converter combined with a Proton Exchange Membrane Fuel Cell (PEMFC). The DC/DC converter must respond to challenging issues in FCEV applications such as: low weight and small volume, high energy efficiency, fuel cell current ripple reduction and reliability. Basing on a thorough bibliographical study on non-isolated and isolated DC/DC converter topologies, an interleaved DC/DC boost converter has been chosen, meeting the FCEV requirements.The purpose of this thesis has then consisted in sizing and controlling the chosen fault-tolerant DC/DC converter topology for FCEVs. Algorithms for degraded mode management of this converter have been developed and implemented experimentally. As such, the interaction between PEMFC and interleaved DC/DC boost converter has been investigated. A theoretical approach, simulation and experimental results have been carried out to complete this work.

[pt] Este trabalho investiga métodos de detecção de falhas baseados em sistemas imunológicos artificiais, especificamente aqueles baseados no algoritmo de seleção negativa (NSA) e em outras técnicas de reconhecimento próprio/nãopróprio. Inicialmente, foi proposto um esquema de representação baseado em hiperesferas com centros e raios variáveis e três modelos capazes de gerar detectores, com esta representação, de forma eficiente. O primeiro modelo utiliza algoritmos genéticos onde cada gene do cromossomo contém um índice para um ponto de uma distribuição quasi-aleatória que servirá como centro do detector e uma função decodificadora responsável por determinar os raios apropriados. A aptidão do cromossomo é dada por uma estimativa do volume coberto através uma integral de Monte Carlo. O segundo modelo utiliza o particionamento Quadtree para gerar o posicionamento dos detectores e o valor dos raios. Este modelo pode realizar o particionamento a partir de uma função de detecção ou através de divisões recursivas de um detector inicial que ocupa todo o espaço. O terceiro modelo é inspirado nas redes imunológicas. Neste modelo, as células B representam os detectores e a rede formada por eles dá a posição e o raio de cada detector. Experimentos com dados sintéticos e reais demonstram a capacidade dos algoritmos propostos e que eles apresentam melhorias nos aspectos de escalabilidade e desempenho na detecção de falhas. / [en] This work investigates fault detection methods based on Artificial Immune Systems, specifically the negative selection algorithm (NSA) and other self/nonself recognition techniques. First, there was proposed a representation scheme based on hyperspheres with variable center and radius, and three models, which are very capable to generate detectors, based on that representation scheme, in an effective way. The first model employs Genetic Algorithms where each chromosome gene represents an index to a point in a quasi- random distribution, that will serve as a detector center, a decoder function will be responsible to determine the appropriate radius. The chromosome fitness is given by a valuation of the covered volume, which is calculated through a Monte Carlo integral. The second model uses the Quadtree space partition technique to generate the detectors positions and their radius. The space partition could be done by using a detection function or by recursive divisions of an initial detector that occupies the whole space. In third model, inspired on immune networks, the B cells represent the detectors and the network that is established by them gives the location and radius of each detector. Experiments with syntetic and real data show that the proposed algorithms improve scalability and perform better in fault detection.

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.

<p>This master thesis report discusses the use of self-organizing maps in a diesel engine management system. Self-organizing maps are one type of artificial neural networks that are good at visualizing data and solving classification problems. The system studied is the Vindax(R) development system from Axeon Ltd. By rewriting the problem formulation also function estimation and conditioning problems can be solved apart from classification problems. </p><p>In this report a feasibility study of the Vindax(R) development system is performed and for implementation the inlet air system is diagnosed and the engine torque is estimated. The results indicate that self-organizing maps can be used in future diagnosis functions as well as virtual sensors when physical models are hard to accomplish.</p>

This dissertation focused on the IRIS design since this will likely be one of the designs of choice for future deployment in the U.S and developing countries. With a net 335 MWe output IRIS novel design falls in the “medium” size category and it is a potential candidate for the so called modular reactors, which may be appropriate for base load electricity generation, especially in regions with smaller electricity grids, but especially well suited for more specialized non-electrical energy applications such as district heating and process steam for desalination. The first objective of this dissertation is to evaluate and quantify the performance of a Nuclear Power Plant (NPP) comprised of two IRIS reactor modules operating simultaneously with a common steam header, which in turn is connected to a single turbine, resulting in a steam-mixing control problem with respect to “load-following” scenarios, such as varying load during the day or reduced consumption during the weekend. To solve this problem a single-module IRIS SIMULINK model previously developed by another researcher is modified to include a second module and was used to quantify the responses from both modules. In order to develop research related to instrumentation and control, and equipment and sensor monitoring, the second objective is to build a two-tank multivariate loop in the Nuclear Engineering Department at the University of Tennessee. This loop provides the framework necessary to investigate and test control strategies and fault detection in sensors, equipment and actuators. The third objective is to experimentally develop and demonstrate a fault-tolerant control strategy using this loop. Using six correlated variables in a single-tank configuration, five inferential models and one Auto-Associative Kernel Regression (AAKR) model were developed to detect faults in process sensors. Once detected the faulty measurements were successfully substituted with prediction values, which would provide the necessary flexibility and time to find the source of discrepancy and resolve it, such as in an operating power plant. Finally, using the same empirical models, an actuator failure was simulated and once detected the control was automatically transferred and reconfigured from one tank to another, providing survivability to the system.