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Índice de não-detecção de erros grosseiros no processo de estimação de estado em sistemas elétricos de potência / Undetectability index of gross errors in power systems state estimationBenedito, Raphael Augusto de Souza 03 June 2011 (has links)
A partir de uma análise geométrica, do estimador de estado por mínimos quadrados ponderados, propõe-se, neste trabalho, um índice para classificação das medidas de acordo com as suas características de não refletirem grande parcela de seus erros nos resíduos do processo de estimação de estado, por mínimos quadrados ponderados. O índice proposto foi denominado Índice de Não-Detecção de Erros, ou apenas UI (Undetectability Index). As medidas com maiores UI são aquelas cujos erros grosseiros (EGs) são mais difíceis de serem detectados através de métodos que fazem uso da análise dos resíduos. Isto porque os erros dessas medidas são, de certa forma, \"mascarados\", isto é, não são refletidos nos resíduos das mesmas. Nesse sentido, a medida crítica é o caso limite de medidas cujos erros são mascarados, isto é, possui UI infinito e seu resíduo é igual a zero, independente de a mesma ter ou não EG. Para obtenção dos índices UI das medidas, desenvolveu-se um algoritmo simples e de fácil implementação. Tomando por base o índice UI, propõe-se, também, uma metodologia para processamento de EGs e dois algoritmos para projeto ou fortalecimento de sistemas de medição. Esses algoritmos possibilitam a obtenção de sistemas de medição confiáveis (observáveis e isentos de medidas críticas e de conjuntos críticas de medidas), de baixo custo e formados por medidas com índices UI menores que um valor pré-estabelecido. Para validar o índice UI e as suas aplicações propostas neste trabalho, realizaram-se diversas simulações computacionais nos sistemas de 14 e 30 barras do IEEE, tendo sido satisfatórios todos os resultados obtidos. / The present thesis proposes an index, called Undetectability Index (UI), to classify the measurements according to their characteristics of not reflecting their errors into the residuals of the weighted least squares state estimation process from a geometric analysis of this estimator. Gross errors in measurements with higher UIs are very difficult to be detected by methods based on the residual analysis, as the errors in those measurements are \"masked\", i.e., they are not reflected in the residuals. In this sense, critical measurements are the limit case of measurements that mask errors, that is, they have infinite UI and their residuals are always zero independently of their having or not gross errors. Based on the UI a methodology for gross error processing and two algorithms for metering system planning are also proposed in this thesis. These algorithms enable the obtaining of reliable measurement systems (observable and free from critical measurements and critical sets of measurements) with low investment and containing only measurements with UIs lower than a pre-established value. Several simulation results (with IEEE 14-bus and 30-bus systems) have validated the UI and its application.
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Índice de não-detecção de erros grosseiros no processo de estimação de estado em sistemas elétricos de potência / Undetectability index of gross errors in power systems state estimationRaphael Augusto de Souza Benedito 03 June 2011 (has links)
A partir de uma análise geométrica, do estimador de estado por mínimos quadrados ponderados, propõe-se, neste trabalho, um índice para classificação das medidas de acordo com as suas características de não refletirem grande parcela de seus erros nos resíduos do processo de estimação de estado, por mínimos quadrados ponderados. O índice proposto foi denominado Índice de Não-Detecção de Erros, ou apenas UI (Undetectability Index). As medidas com maiores UI são aquelas cujos erros grosseiros (EGs) são mais difíceis de serem detectados através de métodos que fazem uso da análise dos resíduos. Isto porque os erros dessas medidas são, de certa forma, \"mascarados\", isto é, não são refletidos nos resíduos das mesmas. Nesse sentido, a medida crítica é o caso limite de medidas cujos erros são mascarados, isto é, possui UI infinito e seu resíduo é igual a zero, independente de a mesma ter ou não EG. Para obtenção dos índices UI das medidas, desenvolveu-se um algoritmo simples e de fácil implementação. Tomando por base o índice UI, propõe-se, também, uma metodologia para processamento de EGs e dois algoritmos para projeto ou fortalecimento de sistemas de medição. Esses algoritmos possibilitam a obtenção de sistemas de medição confiáveis (observáveis e isentos de medidas críticas e de conjuntos críticas de medidas), de baixo custo e formados por medidas com índices UI menores que um valor pré-estabelecido. Para validar o índice UI e as suas aplicações propostas neste trabalho, realizaram-se diversas simulações computacionais nos sistemas de 14 e 30 barras do IEEE, tendo sido satisfatórios todos os resultados obtidos. / The present thesis proposes an index, called Undetectability Index (UI), to classify the measurements according to their characteristics of not reflecting their errors into the residuals of the weighted least squares state estimation process from a geometric analysis of this estimator. Gross errors in measurements with higher UIs are very difficult to be detected by methods based on the residual analysis, as the errors in those measurements are \"masked\", i.e., they are not reflected in the residuals. In this sense, critical measurements are the limit case of measurements that mask errors, that is, they have infinite UI and their residuals are always zero independently of their having or not gross errors. Based on the UI a methodology for gross error processing and two algorithms for metering system planning are also proposed in this thesis. These algorithms enable the obtaining of reliable measurement systems (observable and free from critical measurements and critical sets of measurements) with low investment and containing only measurements with UIs lower than a pre-established value. Several simulation results (with IEEE 14-bus and 30-bus systems) have validated the UI and its application.
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Diagnostic and fault-tolerant control applied to an unmanned aerial vehicle / Diagnostic et tolérance aux fautes appliqués à un droneMerheb, Abdel-Razzak 05 December 2016 (has links)
Les travaux de recherches sur la commande, le diagnostic et la tolérance aux défauts appliqués aux drones deviennent de plus en plus populaires. Il est judicieux de concevoir des lois de commande qui garantissent la stabilité et les performances du drone, non seulement dans le cas nominal, mais également en présence de fortes perturbations et de défauts.Dans cette thèse, un nouvel algorithme bio-inspiré adapté pour la recherche de solutions dans des problèmes d’optimisation est développé. Cet algorithme est utilisé pour trouver les gains des différents contrôleurs conçus pour les drones. La commande par mode glissant est utilisée pour développer deux contrôleurs passifs tolérants aux défauts pour les quadrirotors: un contrôleur par mode glissant augmentée avec un intégrateur, et un contrôleur par mode glissant implémenté en cascade. Parce que les commandes passives ont une robustesse réduite, une commande active par mode glissant est développée. Pour traiter les défauts extrêmes, un contrôleur d’urgence basé sur la conversion du quadrirotor en trirotor est développé. Les commandes actives, passives, et le contrôleur d’urgences sont ensuite intégrés pour former un contrôleur tolérant aux défauts capable de gérer un grand nombre de défaillances tout en garantissant les ressources actionneur et en limitant la charge de calcul du processeur. Finalement, des contrôleurs tolérants aux défauts, actifs et passifs, basés sur des méthodes par mode glissant du premier et deuxième ordre sont développées pour les octorotors. La commande active utilise des méthodes d’allocation de contrôles pour redistribuer les efforts sur les actionneurs sains, réduisant ainsi l’effet du défaut. / Unmanned Aerial Vehicles (UAV) are more and more popular for their civil and military applications. Classical control laws usually show weaknesses in the presence of parameter uncertainties, environmental disturbances, and actuator and sensor faults. Therefore, it is judicious to design a control law capable of stabilizing the UAV not only in the fault-free nominal cases, but also in the presence of disturbances and faults. In this thesis, a new bio-inspired search algorithm called Ecological Systems Algorithm (ESA) suitable for engineering optimization problems is developed. The algorithm is used over the thesis to find optimal gains for the fault tolerant controllers. Sliding Mode Control theory is used to develop two Passive Fault Tolerant Controllers for quadrotor UAVs: Regular and Cascaded SMC. Because Passive Controllers handle a few numbers of faults, an Active Sliding Mode Fault Tolerant Controller using Kalman Filter is developed. To overcome severe faults and failures, an emergency controller based on the Quadrotor-to-Trirotor conversion maneuver is developed. The Controllers developed so far (Passive, Active, and emergency controllers) are then integrated to form the Integrated Fault Tolerant Controller (IFTC). The IFTC is a powerful controller that is able to handle a wide number of faults, and save actuator resources as well as processor computational effort. Finally, Passive and Active Fault Tolerant Controllers are designed for octorotor UAVs based on First Order and Second Order Sliding Mode Control. The AFTC uses Dynamic and Pseudo-Inverse Control Allocation methods to redistribute the control effort among healthy actuators reducing the effect of fault.
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Re-identifikace vozidla pomocí rozpoznání jeho registrační značky / Re-Identification of Vehicles by License Plate RecognitionŠpaňhel, Jakub January 2015 (has links)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Návrh přístroje pro analýzu vzniku a šíření trhlin / Design of instrument for the analysis of crack initiation and propagationŠubrt, Stanislav January 2014 (has links)
The main goal of this thesis is to get an insight into a field of non-destructive testing using potential drop techniques that have nowadays become the standard not only in the fatigue and loading tests but also in the industry. These methods can serve to non-destructively and continuously measure material specimens, thickness, corrosion losses, deformations, spectroscopy and detection and analysis of crack geometry. They can help to identify materials and measure material changes over time. The second part of this thesis deals with designing the aperture for detection of cracks in steam and product piping using potential drop technique modified by Ing. Ladislav Korec, CSc. Last part deals with extensive testing, experimenting and evaluation of the aperture.
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