Made available in DSpace on 2014-12-17T15:47:04Z (GMT). No. of bitstreams: 1 SeverinoPGN_TESE.pdf: 2322839 bytes, checksum: eda5c48fde7c920680bcb8d8be8d5d21 (MD5) Previous issue date: 2014-02-27 / The camera motion estimation represents one of the fundamental problems in Computer Vision and it may be solved by several methods. Preemptive RANSAC is one of them, which in spite of its robustness and speed possesses a lack of flexibility related to the requirements of applications and hardware platforms using it. In this work, we propose an improvement to the structure of Preemptive RANSAC in order to overcome such limitations and make it feasible to execute on devices with heterogeneous resources (specially low budget systems) under tighter time and accuracy constraints. We derived a function called BRUMA from Preemptive RANSAC, which is able to generalize several preemption schemes, allowing previously fixed parameters (block size and elimination factor) to be changed according the applications constraints. We also propose the Generalized Preemptive RANSAC method, which allows to determine the maximum number of hipotheses an algorithm may generate. The experiments performed show the superiority of our method in the expected scenarios. Moreover, additional experiments show that the multimethod hypotheses generation achieved more robust results related to the variability in the set of evaluated motion directions / A estima??o de pose/movimento de c?mera constitui um dos problemas fundamentais na vis?o computacional e pode ser resolvido por v?rios m?todos. Dentre estes m?todos se destaca o Preemptive RANSAC (RANSAC Preemptivo), que apesar da robustez e velocidade apresenta problemas de falta de flexibilidade em rela??o a requerimentos das aplica??es e plataformas computacionais utilizadas. Neste trabalho, propomos um aperfei?oamento da estrutura do Preemptive RANSAC para superar esta limita??o e viabilizar sua execu??o em dispositivos com recursos variados (enfatizando os de poucas capacidades) atendendo a requisitos de tempo e precis?o diversos. Derivamos do Preemptive RANSAC uma fun??o a que chamamos BRUMA, que ? capaz de generalizar v?rios esquemas de preemp??o e que permite que par?metros anteriormente fixos (tamanho de bloco e fator de elimina??o) sejam configurados de acordo com as restri??es da aplica??o. Propomos o m?todo Generalized Preemptive RANSAC (RANSAC Preemptivo Generalizado) que permite ainda alterar a quantidade m?xima de hip?teses a gerar. Os experimentos demonstraram superioridade de nossa proposta nos cen?rios esperados. Al?m disso, experimentos adicionais demonstram que a gera??o de hip?teses multim?todos produz resultados mais robustos em rela??o ? variabilidade nos tipos de movimento executados

La méconnaissance de la géométrie réelle d'une structure mène à une évaluation incorrecte de son état. Par conséquent, une estimation imprécise de sa capacité portante, sa durabilité, sa stabilité et la nécessité de mettre en place une réparation ou un renforcement. En outre, l'optimisation du temps requis pour le processus de réparation a besoin de bien connaître les différentes parties de la structure à évaluer et également pour éviter les zones critiques telles que les aciers, les câbles, etc., lors de la réparation. Par conséquent, il est nécessaire d'utiliser des techniques d'évaluation non destructive (END) afin de connaître la géométrie réelle de la structure, notamment l'emplacement des armatures dans les structures en béton armé. Le GPR est considéré comme une technique non-destructive idéale pour détecter et localiser les renforts. Cependant, sa précision de localisation est limitée. Le but de ce projet de recherche a donc été d'accroître la précision du GPR en matière de reconnaissance géométrique interne de structures en béton armé. L'objectif principal de cette étude est de localiser précisément le positionnement des armatures dans le plan ausculté ainsi qu'en profondeur. Pour atteindre cet objectif, une nouvelle méthodologie de mesures et du traitement des signaux GPR a été proposée dans cette étude. Plusieurs configurations d'acquisition de données en utilisant des signaux simulés sont testées pour proposer et développer un algorithme d'imagerie du milieu de propagation afin de définir sa géométrie interne et de localiser précisément les barres de renforcement. Des traitements supplémentaires sont appliqués pour améliorer la précision de la détection et pour identifier les différentes interfaces dans le milieu testé. L'algorithme et le traitement sont appliqués aux signaux simulés. Des validations expérimentales ont ensuite été appliquées aux signaux réels acquis sur différentes dalles en béton armé. L'objectif est de tester la capacité de l'algorithme d'imagerie proposé pour localiser différents objets enfouis. Les résultats encourageants montrent que cet algorithme est capable d'estimer la position de différents objets enfouis et pas uniquement les armatures avec une erreur d'estimation de (0-1) mm. Les performances de l'algorithme ont été comparées à celles d'une méthode de migration et aux résultats de mesure obtenus avec un pachomètre. Ces comparaisons ont systématiquement révélé une meilleure précision de la localisation avec l'algorithme développé.Une autre étude a été proposée dans ce travail en testant l'algorithme avec des signaux réels modifiés. Ces signaux sont produits en réduisant le gain le moins possible. La conclusion la plus évidente de cette étude est que l'algorithme proposé est capable de localiser les différents objets même si les signaux réfléchis par eux sont de faible amplitude. / Lack of acquaintance in the real geometry of a structure leads to incorrect evaluation of its state. Consequently, this will lead to inaccurate estimation of bearing capacity, durability, stability and moreover, the need for repair or strengthening. Furthermore, optimization of the required time for repair process needs to well recognize the parts of structure to be assessed and also to avoid the critical zones such as reinforcing bars, cables, etc., during repairing. Therefore; it becomes necessary to use a non-destructive testing (NDT) method in order to know the real geometry of structure in particular, the location of reinforcements in reinforced concrete structures. GPR is considered as an ideal non-invasive technique in detecting and locating these reinforcements. However, its accuracy in localization is limited. The aim of this research project has therefore been to increase the accuracy of GPR in recognizing the internal geometry of reinforced concrete structures. The main objective of this study is to locate accurately the position of reinforcements into three dimensions. To achieve this purpose, a new methodology for GPR measurement and processing is proposed in this study.Several configurations of data acquisition using simulated signals are tested to propose and develop an appropriate imaging algorithm for the propagation medium to imagine its internal geometry and to locate accurately the reinforcing bars. Further processing are applied to improve the accuracy of detection and to identify the different interfaces in the tested medium. Both algorithm and processing are applied on simulated signals. Subsequent experimental validations have been applied using real signals acquired from different real reinforced concrete slabs. The goal is to test the ability of proposed imaging algorithm for the localization of different targets. The encouraging results indicate that this algorithm is able to estimate the position of different buried targets and not only the reinforcing bars with an estimation error of (0-1)mm.The performance of proposed algorithm has compared to those of migration method and to the results obtained from pachometer. These comparisons have systematically revealed a better localization accuracy using the developed algorithm.Another study has been proposed in this work by testing the algorithm using modified real signals. These signals are produced by reducing the gain as less as possible. The most obvious finding to emerge from this study is that the proposed algorithm is able to localize the different goals even if the signals reflected by them are of low amplitude.

Made available in DSpace on 2015-03-26T13:27:54Z (GMT). No. of bitstreams: 1 texto completo.pdf: 4751258 bytes, checksum: 0e480b21213f063f9d31d1243a36f77a (MD5) Previous issue date: 2010-06-29 / This paper aims to analyze the Ground Penetrating RADAR as tool in the determination of the thickness of the layers of the flexible road pavement of automatic way and the density of the asphalt layer supported by integrated testing of GPR and geotechnical data. The first experiment was conducted at the Presidente Dutra highway (BR116), Pirai - RJ, while the data for the second experiment were obtained from the BR040 highway, Sete Lagoas - MG. In order to achieve the objectives of this study, two methodologies were developed: the first one, directed to the identification of the thicknesses of the layers of flexible pavements of automated way; the second one, focused on determining the density of the layer of asphalt surfaces. The first methodology showed promising results, once it presented good classification results for the classes 1 (off-set) and 3 (macadam), however, was confusion between the "blocks" classified for the classes 2 (asphalt) and 4 (subgrade). A possible alternative, for improvement, would be: to use other texture extractor of the wavelet transform family; to use another type of interpolation, using a that better represents the trends of the coefficients to be generated the surface; to increase the number of training and testing samples, or even to use another type of classifier, such as Artificial Neural Networks. However, this is a field that is worth being investigated more deeply, since the results proved to be significant. The second methodology, regarding the correlation of the density of the asphalt layer through the dielectric value, measured by means an ground coupled antenna, of 1,6GHz, using the technique of the reflection, it presented satisfactory values in spite of the few sampling points, showing to be a good alternative to determine indirectly the density of the asphalt layer and for future works in the area. / Este trabalho tem o propósito de analisar o desempenho do RADAR de penetração no solo como ferramenta na determinação das espessuras das camadas do pavimento rodoviário flexível de maneira automática e a densidade da camada de revestimento apoiado em testes integrados de GPR e dados geotécnicos. O primeiro experimento foi realizado na rodovia Presidente Dutra (BR116), município de Piraí - RJ, em quanto os dados para o segundo experimento foram obtidos na rodovia BR040, município de Sete Lagoas - MG. Para atingir os objetivos do trabalho foram elaboradas duas metodologias: a primeira delas, direcionada à identificação das espessuras das camadas de pavimentos flexíveis de modo automatizado; a segunda, voltada para a determinação da densidade da camada de revestimento asfáltico. A primeira metodologia apresentou, de uma maneira geral, resultados promissores, uma vez que foram bons os resultados de classificação para as classes 1 (off-set) e 3 (macadame), no entanto, houve confusão entre os “blocos” classificados para as classes 2 (revestimento) e 4 (subleito). Uma possível alternativa para a melhoria dos resultados seria mudar o extrator de textura utilizado (transformada wavelet), valeria apena testar outros extratores da família wavelet; outra opção seria utilizar outro tipo de interpolador, usando um que pegue mais as tendências dos coeficientes ao se gerar a superfície; também seria interessante aumentar o número de amostras de treinamento e teste, ou até mesmo, utilizar outro tipo de classificador, como por exemplo, Redes Neurais Artificiais. Todavia, esse é um campo que vale ser pesquisado mais profundamente, uma vez que os resultados alcançados se mostraram esperançosos. A segunda metodologia, referente à correlação da densidade da camada de revestimento através do valor dielétrico, medido por meio de uma antena de contato no solo, de 1,6 GHz, utilizando a técnica da reflexão, apresentou valores satisfatórios apesar dos poucos pontos amostrados, mostrando ser uma boa escolha para se determinar a densidade da camada de revestimento de maneira indireta e para trabalhos futuros na área.

Made available in DSpace on 2014-12-17T14:09:15Z (GMT). No. of bitstreams: 1 EduardoHSA_TESE3red.pdf: 5316067 bytes, checksum: 9b841153bb325e14b32dc463a70e5a45 (MD5) Previous issue date: 2013-01-25 / This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water) / Esta tese apresenta a elabora??o de uma proposta metodol?gica para o desenvolvimento de um sistema inteligente, capaz de obter automaticamente a porosidade efetiva, em camadas sedimentares, a partir de um banco de dados constru?do com informa??es do Radar de Penetra??o no Solo (Ground Penetrating Radar GPR). O sistema inteligente foi constru?do para modelar a rela??o entre a porosidade (vari?vel resposta) e os atributos eletromagn?ticos do GPR (vari?veis explicativas). Com ele foi estimada a porosidade utilizando modelo de rede neural artificial (Multilayer Perceptron - MLP) e regress?o linear m?ltipla. Os dados da vari?vel resposta e das vari?veis explicativas foram obtidos em laborat?rio e em levantamentos GPR delineados em s?tios controlados em campo e laborat?rio. O sistema inteligente proposto possui a capacidade de estimar a porosidade a partir de qualquer banco de dados dispon?vel, que envolvam as mesmas vari?veis utilizadas nesta tese. A arquitetura da rede neural utilizada pode ser modificada de acordo com a necessidade existente, adequando-se aos bancos de dados dispon?veis. A utiliza??o do Modelo de Regress?o Linear M?ltipla permitiu que fosse identificada e quantificada a influ?ncia (grau de efeito) de cada vari?vel explicativa na estimativa da porosidade. A metodologia proposta pode revolucionar o uso do GPR por permitir, n?o apenas o imageamento das geometrias e f?cies sedimentares, mas principalmente a obten??o autom?tica da porosidade um dos par?metros mais importantes na caracteriza??o de rochas reservat?rios (petrol?feros ou aqu?feros)

Made available in DSpace on 2015-03-13T17:08:38Z (GMT). No. of bitstreams: 1 VictorAS_DISSERT.pdf: 7384161 bytes, checksum: 52530e2ae828c1016d52cf0da52743d6 (MD5) Previous issue date: 2013-05-21 / In this paper we present the methodological procedures involved in the digital imaging in mesoscale of a block of travertines rock of quaternary age, originating from the city of Acquasanta, located in the Apennines, Italy. This rocky block, called T-Block, was stored in the courtyard of the Laborat?rio Experimental Petr?leo "Kelsen Valente" (LabPetro), of Universidade Estadual de Campinas (UNICAMP), so that from it were performed Scientific studies, mainly for research groups universities and research centers working in brazilian areas of reservoir characterization and 3D digital imaging. The purpose of this work is the development of a Model Solid Digital, from the use of non-invasive techniques of digital 3D imaging of internal and external surfaces of the T-Block. For the imaging of the external surfaces technology has been used LIDAR (Light Detection and Range) and the imaging surface Interior was done using Ground Penetrating Radar (GPR), moreover, profiles were obtained with a Gamma Ray Gamae-spect?metro laptop. The goal of 3D digital imaging involved the identification and parameterization of surface geological and sedimentary facies that could represent heterogeneities depositional mesoscale, based on study of a block rocky with dimensions of approximately 1.60 m x 1.60 m x 2.70 m. The data acquired by means of terrestrial laser scanner made available georeferenced spatial information of the surface of the block (X, Y, Z), and varying the intensity values of the return laser beam and high resolution RGB data (3 mm x 3 mm), total points acquired 28,505,106. This information was used as an aid in the interpretation of radargrams and are ready to be displayed in rooms virtual reality. With the GPR was obtained 15 profiles of 2.3 m and 2 3D grids, each with 24 sections horizontal of 1.3 and 14 m vertical sections of 2.3 m, both the Antenna 900 MHz to about 2600 MHz antenna. Finally, the use of GPR associated with Laser Scanner enabled the identification and 3D mapping of 3 different radarf?cies which were correlated with three sedimentary facies as had been defined at the outset. The 6 profiles showed gamma a low amplitude variation in the values of radioactivity. This is likely due to the fact of the sedimentary layers profiled have the same mineralogical composition, being composed by carbonate sediments, with no clay in siliciclastic pellitic layers or other mineral carrier elements radioactive / Nesse trabalho s?o apresentados os procedimentos metodol?gicos envolvidos no imageamento digital em mesoescala de um bloco de rochas travertinas de idade quatern?ria, oriundas da cidade de Acquasanta, situada na cordilheira dos Apeninos, na It?lia. Esse bloco rochoso, denominado de T-Block, foi armazenado no p?tio do Laborat?rio Experimental de Petr?leo "Kelsen Valente" (LabPetro), da Universidade Estadual de Campinas (UNICAMP) para que a partir dele fossem realizados estudos cient?ficos, principalmente para grupos de pesquisa das universidades e centros de pesquisa brasileiros que atuam nas ?reas de caracteriza??o de reservat?rio e imageamento digital 3D. A proposta deste trabalho consiste na elabora??o de um Modelo de S?lido Digital, a partir da utiliza??o de t?cnicas n?o-invasivas de imageamento digital 3D das superf?cies interna e externa do T-Block. Para o imageamento das superf?cies externas foi utilizada a tecnologia LIDAR (Light Detection and Range) e para o imageamento das superf?cies internas foi feita a utiliza??o do Ground Penetrating Radar (GPR), al?m disso, foram adquiridos perfis de Gamma Ray com um Gamaespect?metro port?til. O objetivo do imageamento digital 3D consistiu na identifica??o e parametriza??o de superf?cies geol?gicas e de f?cies sedimentares que pudessem representar heterogeneidades deposicionais em mesoescala, tomando como base de estudo um bloco rochoso com dimens?es de aproximadamente 1,60m x 1,60m x 2,70 m. Os dados adquiridos por meio do Laser Scanner terrestre disponibilizaram informa??es espaciais georreferenciadas da superf?cie do bloco (X, Y, Z), al?m de valores de varia??o de intensidade de retorno do raio laser e dados RGB com alta resolu??o (3 mm x 3 mm), totalizando 28.505.106 pontos adquiridos. Essas informa??es foram utilizadas como auxilio durante a interpreta??o dos radargramas e est?o prontas para ser exibidas em salas de realidade virtual. Com o GPR, foram adquiridos 15 perfis de 2,3 m e 2 grids 3D, cada um com 24 se??es horizontais de 1,3 m e 14 se??es verticais de 2,3 m, tanto com a antena de 900 MHz quanto com a antena de 2600 MHz. Por fim, o uso do GPR associado ao Laser Scanner possibilitou a identifica??o e mapeamento 3D de 3 radarf?cies distintas as quais foram correlacionadas a 3 f?cies sedimentares j? que j? haviam sido definidas no inicio do trabalho. Os 6 perfis de raios gama mostraram uma baixa varia??o na amplitude dos valores de radioatividade. Provavelmente, isso ocorreu devido ao fato das camadas sedimentares perfiladas possu?rem a mesma composi??o mineral?gica, sendo compostas por sedimentos carbon?ticos, com aus?ncia de argila silicicl?stica nas camadas mais pel?ticas ou de outro mineral portador de elementos radioativos

Le géoradar, ou Ground Penetrating Radar (GPR) en anglais, est une méthode non destructive couramment utilisée pour l'auscultation des ouvrages en béton. L'intérêt de cette méthode réside sur sa capacité à ausculter rapidement des très grandes surfaces, elle est de plus en plus employée en Génie Civil. Habituellement, cette méthode est utilisée en Génie Civil pour la localisation les aciers de renforcements, ou bien pour l'estimation de l'épaisseur d'enrobage du béton. Toutefois, la méthode GPR peut aussi être utilisée pour l'auscultation du béton. En effet, le béton est un matériau diélectrique poreux qui peut modifier la propagation des ondes électromagnétiques (EM). Les résultats les plus récents présentent la capacité du GPR à évaluer la teneur en eau. Cependant, le GPR pourrait très bien aussi être utilisé pour la détection des ions chlorure présents dans la solution interstitielle du béton, car comme les chlorures modifient la conductivité du béton ils sont susceptibles d'atténuer les ondes électromagnétiques. Néanmoins, seulement quelques études ont été menées dans ce domaine. Par conséquent, dans cette étude, nous proposons d'utiliser les ondes EM du géoradar pour estimer conjointement la teneur en eau et la teneur en chlorure du béton pour différents corps d'épreuves. Pour cela, plusieurs séries de corps d'épreuves sont utilisées avec des modes de contaminations par les chlorures différents. Une procédure de mesure de la vitesse à partir de l'analyse des signaux réfléchis est proposée. On démontre que la vitesse des ondes EM est essentiellement affectée par la teneur en eau alors que l'atténuation est sensible à la fois à la teneur en eau et à la teneur en chlorures. Ensuite, dans un second temps, nous testons différents modèles de permittivité pour prédire les mesures de constante diélectrique et du facteur de pertes évalués à partir des mesures par GPR ou de résistivité électrique. / Ground Penetrating Radar (GPR) is an usual nondestructive testing method for the assessment of concrete structures. The benefit of this method lies within its ability to assess quickly a large scale of concrete surface. Generally, GPR is used for the localization of reinforcements or for the thickness measurements. However, GPR can be also used for the diagnosis of concrete because concrete is a porous dielectric material which can modify the propagation of the electromagnetic (EM) waves. Most common results present the ability of GPR to assess moisture. But, GPR could be also used to detect the presence of chlorides into the interstitial concrete solution as chlorides can modify the concrete conductivity and altered the electromagnetic signal waves. However, only few studies have been carry-out on that field. Therefore, in this study, we propose to use GPR electromagnetic waves to evaluate both the water content and the chloride content inside the interstitial concrete solution of several tests concrete samples. So, several groups of concrete samples with the same formulation will be conditioned for different chloride contamination modes. Thereafter, a velocity measurement process will be proposed from the reflected signal wave analysis. In that process, we will show that the velocity is only affected by the water content while the attenuation strongly affected by both the water content and the chloride content. Furthermore, we will test several permittivity models to predict the dielectric permittivity and the loss factor estimated from the concrete samples measurements with the GPR device and the electrical resistivity device.

No description available.

[EN] Over time, due to multiple operational and maintenance activities, the networks of water supply systems (WSSs) undergo interventions, modifications or even are closed. In many cases, these activities are not properly registered. Knowledge of the paths and characteristics (status and age, etc.) of the WSS pipes is obviously necessary for efficient and dynamic management of such systems. This problem is greatly augmented by considering the detection and control of leaks. Access to reliable leakage information is a complex task. In many cases, leaks are detected when the damage is already considerable, which brings high social and economic costs. In this sense, non-destructive methods (e.g., ground penetrating radar - GPR) may be a constructive response to these problems, since they allow, as evidenced in this thesis, to ascertain paths of pipes, identify component characteristics, and detect primordial water leaks. Selection of GPR in this work is justified by its characteristics as non-destructive technique that allows studying both metallic and non-metallic objects. Although the capture of information with GPR is usually successful, such aspects as the capture settings, the large volume of generated information, and the use and interpretation of such information require high level of skill and experience. This dissertation may be seen as a step forward towards the development of tools able to tackle the problem of lack of knowledge on the WSS buried assets. The main objective of this doctoral work is thus to generate tools and assess their feasibility of application to the characterization of components of WSSs from GPR images. In this work we have carried out laboratory tests specifically designed to propose, develop and evaluate methods for the characterization of the WSS buried components. Additionally, we have conducted field tests, which have enabled us to determine the feasibility of implementing such methodologies under uncontrolled conditions. The methodologies developed are based on techniques of intelligent data analysis. The basic principle of this work has involved the processing of data obtained through the GPR to look for useful information about WSS components, with special emphasis on the pipes. After performing numerous activities, one can conclude that, using GPR images, it is feasible to obtain more information than the typical identification of hyperbolae currently performed. In addition, this information can be observed directly, e.g. more simply, using the methodologies proposed in this doctoral work. These methodologies also prove that it is feasible to identify patterns (especially with the preprocessing algorithm termed Agent race) that provide fairly good approximation of the location of leaks in WSSs. Also, in the case of pipes, one can obtain such other characteristics as diameter and material. The main outcomes of this thesis consist in a series of tools we have developed to locate, identify and visualize WSS components from GPR images. Most interestingly, the data are synthesized and reduced so that the characteristics of the different components of the images recorded in GPR are preserved. The ultimate goal is that the developed tools facilitate decision-making in the technical management of WSSs, and that such tools can even be operated by personnel with limited experience in handling non-destructive methodologies, specifically GPR. / [ES] Con el paso del tiempo, y debido a múltiples actividades operacionales y de mantenimiento, las redes de los sistemas de abastecimiento de agua (SAAs) sufren intervenciones, modificaciones o incluso, son clausuradas, sin que, en muchos casos, estas actividades sean correctamente registradas. El conocimiento de los trazados y características (estado y edad, entre otros) de las tuberías en los SAAs es obviamente necesario para una gestión eficiente y dinámica de tales sistemas. A esta problemática se suma la detección y el control de las fugas de agua. El acceso a información fiable sobre las fugas es una tarea compleja. En muchos casos, las fugas son detectadas cuando los daños en la red son ya considerables, lo que trae consigo altos costes sociales y económicos. En este sentido, los métodos no destructivos (por ejemplo, ground penetrating radar - GPR), pueden ser una respuesta a estas problemáticas, ya que permiten, como se pone de manifiesto en esta tesis, localizar los trazados de las tuberías, identificar características de los componentes y detectar las fugas de agua cuando aún no son significativas. La selección del GPR, en este trabajo se justifica por sus características como técnica no destructiva, que permite estudiar tanto objetos metálicos como no metálicos. Aunque la captura de información con GPR suele ser exitosa, la configuración de la captura, el gran volumen de información, y el uso y la interpretación de la información requieren de alto nivel de habilidad y experiencia por parte del personal. Esta tesis doctoral se plantea como un avance hacia el desarrollo de herramientas que permitan responder a la problemática del desconocimiento de los activos enterrados de los SAAs. El objetivo principal de este trabajo doctoral es, pues, generar herramientas y evaluar la viabilidad de su aplicación en la caracterización de componentes de un SAA, a partir de imágenes GPR. En este trabajo hemos realizado ensayos de laboratorio específicamente diseñados para plantear, elaborar y evaluar metodologías para la caracterización de los componentes enterrados de los SAAs. Adicionalmente, hemos realizado ensayos de campo, que han permitido determinar la viabilidad de aplicación de tales metodologías bajo condiciones no controladas. Las metodologías elaboradas están basadas en técnicas de análisis inteligentes de datos. El principio básico de este trabajo ha consistido en el tratamiento adecuado de los datos obtenidos mediante el GPR, a fin de buscar información de utilidad para los SAAs respecto a sus componentes, con especial énfasis en las tuberías. Tras la realización de múltiples actividades, se puede concluir que es viable obtener más información de las imágenes de GPR que la que actualmente se obtiene con la típica identificación de hipérbolas. Esta información, además, puede ser observada directamente, de manera más sencilla, mediante las metodologías planteadas en este trabajo doctoral. Con estas metodologías se ha probado que también es viable la identificación de patrones (especialmente el pre-procesado con el algoritmo Agent race) que proporcionan aproximación bastante acertada de la localización de las fugas de agua en los SAAs. También, en el caso de las tuberías, se puede obtener otro tipo de características tales como el diámetro y el material. Como resultado de esta tesis se han desarrollado una serie de herramientas que permiten visualizar, identificar y localizar componentes de los SAAs a partir de imágenes de GPR. El resultado más interesante es que los resultados obtenidos son sintetizados y reducidos de manera que preservan las características de los diferentes componentes registrados en las imágenes de GPR. El objetivo último es que las herramientas desarrolladas faciliten la toma de decisiones en la gestión técnica de los SAAs y que tales herramientas puedan ser operadas incluso por personal con una experiencia limitada en el manejo / [CA] Amb el temps, a causa de les múltiples activitats d'operació i manteniment, les xarxes de sistemes d'abastament d'aigua (SAAs) se sotmeten a intervencions, modificacions o fins i tot estan tancades. En molts casos, aquestes activitats no estan degudament registrats. El coneixement dels camins i característiques (estat i edat, etc.) de les canonades d'aigua i sanejament fa evident la necessitat d'una gestió eficient i dinàmica d'aquests sistemes. Aquest problema es veu augmentat en gran mesura tenint en compte la detecció i control de fuites. L'accés a informació fiable sobre les fuites és una tasca complexa. En molts casos, les fugues es detecten quan el dany ja és considerable, el que porta costos socials i econòmics. En aquest sentit, els mètodes no destructius (per exemple, ground penetrating radar - GPR) poden ser una resposta constructiva a aquests problemes, ja que permeten, com s'evidencia en aquesta tesi, per determinar rutes de canonades, identificar les característiques dels components, i detectar les fuites d'aigua quan encara no són significatives. La selecció del GPR en aquest treball es justifica per les seves característiques com a tècnica no destructiva que permet estudiar tant objectes metàl·lics i no metàl·lics. Tot i que la captura d'informació amb GPR sol ser reeixida, aspectes com ara la configuració de captura, el gran volum d'informació que es genera, i l'ús i la interpretació d'aquesta informació requereix alt nivell d'habilitat i experiència. Aquesta tesi pot ser vista com un pas endavant cap al desenvolupament d'eines capaces d'abordar el problema de la manca de coneixement sobre els actius d'aigua i sanejament enterrat. L'objectiu principal d'aquest treball doctoral és, doncs, generar eines i avaluar la seva factibilitat d'aplicació a la caracterització dels components de los SAAs, a partir d'imatges GPR. En aquest treball s'han dut a terme proves de laboratori específicament dissenyats per proposar, desenvolupar i avaluar mètodes per a la caracterització dels components d'aigua i sanejament soterrat. A més, hem dut a terme proves de camp, que ens han permès determinar la viabilitat de la implementació d'aquestes metodologies en condicions no controlades. Les metodologies desenvolupades es basen en tècniques d'anàlisi intel·ligent de dades. El principi bàsic d'aquest treball ha consistit en el tractament de dades obtingudes a través del GPR per buscar informació útil sobre els components d'SAA, amb especial èmfasi en la canonades. Després de realitzar nombroses activitats, es pot concloure que, amb l'ús d'imatges de GPR, és factible obtenir més informació que la identificació típica d'hipèrboles realitzat actualment. A més, aquesta informació pot ser observada directament, per exemple, més simplement, utilitzant les metodologies proposades en aquest treball doctoral. Aquestes metodologies també demostren que és factible per identificar patrons (especialment el pre-processat amb l'algoritme Agent race) que proporcionen bastant bona aproximació de la localització de fuites en SAAs. També, en el cas de tubs, es pot obtenir altres característiques com ara el diàmetre i el material. Els principals resultats d'aquesta tesi consisteixen en una sèrie d'eines que hem desenvolupat per localitzar, identificar i visualitzar els components dels SAAS a partir d'imatges GPR. El resultat més interessant és que els resultats obtinguts són sintetitzats i reduïts de manera que preserven les característiques dels diferents components registrats en les imatges de GPR. L'objectiu final és que les eines desenvolupades faciliten la presa de decisions en la gestió tècnica de SAA, i que tals eines poden fins i tot ser operades per personal amb poca experiència en el maneig de metodologies no destructives, específicament GPR. / Ayala Cabrera, D. (2015). Characterization of components of water supply systems from GPR images and tools of intelligent data analysis [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59235 / Premios Extraordinarios de tesis doctorales

The “green agenda” combined with highway congestion has accelerated the demand for increased freight and passenger travel on the world’s railways. These increases have driven demand for more efficient and rapid investigation of trackbed ballast. Network Rail and other rail infrastructure operators spend significant financial sums on inspecting, tamping, adjusting, cleaning, and replacing trackbed ballast. Such maintenance is often to the detriment of normal network operation. Industry requires a method of ballast evaluation that is non-intrusive, cheap, can appraise long stretches of track in a short period of time, and give a fingerprinting result from which time-to-maintenance can be calculated and planned. Thus, the aim was to develop evaluation methods using non-destructive testing techniques. A 10-year old full-scale trackbed composed of variously fouled ballast was re-visited and used for experimentation. The condition of the ballast was calculated using the Ionescu Fouling Index. Earlier research at the University of Edinburgh enabled researchers worldwide to characterise ballast using ground penetrating radar (GPR). This research was repeated, validated and taken forward in a series of GPR experiments on the trackbed using a range of antennas from 500MHz to 2.6GHz. New "scatter" metrics were developed to determine ballast condition from the GPR waveforms. These metrics were then used to predict the Ionescu Fouling Index with a correlation coefficient greater than 0.9. One of the current approaches to evaluating the stiffness of railway ballast is to use a Falling Weight Deflectometer (FWD). The viability of using a Prima 100 mini-FWD on railways to measure stiffness was determined and deemed to be ineffective on ballast. The applicability of the impulse response technique on railways was determined. An instrumented hammer was used to excite the ballast, with a geophone measuring the response. The Frequency Response Function of this was successfully correlated with the Ionescu Fouling Index with a correlation coefficient also greater than 0.9. Finally, using GPR data and measured stiffness data collected by Banverket, Sweden, a numerical model to successfully relate radar responses to stiffness was developed.

The Charity Hospital Cemetery in New Orleans, Louisiana, was used as a potter's field for over 150 years. When Charity Hospital considered selling a portion of the property ground penetrating radar (GPR) and thermal infrared (TIR) data were collected in the cemetery to locate unmarked graves. The TIR data could not be used because the expert died before compiling the TIR data. Therefore, the GPR data was the sole source of subsurface information. GPR anomalies were used to excavate 3 areas where bones and hospital supplies were subsequently found, unfortunately very limited analyses were possible on the analog GPR data. The study presented here involved digitizing data and conducting a more thorough analysis of map patterns to determine whether GPR data could be used reliably to locate burials in the cemetery. The study's result indicates that GPR is a reliable source for burial detection and other anomalies in the subsurface.