This thesis presents an inspection method based on RGB-D profiling for the rail industry. The proposed approach uses inexpensive RGB-D cameras to generate color and geometrical information of the observations, and stitches each consecutive scan from the sensor to form a map, provided that the two scans contain the information from the same observation. Using a technique known as pairwise registration, the errors between these consecutive scans are minimized using error minimization algorithms such as Iterative Closest Point and Normal Distributions Transform. Once the error between each consecutive scan is minimized, the scans are then converted into a global co-ordinate frame work to form a global map of all the added scans. The proposed approach could be used as a map-based identification technique by comparing the past global map to newly acquired scans while also reducing computation time effectively. The effectiveness of this approach is demonstrated by developing a system that uses multiple RGB-D cameras to detect railway defects such as spikes. The applicability of the proposed approach to other applications is then evaluated by profiling long lengths of road. / Master of Science

[pt] Diversos sistemas e aplicações são capazes de identificar um determinado contexto de uso em tempo real, detectando informações para antecipar situações e otimizar sua interface. Esses sistemas que agem de forma contextual e, muitas das vezes, proativa pertencem à área da Computação ciente de contexto. O aplicativo Google para sistemas Android e IOS possui um serviço de assistente virtual para dispositivos móveis que utiliza dados da conta do usuário obtidos através dos serviços Google, além de dados do próprio dispositivo. O assistente é capaz de identificar hábitos, antever necessidades e oferecer cards de informações antes mesmo que sejam pedidos pelo usuário. Pertencendo ao campo da computação ciente de contexto, o aplicativo Google foi eleito como objeto de estudo e avaliado sob o viés da engenharia semiótica. Através da interface do aplicativo, analisou-se a qualidade da comunicação designer-usuário, tendo por objetivo verificar não apenas a eficiência da assistência virtual oferecida pelo sistema, mas também a autonomia do usuário e a flexibilidade do aplicativo diante de suas necessidades. / [en] Many modern systems and applications are capable of analising the contexts of use in real time, identifying key information to anticipate upcoming actions and optimize their interfaces. Those systems that work in a contextual manner and, usually, in a proactive way, belong to the Context Aware Computing area. The Google App for Android and iOS devices has a virtual assistant service that collects data obtained from different sources associated to the user account and links them to data from the user device. The assistant can identify habits, anticipate probable needs and offer information cards even before the user asks for them. Being part of the Context Aware Computing field, the Google App was elected as study object and was evaluated under the Semiotics Engineering bias. From the application s interface, the quality of the user-designer communication was analysed so, not only the virtual assistant efficiency could be evaluated, but also the user autonomy and the application flexibility according to his needs.

Made available in DSpace on 2015-04-11T14:02:42Z (GMT). No. of bitstreams: 1 edna.pdf: 3673971 bytes, checksum: 89ecadfcc33fc87adf6e023ed082081a (MD5) Previous issue date: 2010-12-29 / In order to evaluate communicability in virtual environments developed using Moodle, also considering how novice students react when developing basic tasks through that software, this work describes how MIS and MAC two methods from Semiotic Engineering were used to evaluate designer-user interaction (under student profile) in this class of environment. From experiments with Moodle IFAM and ColabWeb, both environments currently used with distance learning courses offered by two Brazilian Federal Higher Education institutions, we describe how application of a successive refinement schema for the interface, based on the setting of elements available. / Com o objetivo de avaliar a comunicabilidade de ambientes virtuais desenvolvidos a partir da plataforma Moodle, verificando como alunos novatos reagem ao realizarem determinadas tarefas utilizando o sistema, este trabalho descreve como os métodos MIS e MAC da Engenharia Semiótica foram aplicados para a avaliação da interação designer-usuário (perfil aluno) em ambientes dessa categoria. A partir de experimentos com os ambientes Moodle IFAM e ColabWeb, ambos utilizados nas disciplinas a distância oferecidas atualmente por duas IFES, descrevemos a aplicação de um esquema de refinamentos sucessivos da interface a partir da modificação dos elementos de configuração disponíveis.

Undichte Abwassersysteme sind in unserer urbanisierten Welt allgegenwärtig, und aufgrund ihrer versteckten Infrastruktur und der schwierigen Überwachung bleiben ihre Leckagen oft in der Anfangsphase unbemerkt. Trotz der umfangreichen technologischen Entwicklung bei den Kanalinspektionsmethoden und den dazugehörigen Techniken ist die Überwachung von Abwasserkanälen auf städtischer Ebene nach wie vor kostspielig und schwierig. Daher werden ein Empfehlungsverfahren und eine Methodenklassifizierung benötigt, um einen nachhaltigen und kosteneffizienten Kanalinspektionsplan auf Stadtebene zu erstellen. In diesem Zusammenhang kann diese Studie im Wesentlichen in drei Teile gegliedert werden. Zunächst wurde eine umfassende Literaturstudie zu den verfügbaren Kanalinspektionsmethoden durchgeführt, um ein umfassenderes Verständnis für deren Wirkungsbereich und technischen Grad zu erhalten. Darüber hinaus wurden diese Inspektionsmethoden auf der Grundlage ihres Wirkungsbereichs in drei Stufen eingeteilt, wobei Stufe 1 die Methoden mit dem größten Wirkungsbereich umfasst, wie z. B. die Verschlechterungsmodellierung, die ein umfassendes und dennoch zuverlässiges Verständnis der Integrität des Abwassersystems ermöglicht. Stufe 2 bietet intermediäre Inspektionsmethoden wie Wärmebildaufnahmen aus der Luft und geoelektrische Inspektionstechniken, die eine zerstörungsfreie Inspektion, der von Stufe 1 vorgeschlagenen Bereiche ermöglichen. Bei den Methoden der Stufe 3 handelt es sich in erster Linie um Inspektionstechniken in der Rohrleitung, die häufig eine Rohrentwässerung erfordern und im Gegenzug für eine hohe Erkennungsgenauigkeit kostspielig zu implementieren sind. Zweitens wurde als Beitrag zu den Tier-1-Methoden das Vulnerability Hotspot Mapping entwickelt, ein GIS-gestütztes Modell, das die am häufigsten von den Entleerungsmodellen verwendeten Faktoren berücksichtigt und Bereiche des Abwassersystems anbietet, die besonders anfällig für Leckagen sind. Die Validierungs- und Sensitivitätsanalysen ergaben, dass die Fließgeschwindigkeit, das Rohralter und die Oberflächenvegetation die sinnvollsten Faktoren für das Modell sind. Darüber hinaus ergab das lineare Modell einen Wirkungsgrad von 76 % und einen mittleren quadratischen Fehler von 0,918, während es durch den Random-Forest-Algorithmus mit 400 Bäumen verbessert wurde, was auf das Potenzial der Schwachstellen-Kartierung als frühzeitige Methode zur Kanalinspektion auf Stadtebene hinweist. Drittens wurden die Tier-2-Methoden aktualisiert, indem das Potenzial der elektrischen Widerstandstomographie und der Mise-la-masse-Techniken als geoelektrische und zerstörungsfreie Methoden hervorgehoben wurde, die experimentell in einem Holzrahmen mit einer Matrix aus Sensoren und Elektroden getestet wurden. Der Versuchsbehälter besteht aus drei Schichten von Elektroden in gesättigten und ungesättigten Zonen, in denen verschiedene Leckageszenarien durchgeführt wurden, um die Sichtbarkeit von Leckagen mit diesen Methoden zu untersuchen. Trotz der Fähigkeit dieser Methoden zur Leckageerkennung wurde festgestellt, dass die elektrische Widerstandstomographie eine höhere Leckageerkennungsempfindlichkeit als die Mise à la masse hat, während sie eine geringere Flexibilität bietet, was ein wichtiger Punkt bei der Methodenauswahl ist. Darüber hinaus wurde festgestellt, dass Mise à-la-masse empfindlicher auf das Vorhandensein von Leckagen reagiert als auf Feuchtigkeits- und Temperaturschwankungen, was zu einem Pearson's r und R2 von 0,8 bzw. 0,7 im Vergleich zu den während der Leckageszenarien gesammelten Daten führte. Insgesamt schlägt diese Studie vor, dass mindestens zwei (vorzugsweise drei) Inspektionstechniken, die zu verschiedenen Ebenen gehören, eingesetzt werden sollten, um einen nachhaltigen Inspektionsplan auf Stadtebene zu haben. Der vorgeschlagene Ansatz hilft dabei, ein Gleichgewicht zwischen Kosten und Präzision sowie ein Gleichgewicht zwischen Zeit und Einwirkungsbereich herzustellen, was einen dezentralisierten und nachhaltigen Inspektionsplan ermöglicht.:List of Abbreviations .......................................................................................... IX List of Peer-Reviewed Publications on the Ph.D. Topic .................................. X List of Co-authored Peer-Reviewed Publications on the Ph.D. Topic ............ X 1 General Introduction........................................................................... 1 1.1 Background ....................................................................................................... 1 1.2 Aim and Objectives .......................................................................................... 3 1.3 Structure of the Document ............................................................................. 3 2 Towards a Decentralized Solution for Sewer Leakage Detection .............................................................................................. 8 2.1 Introduction ...................................................................................................... 10 2.2 Sewer inspection methods (SIMs) overview ................................................. 11 2.2.1 Tier-one (T-I) ................................................................................................................. 11 Deterioration models ....................................................................................................... 12 Hotspot mapping .............................................................................................................. 14 2.2.2 Tier-two (T-II) methods ............................................................................................... 15 Aerial thermal imaging (ATI) ............................................................................................ 15 Ground penetration radar (GPR) .................................................................................... 16 Electrical resistivity tomography (ERT) ........................................................................... 17 Mise-à-la-masse method (MLM)...................................................................................... 18 Soil Sampling ..................................................................................................................... 18 2.2.3 Tier-three (T-III) methods ........................................................................................... 20 General approaches ......................................................................................................... 20 Laser scanning ................................................................................................................... 21 Visual inspection ............................................................................................................... 21 Acoustic methods ............................................................................................................. 22 Ultrasonic inspection ........................................................................................................ 24 Multi-sensor robots .......................................................................................................... 24 Electromagnetic Inspection ............................................................................................. 26 Thermography Inspection ............................................................................................... 26 Tracer Test ......................................................................................................................... 27 VII 2.3 Discussion.......................................................................................................... 30 2.4 Conclusion and outlook ................................................................................... 33 2.5 References ......................................................................................................... 34 3 Vulnerability Hotspot Mapping (VHM) of Sewer Pipes based on Deterioration Factors .................................................................... 42 3.1 Introduction ...................................................................................................... 43 3.2 Materials and Methods.................................................................................... 44 3.2.1 Overview of the sewer deterioration factors. .......................................................... 45 Pipe Age .............................................................................................................................. 46 Pipe Material ...................................................................................................................... 47 Sewer Type ......................................................................................................................... 48 Flow Velocity ...................................................................................................................... 48 Node Degree...................................................................................................................... 49 Surface Vegetation ............................................................................................................ 50 Criticality class and weighting matrix ............................................................................. 50 3.3 Case study ......................................................................................................... 52 3.4 Results and discussions ................................................................................... 54 3.4.1 Network assessment .................................................................................................. 54 3.4.2 Validation and sensitivity analysis ............................................................................ 56 3.5 Summary and conclusion ................................................................................ 61 3.6 Reference........................................................................................................... 63 4 Laboratory Application of the Mise-à-la-Masse (MALM) for Sewer Leakage Detection as an intermediary inspection method. ................................................................................................ 67 4.1 Introduction ...................................................................................................... 68 4.2 Methodology ..................................................................................................... 70 4.2.1 Mise-à-la-Masse method (MALM) .............................................................................. 70 4.2.2 Experimental setup ..................................................................................................... 70 4.2.3 Measurement principles ............................................................................................ 72 4.2.4 Assessed Scenarios ..................................................................................................... 73 4.3 Results and discussions ................................................................................... 74 VIII Inhaltsverzeichnis 4.3.1 Contour Visualization ................................................................................................. 74 First Leakage scenario ...................................................................................................... 74 Other leakage scenarios .................................................................................................. 75 4.3.2 Trend Analyses ............................................................................................................ 77 Leakage proximity ............................................................................................................. 77 Vertical Assessment .......................................................................................................... 78 4.3.3 Data Validation and Sensitivity Analyses ................................................................. 79 Data Validation .................................................................................................................. 79 Sensitivity Analyses ........................................................................................................... 80 4.3.4 Application in practice ................................................................................................ 82 4.4 Summary and Conclusion ............................................................................... 83 4.5 References ......................................................................................................... 85 5 Conclusions and Outlooks .................................................................. 88 5.1 Discussion and Conclusions ............................................................................ 88 5.2 Outlooks ............................................................................................................ 89 6 Supplementary Information ............................................................... 92 / Leaky sewer systems are present in our urbanized world and due to their hidden infrastructure and monitoring challenges, their leakages tend to remain unnoticed often at initial stages. Despite an extensive technological development in sewer inspection methods and their implemented techniques, sewer monitoring at the city scale remains costly and challenging. Therefore, a recommendation procedure and method classification are needed to have a sustainable and cost-effective sewer inspection plan at the city scale. In this context, this study can be mainly divided into three parts. First, an extensive study literature was conducted on available sewer inspection methods to have a wider understanding on their area of impacts and technicality levels, Furthermore, these inspection methods were categorized into three tiers based on their area of impact where Tier-1 consists of largest area of impact methods such as deterioration modelling, which provide a vast yet reliable understanding of the sewer system integrity. Tier-2 offers intermediatory inspection methods such as aerial thermal imagery and geo-electrical inspection techniques, which can provide a non-destructive inspection on areas suggested from Tier-1 techniques. Following the area of impact, Tier-3 methods are mostly in-pipe inspection techniques, which often demand pipe dewatering and are costly to implement in returns of a high detection precision. Second, as a contribution to Tier-1 methods, Vulnerability Hotspot Mapping was developed, which is a GIS-based model according to the most frequently used factors by deterioration models and offers areas of the sewer system more prone to leakage. The validation and sensitivity analyses revealed that flow velocity, pipe age, and surface vegetation are the most sensible factors to the model respectively. Furthermore, the linear model resulted in 76% of efficiency and mean squared error of 0,918 while it was improved with random forest algorithm with 400 trees, which points out the vulnerability mapping potential as an early sewer inspection method at the city scale. Third, Tier-2 methods were updated by emphasizing on the potential of Electrical Resistivity Tomography and Mise à-la-masse techniques as geo-electrical and non-destructive methods, which were experimentally tested within a wooden frame with a matrix of sensors and electrodes implemented. The experimental tank consists of three layers of electrodes in saturated and unsaturated zones, when various leakage scenarios were conducted to investigate on leakage visibility by these methods. Despite the capability of these methods for leakage detection, it was assessed that Electrical Resistivity Tomography has higher leakage detection sensibility than Mise à-la-masse while offering less mobility, which is a considerable point in method selection process. Moreover, it was observed that Mise à-la-masse is more sensitive to leakage presence rather than humidity and temperature variations and resulted in 0.8 and 0.7 in Pearson’s r and R2 respectively in comparison to sampled data during the leakage scenarios. All over, this study suggests that at least two (preferably 3) inspection techniques belonging to different tiers should be implemented to have a sustainable inspection plan at the city scale. The proposed approach helps to have a balance between cost and precision as well as an equilibrium between time and area of impact, which provides a decentralized and sustainable inspection plan.:List of Abbreviations .......................................................................................... IX List of Peer-Reviewed Publications on the Ph.D. Topic .................................. X List of Co-authored Peer-Reviewed Publications on the Ph.D. Topic ............ X 1 General Introduction........................................................................... 1 1.1 Background ....................................................................................................... 1 1.2 Aim and Objectives .......................................................................................... 3 1.3 Structure of the Document ............................................................................. 3 2 Towards a Decentralized Solution for Sewer Leakage Detection .............................................................................................. 8 2.1 Introduction ...................................................................................................... 10 2.2 Sewer inspection methods (SIMs) overview ................................................. 11 2.2.1 Tier-one (T-I) ................................................................................................................. 11 Deterioration models ....................................................................................................... 12 Hotspot mapping .............................................................................................................. 14 2.2.2 Tier-two (T-II) methods ............................................................................................... 15 Aerial thermal imaging (ATI) ............................................................................................ 15 Ground penetration radar (GPR) .................................................................................... 16 Electrical resistivity tomography (ERT) ........................................................................... 17 Mise-à-la-masse method (MLM)...................................................................................... 18 Soil Sampling ..................................................................................................................... 18 2.2.3 Tier-three (T-III) methods ........................................................................................... 20 General approaches ......................................................................................................... 20 Laser scanning ................................................................................................................... 21 Visual inspection ............................................................................................................... 21 Acoustic methods ............................................................................................................. 22 Ultrasonic inspection ........................................................................................................ 24 Multi-sensor robots .......................................................................................................... 24 Electromagnetic Inspection ............................................................................................. 26 Thermography Inspection ............................................................................................... 26 Tracer Test ......................................................................................................................... 27 VII 2.3 Discussion.......................................................................................................... 30 2.4 Conclusion and outlook ................................................................................... 33 2.5 References ......................................................................................................... 34 3 Vulnerability Hotspot Mapping (VHM) of Sewer Pipes based on Deterioration Factors .................................................................... 42 3.1 Introduction ...................................................................................................... 43 3.2 Materials and Methods.................................................................................... 44 3.2.1 Overview of the sewer deterioration factors. .......................................................... 45 Pipe Age .............................................................................................................................. 46 Pipe Material ...................................................................................................................... 47 Sewer Type ......................................................................................................................... 48 Flow Velocity ...................................................................................................................... 48 Node Degree...................................................................................................................... 49 Surface Vegetation ............................................................................................................ 50 Criticality class and weighting matrix ............................................................................. 50 3.3 Case study ......................................................................................................... 52 3.4 Results and discussions ................................................................................... 54 3.4.1 Network assessment .................................................................................................. 54 3.4.2 Validation and sensitivity analysis ............................................................................ 56 3.5 Summary and conclusion ................................................................................ 61 3.6 Reference........................................................................................................... 63 4 Laboratory Application of the Mise-à-la-Masse (MALM) for Sewer Leakage Detection as an intermediary inspection method. ................................................................................................ 67 4.1 Introduction ...................................................................................................... 68 4.2 Methodology ..................................................................................................... 70 4.2.1 Mise-à-la-Masse method (MALM) .............................................................................. 70 4.2.2 Experimental setup ..................................................................................................... 70 4.2.3 Measurement principles ............................................................................................ 72 4.2.4 Assessed Scenarios ..................................................................................................... 73 4.3 Results and discussions ................................................................................... 74 VIII Inhaltsverzeichnis 4.3.1 Contour Visualization ................................................................................................. 74 First Leakage scenario ...................................................................................................... 74 Other leakage scenarios .................................................................................................. 75 4.3.2 Trend Analyses ............................................................................................................ 77 Leakage proximity ............................................................................................................. 77 Vertical Assessment .......................................................................................................... 78 4.3.3 Data Validation and Sensitivity Analyses ................................................................. 79 Data Validation .................................................................................................................. 79 Sensitivity Analyses ........................................................................................................... 80 4.3.4 Application in practice ................................................................................................ 82 4.4 Summary and Conclusion ............................................................................... 83 4.5 References ......................................................................................................... 85 5 Conclusions and Outlooks .................................................................. 88 5.1 Discussion and Conclusions ............................................................................ 88 5.2 Outlooks ............................................................................................................ 89 6 Supplementary Information ............................................................... 92

This thesis addresses the problem of registering one point set with respect to another. This problem arises in the context of the use of CMM/Scanners to inspect objects especially with freeform surfaces. The tolerance verification process now requires the comparison of measured points with the nominal geometry. This entails placement of the measured point set in the same reference frame as the nominal model. This problem is referred to as the registration or localization problem. In the most general form the tolerance verification task involves registering multiple point sets corresponding to multi-step scan of an object with respect to the nominal CAD model. This problem is addressed in three phases. This thesis presents a novel approach to automated inspection by matching point sets based on the Iterative Closest Point (ICP) algorithm. The Modified ICP (MICP) algorithm presented in the thesis improves upon the existing methods through the use of a localized region based triangulation technique to obtain correspondences for all the inspection points and achieves dramatic reduction in computational effort. The use of point sets to represent the nominal surface and shapes enables handling different systems and formats. Next, the thesis addresses the important problem of establishing registration between point sets in different reference frames when the initial relative pose between them is significantly large. A novel initial pose invariant methodology has been developed. Finally, the above approach is extended to registration of multiview inspection data sets based on acquisition of transformation information of each inspection view using the virtual gauging concept. This thesis describes implementation to address each of these problems in the area of automated registration and verification leading towards automatic inspection.