Turnouts are an important part of railway infrastructure for two reasons: infrastructure andmaintenance. For the infrastructure they provide the flexibility to allow the formulation and branchingof railway network and for maintenance they consume a large part of maintenance budget and have aprominent place in maintenance planning policy and activities. This is because as a “mechanical object”,a turnout often experiences malfunctions. The problem becomes even more complicated, since a turnoutis composed of many different parts and each of them fails for very different reasons (e.g. switch bladesvs crossing part). This is reflected in the different needs for maintenance activities, as railways areforced to pour in excessive amounts of resources to carry out emergency repairs, or to carry outunnecessary scheduled maintenance works in turnouts, which do not need to be inspected or repaired.Therefore, it is difficult to plan and organize maintenance activities in turnouts in an efficient manner.This raises the question of whether malfunctions in turnouts can be predicted and used as informationfor the maintenance planning process in order to optimize it and develop it into a more reliablepreventive maintenance planning.The aim of this analysis is to attempt to model the probability of various malfunctions in turnouts asa function of their main geometric and operational characteristics by using logistic regression modelsand then input these results into the maintenance planning process in order to optimize it. First, it wasimportant to objectify the railway track system and the turnout components, both in terms of parts andinterrelationships. Furthermore, the process and basic elements of railway maintenance planning weredefined, as well as arguments that motivate a turn towards preventive maintenance planningmethodologies. This was done through a comprehensive literature study.The basis of this research was case studies, which described the relationship between geometricaland operational characteristics of turnouts and their wear, as well as risk-based modelling methods inrailway maintenance planning. To create the analysis model, data from turnouts in eastern regionprovided by the Swedish Transport Administration were used, both from the point of view of describingthe underlying causes of turnout malfunctions and to formulate an object-oriented database suitable forusing in logistic regression models. The goal was a logit model that calculated the malfunctionprobability of a turnout, which could be used directly into a maintenance planning framework, whichranked maintenance activities in turnouts.The results obtained showed that although the model suffers from low correlation, differentrelationships between input variables and different functional errors were established. Furthermore, thepotential of these analytical models and modeling structures was shown to be able to developpreventive, predictive railway maintenance plans, but further analysis of the data structure is required,especially regarding data quality. Finally, further possible research areas are presented. / Spårväxlar är viktiga delar av järnvägens infrastruktur av två orsaker: infrastruktur och underhåll.För infrastrukturen ger de möjlighet till flexibla tillåter de formulering och grenning av järnvägsnät ochför underhållet konsumerar de en stor del av underhållsbudgeten och de har en framträdande plats iunderhållsplaneringspolitiken och aktiviteterna. Detta beror på att som ett ”maskinellt objekt”, harspårväxeln ofta fel. Problemet blir ännu mer komplicerat, eftersom en spårväxel består av många olikadelar och var och en av dem bryts ner av mycket olika skäl (t.ex. tunganordning vs korsningsdel). Dettaåterspeglas i olika behov av underhållsaktiviteter. Eftersom järnvägarna tvingas hålla alltför storamängder resurser för att utföra akuta reparationer eller för att utföra onödiga schemalagdaunderhållsarbeten i spårväxlar, som inte behöver inspekteras eller repareras. Därför är det svårt attplanera och organisera underhållsaktiviteter för spårväxlarna på ett effektivt sätt. Detta ställer fråganom funktionsfel i spårväxlar kan förutsägas och användas som information till  underhållsplaneringsprocessen för att optimera den och utveckla den till en pålitligare förebyggandeunderhållsplanering.Syftet med denna analys är att försöka modellera sannolikheten för olika funktionsfel i spårväxlarsom en funktion av deras huvudsakliga geometriska och operativa egenskaper med användning avlogistiska regressionsmodeller och sedan mata dessa resultat in i underhållsplaneringsprocessen för attoptimera den. För det första var det viktigt att objektifiera järnvägsspårsystemet ochspårväxlarkomponenterna, både vad gäller delar och inbördes förhållanden. Dessutom definieradesprocessen och grundelementen i järnvägsunderhållsplaneringen, samt att argument som motiverarförändring till förebyggande underhållsplaneringsmetoder. Detta gjordes genom en omfattandelitteraturstudie.Grunden i denna analys var fallstudier, som beskrev förhållandet mellan geometriska ochoperationella egenskaper hos spårväxlar och deras förslitning samt riskbaserade modelleringsmetoder ijärnvägsunderhållsplanering. För att skapa analysmodellen användes data från spårväxlar i östraregionen som tillhandahölls av Trafikverket, både ur synpunkten att beskriva de underliggandeorsakerna till spårväxlarsfel och för att formulera en objektorienterad databas lämplig för användning ilogistiska regressionsmodeller. Målet var en logitmodell som beräknade sannolikheten för fel i enspårväxel, som kunde användas direkt i en underhållsplaneringsram, som rangordnar lämpigaunderhållsaktiviteter i spårväxlar.Erhållna resultat visade att även om modellen lider av låg korrelation, konstaterades olika sambandmellan ingående variabler och olika funktionsfel. Vidare visades potentialen hos dessa analysmodelleroch modelleringsstrukturer för att kunna utveckla förebyggande, förutsägbarajärnvägsunderhållsplaner, men det krävs troligtvis ytterligare analys av datastrukturen, specielltangående datakvaliteten. Slutligen presenteras ytterligare möjliga forskningsområden.

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Cette thèse s’inscrit dans le domaine de l'intelligence ambiante (Ambient Intelligence - AmI). Les systèmes AmI sont des systèmes interactifs composés de plusieurs éléments hétérogènes. Principalement : les capteurs et les effecteurs.D'un point de vue fonctionnel, l'objectif des systèmes AmI est d'activer certains effecteurs, sur la base des mesures des capteurs. Toutefois, les capteurs et les effecteurs peuvent subir des défaillances. Notre motivation dans cette thèse est de munir les systèmes AmI de capacités d'auto-détection des pannes.Les ressources physiques ne sont pas nécessairement connues au moment de la conception, mais elles sont plutôt découvertes dynamiquement lors de l'exécution. Il est donc impossible d’appliquer les techniques classiques pour prédéterminer des boucles de régulation ad-hoc.Nous proposons une nouvelle approche où la stratégie de détection de défaillances est déterminée dynamiquement lors de l'exécution. Pour cela, les couplages entre capteurs et effecteurs sont déduits automatiquement lors de l’exécution. Ceci est rendu possible par la modélisation des caractéristiques des capteurs, des effecteurs, ainsi que des phénomènes physiques (que nous appelons effets) qui sont attendus dans l'environnement ambiant suite à une action d’un effecteur. Ces effets sont utilisés en run-time pour lier les effecteurs (produisant les effets) avec les capteurs correspondants (détectant ces effets). Nous introduisons une plateforme de détection des pannes qui génère à l’exécution un modèle de prédiction des valeurs attendues sur les capteurs. Ce modèle, de nature hétérogène (il mêle flots de données et automates finis) est exécuté par un outil adapté (ModHel’X) de façon à fournir les valeurs attendues à chaque instant. Notre plateforme compare alors ces valeurs avec les valeurs réellement mesurées de façon à détecter les défaillances. / This thesis takes place in the field of Ambient Intelligence (AmI). AmI Systems are interactive systems composed of many heterogeneous components. From a hardware perspective these components can be divided into two main classes: sensors, using which the system observes its surroundings, and actuators, through which the system acts upon its surroundings in order to execute specific tasks.From a functional point of view, the goal of AmI Systems is to activate some actuators, based on data provided by some sensors. However, sensors and actuators may suffer failures. Our motivation in this thesis is to equip ambient systems with self fault detection capabilities. One of the particularities of AmI systems is that instances of physical resources (mainly sensors and actuators) are not necessarily known at design time; instead they are dynamically discovered at run-time. In consequence, one could not apply classical control theory to pre-determine closed control loops using the available sensors. We propose an approach in which the fault detection and diagnosis in AmI systems is dynamically done at run-time, while decoupling actuators and sensors at design time. We introduce a Fault Detection and Diagnosis framework modeling the generic characteristics of actuators and sensors, and the physical effects that are expected on the physical environment when a given action is performed by the system's actuators. These effects are then used at run-time to link actuators (that produce them) with the corresponding sensors (that detect them). Most importantly the mathematical model describing each effect allows the calculation of the expected readings of sensors. Comparing the predicted values with the actual values provided by sensors allows us to achieve fault-detection.

This dissertation named Family and child with hyperactivity syndrome and attention deficit (hereinafter child with ADHD - Attention Deficit Hyperactivity Disorders) is concerning with problems of families which are bringing up, caring and a looking after a child with ADHD. The aim of the dissertation is mapping of life of a family with child suffering from ADHD. Furthermore to describe how such a family perceives behavior of other people from the surrounding towards such a family. Also how a child with ADHD syndrome intervene in a life of its siblings and social functioning of its own family. Within the dissertation there is determined one important question "What is like a life of a family with a child suffering from ADHD syndrome". Theoretical part of the dissertation describes ADHD syndrome. How is it possible to influence ADHD and what are latest medical treatments of children and adults. Within the theoretical part attention is also given to the educational possibilities for children with ADHD, family relationships and potentially socially dangerous effects of children and adults influenced by ADHD syndrome. For the empiric part of the dissertation was chosen method of qualitative research via technique of semi-structured interview containing 26 questions led with 7 mothers of children suffering from ADHD syndrome. Questions are directed at social functioning of each family and their family life. The findings are showing that family life where there is a child with ADHD is directly and strongly influenced. Children with ADHD syndrome need more care than other children in the family and this causes unease and uneven relations between siblings. Children with syndrome do not achieve results matching their intelligence, they lag behind their potential. It was proved that older children show socially dangerous effects such as tobacco or drug addiction. Also the whole family is often seen in by the public in a negative light. This dissertation can be beneficial to parents of children with ADHD syndrome who can compare their feelings with feelings and experience of other parents who have a child affected with such disorder.

The objective of this thesis is to develop vibration-based fault detection strategies for on-line condition monitoring of gear transmission systems. The study divides the thesis into three sections. First of all, the local stresses created by a root fatigue crack on a pinion spur gear are analyzed using a quasi-static finite element model and non-linear contact mechanics simulation. Backlash between gear teeth which is essential to provide better lubrication on tooth surfaces and to eliminate interference is included as a defect and a necessary part of transmission design. The second section is dedicated to fixed axis power trains. Torsional vibration is shown to cause teeth separation and double-sided impacts in unloaded and lightly loaded gearing drives. The transient and steady-state dynamic loading on teeth within a two stage crank-slider mechanism arising from backlash and geometric manufacturing errors is investigated by utilizing a non-linear multi-body dynamics software model. The multi-body model drastically reduces the computation time required by finite element methods to simulate realistic operation. The gears are considered rigid with elastic contact surfaces defined by a penalty based non-linear contact formulation. The third section examines a practical differential planetary transmission which combines two inputs and one output. Planetary gears with only backlash errors are compared to those containing both backlash and tooth defects under different kinematic and loading conditions. Fast Fourier Transform (FFT) analysis shows the appearance of side band modulations and harmonics of the gear mesh frequency. A joint time-frequency analysis (JTFA) during start-up reveals the unique vibration patterns for fixed axis gear train and differential planetary gear, respectively, when the contact forces increase during acceleration.