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<p>In order to maximize operating time of an industrial machine and minimize stand-by time, service time and operating costs, a diagnostic system can be a useful tool. Diagnostic systems employ information already available in a machine’s control system (such as control signals, system state, sensor readings and so forth) to perform intelligent fault detection and localisation, and predict future faults and service needs.</p><p>CC Systems develops advanced electronics and control systems for industrial machines and vehicles operating in rough environments. One of their products is a diagnostic platform called Diagnostic Runtime Engine (DRE), supplying the customer with a tool for building a diagnostic system. The platform offers supervision of the control system. Actions are performed when it detects a possible fault or indication of a potential future fault. An action could be for example the creation of an alarm.</p><p>The DRE, as designed today, only works together with a control system running in an environment called CoDeSys. In this master thesis a new architecture of the platform is presented, with the objective to make the platform compatible with an arbitrary control system. A prototype is implemented to prove the concept of the suggested architecture model. A number of different standard diagnostic blocks, used for building the diagnostic system, are also suggested with the objective to make it easier for the user to employ the DRE. A proposition of how development with the diagnostic platform can proceed beyond this thesis is also presented.</p> / <p>För att maximera drifttid hos en industriell maskin och minimera driftskostnader samt standby- och service-tid, kan ett diagnostiksystem användas. Ett sådant system använder sig av information som redan finns tillgänglig i maskinens styrsystem (så som styrsignaler, tillstånd, sensorvärden och så vidare) för att utföra feldetektering och fellokalisering samt analys av möjliga framtida feltillstånd och servicebehov.</p><p>CC Systems utvecklar avancerade elektronikkomponenter och styrsystem för industriella maskiner och fordon. En av deras produkter är en diagnostikplattform, Diagnostic Runtime Engine (DRE), som erbjuder ett verktyg för att bygga upp ett diagnostiksystem. Plattformen möjliggör övervakning av styrsystemet, och detektion av ett nuvarande feltillstånd eller möjligt framtida feltillstånd leder till att en handling utförs. En handling kan till exempel vara att ett alarm skapas.</p><p>Diagnostikplattformen, som den är gjord idag, fungerar bara tillsammans med ett styrsystem som är implementerat i utvecklingsmiljön CoDeSys. I detta examensarbete presenteras en ny arkitektur på plattformen som möjliggör användande tillsammans med ett godtyckligt styrsystem. En prototyp är implementerad för att visa att den föreslagna arkitekturmodellen fungerar i praktiken. Dessutom är ett antal standard-diagnostikblock, som används då ett diagnostiksystem byggs upp, föreslagna. Standardblocken har till syfte att underlätta användandet av diagnostikplattformen. Ett förslag för hur DRE kan byggas om och utvecklas i framtiden är också presenterat.</p>

This dissertation deals with the development of a model-based diagnostic system for air brake systems that are widely used in commercial vehicles, such as trucks, tractor-trailers, buses, etc. The performance of these brake systems is sensitive to maintenance and hence they require frequent inspections. Current inspection techniques require an inspector to go underneath a vehicle to check the brake system for possible faults, such as leaks, worn brake pads, out-of-adjustment of push rods, etc. Such inspections are time consuming, labor intensive and difficult to perform on vehicles with a low ground clearance. In this context, the development of an onboard/ handheld diagnostic tool for air brakes would be of significant value. Such a tool would automate the brake inspection process, thereby reducing the inspection time and improving the safety of operation of commercial vehicles. In this dissertation, diagnostic schemes are developed to automatically detect two important and prevalent faults that can occur in air brake systems – leaks and out-of-adjustment of push rods. These diagnostic schemes are developed based on a nonlinear model for the pneumatic subsystem of the air brake system that correlates the pressure transients in the brake chamber with the supply pressure to the treadle valve and the displacement of the treadle valve plunger. These diagnostic schemes have been corroborated with data obtained from the experimental facility at Texas A&M University and the results are presented. The response of the pneumatic subsystem of the air brake system is such that it can be classified as what is known as a “Sequential Hybrid System”. In this dissertation, the term “hybrid systems” is used to denote those systems whose mathematical representation involves a finite set of governing ordinary differential equations corresponding to a finite set of modes of operation. The problem of estimating the push rod stroke is posed as a parameter estimation problem and a transition detection problem involving the hybrid model of the pneumatic subsystem of the air brake system. Also, parameter estimation schemes for a class of sequential hybrid systems are developed. The efficacy of these schemes is illustrated with some examples.

In order to maximize operating time of an industrial machine and minimize stand-by time, service time and operating costs, a diagnostic system can be a useful tool. Diagnostic systems employ information already available in a machine’s control system (such as control signals, system state, sensor readings and so forth) to perform intelligent fault detection and localisation, and predict future faults and service needs. CC Systems develops advanced electronics and control systems for industrial machines and vehicles operating in rough environments. One of their products is a diagnostic platform called Diagnostic Runtime Engine (DRE), supplying the customer with a tool for building a diagnostic system. The platform offers supervision of the control system. Actions are performed when it detects a possible fault or indication of a potential future fault. An action could be for example the creation of an alarm. The DRE, as designed today, only works together with a control system running in an environment called CoDeSys. In this master thesis a new architecture of the platform is presented, with the objective to make the platform compatible with an arbitrary control system. A prototype is implemented to prove the concept of the suggested architecture model. A number of different standard diagnostic blocks, used for building the diagnostic system, are also suggested with the objective to make it easier for the user to employ the DRE. A proposition of how development with the diagnostic platform can proceed beyond this thesis is also presented. / För att maximera drifttid hos en industriell maskin och minimera driftskostnader samt standby- och service-tid, kan ett diagnostiksystem användas. Ett sådant system använder sig av information som redan finns tillgänglig i maskinens styrsystem (så som styrsignaler, tillstånd, sensorvärden och så vidare) för att utföra feldetektering och fellokalisering samt analys av möjliga framtida feltillstånd och servicebehov. CC Systems utvecklar avancerade elektronikkomponenter och styrsystem för industriella maskiner och fordon. En av deras produkter är en diagnostikplattform, Diagnostic Runtime Engine (DRE), som erbjuder ett verktyg för att bygga upp ett diagnostiksystem. Plattformen möjliggör övervakning av styrsystemet, och detektion av ett nuvarande feltillstånd eller möjligt framtida feltillstånd leder till att en handling utförs. En handling kan till exempel vara att ett alarm skapas. Diagnostikplattformen, som den är gjord idag, fungerar bara tillsammans med ett styrsystem som är implementerat i utvecklingsmiljön CoDeSys. I detta examensarbete presenteras en ny arkitektur på plattformen som möjliggör användande tillsammans med ett godtyckligt styrsystem. En prototyp är implementerad för att visa att den föreslagna arkitekturmodellen fungerar i praktiken. Dessutom är ett antal standard-diagnostikblock, som används då ett diagnostiksystem byggs upp, föreslagna. Standardblocken har till syfte att underlätta användandet av diagnostikplattformen. Ett förslag för hur DRE kan byggas om och utvecklas i framtiden är också presenterat.

This master thesis deals with data processing from an online diagnostic system. The theoretical part of the work is divided into three chapters, the first deals with technical diagnostics as such, there are basic terminology and concepts associated with technical diagnostics, such as diagnostic methods, tools, models and signals. The second part is focused on diagnostic systems and their division. This chapter also provides some examples of online diagnostic monitoring systems from three different companies. The last chapter of the theoretical part is devoted to the description of the possibilities of data collection from diagnostic systems, ie. description of communication buses and protocols. The practical part of this work focuses on creating an application for data collection and visualization.

This master’s thesis deals with online vibration diagnostics of the milling machine spindle. It is aimed at the implementation of the complex online vibration diagnostics system to chosen milling machine, the suggestion of the vibration measurement system and the suggestion of the evaluation of changes of the technical condition of this milling machine spindle. The description of the vibration diagnostics, the description of the milling machine spindle construction and function and the suggestions for the practical application of vibration diagnostics are also parts of this thesis.

The objective of this diploma thesis is design and realization of I2C bus analyzer. I2C bus protocol is briefly described, together with means of connecting devices to the bus. Next the basic requirements for I2C bus analyzer are defined. Then the design of hardware I2C-to-USB converter including block description is proposed. The chapter dedicated to converter firmware describes method of communication with PC, decoding of intercepted commands and principles of master, slave and passive mode of bus monitoring. The last part is focused on operation software and its structure. Described are individual interfaces, most notable classes and default plugin modules.

Cette thèse s'inscrit dans le contexte de diagnostic assisté par ordinateur pour la localisation subcellulaire des protéines dans les images microscopiques. L'objectif est la conception et le développement d'un système de classification automatique permettant d'identifier le compartiment cellulaire dans lequel une protéine d'intérêt exerce son activité biologique. Afin de surmonter les difficultés rencontrées pour discerner les compartiments cellulaires présents dans les images microscopiques, les systèmes décrits dans la littérature proposent d'extraire plusieurs descripteurs associés à une combinaison de classifieurs. Dans cette thèse, nous proposons un schéma de classification différent répondant mieux aux besoins de généricité et de flexibilité pour traiter différentes bases d'images.Dans le but de fournir une caractérisation riche des images microscopiques, nous proposons un nouveau système de représentation permettant d'englober de multiples descripteurs visuels identifiés dans les différentes approches d'extraction de caractéristiques : locale, fréquentielle, globale et par région. Nous formulons ensuite le problème de fusion et de sélection des caractéristiques sous forme d'un problème de sélection de noyaux. Basé sur l'apprentissage de noyaux multiples (MKL), les tâches de sélection et de fusion de caractéristiques sont considérées simultanément. Les expériences effectuées montrent que la plateforme de classification proposée est à la fois plus simple, plus générique et souvent plus performante que les autres approches de la littérature. Dans le but d'approfondir notre étude sur l'apprentissage de noyaux multiples, nous définissons un nouveau formalisme d'apprentissage MKL réalisé en deux étapes. Cette contribution consiste à proposer trois termes régularisant liés à la résolution du problème d'apprentissage des poids associés à une combinaison linéaire de noyaux, problème reformulé en un problème de classification à vaste marge dans l'espace des couples. Le premier terme régularisant proposé assure une sélection parcimonieuse des noyaux. Les deux autres termes ont été conçus afin de tenir compte de la similarité entre les noyaux via une métrique basée sur la corrélation. Les différentes expérimentations réalisées montrent que le formalisme proposé permet d'obtenir des résultats de même ordre que les méthodes de référence, mais offrant l'avantage d'utiliser moins de fonctions noyaux. / This thesis arises in the context of computer aided analysis for subcellular protein localization in microscopic images. The aim is the establishment of an automatic classification system allowing to identify the cellular compartment in which a protein of interest exerts its biological activity. In order to overcome the difficulties in attempting to discern the cellular compartments in microscopic images, the existing state-of-art systems use several descriptors to train an ensemble of classifiers. In this thesis, we propose a different classification scheme wich better cope with the requirement of genericity and flexibility to treat various image datasets. Aiming to provide an efficient image characterization of microscopic images, a new feature system combining local, frequency-domain, global, and region-based features is proposed. Then, we formulate the problem of heterogeneous feature fusion as a kernel selection problem. Using multiple kernel learning, the problems of optimal feature sets selection and classifier training are simultaneously resolved. The proposed combination scheme leads to a simple and a generic framework capable of providing a high performance for microscopy image classification. Extensive experiments were carried out using widely-used and best known datasets. When compared with the state-of-the-art systems, our framework is more generic and outperforms other classification systems. To further expand our study on multiple kernel learning, we introduce a new formalism for learning with multiple kernels performed in two steps. This contribution consists in proposing three regularized terms with in the minimization of kernels weights problem, formulated as a classification problem using Separators with Vast Margin on the space of pairs of data. The first term ensures that kernels selection leads to a sparse representation. While the second and the third terms introduce the concept of kernels similarity by using a correlation measure. Experiments on various biomedical image datasets show a promising performance of our method compared to states of art methods.

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The goal of the thesis "Evaluation of the travel agency Expecta, s.r.o." is to determine the investment value of the company for the purpose of the future sale. Firstly the strategic analysis is applied, on which basis the future turnovers are estimated. Afterwards the company is analyzed from the financial point of view. The classical methods (ex. Horizontal and vertical analyses of the financial statements) and also analysis of EVA along with the diagnostic system of financial indicators "INFA" are used. The information arising from both analysisses serve as a basis for the construction of a planned profit and loss statement and a planned balance sheet. In the last part of this thesis the investment value of the firm is calculated by using a yield method based on the indicator EVA.