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<p>Technical systems of today are often complex and integrated. To maintain operational functionality and security it is sometimes necessary to have a surveillance system which can detect a fault in an early stage. The device that detects and locates the faulty component is called a diagnosis system. There are several different approaches to fault diagnosis, this study focus on a part of technical diagnosis that uses a model of the system for assistance to make the diagnosis. In the creation of the model of the system computer tools can be used, in this thesis it is investigated if one such software tool is practical to use in the building of the model of the system.</p><p>One aspect of technical diagnosis based on models is the creation of a model of the process in question with support for faults, a fault model. In this thesis, Modelica is used to create fault models. The models produced from Modelica are then analyzed by some existing diagnosis algorithms.</p><p>The approach of designing fault models in Modelica and then exporting the corresponding system and perform diagnosis analysis on it in Matlab is considered feasible. But the process falls a bit short of the aim of a automatic model building and and diagnosis analysis procedure.</p><p>If the results from this thesis are to be used in the future will depend on if the freedom that Modelica gives in designing fault models are deemed worthwhile to accommodate so that the results from the modeling suits the diagnosis analysis. One way to do ease this transformation of data is to restrict the freedom of model designs in Modelica but then some of the benefit that Modelica brings is negated. It is shown here however that it it possible to design fault models in Modelica and then use the results to analyze the models regarding sensor placement and test design.</p>

Technical systems of today are often complex and integrated. To maintain operational functionality and security it is sometimes necessary to have a surveillance system which can detect a fault in an early stage. The device that detects and locates the faulty component is called a diagnosis system. There are several different approaches to fault diagnosis, this study focus on a part of technical diagnosis that uses a model of the system for assistance to make the diagnosis. In the creation of the model of the system computer tools can be used, in this thesis it is investigated if one such software tool is practical to use in the building of the model of the system. One aspect of technical diagnosis based on models is the creation of a model of the process in question with support for faults, a fault model. In this thesis, Modelica is used to create fault models. The models produced from Modelica are then analyzed by some existing diagnosis algorithms. The approach of designing fault models in Modelica and then exporting the corresponding system and perform diagnosis analysis on it in Matlab is considered feasible. But the process falls a bit short of the aim of a automatic model building and and diagnosis analysis procedure. If the results from this thesis are to be used in the future will depend on if the freedom that Modelica gives in designing fault models are deemed worthwhile to accommodate so that the results from the modeling suits the diagnosis analysis. One way to do ease this transformation of data is to restrict the freedom of model designs in Modelica but then some of the benefit that Modelica brings is negated. It is shown here however that it it possible to design fault models in Modelica and then use the results to analyze the models regarding sensor placement and test design.

Práce se zabývá metodami pro testování lineárních analogových obvodů v kmitočtové oblasti. Cílem je navrhnout efektivní metody pro automatické generování testovacího plánu. Snížením počtu měření a výpočetní náročnosti lze výrazně snížit náklady za testování. Práce se zabývá multifrekveční parametrickou poruchovou analýzou, která byla plně implementována do programu Matlab. Vhodnou volbou testovacích kmitočtů lze potlačit chyby měření a chyby způsobené výrobními tolerancemi obvodových prvků. Navržené metody pro optimální volbu kmitočtů byly statisticky ověřeny metodou MonteCarlo. Pro zvýšení přesnosti a snížení výpočetní náročnosti poruchové analýzy byly vyvinuty postupy založené na metodě nejmenších čtverců a přibližné symbolické analýze.