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Abstract



Parsing and Validation of Modelica Models Utilising Fault Diagnosis


Models have become an indispensable tool within most industrial sectors and are used to reduce costs, enhance the performance of a system etc. The computer support within modelling is extensive, whereof the programming language Modelica is eminent, especially for multi-domain models. Dymola, a commercial program, is built on Modelica and is foremost used for simulation purposes, but many applications for which models are useful are not supported by Dymola. Instead other tools, e.g., Matlab, could be used to exploit the full potential of a model, which means that it first would be needed to be translated. This master’s thesis examines one of the possible ways to accomplish this. Specifically the possibility to translate Modelica-models via an xml file, generated by Dymola, is examined. The structure and content of this file is explored, and based thereupon a software is implemented in Python, which successfully translates the models constituting the base for this thesis. Specifically the method was developed on a model of a sub-system of Saab 39 Gripen air-plane. Besides porting models between different languages, it is of great interest to determine how well a model describes the system on which it is based. Hence a new method for model validation is developed using the Matlab Fault Diagnosis Toolbox, which also determines the Matlab syntax of the Modelica trans- lation. The novelty with the developed method, compared to traditional model validation methods, is that it is equation based. It is meant to point out specifically which equations are poorly fitted to validation data. On a simple example model the method was successfully used to isolate a poorly fitted equation. This is accomplished by introducing faults to the equations and generating residuals, based on sets of over-determined equations. As a measure of the modelling error the estimation error of the simulated residuals is used, which are weighted together depending on the fault properties of the residuals.

Karin Lockowandt

2017

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