I en globaliserad värld där produktägare finner sina produkter på alltmer avslägsna platser, ökar behovet av att på ett så ekonomiskt och tidseffektivt sätt som möjligt, utföra reperationer och underhållningsarbeten. Att erbjuda en stark och mer effektiv eftermarknadssupport kan öka företagens konkurrenskraft och framför allt göra dem kostnadseffektiva med avseende på lägre bemanningsstyrka. Ett sätt att underlätta underhållningsarbetet är genom att använda modellbaserad diagnos för att generera underlag vid exempelvis reperationsarbeten. Denna rapport undersöker möjligheterna att utifrån en modell av en hydraulisk applikation, utföra autogenererad diagnostik bland annat iform av felträdsanalys. Innehållet i rapporten beskriver även hur modelleringsarbetet har gått till och utveckling av modellens ingående komponenter. Examensarbetet är utfört på Combitech AB, Linköping.

<p>When developing products, reliability is an important factor that has to be considered. For safety critical systems it is important to know the probability that an item will perform a required function without failure under stated conditions for a stated period of time. The main goal of a reliability prediction analysis is to predict the rate at which the product of a system will fail. To perform this prediction there are a number of methodologies available.</p><p>This Master Thesis proposes a model-based approach for reliability prediction calculations based on the physics of failure and supported by analysis of test-data field returns and physical models provided by the FIDES methodology. FIDES based reliability models have been integrated into a model-based diagnosis environment for seamless integration with other safety assessment analysis.</p><p>The model-based diagnosis environment used in this thesis is model-based reasoner RODON developed by Uptime Solutions AB. Components that uses the FIDES methodology have been developed in RODON, where components can be combined to systems by drag and drop method. Usage profiles that are defined according to the FIDES methodology in RODON are not system specific, which makes them reusable in other systems. The developed library of components and usage profiles makes it easy to model complex systems and perform reliability predictions according to the FIDES methodology.</p>

<p>As machines are increasingly used to fulfill even more needs of mankind, the dependence upon those machines increase. To prevent catastrophic failure and to facilitate maintenance a diagnostic system can be used. A diagnostic system supervises the system and can alarm the operator when a fault has occurred, and possibly determine what the cause may be. One architecture of a diagnostic system is a number of tests run by an on-board computer checking certain combinations of sensor values and control signals chosen in advance. To design these tests is a difficult task, which leads to the desire to automate the test construction. A part of this task can be performed using structural methods.</p><p>In this thesis model based diagnosis is considered. This means that a formal mathematical model is used. The models typically consist of a number of equations describing the behavior of the system. In structural methods it is only considered if a variable exists in an equation or not. The goal of this master thesis project has been to apply structural methods to RODON models. RODON is a software diagnostics tool brought to market by Sörman Information & Media, which can perform various diagnostic-related tasks based on a single model. This model is defined in an object oriented fashion using a Modelica-like language called Rodelica. A prototype implementation of a structural algorithm plug-in has been developed and integrated into RODON. An additional part of the project has been to investigate further possible uses of structural algorithms in RODON, apart from diagnostic test construction. This has been performed as a series of interviews with Sörman and university employees.</p><p>The work performed in this thesis has shown that it is possible to apply structural methods to RODON models. It has also shown that even a prototype implementation can handle quite large systems. Some problems have been found as well, most notably in extracting a structural model from a RODON model. A consequence is that the developed structural plug-in only works for a subset of RODON models. It might be possible to deal with these problems if more time would be spent on the task. Finally, the interview survey revealed other possible uses of structural methods in RODON, including optimal sensor placement analysis and isolability and detectability analysis.</p>

<p>Diagnosis is the task of finding faults or malfunctioning components in a technical system, e.g a car. When doing diagnosis on cars with combustion engines, a computer program can be used. The computer program, also called diagnosis system, needs information about the car. This information could be data sheets of all the electronic components in the car. It could also be a description of how the engine behaves in a nominal and a non-nominal case. This information is contained in a model of the engine. RODON, a diagnostic tool developed by Sörman Information and Media AB, uses models of systems for conflict detection diagnosis. RODON needs fault models of the components to do diagnosis. The diagnosis system is then used in workshops, factories, or other places where cars need to be surveyed.</p><p>In this thesis, a Simulink model of the nominal behaviour of a combustion engine is given. The problem is how to make use of the model as well as the diagnostic tool RODON for combustion engine diagnosis. To solve this, the Simulink model is translated into a RODON model. Translating a Simulink model into a RODON model requires a new library in RODON. The library developed in this thesis is called AdvancedBlocks library.</p><p>The Simulink model describes the nominal behaviour of a combustion engine but for diagnosis with RODON, fault models are needed as well. Several types of faults that can occur in an engine have been studied and fault models have been implemented in RODON. The conclusion is that diagnosis in RODON with a translated engine model is possible.</p>

Diagnosis is the task of finding faults or malfunctioning components in a technical system, e.g a car. When doing diagnosis on cars with combustion engines, a computer program can be used. The computer program, also called diagnosis system, needs information about the car. This information could be data sheets of all the electronic components in the car. It could also be a description of how the engine behaves in a nominal and a non-nominal case. This information is contained in a model of the engine. RODON, a diagnostic tool developed by Sörman Information and Media AB, uses models of systems for conflict detection diagnosis. RODON needs fault models of the components to do diagnosis. The diagnosis system is then used in workshops, factories, or other places where cars need to be surveyed. In this thesis, a Simulink model of the nominal behaviour of a combustion engine is given. The problem is how to make use of the model as well as the diagnostic tool RODON for combustion engine diagnosis. To solve this, the Simulink model is translated into a RODON model. Translating a Simulink model into a RODON model requires a new library in RODON. The library developed in this thesis is called AdvancedBlocks library. The Simulink model describes the nominal behaviour of a combustion engine but for diagnosis with RODON, fault models are needed as well. Several types of faults that can occur in an engine have been studied and fault models have been implemented in RODON. The conclusion is that diagnosis in RODON with a translated engine model is possible.

When developing products, reliability is an important factor that has to be considered. For safety critical systems it is important to know the probability that an item will perform a required function without failure under stated conditions for a stated period of time. The main goal of a reliability prediction analysis is to predict the rate at which the product of a system will fail. To perform this prediction there are a number of methodologies available. This Master Thesis proposes a model-based approach for reliability prediction calculations based on the physics of failure and supported by analysis of test-data field returns and physical models provided by the FIDES methodology. FIDES based reliability models have been integrated into a model-based diagnosis environment for seamless integration with other safety assessment analysis. The model-based diagnosis environment used in this thesis is model-based reasoner RODON developed by Uptime Solutions AB. Components that uses the FIDES methodology have been developed in RODON, where components can be combined to systems by drag and drop method. Usage profiles that are defined according to the FIDES methodology in RODON are not system specific, which makes them reusable in other systems. The developed library of components and usage profiles makes it easy to model complex systems and perform reliability predictions according to the FIDES methodology.

<p>Rodon is a diagnostic tool developed by Sörman. SAAB’s interest in Rodon regards the possibility to use the tool for development and operations of aircraft systems. The main goal of this thesis was to evaluate the capacity of Rodon and determine how SAAB can use the diagnostic tool during development and operations.</p><p>The tool uses model based diagnosis with artificial intelligence for fault isolation which is a powerful approach. If Rodon is introduced at SAAB, then detailed models of systems will be necessary to create, including the nominal behavior of the system and different faulty behaviors. In order to achieve high quality fault isolation, it is necessary to have complete and consistent models. To be able to use all applications that Rodon feature for a modeled system, preferable characteristics are that the model should be static, have discrete control signals, and have well defined system behavioral modes.</p><p>During development of a system Rodon can be used to improve and easy the work for failure analysis, guidance of sensor placements, evaluation of tests, generation of decision structures, and fault isolation. Since design of tests during development is a desirable application that Rodon does not have, two different methods are presented that utilizes Rodon to generate all possible limit checking tests.</p><p>In conclusion, Rodon can be very useful in several different aspects if introduced, but benefits gained by using Rodon will have to be compared to the labor cost of creating good models.</p>

As machines are increasingly used to fulfill even more needs of mankind, the dependence upon those machines increase. To prevent catastrophic failure and to facilitate maintenance a diagnostic system can be used. A diagnostic system supervises the system and can alarm the operator when a fault has occurred, and possibly determine what the cause may be. One architecture of a diagnostic system is a number of tests run by an on-board computer checking certain combinations of sensor values and control signals chosen in advance. To design these tests is a difficult task, which leads to the desire to automate the test construction. A part of this task can be performed using structural methods. In this thesis model based diagnosis is considered. This means that a formal mathematical model is used. The models typically consist of a number of equations describing the behavior of the system. In structural methods it is only considered if a variable exists in an equation or not. The goal of this master thesis project has been to apply structural methods to RODON models. RODON is a software diagnostics tool brought to market by Sörman Information &amp; Media, which can perform various diagnostic-related tasks based on a single model. This model is defined in an object oriented fashion using a Modelica-like language called Rodelica. A prototype implementation of a structural algorithm plug-in has been developed and integrated into RODON. An additional part of the project has been to investigate further possible uses of structural algorithms in RODON, apart from diagnostic test construction. This has been performed as a series of interviews with Sörman and university employees. The work performed in this thesis has shown that it is possible to apply structural methods to RODON models. It has also shown that even a prototype implementation can handle quite large systems. Some problems have been found as well, most notably in extracting a structural model from a RODON model. A consequence is that the developed structural plug-in only works for a subset of RODON models. It might be possible to deal with these problems if more time would be spent on the task. Finally, the interview survey revealed other possible uses of structural methods in RODON, including optimal sensor placement analysis and isolability and detectability analysis.

<p>As space exploration vehicles travel deeper into space, their distance to earth increases.The increased communication delays and ground personnel costs motivatea migration of the vehicle health management into space. A way to achieve thisis to use a diagnosis system. A diagnosis system uses sensor readings to automaticallydetect faults and possibly locate the cause of it. The diagnosis system usedin this thesis is a model-based reasoning tool called RODON developed by UptimeSolutions AB. RODON uses information of both nominal and faulty behavior ofthe target system mathematically formulated in a model.The advanced diagnostics and prognostics testbed (ADAPT) developed at theNASA Ames Research Center provides a stepping stone between pure researchand deployment of diagnosis and prognosis systems in aerospace systems. Thehardware of the testbed is an electrical power system (EPS) that represents theEPS of a space exploration vehicle. ADAPT consists of a controlled and monitoredenvironment where faults can be injected into a system in a controlled manner andthe performance of the diagnosis system carefully monitored. The main goal of thethesis project was to build a model of the ADAPT EPS that was used to diagnosethe testbed and to generate decision trees (or trouble-shooting trees).The results from the diagnostic analysis were good and all injected faults thataffected the actual function of the EPS were detected. All sensor faults weredetected except faults in temperature sensors. A less detailed model would haveisolated the correct faulty component(s) in the experiments. However, the goal wasto create a detailed model that can detect more than the faults currently injectedinto ADAPT. The created model is stationary but a dynamic model would havebeen able to detect faults in temperature sensors.Based on the presented results, RODON is very well suited for stationary analysisof large systems with a mixture of continuous and discrete signals. It is possibleto get very good results using RODON but in turn it requires an equally goodmodel. A full analysis of the dynamic capabilities of RODON was never conductedin the thesis which is why no conclusions can be drawn for that case.</p><p> </p>

Rodon is a diagnostic tool developed by Sörman. SAAB’s interest in Rodon regards the possibility to use the tool for development and operations of aircraft systems. The main goal of this thesis was to evaluate the capacity of Rodon and determine how SAAB can use the diagnostic tool during development and operations. The tool uses model based diagnosis with artificial intelligence for fault isolation which is a powerful approach. If Rodon is introduced at SAAB, then detailed models of systems will be necessary to create, including the nominal behavior of the system and different faulty behaviors. In order to achieve high quality fault isolation, it is necessary to have complete and consistent models. To be able to use all applications that Rodon feature for a modeled system, preferable characteristics are that the model should be static, have discrete control signals, and have well defined system behavioral modes. During development of a system Rodon can be used to improve and easy the work for failure analysis, guidance of sensor placements, evaluation of tests, generation of decision structures, and fault isolation. Since design of tests during development is a desirable application that Rodon does not have, two different methods are presented that utilizes Rodon to generate all possible limit checking tests. In conclusion, Rodon can be very useful in several different aspects if introduced, but benefits gained by using Rodon will have to be compared to the labor cost of creating good models.