Diagnosis System Conceptual Design Utilizing Structural Methods - Applied on a UAV's Fuel System
To simplify troubleshooting and reliability of a process, a diagnosis
system can supervise the process and alarm if any faults are
detected. A diagnosis system can also identify one, or several faults,
i.e. isolate faults, that may have caused the alarm. If model-based
diagnosis is used, tests based on observations from the process are
compared to a model of the process to diagnose the process. It can be
a hard task to find which tests to be used for maximal fault detection
and fault isolation. Structural Methods require not very detailed
knowledge of the process to be diagnosed and can be used to find such
tests early in the design of new processes. Sensors are used to get
observations of a process. Therefore, sensors placed on different
positions in the process gives different possibilities for
observations. A specific set of sensors are in this work called a
sensor configuration.
This thesis contributes with a method to predict and examine the fault
detection and fault isolation possibility. By using these two
diagnosis properties, a suitable sensor configuration is computed and
tests to be used in a future diagnosis system are suggested. For this
task an algorithm which can be used in the design phase of diagnosis
systems, and a Matlab implementation of this algorithm are described.
In one part of this work the Matlab implementation and the algorithm
are used to study how a model-based diagnosis-system can be used to
supervise the fuel system in an Unmanned Aerial Vehicle (UAV).
Tobias Axelsson
2004
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