Structural Diagnosis Implementation of Dymola Models using Matlab Fault Diagnosis Toolbox
Models are of great interest in many fields of engineering as they
enable prediction of a systems behaviour, given an initial mode of the
system. However, in the field of model-based diagnosis the models are
used in a reverse manner, as they are combined with the observations
of the systems behaviour in order to estimate the system mode. This
thesis describes computation of diagnostic systems based on models
implemented in Dymola. Dymola is a program that uses the language
Modelica. The Dymola models are translated to Matlab, where an
application called Fault Diagnosis Toolbox, FDT is applied. The FDT
has functionality for pinpointing minimal overdetermined sets of
equations, MSOs, which is developed further in this thesis. It is
shown that the implemented algorithm has exponential time complexity
with regards to what level the system is overdetermined,also known as
the degree of redundancy. The MSOs are used to generate residuals,
which are functions that are equal to zero given that the system is
fault-free. Residual generation in Dymola is added to the original
methods of the FDT andthe results of the Dymola methods are compared
to the original FDT methods, when given identical data. Based on these
tests it is concluded that adding the Dymola methods to the FDT
results in higher accuracy, as well as a new way tocompute optimal
observer gain. The FDT methods are applied to 2 models, one model is
based on a system ofJAS 39 Gripen; SECS, which stands for Secondary
Enviromental Control System. Also, applications are made on a simpler
model; a Two Tank System. It is validated that the computational
properties of the developed methods in Dymolaand Matlab differs and
that it therefore exists benefits of adding the Dymola implementations
to the current FDT methods. Furthermore, the investigation of the
potential isolability based on the current setup of sensors in SECS
shows that full isolability is achievable by adding 2 mass flow
sensors, and that the isolability is not limited by causality
constraints. One of the found MSOs is solvable in Dymola when given
data from a fault-free simulation. However, if the simulation is not
fault-free, the same MSO results in a singular equation system. By
utilizing MSOs that had no reaction to any modelled faults, certain
non-monitored faults is isolated from the monitored ones and therefore
the risk of false alarms is reduced. Some residuals are generated as
observers, and a new method for constructing observers is found during
the thesis by using Lannerheds theorem in combination with
Pontryagin’s Minimum Priniple. This method enables evaluation of
observer based residuals in Dymola without any selection of a specific
operating point, as well as evaluation of observers based on
high-index Differential Algebraic Equations, DAEs. The method also
results in completely different behaviourof the estimation error
compared to the method that is already implemented inthe FDT. For
example, one of the new observer-implementations achieves both an
estimation error that converges faster towards zero when no faults are
implementedin the monitored system, and a sharper reaction to
implemented faults.
Petter Lannerhed
2017
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Last updated: 2021-11-10
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