Fault isolation for an industrial gas turbine with a model-based diagnosis approach
Model based diagnosis and supervision of industrial gas turbines are
studied. Monitoring of an industrial gas turbine is important as it
gives valuable information for the customer about service performance
and process health. The overall objective of the paper is to develop a
systematic procedure for modelling and design of a model based
diagnosis system, where each step in the process can be automated and
implemented using available software tools. A new Modelica gas media
library is developed, resulting in a significant model size reduction
compared to if standard Modelica components are used. A systematic
method is developed that, based on the diagnosis model, extracts
relevant parts of the model and transforms it into a form suitable for
stan- dard observer design techniques. This method involves techniques
from simulation of DAE models and a model reduction step. The size of
the final diagnosis model is 20% of the original model size.
Combining the modeling results with fault isolation techniques,
simultaneous isolation of sensor faults and fault tolerant health
parameter estimation is achieved.
Emil Larsson, Jan Åslund, Erik Frisk and Lars Eriksson
2010

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