Fault Tolerant Supervision of an Industrial Gas Turbine
Supervision of the performance of an industrial gas turbine is
important since it gives valuable information of the process health
and makes efficient determination of compressor wash intervals
possible. Slowly varying sensor faults can easily be misinterpreted as
performance degradations and result in an unnecessary compressor wash.
Here, a diagnostic algorithm is carefully combined with non-linear
state observers to achieve fault tolerant performance estimation. The
proposed approach is evaluated in an experimental case study with six
months of measurement data from a gas turbine site. The investigation
shows that faults in all gas path instrumentation sensors are
detectable and isolable. A key result of the case study is the ability
to detect and isolate a slowly varying sensor fault in the discharge
temperature sensor after the compressor. The fault is detected and
isolated before the wash condition of the compressor is triggered,
resulting in fault tolerant estimation of compressor health
parameters.charge temperature sensor after the compressor. The fault
is detected and isolated before the wash condition of the compressor
is triggered, resulting in fault tolerant estimation of compressor
health parameters.
Emil Larsson, Jan Åslund, Erik Frisk and Lars Eriksson
2013

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