Silicon Carbide Photodiode Flame Temperature Sensors in an Active Combustion Pattern Factor Control System

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Introduction
The combustion pattern factor in a gas turbine is a measurement
of the difference between the peak and average temperature at the
turbine inlet.
where Tpeak is the measured peak temperature at the combustor
exit and Tavg is the average of the measured temperatures.
The objective of active pattern factor control APFC is to minimize
the pattern factor by modulating the fuel flow to each fuel
nozzle while maintaining a constant engine firing temperature.
Reducing the burner pattern factor through active control has
many potential advantages, including elimination of hot streaks at
the turbine inlet, more efficient fuel burning, decreased emissions,
and increased life of expensive hot-zone parts such as turbine
nozzles and blades. As a secondary effect, APFC also can potentially
enable an overall increase in average firing temperature and,
thus, engine efficiency by reducing required firing temperature
operating margins that have been necessary because of large combustion
pattern factors.


Technical Approach
Figure 1 provides an overview of the technical approach to
control the turbine’s pattern factor using the FTS. The APFC is
made up of several interacting data analysis modules that can be
separated into three major components.
• the flame temperature sensors
• the combustor and sensor health models that interpret the
signals from the FTS


Active Pattern Factor Controller. A number of algorithms
for controlling the individual fuel valves were evaluated.
These included a decentralized Proportional plus Integral controller
and a neural-network based adaptive controller. In the end, the
team developed a controller, which consists of a fault-tolerant
peak/valley detection/switching module integral controller.


Simulation Results
To test the APFC, the system was run through a number of
simulated scenarios. Two are presented here. In these two scenarios,
the T700 engine repeated the same engine operating cycle.
The system is given an initial unbalanced pattern factor. The engine
cycle starts with a throttle step input at t=0. When the engine
reaches a steady state at around the 9 s point, a mode detector
turns on the pattern factor controller.
The first simulation is a of a health system. The second simulation
introduces a nozzle malfunction. Other simulations run but
not included in this paper included dirty optics e.g., viewport,
sensor failures, and sensor biases.