Driven by economic pressures and government emissions regulations, the
electric power industry is moving toward tighter control of boilers t
o improve plant efficiency and reduce emissions. Tighter control depen
ds on better boiler diagnostic tools, especially for discriminating dy
namic patterns and correlating those patterns with overall performance
. Our research indicates that improved discrimination of dynamic patte
rns in boilers can be achieved by combining traditional data analysis
techniques and chaotic time series analysis. Suggested analysis tools
and data acquisition procedures are described, along with example resu
lts for measurements from a pressurized fluidized bed and a low-NOx pu
lverized coal boiler.