Timothy A. Fuller , Thomas J. Flynn , C. Stuart Daw
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引用次数: 7
Abstract
Driven by economic pressures and government emission regulations, the electric power industry is moving toward tighter control of boilers to improve plant efficiency and reduce emissions. Tighter control depends on better boiler diagnostic tools, especially for discriminating dynamic patterns and correlating those patterns with overall performance. Our research indicated that improved discrimination of dynamic pattern 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 results for measurements from a pressurized fluidized bed and a lowx pulverized coal boiler.
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