Driven by economic pressures and government emissions 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 disciminating dynamic patterns and correlating those patterns with overall performance. Our research indicates that improved discrimination of dynamic patterns 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 low-NOx pulverized coal combustor.
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Updated: 1998-01-05 ceaf