The soft measuring model, for pollutants release from coal combusting in power plant boiler, was combined with the test data obtained from boiler operation, established on the basis of technology for CMAC artificial neural network, and adopted the hyper CMAC structure and algorithm. The characteristic data about coal quality from boiler operation and combusting conditions in the furnace were took as its input parameters, to achieve precise prediction and on-line measurement of concentration of sulfur and nitrogen pollutant emission. It was effective to guide operator in the power plant to optimize combustion and control pollutants emission.
A Neural-Network-Based Method for Ash Fouling Prediction of Heat Transfer Surface in Coal-fired Power Plant Boiler
