To realize high combustion efficiency and low pollution emission for coal-fired utility boilers

the constrained fuzzy weighted extracting rules algorithm was proposed for boiler combustion optimization

which can quickly determine the quantitative relationship among different combustion variables. Moreover

with the algorithm at the core

a data mining approach was presented to extract the optimal rules of boiler combustion from massive historical operation data covering full-scale working condition. A knowledge base for multi-objective combustion optimization could be developed by all the optimal rules. Experiments on the generator units proved that

by using this boiler combustion optimization rule

the NOx emission decreased by 69.47 mg/m~3 on average

the carbon content in fly ash reduced by 0.05% on average and the boiler efficiency increased by 0.11% on average

comparing with the operation results without optimal rules. Therefore

the data mining approach can be effective in relieving pressure on energy conservation and pollution reduction and is convenient to be implemented in practice.