Optimization Decision Technology for Fine Coal Blending and Combustion of Industrial Coal-fired Boilers Based on LIBS Iteration
There are many types and components of fuel involved in coal blending and combustion,which affect the operational efficiency and nitrogen oxide production of industrial coal-fired boilers.Therefore,a refined coal blending and combustion optimization decision-making tech-nology for industrial coal-fired boilers based on LIBS iteration is proposed.Analyze and clarify the characteristics of coal blending,obtain LIBS spectral data of coal blending elements based on LIBS iterative technology,remove LIBS spectral noise data using S-G filter,extract LIBS spectral data characteristics using Random forest method,quantitatively detect coal blending elements,construct optimization decision objective function of coal blending and combustion,and develop objective function solution program,By executing the program,the optimiza-tion decision plan for fine coal blending and combustion of industrial coal-fired boilers can be obtained.The experimental data shows that un-der different experimental group backgrounds,the minimum total nitrogen oxide production obtained by applying the proposed technology is 200 mg·m3,and the maximum efficiency of industrial coal-fired boilers is 96%,fully confirming that the proposed technology has better ap-plication performance.
refinementindustrial coal-fired boilersoptimize decision-makingLIBS iterative algorithmblending and burning of coalele-ment analysis and prediction of coal quality