Study On Tracking And Identifying Technology Of Boiler Coal Quality

The coal quality is an important parameter affecting the operation of coal-fired power plant boilers.When the coal quality changes,the operation parameters of pulverizing and air distribution system can be adjusted in time according to different coal quality characteristics,so as to optimize the combustion performance of the boilers.The research on online coal quality detection technology has not been well solved in the field of combustion detection,and has become an important bottleneck in the optimization of combustion.It is of great significance to optimize the boiler combustion and unit control to obtain the real-time coal quality data of each coal mill outlet into the boiler.In recent years,all kinds of coal quality online detection technology and products have been developing continuously,and some applications have been obtained in domestic power plants.However,its measurement reliability and accuracy still can not meet the requirements of combustion adjustment,and the price is expensive,the daily maintenance is large,so it can not be applied in the field.Therefore,it is of great significance for the operation of coal-fired boilers to study a method which can realize the online tracking and identification of coal quality.This article is based on a wind pipe coal powder electrostatic measurement signals and the principle of coal quality variation correlation,based on the analysis of static induction signal and coal quality,a wind pipe pulverized coal flow velocity,concentration,temperature,on the basis of electrostatic signal is proposed based on recognition of coal mill charging methods,research is given based on coal quality change recognition,based on the coal mill information,coal quality testing information,The coal bunker material level supervision carries on the real time grinding into the furnace coal quality data tracking scheme;Through the actual acquisition of electrostatic measurement signal,coal quality test data,coal mill operation data and other relevant data of a 1000MW unit in a power plant,the coal quality identification model based on RNN neural network is established to realize the online tracking of boiler coal quality,which verifies the feasibility of the online identification and tracking method proposed in this paper.