Dissertation > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing

Study of Pure Firing BFG Boiler’s Burning Prediction Based on ANN

Author ZhuYuXiang
Tutor LuFang;WangNaiYi
School Shanghai Jiaotong University
Course Power Engineering
Keywords Full- burning blast furnace gas boiler Combustion Stability Factors Artificial Neural Networks Combustion forecasting model
Type Master's thesis
Year 2008
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Blast furnace gas is a by-product of the metallurgical industry in the ironmaking process , a low calorific value and toxic gases . Blast Furnace Gas boiler because of the blast furnace gas as a boiler fuel thus have their own unique characteristics in the design , manufacture and operation of the boiler . Completely blast furnace gas as a boiler fuel , burning blast furnace gas boiler run with ironmaking blast furnace is closely related to the condition . Make timely changes in the operating conditions of the blast furnace the Full Blast Furnace Gas blast furnace combustion forecast , the stable operation of the full- burning blast furnace gas boiler has a certain significance . From the generation of blast furnace gas , nature and combustion mechanism proceed to analyze the factors that affect the operation of the full- burning blast furnace gas boiler combustion stability , then the powerful nonlinear mapping function based on BP artificial neural network to establish a full- burning blast furnace gas blast furnace stability combustion forecasting model . Running data collected wholly- burning blast furnace gas boiler scene of the forecasting model training and testing , the model can provide technical guarantee for the optimization of the Blast Furnace Gas boiler run , able to basically meet the actual demand forecasting model by the on-site inspection .

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