摘要
提出了采用BP神经网络模型与改进热力计算相结合的方法确定锅炉运行参数基准值。计算中采用BP神经网络模型预测飞灰含碳量的基准值,并根据锅炉运行负荷选取炉膛出口烟气温度计算公式,采用"登山原理"确定过量空气系数的方法确定关键运行参数基准值。最后,以一台HG1025/18.2-M锅炉为例,计算70%、50%负荷下该锅炉运行参数的基准值,得到随着锅炉负荷的降低炉膛出口过量空气系数明显增加,飞灰含碳量和机械未完全燃烧热损失显著降低。证明该方法能够很好地反映锅炉负荷、煤质特性参数改变对运行参数基准值的影响。
Through analyzing the problems of the prevailing method for determining the reference values of operating parameters of a boiler,the authors presented a method for determining the reference values of parameters of a boiler by combining the BP neural network with the improved thermodynamic calculation.During the calculation,the BP neural network model was used to predict the reference value of the carbon content of the flyash and according to the operating load of the boiler,a formulae for calculating the flue gas temperature at the outlet of the furnace was chosen.The method for determining the excess air factor in the'mountain-climbing theory'was used to determine the reference values of the key operating parameters.Finally,with a HG1025/18.2-M boiler serving as an example,the reference values of the operating parameters of the boiler were calculated at 50 % and 70% load,obtaining a conclusion that the excess air ratio at the outlet of the furnace will remarkably increase with a decrease of the boiler load and the carbon content of the flyash and the thermal loss due to the mechanical unburn-out combustion will markedly decrease.It has been proven that the method in question can reflect very well the influence of a change of the boiler load and coal quality characteristic parameters on the reference values of the operating parameters.
出处
《热能动力工程》
CAS
CSCD
北大核心
2011年第5期566-570,633,共5页
Journal of Engineering for Thermal Energy and Power