玉米秸秆热裂解产物产率预测分析  

Predict Product Yields of Corn Stalk Plasma Pyrolysis

作　　者：张春梅[1] 刘庆玉[1] 易维明[2] 柏雪卫[1] 张文基[1] 来世鹏[3] 

机构地区：[1]沈阳农业大学工程学院,沈阳110866 [2]山东理工大学清洁能源工程技术研究中心,淄博255049 [3]建设部沈阳煤气热力研究设计院,沈阳110026

出　　处：《农业机械学报》2011年第9期120-123,185,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：辽宁省秸秆能源化利用项目

摘　　要：以影响热裂解液化过程的因素(输入功率、压差、氩气流量和进料率)为网络输入,热裂解液化产物为网络输出,应用BP神经网络模型法对玉米秸秆热裂解液化产物产率进行了预测分析,并将预测结果与非线性回归分析法进行了比较分析。结果表明,采用BP神经网络模型预测输出值与试验值间的相对误差总体上在5%之内,说明模拟预测的效果较好。对BP神经网络模型法与非线性回归方法的预测结果对比分析显示:在试验数据范围内,BP神经网络模型对玉米秸秆热裂解3种产物产率的预测值更接近试验值,计算精度比非线性回归方法略高。A method for predicting product-yield of corn stalk pyrolysis was established by means of BP neural network model. The model consisted of three neuron layers： input layer with four nodes which affected the pyrolysis process. It included input power, air flow rate, feeding rate and pressure, output layer with pyrolysis liquid yield and hidden layer. If the training data were representative, the results obtained by neural network model could be well in accordance with the experimental results and its errors would be less than 5%. The results obtained by neural network are more accurate than those obtained by non- linear regression.

关 键 词：玉米秸秆 热裂解 神经网络模型 产率 预测 

分 类 号：TK6[动力工程及工程热物理—生物能]