【作者】 杜朝波；

【导师】 王印松； 高建强；

【作者基本信息】 华北电力大学（河北） ， 模式识别与智能系统， 2005， 硕士

【摘要】 本文基于两台450t/h循环流化床锅炉的运行数据,主要做了以下研究: 循环回路各温度和压力的数值、分布和变化规律;给煤、一次风、二次风、氧量、主汽参数、减温水、排烟温度、飞灰含碳量等主要参数在不同工况下的变化规律;运行过程中出现的主要问题和处理方法。在运行特性分析的基础上,基于神经网络方法建立了反映大型循环流化床锅炉床温动态变化规律的非线性数学模型。该模型主要考虑了给煤量和一次风量对床温的影响,将这两个量作为模型的基本输入。还将给煤量、一次风量和床温的历史数据进行离散化处理,并用离散后相关时间序列的数据扩充了神经网络的输入维数,使神经网络模型可以反映床温的动态变化特性,从而建立了床温非线性动态模型。更多还原

【Abstract】 On the basis of operation data of two 450t/h commercial CFB boilers, the author has made a study of CFB boiler. The numerical values, distribution laws and change laws of temperature and pressure in the circulating loop are studied. The change laws of fuel supply, primary air, secondary air, oxygen concentration, main steam parameters, attemperating water, and exhaust gas temperature at different operating conditions are also presented. Furthermore, in operation the main faults and solutions are also discussed. Through the method of neural network, the author develops the model of bed temperature which can reflect the dynamic change laws of bed temperature of large-scale CFB boiler. Developing the model, the author thinks that Fuel supply and primary air have dominate effect on bed temperature. To reflect dynamic characteristics of bed temperature, the inputs of neural network are expanded by adding the historical data of fuel supply, primary air and bed temperature.更多还原