【作者】 陈晨；

【导师】 王述洋；

【作者基本信息】 东北林业大学 ， 机械工程， 2010， 硕士

【摘要】 随着中国经济的高速发展,国家大力发展城镇化建设,以及人们对生活水平的要求不断提高,如何让城镇居民的供暖质量提高越来越受到人们的关注。目前,我国北方主要城市的供暖仍然以煤为主要燃料,不但每年要消耗大量的煤炭资源,同时也造成严重的环境污染。在世界能源日益紧张、现有常规能源面临枯竭、煤炭价格逐年上涨的背景下,采用成本低、环保性好、具有“零排放”特点的生物质燃料作为供暖锅炉的燃料已成为必然的趋势。因此,研究和开发以生物质为燃料、具有优良控制水平的集中供暖锅炉,对节省宝贵的煤炭资源、有效的减少温室气体排放、保护人类的生存环境,具有重要的经济意义和环保意义。本论文是以国家星火计划项目(2007EA105008)为依托,对现有生物质供暖锅炉结构进行改造设计,并对其喂料及其配风进行自动控制研究和设计,以期达到既节省燃料,又提高供热效能的目的。本文在对生物质成型燃料燃烧特性分析的基础上,对燃料燃烧的发热量进行了分析和计算,着重研究了配风对燃烧速度的影响,并对送料机进行了选型计算；给出了生物质集中供暖锅炉喂料与配风控制系统的总体设计方案；对控制系统下位机PLC的硬件与软件进行了设计；根据锅炉燃烧系统数学建模困难、热传递延时大且不稳定等特点,首次采用RBF(Radial Basis Function)神经网络作为控制器的算法,将一种融合了聚类算法、正交最小二乘学习算法及梯度下降法的递增式RBF神经网络算法应用于该控制系统的建模,并运用MATLAB进行了仿真,结果表明,所选用的方法及所建立的模型适用于生物质集中供暖锅炉喂料及配风控制要求。本论文研究结果对今后生物质供暖锅炉的自动化技术研究与开发具有一定的参考价值。更多还原

【Abstract】 With China’s rapid economic development, urbanization countries develop and people’s living standard continues to improve, and how to improve the heating quality of urban residents will be attract more and more people’s attention.Currently, the main cities in North China are mainly using coal-burning heating still, and this will consume a large amount of coal resources. Under the background of the increasing tension in the world’s energy, facing with the existing conventional energy depletion and the rising coal prices each year, using biomass briquettes of this low-cost, efficient fuel for heating has become the inevitable trend; what’s more,conventional energy use produces a lot of"CO2", a huge threat to the global environment, and therefore, biomass briquettes "zero discharge" of advantages will help alleviate the damage to the environment of human.This article is based on "National Spark Program (2007EA105008)" scientific research projects to study the basis of existing transformation of biomass heating boilers, which is able to feed materials with air volume control, to not only save fuel, but also improve the heating efficiency. Through the analysis of the distribution on the combustion velocity of the wind in the biomass briquette combustion, the heat of fuel combustion are calculated, and the selection of feeding were calculated; the central heating boiler biomassfeed and air distribution control system design program is provided; design the hardware and software of the lower computer PLC control system. According to the difficulties in the mathematical model of the boiler combustion system and the large and unsteady heat transfer delay characteristics, this paper uses the RBF(Radial Basis Function) neural network as a controller algorithm; based on the learning algorithm in the study, the Fusion of the clustering algorithm, orthogonal least squares learning algorithm and the incremental gradient descent method are applied to the RBF neural networkcontrol system. Verify the feasibility of this incremental algorithm through the simulation by using MATLAB.There has a lot of research focusing on biomass heating boilers in the country.This is the first time to utilize RBF neural network to feed the biomass boiler heating system with air control, and to train the neural network. The simulation results have achieved the expected goal, which provide automated operationgood guidance and reference in the future of biomass heating boilers.更多还原