【作者】 周洪煜；

【导师】 童明伟；

【作者基本信息】 重庆大学 ， 热能工程， 2007， 博士

【摘要】 随着国民经济的飞速发展及对能源需求的日益增大,节能与减少温室气体排放已经被提到非常重要的高度。如何减少能耗,提高能源的有效利用率是关系到我国经济可持续发展的重要问题。在城市建筑物的能耗中,中央空调系统所占的比重最大。根据有关方面的统计,中央空调部分大概占建筑物总能耗的40%～50%,是城市建筑的主要耗能对象。为了降低空调系统的能耗,本课题以中央空调系统作为研究对象,结合实际科研项目,采用先进的控制算法,我们研制出了基于人工智能和专家系统的中央空调节能运行及故障诊断系统。本论文包括以下内容:①中央空调节能运行与中央空调故障诊断系统的发展历史及国内外现状,对中央空调系统的能耗情况进行了分析。建立了基于设备运行的节能技术框架及节能目标体系。②应用计算机控制技术,设计、安装实施了中央空调节能运行与故障自诊断系统,经过近两年的实际运行,设备运行情况良好,完全达到预期的节能目的与自诊断效果。③作为博士研究生论文的第一个创新点,针对中央空调系统存在的非线形和大的滞后,采用了创新的控制手段,在中央空调系统的运行控制中率先提出了先进的基于混合神经网络的非线性预测函数控制及SMITH预估控制算法,编制出控制算法软件并将其应用到实际对象中,完全达到预期的控制效果,经过实际运行对比测算,其节电效果达到30%以上,产生了良好经济的效益。④论文的第二个创新点,结合重庆市建委下达的科研课题,针对中央空调系统在运行中的实际情况,系统地编制了中央空调系统运行故障专家库,建立了中央空调系统运行故障自诊断系统,系统能够在运行过程中进行运行状态提示、故障预报、故障产生原因分析和相应的对策提示等。经过运行实践表明其对防止重大事故的发生,提高设备的有效利用时间,延长其使用寿命都具有良好的效果。该专家库系统被评定为国内领先并获得2006年重庆市科技进步三等奖。实践证明,本论文所研究的基于人工智能和专家系统的中央空调节能运行和专家诊断技术,对降低中央空调的运行能耗,提高运行质量,增加有效运行时间、防止重大事故发生等方面效果明显,具有很大的推广价值。更多还原

【Abstract】 Energy-saving and reduction of greenhouse gas emissions have gained great importance with the vigorous development of the national economy and the increasing demands for energy. How to reduce energy consumption and increase energy utilization effectively are important issues for sustainable economic development of our country.The central air-conditioning system has the largest share of the energy consumption of city buildings. According to relevant statistics, the central air-conditioning system accounts for 40% -50% of the total energy consumption of buildings, hence the main energy consuming source of urban buildings. In order to reduce the energy consumption of the central air-conditioning system, in the present research, which combines actual research programs and adopts advancing control algorithms, we have developed the central air-conditioning energy saving operation system and the fault diagnosis system which are based on artificial intelligence and expert systems.The thesis includes the following contents:①It introduces the history of the energy-saving operation system and the fault diagnosis system of central air-conditioning and the current foreign and domestic situations, analyses the energy consumption of central air-conditioning and establishes energy-saving techno-framework and target system based on equipment running.②It introduces the designing, assembling and running of the computer-based energy-saving system and fault diagnosis system of central air-conditioning. After two years of operation, all the equipment is in good condition, and also reaches the expected goal of saving energy and self-diagnosing.③Using innovative means of control to deal with non-linear and serious delay problems of the central air-conditioning system is an innovative point of this doctoral thesis. The idea of an advanced arithmetic based on non-linear predictive function control and SMITH estimate-calculation in the running control of the central air-conditioning is put forward. The programming and the application of the control software in the actual system has completely reached the expected aim. The counting of the actual operation shows it reduces the use of electricity by over 30%, so it can produce remarkable economic benefits.④The paper’s second innovation, combined with the research projects issued by the Chongqing Municipal Construction Committee, and aiming at the actual condition of central air-conditioning in running, is the systematic programming of an expert database of the central air-conditioning problems in operation and the successful establishing of the fault self-diagnosis system. The system can show the running condition, forecast faults, analyze reasons and prompt treatments, etc. Operation practices show that it can prevent serious accidents, prolong effective using time and the life of equipment after actual running. The expert database system has been assessed as nationally leading and received the Third Prize of The Progress of Science and Technology of the Chongqing Municipality in 2006.Practice has proved that the technique of the central air-conditioning energy-saving operation and fault diagnosis based on artificial intelligence and expert system can reduce the central air-condition energy consumption, and improve the operation quality, increase the effective operation time, prevent serious accidents, etc. It has considerable spreading value.更多还原