深圳市大型商场空气品质的测试与分析

本文根据对位于深圳市不同片区的五家大型商场进行室内空气品质现场检测所得的数据,分析了这些商场的室内空气品质状况,各商场不同楼层、不同售货区的空气品质参数分布规律,以及周末、平日、不同时段室内空气品质参数的变化规律,并结合现场实际情况对其原因进行了分析。     

中央空调系统水泵变频应用中存在的几个问题

本文分析了中央空调系统中水泵变频及其运行管理方面所存在的影响节能效果与运行管理质量的几个主要问题 ,提出了相应的解决办法 ,并对中央空调系统水泵变频决策与运行管理提出了几点建议。     

智能化空调设计负荷计算软件的开发

为了解决目前已有空调负荷计算软件使用效率低，不符合设计人员思维习惯的弊病，本文将基于神经网络的专家系统技术与空调负荷“指标估算法”结合起来，开发了一套智能化空调负荷计算软件，对空调设计负荷计算的智能化进行了有益的尝试。该软件计算结果准确，特别适合于经验不足的设计人员使用。     

空调风机的特点及合理选型

介绍了空调风机的特点，并通过实例说明了风机合理的选型过程。     

THERMODYNAMIC PERFORMANCE PREDICTION FOR NON-CFC MIXTURES

The ideal thermodynamic performances of a variety of non-CFC refrigerants and their mixtures were calculated by using the Patel-Teja equation of state. The results indicated that the preferable non-CFC refrigerant mixtures could be HCFC-I24 +HFC-152a, HFC-152a + HFC-134, dimethyl ether + HCFC-22, and dimethyl ether + HCFC-124 for air-conditioning systems, and binary mixtures of HCFC-22 + HFC-125, and HCFC-22 + HFC-143a for low-temperature applications. Those potential non-CFC mixtures were suggested for further investigations.     

Realization of robust nonlinear model predictive control by offline optimisation

This paper describes a new method for increasing the computational efficiency of nonlinear robust model-based predictive control. It is based on the application of neuro-fuzzy networks and improves the computation efficiency by arranging the online optimisation to be done offline. The offline optimisation is realized by offline training a neuro-fuzzy network, consisting of zero-order T–S fuzzy rules, which is designed to approximate the input–output relationship of a robust model-based predictive controller. The design and the training of the neuro-fuzzy network are described, and the corresponding control algorithm is developed. Experiment results performed on the temperature control loop of an experimental air-handling unit (AHU) demonstrate the effectiveness of this approach.     

医院放射科空调系统的辐射防护问题

介绍了医院放射科产生射线的设备及射线的种类,介绍了空调风管穿越放射科房间墙壁时的处理措施,并着重介绍了包裹在风管外的辐射防护材料的屏蔽厚度的计算问题.     

采用单神经元自适应控制高精度空调系统仿真

暖通空调领域中的被控对象(空调房间)大多具有大滞后、慢时变、非线性特点，且受各种不确定因素影响，经典控制方法难以实现精确控制。该文正是针对上述实际，将具有自学习、自适应功能的神经元控制算法引入高精度空调控制领域，并通过MATLAB仿真，考察了系统的控制效果。仿真结果表明此控制方法具有超调小、抗干扰能力强、控温精度高的优点，从而为空调系统的高精度控制提出了一个新的途径。     

Steady-state investigation of water vapor adsorption for thermally driven adsorption based greenhouse air-conditioning system

In the present study, water vapor adsorption onto silica-gel, activated carbon powder (ACP) and activated carbon fiber (ACF) has been experimentally measured at 20, 30 and 50 °C using a volumetric method based adsorption measurement apparatus for greenhouse air-conditioning (AC). The Guggenheim–Anderson–De Boer and Dubinin–Astakhov adsorption models are used to fit the adsorption data of silica-gel and ACP/ACF, respectively. The isosteric heat of adsorption is determined by Clausius–Clapeyron relationship. The adsorbents are evaluated for low-temperature regeneration with aim to develop solar operated AC system for greenhouses. Ideal growth zone for agricultural products is determined by which the steady-state desiccant AC cycle is evaluated on the psychometric chart and adsorption isobars.Steady-state moisture cycled (MC_SS) by each adsorbent is determined for demand category-I, II and III which are based on 60%, 40% and 20% relative humidity of dehumidified air, respectively. In case of demand category-I, the ACP enables maximum MC_SS at all regeneration temperatures (T_reg), ideally sitting at 47 °C. The ACF enables double MC_SS as compared to silica-gel during demand category-II at T_reg ≥59 °C. However, the silica-gel is found the only applicable adsorbent for the demand category-III.     

空调制冷压缩机技术发展研究及其展望

介绍了压缩机的发展历程及现状,尤其是国内近年来在涡旋压缩机型线、工质、润滑以及变频技术应用等方面的研究。通过对涡旋式压缩机回顾,提出了涡旋式压缩机发展方向。近来年,伴随着压缩机相关工业技术的进步,制冷与空调压缩机技术也得到了快速发展,制冷系统的整机能效比有了很大提高。但由于未来的能源供应趋紧和环境保护的双重压力,迫使我们不断探索制冷与空调行业的新技术,以适应我国国情的能源发展战略要求和构建和谐社会目标。