Indoor biological contamination and HVAC system secondary contamination problems caused wide public concerns. Biological contamination control will be the next step to achieve better IAQ. The most efficient and safe w...Indoor biological contamination and HVAC system secondary contamination problems caused wide public concerns. Biological contamination control will be the next step to achieve better IAQ. The most efficient and safe way to control biological contamination was to limit relative humidity in HVAC system and conditioned environment in the range that is more unsuitable for microorganism to survive. In this paper,by referring to bio-clean project experiences,a system-based humidity priority control manner came into being by lowering outdoor air humidity ratio to eliminate all indoor latent load and using self recirculation units to bear indoor sensible load. Based on the whole-course residue humidity contaminant control concept,dynamic step models for coil and conditioned zone were developed to describe mass and energy conservation and transformation processes. Then,HVAC system and conditioned zone dynamic models were established on LabVIEW+Matlab platform to investigate optimized regulation types,input signatures and control logics. Decoupling between cooling and dehumidification processes can be achieved and a more simplified and stable control system can be acquired by the system-based humidity priority control strategy. Therefore,it was a promising way for controlling biological pollution in buildings in order to achieve better IAQ.展开更多
为了提高室内照明均一性智能控制能力,提出基于虚拟现实的室内照明均一性智能控制系统设计方法。首先,构建室内照明均一性控制约束参量模型,采用光学跟踪方法进行室内照明均一性输出调节。然后,根据光强的散射性以及衍射性进行室内照明...为了提高室内照明均一性智能控制能力,提出基于虚拟现实的室内照明均一性智能控制系统设计方法。首先,构建室内照明均一性控制约束参量模型,采用光学跟踪方法进行室内照明均一性输出调节。然后,根据光强的散射性以及衍射性进行室内照明的输出强度误差补偿,采用高速和高分辨率的光学传感跟踪融合方法进行室内照明均一性智能调节。最后,采用3D Studio Max进行室内照明均一性控制的虚拟现实仿真。仿真结果表明,采用该方法进行室内照明均一性智能控制的输出稳定性较好,光照调节的误差较低,提高了照明的均一性控制能力。展开更多
基金Project(2006BAJ02A10) supported by the National Key Technologies R & D Program of China
文摘Indoor biological contamination and HVAC system secondary contamination problems caused wide public concerns. Biological contamination control will be the next step to achieve better IAQ. The most efficient and safe way to control biological contamination was to limit relative humidity in HVAC system and conditioned environment in the range that is more unsuitable for microorganism to survive. In this paper,by referring to bio-clean project experiences,a system-based humidity priority control manner came into being by lowering outdoor air humidity ratio to eliminate all indoor latent load and using self recirculation units to bear indoor sensible load. Based on the whole-course residue humidity contaminant control concept,dynamic step models for coil and conditioned zone were developed to describe mass and energy conservation and transformation processes. Then,HVAC system and conditioned zone dynamic models were established on LabVIEW+Matlab platform to investigate optimized regulation types,input signatures and control logics. Decoupling between cooling and dehumidification processes can be achieved and a more simplified and stable control system can be acquired by the system-based humidity priority control strategy. Therefore,it was a promising way for controlling biological pollution in buildings in order to achieve better IAQ.
文摘为了提高室内照明均一性智能控制能力,提出基于虚拟现实的室内照明均一性智能控制系统设计方法。首先,构建室内照明均一性控制约束参量模型,采用光学跟踪方法进行室内照明均一性输出调节。然后,根据光强的散射性以及衍射性进行室内照明的输出强度误差补偿,采用高速和高分辨率的光学传感跟踪融合方法进行室内照明均一性智能调节。最后,采用3D Studio Max进行室内照明均一性控制的虚拟现实仿真。仿真结果表明,采用该方法进行室内照明均一性智能控制的输出稳定性较好,光照调节的误差较低,提高了照明的均一性控制能力。
