HVAC系统多传感器数据融合研究

Research on Multi-Sensor Data Fusion of HVAC System

提出了一种简单的、易实现的PMV(Predicted Mean Vote)值的计算方法。针对HVAC(Heating Ventilation and Air Conditioning)系统检测装置和控制系统存在的时间滞后,使人体舒适性得不到很好的满足,并且有额外的能量消耗,进而研究了多传感器数据融合算法及基于D-S证据理论的最小风险决策算法以满足HVAC系统做出合理的决策。根据决策结果可以调节最优的空气量,改进空气处理系统的响应速率,最后利用Labview开发环境来实现数据融合算法。将Labview与多传感器数据融合应用于HVAC系统,增强了研究的系统的稳定性和快速性,保证了人体的舒适性,并且减少了能耗。

A simple and easy to achieve method of calculating PMV（Predicted Mean Vote）value is presen- ted. Time lag in detection devices and control systems of HVAC（Heating Ventilation and Air Conditioning） system makes human comfortable not very well and generates additional energy consumption. Aiming at this problem, multi-sensor data fusion algorithm and minimum risk decision-making algorithm are studied to meet the needs of HVAC system to make a reasonable decision-making. According to the result of decision-making,optimal air amount can be adjusted, and the response rate of air handling system is improved. Finally,Labview is used to realize data fusion algorithm. Labview and data fusion are applied to HVAC system, then the stabilitY and rapidity of the system researched are enhanced, and human comfort is ensured while energy consumption is reducted.