既有办公建筑变风量空调系统诊断及改造

既有办公建筑的变风量空调系统普遍存在VAVbox入口直管段过短、二次风采用过长或弯折的软管、单独隔间回风不畅等问题。相关自控系统则存在风量传感器不准、风机变频逻辑缺失、楼控系统卡顿等。针对既有办公建筑的变风量空调系统的常见问题,通过实际项目案例介绍了诊断、改造及优化的方法。通过诊断明确问题症结,提出改造建议。改造目标是修补空调系统缺陷、恢复变风量控制功能及满足现有房间的个性化需求。改造完成后,对系统能力、控制逻辑及室内效果进行验证,并基于效果验证进行自控参数优化调适,最终实现变风量空调的自动运行。对既有办公建筑变风量空调系统的诊断及改造提供了清晰的思路。

汽车空调制冷系统故障诊断浅析

汽车空调为车内人员提供了冬暖夏凉的乘车环境。然而由于汽车空调的工作环境极其恶劣,导致空调系统容易出现各种故障,尤其是空调制冷系统。

基于虚拟仪器的汽车空调故障诊断系统的设计与开发

本文以帕萨特B5空调系统为基础,利用虚拟仪器设计开发汽车空调故障诊断教学系统,可以实现汽车空调故障诊断的离线模拟练习、在线实时检测以及标准数据查询等功能,优化了教学手段,提升了教学效果。

Fault isolation of air handling unit based on neural network

Aiming at various faults in an air conditioning system,the fault characteristics are analyzed.The influence of the faults on the energy consumption and thermal comfort of the system are also discussed.The simulation results show that the measurement faults of the supply air temperature can lead to the increase in energy consumption.According to the fault characteristics,a data-driven method based on a neural network is presented to detect and diagnose the faults of air handling units.First,the historical data are selected to train the neural network so that it can recognize and predict the operation of the system.Then,the faults can be diagnosed by calculating the relative errors denoting the difference between the measuring values and the prediction outputs.Finally,the fault diagnosis strategy using the neural network is validated by using a simulator based on the TRNSYS platform.The results show that the neural network can diagnose different faults of the temperature,the flow rate and the pressure sensors in the air conditioning system.