Development of Fault Detection and Diagnosis Tool for Building Air-conditioning Systems Based on Knowledge Database

建筑空调系统的故障检测与诊断是调试过程中需要验证的重要项目之一。然而，如果没有实际使用的能力，开发用于FDD的工具是非常不充分的。本研究的目的是开发一个易于使用的FDD工具，帮助发现整个建筑空调系统的故障点。本研究得到的结果如下：1。作为FDD工具的启动器，开发了某实验小楼空调系统的仿真程序，并利用实测数据对仿真参数进行了标定。通过仿真程序可以对室内空气温度、系统COP和系统日耗电量进行高精度的仿真。开发了FDD原型工具，并将其引入实验楼的BEMS中，验证了该工具的实用性。在夏季实验中，三种断层已多次重现；房间设置温度故障、送风风机温度控制故障、HPC产生的冷/热水设置温度故障，尝试用开发的工具进行检测。结果表明，该工具检测故障的概率约为90%。通过对某办公大楼空调系统的仿真研究，定量地考察了该工具的节能效果。结果表明，与不使用该工具的情况相比，该工具在夏季、春季和冬季发生故障的概率较高，每年可节省5-10%的能源消耗。

Fault detection and diagnosis (FDD) in building air conditioning systems is one of essential items which should be verified in commissioning process. Development of a tool to FDD is, however, extremely insufficient without ability to use practically. The purpose of this study is to develop an easy-to-use FDD tool that helps to find the faulty place through the whole building air conditioning system. The results obtained in this study are as follows;1. The simulation program of an air-conditioning system introduced in an experimental small building has been developed as a launcher of FDD tool, and the simulation parameters have been calibrated by the measured data. The indoor air temperature, system COP and system daily electric power Consumption could be simulated in high accuracy by the simulation program.2. The prototype FDD tool has been developed, and verified the tool's practicability by introducing in BEMS of the experimental building. In summer experiments, three kinds of fault have been reproduced several times; fault to set up temperature in rooms, fault to control temperature at the fan for the air supply and fault of cold/hot water set up temperature generated by the HPC, and tried to detect them by the developed tool. In the results, the probability that the tool could detect the faults was about 90%.3. The tool's energy saving effect has been examined quantitatively by simulation case studies targeted an actual air-conditioning system in an office building. In the results, it has been clarified that faults generated in summer, spring and winter seasons could be detected in high probability, and the tool could save energy consumption 5-10% yearly, compared to a case that the tool was not used.