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

楼宇空调系统的故障检测与诊断是调试过程中必须验证的项目之一。然而，如果没有实际使用的能力，开发FDD工具是极其不够的。本研究的目的是开发一个简单易用的故障诊断工具，以帮助找到故障的地方，通过整个建筑物的空调系统。本研究取得的主要结果如下：1.开发了某实验小建筑空调系统的仿真程序，作为FDD工具的启动器，并利用实测数据对仿真参数进行了标定。该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.开发了原型FDD工具，并将其应用于实验楼的BEMS中，验证了该工具的实用性。在夏季实验中，三种故障已被再现多次;故障设置温度的房间，故障控制温度在风扇的空气供应和故障的冷/热水设置温度由HPC产生的，并试图通过开发的工具来检测它们。结果表明，该工具检测故障的概率约为90%.该工具的节能效果进行了定量的模拟案例研究，针对一个实际的空调系统在办公楼。在结果中，它已经澄清，在夏季，春季和冬季季节产生的故障可以检测到在高概率，该工具可以节省能源消耗5-10%，每年相比，该工具没有使用的情况下。

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.