This paper describes a new tool developed for the detection of operating faults in ventilation units with heat recovery. In principle, the tool is based on the APAR (Air Handling Unit Performance Assessment Rules) method. By following the semantic data description in accordance with the BrickSchema and Project Haystack initiatives, the tool is portable. The executive part of the fault detection system consists of several dozen detection rules, which simultaneously seeks to estimate wasted energy, the threat to user comfort, or the risk of reduced device lifespan, so that the detected faults can be sorted according to their severity.

The developed detection tool was validated on real devices incorporated in a pilot plant. For validation purposes, the method of fault induction on real HVAC (Heating, Ventilation and Air Conditioning system) units was used, with subsequent inspection of whether the faults were revealed or not. The results revealed a 90% detection rate. The data set created as a result of this pilot plant is published as an annex to this article.

In addition, the ability of the detection tool to reveal faults was also verified on the basis of data sets of measurements taken during the standard operation of several dozen HVAC units. The elimination of the identified operating faults generated energy savings of several thousands of dollars per year.

本文介绍了一种新工具，该工具可用于检测具有热回收功能的通风设备中的操作故障。原则上，该工具基于APAR（空气处理机组性能评估规则）方法。通过按照BrickSchema和Project Haystack计划遵循语义数据描述，该工具是可移植的。故障检测系统的执行部分由几十个检测规则组成，这些规则同时旨在估计浪费的能量，对用户舒适度的威胁或缩短设备使用寿命的风险，以便可以根据故障的严重性对故障进行分类。

该开发的检测工具已在包含在中试工厂中的真实设备上得到验证。为了进行验证，使用了在实际的HVAC（供暖，通风和空调系统）单元上引发故障的方法，随后检查了是否发现了故障。结果表明检出率为90％。由于该试验工厂而创建的数据集已作为本文的附件发布。

此外，还根据几十个HVAC单元在标准操作期间进行的测量数据集，验证了检测工具发现故障的能力。消除已发现的操作故障，每年可节省数千美元的能源。