Development of FDD-ON: an Ontology for VAV HVAC System Fault Detection and Diagnostics

Buildings lose efficiency and reliability when HVAC faults go undetected, but fault-detection systems are hampered by inconsistent, siloed data across equipment and vendors. FDD-ON addresses this by creating a formal ontology for variable air volume HVAC systems, defining faults, symptoms, and impacts through a shared vocabulary and explicit cause-effect relationships. This gives machines a common language for diagnostic reasoning. Applications include digital-twin building management, predictive maintenance platforms, and AI-driven facilities systems that need to interpret and share diagnostic data across different tools, ultimately supporting more scalable and interoperable smart-building infrastructure. Authors: Yimin Chen, Brian Fricke, Bo Shen, Jamie Lian, Mingkan Zhang, Paper: https://arxiv.org/abs/2607.29657v1