Fault detection and localization using IFC: a case study of BIM-based visualisation of BAS-related faults

Based on a topological network for fault detection and localization, this paper proposes a BIM-based visualisation technique for diagnosing BAS (Building Automation Systems) components in terms of forward and backward fault propagation. The premise is twofold: (1) that visualisation of a building can provide a spatial context auxiliary to human reasoning; (2) that BIM models can be accessed to generate accurate 3D visualisation of spatial-functional relations of building components targeted by a fault detection strategy. Implemented in Python, the visualisation technique is tested on a case study by executing knowledge-based diagnostic rules, retrieving data from the building’s IFC content and generating visualisation of the fault detection and localisation results.