Faults in heating, ventilation and air conditioning (HVAC) systems cause increased energy consumption, degrading
thermal comforts, growing operational cost and reduced system lifespan. An effective evaluation of fault effects is
critical to the development of various fault diagnostics solutions, the improvement of operation maintenance and the
optimization of monitoring systems. In the HVAC area, a majority of research work in evaluating fault effects was to
analyze energy consumption impacts or thermal comfort impacts. However, a handful of research has been
conducted on evaluating fault effects on various measurements, which are increasingly employed to monitor
equipment operation. Fault effects on various measurements may display different symptom patterns and present
changed sensitivities when the equipment operates under various faults, severity levels, as well as operation
conditions. However, a long-term observation of fault symptoms under various operational conditions, different fault
types and severity levels to evaluate fault effects is extremely challenging. In this paper, a simulation-based
framework was proposed to evaluate fault effects in fan coil units (FCUs). Two metrics namely fault symptom
occurrence probability (SOP) and fault symptom daily continuous duration (SDCD) were developed to quantify
fault symptoms under various FCU faults. A total of 18 common FCU faults at different severity levels were
implemented on the developed HVACSIM+ simulation platform to obtain a full year fault inclusive data set for 48
fault simulation cases. The framework, as well as obtained SOP and SDCD distributions will benefit multiple folds
such as the development of probability-based fault diagnostics inference approaches, optimization of sensor
location, and fault prioritization.