%0 Journal Article
%K Fault symptom evaluation
%K Fault effects
%K Symptom occurrence probability
%K Symptom intensity
%K Fan coil unit
%K HVACSIM+
%A Yimin Chen
%A Guanjing Lin
%A Zhelun Chen
%A Jin Wen
%A Jessica Granderson
%B Energy and Buildings
%D 2022
%G eng
%R doi.org/10.1016/j.enbuild.2022.112041
%T A simulation-based evaluation of fan coil unit fault effects
%V 263
%8 03/2022
%X <p>Faults in heating, ventilation and air conditioning (HVAC) systems cause increased energy consumption, degrading<br />thermal comforts, growing operational cost and reduced system lifespan. An effective evaluation of fault effects is<br />critical to the development of various fault diagnostics solutions, the improvement of operation maintenance and the<br />optimization of monitoring systems. In the HVAC area, a majority of research work in evaluating fault effects was to<br />analyze energy consumption impacts or thermal comfort impacts. However, a handful of research has been<br />conducted on evaluating fault effects on various measurements, which are increasingly employed to monitor<br />equipment operation. Fault effects on various measurements may display different symptom patterns and present<br />changed sensitivities when the equipment operates under various faults, severity levels, as well as operation<br />conditions. However, a long-term observation of fault symptoms under various operational conditions, different fault<br />types and severity levels to evaluate fault effects is extremely challenging. In this paper, a simulation-based<br />framework was proposed to evaluate fault effects in fan coil units (FCUs). Two metrics namely fault symptom<br />occurrence probability (SOP) and fault symptom daily continuous duration (SDCD) were developed to quantify<br />fault symptoms under various FCU faults. A total of 18 common FCU faults at different severity levels were<br />implemented on the developed HVACSIM+ simulation platform to obtain a full year fault inclusive data set for 48<br />fault simulation cases. The framework, as well as obtained SOP and SDCD distributions will benefit multiple folds<br />such as the development of probability-based fault diagnostics inference approaches, optimization of sensor<br />location, and fault prioritization.</p>