Publications
2022
Chen, Yimin; Lin, Guanjing; Chen, Zhelun; Wen, Jin; Granderson, Jessica
A simulation-based evaluation of fan coil unit fault effects Journal Article
In: Energy and Buildings, vol. 263, pp. 112041, 2022, ISSN: 0378-7788.
Abstract | Links | BibTeX | Tags: Fan Coil unit, Fault effects, Fault symptom evaluation, HVACSIM+, Symptom intensity, Symptom occurrence probability
@article{CHEN2022112041,
title = {A simulation-based evaluation of fan coil unit fault effects},
author = {Yimin Chen and Guanjing Lin and Zhelun Chen and Jin Wen and Jessica Granderson},
url = {https://www.sciencedirect.com/science/article/pii/S0378778822002122},
doi = {https://doi.org/10.1016/j.enbuild.2022.112041},
issn = {0378-7788},
year = {2022},
date = {2022-01-01},
journal = {Energy and Buildings},
volume = {263},
pages = {112041},
abstract = {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's 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 operation 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.},
keywords = {Fan Coil unit, Fault effects, Fault symptom evaluation, HVACSIM+, Symptom intensity, Symptom occurrence probability},
pubstate = {published},
tppubtype = {article}
}
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’s 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 operation 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.