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Diagnostic Bayesian networks for diagnosing air handling units faults – part I: Faults in dampers, fans, filters and sensors
Journal article   Open access   Peer reviewed

Diagnostic Bayesian networks for diagnosing air handling units faults – part I: Faults in dampers, fans, filters and sensors

Yang Zhao, Jin Wen, Fu Xiao, Xuebin Yang and Shengwei Wang
Applied thermal engineering, v 111, pp 1272-1286
25 Jan 2017
DOI: https://doi.org/10.1016/j.applthermaleng.2015.09.121
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
http://ira.lib.polyu.edu.hk/bitstream/10397/102960/1/Xiao_Diagnostic_Bayesian_Networks.pdfView
Accepted (AM)CC BY-NC-ND V4.0,  Open

Abstract

Air handling unit Bayesian network Fault detection Fault diagnosis
"A diagnostic Bayesian networks-based method is proposed for AHU fault diagnosis."4 DBNs are developed to diagnose ten typical faults with fourteen fault detectors."Evaluations are made using the experimental data from the ASHRAE Project RP-1312. Faults in air handling units (AHUs) affect the building energy efficiency and indoor environmental quality significantly. There is still a lack of effective methods for diagnosing AHU faults automatically. In this study, a diagnostic Bayesian networks (DBNs)-based method is proposed to diagnose 28 faults, which cover most of common faults in AHUs. The basic idea is to fully utilize all diagnostic information in an information fusion way. The DBNs are developed based on a comprehensive survey of AHU fault detection and diagnosis (FDD) methods and fault patterns reported in three AHU FDD projects including NIST 6964, ASHRAE projects RP-1020 and RP-1312. The study is published in two parts. In the Part I, the methodology is described firstly. Four DBNs are developed to diagnose faults in fans, dampers, ducts, filters and sensors. There are 10 typical faults concerned and 14 fault detectors introduced. Evaluations are made using the experimental data from the ASHRAE Project RP-1312. Results show that the DBN-based method is effective in diagnosing faults even when the diagnostic information is uncertain and incomplete.

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156 citations in Web of Science
171 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#13 Climate Action
#11 Sustainable Cities and Communities
#7 Affordable and Clean Energy

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Energy & Fuels
Engineering, Mechanical
Mechanics
Thermodynamics
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