Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28369
Title: Diagnostic Bayesian networks for diagnosing air handling units faults - Part II: Faults in coils and sensors
Authors: Zhao, Y
Wen, J
Wang, S 
Keywords: Air handling unit
Bayesian network
Fault detection
Fault diagnosis
Issue Date: 2015
Publisher: Pergamon Press
Source: Applied thermal engineering, 2015, v. 90, p. 145-157 How to cite?
Journal: Applied thermal engineering 
Abstract: This is the second part of a study on diagnostic Bayesian networks (DBNs)-based method for diagnosing faults in air handling units (AHUs) in buildings. In this part, 4 DBNs are developed to diagnose faults in heating/cooling coils, sensors and faults in secondary supply chilled water/heating water systems. There are 18 typical faults concerned and 35 fault detectors introduced. The DBNs are developed mainly on the basis of first principles and fault patterns resulted from literature and three AHU fault detection and diagnosis (FDD) projects. Efficient fault detection rules/methods from a comprehensive literature survey are integrated into the DBNs. Also, some new fault detection rules are developed. The 4 DBNs were evaluated using experimental data from ASHRAE Project RP-1312. Results show that the proposed DBNs effectively diagnosed AHU faults.
URI: http://hdl.handle.net/10397/28369
ISSN: 1359-4311
EISSN: 1873-5606
DOI: 10.1016/j.applthermaleng.2015.07.001
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

12
Last Week
2
Last month
1
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

9
Last Week
0
Last month
0
Citations as of Aug 15, 2017

Page view(s)

41
Last Week
2
Last month
Checked on Aug 21, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.