Article | Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015 | Fault Detection and Diagnosis with Modelica Language using Deep Belief Network
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Title:
Fault Detection and Diagnosis with Modelica Language using Deep Belief Network
Author:
Dongkyu Lee: Green City R&D Team, R&D Division, Hyundai Engineering and Construction Company, South Korea Byoungdoo Lee: Green City R&D Team, R&D Division, Hyundai Engineering and Construction Company, South Korea Jin Woo Shin: Department of Electrical Engineering, KAIST, South Korea
DOI:
10.3384/ecp15118615
Download:
Full text (pdf)
Year:
2015
Conference:
Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015
Issue:
118
Article no.:
066
Pages:
615-623
No. of pages:
9
Publication type:
Abstract and Fulltext
Published:
2015-09-18
ISBN:
978-91-7685-955-1
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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The air handling unit (AHU) is the main component of heating, ventilation and air-conditioning (HVAC) systems, and irregular faults in AHUs are major sources of energy consumption. For energy efficient operation of HVAC, this paper aims to detect and diagnose three abnormal states in the AHU with the popular deep learning model, called Deep Belief Network (DBN), where we train it using various data generated by Modelica.

Keywords: Fault detectin and diagnosis; Air-handling unit; Deep Belief Network

Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Author:
Dongkyu Lee, Byoungdoo Lee, Jin Woo Shin
Title:
Fault Detection and Diagnosis with Modelica Language using Deep Belief Network
DOI:
http://dx.doi.org/10.3384/ecp15118615
References:

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Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Author:
Dongkyu Lee, Byoungdoo Lee, Jin Woo Shin
Title:
Fault Detection and Diagnosis with Modelica Language using Deep Belief Network
DOI:
http://dx.doi.org/10.3384/ecp15118615
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