Fault detection and diagnosis with modelica
language using deep belief network
Accepted 17th
July, 2017
Byoungdoo Lee, Dongkyu Lee and
Deaheom Park
Green Building Research Team, R&D Division, Hyundai Engineering and
Construction, South Korea.
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 detection and diagnosis, air-handling
unit, deep belief network, Modelica.
This is an open access article
published under the terms of the
Creative Commons Attribution
License, which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is
properly cited.
Cite this article as:
Lee B, Lee D, Park D (2017). Fault detection and diagnosis with modelica
language using deep belief network. Acad. J. Environ. Sci. 5(7): 108-117.
