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Automated Fault Detection and Diagnosis for HVAC&R Systems: Functional Description and Lessons Learnt

[+] Author Affiliations
T. Agami Reddy

Drexel University, Philadelphia, PA

Paper No. ES2008-54027, pp. 589-599; 11 pages
  • ASME 2008 2nd International Conference on Energy Sustainability collocated with the Heat Transfer, Fluids Engineering, and 3rd Energy Nanotechnology Conferences
  • ASME 2008 2nd International Conference on Energy Sustainability, Volume 1
  • Jacksonville, Florida, USA, August 10–14, 2008
  • Conference Sponsors: Advanced Energy Systems Division and Solar Energy Division
  • ISBN: 978-0-7918-4319-2 | eISBN: 0-7918-3832-3
  • Copyright © 2008 by ASME


From the last two decades, the development of robust automated fault detection and diagnosis (FDD) methods applicable to HVAC&R equipment has been an area of active research, and several papers have been written on this issue. However, the use of these systems is not prevalent in the industry as yet, and some reasons for this status are presented in this paper. This paper also provides a description of the various functions and capabilities of an automated FDD system and summarizes pertinent lessons learnt from previous research studies. It is not meant to be a bibliographic review but a clear description and succinct assessment of the various issues which impact this topical area.

Copyright © 2008 by ASME



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