Although Energy Management and Control Systems (EMCS) have since the early 1970’s contributed significantly to the reduction (20-40 percent) of energy use in buildings without sacrificing occupants’ comfort, their full capabilities have not been completely realized. This is in part due to their inability to quickly detect and compensate for failures in the Heating, Ventilation and Air Conditioning (HVAC) system. In fact, no matter how good the control scheme for the HVAC system might be, the presence of undetected faults can completely offset any expected savings. This paper presents a methodology for detecting faults in an HVAC system using a nonlinear mathematical model and an extended Kalman filter. The technique was implemented in a computer program and successfully used to detect “planted” faults in simulations of the air handler unit of an HVAC system. Test results are presented to demonstrate the effectiveness of the methodology.
Skip Nav Destination
Article navigation
December 1985
Research Papers
An Innovation-Based Methodology for HVAC System Fault Detection
P. B. Usoro,
P. B. Usoro
Scientific Systems, Inc., Cambridge, MA 02140
Search for other works by this author on:
I. C. Schick,
I. C. Schick
Scientific Systems, Inc., Cambridge, MA 02140
Search for other works by this author on:
S. Negahdaripour
S. Negahdaripour
Scientific Systems, Inc., Cambridge, MA 02140
Search for other works by this author on:
P. B. Usoro
Scientific Systems, Inc., Cambridge, MA 02140
I. C. Schick
Scientific Systems, Inc., Cambridge, MA 02140
S. Negahdaripour
Scientific Systems, Inc., Cambridge, MA 02140
J. Dyn. Sys., Meas., Control. Dec 1985, 107(4): 284-289 (6 pages)
Published Online: December 1, 1985
Article history
Received:
December 1, 1984
Online:
July 21, 2009
Citation
Usoro, P. B., Schick, I. C., and Negahdaripour, S. (December 1, 1985). "An Innovation-Based Methodology for HVAC System Fault Detection." ASME. J. Dyn. Sys., Meas., Control. December 1985; 107(4): 284–289. https://doi.org/10.1115/1.3140737
Download citation file:
Get Email Alerts
An Adaptive Sliding-Mode Observer-Based Fuzzy PI Control Method for Temperature Control of Laser Soldering Process
J. Dyn. Sys., Meas., Control
Fault detection of automotive engine system based on Canonical Variate Analysis combined with Bhattacharyya Distance
J. Dyn. Sys., Meas., Control
Multi Combustor Turbine Engine Acceleration Process Control Law Design
J. Dyn. Sys., Meas., Control (July 2025)
Related Articles
Bringing Automated Fault Detection and Diagnostics Tools for HVAC&R Into the Mainstream
J. Eng. Sustain. Bldgs. Cities (August,2020)
Multivariate Regression Modeling
J. Sol. Energy Eng (August,1998)
A Passivity-Based Power-Shaping Control of Building HVAC Systems
J. Dyn. Sys., Meas., Control (November,2017)
Cost-Optimal Coordination of Interacting HVAC Loads in Buildings
J. Dyn. Sys., Meas., Control (April,2018)
Related Chapters
Dynamic Cool Roofing Systems
Advanced Energy Efficient Building Envelope Systems
Automated Fault Detection and Diagnosis in HVAC Systems
Handbook of Integrated and Sustainable Buildings Equipment and Systems, Volume I: Energy Systems
Energy Consumption Simulation and Energy Conservation Measures for Typical Public Buildings in Chengdu
International Conference on Green Buildings and Optimization Design (GBOD 2012)