Although energy management and control systems (EMCS) have since the early 1970's contributed significantly to the reduction (20-40%) 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 heat, ventilating 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. The authors present a methodology for detecting and diagnosing faults in an HVAC system using a nonlinear mathematical model and 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. Simulation test results show that by sampling measurements every second, a 1 degree C room temperature sensor bias can be detected within 5-10 seconds of occurence. Such early detection capability for faults would greatly enhance the economic operation of the HVAC system.
|Original language||English (US)|
|Number of pages||7|
|Journal||Proceedings of the American Control Conference|
|State||Published - Dec 1 1985|
ASJC Scopus subject areas
- Electrical and Electronic Engineering