A general method for calculating the uncertainty of virtual sensors for packaged air conditioners. (March 2016)

• Record Type: Journal Article
• Authors: Cheung, Howard; Braun, James E.
• Is Part Of: International journal of refrigeration. Volume 63(2016:Mar.)
• Page Start: 225
• Page End: 236
• Publication Date: 2016-03
• Subjects: Virtual sensor -- Uncertainty -- Leverage -- Regression diagnostics -- Packaged air conditioners; Capteur virtuel -- Incertitude -- Influence -- Diagnostic de régression -- Conditionneurs d'air compacts; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2015.06.022
• Languages: English
• ISSNs: 0140-7007

Abstract

Highlights: Virtual sensor uncertainty from model inputs, outputs, calibration and regression. Virtual sensors for power consumption of packaged air conditioning units. Effects of calibration data on virtual sensor uncertainty. Abstract: Virtual sensors use data from low-cost measurements and calibrated models to provide outputs that would either be too expensive or impossible to measure directly. Virtual sensor technology has the potential to enable cost-effective implementation of advanced monitoring, diagnostic, and/or control features for buildings. While it is commonly known that the reliability of virtual sensors depends on the amount and conditions of calibration data, no methods have been presented that quantify the effect of the conditions of calibration data on virtual sensor output uncertainty. In this paper, a general method is presented for estimating the virtual sensor output uncertainty in terms of the uncertainty, conditions and amount of calibration data. The method is demonstrated with a power consumption virtual sensor for packaged air conditioning systems.