Bayesian Belief Networks (BBN) and Expert Systems for supporting model based sensor fault detection analysis of smart building systems

Bayesian Belief Networks (BBN) and Expert Systems for supporting model based sensor fault detection analysis of smart building systems

Schagen, J.D. (The Hague University of Applied Sciences)
Taal, A. (The Hague University of Applied Sciences)
Itard, L.C.M. (TU Delft OLD Housing Quality and Process Innovation; The Hague University of Applied Sciences)

Heiselberg, Per Kvols (editor)

2016

The Hague University in Delft uses an advanced climate control system. All sensors and actuators are monitored and deviations from the sensor data are reported daily. The building manager will have to combine the information from the sensor data in order to draw the right conclusions. In this paper, two possible solutions are described for analyzing the data by a computer program. The first solution is by means of a rule-based program, in which predetermined situations have been defined. The data from the sensors are fed into the program and the program checks whether it matches any of the situations. The second solution is to make use of a Bayesian Belief Network. This is a mathematical model that describes the symptoms and causes of a particular problem. With imported sensor data a computer program calculates the likelihood of particular causes of data symptoms.

Bayesian Belief Networks
Expert System
HVAC system
sensor fault detection

http://resolver.tudelft.nl/uuid:d4b79769-2188-4aec-8207-bb3f1919d986

Aalborg University

CLIMA 2016: Proceedings of the 12th REHVA World Congress

CLIMA 2016 - 12th REHVA World Congress, 2016-05-22 → 2016-05-25, Aalborg, Denmark

Institutional Repository

conference paper

© 2016 J.D. Schagen, A. Taal, L.C.M. Itard