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A Qualitive Modeling Approach for Fault Detection and Diagnosis on HVAC Systems
Abstract
This paper describes the basics and first test results
of a model based approach using qualitative
modeling to perform Fault Detection and Diagnostics
(FDD) on HVAC and R systems. A quantized system
describing the qualitative behavior of a dynamical
system is established by transforming numerical
inputs into qualitative values or states. Then, the
qualitative model is used to determine system-states
or outputs that may occur in the future. The qualitative
model determines the probability that a subsequent
condition might occur. The model can then be
used for FDD purposes by comparing the expected
states of the faultless system with the occurring states
of the real process. The paper presents the first results
of the model, trained with measurement data of an air
handling unit (AHU) heating coil. The authors plan to
extend the model to further AHU components and to
test them against real data to assess their performance
for FDD and their economic viability in terms of
engineering efforts and costs by comparing them with
a rule-based FDD system. It is then planned to implement
and test the models on several large
HVAC and R systems operating at two major European
airports in the framework of the FP7 European project
CASCADE ICT for Energy Efficient Airports.
Citation
Muller, T.; Rehault, N.; Rist, T. (2013). A Qualitive Modeling Approach for Fault Detection and Diagnosis on HVAC Systems. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /151437.