Ahmad Alsaab
ESI UK, UK
Morgan Cameron
ESI Group, France
Colin Hough
ESI UK, UK
Purna Musunuru
ESI US R&D, USA
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https://doi.org/10.3384/ecp20169179Published in: Proceedings of the American Modelica Conference 2020, Boulder, Colorado, USA, March 23-25, 2020
Linköping Electronic Conference Proceedings 169:19, p. 179-185
Published: 2020-11-03
ISBN: 978-91-7929-900-2
ISSN: 1650-3686 (print), 1650-3740 (online)
We compare a number of different methods for
estimating model parameters based on external stimuli.
We examine the trade-offs between the different
methodologies with respect to the modelling effort
necessary to implement them and the granularity of the
estimation obtained. In implementing these methods, we
utilize Modelica and FMI.
As an application we show how these methods can be
combined with component fault modes to provide
effective real-time estimates of the health of a physical
asset based on thermal sensor data. In particular, we
contrast the effectiveness of the different estimators in
predicting the degree and location of fault.
