Ssb2002RpePaperAsSubmitted.pdf (370.22 kB)
Non-linear recursive parameter estimation applied to fault detection and diagnosis in real buildings
conference contribution
posted on 2012-07-26, 11:06 authored by Richard BuswellRichard Buswell, Philip Haves, Timothy I. Salsbury, Jonathan WrightJonathan WrightThis paper describes a fault detection and diagnosis scheme based on parameter estimation and
presents results from its application to a cooling coil subsystem in a real building. A non-linear
adaptation of the Prediction Error Forgetting (PEF), algorithm is employed to estimate the
parameters of a simple, steady-state, first principles based cooling coil model. A steady-state
detector is used to discard data with excessive transients. Three model parameters represent
possible faults; control valve leakage, coil fouling and sensor offset. These parameters are
estimated recursively, together with the uncertainty in the estimated values. A significant change
in a particular parameter indicates abnormal operation and suggests a diagnosis. The paper
describes the first-principle models and their fault parameters, the steady-state detector, and the
recursive parameter estimation algorithm. Results from the application of the technique to data
measured in a test building demonstrate that valve leakage and coil fouling can be detected and
diagnosed. The applicability of the approach to fault detection and diagnosis in real systems is
also discussed.
History
School
- Architecture, Building and Civil Engineering
Citation
BUSWELL, R.A., HAVES, P., SALSBURY, T.I. and WRIGHT, J.A., 2002. Non-linear recursive parameter estimation applied to fault detection and diagnosis in real buildings. IN: Proceedings of the 6th International Conference on System Simulation in Buildings, University of Liege, Belgium, 15-18 December 2002.Version
- AM (Accepted Manuscript)
Publication date
2002Notes
This is a conference paper.Language
- en