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Semantic Models and Rule-based Reasoning for Fault Detection and Diagnostics: Applications in Heating, Ventilating and Air Conditioning Systems

Authors:
Parastoo Delgoshaei
Mark Austin
Daniel Veronica

Keywords: Fault Detection and Diagnostics; Ontology; Semantic; Rule-based; Heating Ventilating and Air-conditioning (HVAC) systems

Abstract:
This paper discusses an extensible model-based semantic framework for fault detection and diagnostics (FDD) in systems simulation and control. Generally speaking, state-of-the art fault detection methods are equipment and domain specific. As a result, the applicability of these methods in different domains is very limited. Our proposed approach focuses on developing formal models (ontologies) across categories of domain-specific and domain-independent (time and space) phenomena. It then leverages inference-based reasoning over the ontologies for FDD purposes. Together, these techniques provide a semantic framework for the definition and evaluation of multidisplinary concepts relating to a system. FDD rules associated to those concepts are implemented as inference-based rules and are evaluated by a reasoner. We exercise the proposed method by looking at a FDD problem for heating, ventilating and air-conditioning (HVAC) systems simulation.

Pages: 48 to 53

Copyright: Copyright (c) IARIA, 2017

Publication date: April 23, 2017

Published in: conference

ISSN: 2308-4243

ISBN: 978-1-61208-547-0

Location: Venice, Italy

Dates: from April 23, 2017 to April 27, 2017