Open AccessEfficient control and Fault Detection and Isolation in Building HVAC systems
Author(s) -
Avisek Naug
Publication year - 2018
Publication title -
proceedings of the annual conference of the prognostics and health management society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.18
H-Index - 11
ISSN - 2325-0178
DOI - 10.36001/phmconf.2018.v10i1.709
Subject(s) - hvac , bond graph , fault detection and isolation , computer science , fault (geology) , isolation (microbiology) , control (management) , control engineering , work (physics) , reliability engineering , artificial intelligence , engineering , actuator , air conditioning , mechanical engineering , mathematics , microbiology and biotechnology , combinatorics , seismology , biology , geology
My thesis work is focused on advancing the state of the art in smart building monitoring and control problems. A major part of my thesis will develop combined model- and data-driven models for the energy systems of buildings and apply them for energy monitoring and optimization, fault diagnosis, and fault-adaptive control. In past work, I have already developed initial machine learning-based models for energy optimization. In this paper, I am focusing on developing a framework using bond graphs to build a model of the HVAC system and understand how different factors affect the measurement variables of this system. This information will help us do subsequent fault diagnosis by studying the characteristics of the system behavior represented by the temporal causal graph. It will also provide the basis for fault-adaptive control of buildings