Impact Factor:6.636

DOI Number:10.1109/TASE.2020.2979166

Affiliation of Author(s):Nanjing University of Information Science and Technology

Journal:IEEE Transactions on Automation Science and Engineering

Funded by:National Science Foundation under Grant CCF-1331850

Key Words:Air handling system, fault prognosis, remaining useful life, hidden semi-Markov model

Abstract:Fault prognosis of air handling systems, which are key sub-systems of Heating, Ventilation and Air Conditioning systems, allows system operators to know the Remaining Useful Life (RUL), thus preventing unexpected breakdowns and reducing operational and maintenance costs.  In this paper, a new hidden Semi-Markov model-based method is developed.  In the method, only relevant state transition points are selected and estimated, leading to computational efficiency.  Physics-based models are used in a novel way to provide “mapping matrices” relating component capacities to fault severities.

All the Authors:Peter B. Luh,Krishna R. Pattipati

First Author:Ying Yan

Indexed by:Journal paper

Discipline:Engineering

First-Level Discipline:Control Science and Engineering

Document Type:J

Volume:17

Issue:4

Page Number:2145-2153

ISSN No.:1545-5955

Translation or Not:no

Date of Publication:2020-03-07

Included Journals:SCI