Open AccessIntegrated Health Management System Approach
Author(s) -
Edward W. Mayfield,
Guangxing Niu,
Bin Zhang,
Paul Ziehl,
Michael Golda
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.v10i1.552
Subject(s) - prognostics , testbed , scalability , navy , reliability engineering , variety (cybernetics) , fault (geology) , computer science , condition monitoring , feature (linguistics) , systems engineering , engineering , artificial intelligence , database , computer network , electrical engineering , archaeology , seismology , history , geology , linguistics , philosophy
This paper aims to develop an integrated shipboard condition prognostics system that integrates sensing, feature extraction, and particle filtering-based diagnostic and prognostic algorithms with applications to bearing systems. The proposed effort aims to provide effective assessment of the condition of shipboard rotating machinery systems and lower the operation and maintenance (O&M) cost. The proposed work is tested on data of various fault modes, models with multiple interactive faults, and experimental testbed as a whole system. The proposed condition prognostics system is scalable, generic, easy-to-implement, and mathematically rigorous, which can be applied to a variety of Navy applications.