International Journal of Computational Intelligence Systems

Volume 1, Issue 1, January 2008, Pages 94 - 102

Current Computational Trends in Equipment Prognostics

Authors
J. Wesley Hines, Alexander Usynin
Corresponding Author
J. Wesley Hines
Available Online 1 January 2008.
DOI
https://doi.org/10.2991/ijcis.2008.1.1.7How to use a DOI?
Abstract
CURRENT COMPUTATIONAL TRENDS IN EQUIPMENT PROGNOSTICS The article overviews current trends in research studies related to reliability prediction and prognostics. The trends are organized into three major types of prognostic models: failure data models, stressor models, and degradation models. Methods in each of these categories are presented and examples are given. Ad- ditionally, three particular computational prognostic approaches are considered; these are Markov chain- based models, general path models, and shock models. A Bayesian technique is then presented which integrates the prognostic types by incorporate prior reliability knowledge into the prognostic models. Finally, the article also discusses the usage of diagnostic/prognostic predictions for optimal control.
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
1 - 1
Pages
94 - 102
Publication Date
2008/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2008.1.1.7How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - J. Wesley Hines
AU  - Alexander Usynin
PY  - 2008
DA  - 2008/01
TI  - Current Computational Trends in Equipment Prognostics
JO  - International Journal of Computational Intelligence Systems
SP  - 94
EP  - 102
VL  - 1
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2008.1.1.7
DO  - https://doi.org/10.2991/ijcis.2008.1.1.7
ID  - Hines2008
ER  -