| タイトル | Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation |
| 本文（外部サイト） | http://hdl.handle.net/2060/20130008989 |
| 著者（英） | Galvan, Jose Ramon; Goebel, Kai Frank; Saxena, Abhinav |
| 著者所属（英） | NASA Ames Research Center |
| 発行日 | 2012-09-23 |
| 言語 | eng |
| 内容記述 | This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions. |
| NASA分類 | Quality Assurance and Reliability |
| レポートNO | ARC-E-DAA-TN5954 |
| 権利 | Copyright, Distribution as joint owner in the copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/239146 |
