Issue |
MATEC Web Conf.
Volume 261, 2019
5ième Congrès International Francophone de Mécanique Avancée (CIFMA 2018)
|
|
---|---|---|
Article Number | 02003 | |
Number of page(s) | 3 | |
Section | Design, Reliability, and Optimization | |
DOI | https://doi.org/10.1051/matecconf/201926102003 | |
Published online | 29 January 2019 |
Remaining useful life prediction for ball bearings based on health indicators
FEMTO-ST institute, Univ. Bourgogne Franche-Comté, CNRS, ENSMM, Besançon, 25000, France
* Corresponding author: zeina.almasry@femto-st.fr
Uncertainty in remaining useful life (RUL) prediction is nowadays a scientific problem that occupies industrials. Many prognostic models have been developed to respond to this issue from probabilistic to non-probabilistic approaches. In this paper, we deal with a non- probabilistic model for RUL prediction. For this purpose, we propose a model, which is based on health indicators information, that allows to estimate the RUL of ball bearings. The method is applied to simulated data provided by the PRONOSTIA platform designed and realized at AS2M department of FEMTO- ST Institute.
© Owned by the authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.