VALIŠ, David and Ondřej POKORA. Estimation of residual life based on vehicle tribo data. In IEEE International Conference on Industrial Engineering and Engineering Management. Bangkok: IEEE Computer Society, 2014, p. 1427-1431. ISBN 978-1-4799-0986-5. Available from: https://dx.doi.org/10.1109/IEEM.2013.6962646.
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Basic information
Original name Estimation of residual life based on vehicle tribo data
Authors VALIŠ, David (203 Czech Republic, guarantor) and Ondřej POKORA (203 Czech Republic, belonging to the institution).
Edition Bangkok, IEEE International Conference on Industrial Engineering and Engineering Management, p. 1427-1431, 5 pp. 2014.
Publisher IEEE Computer Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20306 Audio engineering, reliability analysis
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14310/14:00086996
Organization unit Faculty of Science
ISBN 978-1-4799-0986-5
ISSN 2157-3611
Doi http://dx.doi.org/10.1109/IEEM.2013.6962646
UT WoS 000395631500284
Keywords in English field data assessment; first hitting time; maintenance optimization; off-line diagnostics; residual life
Tags AKR
Tags International impact, Reviewed
Changed by Changed by: Mgr. Marie Šípková, DiS., učo 437722. Changed: 26/8/2020 10:56.
Abstract
The aim of the article is to estimate a system technical life. When estimating a residual technical life statistically, a big amount of tribo-diagnostic data is used. This data serves as the initial source of information. It includes the information about particles contained in oil which testify to oil condition as well as system condition. We focus on the particles which we consider to be interesting. This kind of information has good technical and analytical potential which has not been explored well yet. By modelling the occurrence of particles in oil we expect to find out when a more adequate moment for performing preventive maintenance might come. The way of modelling is based on the specific characteristics of diffusion processes, namely the Wiener process. Following the modelling results we could in fact set the principles of 'CBM - Condition Based Maintenance'. However, the possibilities are much wider, since we can also plan operation and mission. All these steps result in inevitable cost saving.
PrintDisplayed: 16/9/2024 21:56