VALIŠ, David, Libor ŽÁK and Ondřej POKORA. System Condition Estimation Based on Selected Tribodiagnostic Data. Quality and Reliability Engineering International. WILEY-BLACKWELL, vol. 32, No 2, p. 635-645. ISSN 0748-8017. doi:10.1002/qre.1778. 2016.
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Basic information
Original name System Condition Estimation Based on Selected Tribodiagnostic Data
Authors VALIŠ, David (203 Czech Republic), Libor ŽÁK (203 Czech Republic) and Ondřej POKORA (203 Czech Republic, guarantor, belonging to the institution).
Edition Quality and Reliability Engineering International, WILEY-BLACKWELL, 2016, 0748-8017.
Other information
Original language English
Type of outcome Article in a journal
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
Impact factor Impact factor: 1.366
RIV identification code RIV/00216224:14310/16:00089060
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1002/qre.1778
UT WoS 000370273700024
Keywords in English field data assessment; off-line diagnostics; first-hitting time; system residual technical life; maintenance optimisation; diffusion processes
Tags AKR
Tags International impact, Reviewed
Changed by Changed by: Mgr. Ondřej Pokora, Ph.D., učo 42536. Changed: 13/3/2018 15:51.
Abstract
The aim of the paper is to estimate a system-soft failure occurrence and residual technical life. When estimating a residual technical life statistically, usually a big amount of tribodiagnostic data is used. Data include the information about particles contained in oil that testifies to oil and system conditions. We focus here on the particles that we consider to be interesting. They are ferrum (Fe) and lead (Pb) as contact degradation product. By modelling the occurrence of particles in oil, we expect to determine the expected moment for soft failure occurrence or adequate moment to perform preventive maintenance. The way of our modelling is based on the specific characteristics of diffusion processes, namely the Wiener process with positive drift and Ornstein–Uhlenbeck process. Following the modelling results, we could judge hazard rate and set-up principles of ‘CBM - Condition Based Maintenance’ (CBM). However, the possibilities are much wider, because we can also plan operation, mission and reduce life cost. Copyright © 2015 John Wiley & Sons, Ltd.
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