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@article{1196454,
author = {Vališ, David and Žák, Libor and Pokora, Ondřej},
article_location = {London},
article_number = {1},
doi = {http://dx.doi.org/10.1177/1748006X14547789},
keywords = {Failure prediction; system residual technical life estimation; field data; Wiener process},
language = {eng},
issn = {1748-006X},
journal = {Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability},
title = {Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data},
url = {https://journals.sagepub.com/doi/abs/10.1177/1748006X14547789},
volume = {229},
year = {2015}
}
TY - JOUR
ID - 1196454
AU - Vališ, David - Žák, Libor - Pokora, Ondřej
PY - 2015
TI - Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data
JF - Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
VL - 229
IS - 1
SP - 36-45
EP - 36-45
PB - SAGE Publications Ltd
SN - 1748006X
KW - Failure prediction
KW - system residual technical life estimation
KW - field data
KW - Wiener process
UR - https://journals.sagepub.com/doi/abs/10.1177/1748006X14547789
N2 - At present, numerous approaches are devoted to monitoring a system state. Their intention is to determine the current state of a system and predict reliability parameters for the future. This article addresses one of the several possible approaches that allows us to determine a system technical state on the basis of diagnostic data. These diagnostic data are from the area of tribiodagnostics, namely, engine oil. The article examines iron and lead particles that are selected deliberately with respect to their origin in kinematic parts of the system and their degree of correlation with operation measures. The particles occur in oil during both operating time and calendar time development. To model their occurrence during operation time, we have used, in the first part of the article, a mathematical regression method to set parameters. In the second part, we have applied a diffusion model based on a Wiener process. The results confirm that we are able to estimate the residual technical life of a system. Moreover, the results enable us to schedule properly the intervals of preventive maintenance (oil change) and to plan a mission/operation. This results in optimising life cycle costs. It is assumed that the potential of the diagnostic data will be extracted by other approaches and methods. In the subsequent work, it will be useful to determine specific interval values of optimised preventive maintenance.
ER -
VALIŠ, David, Libor ŽÁK and Ondřej POKORA. Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data. \textit{Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability}. London: SAGE Publications Ltd, 2015, vol.~229, No~1, p.~36-45. ISSN~1748-006X. Available from: https://dx.doi.org/10.1177/1748006X14547789.
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