2015
Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data
VALIŠ, David, Libor ŽÁK a Ondřej POKORAZákladní údaje
Originální název
Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data
Autoři
VALIŠ, David (203 Česká republika, garant), Libor ŽÁK (203 Česká republika) a Ondřej POKORA (203 Česká republika, domácí)
Vydání
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability, London, SAGE Publications Ltd, 2015, 1748-006X
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
20306 Audio engineering, reliability analysis
Stát vydavatele
Velká Británie a Severní Irsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 1.073
Kód RIV
RIV/00216224:14310/15:00082089
Organizační jednotka
Přírodovědecká fakulta
UT WoS
000349221400004
Klíčová slova anglicky
Failure prediction; system residual technical life estimation; field data; Wiener process
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 5. 11. 2019 11:26, Mgr. Marie Šípková, DiS.
Anotace
V originále
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.