J 2016

Perspective analysis outcomes of selected tribodiagnostic data used as input for condition based maintenance

VALIŠ, David, Libor ŽÁK, Ondřej POKORA a Petr LÁNSKÝ

Základní údaje

Originální název

Perspective analysis outcomes of selected tribodiagnostic data used as input for condition based maintenance

Autoři

VALIŠ, David (203 Česká republika, garant), Libor ŽÁK (203 Česká republika), Ondřej POKORA (203 Česká republika, domácí) a Petr LÁNSKÝ (203 Česká republika, domácí)

Vydání

Reliability engineering & system safety, ELSEVIER SCI LTD, 2016, 0951-8320

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

Impakt faktor

Impact factor: 3.153

Kód RIV

RIV/00216224:14310/16:00089525

Organizační jednotka

Přírodovědecká fakulta

UT WoS

000365367300023

Klíčová slova anglicky

Field data assessment; Off-line diagnostics; First hitting time; System residual technical life; Maintenance optimization; Diffusion processes

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 14. 3. 2018 15:39, Mgr. Ondřej Pokora, Ph.D.

Anotace

V originále

The aim of this article is to estimate system soft failure occurrence and residual technical life in order to optimise firmly planned preventive maintenance. To do this, selected wear particles from oil field data are analysed. Using a large tribodiagnostic dataset we estimate the residual technical life of the observed system statistically. The dataset includes information about particles contained in oil which testify to oil conditions as well as system conditions. We focus here on the wear particles which we (and other analysts) consider to be interesting, ferrum (Fe) and lead (Pb), regarded as contact degradation and wear products. By modelling the occurrence of particles in oil we plan to determine the expected moment when soft failure occurs; this moment might then be set as the time to perform preventive maintenance (PM). Both operation time and calendar time are used here for modelling, for soft failure occurrence determination and for residual technical life estimation. The modelling is based on the specific characteristics of two diffusion processes, the Wiener process (WP) with positive drift and the OrnsteinUhlenbeck process (OUP). We also applied a fuzzy inference system to support our first results from the diffusion processes as there is a level of uncertainty and fuzziness in the oil field data. Following the modelling outcomes we are able to judge the system hazard rate, predict expected mean residual life and set up principles of "condition based maintenance" (CBM) for this system. However, the possible uses of our outcomes are much wider. For example, they can be used as inputs for operation and mission planning, and life cycle costs can be significantly reduced thanks to the maintenance optimisation.