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Failure prediction of diesel engine based on occurrence of selected wear particles in oil

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F14%3APU115449" target="_blank" >RIV/00216305:26210/14:PU115449 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216224:14310/15:00082688 RIV/60162694:G43__/15:00522868

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Failure prediction of diesel engine based on occurrence of selected wear particles in oil

  • Original language description

    This paper introduces analytical and prognostic methods used for assessing system material wear to predict a failure occurrence. The principles presented in the article are based on indirect but real diagnostic oil data. We concentrate on wear metal particles such as iron (Fe) and lead (Pb) as potential failure indicators.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20306 - Audio engineering, reliability analysis

Result continuities

  • Project

    <a href="/en/project/LO1202" target="_blank" >LO1202: NETME CENTRE PLUS</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ENGINEERING FAILURE ANALYSIS

  • ISSN

    1350-6307

  • e-ISSN

    1873-1961

  • Volume of the periodical

    56

  • Issue of the periodical within the volume

    10/2015

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    11

  • Pages from-to

    501-511

  • UT code for WoS article

    000361832300049

  • EID of the result in the Scopus database