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Monitoring internal combustion engine wear from engine oil using linear regression

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F26%3A00564782" target="_blank" >RIV/60162694:G43__/26:00564782 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.spiedigitallibrary.org/conference-proceedings-of-spie" target="_blank" >https://www.spiedigitallibrary.org/conference-proceedings-of-spie</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1117/12.3083483" target="_blank" >10.1117/12.3083483</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Monitoring internal combustion engine wear from engine oil using linear regression

  • Original language description

    This paper deals with the wear monitoring of an internal combustion engine in a heavy combat vehicle. For the purpose of the study, engine oil samples were collected and then checked using a technique called atomic emission spectroscopy (AES). This is one of the modern ways of measuring metallic elements in oil, including iron. The amount of iron in engine oil is expressed in parts per million (ppm). This indicates how much the metal parts of an internal combustion engine are worn. Engine oil samples from 15 combat vehicles over several years were used for the experiment. The aim of this work was to predict the iron concentration in engine oil using a suitable mathematical method. Robust linear regression with MM estimator is used in this paper. It is a method that combines high robustness to outliers and minimizes a weighted loss function using an iterative optimization approach. The second method used is the least squares method, which is a mathematical technique that works by minimizing the sum of the squares of the differences between the actual values and the values predicted by the model.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20300 - Mechanical engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of SPIE - The International Society for Optical Engineering

  • ISBN

    978-1-5106-9521-4

  • ISSN

    0277-786X

  • e-ISSN

    1996-756X

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    SPIE

  • Place of publication

  • Event location

    Singapore, Republic of Singapore

  • Event date

    Jun 30, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article