Lamia Benzaid,, Nedjem-eddine Benchouia and Azzeddine Bouzaouit (2020) Modeling the Degradation of Viscosity of Engine Oils with a Stochastic Method. ICIC Express Letters, Part B: Applications – An International Journal of Research and Surveys , Volume 11,Number 1(ICICELB-1907-008)), 9-15, ICIC-ELB
Scientific Publications
Important: This page is frozen. New documents are now available in the digital repository DSpace
Abstract
In this paper, we present an analytical study to describe the monitoring and
change in the condition of viscosity of lubricating oil used in combustion engines, and exploited
under very severe conditions. The objective is to determine the remaining lifetime
of this oil. Stochastic methods in general are statistical methods that can be employed in
predictive analysis, and they highly depend on probability theory. Markov models in particular,
make it possible to predict the degradation of the oil viscosity after a determined
operating time. In these, degradation can be described by transition probabilities from
one state to another. Knowing that Markov models are used to describe the transition
probability to a new state (i) at time (t) based directly on probability of the previous state
(j) at time (t–1). In this context, we propose a Markov model to study the degradation
law for the SAE 40 oil. The latter is designed for the lubrication of locomotives engines
under the working conditions of a steel plant in Algeria. We have demonstrated that
the proposed model gives detailed results describing the different conditions/states of the
analyzed oil.
Keywords: Lubrication, Engine oil, Viscosity, Service time, Markov chain
change in the condition of viscosity of lubricating oil used in combustion engines, and exploited
under very severe conditions. The objective is to determine the remaining lifetime
of this oil. Stochastic methods in general are statistical methods that can be employed in
predictive analysis, and they highly depend on probability theory. Markov models in particular,
make it possible to predict the degradation of the oil viscosity after a determined
operating time. In these, degradation can be described by transition probabilities from
one state to another. Knowing that Markov models are used to describe the transition
probability to a new state (i) at time (t) based directly on probability of the previous state
(j) at time (t–1). In this context, we propose a Markov model to study the degradation
law for the SAE 40 oil. The latter is designed for the lubrication of locomotives engines
under the working conditions of a steel plant in Algeria. We have demonstrated that
the proposed model gives detailed results describing the different conditions/states of the
analyzed oil.
Keywords: Lubrication, Engine oil, Viscosity, Service time, Markov chain
Information
| Item Type | Journal |
|---|---|
| Divisions | |
| ePrint ID | 2155 |
| Date Deposited | 2020-04-08 |
| Further Information | Google Scholar |
| URI | https://univ-soukahras.dz/en/publication/article/2155 |
BibTex
@article{uniusa2155,
title={Modeling the Degradation of Viscosity of Engine Oils with a Stochastic Method},
author={Lamia Benzaid,, Nedjem-eddine Benchouia and Azzeddine Bouzaouit},
journal={ICIC Express Letters, Part B: Applications – An International Journal of Research and Surveys}
year={2020},
volume={Volume 11,Number 1},
number={ICICELB-1907-008)},
pages={9-15},
publisher={ICIC-ELB}
}
title={Modeling the Degradation of Viscosity of Engine Oils with a Stochastic Method},
author={Lamia Benzaid,, Nedjem-eddine Benchouia and Azzeddine Bouzaouit},
journal={ICIC Express Letters, Part B: Applications – An International Journal of Research and Surveys}
year={2020},
volume={Volume 11,Number 1},
number={ICICELB-1907-008)},
pages={9-15},
publisher={ICIC-ELB}
}