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Vol.11, No.2, May 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Determining the Main Characteristics of Motor Lubricants Using Color Indices and Prediction Models
Zlatin Zlatev, Albena Ivanova-Vasileva, Tsvetelina Georgieva, Plamen Daskalov
© 2022 Plamen Daskalov, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 11, Issue 2, Pages 706-711, ISSN 2217-8309, DOI: 10.18421/TEM112-25, May 2022.
Received: 14 February 2022. Revised: 15 April 2022.
Abstract:
This paper proposes tools for predicting the main characteristics of motor lubricating oils that can be used to assess their quality. A comparative analysis of four measuring devices, operating on optical principle, was performed to predict the main characteristics of motor lubricating oils. It has been found that the combined use of seven color indices leads to increased accuracy in predicting the value characteristics of motor oils. The two main components are needed to reduce the data volume of the vector containing these features, which leads to a reduction in the volume of data used. It was found that according to colorimeter data, regression models have higher predictive properties than those obtained with a video camera and a digital camera. The proposed research tools can be used with single-board microcomputer systems, which do not require complex computational procedures. The use of the proposed in this article techniques and tools in practice would reduce the effect of the measuring instrument experience.
Keywords –optical sensors, oil production, regression analysis, color components, rheological properties, principal component analysis. |
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