<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>The crude distillation unit is the most critical elements in the refining process. Moreover, most of the equipment in the distillation unit are made of general carbon steels. Data analysis models, machine learning techniques can predict corrosion degradation rates. We used Pearson’s correlation coefficient and multiple linear regression, to predict the impact of process parameters. Altogether, we have analysed 84 channels of technological parameters, and 22 different types of crude oils. Among the corrosion agents, the chloride content strongly affected the weight loss of coupons, where the highest coefficient was 0.68. The most influential parameter is found to be the pH value. Thus, an estimation method of the pH value is set up to predict the corrosion degradation rate. The regression correlation for estimating the pH value is 0.53 if the corrosion agents are not used, which can be improved to 0.76 if the corrosion agents are also used in the regression analysis.</p>
</abstract>

The crude distillation unit is the most critical elements in the refining process. Moreover, most of the equipment in the distillation unit are made of general carbon steels. Data analysis models, machine learning techniques can predict corrosion degradation rates. We used Pearson’s correlation coefficient and multiple linear regression, to predict the impact of process parameters. Altogether, we have analysed 84 channels of technological parameters, and 22 different types of crude oils. Among the corrosion agents, the chloride content strongly affected the weight loss of coupons, where the highest coefficient was 0.68. The most influential parameter is found to be the pH value. Thus, an estimation method of the pH value is set up to predict the corrosion degradation rate. The regression correlation for estimating the pH value is 0.53 if the corrosion agents are not used, which can be improved to 0.76 if the corrosion agents are also used in the regression analysis.

Application of Regression Models on the Prediction of Corrosion Degradation of a Crude Oil Distillation Unit

Department of Materials Science & Engineering, Faculty of Mechanical Engineering

Budapest University of Technology and Economics

Department of Hydrodynamic Systems, Faculty of Mechanical Engineering

Advances in Materials Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The crude distillation unit is the most critical elements in the refining process. Moreover, most of the equipment in the distillation unit are made of general...

Application of Regression Models on the Prediction of Corrosion Degradation of a Crude Oil Distillation Unit

Publié en ligne: 16 mars 2024

Pages: 72 - 85

DOI: https://doi.org/10.2478/adms-2024-0005

Mots clés
regression analysis, corrosion prediction, predictive maintenance, carbon steel

© 2024 Balázs Varbai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Application of Regression Models on the Prediction of Corrosion Degradation of a Crude Oil Distillation Unit

Publié en ligne: 16 mars 2024

Pages: 72 - 85

DOI: https://doi.org/10.2478/adms-2024-0005

Mots clésregression analysis, corrosion prediction, predictive maintenance, carbon steel

© 2024 Balázs Varbai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
regression analysis, corrosion prediction, predictive maintenance, carbon steel