Issue |
E3S Web of Conf.
Volume 225, 2021
II International Conference “Corrosion in the Oil & Gas Industry” 2020
|
|
---|---|---|
Article Number | 06002 | |
Number of page(s) | 4 | |
Section | Failure Analysis | |
DOI | https://doi.org/10.1051/e3sconf/202122506002 | |
Published online | 05 January 2021 |
Intellectualizing analysis and assessment of statistical data on field pipeline failures due to internal corrosion
1 Tomsk Polytechnic University, 30, Lenina ave., Tomsk, 634050, Russia
2 TomskNIPIneft JSC, 72, Mira ave., Tomsk, 634027, Russia
* Corresponding author: karmachevd@gmail.com
The paper presents some results of a study meant to create an expert system used to select a material design and method of internal corrosion protection for field pipelines at the design stage. The author has performed an intellectual analysis of operating statistical data on field pipeline failures. The first part of the paper describes the initial sample and the exploratory analysis performed. The second and the third parts describe the processes of creating and assessing a classifier based on the Random Forest algorithm. To assess the quality of the classifiers, the author has calculated the shares of correct answers in the algorithm (accuracy), precision and recall, as well as the F1-score. The author makes a conclusion about satisfactory values of quality metrics and outlines areas for further research.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.