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Datascience To Enhance Pipeline Maintenance

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The paper will cover the construction method (based on Random forest algorithms), the first results. We will see the enhancements of the model by injecting more data and modifying mathematical rule, and how it will be able to integrate a new decision support tool.

Product Number: 51322-17508-SG
Author: David Toschini, Markéta Lallementová, Anthony Dequick, Bernard Masson, Thomas Zamojski
Publication Date: 2022
Industries: Corrosion Monitoring and Control , Coatings
$0.00
$20.00
$20.00

We can now make improvements on the assessment of the external coating condition of underground pipelines: in fact, after excavation and examination, only a small proportion of detected coating anomalies contain also a metallic fault or worse corrosion. GRTgaz, operator and owner of the longest high-pressure natural gas grid in Europe (approximatively 32 000km (19,884 miles), has tested an analytical approach based on historical data to increase the success rate (from the understanding of the problem and the available data, to the elaboration of algorithms and the optimization of their parameter). Different data sources to extract new knowledge have been used, works have been prioritized and the excavations have been optimized in order to have fewer but more efficient interventions.

We can now make improvements on the assessment of the external coating condition of underground pipelines: in fact, after excavation and examination, only a small proportion of detected coating anomalies contain also a metallic fault or worse corrosion. GRTgaz, operator and owner of the longest high-pressure natural gas grid in Europe (approximatively 32 000km (19,884 miles), has tested an analytical approach based on historical data to increase the success rate (from the understanding of the problem and the available data, to the elaboration of algorithms and the optimization of their parameter). Different data sources to extract new knowledge have been used, works have been prioritized and the excavations have been optimized in order to have fewer but more efficient interventions.

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Product Number: 51322-17813-SG
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