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Proceedings Papers

Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition

Available to Purchase

Martin Di Blasi, Zhan Li
Proc. ASME. IPC2016, Volume 3: Operations, Monitoring and Maintenance; Materials and Joining, V003T04A011, September 26–30, 2016
Publisher: American Society of Mechanical Engineers
Paper No: IPC2016-64471
https://doi.org/10.1115/IPC2016-64471
View Paper titled, Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition
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Topics: Machine learning, Pattern recognition, Pipelines, Rupture, Leakage, American Petroleum Institute, Cybernetics, Reliability