A  Classification and Quantitative Assessment Method for Internal and External Surface Defects in Pipelines Based on Astc-Net

Author:

Yuan Jie,Qiao Mengtian,Hu Chun,Cheng Yufei,Wang Zhen,Zheng Dezhi

Publisher

Elsevier BV

Reference25 articles.

1. Leak detection and localization techniques in oil and gas pipeline: A bibliometric and systematic review;Jie Yuan;Engineering Failure Analysis,2023

2. Dayahead city natural gas load forecasting based on decomposition-fusion technique and diversified ensemble learning model;Fengyun Li;Applied Energy,2021

3. Frequency response function method for dynamic gas flow modeling and its application in pipeline system leakage diagnosis;Xia Li;Applied Energy,2022

4. Development of a physics-informed doubly fed cross-residual deep neural network for high-precision magnetic flux leakage defect size estimation;Hongyu Sun;IEEE Transactions on Industrial Informatics,2022

5. An iterative stacking method for pipeline defect inversion with complex mfl signals;Ge Yu;IEEE Transactions on Instrumentation and Measurement,2020

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