Defect identification for oil and gas pipeline safety based on autonomous deep learning network

Author:

Zhang Min,Guo YanbaoORCID,Xie Qiuju,Zhang Yuansheng,Wang Deguo,Chen Jinzhong

Publisher

Elsevier BV

Subject

Computer Networks and Communications

Reference49 articles.

1. Distribution and potential of global oil and gas resources;Tong;Petrol. Explor. Dev.,2018

2. The reflection of the fundamental torsional mode from cracks and notches in pipes;Demma;J. Acoust. Soc. Am.,2003

3. K. Reber, M. Beller, H. Willems, et al., A new generation of ultrasonic in-line inspection tools for detecting, Sizing and Locating Metal Loss and Cracks in Transmission Pipelines, in: Proceedings of the IEEE Ultrasonics Symposium, Vol. 1, no. 1, pp. 665–671.

4. Analysis of magnetic-flux leakage (mfl) data for pipeline corrosion assessment;Peng;IEEE Trans. Magn.,2020

5. The science of pipe corrosion: A review of the literature on the corrosion of ferrous metals in soils;Cole;Corros. Sci.,2012

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