A Deep Learning-Based Approach for Pipeline Cracks Monitoring-Reference-Cited by-同舟云学术

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A Deep Learning-Based Approach for Pipeline Cracks Monitoring

Published:2022-11-16 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
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Author:

Altabey Wael A.¹,Kouritem Sallam A.¹,Abouheaf Mohammed I.²,Nahas Nabil³

Affiliation:

1. Alexandria University,Faculty of Engineering,Department of Mechanical Engineering,Alexandria,Egypt,21544

2. Bowling Green State University,Mechatronics Engineering Technology,Bowling Green,OH,USA,43402

3. Université de Moncton,Faculté d'administration,Moncton,NB,Canada,E1A 3E9

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9987724/9987729/09987998.pdf?arnumber=9987998

Reference59 articles.

1. Efficiency of grey wolf optimization algorithm for damage detection of skeletal structures via expanded mode shapes

2. Applying Neural Networks for Tire Pressure Monitoring Systems

3. The thermal effect on electrical capacitance sensor for two-phase flow monitoring

4. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition;he;IEEE Transactions on Pattern Analysis and Machine Intelligence,2015

5. Detection of Fatigue Crack in Basalt FRP Laminate Composite Pipe using Electrical Potential Change Method

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1. A comprehensive study of a long-term creep thermo-mechanical fatigue behavior monitoring of BFRP composite pipeline using electrical capacitance sensors and deep learning algorithm;International Journal of Fatigue;2024-07

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3. A Mathematical Modeling of BFRP Laminated Composite Double-Chamber Mufflers Based Acoustic Transmission Loss Optimization;Lecture Notes in Civil Engineering;2024

4. Pavement Pothole Monitoring via Artificial Intelligence Technology;2023 IEEE International Smart Cities Conference (ISC2);2023-09-24

5. Intelligence Approach for Structural Monitoring via UAV-Artificial Intelligence-Based;2023 IEEE International Smart Cities Conference (ISC2);2023-09-24

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