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Keywords: convolutional neural network
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Journal Articles

Defect Detection of Polyethylene Gas Pipeline Based on Convolutional Neural Networks and Image Processing

Jun-qiang Wang, Sixi Zha, Jia-chen Sun, Yang Wang, Hui-qing Lan
Journal: Journal of Pressure Vessel Technology
Publisher: ASME
Article Type: Research-Article
J. Pressure Vessel Technol. December 2024, 146(6): 061801.
Paper No: PVT-24-1090
https://doi.org/10.1115/1.4066676
Published Online: October 22, 2024
... was established based on the convolutional neural network (CNN), and appropriate model parameters were optimized through model training. The defect recognition rate of the improved model can reach 94.76%. Following, the weighted average graying algorithm was used to separate the defects characterized...
View Article titled, Defect Detection of Polyethylene Gas Pipeline Based on <span class="search-highlight">Convolutional</span> <span class="search-highlight">Neural</span> <span class="search-highlight">Networks</span> and Image Processing
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Topics: Algorithms, Deformation, Pipelines, Pipes, Flaw detection, Edge detection, Convolutional neural networks, Image processing
Journal Articles

Convolutional Neural Network Based Defect Recognition Model for Phased Array Ultrasonic Testing Images of Electrofusion Joints

Yangji Tao, Jianfeng Shi, Weican Guo, Jinyang Zheng
Journal: Journal of Pressure Vessel Technology
Publisher: ASME
Article Type: Technical Briefs
J. Pressure Vessel Technol. April 2023, 145(2): 024502.
Paper No: PVT-21-1178
https://doi.org/10.1115/1.4056836
Published Online: February 22, 2023
.... 10.1109/TPAMI.2016.2577031 [13] Jin , Y. , Zhang , D. , Li , M. , Wang , Z. , and Chen , Y. , 2019 , “ A Fuzzy Support Vector Machine-Enhanced Convolutional Neural Network for Recognition of Glass Defects ,” Int. J. Fuzzy Syst. , 21 ( 6 ), pp. 1870 – 1881...
View Article titled, <span class="search-highlight">Convolutional</span> <span class="search-highlight">Neural</span> <span class="search-highlight">Network</span> Based Defect Recognition Model for Phased Array Ultrasonic Testing Images of Electrofusion Joints
Open the PDF for <span class="search-highlight">Convolutional</span> <span class="search-highlight">Neural</span> <span class="search-highlight">Network</span> Based Defect Recognition Model for Phased Array Ultrasonic Testing Images of Electrofusion Joints in another window
Topics: Artificial neural networks, Flaw detection, Inspection, Ultrasonic testing, Welding, Wire