研究论文
Development of a convolutional neural network model to predict the size and location of corrosion defects on pipelines based on magnetic flux leakage signals
Y. Shen, Wenxing Zhou
Western University
来源International Journal of Pressure Vessels and Piping
年份2023
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工程Non-Destructive Testing Techniques
Structural Integrity and Reliability Analysis · Infrastructure Maintenance and Monitoring
参考文献 66
Electromagnetic methods for detecting corrosion in underground pipelines: magnetic flux leakage (MFL)
被引 23Thomas A. Bubenik · Elsevier eBooks · 2014
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
被引 147Zizhen Yao, Walter L. Ruzzo · BMC Bioinformatics · 2006
Three‐dimensional defect inversion from magnetic flux leakage signals using iterative neural network
被引 58Junjie Chen, Songling Huang, Wei Guo Zhao · IET Science Measurement & Technology · 2015
此处列出前 3 条
引用本文 26
Systematic Evaluation of Ultrasonic In-Line Inspection Techniques for Oil and Gas Pipeline Defects Based on Bibliometric Analysis
被引 33Jie Huang, Pengchao Chen, Rui Li · Sensors · 2024
In-line inspection methods and tools for oil and gas pipeline: A review
被引 24Jia Zhang, Mingnan Sun, Lin Qin · International Journal of Pressure Vessels and Piping · 2024
A comprehensive review on the application of neural network model in microbial fermentation
被引 18Jiacong Huang, Qi Guo, Xu-Hong Li · Bioresource Technology · 2024
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