Results 251 to 260 of about 219,781 (336)

A Novel Crack Quantification Method for Ultra-High-Definition Magnetic Flux Leakage Detection in Pipeline Inspection

IEEE Sensors Journal, 2022
Cracks that may cause pipeline cracking and leakage become the main risk of in-service pipelines after conventional metal loss defects have been detected.
Yue Long, Jinghua Zhang, Songling Huang, Lisha Peng, Wenzhi Wang, Shen Wang, Wei Zhao   +6 more
semanticscholar   +3 more sources

Multisensor Fusion for Magnetic Flux Leakage Defect Characterization Under Information Incompletion

IEEE Transactions on Industrial Electronics, 2021
Magnetic flux leakage (MFL) inspection robots are widely used in the pipeline inspection industry to obtain MFL information from multisensor sources. Multisensor fusion is required for precise defect characterization.
Mingrui Fu, Jinhai Liu, Hua-guang Zhang, Senxiang Lu   +3 more
semanticscholar   +3 more sources

Pipeline Magnetic Flux Leakage Image Detection Algorithm Based on Multiscale SSD Network

IEEE Transactions on Industrial Informatics, 2020
In order to solve the problem of low detection accuracy of small targets in the SSD detection algorithm, a pipeline magnetic flux leakage image detection algorithm based on multiscale SSD network is proposed in this paper.
Lijian Yang, Zhujun Wang, Song-wei Gao
semanticscholar   +3 more sources

An Intelligent Defect Detection Approach Based on Cascade Attention Network Under Complex Magnetic Flux Leakage Signals

IEEE transactions on industrial electronics (1982. Print), 2023
Magnetic flux leakage (MFL) detection robots are broadly employed in acquiring MFL signals to detect pipeline defects. However, influenced by the complex pipeline environments, the accuracy of defect detection under complex MFL signals is undesirable. To
Jinhai Liu, Xiangkai Shen, Jianfeng Wang, Lin Jiang, Hua-guang Zhang   +4 more
semanticscholar   +1 more source

A Novel Cascaded Deep Learning Model for the Detection and Quantification of Defects in Pipelines via Magnetic Flux Leakage Signals

IEEE Transactions on Instrumentation and Measurement, 2023
In this article, we present a machine learning-based quantitative method for the interpretation of signals gathered from nondestructive testing (NDT) of steel pipelines via a semi-autonomous in-line-inspection (ILI) robot.
Veysel Yuksel, Y. Tetik, Mahmut Omer Basturk, Onur Recepoglu, Kursad Gokce, M.A. Cimen   +5 more
semanticscholar   +1 more source

Defect Size Quantification for Pipeline Magnetic Flux Leakage Detection System via Multilevel Knowledge-Guided Neural Network

IEEE transactions on industrial electronics (1982. Print), 2023
Defect size quantification plays a vital role in pipeline magnetic flux leakage detection system. However, most existing methods suffer from poor applicability and low precision due to the complex industrial process.
Lei Wang, Hua-guang Zhang, Jinhai Liu, Fuming Qu, Fengyuan Zuo   +4 more
semanticscholar   +1 more source

Image recognition model of pipeline magnetic flux leakage detection based on deep learning

Corrosion reviews, 2023
Deep learning algorithm has a wide range of applications and excellent performance in the field of engineering image recognition. At present, the detection and recognition of buried metal pipeline defects still mainly rely on manual work, which is ...
Zhenchang Xu, Kuirong Liu, Bill Gu, Luchun Yan, Xiaolu Pang, K. Gao   +5 more
semanticscholar   +1 more source

A Fast Magnetic Flux Leakage Small Defect Detection Network

IEEE Transactions on Industrial Informatics, 2023
To solve the problem of the difficult and slow detection of small defects in magnetic flux leakage (MFL), we propose a fast MFL small defect detection network (FSDDNet).
Fucheng Han, Xianming Lang
semanticscholar   +1 more source

Pipeline Irregular Defect Inversion for Magnetic Flux Leakage Detection System Based on Heterogeneous Multiclass Feature Fusion

IEEE Transactions on Instrumentation and Measurement, 2023
Defect inversion estimates the defect size quantitatively, which is a significant process in the magnetic flux leakage (MFL) detection system. The actual measured defects are irregular due to the complex environment, which leads to signal deformation ...
Lin Jiang, Hua-guang Zhang, Jinhai Liu, Xiangkai Shen, Lei Wang   +4 more
semanticscholar   +1 more source

A Multisensor Cycle-Supervised Convolutional Neural Network for Anomaly Detection on Magnetic Flux Leakage Signals

IEEE Transactions on Industrial Informatics, 2022
To improve the validity of magnetic flux leakage (MFL) multisensor signals, anomaly detection has become a significant part of MFL signal processing. The anomalies in MFL are uncertain and have no prior information or labels. Therefore, the detection and
Lin Jiang, Hua-guang Zhang, Jinhai Liu, Xian-geng Shen, Hang Xu   +4 more
semanticscholar   +1 more source