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A fast method for rectangular crack sizes reconstruction in magnetic flux leakage testing
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4613-0383-1openalex-snapshot
Review of Progress in Quantitative Nondestructive Evaluation
inferredcites →https://doi.org/10.1007/s003390100899openalex-snapshot
Estimating the sizes of surface cracks based on Hall element measurements of the leakage magnetic field and a dipole model of a crack
inferredcites →https://doi.org/10.1007/s11721-007-0002-0openalex-snapshot
Particle swarm optimization
inferredcites →https://doi.org/10.1016/0029-1021(71)90018-1openalex-snapshot
Research techniques in nondestructive testing
inferredcites →https://doi.org/10.1016/0308-9126(86)90134-3openalex-snapshot
New findings in the field of non-destructive magnetic leakage field inspection
inferredcites →https://doi.org/10.1016/j.ndteint.2005.11.004openalex-snapshot
Detection and measurement of surface cracks in ferromagnetic materials using eddy current testing
inferredcites →https://doi.org/10.1016/s0963-8695(03)00051-3openalex-snapshot
Modeling of the yoke-magnetization in MFL-testing by finite elements
inferredcites →https://doi.org/10.1016/s0963-8695(98)00020-6openalex-snapshot
Method for sizing of 3-D surface breaking flaws by leakage flux
inferredcites →https://doi.org/10.1049/iet-smt:20060069openalex-snapshot
Improved FEM model for defect-shape construction from MFL signal by using genetic algorithm
inferredcites →https://doi.org/10.1063/1.1306093openalex-snapshot
Study of the dipole model of a crack
inferredcites →https://doi.org/10.1063/1.1558693openalex-snapshot
Neural network-based inversion algorithms in magnetic flux leakage nondestructive evaluation
inferredcites →https://doi.org/10.1109/tmag.2002.804817openalex-snapshot
Electromagnetic NDE signal inversion by function-approximation neural networks
inferredcites →https://doi.org/10.1115/1.3167651openalex-snapshot
Research Techniques in Nondestructive Testing
inferredcites →https://doi.org/10.1179/000705978798318765openalex-snapshot
Research Techniques in Non-Destructive Testing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Design of a Magnetic Flux Leakage (Mfl) Device for Efficient Corrosion Defect Detection
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Optimal Design of the Handled Device to Detect Defects of Connected Piping Systems Based on the Magnetic Flux Leakage Method
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A Methodology for Identifying Defects in the Magnetic Flux Leakage Method and Suggestions for Standard Specimens
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Overview of Researches on the Nondestructive Testing Method of Metal Magnetic Memory: Status and Challenges
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Development of a convolutional neural network model to predict the size and location of corrosion defects on pipelines based on magnetic flux leakage signals
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Crack characterization in ferromagnetic steels by pulsed eddy current technique based on GA-BP neural network model
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Evaluation of defect depth in ferromagnetic materials via magnetic flux leakage method with a double Hall sensor
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Real-time online inversion of GA-PSO-BP flux leakage defects based on information fusion: Numerical simulation and experimental research
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A review of metal magnetic memory technology in civil engineering
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Discontinuity inspection in pipelines: A comparison review
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Influence of spatial winding distribution of flexible eddy current sensor on quantitative monitoring of subsurface cracks
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Fast reconstruction method for defect profiles of ferromagnetic materials based on metal magnetic memory technique
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Analysis of the universality of the residual stress evaluation method based on residual magnetic field measurements
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Defect classification and quantification method based on AC magnetic flux leakage time domain signal characteristics
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Low-power eddy current detection with 1-1 type magnetoelectric sensor for pipeline cracks monitoring
inferred← citeshttps://doi.org/10.1016/j.sna.2025.117367openalex-snapshot
The synergistic evolution of pipeline MFL inspection: A review on the fusion of physical models, AI, and multi-modal sensing
inferred← citeshttps://doi.org/10.1016/j.ymssp.2025.112408openalex-snapshot
A multidirectional magnetic flux leakage detection based crack 3-D profile reconstruction method
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Flaw Sizing from Three-Dimensional Magnetic Flux Leakage Images Using a Feedforward Neural Network-Based Machine Learning Technique
inferred← citeshttps://doi.org/10.1080/10589759.2012.740040openalex-snapshot
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An improved magnetic dipole model for MFL testing based on non-uniform magnetic charge distribution
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Automated matching and visualisation of magnetic flux leakage data in shale gas pipeline based on ICP and DBSCAN algorithm
inferred← citeshttps://doi.org/10.1088/1361-6420/ad2f63openalex-snapshot
Quantifying predictive uncertainty in damage classification for nondestructive evaluation using Bayesian approximation and deep learning
inferred← citeshttps://doi.org/10.1088/1361-6501/acac45openalex-snapshot
Study of MFL signal identification in pipelines based on non-uniform magnetic charge distribution patterns
inferred← citeshttps://doi.org/10.1088/1757-899x/424/1/012010openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/imtc.2011.5944294openalex-snapshot
Simulation on high speed rail magnetic flux leakage inspection
inferred← citeshttps://doi.org/10.1109/indin51400.2023.10218172openalex-snapshot
Graph Neural Network-Based Measurement Inference on Irregular Sensor Geometries
inferred← citeshttps://doi.org/10.1109/ist.2011.5962202openalex-snapshot
Approximating the distribution of flaws in magnetic materials using the generalized inverse
inferred← citeshttps://doi.org/10.1109/tim.2023.3238756openalex-snapshot
Crack Detection Method Based on the Poly-Magnetic Probe Structure
inferred← citeshttps://doi.org/10.1109/tmag.2012.2208119openalex-snapshot
Fast Magnetic Flux Leakage Signal Inversion for the Reconstruction of Arbitrary Defect Profiles in Steel Using Finite Elements
inferred← citeshttps://doi.org/10.1109/tmag.2015.2498119openalex-snapshot
Cuckoo Search and Particle Filter-Based Inversing Approach to Estimating Defects via Magnetic Flux Leakage Signals
inferred← citeshttps://doi.org/10.1109/tmag.2018.2809671openalex-snapshot
Importance of Magnetizing Field on Magnetic Flux Leakage Signal of Defects
inferred← citeshttps://doi.org/10.1109/tmag.2018.2816075openalex-snapshot
Highly Sensitive Planar Hall Magnetoresistive Sensor for Magnetic Flux Leakage Pipeline Inspection
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Quantitative Inversion of Stress and Crack in Ferromagnetic Materials Based on Metal Magnetic Memory Method
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Evaluation of a Magnetic Dipole Model in a DC Magnetic Flux Leakage System
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A Fast Forward Model for Surface Defect Characterization in Magnetic Flux Leakage Testing
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Numerical Simulation and Experimental Research on Crack Magnetic Flux Leakage Field
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Magnetic Flux Leakage Signal Inversion Based on Improved Efficient Population Utilization Strategy for Particle Swarm Optimization
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A method for quantitative identification of magnetic flux leakage of fatigue cracks in ferromagnetic components
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Development of a robot-based magnetic flux leakage inspection system
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Classification and Regression of Pinhole Corrosions on Pipelines Based on Magnetic Flux Leakage Signals Using Convolutional Neural Networks
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A Review of Magnetic Flux Leakage Nondestructive Testing
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Fast Estimation of Defect Profiles from the Magnetic Flux Leakage Signal Based on a Multi-Power Affine Projection Algorithm
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Theory and Application of Magnetic Flux Leakage Pipeline Detection
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Phase-Extraction-Based MFL Testing for Subsurface Defect in Ferromagnetic Steel Plate
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