ReviewMaterials (Basel, Switzerland)2022
A Review of Magnetic Flux Leakage Nondestructive Testing.
Review in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Identification of Roll Defect or Damage Based on Rayleigh Waves and Deep Convolutional Neural Network Models.Materials (Basel, Switzerland) · 2026Article
- Detection and Analysis of Conveyor Belt Damage: A Review of Sensing Technologies and Signal-Based Approaches.Sensors (Basel, Switzerland) · 2026Review
- Eddy-Current-Induced Waveform Reconstruction by Metallic Probe Carriers in Magnetic Flux Leakage Inspection.Sensors (Basel, Switzerland) · 2026Article
- Evolution Mechanism and High-Precision Quantitative Identification of MFL Signals from Defects Under Supersaturated Magnetization Conditions.Sensors (Basel, Switzerland) · 2026Article
- A structure-preserving diffusion-based zero-shot learning framework for multimodal magnetic flux leakage signal analysis.Scientific reports · 2026Article
- Magnetic Induction Sensing of Corrosion on Steel Pipes: Feasibility, Instrument Design and First Test Results.Sensors (Basel, Switzerland) · 2026Article
- An improved YOLO11 network integrated with sample generation for the intelligent detection of steel plate surface defects.PloS one · 2026Article
- Effect of Sensor Head Orientation on the Accuracy of Magnetic Defect Detection in Steel-Cord Conveyor Belts.Sensors (Basel, Switzerland) · 2025Article
- A contribution to reliable rail transport: AI-powered real-time wheel defect detection.Scientific reports · 2025Article
- Recent Advances in Non-Destructive Testing Technology for Coated Steel Structure Welds.Sensors (Basel, Switzerland) · 2025Review
- Advances and challenges in oil and gas pipeline pigging technology: a comprehensive review.Scientific reports · 2025Article
- Research on Nondestructive Testing Method Based on Magnetic Characteristics of Electron Beam Weld Defects.Sensors (Basel, Switzerland) · 2025Article
- A Novel Defect Quantification Method Utilizing Multi-Sensor Magnetic Flux Leakage Signal Fusion.Sensors (Basel, Switzerland) · 2024Article
- Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review.Sensors (Basel, Switzerland) · 2024Review
- Study on the Impact of Pole Spacing on Magnetic Flux Leakage Detection under Oversaturated Magnetization.Sensors (Basel, Switzerland) · 2024Article
- Deep Learning Approach for Pitting Corrosion Detection in Gas Pipelines.Sensors (Basel, Switzerland) · 2024Article
- A Novel Defect Detection Method for Overhead Ground Wire.Sensors (Basel, Switzerland) · 2023Article
- Use of Different Types of Magnetic Field Sensors in Diagnosing the State of Ferromagnetic Elements Based on Residual Magnetic Field Measurements.Sensors (Basel, Switzerland) · 2023Article
- Detection of Rail Defects Using NDT Methods.Sensors (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Magnetic flux leakage (MFL) testing is a widely used nondestructive testing (NDT) method for the inspection of ferromagnetic materials. This review paper presents the basic principles of MFL testing and summarizes the recent advances in MFL. An analytical expression for the leakage magnetic field based on the 3D magnetic dipole model is provided. Based on the model, the effects of defect size, defect orientation, and liftoff distance have been analyzed. Other influencing factors, such as magnetization strength, testing speed, surface roughness, and stress, have also been introduced. As the most important steps of MFL, the excitation method (a permanent magnet, DC, AC, pulsed) and sensing methods (Hall element, GMR, TMR, etc.), have been introduced in detail. Finally, the algorithms for the quantification of defects and the applications of MFL have been introduced.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.