scholarly journals A Method for Detecting Surface Defects in Railhead by Magnetic Flux Leakage

2021 ◽  
Vol 11 (20) ◽  
pp. 9489
Author(s):  
Yinliang Jia ◽  
Shicheng Zhang ◽  
Ping Wang ◽  
Kailun Ji
Keyword(s):  
Magnetic Flux ◽  
Surface Defects ◽  
Rapid Development ◽  
Magnetic Flux Leakage ◽  
Detection Accuracy ◽  
Physical Experiments ◽  
Detection Technology ◽  
Element Simulation ◽  
Lift Off ◽  
Flux Leakage

With the rapid development of the world’s railways, rail is vital to ensure the safety of rail transit. This article focuses on the magnetic flux leakage (MFL) non-destructive detection technology of the surface defects in railhead. A Multi-sensors method is proposed. The main sensor and four auxiliary sensors are arranged in the detection direction. Firstly, the root mean square (RMS) of the x-component of the main sensor signal is calculated. In the data more significant than the threshold, the defects are determined by the relative values of the sensors signal. The optimal distances among these sensors are calculated to the size of a defect and the lift-off. From the finite element simulation and physical experiments, it is shown that this method can effectively suppress vibration interference and improve the detection accuracy of defects.

scholarly journals An Analytical Model for Prediction of Magnetic Flux Leakage from Surface Defects in Ferromagnetic Tubes

2016 ◽  
Vol 16 (1) ◽  
pp. 8-13 ◽  
Author(s):  
V. Suresh ◽  
A. Abudhahir
Keyword(s):  
Magnetic Flux ◽  
Analytical Model ◽  
Surface Defects ◽  
Experimental Results ◽  
Magnetic Flux Leakage ◽  
Analytical Expression ◽  
Cylindrical Holes ◽  
Lift Off ◽  
Flux Leakage ◽  
Good Agreement

Abstract In this paper, an analytical model is proposed to predict magnetic flux leakage (MFL) signals from the surface defects in ferromagnetic tubes. The analytical expression consists of elliptic integrals of first kind based on the magnetic dipole model. The radial (Bz) component of leakage fields is computed from the cylindrical holes in ferromagnetic tubes. The effectiveness of the model has been studied by analyzing MFL signals as a function of the defect parameters and lift-off. The model predicted results are verified with experimental results and a good agreement is observed between the analytical and the experimental results. This analytical expression could be used for quick prediction of MFL signals and also input data for defect reconstructions in inverse MFL problem.

scholarly journals Research on the Method of Predicting Corrosion width of Cables Based on the Spontaneous Magnetic Flux Leakage

Materials ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2154 ◽  
Author(s):  
Yinghao Qu ◽  
Hong Zhang ◽  
Ruiqiang Zhao ◽  
Leng Liao ◽  
Yi Zhou
Keyword(s):  
Magnetic Flux ◽  
Safety Assessment ◽  
Steel Wire ◽  
Safety Performance ◽  
Magnetic Flux Leakage ◽  
Detection Accuracy ◽  
Lift Off ◽  
Point Distance ◽  
Flux Component ◽  
Flux Leakage

The detection of cable corrosion is of great significance to the evaluation of cable safety performance. Based on the principle of spontaneous magnetic flux leakage (SMFL), a new method for predicting the corrosion width of cables is proposed. In this paper, in order to quantify the width of corrosion, the parameter about intersecting point distance between curves of magnetic flux component of x direction at different lift off heights (Dx) is proposed by establishing the theoretical model of the magnetic dipole of the rectangular corrosion defect. The MATLAB software was used to analyze the influencing factors of Dx. The results indicate that there exists an obvious linear relationship between the Dx and the y (lift off height), and the Dx–y curves converge to near the true corrosion width when y = 0. The 1/4 and 3/4 quantiles of the Dx–y image were used for linear fitting, which the intercept of the fitting equation was used to represent the predicted corrosion width. After the experimental study on the corrosion width detection for the parallel steel wire and steel strand, it is found that this method can effectively improve the detection accuracy, which plays an important role in cable safety assessment.

Experimental Study of the Influencing Factors of Elevator Cable Magnetic Flux Leakage Detection Signal

2013 ◽  
Vol 711 ◽  
pp. 327-332
Author(s):  
Yi Su ◽  
Zhen Zhang ◽  
Tao Zhang ◽  
Ming Li Yang ◽  
Mei Lin ◽  
...  
Keyword(s):  
Magnetic Flux ◽  
Magnetic Flux Leakage ◽  
Probe Design ◽  
Détection Signal ◽  
Detection Mechanism ◽  
Fracture Width ◽  
Lift Off ◽  
Elevator Cable ◽  
Flux Leakage ◽  
Detection Signal

The detection mechanism of Magnetic Flux Leakage (MFL) Method of elevator cable is proposed. Using Gauss-Mercury method to analyze the influence of different factors that lift-off value, fracture width, broken wires number and diameter and depth all that based on the collecting experimental system of MFL signals. The method can be used to optimize the detection probe design and detection signal processing.

Practical evaluation of velocity effects on the magnetic flux leakage technique for storage tank inspection

2020 ◽  
Vol 62 (2) ◽  
pp. 73-80
Author(s):  
A L Pullen ◽  
P C Charlton ◽  
N R Pearson ◽  
N J Whitehead
Keyword(s):  
Magnetic Flux ◽  
Storage Tank ◽  
Eddy Currents ◽  
Surface Defects ◽  
Signal Amplitude ◽  
Magnetic Flux Leakage ◽  
Scanning Velocity ◽  
Near Surface ◽  
Practical Evaluation ◽  
Flux Leakage

Magnetic flux leakage (MFL) is a technique commonly used to inspect storage tank floors. This paper describes a practical evaluation of the effect of scanning velocity on defect detection in mild steel plates with thicknesses of 6 mm, 12 mm and 16 mm using a fixed permanent magnetic yoke. Each plate includes four semi-spherical defects ranging from 20% to 80% through-wall thickness. It was found that scanning velocity has a direct effect on defect characterisation due to the distorted magnetic field resulting from induced eddy currents that affect the MFL signal amplitude. This occurs when the inspection velocity is increased and a reduction in the MFL signal amplitudes is observed for far-surface defects. The opposite applies for the top surface, where an increase is seen for near-surface MFL amplitudes when there is insufficient flux saturating the inspection material due to the concentration of induced flux near the top surface. These findings suggest that procedures should be altered to minimise these effects based on inspection requirements. For thicker plates and when far-surface defects are of interest, inspection speeds should be reduced. If only near-surface defects are being considered then increased speeds can be used, provided that the sensor range is sufficient to cope with the increased signal amplitudes so that signal clipping does not become an issue.

scholarly journals A Lift-Off-Tolerant Magnetic Flux Leakage Testing Method for Drill Pipes at Wellhead

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 201 ◽  
Author(s):  
Jianbo Wu ◽  
Hui Fang ◽  
Long Li ◽  
Jie Wang ◽  
Xiaoming Huang ◽  
...  
Keyword(s):  
Magnetic Flux ◽  
Magnetic Flux Leakage ◽  
Testing Method ◽  
Drill Pipes ◽  
Lift Off ◽  
Flux Leakage ◽  
Magnetic Flux Leakage Testing

Tsallis Entropy Segmentation and Shape Feature-based Classification of Defects in the Simulated Magnetic Flux Leakage Images of Steam Generator Tubes

2019 ◽  
Vol 34 (01) ◽  
pp. 2054002
Author(s):  
Jackson Daniel ◽  
A. Abudhahir ◽  
J. Janet Paulin
Keyword(s):  
Magnetic Flux ◽  
Steam Generator ◽  
Defect Detection ◽  
Performance Metrics ◽  
Tsallis Entropy ◽  
Magnetic Flux Leakage ◽  
Equivalent Diameter ◽  
Detection Accuracy ◽  
Back Propagation Algorithm ◽  
Flux Leakage

Early detection of water or steam leaks into sodium in the steam generator units of nuclear reactors is an important requirement from safety and economic considerations. Automated defect detection and classification algorithm for categorizing the defects in the steam generator tube (SGT) of nuclear power plants using magnetic flux leakage (MFL) technique has been developed. MFL detection is one of the most prevalent methods of pipeline inspection. Comsol 4.3a, a multiphysics modeling software has been used to obtain the simulated MFL defect images. Different thresholding methods are applied to segment the defect images. Performance metrics have been computed to identify the better segmentation technique. Shape-based feature sets such as area, perimeter, equivalent diameter, roundness, bounding box, circularity ratio and eccentricity for defect have been extracted as features for defect detection and classification. A feed forward neural network has been constructed and trained using a back-propagation algorithm. The shape features extracted from Tsallis entropy-based segmented MFL images have been used as inputs for training and recognizing shapes. The proposed method with Tsallis entropy segmentation and shape-based feature set has yielded the promising results with detection accuracy of 100% and average classification accuracy of 96.11%.

A novel magnetic flux leakage method based on the ferromagnetic lift-off layer with through groove

2021 ◽  
Vol 332 ◽  
pp. 113091
Author(s):  
Jian Tang ◽  
Rongbiao Wang ◽  
Bocheng Liu ◽  
Yihua Kang
Keyword(s):  
Magnetic Flux ◽  
Magnetic Flux Leakage ◽  
Lift Off ◽  
Flux Leakage
Sign in / Sign up

Export Citation Format

Share Document