Magnetic Flux Leakage Method Research Articles

Steel Wire Rope Damage Width Identification Method Based on Residual Networks and Multi-Channel Feature Fusion

In order to ensure the safety of steel wire rope in various application scenarios, it is particularly important to quantitatively detect the defects of wire rope. Complex detection conditions affect the detection efficiency of wire rope. Therefore, based on the magnetic flux leakage method, this study proposes a method to identify the damage width of steel wire rope for multi-channel fusion of a Hall sensor array. Firstly, the Hall sensor array is used to capture the magnetic flux leakage data of steel wire rope; then, continuous wavelet transform is used to decompose the original data, and moving average filtering is used to denoise each component; the denoised components are merged and converted into a time spectrum, and the time spectrum is classified by ResNet50 image classification model to realize the detection of wire rope damage width. According to the dataset used in this study, the results show that the proposed method performs best in the mainstream noise reduction model; detection accuracy for the width of damage in steel wire ropes is 97%, which proves that the proposed method is effective and feasible.

Magnetic characterisation of ferromagnetic material

In magnetic and electromagnetic non-destructive testing, the physical properties of the material are often not well known or completely unknown. The design of the non-destructive testing systems that provide the magnetisation is often oversized in order to get enough magnetic saturation (e.g. in magnetic flux leakage method or in magnetoscopy method). An improvement of the device performances, expressed usually by the signal to noise ratio, can be obtained only when the designer of the device well knows the material characteristic in terms of magnetic curve, the curve that links the magnetic field strengths to the magnetic flux density. A good device must be able to saturate the material sample under test but not to overcame determinate values. In fact, when the magnetisation is low, the leakage of the flux is negligible, while when the magnetisation is too strong the material tends to be like air and the leakage flux is negligible too. The experimental characterisation is derived from the technique adopted for the testing of soft magnetic material adopted in electrical machines or electromechanical actuators. In the present paper will be presented some material characterisation useful for the non-destructive testing of railway track, metallic ropes or reinforcement iron.

A novel sensor based on the composite mechanism of magnetic flux leakage and magnetic field disturbance for comprehensive inspection of defects with varying angles and widths

Ferromagnetic components are susceptible to various defects after prolonged service. The defects generated in these components are diverse and exhibit irregular orientation, which may impede comprehensive defect examination using a single magnetic testing method. This paper proposes a novel magnetic measurement sensor that integrates the principles of magnetic flux leakage (MFL) and magnetic field disturbance (MFD). The combined theory is analyzed and validated through the utilization of finite element method (FEM) simulations as well as experimental investigations. By comparing simulation results with experimental data, the composite nature of the signal acquired beneath a magnetic bridge is convincingly demonstrated. In comparison to conventional MFL and MFD methods, this innovative sensor exhibits superior defect detection performance for varying angles and widths, while also addressing some inherent limitations associated with MFL and MFD principles.

Application of magnetic flux leakage method in the crimping inspection of carbon fiber conductor

Compared with steel core aluminum strand wire, carbon fiber composite core wire has many excellent characteristics such as large flow capacity, good heat resistance, light weight, but its mechanical properties are poor, and the unqualified crimping quality is easy to lead to wire breakage accidents, which greatly affects its popularization. For this reason, a scheme for the detection of crimping defects of carbon fiber composite mandrel based on magnetic leakage method is proposed. Firstly, the finite element analysis model of the clamping fixture was established, and then the magnetic pole distance k and radial air gap n of the magnetic leakage testing device were explored. Based on the signal-to-noise ratio under the two typical defect conditions of fracture and low pressure, the most suitable excitation structure parameters of the magnetic leakage device were obtained. The results show that when k=55mm and n=3.5mm, the signal-to-noise ratio of MFL detection device reaches the best effect. The research results are of great significance to the quality inspection of compacts of carbon fiber composite mandrel.

Evaluation of Pipe Thickness by Magnetic Hammer Test with a Tunnel Magnetoresistive Sensor.

A new nondestructive inspection method, the magnetic hammer test (MHT), which uses a compact and highly sensitive tunnel magnetoresistance (TMR) sensor, is proposed. This method complements the magnetic flux leakage method and eliminates the issues of the hammer test. It can therefore detect weak magnetic fields generated by the natural vibration of a pipe with a high signal-to-noise ratio. In this study, several steel pipes with different wall thicknesses were measured using a TMR sensor to demonstrate the superiority of MHT. The results of the measurement show that wall thickness can be evaluated with the accuracy of several tens of microns from the change in the natural vibration frequency of the specimen pipe. The pipes were also inspected underwater using a waterproofed TMR sensor, which demonstrated an accuracy of less than 100 μm. The validity of these results was by simulating the shielding of magnetic fields and vibration of the pipes with the finite element method (FEM) analysis. The proposed noncontact, fast, and accurate method for thickness testing of long-distance pipes will contribute to unmanned, manpower-saving nondestructive testing (NDT) in the future.

Scope of applicability of the technique for constructing magnetic induction lines for flaw defectometry of extended objects

A technique for approximate solution of the inverse geometric problem of magnetostatics for a plate made of a soft magnetic ferromagnet in a magnetic field is presented. The technique is presented both for the case of the location of magnetic transducers directly above the surface defect of loss of continuity of the metal, and for the case in which the magnetic transducers are located above the defect-free surface of the plate. It is assumed that the plate is accessible from one side only. The sizes of defects in which the proposed technique works reliably are determined. It is shown that the proposed technique can be used in mobile devices to carry out flaw detection of drill pipes using the MFL (Magnetic flux leakage) method directly at drilling sites.

The homogeneity effects of magnetic flux density distribution on the detection of railhead surface defects via the magnetic flux leakage method

Magnetic flux leakage (MFL) is a non-destructive testing method used to detect railhead surface defects. For effective MFL testing, the homogeneity of the magnetic flux density distribution (MFDD) within the railhead is crucial. Inhomogeneous formation of the MFDD within the railhead reduces the efficiency of the MFL testing. The homogeneity of the MFDD depends on the distance between poles (DBP) of the MFL testing system. According to the literature, as the DBP parameter increases, the MFDD becomes more homogeneous. In this study, four different homogeneity levels of the MFDD are introduced based on the DBP parameter. 3D finite element method (FEM) modelling simulation is conducted to obtain MFL testing analyses. The analyses are performed on a rail that contains rectangular surface defects of varying depth and length. The results of this study are evaluated using characteristic features of the MFL signal BX component, namely the slope of the baseline, the bottom value and the peak-to-peak value. The results show that if the homogeneity level of the MFDD within the railhead is higher, the bottom value and slope of the baseline decrease and the peak-to-peak value increases. This indicates that higher homogeneity of the MFDD enhances the detection efficiency of the MFL testing. Eventually, it is found that with the formation of nearly 100% homogeneous MFDD in the railhead, the slope of the baseline, the bottom value and the peak-to-peak value are enhanced by up to 83%, 77% and 12%, respectively.

Circumferential Localization of a Crack in Cylindrical Ferromagnetic Rods Based on the Fourier Coefficients of the Radial Directional Magnetic Flux Leakage

In this paper, we present a novel magnetic flux leakage method to estimate the circumferential position of a crack in cylindrical ferromagnetic rods by modelling the crack as a magnetic dipole. The first-order Fourier coefficients of the radial component of the magnetic flux leakage are measured using two coils with widths proportional to | cos ϕ| and | sin ϕ|, where ϕ is the circumferential location of the rod surface. The circumferential and axial location of a crack is estimated using only two sensors, as demonstrated for an S45C cylindrical rod.

Using a magnetic flux leakage method to estimate railway track bolted joint gaps

The periodic estimation of the rail joint gap values allows evaluating the reliability of the continuous welded railway track and preventing its temperature deformations. The purpose of this study is to search for a simple and reliable way to evaluate the rail joint gap, which allows you to determine the desired values during high-speed inspection in automatic mode in a wide range of temperatures. A brief overview of existing techniques for evaluating rail joint gaps based on different physical principles is given. In the proposed technique, a magnetic flux leakage (MFL) method with the placement of electromagnets on the wheel axes of a car bogie is used. Such magnetization systems are applied recently on flaw-detector cars and provide a stable magnetic flux in the tested rails. Using a three-dimensional model of the rail segment with a bolt joint, we studied the characteristics of the magnetic flux leakage fields when changing the size of the rail gap in the entire practical range. The characteristics are selected that are most sensitive to a change in the gap and by which its value can be determined. With small values of the gaps the amplitude of the magnetic sensor signal is proposed as a main informative parameter, and with large gaps the estimation based on the distance between the signal extremums is more preferred. The results of computer modeling of the influence of the joint gap on the parameters of the magnetic signal qualitatively coincide with the results of field measurements made at inspection speeds up to 60 km/h.

Using a Magnetic Flux Leakage Method to Evaluate Gaps in Railroad Bolt Joints

Using a Magnetic Flux Leakage Method to Evaluate Gaps in Railroad Bolt Joints

A novel MFL detection method based on low frequency AC magnetization for identification defect

The reasons of structural failure of metal equipment are corrosion defects (Cdft) and stress defects (Sdft). But the sources and mechanisms of development of Cdft and Sdft are entirely different. The identification of Cdft and Sdft is a necessary prerequisite for the analysis of structural failures of metallic equipment. The magnetic domains move and rotate caused by Sdft and low frequency (f<30Hz) magnetic excitations. Both mechanical structural changes and magnetic excitation affect the magnetic domains. Under low frequency excitation conditions, the Cdft does not cause the magnetic domains to change. In this paper, an analysis of magnetic dipole density using magnetic domain variation and magnetic permeability variation is proposed. The low frequency alternating current magnetic flux leakage (ACMFL) method was used to identify Cdft and Sdft. The method combines the advantages of unsaturated excitation direct current magnetic flux leakage (DCMFL) and ACMFL with its low frequency characteristics. Simulations are used to determine the scanned surface signals. Multi-point and single-point experiments and as well as the corresponding simulations are used to verify the conclusions presented in this paper. In addition, this paper compares the difference between the proposed method and the DCMFL method using experiments, and also compares the difference between our proposed method and medium-high frequency ACMFL method.

Image Registration for Visualizing Magnetic Flux Leakage Testing under Different Orientations of Magnetization

The Magnetic Flux Leakage (MFL) visualization technique is widely used in the surface defect inspection of ferromagnetic materials. However, the information of the images detected through the MFL method is incomplete when the defect (especially for the cracks) is complex, and some information would be lost when magnetized unidirectionally. Then, the multidirectional magnetization method is proposed to fuse the images detected under different magnetization orientations. It causes a critical problem: the existing image registration methods cannot be applied to align the images because the images are different when detected under different magnetization orientations. This study presents a novel image registration method for MFL visualization to solve this problem. In order to evaluate the registration, and to fuse the information detected in different directions, the mutual information between the reference image and the MFL image calculated by the forward model is designed as a measure. Furthermore, Particle Swarm Optimization (PSO) is used to optimize the registration process. The comparative experimental results demonstrate that this method has a higher registration accuracy for the MFL images of complex cracks than the existing methods.

Train Wheel Magnetic Flux Leakage Testing Method Based on Local Magnetization Enhancement

Non-destructive testing (NDT) of train wheels fatigue cracks is a critical technology to ensure railway safety. Early fatigue cracks are small and difficult to detect. In this paper, the magnetic flux leakage (MFL) method is proposed to detect train fatigue cracks. The unsaturated magnetization state near the defect area is revealed through magnetic circuit analysis and finite element methods. As a result, leakage magnetic fields will decay sharply for small fatigue cracks, and they are difficult to detect by the traditional MFL method. To improve the magnetization state near defect areas, a novel MFL method based on local magnetization enhancement is proposed and developed. Experimental verification is also conducted by a train wheel NDT device. Testing results show that this method achieves excellent performance in the detection of defects in train wheels.

Determining the Effect of Velocity on Sensor Selection and Position in Non-Destructive Testing With Magnetic Flux Leakage Method: A Pipe Inspection Gauge Design Study With ANSYS Maxwell

Determining the Effect of Velocity on Sensor Selection and Position in Non-Destructive Testing With Magnetic Flux Leakage Method: A Pipe Inspection Gauge Design Study With ANSYS Maxwell

Application of Magnetic Flux Leakage (MFL) method to non-destructively characterize the microstructure and corrosion behaviour of API X65 grade steel

The goal of this research is to investigate the ability of the Magnetic Flux Leakage (MFL) method to characterize the microstructural features and corrosion performance of heat-treated API X65 grade steel in a non-destructive way. Various microstructures were created by austenitizing the specimens of API X65 steel at 950 °C for 45 min, followed by cooling in the furnace, air, oil, and water. SEM observations indicated that applying various heat-treating cycles led to three major microstructural changes in the ferrite phase, including volume fraction, grain size, and morphology. It was also found that an increase in cooling rate, increases the corrosion current density (icorr) obtained by the Potentiodynamic Polarization (PDP) test and decreases the charge transfer resistance (Rct) measured by Electrochemical Impedance Spectroscopy (EIS) technique. Furthermore, surface analysis of corroded samples showed that the higher ferrite (anode) to cementite (cathode) ratios in the furnace/air-cooled samples boost the corrosion performance, while uniform and localized corrosion have taken place on the oil and water quenched samples due to the higher density of dislocation and their acicular structure. Non-destructive evaluations indicated that microstructural changes as a result of various heat-treating cycles dramatically affect the magnetic permeability, which considerably influences the magnetic flux leaked from the surface and detected by the Hall effect sensor in the MFL method. Two MFL parameters, peak-to-peak amplitude, and slopes of the raw curves of the Hall sensor outputs at zero-crossing points were studied for the specimens. The results revealed good correlations between MFL parameters and values of icorr and Rct. Additionally, in this study, an “optimal range” has been proposed for the MFL outputs, which can be adjusted according to the required range of mechanical properties and corrosion behavior in the inspection process of API X65 steel specimens after heat treatment.

Experiment and simulation on testing steel plate with corrosion defects via magnetic flux leakage method

The testing of corrosion defects of steel components in engineering is critical to ensure the service safety of structures in civil engineering. Although some research of the corrosion of steel components using magnetic flux leakage (MFL) testing has been carried out, the quantitative evaluation of corrosion parameters has not been achieved due to the lack of quantitative analysis on the relationship between corrosion parameters (action zone, corrosion amount) and the MFL signal. In this paper, the steel plate is taken as the specimens of nondestructive testing. The MFL testing technology was used to measure the change laws of the MFL signal and its characteristic with under different lengths of the action zone and corrosion amount. The finite element simulation of the corrosion testing shows a good correlation with the MFL testing experiment. Combined with finite element simulation and experimental data, a detailed process for quantitative evaluation of the corrosion length and corrosion amount is established based on the corrosion signal characteristic. Based on the analysis of the signal characteristics measured by the experiment, it is confirmed that the evaluation accuracy of the corrosion amount of the steel plate can be guaranteed to be about 1.0 g, which demonstrates the feasibility of quantitative evaluation of corrosion parameters based on the MFL signal.

The Research of 30 mm Detecting Distance of Testing Device for Wire Rope Based on Open Magnetizer

Wire rope will have defects such as local faults (LF) and loss of metal area (LMA) during the long-term using process. The nondestructive testing method of magnetic flux leakage (MFL) has been widely used in wire rope defect detection. Currently, the detecting distance between magnetic sensors and wire rope with the MFL method is relatively small (2–5 mm). Considering the inner surface of the sensor head is close to the wire rope, it quickly leads to the sensor head scraping off the surface oil of the wire rope or being stuck by a cut wire in the course of MFL detection. Therefore, it is challenging to realize the sensor with MFL detection of wire rope obtaining the weak signal at a large lift-off (&gt;30 mm). This study used finite element analysis to verify if the MFL signal exists at the large lift-off (&gt;30 mm). Meanwhile, the sensor head was improved using an open magnetizer to make the wire rope reach saturation and excite enough magnetic leakage field. By combining magnetic sensing and coupling and a weak analog signal processing method, not only was the signal effectively detected, but also the signal-to-noise ratio (SNR) was improved. Finally, experiments verify the feasibility of detecting defects at a large distance. The method also has been applied in the high-speed detection of wire rope, which can detect broken wire of 1 mm diameter.

Research on the manufacture of equipment for detecting defects of disjointed, small diameter steel pipes by magnetic flux leakage method

This paper presents a design and pilot fabrication of the EMI (electromagnetic inspection) device to meet the requirements of non-destructive inspection of defects on straight, small diameter, variable drill pipes. The improved feature of this device is to replace the normal Hall sensor with the planar Hall sensor with high sensitivity, temperature and time stability to investigate the magnetic field variation caused by the variation of tube thickness. The test unit for detecting longitudinal defects has a new structure with a magnetic field that is magnetised along the circumference of the tube by an electromagnet. The magnetisation system and the test tube do not need to rotate during the measurement. The EMI equipment is expected to be tested at the Electromechanical Enterprise of Vietsovpetro.

Evaluation of defect depth in ferromagnetic materials via magnetic flux leakage method with a double Hall sensor

In the magnetic flux leakage (MFL) testing method, a linear mapping is used for the direct evaluation of defects by applying a single Hall sensor to measure the signal under a certain lift-off value. Inevitably, the uncertainty of the lift-off value in practical testing affects the accuracy of the estimated defect size. To overcome this uncertainty in the lift-off value, this paper proposes a double Hall sensor configuration with a fixed lift-off interval, and establishes an evaluation method for the defect depth through the MFL signals measured by this sensor. The effectiveness of the proposed evaluation method is verified by theoretical analysis, with the double Hall sensor providing two different lift-off values above the surface of the specimen that characterize the tested defect. Based on the error between the measured signal characteristics induced by the tested defect and the predicted values from a fast calculation model, a particle swarm optimization algorithm is employed to realize accurate evaluation of the defect depth. Theoretical research shows that the characteristic values measured by the double Hall sensor enable the defect depth to be accurately estimated. The use of a double Hall sensor with a fixed lift-off interval allows the proposed evaluation method to compensate for the unknown lift-off value in practical testing.

Crack identification system on MOH cold rolled grain oriented sheets: Application of K-fold cross validated BRANN

To increase efficiency of transformers, iron (hysteresis and Fuko losses), copper and abnormal losses must be prevented. Hysteresis loss may be significantly reduced by adding silicon to iron, and Fuko loss may be significantly reduced by using cold-rolled grain-oriented steel (CRGO) in the form of thin sheets with high resistance. To reduce abnormal losses, it is necessary not to use CRGO with ferromagnetic features including cracks in the core sequence. In line with this, currently, the magnetic flux leakage (MFL) method is commonly used to research cracks in ferromagnetic materials. Generally, literature studies researched the variation characteristics of MFL signals collected with magnetic sensors and size of amplitude values according to the physical properties (crack width, crack depth, etc.) of the crack in the ferromagnetic material. Different to the literature, our primary aim in this study is to determine this variation according to the type and geometric features of an artificial full crack with known physical properties created in MOH CRGO steel. The secondary aim of our study is to develop an artificial neural network predicting the type and geometric features of a full crack with unknown geometric features using the data obtained. In line with this, our study first produced an MFL measurement system. Then, artificial full crack samples were prepared with different types and geometric features using MOH CRGO steel. These artificial full crack samples were magnetized by being placed in the core of an electromagnet with 50 kHz AC signal and the surface of the material was scanned in a single dimension with a location-controlled fluxgate sensor. Harmonics of signals obtained from the fluxgate sensor were investigated with DSP lock-in amplifier and the amplitude values for the harmonics with greatest variation were uploaded to the computer. Finally, 3 different Bayesian regularized artificial neural networks (BRANN) were developed and trained using the harmonic amplitude values for full crack samples with known geometric features and used to predict the type and geometric features of full cracks with unknown geometric features. The first of these BRANN was used to identify the fixed or variable width of the full crack type, while the others were used to find the geometric features according to the full crack type. For the BRANNs trained with the K-fold cross-validation method, accuracy degrees of R = 0.99934, R = 0.99999 and R = 0.91654 were obtained, respectively. The trained BRANNs provided results compatible with reality for artificial full crack models with unknown crack type and geometric properties.