Metal Magnetic Memory Research Articles

Crack propagation characterization and statistical evaluation of fatigue life for locally corroded bridge steel based on metal magnetic memory method

Corrosion has a great endangerment for the fatigue performance of bridge steel members. As a newly developed self-magnetic leakage (SMFL) nondestructive testing (NDT) technique, metal magnetic memory (MMM) is regarded as a potential and feasible approach for examining fatigue damage of ferromagnetic material. Thus, the tension-tension high cycle fatigue (HCF) tests for the Q345qD bridge steel sheet specimens with local corrosion were carried out in this paper, and the normal component HSF(y) of SMFL field on the surface of specimens were investigated innovatively via MMM method. The experimental results show that the mutational crest (or trough) and the crest-trough (or trough-crest) behavior on the curves of HSF(y) signal and its gradient K can accurately indicate the range of corroded region and locate fatigue crack position. Then, the significant experimental correlations between magnetic characteristic parameters and crack size were demonstrated. The maximum value (or the minimum value) Km and the crest area Ka of the gradient curve can be utilized for the comprehensive characterization of crack initiation and propagation in the corroded region. Comparing with the experimental correlations proved that the established improved magnetic dipole models were reliable to simulate the variation of HSF(y) signal at the corroded region before and after cracking. Finally, based on the naive Bayesian model, the statistical evaluation of normalized fatigue life for corroded bridge steel was realized by classification via magnetic characteristic parameter. This research will serve as a base for future studies of fatigue crack detection and fatigue life estimation on the corroded bridge steel component based on MMM method.

Measurements of the Magnetic Field Variations Related with the Size of V-Shaped Notches in Steel Pipes

Gas and oil pipeline networks require periodic inspections to detect cracks or notches that can cause industrial accidents and environmental contamination. For these inspections, the metal magnetic memory (MMM) method could be used as a non-destructive testing (NDT) technique, which does not need expensive equipment and high-skilled operators. However, more investigations are required to quantify the size and shape of defects in ferromagnetic pipes using the MMM signals. We present experimental measurements of MMM signals around five small V-shaped notches of an ASTM-A36 steel pipe using a three-axis magnetoresistive sensor. The V-shaped notches have different values of depth (500 µm, 1000 µm, 1500 µm, 2000 µm and 2500 µm) and width (1000 µm, 1500 µm, 2000 µm, 3000 µm and 3500 µm). We measured the variations of tangential and normal MMM signals around these defects and their relationships with the size of each defect. The first V-notch defect (500 μm depth and 1000 μm width) registers variations of the tangential and normal MMM signals of 14.32 μT ± 1.62 μT and 27.95 μT ± 1.14 μT, respectively. On the other hand, the fifth V-notch defect (2500 μm depth and 3500 μm width) has variations of the tangential and normal MMM signals of 68.75 μT ± 1.10 μT and 71.37 μT ± 0.72 μT, respectively. The MMM method could be used for real-time monitoring of V-shaped notches in steel pipes. This method does not require special treatment of steel pipes.

Corrosion non-destructive testing of loaded steel strand based on self-magnetic flux leakage effect

ABSTRACT The metal magnetic memory is used to detect the micro damage of structure based on the SMFL (self-magnetic flux leakage) effect, but it lacks an effective comprehensive diagnosis index suitable for the ferromagnetic material. In this paper, steel strand specimens were tensioned at different force levels, and the experimental study on the corrosion detection was carried out. Besides the monitoring analysis of the cable force, the initial structural magnetic field ΔBx 0 and the surface SMFL signals Bx (α) induced by corrosion were both analysed. The results show that ΔBx 0 curves of steel strand material present the periodic fluctuation. Considering ΔBx 0 and measuring distance z, the proposed dimensionless damage analysis index X can be used for the quantitative research of corrosion diagnosis. The small influence of the cable force on index X is also illustrated. Moreover, the strong correlation that exists between the average maximum index and the corrosion ratio α is well fitted by the three-order polynomial curves.

Diagnostics of Reinforcement Conditions in Concrete Structures by GPR, Impact-Echo Method and Metal Magnetic Memory Method

It is important to use adequately reliable non-destructive methods that would be capable of determining the reinforcement conditions in concrete structures. Three different methods: ground penetrating radar, impact-echo method, and metal magnetic memory method were used for testing laboratory-prepared reinforced concrete beams (with a reinforcing bar of the same diameter along its whole length, reinforcing bar locally impaired, and reinforcing bar interrupted). The ground-penetrating radar proved the correlation of signal parameters with the reinforcing bar condition. An impairment/interruption reinforcing bar appeared in the record from measurements in the transversal and longitudinal direction by changes of the observed depth of the reinforcing bar from the concrete surface and direct wave attenuation. The impact-echo method proved that the shifts of the dominant frequencies from the response signal correspond with the impairment/interruption of the reinforcing bar. Results of diagnostics by the metal magnetic memory method were presented by a magnetogram of the magnetic field strength and field gradient on the measured distance. The changes in the magnetic field strength proved different stress concentration zones due to the reinforcing bar condition. The used non-destructive methods showed that they are capable of indicating the different reinforcement conditions in reinforced concrete beams. This paper indicates in which cases and for what reason it is appropriate to use these three methods and in what way they differ from each other.

Characterisation of Steel Components Fatigue Life Phenomenon Based on Magnetic Flux Leakage Parameters

The metal magnetic memory (MMM) method is highly effective in assessing the extent of early damage, such as fatigue crack in ferromagnetic components due to the existence of stress concentration zones (SCZs). However, there are limited studies on the relationship between the magnetic signal parameter in predicting the fatigue life of ferromagnetic components. With the advent of information relating to fatigue life, the risk of failure of a component can be reduced, if not avoided. Therefore, this study was conducted using the MMM method to establish a relationship between the magnetic signal parameters in the SCZ with fatigue characteristics in predicting the fatigue life of the specimen. A cyclic test was conducted on SAE 1045 steel specimens using a constant amplitude tension–compression stress with a stress ratio of −1. To investigate the effect of load value on the fatigue life of the specimens, seven percentage values of ultimate tensile strength (UTS) were used: 50%, 55%, 60%, 65%, 70%, 75%, and 80%. During the fatigue crack growth test, the MMM sensor was used to scan the magnetic signal data. Then, the data were analysed using the MMM Lifetime 2.0 software to obtain the fatigue life. Correlation graphs were plotted to determine the relationship between the MMM Lifetime 2.0 residual life and experimental residual life. The experimental results show that the distribution of magnetic signals was affected by the number of cycles and measurement line. As the number of cycles increased, the magnetic signal changes were more noticeable. For the measurement line, when the line was located near the crack initiation point, the magnetic signal distribution became clearer due to the presence of the SCZ. The evaluation of the maximum gradient, Kmax, variation also helped to assess the level of fatigue life based on the three stages of fatigue crack formation. Whereas, for the fatigue life assessment, the second measurement line (L2) and a contraction value of 0.7 were found to be suitable for predicting the fatigue life of specimens using MMM Lifetime 2.0 software. The experimental fatigue life and MMM Lifetime 2.0 fatigue life distribution of both parameters were in the two-factor range with the correlation coefficient, R2 of 0.9983. As such, the fatigue prediction results were acceptable. Accordingly, this study has demonstrated that the MMM method can be used to predict the remaining life of ferromagnetic components if the right parameters are used.

Quantitative Study of MMM Signal Features for Internal Weld Crack Detection in Long-Distance Oil and Gas Pipelines

The metal magnetic memory (MMM) inspection technology is an effective method to detect the stress damage of ferromagnetic materials, and it especially possesses great application potential in the field of long-distance oil and gas pipeline weld crack detection. In order to study the MMM generation mechanism and the signal feature of weld cracks, a model to quantitatively calculate the MMM signal of nonuniform magnetic charge of internal inspection is proposed. The effect of changes to the crack depth, the crack width, and the pipeline internal pressure on the MMM signal is studied, and the theoretical results have been proved by extensive experimental studies. The results indicate that the axial component has only one peak value, while the radial component has two pairs of independent and zero-crossing peak-to-peak values, of which the outside pair corresponds to the weld and the inside pair corresponds to the crack. The feature values change nonlinearly with the crack depth, and the growth rate decreases gradually. The feature values increase linearly with the crack width, and the radial component is more sensitive to width than the axial component. The internal pressure will increase the stress concentration around the weld and the crack, but the stress around the crack responds more sensitively. Therefore, the MMM signal is positively correlated with the internal pressure, and the feature value will increase linearly.

Analytical solution of magneto-mechanical magnetic dipole model for metal magnetic memory method

Magnetic dipole theory has been widely and successfully used to explain the leakage magnetic field signals. Because the model parameter such as magnetic dipole density is not easy to quantify, magnetic dipole theory often needs normalizing in application, which is considered to be unsuitable for quantitatively analyzing the magnetic memory signals with the stress effect. In this paper, the theoretical model of magneto-mechanical coupling magnetic dipole is established, which is suitable for analyzing the stress effect on magnetic signals in magnetic memory testing method. Based on the ferromagnetic theory, the equivalent field under the combined action of the applied load and the magnetic field is determined. And then, the magneto-mechanical analytical model is obtained for the isotropic ferromagnetic material under the weak magnetic field based on the first-order magnetization approximation in the weak magnetization state. Under the assumptions of rectangular and V-shaped magnetic charge distribution for the two-dimensional magnetic signal problem, the theoretical analytical models of the magnetic memory signals from the smooth and cracked specimens, and the analytical models of the magnetic memory signal induced by the rectangular and V-shaped surface defect are established. Based on the analytical solution of the proposed magneto-mechanical magnetic dipole theory, the difference in signal between before and after the failure of the specimen, the signal from the rectangular and V-shaped defect, and other influencing factors and laws of the magnetic signal are analyzed in detail. In particular, the influence of stress, environmental magnetic field, defect morphology and size, lift-off effect, specimen size and other factors on magnetic memory signals can be described based on the analytical solution of magneto-mechanical magnetic dipole models proposed in this paper. The proposed analytical model of magneto-mechanical magnetic dipole in this paper is simple and easy to use, and the present research shows that the proposed analytical solution in this paper can explain some basic experimental phenomena and laws in magnetic memory testing experiments. In addition, the precise magneto-mechanical coupling quantitative model combined with the finite element analysis method is still needed for accurately analyzing the magnetic memory signals in experiment.

Research on Denoising Method of Metal Magnetic Memory Signal

As the main transportation mode of oil and gas, oil and gas pipelines play an irreplaceable role in energy transportation. Metal magnetic memory detection technology can detect early stress concentration and invisible damage, and can be detected under the action of the geomagnetic field, without the need to magnetize the pipeline in advance. Since the magnetic memory signal is relatively weak, the actual detected signal will be affected by environmental noise, sensor jitter, and pipeline surface deposits. Therefore, the magnetic memory signal needs to be denoised. In this paper, the translation invariant wavelet denoising method, which is improved based on wavelet threshold denoising method, is used to denoise the collected pipeline magnetic memory signals. The experimental results show that the signal-to-noise ratio (SNR) obtained by this method is 4.97 % higher than the unmodified wavelet threshold denoising, and 3.18 % higher than the SNR obtained by the particle swarm optimization wavelet threshold denoising.

USE OF A ROLLED DEEP NEURAL NETWORK TO DETERMINE THE CHANGE OF THE STRESSED AND DEFORMED STATE OF VERTICAL STEEL CYLINDERAL TANKS BY THE MOVEMENT OF THEIR SURFACE

The main place in determining the mechanical characteristics of the RVS material is occupied by methods and means of VAT control, which include the method of coercive force; magnetic anisotropy method; Barkhausen method, magnetic metal memory (MPM) method, strain gauge method. The advantages of magnetic methods are the ability to control without decommissioning the RVS, safety. The disadvantages inherent in almost all magnetic control methods include the need to prepare the controlled surface, the difficulty of determining the position of the sensors in relation to the maximum loads, the dependence of control results on methods and conditions of measurement, the influence of the air layer between the sensor and the controlled surface.It's shown that to determine the further safe operation possibility of vertical steel cylindrical tank it is necessary to know their stress-strain state. The shortcomings of the existing experimental and mathematical methods of its estimation were highlighted. It's proposed to use a convolutional deep neural network to determine the stress state of a vertical steel cylindrical tank. As input data, it's proposed to use data on the movement of its wall obtained, for example, as a result of geometric calibration at two points in time. The input data was presented in the form of an array of dimensions 8x12, then used convolution and max-pulling. The last layer is fully connected. It's proposed to use cross-entropy as a cost function. To increase the amount of training data, it is proposed to use the values of displacements on stresses obtained by modeling different effects on a cylindrical tank with different shape defects using the SolidWorks package. Possible ways to improve the proposed method are proposed.For further research and improvement of the proposed method, you can try to use other hyper parameters in the neural network, in particular to change the number of feature maps, the size of the local receptive field, the size of the shift step of the receptive field and others.You can also try using the source layer with a different number of neurons and softmax as a function of cost.

Investigation of the Impact of Load on the Magnetic Field Strength of the Crane by the Magnetic Metal Memory Technique.

The paper deals with the problem of applicability of the metal magnetic memory (MMM) technique in the crane structural inspection and monitoring. The MMM method does not require the external magnetization of a structure that results in reduction of downtime of maintenance operations. Measurement of the intensity of the self-magnetic leakage signal can be an alternative to other non-destructive methods used for inspection of a large crane’s structure and equipment. However, the complexity of the residual magnetization effect in the MMM technique is the problem with its application. Thus, the magnetic flux leakage behavior on the crane girder surface under different measurements and the crane’s load conditions is analyzed based on the results obtained during experiments carried out on the overhead traveling crane.

Application of Metal Magnetic Memory Testing for Quantitative Evaluation of Stress Concentration in Ferromagnetic Steels

The objective of this research is to develop a quantitative algorithm between the magnetic parameter bm and the stress concentration factor in ferromagnetic steels. Specimens of U71Mn steel were machined into smooth plates with artificial defects (circular holes and rectangular holes) to represent various stress concentration degrees. Variations of the magnetic parameter bm with the stress concentration factor and the defect area were studied, respectively. The magnetic parameter bm of the U71Mn steel specimen was compared with that of the X80 steel specimen. Quantitative correlations of the magnetic parameter bm with the stress concentration factor and the defect area were investigated. The results show that the magnetic parameter bm is exponentially varied to the stress concentration factor and the defect area. The quantitative algorithm between the magnetic parameter bm and the stress concentration factor is influenced by the defect shape and the material type. An equation was proposed to evaluate the defect area based on the magnetic parameter bm.

A dual-dipole model for stress concentration evaluation based on magnetic scalar potential analysis

Experiment shows that the normal component and the amplitude of the spontaneous magnetic signals on the surface of the ferromagnetic part, induced by a stress concentration zone (SCZ) caused by local plastic deformation, have only one peak. These waveform characteristics are precisely opposite of the defect identification criteria proposed by the metal magnetic memory (MMM) method, which include that the normal component of magnetic signals changes to its polarity and the tangential component reaches a peak value. At the beginning, a magnetic dual-dipole model is accordingly proposed to describe and evaluate the stress concentration in ferromagnetic materials. The contour maps of the magnetic scalar potential show that there is a magnetic source generated in the damaged area. This source can be simplified as a dual-dipole. It comes from the two peaks of stress variation at the edges of the SCZ. Furthermore, the maximum potential of magnetic anomalies was obtained. The values are influenced by the applied loading and deflection of the specimen. It decays exponentially with the increase of lift-off values in the air domain. Finally, residual stresses along the scanning line were measured to confirm the theoretical analysis. This dual-dipole model in the MMM technique is feasible to evaluate the stress concentration caused by local plastic deformation.

Study on the early fatigue damage evaluation of high strength steel by using three components of metal magnetic memory signal

In this paper, the early fatigue damage evaluation of high strength steel was discussed. By using CH-3600 Gauss meter and three channel metal magnetic memory probe, the three components of MMM signal, including Bx, By and Bz signals, were collected, and a non-ferromagnetic three-dimensional platform was employed. Based on the high cycle fatigue test, the Bx, By and Bz signals, corresponding to different fatigue cycles, were collected. The results show that the lift-off of probe is important for the characteristic parameter of Bx, By and Bz signals (defining Bxave, Byave and Kz, respectively), as lift-off of probe increases, the characteristic parameter decreases fast and tends to be stable gradually. As fatigue cycle increases, the changes on Bxave, Byave and Kz are very similar, but compared with Byave, the Bxave and Kz change more smoothly and are more suitable for evaluating the early fatigue damage. As fatigue stress increases gradually, the values of Bxave-2 and Kz-2 increases linearly. At last, the experimental results are explained on the base of grain slip and magnetostriction effect, and the interaction of magnetic domain, dislocation and the internal stress is considered to be as the main reason for the change of Bxave and Kz.

Effect of tensile stress on metal magnetic memory signals during on-line measurement in ferromagnetic steel

Metal magnetic memory testing (MMMT) is a promising nondestructive technique for early damage evaluation of ferromagnetic materials due to its high sensitivity to the stress state. An experimental investigation of the effect of axial applied stress on MMMT signals, both the normal component Bz and the tangential component Bx, under on-line loaded and unloaded measurement condition has been carried out during the whole tensile test in 0.45%C steel. In the elastic deformation stage, Bz signal kept rotating counterclockwise while Bx signal kept moving upward under on-line measurement both when loaded and unloaded, but the MMMT signals measured unloaded tended to resume the initial state compared those measured loaded. In the plastic deformation stage, Bz signal rotated clockwise while Bx signal moved downward under on-line loaded measurement with the increase of tensile stress, while the MMMT signals measured unloaded reversed compared those measured loaded. The results of the present work indicate that MMMT is a feasible solution for stress state on-line monitoring of ferromagnetic components.

Application of Metal Magnetic Memory Testing Technology to the Detection of Stress Corrosion Defect

The damage of equipment manufactured with ferromagnetic materials in service can be effectively detected by Metal Magnetic Memory Testing (MMMT) technology, which has received extensive attention in various industry fields. The effect of stress or strain on Magnetic Flux Leakage (MFL) signals of ferromagnetic materials has been researched by many scholars for assessing stress concentration and fatigue damage. However, there is still a lack of research on the detection of stress corrosion damage of ferromagnetic materials by MMMT technology. In this paper, the electrochemical corrosion system was designed for corrosion experiments, and three different experiments were performed to study the effect of corrosion on MFL signals. The distribution of MFL signals on the surface of the specimen was investigated. The results indicated that both the normal component Hn and tangential component Ht of MFL signals presented different signal characteristics when the specimen was subjected to different working conditions. Finally, two characterization parameters, Sn and St, were defined to evaluate the corrosion degree of the specimen, and St is better. The direct dependence of corrosion depth on the parameter was developed and the average error rates between the predicted and measured values are 8.94% under the same working condition. Therefore, the expression can be used to evaluate the corrosion degree of the specimen quantitatively. The results are significant for detecting and assessing the corrosion defect of ferromagnetic materials.

Comprehensive inspection of refrigerated ammonia storage tank welded joints by the metal magnetic memory technique and conventional NDT methods

Refrigerated ammonia storage tanks (RAST) are hazardous industrial facilities, where accidents with severe consequences occur. Defects of welded joints are one of the main reasons of RAST accident occurrence. Due to this, during the technical inspection, special attention is paid to quality control of welded joints. The use of non-destructive testing (NDT) for defect detection is essentially important as it can be used to assess the integrity of such critical steel structures as storage tanks. Among the several NDT techniques available, acoustic emission (AE) can supply valuable information assessing structural integrity, detecting flaws and leaks in base metal and welded joint. However, assessing structural integrity usually includes other NDT techniques (e.g., visual examination, ultrasonic testing, dye penetrant test) additionally to AE, providing complementarity between different NDT techniques. Nevertheless, conventional NDT methods are aimed at detecting only the defects that occurred during manufacturing and operation and do not assume stress-strained state (SSS) assessment. The metal magnetic memory (MMM) technique is a passive magnetic one that is recommended to be applied for SSS assessment in accordance with guidance documents. A flaw detectability relation between UT and MMM techniques is observed.

Study on the characteristics of metal magnetic memory signal of X70 pipeline steel

In view of the zero crossing phenomenon of the normal component of the magnetic memory signal on the surface of the ferromagnetic component in the crack or stress concentration, many scholars have disputes about it. In this paper, through the simulation of the crack by wire cutting, the normal component of the magnetic leakage signal on the surface of the pipeline component is stretched on the tensile testing machine, and the normal component of the magnetic memory signal on the surface of the pipeline component is analyzed. It is found that the zero crossing phenomenon does exist in the normal component of the crack, but the zero crossing occurs with the pulling when the load increases to a certain extent, it will not drift after passing the zero point. The results show that the normal component cannot be used to judge the crack or stress concentration simply.

Study of the structure and mechanical properties of engineering products made of austenitic-martensitic steel, using the metal magnetic memory technique

Spontaneous phase transformation in local areas of the austenitic microstructure to martensite with the release of carbides may appear during the manufacturing or operation of engineering products made of two-phase austenitic-martensitic steel grades. When inspecting the quality of products made of these steels, the problem of detecting the local zones of the martensitic phase and carbide precipitation in the product metal arises. The article presents the results of an inspection by means of the metal magnetic memory (MMM) technique of centrifugal compressor impellers made of austenitic-martensitic steel 07Cr16Ni6. It was demonstrated that in the areas of stray field indications detected by means of the MMM technique, strength properties deteriorate, the metal structure degrades with abrupt changing of the metal phase composition and a carbide network formation, unacceptable δ-ferrite, was detected in the structure, and micro- and macro-cracks were found.

Magneto-mechanical coupling model of ferromagnetic materials under fatigue loading and its application in metal magnetic memory method

Fatigue damage of materials is generally evaluated by the degree of degradation of mechanical properties under fatigue loading. Existing experiments show that fatigue damage of ferromagnetic materials can also be evaluated utilizing changes in magnetization, but the quantitative relationship between magnetization changes and fatigue damage is still unclear. In this paper, a nonlinear magneto-mechanical coupling constitutive relation for ferromagnetic materials under fatigue loading is established based on the local equilibrium state of magnetization and the stress-strain response relationship in classical fatigue theory. The magnetic induction intensity of the ferromagnetic materials predicted by the present model increases with the number of cyclic loadings, and then tends to stabilize and finally increase rapidly, which is consistent with the existing experimental results. The model can also predict the evolution of complex magneto-mechanical coupling behavior under different loading times. In addition, the relationship between the evolution of spontaneous magnetic field (SMF) and fatigue damage for ferromagnetic materials is discussed in details. These results are helpful to understand the magneto-mechanical coupling behavior of ferromagnetic materials during fatigue damage process and also have important significance for the fatigue damage monitoring in practical engineering.

Metal magnetic memory inspection of Q345B steel beam in four point bending fatigue test

The metal magnetic memory (MMM) method is a nondestructive testing method to inspect the early damage of steel structures. A four-point bending fatigue beam was inspected by this method during the whole fatigue life. The self-magnetic-leakage field (SMLF) values were measured during the test of the Q345B steel beam. Frequency of 3 Hz and stress ratio of 0.2 contributed to the fatigue life of 100,180 cycles. Test results indicate that both the normal and tangential component of the SMLF values can identify the stress concentration and the crack zones. The gradient can reflect the degree of damage. Furthermore, in order to study the change law of the SMLF values in the crack zone, an improved magnetic dipole model considering the crack dimensions and shape is proposed. The model predictions are in very good agreement with the corresponding test results. Lastly, three characteristic parameters, i.e. average ΔHp(y) field values, resultant magnetic field value H and magnetic parameter m, were extracted from the test data. These parameters can judge the fatigue stage and the damage degree of the specimen. Therefore, the research lays the experimental and theoretical foundation for using the MMM method to inspect steel structures under fatigue bending loads.