Metal Magnetic Memory Signal Research Articles

Magnetic Evaluation on Disassembly Damage of an Interference Fit Joint

Developing a method for disassembly damage evaluation is of great significance for the key components in maintenance and remanufacturing. Disassembly of the interference fit joint between the shaft and impeller, which could inevitably bring damages to the parts’ surface, was investigated. The ferromagnetic materials FV520B (impeller) and 40CrNiMo7 (shaft) were used in the disassembly experiments. Experiments showed that different damage degrees appeared on the disassembled interface as a result of single sliding friction under different loads. The stress concentration and plastic deformation stimulated changes in magnetic domains, which led to the distortion of surface spontaneous magnetic field and the induction of metal magnetic memory (MMM) signals. The tangential components of MMM signals had peak-trough features with zero-crossing points, and the normal components showed peak features. The visible features of the distorted MMM signals could locate the position of the defects. The average damage depth Sa, peak-trough difference Wpp and peak area S had been proposed as characteristic values. The linear relationship between Sa and Wpp, Sa and S was further obtained, respectively. It indicated that the MMM technique was capable of quantitatively evaluating the disassembly damage of ferromagnetic parts, which also provided a reference for the remanufacturability assessment and the selection of repairing processes in remanufacturing engineering.

Study on metal magnetic memory signal of buried defect in fracture process

To study the magnetic memory signal characteristics of buried defects and for timely detection of the buried defects and stress concentration areas of metal components, defect samples with different burial depths were fabricated. The relationship between the magnetic memory signals and burial depths of the defects was studied. The variation in the magnetic memory signals of the buried defects was studied under different load stages (initial loading, mid-loading, critical fracture, and after fracture). The results show that the magnetic memory detection method can detect buried defects, and the strength of the magnetic field and its gradient decrease with an increase in the burial depth. The strength of the same defect magnetic field and its gradient decrease initially and then increase under the action of an external load, and then, increase sharply at the critical fracture stage. The research results are of considerable significance for the detection of defects in ferromagnetic materials.

A method for identifying geometrical defects and stress concentration zones in MMM technique

Metal magnetic memory (MMM) technique is a kind of passive magnetic non-destructive inspection technique sensitive to early damage due to stress concentration in ferromagnetic components. However, geometrical defects and stress concentration zones probably coexist in an inspected component, which will make trouble for damage evaluation. In the paper, a 3-Dimensional (3D) numerical simulation based on a stress-induced magnetic anisotropic constitutive model is employed to produce the MMM signals of an ×80 pipeline steel plate with a center hole stretched in the geomagnetic field. The effects of the hole and the nearby stress-concentration zones on the MMM signal characteristics are respectively studied, and then a simple and convenient MMM signal processing method is proposed to identify two kinds of damage. This work is useful for improving accuracy of the MMM technique in damage evaluation.

Measurement System of Metal Magnetic Memory Method Signals around Rectangular Defects of a Ferromagnetic Pipe

Oil and gas pipeline networks require the periodic inspection of their infrastructure, which can cause gas and oil leakage with several damages to the environment and human health. For this, non-destructive testing (NDT) techniques of low-cost and easy implementation are required. An option is the metal magnetic memory (MMM) method, which could be used for real-time monitoring defects of ferromagnetic structures based on the analysis of self-magnetic leakage fields distribution around each defect. This method only requires magnetic sensors with high resolution and a data processing system. We present a measurement system of tangential and normal MMM signals of three rectangular defects of an ASTM A-36 steel pipe. This system is formed by a magnetoresistive sensor, an Arduino nano and a virtual instrumentation. The measured magnetic signals have non-uniform distributions around the rectangular defects, which have small differences with respect to the results obtained of a 2D magnetic dipole model. The size of each rectangular defect is related to the amplitude and shape of its tangential and normal MMM signals. The proposed system could be used for real-time monitoring of the size and location of rectangular defects of ferromagnetic pipes. This system does not require expensive equipment, operators with high skill level or a special treatment of the ferromagnetic samples.

Comparison between Magnetic Field Distribution Analysis and Metal Magnetic Memory (MMM) Testing Results Around Artificial Cracks under Loads

In this research, the behavior of the metal magnetic memory (MMM) signals near the artificial cracks located the back side of A572 specimens are tried. The materials are used as power transmission tower material. The variations of the MMM signals with the applied tensile loads are studied. It is found that both the tangential component, Hp(x), and the normal component, Hp(y), are effectively showed the stress concentration zone (SCZ) caused by discontinuities. The results of modeling and MMM technique showed that the loads create residual stress and lead to the change of magnetic field strength around artificial cracks in the specimen and that is relatively different from the crack free area. This research is useful for expending MMM method as a tool of nondestructive testing method for detecting subsurface flaws.

An anisotropic magneto-mechanical model of ferromagnetic materials for the magnetic memory testing method

The metal magnetic memory (MMM) method shows great potential in the early damage evaluation of ferromagnetic materials. The MMM signal is affected by the environmental magnetic field because of the magneto-mechanical coupling effect. For instance, the effect of the environmental magnetic field is connected with the angle between the environmental magnetic field and the detected structure, which is referred to as the angle effect. This paper aims to explore the angle effect on the MMM method under the weak magnetic field. An anisotropic nonlinear magneto-mechanical constitutive relationship is proposed based on the magnetic domain theory and the approach law. Compared to the existing model, the present constitutive relationship in this paper can predict the stress-magnetization curve of ferromagnetic materials under the combined action of the loading stress and the environmental magnetic field with different directions. Based on the present constitutive relationship, an anisotropic nonlinear magneto-mechanical model of the MMM method is established, and then the angle effect is discussed in detail. The prediction of the anisotropic nonlinear magneto-mechanical model shows a good agreement with experimental data. The proposed model can clarify the reasons for some complex phenomena of the MMM signal, and thus help in the practical application of the MMM method.

The detection of corrosion of steel strands based on weak magnetic flux leakage effect of metal magnetic memory

The cable corrosion is an unsolved difficult problem in the engineering field. At present, the corrosion of steel strands has become the key factor affecting the health of cable. In order to effectively detect the corrosion of steel cables, metal magnetic memory (MMM) non-destructive testing technology is applied. Through experimental research, the distribution characteristics of magnetic flux leakage (MFL) signals of corrosion magnetic memory are analyzed. Some criterions of steel strand corrosion degree based on the characteristics of MMM signals are constructed. The test results show that the MFL signals change obviously for the corroded specimens, and the tangential component of the magnetic flux leakage appears minimum in the middle of the corroded region. The relationship between the tangential component minimum value and the corrosion degree of the specimens presents the Boltzmann function distribution. With the increase of the lift-off value of the magnetic sensor, the MFL signals of the corroded specimens decrease sharply. A slight difference in the lift-off value can cause a large fluctuation in the minimum value of the tangential component of the MFL signals.

Studies on influences of initial magnetization state on metal magnetic memory signal

Metal magnetic memory testing is a novel testing method which can early test stress concentration level of ferromagnetic components. In theory, the influences of the initial magnetization on the magnetic memory signal were studied. In the experimental aspect, take Q235 steel specimen for example, the relationship between initial magnetization state and metal magnetic memory signal was researched by static tensile test under three different initial magnetization conditions. Both the experimental studies and theoretical analysis come to similar conclusion that the variation trend of magnetization with the stress is that the initial magnetization status tends to shift towards the non-hysteresis magnetization state. With the increasing of stress, the magnetizing state gradually shifts towards the anhysteretic magnetization state, and the variation rate is directly proportional to the difference between the initial magnetization and the non-hysteresis magnetization. Our study indicates that the initial magnetization state has an important influence on the magnetic memory signal, and the research results can provide reference for quantitative test of metal magnetic memory testing technology.

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

To monitor fatigue crack initiation and propagation, and to judge the fatigue damage status of ferromagnetic material, fatigue bending tests of four-point single edge notch bend (SENB4) specimens were carried out. Metal magnetic memory signals were measured during the whole fatigue process. The results showed that the fatigue process could be divided into four stages by observing the morphology of the fracture surface. With the increase of fatigue loading cycles, the tangential component of the magnetic field (Hx) and the normal component of the magnetic field (Hy) increased. At the notch Hx presented a “trough” shape and had a maximum value at the midpoint, while Hy at the notch rotated clockwise around the midpoint. Compared with the tangential characteristic parameters, the variation of normal characteristic parameters (i.e., maximum gradient value of Hy (Ky-max) and the variation range of Hy at the notch (∆Hyn), with the fatigue loading cycles are more similar to the variation of fatigue crack length with loading cycles), both Ky-max and ∆Hyn had a good linear relationship with fatigue crack length. Plastic deformation accumulated on both sides of the fatigue crack, and metal magnetic memory (MMM) signals measured from the specimens were able to indicate the location of the fatigue crack and the variation of the fatigue crack length. Furthermore, the distribution of magnetic signals was analyzed according to the theories of stress magnetization and magnetic flux leakage.

The probabilistic analysis of fatigue crack effect based on magnetic flux leakage

In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72-0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.

New Method of Metal Magnetic Memory Signal Measuring and Denoising

New Method of Metal Magnetic Memory Signal Measuring and Denoising

Characterization of Stress Concentration by Tangential Component Hp(x) of Metal Magnetic Memory Signals

The correlation between the stress concentration and the spontaneous magnetic signals of metal magnetic memory (MMM) was investigated via tensile tests. Sheet specimens of the Q235 steel were machined into standard bars with rectangular holes to obtain various stress concentration factors. The tangential component Hp(x) of MMM signals and its related magnetic characteristic parameters throughout the loading process were presented and analyzed. It is found that the tangential component Hp(x) is sensitive to the abnormal magnetic changes caused by the local stress concentration in the defect area. The minimum magnetic field is positively correlated to the magnitude of the load and the distance from the notch. The tangential magnetic stress concentration factor presents good numerical stability during the entire loading process, and can be used to evaluate the stress concentration factor. The results obtained will be a complement to the MMM technique.

Quantitative study on the propagation characteristics of MMM signal for stress internal detection of long distance oil and gas pipeline

The metal magnetic memory (MMM) detection technology has great application potential in the field of stress internal detection of long distance oil and gas pipeline due to the non-contact online detection to stress damage; however, the scientific significance of the pipeline stress internal detection results is questioned because the detection signal is affected by the medium during propagation. To study the propagation characteristics of MMM signal, a three-dimensional magnetic balanced magneto-mechanical model is set up based on magnetic charge theory. In this paper, the distribution characteristics of the scattered magnetic field in the stress concentration region are exposed and the propagation characteristics of different components of MMM signal are quantitatively analyzed. Further, the influence of different media on MMM signal propagation is compared, and a systematic experimental study is conducted. The results indicate that MMM signal shows a first-order exponential decay with increasing propagation distance. During the propagation, the tangential signal decays rapidly, and the normal signal is stable and suitable for locating the stress concentration regions. MMM signal decays faster in ferromagnetic medium than in non-ferromagnetic medium.

Thermo-magneto-elastoplastic coupling model of metal magnetic memory testing method for ferromagnetic materials

Metal magnetic memory (MMM) testing (also known as micro-magnetic testing) is a new non-destructive electromagnetic testing method that can diagnose ferromagnetic materials at an early stage by measuring the MMM signal directly on the material surface. Previous experiments have shown that many factors affect MMM signals, in particular, the temperature, the elastoplastic state, and the complex environmental magnetic field. However, the fact that there have been only a few studies of either how these factors affect the signals or the physical coupling mechanisms among them seriously limits the industrial applications of MMM testing. In this paper, a nonlinear constitutive relation for a ferromagnetic material considering the influences of temperature and elastoplastic state is established under a weak magnetic field and is used to establish a nonlinear thermo-magneto-elastoplastic coupling model of MMM testing. Comparing with experimental data verifies that the proposed theoretical model can accurately describe the thermo-magneto-elastoplastic coupling influence on MMM signals. The proposed theoretical model can predict the MMM signals in a complex environment and so is expected to provide a theoretical basis for improving the degree of quantification in MMM testing.

Effect of sample initial magnetic field on the metal magnetic memory NDT result

One of the major concerns regarding the use of Metal Magnetic Memory (MMM) technique is the complexity of residual magnetization effect on output signals. The present study investigates the influence of residual magnetic field on stress induced magnetization. To this end, various initial magnetic fields were induced on a low carbon steel sample, and for each level of residual magnetic field, the sample was subjected to a set of 4-point bending tests and, their corresponding MMM signals were collected from the surface of the bended sample using a tailored metal magnetic memory scanning device. Results showed a strong correlation between sample residual magnetic field and its corresponding level of stress induced magnetic field. It was observed that the sample magnetic field increases with applying the bending stress as long as the initial residual magnet field is low (i.e. <117 mG), but starts decreasing with higher levels of initial residual magnetic fields. Besides, effect of bending stress on the MMM output of a notched sample was investigated. The result, again, showed that MMM signals exhibit a drop at stress concentration zone when sample has high level of initial residual magnetic field.

Quantitative Identification Modeling of Drilling Pipe Damage Levels Based on Metal Magnetic Memory Characteristic Parameters

In order to quantitatively identify drill pipe defect levels by using Metal Magnetic Memory (MMM) technology, an optimized multi-classification FSVM model is first proposed. The material of drill pipes is S355 low carbon alloy steel. The MMM signal characteristics of different damage levels are obtained through a lot of field testing. Considering the dispersion and small samples of MMM data in practical engineering, SVM is introduced to solve the bottleneck of small samples and dispersion. The fussy membership degree function and the parameter combinatorial optimization are adopted to improve the robustness of SVM. By extracting four dimension characteristic parameters, the quantitative MMM identification model is proposed based on optimized multi-classification FSVM algorithm. The test results show that the model precision is 90.17%, which provides a new method for the quantitative MMM evaluation on drilling tool damage levels.

Characteristics of Metal Magnetic Memory Testing of 35CrMo Steel during Fatigue Loading

The fatigue fracture of a drillstring could cause drilling disturbances and some negative impacts (e.g., economic loss) will be brought when restoring the drillstring to functionality. In order to evaluate the effects of the fatigue damage of the drillstring during drilling, a new apparatus, which could monitor the load level in real-time, was built to perform the four-point bending fatigue test on 35CrMo steel, a typical material of drillstrings. Such an apparatus is based on metal magnetic memory (MMM) technology and can acquire the tangential and normal components of MMM signals. Based on the analysis of the change of surface morphology and MMM signals, it was concluded that the variation of MMM signals could be divided into four stages, which are used to accurately describe the fatigue damage process of the drillstring. Additionally, the MMM signal characteristics are introduced to especially evaluate the fatigue damage of the drillstring, including crack initiation. Furthermore, the scanning electron microscopy (SEM) results demonstrated that morphologies of fatigue fracture were related to the variation of MMM signals. Linear fitting results indicated that fatigue crack length had a good linear relationship with the characteristics, so it is feasible to monitor fatigue damage and predict the residual life of a drillstring by using MMM technology.

Sizing of Defect Using Magnetic Memory Signal Based on the Reconstruction Algorithm

A metal magnetic memory (MMM) testing technique is an extensively used qualitative method for locating the position of possible damages in ferromagnetic metal structures. The mechanism of the MMM technique is described by the magnetomechanical effect under the constant magnetizing field of the Earth. Discontinuous defect remarkably affects MMM signals. For the exploration of the influences of defect on MMM signals and the determination of a method to size the defect, experimentation and reconstruction calculation were performed in this paper. Stress was imported into a specimen fabricated with a circular defect to generate the stress-induced MMM signal. The defect size and the residual magnetic field of the specimen were measured after loading. The stress-induced magnetization inside the specimen was reconstructed with measured magnetic field signals using a reconstruction algorithm. The influences of the discontinuous defect on the stress-induced magnetization were quantitatively analyzed. A method for defect imaging and sizing using the MMM technique was proposed. Results corroborate that the reconstructed defect width is congruent with the actual defect width, thereby confirming the effectiveness and applicability of the proposed method.

Characterizing the magnetic memory signals on the surface of plasma transferred arc cladding coating under fatigue loads

The metal magnetic memory signals were measured during dynamic tension tests on the surfaces of the cladding coatings by plasma transferred arc (PTA) welding and the 0.45% C steel. Results showed that the slope of the normal component Hp(y) of magnetic signal and the average value of the tangential component Hp(x) reflect the magnetization of the specimens. The signals increased sharply in the few initial cycles; and then fluctuated around a constant value during fatigue process until fracture. For the PTA cladding coating, the slope of Hp(y) was steeper and the average of Hp(x) was smaller, compared with the 0.45% C steel. The hysteresis curves of cladding layer, bonding layer and substrate were measured by vibrating sample magnetometer testing, and then saturation magnetization, initial susceptibility and coercivity were further calculated. The stress-magnetization curves were also plotted based on the J-A model, which showed that the PTA cladding coating has smaller remanence and coercivity compared with the 0.45% C steel. The microstructures of cladding coating confirmed that the dendritic structure and second-phase of alloy hinder the magnetic domain motion, which was the main factor influencing the variation of magnetic signal during the fatigue tests.

Metal Magnetic Memory Testing of Welded Joints under Fatigue Load

To investigate the influence of stress concentration, crack propagation and types of fatigue loading on metal magnetic memory signals, two groups of fatigue experiments with different types of fatigue loading were carried out on Q235B steel welded joint. The normal components of magnetic flux leakage were measured by metal magnetic memory tester in the course of fatigue test, and the fracture surfaces of specimens were observed by scanning electron microscopy after fatigue tests. The experimental results showed that the normal components of magnetic flux leakage filed, as well as the metal magnetic memory signal, changed polarity and their gradients have peak values at stress concentration zones. The zero position of the normal component of magnetic flux leakage changed gradually with increasing cycle numbers. In addition, the metal magnetic memory signal feature of fatigue crack propagation was affected by the loading type clearly. Moreover, a combination of brittle rupture and ductile rupture was obtained in the fracture morphology figure.