Weld Identification Method Based on Metal Magnetic Memory Detection Technology

Abstract

This invention provides a weld identification method based on metal magnetic memory detection technology, comprising the following steps: detecting the magnetic field strength at the weld; converting the magnetic field strength signal into magnetoelectric signal, acquiring the weld leakage magnetic field signal, performing noise reduction processing, and obtaining the magnetic memory signal value at the weld; extracting the distribution and variation characteristics of the weld's magnetic memory signal using the magnetic gradient tensor measurement method, obtaining the total magnetic field gradient and magnetic tensor modulus gradient; analyzing the mechanomagnetic mechanism of the leakage magnetic field signal variation, proposing damage criteria, obtaining damage evaluation parameters based on the gradient curve of the leakage magnetic field signal, performing numerical simulation, inverting the damage zone, and determining the weld damage location and damage degree; and outputting the identification and detection results. This invention can accurately locate the damage location and transverse and longitudinal width of welds in ferromagnetic material structures, and the use of passive magnetization reduces the cost of use; the inversion and reconstruction of weld defect size and location improves the efficiency and accuracy of identifying and detecting elastic-plastic strain defects in welding.

Description

Technical Field

[0001] This invention relates to the field of magnetic flux leakage detection technology, and more specifically, to a weld identification method based on metal magnetic memory detection technology. Background Technology

[0002] Early physical damage caused by elastic stress concentration and microscopic plastic deformation within engineering materials can reduce the load-bearing capacity of the materials and structures, and may even lead to catastrophic accidents. Internal damage in engineering materials (such as residual stress, stress concentration, and macroscopic defects) can lead to the degradation of the mechanical properties of materials and structures, and may even cause sudden safety accidents, thus having a significant impact on national safety and production development.

[0003] The causes of damage to load-bearing components in modern engineering are complex and diverse, and often persist throughout their entire life cycle. Therefore, effective monitoring of engineering materials and structures is crucial to ensuring safe industrial operation, making effective damage detection of component materials a critical and complex issue.

[0004] Currently, non-destructive testing (NDT) is the most common method for inspecting the interior of engineering structures. The aim of NDT is to effectively inspect and test materials, components, and products without damaging the object being inspected, evaluating their continuity, integrity, and other physical properties. NDT includes NDT (Nondestructive Testing), NDI (Nondestructive Inspection), and NDE (Nondestructive Evaluation). In recent years, NDT and NDI have gradually transitioned to NDE. This requires NDT not only to understand existing defects and their distribution, but also to predict and assess structural components (including lifespan and defect development trends) before damage occurs.

[0005] However, existing traditional non-destructive testing methods such as magnetic particle testing, X-ray testing, eddy current testing, and ultrasonic testing are mostly used to detect defects that have already appeared. They cannot evaluate and analyze the early performance degradation of materials, nor can they prevent accidental fatigue damage to engineering components, which is the main root cause of damage to engineering components and accidents.

[0006] While traditional magnetic flux leakage testing has been widely used in engineering, it is a strong magnetic detection technique that requires an external magnetic field to saturate the component under test. This type of strong magnetic detection technique is relatively effective in detecting macroscopic geometric defects in structures (its principle is that saturated magnetic lines of force cannot pass effectively through geometric defects, resulting in magnetic leakage).

[0007] However, traditional magnetic flux leakage detection techniques, such as strong magnetic field testing, are not suitable for detecting early physical damage to materials (e.g., plastic damage caused by stress concentration). Ferromagnetic materials are microscopically composed of many magnetic domains, each of which exhibits spontaneous magnetization. However, due to the random distribution of the initial domain structure, such as... Figure 6 As shown, the material as a whole does not exhibit magnetism externally; however, when localized physical damage occurs due to stress concentration, under the influence of a weak magnetic field such as the Earth's magnetic field, the material's magnetic domains will exhibit a partially oriented distribution at the damaged site, reflecting the degree of localized damage, such as... Figure 7 As shown. However, in traditional magnetic flux leakage (MF) testing, a strong magnetic field is applied to the workpiece before measurement. Under the influence of this strong magnetic field, all magnetic field lines inside the workpiece will reorient along the direction of the applied magnetic field, causing the magnetic domain distribution that originally reflected the local damage characteristics of the material to disappear, resulting in the loss of physical damage information. Therefore, traditional MF testing technology is not suitable for detecting early damage to materials.

[0008] Micro-damage caused by early microscopic defects in materials is a major potential hazard source for the failure or even sudden destruction of ferromagnetic components. Developing non-destructive methods for early damage to ferromagnetic materials has always been a research hotspot and challenge in the field of non-destructive testing (NDT). NDT actually faces an inverse problem: it must establish an intelligent experimental analysis system based on the detected experimental signals, combined with physical models and simulation methods, to ultimately invert the characteristics of structural defects.

[0009] Welding of metal components is a crucial step in the manufacturing, installation, repair, and modification of engineering components. The quality of the weld is a vital prerequisite for ensuring the safe and normal use of these components. During welding, the weld metal undergoes rapid melting and cooling, inevitably creating a non-equilibrium microstructure and stress concentration zones. These stress concentration zones in the weld accumulate considerable stress energy. To minimize the total free energy within the ferromagnetic component, the increase in stress energy is primarily offset by increasing magnetoelastic energy within the material, resulting in a distorted magnetic field significantly stronger than the Earth's magnetic field. Research on the mechanical properties of metals shows that even in the elastic deformation region of metallic materials, a perfectly elastic body without any energy loss does not exist. Due to various internal friction effects within metals (such as viscoelastic friction and dislocation friction), stress concentration zones formed during loading will inevitably remain after the dynamic load is removed, especially under dynamic loads, large deformations, and high temperatures. These retained stress concentration zones form a distribution pattern similar to a defect leakage magnetic field. During the production, welding, and assembly of ferromagnetic materials, numerous internal defects inevitably arise. Over long-term use, these areas often experience stress concentration, leading to degradation of the material's and structure's mechanical properties. For welded structures, the presence of welding defects inevitably alters their stress-strain state, which in turn changes the signal of the leakage magnetic field on the material surface.

[0010] Therefore, welding defects can be described by extracting characteristic quantities of the leakage magnetic field signal. Metal Magnetic Memory (MMM) inspection technology can detect not only established macroscopic defects but also microscopic defects in the weld, as well as damage initiation stages characterized by high stress concentration levels. This demonstrates that MMM inspection technology has unique advantages in welding defect inspection that other non-destructive testing methods do not possess.

[0011] However, due to the relatively short development time of magnetic memory testing technology for metals, many physical and geometric factors influence the magnetic detection signal (such as residual stress state, degree of local macroscopic defects, geometry and location of plastic deformation zones, etc.). Sufficient magnetic characteristic parameters are needed to describe the specific features of the defects. However, systematic research on defect identification methods based on magnetic memory testing is currently lacking. Metal magnetic memory testing methods can only rely on the tangential component H of the leakage magnetic field. p (x) reaches its maximum value and the normal direction component H p (y) Zero-crossing points determine possible dangerous locations, and this criterion only applies to crack-type defects. It is not applicable to local elastic-plastic deformations present in welds. Obviously, existing magnetic memory detection methods are not sufficient to effectively characterize the specific features of weld defects. Summary of the Invention

[0012] Therefore, the purpose of this invention is to design a method for identifying welds by measuring normal magnetic leakage signals based on metal magnetic memory detection technology. This method involves establishing a micro-statistical weld force-magnetic coupling constitutive model. Using this model, combined with finite element calculations, numerical simulations and measurements are conducted to obtain the magnetic leakage signal characteristics corresponding to uniform stress states and stress concentration states with elastoplastic strain. The effectiveness of the weld force-magnetic coupling constitutive model in identifying magnetic leakage parameters is verified by comparing the calculation results with experimental results. Based on the measured magnetic leakage signals, a damage criterion based on the metal magnetic memory detection method is established, magnetic leakage signal evaluation parameters are obtained, an objective function is constructed, and the size and location of weld defects are inverted and reconstructed, thereby improving the accuracy of weld defect identification.

[0013] In the late 1990s, Russian scholars, represented by Doubov, proposed a novel metal diagnostic technique—magnetic memory testing (MMT). Unlike traditional non-destructive testing methods, MMT is a passive, weak magnetic field detection technique. It evaluates the stress concentration state and damage condition of the material by measuring the distortion of the spontaneous leakage magnetic field formed on the surface of the tested object due to localized stress concentration or damage, thus determining the location and extent of damage. MMT offers advantages such as sensitivity to early material performance degradation, non-contact measurement, and convenient and rapid testing. Its principle is described as follows: When an iron workpiece is subjected to a working load under a geomagnetic environment, its internal magnetic domains undergo directional and irreversible reorientation with magnetostrictive properties, resulting in the largest change in the leakage magnetic field Hp in the stress and deformation concentration areas. This is the tangential component H of the magnetic field. p (x) has a maximum value, while the normal component H p (y) changes and has a zero point. This irreversible change in magnetic state persists after the working load is removed. Thus, through the leakage magnetic field normal component H p By measuring (y), the stress concentration area of ​​the workpiece can be deduced. Therefore, by utilizing the H on the surface of the ferromagnetic workpiece... p The intensity of the change in (y) can be used to infer the area of ​​residual stress concentration inside the workpiece, determine the early damage of the structure, and thus reduce and prevent sudden failure events of components.

[0014] The excitation source for metallic magnetic memory detection is primarily the Earth's magnetic field, requiring no other external excitation, thus making the detection more convenient and faster. Modern materials science and ferromagnetism show that the magnetism of ferromagnetic materials originates from atomic magnetic moments, which in turn primarily originate from the electron spin within atoms. Due to the exchange interactions between electrons of different atoms, the atomic magnetic moments in ferromagnetic materials tend towards a long-range ordered state, i.e., spontaneous magnetization. However, due to the presence of static magnetic energy, many magnetic domains are formed within the ferromagnetic material. Magnetic domains are regions with the same spontaneous magnetization state (i.e., the direction and magnitude of magnetization within the region are consistent, such as...). Figure 3 (As shown). When there is no stress or defect damage inside the ferromagnetic material, the magnetic domains inside the material are in a chaotic and uniform state, the internal magnetization M=0, and it does not exhibit magnetism externally, such as... Figure 3 As shown. Where x, y, and z represent spatial coordinates. When a defect-free material is subjected to an external magnetic field Hex or an external load F, the magnetic domains tend to align parallel to the direction of Hex or F, resulting in uniform magnetization M = Mcst within the material. The leakage magnetic signal x-direction component Hx corresponding to the material surface is a horizontal straight line, and the leakage magnetic signal z-direction component Hz is a slanted straight line, as shown... Figure 4As shown, with the increase of Hext or F, the magnetization inside the material increases, the absolute value of Hx increases, and the slope of Hz increases. When there is stress concentration or geometric defects inside the material, the non-uniform stress inside will lead to non-uniform magnetization M=M(x, y). The leakage magnetic field on the surface of the material will be distorted, Hx will show a single-peak variation characteristic, and Hz will show a peak-peak variation characteristic, such as... Figure 5 As shown. This change persists even after the external magnetic field or load disappears. This distorted leakage magnetic signal can "memorize" the location of stress concentrations and defects in the material; therefore, this phenomenon is called the magnetic memory effect of metallic materials. For the early diagnosis of ferromagnetic components, Metal Magnetic Memory Testing (MMM) is an effective method. Theoretically, MMM is currently the most promising non-destructive testing method for early diagnosis of ferromagnetic materials and structures, and it has already been partially applied in engineering.

[0015] Metal magnetic memory detection has the following characteristics due to its inherent principle:

[0016] (1) Reliable testing of components can be performed without the need for specialized magnetization equipment;

[0017] (2) No special treatment, such as cleaning, is required for the surface of the component being tested;

[0018] (3) The equipment is lightweight, easy to operate, and highly sensitive.

[0019] This invention provides a weld identification method based on metal magnetic memory detection technology, comprising the following steps:

[0020] S1. Arrange magnetic signal detection sensors at the weld of the ferromagnetic material structural component to be tested, and detect the magnetic field strength at the weld.

[0021] S2. Using Hall elements, the detected magnetic field strength is input into an analog-to-digital converter for magneto-electric conversion based on the Hall effect, and the leakage magnetic signal of the weld of the ferromagnetic material structural component is collected.

[0022] The number of Hall elements is 81 to 144, forming a square array of 9×9 to 12×12. The distance between two adjacent Hall elements in the horizontal direction is 2.5 to 3 mm, and the distance between two adjacent Hall elements in the vertical direction is 1.2 to 1.6 mm.

[0023] S3. Noise reduction processing is performed on the leakage magnetic signal of the weld of the ferromagnetic material structural component to obtain the magnetic memory signal value at the weld of the ferromagnetic material structural component.

[0024] S4. Using the magnetic gradient tensor measurement and analysis method, the distribution and variation characteristics of the magnetic memory signal of the weld of the ferromagnetic material structural component are extracted to obtain the total magnetic field gradient and the magnetic tensor modulus gradient.

[0025] S5. Based on the distribution characteristics of the total magnetic field gradient and the magnetic tensor modulus gradient and the location of the extreme points of the magnetic memory signal, analyze the magnetic mechanism of the leakage magnetic signal change, propose damage criteria, obtain damage evaluation parameters according to the gradient curve of the leakage magnetic signal, perform numerical simulation, and use the proposed damage criteria and evaluation parameters to invert the damage area to determine the location and degree of damage of the weld of the ferromagnetic material structural component.

[0026] S6. Output the identification and detection results of leakage magnetic signals.

[0027] Furthermore, the method for analyzing the force-magnetic mechanism of leakage magnetic signal changes in step S5 includes the following steps:

[0028] A. By utilizing linear magnetoelastic energy to improve the Boltzmann distribution, a microscopic statistical model describing the ideal magnetization and magnetostriction of ferromagnetic cubic crystal materials is derived. A weld force-magnetic coupling constitutive model is constructed, and the effects of different stresses and material parameters on the ideal magnetization and magnetostriction coefficients are analyzed. The expression of the weld force-magnetic coupling constitutive model is as follows:

[0029] (1)

[0030] In equation (1), the total effective field H is... total Consider as an elastic field Plastic field and external magnetic field H H The three parts are superimposed: H is the external magnetic field, M is the magnetization intensity of the ferromagnet under the action of the external magnetic field, and σ1, σ2, and σ3 represent the three principal stress values, respectively. ,m,n represent the cosine angles between the three principal stresses and the magnetization direction; E is the absolute value of the atomic magnetic moment of a single magnetic domain; Let be the pinning energy that needs to be overcome for domain rotation, and its value be a material parameter; let the plastic strain be... The dislocation density N satisfies the following linear relationship:

[0031] (2)

[0032] In equation (2), k is a linear coefficient;

[0033] B. Experiments were conducted on the magnetic flux leakage signal of the welded specimen. The distribution characteristics of the magnetic flux leakage signal of the weld were numerically analyzed using the aforementioned weld force-magnetic coupling constitutive model and the finite element method. The effectiveness of the aforementioned weld force-magnetic coupling constitutive model in describing the magnetic flux leakage signal under uniform stress and concentrated stress was verified, and the characteristics of the magnetic flux leakage signal under uniform stress and under stress concentration were evaluated.

[0034] C. Analyze the relationship between elastoplastic effective stress and leakage magnetic signal, and establish the relationship criteria between elastoplastic effective stress parallel to the load direction and leakage magnetic signal perpendicular to the load direction.

[0035] D. Conduct detection, measurement, and numerical analysis calculations on welded specimens containing different weld defect sizes, analyze the sensitivity and correlation of the weld force-magnetic coupling constitutive model to describe the leakage magnetic signal under different welding elastic-plastic stresses, and obtain the leakage magnetic signal characteristics of welding defects.

[0036] E. Based on the gradient of the detected magnetic flux leakage signal, establish a damage criterion, obtain the evaluation parameters of the magnetic flux leakage signal, construct an objective function, and based on the weld force-magnetic coupling constitutive model, use the finite element method or genetic algorithm to invert and reconstruct the weld defects of the welded workpiece to identify the characteristics of the weld defects.

[0037] Furthermore, the method for numerically analyzing the distribution characteristics of weld leakage magnetic flux signal by combining the finite element method in step B includes: two-dimensional finite element numerical simulation analysis and three-dimensional finite element numerical simulation analysis.

[0038] The two-dimensional finite element numerical simulation analysis method includes: simulating and examining different stages of elastic and plastic deformation, the geometric characteristics of defect width, depth, and burial depth, as well as the influence of test direction and sensor lift-off value on the characteristics of leakage magnetic field signal changes using a two-dimensional model; assuming a coercive force H... c =56A / m, with relative permeabilities μ0 set from the center of the specimen outwards at 270, 374, and 527 respectively, and coercivity H =56A / m. c The values ​​were 335, 320, and 280 A / m, respectively, corresponding to plastic strains of 10.0%, 8.0%, and 3.0%.

[0039] The method for three-dimensional finite element numerical simulation analysis includes: without changing the planar dimensions of the two-dimensional model, designing a finite thickness t in the z-axis direction perpendicular to the paper to form a three-dimensional model, examining the three-dimensional effect of leakage magnetic signal: the influence of thickness t, setting the relative permeability μ0 to 270, and the coercivity H... c =335A / m, plastic strain is 8.0%.

[0040] This invention selects specimen models with different weld thicknesses for calculation to obtain normal magnetic flux leakage signals. and tangential leakage magnetic signal The amplitude of the leakage magnetic field changes, and the value of the leakage magnetic field signal gradually increases with the increase of thickness t, but the shape does not change much. With the increase of thickness t, the peak-valley value of the normal leakage magnetic field gradient in the three-dimensional simulation increases. and tangential leakage magnetic gradient peak-to-peak value Both gradually tend towards two-dimensional results; the gradient characteristic width of the normal and tangential leakage magnetic signals and Basically unaffected by changes in thickness, the result of the two-dimensional model is the limit value of the three-dimensional model when the thickness t approaches infinity.

[0041] The two-dimensional numerical simulation results of this invention show that magnetic memory detection is more sensitive to damage occurring on the specimen surface; the smaller the sensor lift-off value, the clearer the change in leakage magnetic field signal can be guaranteed; the specimen orientation has a slight influence on the leakage magnetic field amplitude, but almost no influence on the change in the gradient curve; the numerical simulation results of the two-dimensional model are the limit values ​​when the thickness of the three-dimensional model tends to infinity; leakage magnetic field evaluation parameters. and It can be used to invert the size and shape of the damaged area.

[0042] Numerical analysis of magnetic flux leakage signals in damaged samples was conducted using the finite element method. The results show that:

[0043] Magnetic memory detection is more sensitive to damage occurring on the surface of the specimen; during measurement, the sensor should be kept as close to the surface of the specimen as possible; the specimen orientation has no effect on the change of the leakage magnetic gradient curve; the evaluation parameters for characterizing the damage range proposed by the experimental results can be used to invert the size and shape of the damage area.

[0044] Further, the method for evaluating the characteristics of the leakage magnetic signal under uniform stress state in step B includes:

[0045] The magnitude of uniform stress is evaluated using the following three characteristic parameters:

[0046] (1) The slope of the normal leakage magnetic signal Hz along the trace parallel to the load direction (the slope increases with the increase of load).

[0047] (2) The gradient value of Hz along the trace parallel to the load direction;

[0048] (3) The amplitude of Hx variation along the traces parallel and perpendicular to the load direction.

[0049] Furthermore, the method for evaluating the characteristics of the leakage magnetic signal under stress concentration conditions in step B includes:

[0050] The degree and extent of stress concentration can be assessed using the following five characteristic parameters:

[0051] (1) The extent to which the vertical peak height of Hx along the traces parallel and perpendicular to the load direction increases with the increase of load;

[0052] (2) The degree to which the vertical peak difference between peaks increases as the load increases along the trace parallel to the load direction;

[0053] (3) The peak difference between peaks in the vertical direction along the trace parallel to the load direction of Hz;

[0054] (4) The vertical peak height of the single peak along the traces parallel and perpendicular to the load direction of Hx;

[0055] (5) Hz is the vertical peak height of a single peak located on both sides of the defect and along the trace perpendicular to the load direction.

[0056] The optimal parameters for assessing the degree and extent of stress concentration are:

[0057] The peak difference between peaks along the trace parallel to the load direction in the vertical direction.

[0058] Furthermore, the method for establishing the relationship criteria between the elastoplastic effective stress parallel and perpendicular to the load direction and the leakage magnetic field signal in step C includes:

[0059] The effectiveness of the comprehensive evaluation parameter between the effective elastoplastic stress parallel to the load direction and the leakage magnetic field signal is verified. A comprehensive evaluation parameter between the effective elastoplastic stress perpendicular to the load direction and the leakage magnetic field signal is proposed. The effective elastoplastic stress parallel to the load direction and perpendicular to the load direction is used to characterize the stress distribution in the load direction and the load direction.

[0060] Furthermore, the damage establishment criteria in step E include: criteria for establishing the elastic stage and criteria for establishing the plastic stage;

[0061] The criteria for the elastic phase include: using the slope of the normal leakage magnetic signal. and tangential leakage flux amplitude To determine the stress amplitude in the elastic stage;

[0062] The criteria for the plastic stage include: at stress concentration sites, the normal leakage magnetic signal... Fluctuations occur, leakage magnetic gradient Extreme values ​​appear; tangential leakage magnetic signal Extreme values ​​appear, leakage magnetic gradient A peak-to-peak variation occurs, and the stress crosses zero at the center of the stress concentration.

[0063] During the elastic deformation stage, elastic stress promotes the orientation of magnetic domains along the direction of maximum tensile stress, thereby increasing the average magnetic induction intensity and spatial leakage magnetic field of the material. The damage criterion is that the normal leakage magnetic signal changes linearly along the loading direction, and the slope of the curve increases basically linearly. The slope of the tangential leakage magnetic signal curve remains basically unchanged, and the absolute value of the amplitude gradually increases and tends to a constant value.

[0064] During the plastic deformation stage, micro-defects such as dislocations and twins are formed inside the ferromagnetic material. The formation of micro-defects has a pinning effect, which hinders the magnetization of the ferromagnetic material and reduces its magnetic permeability. The damage criterion is that at the stress concentration site, the normal leakage magnetic signal shows a significant fluctuation, the leakage magnetic gradient shows an extreme value, the tangential leakage magnetic signal shows a significant extreme value, the leakage magnetic gradient shows a peak-to-peak change and crosses zero at the center of the stress concentration.

[0065] Furthermore, the method for obtaining the leakage magnetic field signal evaluation parameters in step E includes:

[0066] Four evaluation parameters are defined: peak-valley value of normal leakage magnetic gradient. , width of normal leakage magnetic gradient Tangential leakage magnetic gradient peak-to-peak value , width of tangential leakage magnetic gradient .

[0067] The vertical distance between two opposing peaks in the gradient curve of the tangential leakage magnetic signal is denoted as . The horizontal spacing between two peaks in the gradient curve of the tangential leakage magnetic signal is the parameter. Used to evaluate the degree of non-uniformity in localized damage to materials. Used to evaluate the extent of localized damage to materials. The higher the value, the more severe the unevenness of the local damage; The higher the value, the larger the area of ​​localized damage. These four parameters can be used to effectively evaluate the degree of unevenness and extent of localized damage to materials.

[0068] Both the leakage magnetic field signal and its gradient curve can provide some characteristic parameters for evaluating the damage (including the degree and extent of damage), but the gradient curve can eliminate the influence of the external magnetic field and better reflect the degree of damage localization. The degree of damage localization can be evaluated using parameters such as peak-to-peak value, peak-to-valley value, and peak value on the leakage magnetic field signal gradient curve; the damage range can be evaluated using parameters such as peak-to-peak width, peak-to-valley width, and horizontal spacing of peak zero-crossing points.

[0069] Furthermore, the method for inverting and reconstructing weld defects in the welded workpiece in step E includes:

[0070] On the xz plane of the welded workpiece surface, measurement traces with an interval of 0.4 mm and parallel to the x-axis are set for different z coordinates. The normal leakage magnetic signal and the tangential leakage magnetic signal on each trace are calculated and extracted. The gradient curve changes of the normal leakage magnetic signal and the tangential leakage magnetic signal are obtained by differentiation.

[0071] Evaluation parameters for obtaining the leakage magnetic field gradient curve on each measurement trace. and The shape of the damaged area is inverted. It is more sensitive to the shape of the damaged area. It should be noted that in numerical simulation, the shape of the damaged area obtained by inversion gradually begins to diverge at both ends of the z-axis, and it is impossible to obtain a closed curve that reflects the original shape of the damaged area. This is because in numerical simulation, when the magnetization direction is along the x-axis, the leakage magnetic signal will attenuate at both ends of the z-axis direction of the damaged area. In actual measurement, if it is allowed to measure along the z-axis direction, the inversion curve in the corresponding direction can be obtained. The two can be superimposed to obtain a complete shape of the damaged area.

[0072] Based on the metal magnetic memory detection technology, the variation characteristics of weld seams in welded workpieces are tested. Based on the analysis of the force-magnetic mechanism of leakage magnetic signal changes, corresponding damage criteria are proposed. Damage evaluation parameters are obtained according to the gradient curve of leakage magnetic signal, numerical simulation is performed, and the damage zone is inverted using the proposed damage criteria and evaluation parameters, thereby improving detection efficiency and accuracy.

[0073] The present invention also provides a computer device, the computer device including a memory, a computer-readable storage medium, a processor, and a computer program stored on the memory and / or the computer-readable storage medium and executable on the processor, wherein the processor executes the program to implement the weld identification method based on metal magnetic memory detection technology as described above.

[0074] Compared with the prior art, the beneficial effects of the present invention are:

[0075] This invention presents a weld identification method based on metal magnetic memory detection technology. This method accurately locates the damage position and transverse and longitudinal width of welds in ferromagnetic material structures. It employs a matrix-type high-precision Hall element to directly measure the ferromagnetic material affected by the Earth's magnetic field magnetization, forming passive magnetization. This eliminates the need for active artificial magnetization of the structure, significantly reducing operating costs. A micro-statistical weld force-magnetic coupling constitutive model is established, requiring fewer material parameters for calculation. Using this model, combined with finite element analysis, numerical simulations and measurements are conducted to obtain leakage magnetic signal characteristics corresponding to uniform stress states and stress concentration states with elastoplastic strain. Comparison of calculation and experimental results verifies the effectiveness of the weld force-magnetic coupling constitutive model in identifying leakage magnetic parameters. Based on the measured leakage magnetic signal gradient, a damage criterion based on the metal magnetic memory detection method is established to obtain leakage magnetic signal evaluation parameters. An objective function is constructed to invert and reconstruct the size and location of weld defects, improving the efficiency and accuracy of identifying and detecting elastoplastic strain defects in welding. Attached Figure Description

[0076] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0077] In the attached diagram:

[0078] Figure 1 This is a flowchart of the weld identification method based on metal magnetic memory detection technology of the present invention;

[0079] Figure 2 This is a schematic diagram of the configuration of a computer device according to an embodiment of the present invention;

[0080] Figure 3 It is a diagram of the spontaneous magnetization state of magnetic domains within a ferromagnetic body;

[0081] Figure 4 It is a diagram of the magnetization state of magnetic domains in a ferromagnetic body under uniform stress from an external magnetic field Hext or an external load F.

[0082] Figure 5 It is a diagram of the non-uniform magnetization state when there is stress concentration or geometric defects in the ferromagnetic material;

[0083] Figure 6 It is a diagram of the random distribution of the initial magnetic domain structure;

[0084] Figure 7 It is a partial directional distribution diagram of magnetic domains at the damaged site, reflecting the degree of local damage, when a material suffers local physical damage due to stress concentration.

[0085] Figure 8 This is a schematic diagram of the dimensions of a two-dimensional model according to an embodiment of the present invention;

[0086] Figure 9 This is a graph showing the relationship between elastic-plastic strain and leakage magnetic signal in an embodiment of the present invention.

[0087] Figure 10 This is a gradient curve of the weld leakage magnetic flux signal according to an embodiment of the present invention;

[0088] Figure 11 This is a flowchart of the analysis of the force-magnetic mechanism of leakage magnetic signal change in step S5 of the present invention. Detailed Implementation

[0089] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0090] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0091] It should be understood that although the terms first, second, and third may be used in this disclosure to describe various signals, these signals should not be limited to these terms. These terms are used only to distinguish signals of the same type from one another. For example, a first signal may also be referred to as a second signal without departing from the scope of this disclosure, and similarly, a second signal may also be referred to as a first signal. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0092] This invention provides a weld identification method based on metal magnetic memory detection technology, see [link to relevant documentation]. Figure 1 As shown, it includes the following steps:

[0093] S1. Arrange magnetic signal detection sensors at the weld of the ferromagnetic material structural component to be tested, and detect the magnetic field strength at the weld.

[0094] S2. Using Hall elements, the detected magnetic field strength is input into an analog-to-digital converter for magneto-electric conversion based on the Hall effect, and the leakage magnetic signal of the weld of the ferromagnetic material structural component is collected.

[0095] The number of Hall elements is 81 to 144, forming a square array of 9×9 to 12×12. The distance between two adjacent Hall elements in the horizontal direction is 2.5 to 3 mm, and the distance between two adjacent Hall elements in the vertical direction is 1.2 to 1.6 mm.

[0096] S3. Noise reduction processing is performed on the leakage magnetic signal of the weld of the ferromagnetic material structural component to obtain the magnetic memory signal value at the weld of the ferromagnetic material structural component.

[0097] S4. Using the magnetic gradient tensor measurement and analysis method, the distribution and variation characteristics of the magnetic memory signal of the weld of the ferromagnetic material structural component are extracted to obtain the total magnetic field gradient and the magnetic tensor modulus gradient.

[0098] S5. Based on the distribution characteristics of the total magnetic field gradient and the magnetic tensor modulus gradient and the location of the extreme points of the magnetic memory signal, analyze the magnetic mechanism of the leakage magnetic signal change, propose damage criteria, obtain damage evaluation parameters according to the gradient curve of the leakage magnetic signal, perform numerical simulation, and use the proposed damage criteria and evaluation parameters to invert the damage area to determine the location and degree of damage of the weld of the ferromagnetic material structural component.

[0099] The method for analyzing the force-magnetic mechanism of leakage magnetic signal changes is described in [reference needed]. Figure 11 As shown, it includes the following steps:

[0100] A. By utilizing linear magnetoelastic energy to improve the Boltzmann distribution, a microscopic statistical model describing the ideal magnetization and magnetostriction of ferromagnetic cubic crystal materials is derived. A weld force-magnetic coupling constitutive model is constructed, and the effects of different stresses and material parameters on the ideal magnetization and magnetostriction coefficients are analyzed. The expression of the weld force-magnetic coupling constitutive model is as follows:

[0101] (1)

[0102] In equation (1), the total effective field H is... total Consider as an elastic field Plastic field and external magnetic field H H The three parts are superimposed: H is the external magnetic field, M is the magnetization intensity of the ferromagnet under the action of the external magnetic field, and σ1, σ2, and σ3 represent the three principal stress values, respectively. ,m,n represent the cosine angles between the three principal stresses and the magnetization direction; E is the absolute value of the atomic magnetic moment of a single magnetic domain; Let be the pinning energy that needs to be overcome for domain rotation, and its value be a material parameter; let the plastic strain be... The dislocation density N satisfies the following linear relationship:

[0103] (2)

[0104] In equation (2), k is a linear coefficient;

[0105] B. Experiments were conducted on the magnetic flux leakage signal of the welded specimen. The distribution characteristics of the magnetic flux leakage signal of the weld were numerically analyzed using the aforementioned weld force-magnetic coupling constitutive model and the finite element method. The effectiveness of the aforementioned weld force-magnetic coupling constitutive model in describing the magnetic flux leakage signal under uniform stress and concentrated stress was verified, and the characteristics of the magnetic flux leakage signal under uniform stress and under stress concentration were evaluated.

[0106] The method for numerically analyzing the distribution characteristics of weld leakage magnetic field signals using the finite element method includes: two-dimensional finite element numerical simulation analysis and three-dimensional finite element numerical simulation analysis.

[0107] The two-dimensional finite element numerical simulation analysis method includes: simulating and examining different stages of elastic and plastic deformation, the geometric characteristics of defect width, depth, and burial depth, as well as the influence of test direction and sensor lift-off value on the characteristics of leakage magnetic field signal changes using a two-dimensional model; assuming a coercive force H... c =56A / m, with relative permeabilities μ0 set from the center of the specimen outwards at 270, 374, and 527 respectively, and coercivity H =56A / m. c The values ​​were 335, 320, and 280 A / m, respectively, corresponding to plastic strains of 10.0%, 8.0%, and 3.0%.

[0108] The method for three-dimensional finite element numerical simulation analysis includes: without changing the planar dimensions of the two-dimensional model (see...). Figure 8 As shown, a finite thickness t is designed in the z-axis direction perpendicular to the paper to form a three-dimensional model. The three-dimensional effect of leakage magnetic signal is examined: the influence of thickness t. The relative permeability μ0 is set to 270, and the coercivity H is... c =335A / m, plastic strain is 8.0%.

[0109] In this embodiment, various specimen models with different weld thicknesses were selected for calculation to obtain the normal magnetic flux leakage signal. and tangential leakage magnetic signal The amplitude of the leakage magnetic field changes, and the value of the leakage magnetic field signal gradually increases with the increase of thickness t, but the shape does not change much. With the increase of thickness t, the peak-valley value of the normal leakage magnetic field gradient in the three-dimensional simulation increases. and tangential leakage magnetic gradient peak-to-peak value Both gradually tend towards two-dimensional results; the gradient characteristic width of the normal and tangential leakage magnetic signals and Basically unaffected by changes in thickness, the result of the two-dimensional model is the limit value of the three-dimensional model when the thickness t approaches infinity.

[0110] In this embodiment, the two-dimensional numerical simulation results show that magnetic memory detection is more sensitive to damage occurring on the surface of the specimen; the smaller the sensor lift-off value, the clearer the change in leakage magnetic field signal can be guaranteed; the specimen orientation has a slight effect on the leakage magnetic field amplitude, but almost no effect on the change in the gradient curve. (See [reference]). Figure 10 As shown; the numerical simulation results of the two-dimensional model are the limit values ​​when the thickness of the three-dimensional model approaches infinity; leakage magnetic field evaluation parameters and It can be used to invert the size and shape of the damaged area.

[0111] Numerical analysis of magnetic flux leakage signals in damaged samples was conducted using the finite element method. The results show that:

[0112] Magnetic memory detection is more sensitive to damage occurring on the surface of the specimen; during measurement, the sensor should be kept as close to the surface of the specimen as possible; the specimen orientation has no effect on the change of the leakage magnetic gradient curve; the evaluation parameters for characterizing the damage range proposed by the experimental results can be used to invert the size and shape of the damage area.

[0113] The method for evaluating the characteristics of leakage magnetic signals under uniform stress includes:

[0114] The magnitude of uniform stress is evaluated using the following three characteristic parameters:

[0115] (1) The slope of the normal leakage magnetic signal Hz along the trace parallel to the load direction (the slope increases with the increase of load).

[0116] (2) The gradient value of Hz along the trace parallel to the load direction;

[0117] (3) The amplitude of Hx variation along the traces parallel and perpendicular to the load direction.

[0118] The method for evaluating the characteristics of leakage magnetic signals under stress concentration conditions includes:

[0119] The degree and extent of stress concentration can be assessed using the following five characteristic parameters:

[0120] (1) The extent to which the vertical peak height of Hx along the traces parallel and perpendicular to the load direction increases with the increase of load;

[0121] (2) The degree to which the vertical peak difference between peaks increases as the load increases along the trace parallel to the load direction;

[0122] (3) The peak difference between peaks in the vertical direction along the trace parallel to the load direction of Hz;

[0123] (4) The vertical peak height of the single peak along the traces parallel and perpendicular to the load direction of Hx;

[0124] (5) Hz is the vertical peak height of a single peak located on both sides of the defect and along the trace perpendicular to the load direction.

[0125] In this implementation, the optimal parameter for assessing the degree and extent of stress concentration is: the peak-to-peak vertical difference along the trace parallel to the load direction.

[0126] C. Analyze the relationship between elastoplastic effective stress and leakage magnetic signal, and establish the relationship criteria between elastoplastic effective stress parallel to the load direction and leakage magnetic signal perpendicular to the load direction.

[0127] The method for establishing the relationship criteria between the elastoplastic effective stress parallel and perpendicular to the load direction and the leakage magnetic field signal includes:

[0128] The effectiveness of the comprehensive evaluation parameter between the effective elastoplastic stress parallel to the load direction and the leakage magnetic field signal is verified. A comprehensive evaluation parameter between the effective elastoplastic stress perpendicular to the load direction and the leakage magnetic field signal is proposed. The effective elastoplastic stress parallel to the load direction and perpendicular to the load direction is used to characterize the stress distribution in the load direction and the load direction.

[0129] D. Welded specimens with different weld defect sizes were tested, measured, and numerically analyzed. The sensitivity and correlation of the weld force-magnetic coupling constitutive model in describing leakage magnetic signals under different welding elastic-plastic stresses were analyzed to obtain the leakage magnetic signal characteristics of welding defects. (See [reference needed]). Figure 9 As shown;

[0130] E. Based on the gradient of the detected magnetic flux leakage signal, establish a damage criterion, obtain the evaluation parameters of the magnetic flux leakage signal, construct an objective function, and based on the weld force-magnetic coupling constitutive model, use the finite element method or genetic algorithm to invert and reconstruct the weld defects of the welded workpiece to identify the characteristics of the weld defects.

[0131] The damage criteria mentioned include: criteria for establishing the elastic stage and criteria for establishing the plastic stage;

[0132] The criteria for the elastic phase include: using the slope of the normal leakage magnetic signal. and tangential leakage flux amplitude To determine the stress amplitude in the elastic stage;

[0133] The criteria for the plastic stage include: at stress concentration sites, the normal leakage magnetic signal... Fluctuations occur, leakage magnetic gradient Extreme values ​​appear; tangential leakage magnetic signal Extreme values ​​appear, leakage magnetic gradient A peak-to-peak variation occurs, and the stress crosses zero at the center of the stress concentration.

[0134] During the elastic deformation stage, elastic stress promotes the orientation of magnetic domains along the direction of maximum tensile stress, thereby increasing the average magnetic induction intensity and spatial leakage magnetic field of the material. The damage criterion is that the normal leakage magnetic signal changes linearly along the loading direction, and the slope of the curve increases basically linearly. The slope of the tangential leakage magnetic signal curve remains basically unchanged, and the absolute value of the amplitude gradually increases and tends to a constant value.

[0135] During the plastic deformation stage, micro-defects such as dislocations and twins are formed inside the ferromagnetic material. The formation of micro-defects has a pinning effect, which hinders the magnetization of the ferromagnetic material and reduces its magnetic permeability. The damage criterion is that at the stress concentration site, the normal leakage magnetic signal shows a significant fluctuation, the leakage magnetic gradient shows an extreme value, the tangential leakage magnetic signal shows a significant extreme value, the leakage magnetic gradient shows a peak-to-peak change and crosses zero at the center of the stress concentration.

[0136] The method for obtaining the evaluation parameters of the leakage magnetic field signal includes:

[0137] Four evaluation parameters are defined: peak-valley value of normal leakage magnetic gradient. , width of normal leakage magnetic gradient Tangential leakage magnetic gradient peak-to-peak value , width of tangential leakage magnetic gradient .

[0138] The vertical distance between two opposing peaks in the gradient curve of the tangential leakage magnetic signal is denoted as . The horizontal spacing between two peaks in the gradient curve of the tangential leakage magnetic signal is the parameter. Used to evaluate the degree of non-uniformity in localized damage to materials. Used to evaluate the extent of localized damage to materials. The higher the value, the more severe the unevenness of the local damage; The higher the value, the larger the area of ​​localized damage. These four parameters can be used to effectively evaluate the degree of unevenness and extent of localized damage to materials.

[0139] Both the leakage magnetic field signal and its gradient curve can provide some characteristic parameters for evaluating the damage (including the degree and extent of damage), but the gradient curve can eliminate the influence of the external magnetic field and better reflect the degree of damage localization. The degree of damage localization can be evaluated using parameters such as peak-to-peak value, peak-to-valley value, and peak value on the leakage magnetic field signal gradient curve; the damage range can be evaluated using parameters such as peak-to-peak width, peak-to-valley width, and horizontal spacing of peak zero-crossing points.

[0140] The method for inverting and reconstructing weld defects in welded workpieces includes:

[0141] On the xz plane of the welded workpiece surface, measurement traces with an interval of 0.4 mm and parallel to the x-axis are set for different z coordinates. The normal leakage magnetic signal and the tangential leakage magnetic signal on each trace are calculated and extracted. The gradient curve changes of the normal leakage magnetic signal and the tangential leakage magnetic signal are obtained by differentiation.

[0142] Evaluation parameters for obtaining the leakage magnetic field gradient curve on each measurement trace. and The shape of the damaged area is inverted. It is more sensitive to the shape of the damaged area. It should be noted that in numerical simulation, the shape of the damaged area obtained by inversion gradually begins to diverge at both ends of the z-axis, and it is impossible to obtain a closed curve that reflects the original shape of the damaged area. This is because in numerical simulation, when the magnetization direction is along the x-axis, the leakage magnetic signal will attenuate at both ends of the z-axis direction of the damaged area. In actual measurement, if it is allowed to measure along the z-axis direction, the inversion curve in the corresponding direction can be obtained. The two can be superimposed to obtain a complete shape of the damaged area.

[0143] S6. Output the identification and detection results of leakage magnetic signals.

[0144] This invention's weld identification method based on metal magnetic memory detection technology can accurately locate the damage position and transverse and longitudinal width of welds in ferromagnetic material structures. It employs a matrix-type high-precision Hall element to directly measure the ferromagnetic material affected by the Earth's magnetic field magnetization, forming passive magnetization. This eliminates the need for active artificial magnetization of the structure, significantly reducing operating costs. Furthermore, a micro-statistical weld force-magnetic coupling constitutive model is established. This model requires fewer material parameters for calculation. Using this model, combined with finite element calculations, numerical simulations and detection measurements are used to obtain the leakage magnetic signal characteristics corresponding to uniform stress states and stress concentration states with elastoplastic strain. Comparison of calculation and experimental results verifies the effectiveness of the weld force-magnetic coupling constitutive model in identifying leakage magnetic parameters. Based on the measured leakage magnetic signal gradient, a damage criterion based on the metal magnetic memory detection method is established to obtain leakage magnetic signal evaluation parameters. An objective function is constructed to invert and reconstruct the size and location of weld defects, improving the efficiency and accuracy of identifying and detecting elastoplastic strain defects in welding.

[0145] This invention also provides a computer device. Figure 2 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention; see the accompanying drawings. Figure 2 As shown, the computer device includes: an input device 23, an output device 24, a memory 22, and a processor 21; the memory 22 is used to store one or more programs; when the one or more programs are executed by the one or more processors 21, the one or more processors 21 implement the weld identification method based on metal magnetic memory detection technology provided in the above embodiments; wherein the input device 23, the output device 24, the memory 22, and the processor 21 can be connected via a bus or other means. Figure 2 Taking the example of a connection between China and Israel via a bus.

[0146] The memory 22, as a read / write storage medium for a computing device, can be used to store software programs and computer-executable programs, such as the program instructions corresponding to the weld identification method based on metal magnetic memory detection technology described in this embodiment of the invention. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device. Furthermore, the memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 22 may further include memory remotely located relative to the processor 21, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0147] The input device 23 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device; the output device 24 may include display devices such as a display screen.

[0148] The processor 21 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 22, thereby realizing the above-mentioned weld seam identification method based on metal magnetic memory detection technology.

[0149] The computer equipment provided above can be used to execute the weld identification method based on metal magnetic memory detection technology provided in the above embodiments, and has corresponding functions and beneficial effects.

[0150] This invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the weld identification method based on metal magnetic memory detection technology provided in the above embodiments. The storage medium can be any type of memory device or storage device, including: mounting media such as CD-ROM, floppy disk, or magnetic tape; computer system memory or random access memory such as DRAM, DDRRAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements; the storage medium may also include other types of memory or combinations thereof; furthermore, the storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet); the second computer system can provide program instructions to the first computer for execution. The storage medium includes two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0151] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the weld identification method based on metal magnetic memory detection technology as described in the above embodiments, but can also perform related operations in the weld identification method based on metal magnetic memory detection technology provided in any embodiment of the present invention.

[0152] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make the same modifications or substitutions to the relevant technical features, and the technical solutions after these modifications or substitutions will all fall within the scope of protection of the present invention.

[0153] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A weld seam identification method based on metal magnetic memory detection technology, characterized in that, Includes the following steps: S1. Arrange magnetic signal detection sensors at the weld of the ferromagnetic material structural component to be tested, and detect the magnetic field strength at the weld. S2. Using Hall elements, the detected magnetic field strength is input into an analog-to-digital converter for magneto-electric conversion based on the Hall effect, and the leakage magnetic signal of the weld of the ferromagnetic material structural component is collected. The number of Hall elements is 81 to 144, forming a square array of 9×9 to 12×12. The distance between two adjacent Hall elements in the horizontal direction is 2.5 to 3 mm, and the distance between two adjacent Hall elements in the vertical direction is 1.2 to 1.6 mm. S3. Noise reduction processing is performed on the leakage magnetic signal of the weld of the ferromagnetic material structural component to obtain the magnetic memory signal value at the weld of the ferromagnetic material structural component. S4. Using the magnetic gradient tensor measurement and analysis method, the distribution and variation characteristics of the magnetic memory signal of the weld of the ferromagnetic material structural component are extracted to obtain the total magnetic field gradient and the magnetic tensor modulus gradient. S5. Based on the distribution characteristics of the total magnetic field gradient and the magnetic tensor modulus gradient and the location of the extreme points of the magnetic memory signal, analyze the magnetic mechanism of the leakage magnetic signal change, propose damage criteria, obtain damage evaluation parameters according to the gradient curve of the leakage magnetic signal, perform numerical simulation, and use the proposed damage criteria and evaluation parameters to invert the damage area to determine the location and degree of damage of the weld of the ferromagnetic material structural component. S6. Output the identification and detection results of leakage magnetic field signal; The method for analyzing the magnetic mechanism of leakage magnetic signal changes in step S5 includes the following steps: A. By utilizing linear magnetoelastic energy to improve the Boltzmann distribution, a microscopic statistical model describing the ideal magnetization and magnetostriction of ferromagnetic cubic crystal materials is derived. A weld force-magnetic coupling constitutive model is constructed, and the effects of different stresses and material parameters on the ideal magnetization and magnetostriction coefficients are analyzed. The expression of the weld force-magnetic coupling constitutive model is as follows: （1） In equation (1), the total effective field H is... total Consider as an elastic field Plastic field and external magnetic field H H The three parts are superimposed: H is the external magnetic field, M is the magnetization intensity of the ferromagnet under the action of the external magnetic field, and σ1, σ2, and σ3 represent the three principal stress values, respectively. , m, n represent the cosine angles between the three principal stresses and the magnetization direction; E is the absolute value of the atomic magnetic moment of a single magnetic domain; Let be the pinning energy that needs to be overcome for domain rotation, and its value be a material parameter; let the plastic strain be... The dislocation density N satisfies the following linear relationship: （2） In equation (2), k is a linear coefficient; B. Experiments were conducted on the magnetic flux leakage signal of the welded specimen. The distribution characteristics of the magnetic flux leakage signal of the weld were numerically analyzed using the aforementioned weld force-magnetic coupling constitutive model and the finite element method. The effectiveness of the aforementioned weld force-magnetic coupling constitutive model in describing the magnetic flux leakage signal under uniform stress and concentrated stress was verified, and the characteristics of the magnetic flux leakage signal under uniform stress and under stress concentration were evaluated. C. Analyze the relationship between elastoplastic effective stress and leakage magnetic signal, and establish the relationship criteria between elastoplastic effective stress parallel to the load direction and leakage magnetic signal perpendicular to the load direction. D. Conduct detection, measurement, and numerical analysis calculations on welded specimens containing different weld defect sizes, analyze the sensitivity and correlation of the weld force-magnetic coupling constitutive model to describe the leakage magnetic signal under different welding elastic-plastic stresses, and obtain the leakage magnetic signal characteristics of welding defects. E. Based on the gradient of the detected magnetic flux leakage signal, establish a damage criterion, obtain the evaluation parameters of the magnetic flux leakage signal, construct an objective function, and based on the weld force-magnetic coupling constitutive model, use the finite element method or genetic algorithm to invert and reconstruct the weld defects of the welded workpiece to identify the characteristics of the weld defects.

2. The weld identification method based on metal magnetic memory detection technology according to claim 1, characterized in that, The method for numerical analysis of the distribution characteristics of weld leakage magnetic field signal using the finite element method in step B includes: two-dimensional finite element numerical simulation analysis and three-dimensional finite element numerical simulation analysis. The two-dimensional finite element numerical simulation analysis method includes: simulating and examining different stages of elastic and plastic deformation, the geometric characteristics of defect width, depth, and burial depth, as well as the influence of test direction and sensor lift-off value on the characteristics of leakage magnetic field signal changes using a two-dimensional model; assuming a coercive force H... c =56A / m, with relative permeabilities μ0 set from the center of the specimen outwards at 270, 374, and 527 respectively, and coercivity H =56A / m. c The values ​​were 335, 320, and 280 A / m, respectively, corresponding to plastic strains of 10.0%, 8.0%, and 3.0%. The method for three-dimensional finite element numerical simulation analysis includes: without changing the planar dimensions of the two-dimensional model, designing a finite thickness t in the z-axis direction perpendicular to the paper to form a three-dimensional model, examining the three-dimensional effect of leakage magnetic signal: the influence of thickness t, setting the relative permeability μ0 to 270, and the coercivity H... c =335A / m, plastic strain is 8.0%.

3. The weld identification method based on metal magnetic memory detection technology according to claim 1, characterized in that, The method for evaluating the characteristics of magnetic flux leakage signals under uniform stress conditions in step B includes: The magnitude of uniform stress is evaluated using the following three characteristic parameters: (1) The slope of the normal leakage magnetic signal Hz along the trace parallel to the load direction; (2) The gradient value of Hz along the trace parallel to the load direction; (3) The amplitude of Hx variation along the traces parallel and perpendicular to the load direction.

4. The weld identification method based on metal magnetic memory detection technology according to claim 1, characterized in that, The method for evaluating the characteristics of leakage magnetic signals under stress concentration conditions in step B includes: The degree and extent of stress concentration can be assessed using the following five characteristic parameters: (1) The extent to which the vertical peak height of Hx along the traces parallel and perpendicular to the load direction increases with the increase of load; (2) The degree to which the vertical peak difference between peaks increases as the load increases along the trace parallel to the load direction; (3) The peak difference between peaks in the vertical direction along the trace parallel to the load direction of Hz; (4) The vertical peak height of the single peak along the traces parallel and perpendicular to the load direction of Hx; (5) Hz is the vertical peak height of a single peak located on both sides of the defect and along the trace perpendicular to the load direction.

5. The weld identification method based on metal magnetic memory detection technology according to claim 1, characterized in that, The method for establishing the relationship criteria between the elastoplastic effective stress parallel and perpendicular to the load direction and the leakage magnetic signal in step C includes: The effectiveness of the comprehensive evaluation parameter between the effective elastoplastic stress parallel to the load direction and the leakage magnetic field signal is verified. A comprehensive evaluation parameter between the effective elastoplastic stress perpendicular to the load direction and the leakage magnetic field signal is proposed. The effective elastoplastic stress parallel to the load direction and perpendicular to the load direction is used to characterize the stress distribution in the load direction and the load direction.

6. The weld identification method based on metal magnetic memory detection technology according to claim 1, characterized in that, The damage criteria established in step E include: criteria for establishing the elastic stage and criteria for establishing the plastic stage; The criteria for the elastic phase include: using the slope of the normal leakage magnetic signal. and tangential leakage flux amplitude To determine the stress amplitude in the elastic stage; The criteria for the plastic stage include: at stress concentration sites, the normal leakage magnetic signal... Fluctuations occur, leakage magnetic gradient Extreme values ​​appear; tangential leakage magnetic signal Extreme values ​​appear, leakage magnetic gradient A peak-to-peak variation occurs, and the stress crosses zero at the center of the stress concentration.

7. The weld identification method based on metal magnetic memory detection technology according to claim 1 or 5, characterized in that, The method for obtaining the leakage magnetic field signal evaluation parameters in step E includes: Four evaluation parameters are defined: peak-valley value of normal leakage magnetic gradient. , width of normal leakage magnetic gradient Tangential leakage magnetic gradient peak-to-peak value , width of tangential leakage magnetic gradient .

8. The weld identification method based on metal magnetic memory detection technology according to claim 7, characterized in that, The method for inverting and reconstructing weld defects in the welded workpiece in step E includes: On the xz plane of the welded workpiece surface, measurement traces with an interval of 0.4 mm and parallel to the x-axis are set for different z coordinates. The normal leakage magnetic signal and the tangential leakage magnetic signal on each trace are calculated and extracted. The gradient curve changes of the normal leakage magnetic signal and the tangential leakage magnetic signal are obtained by differentiation. Evaluation parameters for obtaining the leakage magnetic field gradient curve on each measurement trace. and The shape of the damaged area is inverted. It is the width of the tangential leakage magnetic gradient. It is the gradient characteristic width of the normal leakage magnetic signal.

9. A computer device, the computer device comprising a memory, a computer-readable storage medium, a processor, and a computer program stored on the memory and / or the computer-readable storage medium and executable on the processor, characterized in that, When the processor executes the program, it implements the weld identification method based on metal magnetic memory detection technology as described in any one of claims 1-8.

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