A method for magnetic memory signal feature analysis of a pipe weld

Abstract

The application provides a method for magnetic memory signal feature analysis of a pipeline weld, according to an established welding simulation model of the pipeline weld, residual stress and metal phase change distribution of the pipeline weld after welding and cooling are calculated, the influence of the metal phase change and the residual stress on the material hysteresis feature is analyzed, the magnetic charge density under the combined action of the stress and the phase change is determined based on the hysteresis feature principle, and the magnetic memory analysis model under the coupling of multiple parameters is established. The tangential and normal magnetic signal components at the weld caused by the magnetization effect are calculated based on the established model. The magnetic field strength gradient K is calculated according to the calculated magnetic signal components, and the magnetic field strength gradient can be used for analyzing the damage degree of the weld, thereby providing a basis for further maintenance decision.

Description

Technical Field

[0001] This invention belongs to the field of pipeline nondestructive testing technology, specifically relating to a method for magnetic memory signal feature analysis of pipeline welds. Background Technology

[0002] Long-distance oil and gas pipelines are the "lifeblood" of energy, playing a vital role in promoting economic development, improving people's living standards, and ensuring national defense. Welds are among the weakest points in pipelines, and coupled with additional loads such as soil movement, weld failures are frequent. Pipeline failure can cause enormous loss of life and property, as well as environmental pollution. According to statistics on pipeline accidents in recent years, weld failure is one of the main causes of leaks and bursts in long-distance oil and gas pipelines.

[0003] Magnetic memory (MM) is an emerging nondestructive testing (NDT) technology that has been successfully applied in the detection of micro-damage in long-distance oil and gas pipelines. The MMT signal at pipeline welds is influenced by factors such as material phase transformation, residual stress, and cracks. After high-temperature welding, the microstructure of the weld region changes significantly compared to the substrate, with martensite proliferation occurring. Since martensite grains are smaller than ferrite grains, smaller grain sizes in the sample microstructure result in more internal grain boundaries per unit area, leading to a decrease in magnetic permeability. Simultaneously, the grain volume change in the weld region causes stress interactions between microstructures, generating residual stress in and around the weld region. Under the influence of the Earth's magnetic field, stress concentration areas in metallic materials will experience spontaneous rotation of magnetic domains, forming magnetic poles to offset some of the elastic energy from stress concentration. Existing models cannot analyze the distribution of magnetic signals under the combined effects of non-uniform material microstructure, residual stress, and cracks. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to provide a method for magnetic memory signal feature analysis of pipeline welds, which can solve the problem that existing models cannot analyze the magnetic signal distribution law under the co-coupling of non-uniform material microstructure, residual stress, and cracks.

[0005] To address the aforementioned problems, this invention provides a method for magnetic memory signal feature analysis of pipe welds, specifically comprising the following steps:

[0006] Step 1: Establish a finite element welding simulation model of the pipeline weld. Based on the simulation model, calculate the residual stress and metal phase transformation distribution at the weld.

[0007] Step 2: Establish a weld magnetic memory field analysis model under multi-parameter coupling conditions based on the principle of hysteresis characteristics;

[0008] Step 2.1: Based on the residual stress and metal phase transformation distribution at the weld, calculate the residual stress magnetic charge density and phase transformation magnetic charge density respectively;

[0009] Step 2.2: Establish a multi-parameter coupled analysis model based on the principle of hysteresis characteristics, input the magnetic charge density into the model, and calculate the magnetic signal, which is the normal magnetic signal and the tangential magnetic signal;

[0010] Step 3: Calculate the normal magnetic field intensity gradient and the tangential magnetic field intensity gradient based on the normal magnetic signal and the tangential magnetic signal, respectively.

[0011] Optionally, step 1 specifically includes:

[0012] To establish a finite element welding simulation model for pipeline welds, the following steps are required: model creation and mesh generation, selection of material property parameters, setting of welding process parameters, setting of boundary conditions, and extraction of results.

[0013] Optionally, step 2.1: Calculate the magnetic charge density based on the residual stress and metal phase transformation distribution at the weld, as follows:

[0014] The magnetic charge density of ferromagnetic materials under the influence of phase transition, according to magnetic charge theory, satisfies the following equation:

[0015]

[0016] Where ρ(x1) is the distribution equation of magnetic charge density along the x-direction caused by the change in the material's own magnetic permeability, μ0 is the magnetic permeability, and M... f f is the magnetization of the material. m H represents the volume fraction of phase change in the material. total The equivalent field strength is given by α, and α is the magnetization model parameter (in A / m).

[0017] The magnetic charge density of a ferromagnetic material under stress, according to magnetic charge theory, satisfies the following equation:

[0018]

[0019] ρ(x2) is the distribution equation of magnetic charge density along the x-direction caused by the change in residual stress, σ is the magnitude of residual stress, and M an M is the hysteresis-free magnetization, c is the actual magnetization, c reflects the flexibility coefficient of the domain wall, ξ' is the energy-related coefficient, E is the elastic modulus, and the parameter η considers the influence of stress on the irreversible magnetization change. Its specific value will be affected by a variety of factors, including the manufacturing process of the pipe material, the heat treatment method, and the chemical composition. Taking X70 pipe as an example, η can be taken as 0.1 under tensile stress.

[0020] The magnetic charge density of a material is affected by both microstructure changes and residual stress. The sum of the magnetic charge densities at the same location is the total magnetic charge density ρ(x) at that location, which can then be expressed as:

[0021] ρ(x) = ρ(x1) + ρ(x2)

[0022] Where ρ(x1) is the distribution equation of magnetic charge density along the x direction caused by the change in the material's own magnetic permeability, ρ(x2) is the distribution equation of magnetic charge density along the x direction caused by the change in residual stress, and ρ(x) is the total magnetic charge density at the weld affected by the coupling of residual stress and metal phase transformation.

[0023] Optionally, step 2.2: Establish a multi-parameter coupled analysis model based on the principle of magnetic hysteresis characteristics, input the magnetic charge density into the model, and calculate the magnetic signal. The magnetic signal consists of normal magnetic signal and tangential magnetic signal. If there are no cracks in the weld, the magnetic signal in the weld area is affected by metal phase transformation and residual stress, as follows:

[0024] Along the tangential H x and normal direction H y The magnetic signal components are as follows:

[0025]

[0026]

[0027] Where L is the axial length of the specimen, δ is the thickness of the specimen, θ is the circumferential angle of the pipe weld, ranging from θ1 to θ2, θ1 to θ2 is the circumferential length of the weld, D is the outer diameter of the pipe, R is the outer radius of the pipe, (x S1 ,y S1 ,z S1 ) and (x S2 ,y S2 ,z S2 The coordinates of the source points of the magnetic charge surfaces S1 and S2 generated by the weld are given, and (x,y,z) are the coordinates of the detection point P(x,y,z).

[0028] Optionally, step 2.2: Establish a multi-parameter coupled analysis model based on the principle of magnetic hysteresis characteristics, input the magnetic charge density into the model, and calculate the magnetic signal, which consists of normal magnetic signal and tangential magnetic signal. If cracks appear in the weld, the specific method is as follows:

[0029] Before the ferromagnetic specimen fails, the magnetization effect causes tangential H... x and normal direction H y The magnetic signal components are as follows:

[0030]

[0031]

[0032] Where l is the crack length, d is the crack depth, θ3~θ4 is the circumferential length of the crack, (x S3 ,y S3 ,z S3 ) and (x S4 ,y S4 ,z S4 (x,y,z) represents the coordinates of the source points S3 and S4 of the magnetic charge surfaces generated by the crack, and (x,y,z) represents the coordinates of the detection point P(x,y,z).

[0033] Optionally, step 3: Based on the normal magnetic signal and the tangential magnetic signal, calculate the normal magnetic field intensity gradient and the tangential magnetic field intensity gradient, respectively, as follows:

[0034] Based on the leakage magnetic field at the weld calculated in step 2.2, since the magnetic field strength at the weld changes, the magnetic field strength gradient also changes. The formula for calculating the magnetic field strength gradient is as follows:

[0035]

[0036] In the formula, K is the magnetic field strength gradient value; |ΔH p (y)| represents the difference in magnetic field strength between two adjacent measurement points; Δl k This represents the distance between two adjacent measurement points.

[0037] Beneficial effects

[0038] This invention provides a method for analyzing magnetic memory signal characteristics of pipeline welds. Based on an established pipeline weld simulation model, it calculates the residual stress and metal phase transformation distribution at the weld after welding cooling, analyzes the influence of metal phase transformation and residual stress on the material's magnetic hysteresis characteristics, and determines the magnetic charge density under the combined effects of stress and phase transformation based on the principle of magnetic hysteresis characteristics. A multi-parameter coupled magnetic memory analysis model is established. Based on the established model, the tangential and normal magnetic signal components at the weld caused by magnetization are calculated. The magnetic field strength gradient K is calculated based on the calculated magnetic signal components. This magnetic field strength gradient can be used to analyze the degree of damage at the weld, providing a basis for further maintenance decisions and solving the problem that existing models cannot analyze the magnetic signal distribution under the combined coupling of non-uniform material microstructure, residual stress, and cracks. Attached Figure Description

[0039] Figure 1 This is a flowchart of the finite element welding simulation of pipe welds according to an embodiment of the present invention;

[0040] Figure 2 A schematic diagram illustrating the model and mesh generation in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram illustrating the boundary condition setting in an embodiment of the present invention;

[0042] Figure 4 This is a schematic diagram illustrating the extraction of residual stress results in an embodiment of the present invention;

[0043] Figure 5 This is a schematic diagram illustrating the extraction of metal phase transformation results according to an embodiment of the present invention;

[0044] Figure 6 This is a schematic diagram of the weld magnetic charge distribution according to an embodiment of the present invention;

[0045] Figure 7 This is a schematic diagram comparing the improved model with the traditional model when the weld has no cracks, according to an embodiment of the present invention.

[0046] Figure 8 This is a schematic diagram comparing the improved model with the traditional model when the weld has cracks, according to an embodiment of the present invention.

[0047] Figure 9 This is a schematic diagram illustrating the changes in magnetic gradient under different stresses according to an embodiment of the present invention;

[0048] Figure 10 This is a flowchart of the weld magnetic memory signal analysis according to an embodiment of the present invention. Detailed Implementation

[0049] See also Figures 1 to 10 As shown in the embodiments of the present invention, a method for magnetic memory signal feature analysis of pipeline welds is provided. This application establishes a multi-parameter coupled magnetic signal theoretical analysis model to describe the influence of stress, metal phase transformation, and cracks on the magnetic signal during magnetic memory detection. The analytical solution of the multi-parameter coupled magnetic signal theoretical model is achieved, and the accuracy of the model calculation is verified through experiments. This research method can provide a scientific basis for applications in the field of weld magnetic memory detection and weld damage evaluation.

[0050] Specifically, this includes: based on the established simulation model of pipeline welds, calculating the residual stress and metal phase transformation distribution at the weld after welding cooling; analyzing the influence of metal phase transformation and residual stress on the magnetic hysteresis characteristics of the material; and determining the magnetic charge density under the combined action of stress and phase transformation based on the principle of magnetic hysteresis characteristics, establishing a magnetic memory analysis model under multi-parameter coupling. The influence of the phase transformation volume ratio, residual stress, and cracks at the weld on the characteristic values ​​of the magnetic signal is quantitatively calculated. This provides a basis for pipeline weld fault diagnosis.

[0051] Step 1: Establish a finite element welding simulation model of the pipeline weld. Based on the simulation model, calculate the residual stress and metal phase transformation distribution at the weld.

[0052] like Figure 1 As shown, further steps are needed to establish a finite element welding simulation model for the pipeline weld, which requires model creation and mesh generation, selection of material performance parameters, setting of welding process parameters, setting of boundary conditions, and extraction of results.

[0053] (1) Model building and mesh generation

[0054] Please refer to Figure 2 The temperature changes drastically during pipeline welding, therefore the mesh generation directly affects the calculation and analysis results. Due to the large temperature gradient and complex stress-strain changes in the weld zone, this paper adopts a fine mesh generation for the weld joint area to ensure the accuracy of numerical calculations, while using a coarser mesh in the base material portion far from the weld. Furthermore, the mesh primarily uses hexahedral elements, minimizing the use of tetrahedral elements to avoid function non-convergence issues.

[0055] (2) Selection of material performance parameters

[0056] For material performance parameters, X70 high-strength low-alloy steel is selected, which has high strength and hardness while maintaining a low alloy content, and possesses good weldability and machinability. It is suitable for the harsh environments of long-distance oil and gas pipelines under high temperature and pressure. The basic mechanical properties of X70 pipe are shown in Table 1:

[0057]

[0058] (3) Welding process parameters

[0059] The weld bevel shape is V-shaped, the welding method is submerged arc welding, the welding voltage U is 25V, the welding current I is 200A, the welding speed is 10mm / s, and the ambient temperature is 25℃. A double ellipsoidal heat source model is adopted, which satisfies the following equations:

[0060]

[0061]

[0062] In the formula, q is the heat flux, J / (m³). 2 ·s); x, y, z are coordinates relative to the center of the heat source; a f a is the front length of the ellipsoid, in mm; r denoted as ellipsoid, mm; b is half the width of the ellipsoid, mm; c is the depth of the ellipsoid, mm; Q is the effective power at the depth of the ellipsoid, W.

[0063] (4) Boundary condition setting

[0064] Please refer to Figure 3The structural boundary conditions employ full constraint using circular tubes on both sides to prevent rigid displacement of the model during calculation. The temperature field condition is set to allow heat exchange with the air, with an ambient temperature of 25℃.

[0065] (5) Result extraction

[0066] Based on the established finite element model, a moving thermal load was applied to the weld to simulate welding, and the residual stress distribution and metal phase transformation distribution after welding were simulated and calculated. The result extraction path is the axial direction of the pipe, starting from the leftmost end of the model pipe, passing through the weld to the rightmost end, and the residual stress and metal phase transformation along the extraction path are extracted.

[0067] Step 2: Establish a magnetic memory field analysis model for welds under multi-parameter coupling conditions based on the principle of hysteresis characteristics.

[0068] Furthermore, traditional weld analysis models only consider the influence of residual stress on the magnetic memory signal, thus neglecting the coupling effect of other parameters in the weld. This is not conducive to accurately analyzing the damage level at the weld. To further and more accurately analyze the characteristics of the magnetic memory signal at the weld, three parameters that affect the magnetic memory signal at the weld were studied and analyzed: residual stress, metal phase transformation, and cracks. To highlight the differences between the traditional analysis model and the multi-parameter coupling model, a detailed analysis of the establishment and calculation results of the multi-parameter coupling model is presented below.

[0069] Before establishing a magnetic memory signal analysis model, it is necessary to analyze two scenarios: the presence of cracks and the absence of cracks in the weld. When the weld is crack-free, the weld surface is intact, and the main influencing parameters causing the presence of magnetic memory signals are residual stress and metal phase transformation. When there are cracks in the weld, the weld surface is fractured, and the magnetic memory signal at the weld is a result of the multi-parameter coupling effect of residual stress, metal phase transformation, and cracks.

[0070] Furthermore, when there are no cracks at the weld, the parameters affecting the magnetic memory signal are residual stress and metal phase transformation. The magnitude and distribution of residual stress and metal phase transformation at the weld are calculated using a simulation model, as shown below. Figure 4 and Figure 5 As shown. Figure 4 The diagram shown is a distribution map of residual welding stress. Figure 5 The diagram shows the phase transformation distribution of the weld metal. It can be seen from the figure that the residual stress in the weld exhibits a Gaussian distribution with a large value at the weld ends and a small value at both ends, with the stress at the weld being approximately 260 MPa. The phase transformation in the weld also exhibits a Gaussian distribution with a large value at the weld ends and a small value at both ends, with the martensitic transformation ratio at the weld being approximately 45%.

[0071] Step 2.1: Calculate the magnetic charge density based on the residual stress and metal phase transformation distribution at the weld. Based on the residual stress and metal phase transformation magnitude and distribution calculated by the above simulation, calculate the influence of residual stress and metal phase transformation on the material's magnetic hysteresis characteristics in combination with the principle of magnetic hysteresis.

[0072] Furthermore, the effects of residual stress and metallic phase transformation on the material's magnetic hysteresis properties were calculated using the principle of magnetic hysteresis characteristics. Based on this principle, a multi-parameter coupled magnetic memory field analysis model for the weld was established, and the variation patterns of the magnetic memory signal in the weld and its surrounding area were comprehensively analyzed.

[0073] The process is as follows:

[0074] Defects in ferromagnetic materials exhibit three-dimensional characteristics: length, width, and depth. In the weld region of a pipe, the material's magnetic permeability decreases and magnetic charge accumulates due to material phase transformation and residual stress, thus forming new magnetic poles at both ends of the weld. Therefore, before conducting magnetic memory analysis of the weld, it is necessary to first analyze the influence of residual stress and metal phase transformation on the material's magnetic charge density.

[0075] The magnetic charge density of ferromagnetic materials under the influence of phase transition, according to magnetic charge theory, satisfies the following equation:

[0076]

[0077] Where ρ(x1) is the distribution equation of magnetic charge density along the x-direction caused by the change in the material's own magnetic permeability, μ0 is the magnetic permeability, and M... f f is the magnetization of the material. m H represents the volume fraction of phase change in the material. total denoted as the equivalent field strength, and 'a' as the magnetization model parameter (unit: A / m).

[0078] The magnetic charge density of a ferromagnetic material under stress, according to magnetic charge theory, satisfies the following equation:

[0079]

[0080] ρ(x2) is the distribution equation of magnetic charge density along the x-direction caused by the change in residual stress, σ is the magnitude of residual stress, and M an M is the hysteresis-free magnetization, c is the actual magnetization, c reflects the flexibility coefficient of the domain wall, ξ' is the energy-related coefficient, E is the elastic modulus, and the parameter η considers the influence of stress on the irreversible magnetization change. Its specific value will be affected by a variety of factors, including the manufacturing process of the pipe material, the heat treatment method, and the chemical composition. Taking X70 pipe as an example, η can be taken as 0.1 under tensile stress.

[0081] The magnetic charge density of a material is affected by both microstructure changes and residual stress. The sum of the magnetic charge densities at the same location is the total magnetic charge density ρ(x) at that location, which can then be expressed as:

[0082] ρ(x) = ρ(x1) + ρ(x2)

[0083] like Figure 6 As shown, ρ(x1) is the distribution equation of magnetic charge density along the x-direction caused by the change in the material's own magnetic permeability, and ρ(x2) is the distribution equation of magnetic charge density along the x-direction caused by the change in residual stress. ρ(x) is the total magnetic charge density at the weld affected by the coupling of residual stress and metal phase transformation.

[0084] Step 2.2: Establish a multi-parameter coupled analysis model based on the principle of hysteresis characteristics, input the magnetic charge density into the model, and calculate the magnetic signal, which is the normal magnetic signal and the tangential magnetic signal.

[0085] When the weld is crack-free, the magnetic signal in the weld region is mainly affected by the metal phase transformation and residual stress. Due to the magnetization effect of the metal phase transformation and residual stress on the ferromagnetic material, magnetic charges with opposite polarities and equal densities will appear on both sides of the specimen. Based on the magnetic dipole theory, an analytical solution for the magnetic signal induced by this magnetic charge distribution can be obtained. Before the ferromagnetic specimen fails, the magnetic signal along the tangential H direction is caused by the magnetization effect. x and normal direction H y The magnetic signal components are as follows:

[0086]

[0087]

[0088] Substituting the magnetic charge density of the metal phase transformation and residual stress calculated in step 2.1 into the above model yields the magnetic signals under different stresses or phase transformations.

[0089] Where L is the axial length of the specimen, δ is the thickness of the specimen, θ is the circumferential angle of the pipe weld, ranging from θ1 to θ2, θ1 to θ2 is the circumferential length of the weld, D is the outer diameter of the pipe, R is the outer radius of the pipe, (x S1 ,y S1 ,z S1 ) and (x S2 ,y S2 ,z S2 The coordinates of the source points of the magnetic charge surfaces S1 and S2 generated by the weld are given, and (x,y,z) are the coordinates of the detection point P(x,y,z).

[0090] When a crack appears in the weld, it leads to a loss of material in the weld area. The magnetic path is broken at the crack, causing new magnetic poles to form on both sides of the crack. This results in a sudden change in the magnetic field at the crack location. Based on the theory of magnetic dipoles, an analytical solution for the magnetic signal induced by this magnetic charge distribution can be obtained. Before the ferromagnetic specimen fails, the magnetization effect causes a magnetic field along the tangential H... x and normal direction H y The magnetic signal components are as follows:

[0091]

[0092]

[0093] Where l is the crack length, d is the crack depth, θ3~θ4 is the circumferential length of the crack, (x S3 ,y S3 ,z S3 ) and (x S4 ,y S4 ,z S4 (x,y,z) represents the coordinates of the source points S3 and S4 where the crack was generated. (x,y,z) represents the coordinates of the detection point P(x,y,z).

[0094] To highlight the effectiveness of the improved model, calculations were performed on the improved model, and the results were compared with those of the traditional model. For example... Figure 7 and Figure 8 As shown.

[0095] Figure 7 This figure compares the improved model with the traditional model when the weld is crack-free. The value of 260MPa+0%0fm in the figure represents the result calculated using the traditional model, which only considers the effect of residual stress and thus ignores the influence of metal phase transformation. Figure 7 The phase transition varies from 10%fm to 50%fm. The peak-to-peak values ​​of the normal and tangential components of the magnetic signal increase with the increase of the phase transition ratio. Specifically, for every 10% increase in the phase transition ratio, the average increase in the peak-to-valley value of the normal component is 20.30, and the average increase in the peak-to-valley value of the tangential component is 17.01, while the peak-to-valley spacing remains unchanged.

[0096] Figure 8 This figure compares the improved model with the traditional model when weld cracks are present. As can be seen from the figure, the presence of weld cracks does not alter the overall magnetic memory signal characteristics of the weld. However, when a crack appears in the weld, the normal component exhibits dual peak-valley values: the inner peak-valley value represents the crack characteristic, and the outer peak-valley value represents the weld characteristic; the tangential component shows a maximum value at the crack center. Specifically, for every 1 mm increase in crack depth, the average increase in the inner peak-valley value of the normal component is 24.87, and the average increase in the central peak value of the tangential component is 8.76, while the peak-valley spacing remains unchanged.

[0097] from Figure 7 and Figure 8 It is evident that both the phase transformation parameters and crack parameters of the weld seam affect the magnetic memory signal, parameters that were previously ignored in weld magnetic memory analysis models. Therefore, a comprehensive consideration of various influencing factors is necessary to calculate a more accurate magnitude and distribution of the magnetic memory signal during weld magnetic memory analysis.

[0098] Step 3: Calculate the normal magnetic field intensity gradient and the tangential magnetic field intensity gradient based on the normal magnetic signal and the tangential magnetic signal, respectively.

[0099] The leakage magnetic field at the weld can be calculated using the above formula. Since the magnetic field strength changes significantly at the weld, the magnetic field intensity gradient also changes significantly. The formula for calculating the magnetic field intensity gradient is as follows:

[0100]

[0101] In the formula, K is the magnetic field strength gradient value; |ΔH p (y)| represents the difference in magnetic field strength between two adjacent measurement points; Δl k This represents the distance between two adjacent measurement points.

[0102] Furthermore, to demonstrate the variation of the magnetic field strength gradient at the weld with stress, taking X70 pipe as an example, it is assumed that the material phase transformation in the weld region is constant at 45% fm, while the ferromagnetic material in the remaining regions does not undergo phase transformation. It is also assumed that the residual stress at the weld center ranges from 0 to 400 MPa, encompassing both the elastic and yield stages. The ferromagnetic material is subjected to a geomagnetic field with a strength of 40 A / m horizontally along the x-axis. The magnetic memory signal is calculated using the forward model established in step two, and the degree of damage is calculated, such as... Figure 9 The figure shows the change in magnetic field strength gradient K calculated according to the above formula. When the stress does not exceed the yield strength, the greater the residual stress in the weld, the greater the hazard to the safe operation of the pipeline, and the greater the magnetic field strength gradient. This indicates that the magnetic field strength gradient K can reflect the degree of abnormality in the magnetic memory signal and can also be used as an indicator to evaluate the degree of weld damage.

[0103] Analysis of the magnetic signal gradient at the weld can determine the degree of damage at the weld, providing a basis for further maintenance decisions.

[0104] Please refer to Figure 10This application, based on an established simulation model of pipeline welds, calculates the residual stress and metal phase transformation distribution at the weld after welding cooling, analyzes the influence of metal phase transformation and residual stress on the material's magnetic hysteresis characteristics, and determines the magnetic charge density under the combined action of stress and phase transformation based on the principle of magnetic hysteresis characteristics. A magnetic memory analysis model under multi-parameter coupling is established. Based on the established model, the tangential and normal magnetic signal components at the weld caused by magnetization are calculated. The magnetic field strength gradient K is calculated based on the calculated magnetic signal components. The magnetic field strength gradient can be used to analyze the degree of damage at the weld, providing a basis for further maintenance decisions. This addresses the problem that existing models cannot analyze the magnetic signal distribution under the combined coupling of non-uniform material microstructure, residual stress, and cracks.

[0105] It will be readily understood by those skilled in the art that the aforementioned advantageous methods can be freely combined and superimposed without conflict.

Claims

1. A method for analyzing magnetic memory signal features of pipe welds, characterized in that, Specifically, the steps include the following: Step 1: Establish a finite element welding simulation model of the pipeline weld. Based on the simulation model, calculate the residual stress and metal phase transformation distribution at the weld. Step 2: Establish a weld magnetic memory field analysis model under multi-parameter coupling conditions based on the principle of hysteresis characteristics; Step 2.1: Based on the residual stress and metal phase transformation distribution at the weld, calculate the residual stress magnetic charge density and phase transformation magnetic charge density respectively; The magnetic charge density of a material is affected by both microstructure variations and residual stress; the sum of the magnetic charge densities at the same location is the total magnetic charge density at that location. ,and then Represented as: in The magnetic charge density along the curve caused by the change in the material's own permeability Distribution equation of direction, The magnetic charge density along the residual stress change Distribution equation of direction, The total magnetic charge density at the weld is affected by the coupling of residual stress and metal phase transformation. Step 2.2: Establish a multi-parameter coupled analysis model based on the principle of hysteresis characteristics, input the total magnetic charge density into the model, and calculate the magnetic signal, which consists of normal magnetic signal and tangential magnetic signal; Step 3: Calculate the normal magnetic field intensity gradient and the tangential magnetic field intensity gradient based on the normal magnetic signal and the tangential magnetic signal, respectively.

2. The method for magnetic memory signal feature analysis of pipeline welds according to claim 1, characterized in that, Step 1 specifically includes: To establish a finite element welding simulation model for pipeline welds, the following steps are required: model creation and mesh generation, selection of material property parameters, setting of welding process parameters, setting of boundary conditions, and extraction of results.

3. The method for magnetic memory signal feature analysis of pipeline welds according to claim 1, characterized in that, Step 2.1: Based on the residual stress and metal phase transformation distribution at the weld, the magnetic charge density is calculated as follows: The magnetic charge density of ferromagnetic materials under the influence of phase transition, according to magnetic charge theory, satisfies the following equation: in The magnetic charge density along the curve caused by the change in the material's own permeability Distribution equation of direction, Permeability, The magnetization of the material. This refers to the volume fraction of the phase change in the material. For equivalent field strength, These are the magnetization model parameters, in A / m. The magnetic charge density of a ferromagnetic material under stress, according to magnetic charge theory, satisfies the following equation: The magnetic charge density along the residual stress change Distribution equation of direction, The magnitude of residual stress, The magnetization is hysteresis-free. The actual magnetization is given by c, which reflects the flexibility coefficient of the domain walls. It is a coefficient related to energy, E is the elastic modulus, and the parameter is... The effect of stress on the irreversible magnetization change is considered, and its specific value is affected by a variety of factors, including the manufacturing process of the pipe material, the heat treatment method, and the chemical composition.

4. The method for magnetic memory signal feature analysis of pipeline welds according to claim 1, characterized in that, Step 2.2: Establish a multi-parameter coupled analysis model based on the principle of magnetic hysteresis characteristics. Input the total magnetic charge density into the model and calculate the magnetic signal. The magnetic signal consists of normal magnetic signal and tangential magnetic signal. If there are no cracks in the weld, the magnetic signal in the weld area is affected by metal phase transformation and residual stress, as follows: Along the tangential H x and normal direction H y The magnetic signal components are as follows: in The axial length of the specimen. For the thickness of the specimen, The circumferential angle of the pipe weld is within the range of... , The circumferential angle of the weld is given by D, where D is the outer diameter of the pipe and R is the outer radius of the pipe. , , )and( , , ) is the magnetic charge surface generated for the weld. and The source point coordinates, For testing points The coordinates.

5. The method for magnetic memory signal feature analysis of pipeline welds according to claim 4, characterized in that, Step 2.2: Establish a multi-parameter coupled analysis model based on the principle of magnetic hysteresis characteristics. Input the total magnetic charge density into the model to calculate the magnetic signal, which consists of normal and tangential magnetic signals. If cracks appear in the weld, the specific method is as follows: Before the ferromagnetic specimen fails, the magnetization effect causes tangential H... x and normal direction H y The magnetic signal components are as follows: in, The length of the crack. The crack depth. The circumferential angle of the crack, ( , , )and( , , ) is the magnetic charge surface generated by the crack. and The source point coordinates, For testing points The coordinates.

6. The method for magnetic memory signal feature analysis of pipeline welds according to claim 1, characterized in that, Step 3: Based on the normal magnetic signal and the tangential magnetic signal, calculate the normal magnetic field intensity gradient and the tangential magnetic field intensity gradient, as follows: Based on the leakage magnetic field at the weld calculated in step 2.2, since the magnetic field strength at the weld changes, the magnetic field strength gradient also changes. The formula for calculating the magnetic field strength gradient is as follows: In the formula, K is the magnetic field strength gradient value; The difference in magnetic field strength between two adjacent measurement points; This represents the distance between two adjacent measurement points.

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