CN111581862A - An Equivalent Test Method for Micro-area Mechanical Properties of Welded Joints - Google Patents

Abstract

The invention relates to an equivalent test method for mechanical properties of a welding joint microcell, which comprises the steps of providing a flat welding sample, and establishing a corresponding relation database of tensile mechanical property data and a welding thermal cycle curve and/or the highest temperature; taking a sample to be tested which is made of the same material as the welding sample, welding the sample to be tested according to target welding process parameters, monitoring the temperature change condition of a target micro-area on the sample to be tested, and obtaining a welding thermal cycle curve and/or the highest temperature of the target micro-area; and comparing the welding thermal cycle curve and/or the highest temperature with the corresponding relation database to obtain the mechanical property of the target micro-area. The method has high efficiency, accuracy and reliability in predicting the mechanical property of the welding joint microcell.

Description

An Equivalent Test Method for Micro-area Mechanical Properties of Welded Joints

technical field

The invention relates to an equivalent testing method for the mechanical properties of welded joints, belonging to the technical field of performance testing of metal material connection manufacturing.

Background technique

Welding is an extremely important process for realizing material connection. By heating or pressurizing, or heating and pressurizing at the same time, intermolecular bonds are formed between the materials to be connected to achieve permanent connection methods. Welding methods include fusion welding, pressure Welding, brazing, etc. Fusion welding needs to heat the material to be welded and the filler material (also known as "welding wire") above the melting point to form a liquid molten pool, and then solidify to obtain a weld; pressure welding is generally under the simultaneous action of heating heat and pressure, so that the The process in which the welding material reaches a semi-solid state or above the melting point, and then cools to obtain a weld; in the brazing process, the required heat is relatively low, and it is only necessary to melt the filler material and then wet the surface of the material to be welded to obtain a weld. Regardless of the type of welding method, a certain amount of heat needs to be input during the welding process, not only the filling material will be heated, but also the connecting parts of the materials to be welded. Often, this heating process and post-welding cooling process is considered to be a heat treatment for the joined fine areas of the material to be joined. The effect of this welding heat may change the microstructure and mechanical properties of the welding area of the material to be connected, that is, after the material near the joint is welded, its performance will change compared with its original performance, which is often called thermal influence. .

Metal materials are the most widely used materials in the industry. The strength of the material mainly comes from grain boundary strengthening, precipitation strengthening, dislocation strengthening (also known as work hardening), and its grain size (total grain boundary area per unit volume), Density of dislocations (dislocation length per unit volume), size and number density of precipitates (shape size of particles and number of precipitate particles per unit volume). At present, the most important connection method of metal material structural parts is welding. However, most ferrous metals (such as pure iron, carbon steel, cast iron, etc.) and non-ferrous metals (aluminum alloy, copper alloy, titanium alloy, etc.) have certain sensitivity to welding heat. After the heat input of these materials through welding, if the heated temperature rises above the formation temperature of the above strengthening elements, the grains, phase types, precipitates and dislocations around the weld will have a certain influence. For example, heating may promote the increase of the number of precipitated phases, but it may also cause the growth of the size of the precipitated phase and the change of the phase if the temperature is too high. For example, when the temperature increases, the dislocation density will decrease. The size will further grow, such as steel material heated to normalizing temperature can form more pearlite to strengthen equal.

In order to describe the effect of welding heat on the properties of the weld material, it is generally necessary to clearly describe the heat input method. The welding thermal cycle is often described, which is defined as the process of the temperature of a certain point on the weld and its surrounding base metal changing with time. Welding thermal cycle curve representation. Including parameters such as maximum temperature and heating time. When metal materials are welded, different areas of the weld joint experience different thermal cycles, so different thermal effects are obtained, as shown in Figure 1. Therefore, different subtle areas of the welded joint undergo different changes when heated. Taking low carbon steel as an example, as shown in Figure 2, the closer to the weld, the higher the maximum temperature of its thermal cycle, and even the phase transition region of its grains, such as position 3 in Figure 2, its The temperature reaches the austenitized region, which is equivalent to normalizing after the welding is completed, so the region is called the normalizing region, which can form more normalized pearlite phases, and its mechanical properties will be improved. Taking 6082 aluminum alloy as an example, as shown in Figure 3, the position in the figure is the distance from the reference point to the center of the weld. As shown in the figure, when the distance is less than a certain distance, the state of the precipitation phase in the 6082 aluminum alloy will be significantly changed after the temperature exceeds 150 °C. After the cooling process, the chemical elements form a solid solution state, and the strengthening effect is not as strong as that of the original precipitation phase; when the temperature exceeds 235 °C, the size of the precipitation phase will be significantly coarsened, the strengthening effect will be significantly reduced, and the mechanical properties will be reduced. Because different regions of the welded joint experience different thermal cycles, the different regions have different thermal effects (ie, different final properties) after welding.

It can be seen from the above that the performance of different areas of the welded joint may be strengthened or weakened after the welding machine. Therefore, when welding parts are used in engineering, it is often necessary to know the mechanical properties of each microscopic region of the welded joint, which can be used to predict the location of the weak area of mechanical properties of the welded structure or the failure position of the joint during service. In addition, in the finite element simulation strength check calculation of structural parts, it is often necessary to know the mechanical performance parameters of these micro-regions, such as stress-curve data.

Through experimental tests, such as tensile test of welded joints (the test method corresponds to the national standard GB-T 2651), parameters such as overall strength and elongation after fracture of welded joints can be obtained. However, the obtained performance indicators still cannot provide a complete or fine characterization of the mechanical properties of welded joints, and the mechanical properties (yield strength, tensile strength, elongation, etc.) of each microscopic region are also required. The general practice is to slice the microscopic regions parallel to the weld section to make tensile specimens for tensile experiments. However, when the thickness of the welded material is thin, the obtained welded tensile specimen is not wide enough to meet the requirements of the specified size of the specimen in GB-T 2651, so similar mechanical property characterization cannot be carried out.

At present, some testing methods for the local mechanical properties of welded joints have been reported in the existing literature, such as: micro-shear test, micro-tensile test, micro-punch test, artificial neural network prediction, Gleeble thermal cycle loading simulation, etc. [1-5 ]. In view of the small area of each area of the welded joint, although the micro-shear test and micro-tensile test methods are feasible, the preparation of samples is time-consuming and costly. In the micro-stamping test, the force-displacement curve needs to be obtained first, and then the finite element reverse iteration is performed. Due to the friction between the indenter and the measured material, which is difficult to estimate, the measurement accuracy will be affected. The artificial neural network prediction method is used to test the local mechanical properties of welded joints. The premise is that there must be enough sample data to ensure the reliable prediction results. The workload of this method is huge. The Gleeble thermal cycle simulation method is to explore the performance changes of the alloy by simulating the thermal cycle characteristics during the welding process. In addition, the micro-sample test method is used, because the sample size is relatively small, the experimental test accuracy is sensitive to the size, and the results are inaccurate and the error is large.

references:

[1] Liu Jingan, Wang Yuanliang, Sun Hong. Research on micro-area performance of welded joints of aluminum alloy profiles for vehicles [J]. Light alloy processing technology (1): 41-43.

[2]Lavan D A.Microtensile properties of weld metal[J].ExperimentalTechniques, 1999, 23(3):31-34.

[3] Wang Zhicheng, Qiao Jisen, Chen Jianhong, et al. Analysis of local mechanical properties of aluminum alloy welded joints for passenger cars [J]. Journal of Welding, 2009, 30(1).

[4] Shi Wei, Fan Ding, Chen Jianhong. Prediction of mechanical properties of welded joints based on neural network method [J]. Journal of Welding, 2004, 25(2): 73-76.

[5] Wen Liu, Fenggui Lu, Renjie Yang, et al. Gle-eble simulation of the HAZ in Inconel 617welding [J]. Journal of Materials Processing Technology, 2015, 225:221-228.

SUMMARY OF THE INVENTION

In view of the deficiencies of the prior art, the present invention provides an equivalent testing method for the micro-region mechanical properties of welded joints, so as to efficiently, accurately and reliably predict the micro-region mechanical properties of the welded joints.

In order to solve the above-mentioned technical problems, the technical scheme of the present invention is as follows:

An equivalent testing method for micro-region mechanical properties of welded joints, comprising the following steps:

S1. Provide a flat welding sample, the welding sample has at least one straight edge; take the position of the straight edge as the starting point, along the direction perpendicular to the straight edge and parallel to the welding sample, place the The welding sample is divided into micro-area L ₁ , micro-area L ₂ , micro-area L ₃ , ..., micro-area L _n in turn;

Among them, n is a positive integer; the thickness of a single micro-region does not exceed 2mm;

S2. Apply a welding seam on the welding sample along the straight edge, and at the same time, monitor the temperature change of each micro-area, and obtain the welding thermal cycle curve and/or the maximum temperature of each micro-area;

Alternatively, a welding seam is applied on the welding sample along the straight edge, and a finite element simulation of the temperature field is performed on the welding sample under the same conditions to obtain the welding thermal cycle curve and/or the maximum temperature of each micro-zone;

S3. According to the division of each micro-area, the welded sample after S2 treatment is cut to obtain tensile sample l ₁ , tensile sample l ₂ , tensile sample l ₃ , ..., tensile test like l _n ;

S4. Test the tensile mechanical properties of each tensile specimen obtained in S3, obtain the mechanical property data of each tensile specimen, and establish the correspondence between the tensile mechanical property data and the welding thermal cycle curve and/or the maximum temperature relational database;

S5. Take the test sample of the same material as the welding sample, and perform welding with the target welding process parameters. At the same time, monitor the temperature change of the target micro-area on the test sample to obtain the welding thermal cycle curve of the target micro-area. and/or maximum temperature;

Alternatively, take a sample to be tested of the same material as the welding sample, perform finite element simulation of the temperature field on the sample to be tested under the target welding process parameters, and obtain the welding thermal cycle curve and/or the maximum temperature of the target micro-area ;

S6. Compare the welding thermal cycle curve and/or the maximum temperature obtained in S5 with the corresponding database obtained in S4 to obtain the tensile mechanical properties of the target micro-region.

In the present invention, the maximum temperature can be understood as the maximum value of the temperature on the corresponding welding thermal cycle curve. The database can be further simplified by mapping and comparing the highest temperature.

The thickness of an individual domain refers to the dimension of the domain in a direction perpendicular to the straight edge and parallel to the weld specimen.

Optionally, taking the position of the midpoint of the right-angled side as the starting point, along the direction perpendicular to the straight edge and parallel to the welding sample, divide the welding sample into micro-areas L ₁ and micro-areas L in turn. _2. Micro-areas L ₃ , ..., micro-area L _n ;

Further, in S1, 3≤n≤20.

Further, in S1, the thickness t of the welding sample is 8-12 mm.

Further, in S1, the thickness of the single micro-domain is 0.8-1.2 mm.

Further, in S2 and/or S5, optionally, the temperature change of the corresponding micro-area is detected by a contact temperature measurement method or a non-contact temperature measurement method, and further optionally, the temperature of the corresponding micro-area is detected by a thermocouple. change; further optionally, the temperature change of the corresponding micro-area is detected by an infrared temperature measuring device.

Further, in S3, the sample to be tested includes at least one of a fillet joint, a butt joint, and a lap joint.

Further, in S4, the tensile mechanical properties include at least one of tensile strength, yield strength, elongation after fracture, and strain hardening index.

Further, the sample is one of aluminum alloy, copper alloy, titanium alloy, pure iron, carbon steel, and cast iron.

Optionally, the aluminum alloy is a 6000 series aluminum alloy, and further is a 6082 aluminum alloy or a 6061 aluminum alloy.

Through the equivalent test method of the present invention, on the one hand, the micro-area performance characterization of thin-walled welded joints can be effectively carried out; The cyclic curve or the highest temperature can be corresponded to, and then the mechanical properties of the target position of the target joint can be known, and the complex sample preparation is not required, which simplifies the test process. Therefore, the method is used to predict the mechanical properties of the welded joint micro-region with high efficiency, accuracy and reliability. .

Through the equivalent testing method of the present invention, the performance of each micro-region of the welded joint can be predicted after welding with certain welding parameters, so as to continuously optimize or select suitable welding parameters.

Description of drawings

Figure 1 is a graph of thermal cycling characteristics of a welded joint.

Figure 2 is a graph of the thermal effects of different fine areas of a low carbon steel welded joint.

Figure 3 is the temperature change curve of different positions of the joint during the aluminum alloy welding process.

Figure 4 is a schematic diagram of the cross-sectional structure of the welded sample.

Fig. 5 is a schematic diagram of a state in which a welded sample is clamped.

Figure 6 is the finite element network model of the welded specimen.

Figure 7 is a comparison diagram of the molten pool morphology and cross-sectional size after welding and forming obtained by simulation (left) and experiment (right).

Figure 8 is a comparison diagram of temperature change curves of simulation and experiment at points A1, A2, and A3.

FIG. 9 is a cloud diagram of the temperature field distribution obtained by simulation when each micro-area of the template is in the highest temperature state during the welding process.

Figure 10(a) is a schematic diagram of the layered sampling situation; Figure 10(b) is a top view of a single tensile specimen.

Figure 11 is an engineering stress-strain curve diagram of each equivalent tensile specimen.

Figure 12 is a schematic diagram of the temperature measurement points of the sample to be tested.

FIG. 13 is a comparison diagram of temperature change curves of test points in simulation and experiment.

Figure 14 is a temperature field distribution diagram of the sample to be tested.

Figure 15 is a diagram of a tensile test specimen prepared from the sample to be tested.

Figure 16 is a simulation mesh model of the sample to be tested.

FIG. 17 is the force-displacement curve of the tensile finite element simulation results and the test results of the samples to be tested.

In the figure, 1-welding sample, 2-clamping device.

Detailed ways

The following description describes alternative embodiments of the invention to teach those of ordinary skill in the art how to implement and reproduce the invention. In order to teach the technical solutions of the present invention, some conventional aspects have been simplified or omitted. Those of ordinary skill in the art will appreciate that modifications or substitutions from these embodiments will fall within the scope of the present invention. It will be understood by those of ordinary skill in the art that the following features can be combined in various ways to form various modifications of the invention.

Example 1

In this embodiment, the equivalent testing method for the mechanical properties of the welded joint micro-region includes the following steps:

S1. Provide a flat-plate welding sample, the welding sample has at least one straight edge; starting from the position of the right-angled edge, along the direction perpendicular to the straight edge and parallel to the welding sample, place the The welding sample is divided into micro-area L ₁ , micro-area L ₂ , micro-area L ₃ , ..., micro-area L _n in turn, see Fig. 4 ;

Among them, n is a positive integer; the thickness of a single micro-area is 0.95mm;

S2. Apply a welding seam on the welding sample along the straight edge, and at the same time, monitor the temperature change of each micro-area, and obtain the welding thermal cycle curve and/or the maximum temperature of each micro-area;

Alternatively, a welding seam is applied on the welding sample along the straight edge, and a finite element simulation of the temperature field is performed on the welding sample under the same conditions to obtain the welding thermal cycle curve and/or the maximum temperature of each micro-zone;

S3. According to the division of each micro-area, the welded sample after S2 treatment is cut to obtain tensile sample l ₁ , tensile sample l ₂ , tensile sample l ₃ , ..., tensile test like l _n ;

S4. Test the tensile mechanical properties of each tensile specimen obtained in S3, obtain the mechanical property data of each tensile specimen, and establish the correspondence between the tensile mechanical property data and the welding thermal cycle curve and/or the maximum temperature relational database;

S5. Take the test sample of the same material as the welding sample, and perform welding with the target welding process parameters. At the same time, monitor the temperature change of the target micro-area on the test sample to obtain the welding thermal cycle curve of the target micro-area. and/or maximum temperature;

Alternatively, take a sample to be tested of the same material as the welding sample, perform finite element simulation of the temperature field on the sample to be tested under the target welding process parameters, and obtain the welding thermal cycle curve and/or the maximum temperature of the target micro-area ;

S6. Compare the welding thermal cycle curve and/or the maximum temperature obtained in S5 with the corresponding database obtained in S4 to obtain the tensile mechanical properties of the target micro-region.

Among them, the flat welded sample (ie equivalent welded joint): thickness 10mm, length 300mm, 6061 aluminum plate, heat treatment state is T6, tensile strength is 342Mpa, yield strength is 323MPa, elongation after fracture is 9%.

The reliability of the equivalent test method of the present embodiment is further verified as follows:

The welding wire uses ER5356 aluminum alloy welding wire with a diameter of 1.2 mm, and the chemical composition of the aluminum plate and welding wire is shown in Table 1. The welding equipment adopts an OTC double-pulse MIG welding machine (model DP400), the welding current is 150A, the welding speed is 60cm/min, the wire dry elongation is 15mm, the protective gas is 99.999% argon, and the gas flow is 20L/min. Scrub the aluminum plate with acetone before welding, and then use a wire brush to clean the surface to be welded until the metallic luster is exposed. The welding position is the side of the aluminum plate, and the welding direction is the length direction of the test plate. In order to prevent the vibration of the aluminum plate during welding, both ends are pressed with a clamping device, and the clamping state is shown in Figure 5.

In order to obtain the temperature distribution at different positions of the aluminum plate during the welding process, a series of temperature measurement points are arranged at a distance of 140mm from the arc starting position on one side of the sample plate, and K-type thermocouples are used to collect the temperature data during the welding process in real time. The distances are 5mm, 10mm, and 15mm, respectively, and are recorded as A1, A2, and A3, respectively. The layout of the temperature measurement points is shown in Figure 5.

Table 1 Chemical composition of 6061-T6 aluminum alloy and ER5356 welding wire (mass fraction %)

Finite element simulation of temperature field:

The difference in the micro-area performance of the welded joint is mainly caused by the difference in heat input during welding, so it is necessary to accurately characterize the temperature change in each area. In order to carry out the temperature field and performance prediction analysis, the present invention adopts the finite element analysis method to simulate and analyze the temperature at different positions in the welding sample, and compares it with the temperature curve measured in the experiment, thereby establishing the relationship between the heating temperature and the thermal influence. Correspondence of micro-area performance.

Using the welding analysis platform of the Simufact software, according to the actual size of the aluminum plate and tooling, a three-dimensional finite element model is established and meshed. The model mesh adopts a three-dimensional 8-node element. In order to take into account calculation efficiency and simulation accuracy, the minimum size of the welding sample and weld mesh is divided into 1mm × 1mm × 2mm, the total number of nodes is 125612, the total number of elements is 105735, and the finite element simulation mesh The model is shown in Figure 6. The material parameters are 6061 aluminum alloy, the material of the clamping device is 45 steel, and the physical parameters that come with the material library of the Simufact software are selected, and the process parameters used in the aforementioned welding experiments are input at the same time.

The filling of the welding wire is simulated by the life and death element and the double ellipsoid moving heat source model ^[6-7] . According to the existing research ^[8] , the present invention simplifies the heat transfer between the aluminum plate to be welded, the tooling, and the ambient air into convective heat transfer and radiation heat transfer, and the expression is as follows:

In the formula: h _conv is the convective heat transfer coefficient; T is the instantaneous temperature of the _weldment surface; T ₀ is the room temperature; ε is the radiation coefficient _; /K·m ² , σ is 5.68×10 ^-8 J/K ⁴ ·m ² ·s, ε is 0.08 ^[9-10] .

references:

[6] Zheng Zhentai. Numerical simulation research and application of welding process of large thick-walled structures [D]. Tianjin University, 2007.

[7] AKBARI MOUSAVI S AA, MIRESMAEILI R.Experimental and numericalanalyses of residual stress distributions in TIG welding process for 304Lstainless steel[J].Journal of Materials Processing Technology, 2008, 208:383-394.

[8] Shanmugam N S, Buvanashekaran G, Sankaranarayanasamy K, etal. Atransient finite element simulation of the temperature field and beadprofile of T-joint laser welds[J]. International Journal of Modelling and Simulation, 2010, 30(1):108-122 .

[9] Zhang Jianqiang, Zhang Guodong, Zhao Haiyan, et al. Three-dimensional finite element simulation of welding stress of aluminum alloy sheet [J]. Journal of Welding, 2007, 28(6):5-9.

[10] BIKASS S, ANDERSSON B, PILIPENKO A, LANGTANGEN H P. Simulation of initial cooling rate effect on the extrudate distortion in the aluminum extrusion process [J]. Applied Thermal Engineering, 2012, 40: 326-336.

Figure 7 is a comparison diagram of the molten pool morphology and cross-sectional size obtained after welding and forming obtained by simulation and experiment. The measured actual weld cladding height is 4.7mm, and the simulation result's weld cladding height is 4.8mm, and the simulation error is 2.1%, which is within the acceptable range. The cladding height in the experiment is relatively small, which may be due to the fact that the weld seam is fish-scale in the experiment, and there is a certain error in the selection of the cross-section of the molten pool. Figure 8 is a comparison diagram of temperature change curves of simulation and experiment at points A1, A2, and A3. The initial temperature (within 10s) curve obtained in the experiment has a certain fluctuation, which is caused by the voltage not yet stabilized in the arcing stage. Taking A1 as the analysis object, it can be seen that from room temperature to peak temperature, the time elapsed for experiment and simulation is 12.5s and 12.3s, respectively. When cooling from peak temperature to 200 °C, the time elapsed for experiment and simulation is 26.5s and 25.5s, respectively. s, it can be seen that the temperature measurement points have undergone the process of rapid heating and cooling, and the temperature gradient of the measurement points far away from the weld is much smaller than that near the weld (such as point A3). From the comparative analysis of the simulation results and the experimental measurement results, it can be seen that the parameters of the simulated temperature curve (peak temperature, heating rate, cooling rate) are in good agreement with the relevant parameters in the experiment (error <4.6%), indicating that the simulation results are reliable and realize the The simulation of the temperature field of each micro-region of the welded joint is carried out.

Fig. 9 is a cloud diagram of the temperature field distribution of the cross-section of the template obtained by simulation when the welding process is stable. It can be seen that the temperature on the section is in a horizontal state (distributed by contour lines), and the highest temperature near the weld reaches 633 °C, which is the middle temperature of the weld fusion line; along the direction away from the weld fusion line, the temperature gradually decreases. , the temperature distribution difference of the same layer on the section is very small, it is determined that the equivalent sample of the heat-affected zone can be obtained by slicing the sample perpendicular to the surface of the template, which effectively proves the feasibility of the joint scheme. It can be seen that, whether it is determining the temperature field distribution of the welding sample, or when predicting the test sample, the temperature field distribution can be determined through finite element simulation.

Mechanical property test:

In order to obtain the mechanical properties of heat-affected micro-domain materials under different thermal cycles, equivalent tensile specimens were obtained by layered sample preparation and quasi-static tensile tests were carried out. As shown in Figure 10, the test plate after welding was sliced in layers along the direction away from the weld fusion line by wire cutting, and the sample preparation method was shown in Figure 10(a). The samples taken from the weld fusion line are numbered sequentially from 1. The size of the tensile specimen is designed according to the standard ASTM E8M-09. The detailed size is shown in Figure 10(b). The size and sampling method of the tensile specimen are shown in Figure 10. The mechanical properties of the tensile specimens were tested on an Instron 3369 universal testing machine with a tensile speed of 2 mm/min.

FIG. 11 is the obtained quasi-static tensile test result of the tensile specimen. From the engineering stress-strain curve of the samples, it can be seen that the tensile strength of each sample along the direction away from the weld shows a trend of first decreasing and then increasing. The elongation after fracture is 23.35% and 23.49%, which are significantly higher than other heat-affected micro-zone samples. It can be seen that sample 2 and sample 3 have better plastic deformation ability. The tensile strength of sample 5 is the lowest, which is 201MPa, and its strength coefficient is about 58.6% of the base metal. , the base metal properties have been reached, and it can be inferred that starting from the position of specimen 16, the mechanical properties of the material are no longer affected by the heat of welding. From this, it can be seen that the heat-affected zone is the range of the samples included in the sample 1 to the sample 15, and the width is about 17 mm.

Combined with the temperature simulation results and tensile experimental test results, the temperature variation range of each tensile specimen is obtained. The corresponding relationship between the maximum temperature range and the regional range of the sample is shown in Table 2.

Table 2 Temperature and area range where the sample is located

Experimental verification and application:

Through the above experiments, the corresponding relationship between the micro-area temperature change of the equivalent welded joint and the micro-area heating temperature and the mechanical properties (stress-strain curve) shown in Figure 1 is accurately obtained. Its further potential engineering application value lies in obtaining the temperature distribution law of the sample to be tested through simulation, and the sample to be tested is equivalent to a multilayer material, according to the corresponding relationship between the temperature range of each layer and the mechanical properties (constitutive relationship). , establish a fine model of finite element simulation, and perform fine analysis and prediction on the mechanical properties of the test sample. Compared with the traditional CAE simulation modeling and analysis method, the calculation and prediction accuracy of this method is more accurate.

In order to verify the reliability of the performance prediction of the test specimens, the refined model established by equivalent welding specimens to various materials. The 6061-T6 aluminum plate with a thickness of 3mm and a size of 300mm*150mm produced by extrusion of the same batch of aluminum rods was butt welded, and the temperature field simulation of the sample to be tested was calibrated. Then, according to the temperature field distribution of the sample to be tested in the simulation, the finite element model of the sample to be tested is equivalent to a multi-layer material composition, and the tensile simulation finite element model of the sample to be tested is given the temperature corresponding to the temperature in Table 2. Corresponding heat-affected micro-area material properties, the accuracy of the established equivalent method is evaluated by comparing the quasi-static tensile test results of the tested samples with the simulation results.

Temperature field distribution of the sample to be tested (butt joint):

While welding the butt test plate, use K-type thermocouples to collect the temperature at points B1, B2, and B3 at 5mm, 10mm, and 15mm from the center of the weld (see Figure 12). The temperature simulation of the butt joint and the temperature change curve of the experimental temperature measurement point are shown in Figure 13, and the shape of the cross-section molten pool and the simulated temperature distribution cloud diagram are shown in Figure 14. From the comparison of temperature simulation and experiment curves and molten pool morphology, it can be seen that the temperature curve (error <2.63%) and molten pool morphology of simulation and experiment are in good agreement. It can be seen that the temperature field of the butt joint is The simulation can reflect the temperature distribution of real welding.

The tensile specimen of the butt joint was prepared according to the national standard GT/B 2651-2008, and the size of the tensile specimen is shown in Figure 15. The thickness of the tensile specimen is 0.95 mm.

Table 3 shows the maximum temperature of the simulated/experimental temperature change curves at points B1, B2, and B3 in Fig. 12 .

Table 3 The maximum temperature situation table of the temperature change curve of the simulation/experiment

It can be seen from Table 3 that the maximum temperature in the simulated and experimental temperature curves is very close, and both the simulated maximum temperature and the experimental maximum temperature can be used for prediction. The applicant compared the data in Table 2 with the highest temperature in the experiment, and obtained the predicted values of the mechanical properties of the tensile specimens corresponding to the measuring points B1, B2, and B3, as shown in Table 4.

Table 4. Predicted values of mechanical properties of tensile specimens corresponding to measuring points B1, B2, and B3

Table 5 shows the measured values of the mechanical properties of the tensile specimens corresponding to the measuring points B1, B2, and B3. Comparing Table 4 and Table 5, it can be seen that the predicted value of mechanical properties obtained by the method of the present application is very close to the measured value, indicating that the equivalent testing method of the present invention is highly reliable and can accurately predict the mechanical properties of the target area.

Table 5. Measured values of mechanical properties of tensile specimens corresponding to measuring points B1, B2, and B3

According to the actual size of the quasi-static tensile specimen, the finite element simulation model of the tensile experiment is established. The simulation model adopts 8-node grid elements, the total number of nodes in the whole model is 19374, and the total number of grids is 14668. In the simulation, the material of MAT24 is selected. Considering the simulation accuracy and calculation efficiency, the grid size near the weld (within the range of 3.8mm to 19mm from the center of the weld) is divided into 0.5mm×0.5mm×1mm The location grid size of the weld is divided into 1mm×1mm×1mm. According to the temperature field cloud map obtained by the simulation and the temperature division interval in Table 3, the grid of the butt joint located at 555-633 °C is divided into the Z1 zone, and the mechanical properties of the sample 1 are given, and the temperature is located at the grid of 505-555 °C. It is divided into Z2 area, and the mechanical properties of sample 2 are given, and so on. Finally, the area below the temperature range of sample 16 is divided into the base metal area. The simulation model after the partition is shown in Figure 16. After the partition of the mesh model is completed, the measured material properties of each area are assigned to the finite element model, and then all the degrees of freedom of the fixed end are constrained, and a velocity load of 2 mm/min is applied to the loading end. The mesh element is simulated by the full integration element method. simulation.

Figure 17 is the force-displacement curve of the tensile finite element simulation results and test results of the butt joint. In the initial stage, the tensile specimen is in the elastic deformation stage, and the force changes linearly with the displacement. With the increase of the displacement, the plastic deformation of the tensile specimen begins to dominate, and the change of force and displacement gradually increases nonlinearly. Fracture failure occurs. The peak forces of simulation and experiment are 7182N and 7172N respectively, and the simulation error is 0.1%. The displacement of simulation and experiment at fracture failure is 3.3mm and 3.5mm, respectively, and the simulation error is 5.7%. It can be seen from the variation trend of force with displacement, the magnitude of peak force and the displacement corresponding to fracture failure in the simulation and experimental results of the butt joint that the simulation and experimental results are in good agreement. The method of simulation prediction is feasible, the prediction accuracy can meet the needs of engineering, and it also has a certain reference value for the strength simulation prediction of other joint forms.

In conclusion, the equivalent testing method of the present invention is highly reliable, can effectively predict the mechanical properties of different regions of the welded joint, and has engineering application value.

It should be understood that these embodiments are only used to illustrate the present invention more clearly, but not to limit the scope of the present invention. After reading the present invention, those skilled in the art will recognize various equivalent forms of the present invention. The modifications fall within the scope defined by the appended claims of this application.

Claims (8)

1. An equivalent test method for mechanical properties of a welding joint microcell is characterized by comprising the following steps:

s1, providing a flat welding sample, wherein the welding sample is provided with at least 1 straight edge; taking the position of the straight line edge as a starting point, and dividing the welding sample into micro areas in sequence along the direction which is perpendicular to the straight line edge and parallel to the welding sampleL ₁ Micro-areaL ₂ Micro-areaL ₃ … …, micro-areaL _n ；

Wherein n is a positive integer; the thickness of the single micro-area is not more than 2 mm;

s2, applying a welding seam on the welding sample along the straight line edge, and simultaneously respectively monitoring the temperature change condition of each micro-area to obtain the welding thermal cycle curve and/or the highest temperature of each micro-area;

or applying a welding seam on the welding sample along the straight line edge, and carrying out finite element simulation on the temperature field of the welding sample under the same condition to obtain a welding thermal cycle curve and/or the highest temperature of each micro-area;

s3, cutting the welding sample processed by the S2 according to the division condition of each micro-area to obtain a tensile samplel ₁ Tensile specimenl ₂ Tensile specimenl ₃ … … tensile test specimenl _n ；

S4, detecting the tensile mechanical property of each tensile sample obtained in the step S3 to obtain the mechanical property data of each tensile sample, and establishing a corresponding relation database of the tensile mechanical property data and a welding thermal cycle curve and/or the highest temperature;

s5, taking a to-be-detected sample with the same material as the welding sample, welding according to target welding process parameters, and simultaneously monitoring the temperature change condition of a target micro-area on the to-be-detected sample to obtain a welding thermal cycle curve and/or the highest temperature of the target micro-area;

or, taking a sample to be tested which is the same in material as the welding sample, and carrying out temperature field finite element simulation on the sample to be tested under target welding process parameters to obtain a welding thermal cycle curve and/or the highest temperature of a target micro-area;

and S6, comparing the welding thermal cycle curve and/or the highest temperature obtained in the step S5 with the corresponding relation database obtained in the step S4, and obtaining the tensile mechanical property of the target micro-area.

2. The equivalent test method according to claim 1, wherein in S1, n is 3. ltoreq. n.ltoreq.20.

3. The equivalent test method according to claim 1, wherein in S1, the thickness of the welding specimen is 8-12 mm.

4. The equivalent test method according to claim 1, wherein in S1, the thickness of the single micro domains is 0.8-1.2 mm.

5. The equivalent test method as set forth in claim 1, wherein the temperature change of the corresponding micro-zone is detected by a thermocouple in S2 and/or S5.

6. The equivalent test method according to claim 1, wherein in S3, the test specimen to be tested includes at least one of a corner joint, a butt joint, and a lap joint.

7. The equivalent test method as claimed in claim 1, wherein in S4, the tensile mechanical properties include at least one of tensile strength, yield strength, elongation after break, strain hardening index.

8. The equivalent test method according to any one of claims 1 to 7, wherein the test piece is one of an aluminum alloy, a copper alloy, a titanium alloy, pure iron, carbon steel, cast iron.

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