CN112276313A - Method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of large steel structural part - Google Patents
Method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of large steel structural part Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
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Abstract
The invention discloses a method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of a large steel structural member, which comprises the following steps of 1) determining the welding conditions of the large steel structural member; 2) welding a temperature measuring plate sample, and measuring an actual welding seam and a heat affected zone through metallographic analysis; 3) a thermocouple temperature measuring system is set up for calibration; 4) modeling a temperature measuring plate sample; 5) establishing a three-wire composite welding heat source model; 6) setting boundary condition parameters of a three-wire composite welding heat source model; 7) calculating the welding temperature field distribution of a temperature measuring plate sample model, and extracting the thermal cycle parameter of a certain position of a thermal influence area of the temperature measuring plate sample model; 8) comparing the thermal cycle parameters with the thermal cycle parameters of the actually measured temperature measuring plate sample; if the content is less than 10 percent, entering the step 9); if the value is more than 10%, returning to step 6) to fine adjust and recalculate the parameters; 9) the newly added boundary conditions are reapplied to the thermal plate sample model. The invention solves the problem of high measurement cost of thermal cycle parameters.
Description
Technical Field
The invention relates to a method for predicting welding cycle parameters, in particular to a method for predicting hot cycle parameters of cold and hot multi-wire composite submerged arc welding of a large steel structural member.
Background
The welding process is a special local heating and cooling process, a coarse crystal area of a heat affected zone is in an overheated state, austenite grains are heated and grow seriously, a complex and thick structure is generated after cooling, the toughness is very low, and the overheated coarse crystal area is generally a mechanical property weak area and is easy to generate welding defects such as catalysis, cracks and the like. Therefore, accurately measuring and predicting the thermal cycle curve of each subarea of the weld heat affected zone is the basis for carrying out welding metallurgical analysis and is also the premise for welding numerical simulation calculation and prediction of metallographic structure, mechanical property, welding deformation/stress and the like of the weld heat affected zone. Therefore, the method has great significance for optimizing and controlling the microstructure and the mechanical property of the welding seam and the heat affected zone thereof by accurately measuring and controlling the welding heat cycle parameters.
As an efficient welding process, submerged arc welding has been widely used for thick plate welded structures, such as large ship hulls, welded steel pipes, thick-walled pressure vessels, H-shaped steel beams, and the like. Compared with the traditional single-wire submerged arc welding, the novel cold/hot multi-wire composite submerged arc welding method is adopted for further improving the cladding rate and the production efficiency, a cold wire is mainly inserted between two parallel hot wires, the cold wire is melted by using the redundant heat of the hot wires, and the cladding rate is improved under the condition of not changing the total heat input value, so that the welding speed is improved. However, when fine-grain high-strength steel and a material with strong heat sensitivity are welded, large energy is input into the base material and the welding line, and heat damage may be caused to the base material and the welding line, so that grains in a heat affected zone of the base material are coarsened, a local softening phenomenon is generated, mechanical properties of the heat affected zone are uneven, and welding quality and use performance are affected finally. Therefore, the temperature measurement of the heat affected zone of the multi-wire submerged arc welding of the large steel structure is more and more emphasized.
However, due to practical production limitations, it is labor and material consuming to accurately measure the heat cycle curve of the weld in the heat affected zone. At present, no simple forming method for measuring the heat cycle of the welding heat affected zone of the large-scale high-strength thick plate structural steel exists.
In recent years, with the rapid development of computer technology and finite element numerical simulation technology, the method for simulating the welding of the large-scale thick plate structural steel by using a computer becomes a novel efficient method which saves time and labor, and quantitative analysis calculation and accurate prediction of the welding process are realized by combining an actual process test and a theoretical numerical simulation technology.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of a large steel structural member, which aims to accurately obtain a thermal cycle curve of a welding heat affected zone of the large thick plate steel structural member and solve the problem of high measurement cost of the thermal cycle parameters.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of a large steel structural member comprises the following steps:
1) determining the welding conditions of the large steel structural member;
2) normally welding a temperature measuring plate sample, observing the macroscopic morphology of a cross section profile through metallographic analysis after welding, and measuring the sizes of an actual welding seam and a heat affected zone;
3) building a thermocouple temperature measuring system, calibrating the thermocouple temperature measuring system, and calculating thermal cycle parameters of different positions of a heat affected zone;
4) carrying out three-dimensional modeling on the temperature measuring plate sample by using a finite element and dividing a grid;
5) establishing a three-wire composite welding heat source model according to the test welding condition;
6) setting relevant parameters of boundary conditions of the three-wire composite welding heat source model by referring to actual welding conditions;
7) calculating the welding temperature field distribution of the temperature measurement plate sample model, and extracting the welding thermal cycle parameters of a certain position of a heat affected zone of the temperature measurement plate sample model;
8) comparing and verifying the welding thermal cycle parameter of a certain position of the heat affected zone, which is primarily predicted in the step 7), with the actual thermal cycle parameter of the same position of the temperature measurement plate sample, which is measured by the thermocouple temperature measurement system in the step 3); if the comparison result is less than 10%, entering step 9); if the comparison result is more than 10%, returning to the step 6) to finely adjust the parameters of the three-wire composite welding heat source model, and then entering the step 7) to recalculate until the comparison result is less than 10%;
9) and newly adding boundary conditions to the temperature measurement plate sample model again, calculating the distribution of the welding temperature field, and extracting the welding heat cycle parameters of other positions of the heat affected zone of the temperature measurement plate sample model, thereby completing the prediction of the welding heat cycle parameters of the large steel structural member.
Preferably, in the step 1), the welding conditions of the large steel structural member include a welding station, a workpiece size, an ambient temperature, a multi-wire composite submerged arc welding process, a groove form, a jointed plate material and a welding wire welder material.
Preferably, in the step 3), the thermocouple temperature measuring system adopts a K-type thermocouple.
Preferably, in the step 3), the calibration of the thermocouple temperature measurement system is specifically to design a group of temperature measurement holes with equal spacing and equal depth difference on the front side of the welding seam position of the temperature measurement plate sample, and perform online temperature measurement recording on different positions of the heat affected zone in the welding process of the temperature measurement plate sample by adopting a thermocouple front drilling mode.
Preferably, in the step 4), when the temperature measuring plate sample is modeled, the size of the temperature measuring plate sample is consistent with that of the large-scale steel structural member actually produced by welding.
Preferably, in the step 5), the three-wire composite welding heat source model comprises density distribution of front and rear hot wire flows, and flow rates of front and rear hot wire molten drops and a middle cold wire entering a molten pool;
preferably, the hot wire current density selects a double-ellipsoid heat source formula or a Gaussian plane heat source formula according to the welding wire power, the welding wire diameter and the thickness of the base metal plate.
Preferably, in the step 6), the parameters related to the boundary conditions of the three-wire composite welding heat source model include welding current, voltage, arc width, droplet and speed of the cold wire entering the molten pool.
Preferably, in the step 9), the new boundary conditions include thermal boundary conditions, heat dissipation boundary conditions, and constraint boundary conditions.
The method for predicting the hot-cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member provided by the invention has the following beneficial effects:
1) the method of the invention gives full play to the function of a numerical simulation tool, reduces the workload of the welding process test and greatly reduces the test cost;
2) the method of the invention can successfully predict the temperature field distribution and the thermal cycle parameters of the submerged-arc welding heat affected zone of the large steel structural member, can also be used for other large complex welding structures which are difficult to directly measure or need high measurement cost, and has important significance in actual production.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic view of the arrangement and combination of welding guns for multi-wire composite submerged arc welding in step 1) of the method of the present invention;
FIG. 3 is a metallographic image of a macroscopic cross-sectional morphology of a temperature measuring plate sample after being welded in step 2) of the method of the invention;
FIG. 4 is a schematic diagram of the arrangement of thermocouple temperature measuring points in step 3) of the method of the present invention;
FIG. 5 is a schematic view in the direction A-A of FIG. 4;
FIG. 6 is a schematic diagram of gridding of a temperature measuring plate sample model in step 4) of the method;
FIG. 7 is a schematic diagram of the meshing of the cold/hot multi-wire positions of the three-wire composite welding heat source model in step 5) of the method of the present invention;
FIG. 8 is a cloud diagram of the temperature field distribution of the three-wire composite weld pool in step 7) of the method of the present invention;
FIG. 9 shows predicted results of thermal cycle curves for a #3 measured temperature point of a weld heat affected zone in an embodiment of a method of the present invention;
FIG. 10 shows the measured results of thermal cycle curves of the weld heat affected zone # 3 at the temperature measurement points in the example of the method of the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the drawings and the embodiment.
Referring to fig. 1, the method for predicting the thermal cycle parameters of the cold-hot multi-wire composite submerged arc welding of the large steel structural member provided by the invention comprises the following steps:
1) the welding conditions of the large steel structural member are determined, the specific parameters are shown in the following table 1, and the welding process mainly adopts a jointed board single-side welding and double-side forming station of cold/hot multi-wire composite submerged arc welding. Referring to fig. 2 again, a combination form of arranging front and rear welding torches (with a distance of 50mm) along a welding direction is adopted, a front welding gun 1 adopts a single thick wire 3 (phi 4.0-5.0 mm, namely a front wire), a rear welding gun 2 adopts two multi-thin wires 4 (phi 4.0-5.0 mm, namely a middle wire and a rear wire, wherein the middle wire is a cold wire), a welding joint is in a single-side V-shaped groove with an angle of 70 degrees, a truncated edge is 3mm, and an assembly gap is 0 mm;
TABLE 1 Multi-wire composite submerged arc welding Specifications
2) Selecting a jointed board temperature measurement sample according to the welding conditions in the step 1), and actually welding the temperature measurement plate sample by adopting the same welding conditions as in the step 1), wherein the groove form, the workpiece size and the material of the jointed board sample are completely consistent with those of the large-scale steel structural member. Carrying out normal welding on a jointed board (temperature measuring board) sample, carrying out metallographic analysis after welding to observe the macroscopic morphology of the cross section profile and measure the actual sizes of a welding seam and a heat affected zone, wherein the front face fusion width of a sample welding joint is 13.40mm, the back face fusion width is 11.64mm, and the front face residual height is 1.38mm as shown in figure 3;
3) a multichannel online measurement system for the submerged arc welding thermal cycle parameters of jointed boards is built based on a Labview software platform and mainly comprises a K-type nickel-chromium (anode) -nickel-silicon (cathode) thermocouple, an EM9104C data acquisition card, a thermocouple compensation wire, a shielding wire, a computer and the like. A standard measuring instrument (direct current potentiometer) is adopted to calibrate a temperature measuring system, so that accurate data is provided for the temperature measurement of a subsequent weld heat affected zone;
4) referring to fig. 4 and 5, a set of temperature measuring holes with equal thickness (4mm) and equal distance difference from the edge of the weld line are designed on the front surface of the weld seam of the temperature measuring test plate, so that each zone of the welding heat affected zone 5 has a temperature measuring point, wherein F +1 to F +5 represent the temperature measuring points which are 1mm to 5mm away from the edge of the weld line 6 respectively; then, after the welding is performed by the energy storage welding machine, the welding is performed in a spot welding mode in a temperature measuring hole of a processed test plate to be welded, one end of the thermocouple is connected with a thermocouple compensation line by brazing, the other end of the compensation line is connected with a data acquisition card, temperature measuring results of different positions are displayed and recorded in real time after the welding is started, and thermal cycle parameters of a welding heat affected zone are extracted after experimental results are collated;
5) and carrying out three-dimensional modeling and meshing on the temperature measuring plate sample by using finite element software, and carrying out meshing on the geometric model by adopting a four-node tetrahedron and an eight-node hexahedron unit. Aiming at the welding seam center and the heat affected zone with the rapidly changed temperature gradient, in order to obtain higher prediction precision, a welding seam and a nearby area need to be divided into fine grids, and the size of each grid is set to be 1 mm; in order to comprehensively consider the influence of calculation precision and calculation time, the size of the grid unit far away from the welding seam area is set to be 20 mm; a gradual transition grid is arranged between the two, as shown in figure 6;
6) and (3) establishing a heat source model, wherein the position of the heat source is relatively fixed, and the flat plate moves unidirectionally relative to the heat source so as to realize that the heat source moves along the center of the welding line to the welding direction. The positions of the three heat sources are relatively fixed, the front wire (hot wire, phi 5mm) is positioned in front of the welding direction, the middle wire (cold wire, phi 2.5mm) is positioned between the front wire and the rear wire, and the rear wire (hot wire, phi 2.5mm) is positioned at the rearmost part. According to the actual arc interval and welding parameters of the three-wire composite welding, a welding heat source model is established, and the heat source position is the inflow position of the welding material, as shown in fig. 7. According to the heat source superposition principle, a front wire heat source formula and a rear wire heat source formula are simultaneously applied to corresponding positions, the front wire heat source formula adopts a double-ellipsoid heat source formula, and the rear wire can select the double-ellipsoid heat source formula (thick plate) or the Gaussian heat source formula (thin plate) according to the different plate thicknesses;
7) and setting related parameters of heat source boundary conditions, such as welding current, voltage, arc width, speed of molten drops and cold wires entering a molten pool and the like, by referring to the actual welding condition. Preliminarily determining the heat dissipation boundary conditions and the like of the temperature measuring plate sample model, such as preliminarily determining the convective heat transfer coefficient of a submerged arc welding action area to be 2-3W/m2Determining an action area according to the coverage range of a submerged arc welding flux in the actual welding process; the convection heat transfer coefficient of an uncovered submerged arc welding agent area is 25W/m2Temperature. The quasi-steady-state temperature field distribution of the three-wire composite welding pool can be obtained, and the preliminary calculation result is shown in figure 8;
8) and calculating the temperature field distribution of the sample model of the temperature measuring plate, and extracting the welding thermal cycle parameters of a certain fixed position of a heat affected zone of the temperature measuring plate. Comparing the actual welding thermal cycle parameters with the actual welding thermal cycle parameters at the same positions of the temperature measurement samples obtained in the step 4), if the error between the thermal cycle parameters of the temperature measurement plate sample model and the thermal cycle parameters of the actually measured samples is less than 10 percent according to the comparison result, storing the key parameters of the composite heat source of the temperature measurement plate sample model, otherwise, returning to the step 6) to repeatedly perform fine adjustment verification on the heat source parameters until the error between the thermal cycle parameters of the temperature measurement plate sample model and the thermal cycle parameters of the actually measured temperature measurement plate sample is less than 10 percent, and finally obtaining the key parameters of the composite heat source of the constructed model;
9) and (3) reapplying the thermal boundary conditions, the heat dissipation boundary conditions and the constraint boundary conditions of the temperature measuring plate sample model determined in the step 8) to the numerical simulation analysis of the temperature measuring plate sample model, so that the welding temperature field distribution of the large steel structural member model and the thermal cycle parameters of other key positions of the welding heat affected zone are calculated, and finally the accurate prediction of the welding thermal cycle parameters of the large steel structural member is completed.
Examples
The welding method related to the embodiment aims at cold/hot multi-wire composite submerged arc welding of jointed board butt joint, and adopts a thermocouple front punching mode to measure temperature. Firstly, recording jointed board butt joint conditions: the length of the jointed board is 3000mm, the width is 2000mm, the thickness is 8mm, and the welding specification is shown in the table 1.
In the welding process, a thermocouple measurement experiment is performed on the spliced plate butt-joint sample, as shown in fig. 3, the temperature is measured by using a mode of punching the front side of the thermocouple, the distance between every two temperature measuring holes along the welding direction is 5mm, the depth is 4mm, so as to ensure that the temperature of a welding heat affected zone can be measured by the thermocouple, and the following table 2 shows the peak temperature, the heating speed, the high-temperature retention time and the like of thermal cycle parameters of each temperature measuring point of the thick steel plate multi-wire submerged arc welding temperature measuring test plate.
TABLE 28 mm three-wire composite welding thermal cycle peak parameter measurement results
The heat cycle parameter calculation process of the heat affected zone of the large steel structural member in this embodiment is shown in fig. 1.
Fig. 9 and fig. 10 are respectively a comparison between the simulation prediction result and the actual measurement result of the temperature measurement point (#3) of the welding heat affected zone of the temperature measurement plate in this embodiment, the graphs respectively show the thermal cycle curves of the temperature measurement point 3mm away from the fusion line, and the comparison between the simulation result and the actual measurement result shows that the prediction accuracy of the calculation result of the thermal cycle parameter of the temperature measurement plate at the position F +3 away from the fusion line reaches 90%, and the expected requirement is satisfied. Therefore, the thermal model boundary conditions corrected by the test parameters can be applied to the temperature measurement plate model, so that the thermal cycle parameters of the temperature measurement points at the center of the weld joint and other different positions can be predicted.
The following table 3 shows the comparison of the thermal cycle parameter experiment and simulation results of the temperature measuring plate.
TABLE 3 weld thermal cycle parameter prediction and measurement comparison results for FL +3 position
The boundary conditions corrected by the experimental parameters are reapplied to the numerical simulation calculation of the temperature measurement plate, and the prediction result of the multi-wire submerged arc welding process of the large steel structural member is calculated, as shown in the following table 4.
TABLE 4 comparison of weld thermal cycle parameter predictions at different locations
In summary, the invention provides a method for predicting thermal cycle parameters of cold and hot multi-wire composite submerged arc welding of a large steel structural member, which adopts a computer numerical simulation technology established on the basis of a small amount of process tests to realize quantitative analysis and finite element simulation of thermal cycle parameters of a heat affected zone in the welding process of the large steel structural member, so that on one hand, the multi-wire composite submerged arc welding process parameters (welding wire spacing, welding gun inclination angle, current and voltage and the like) are optimized, on the other hand, the actual welding process tests can be greatly reduced, the production efficiency is greatly improved, the production cost is reduced, and guidance basis is provided for producing a submerged arc welding joint of the large steel structural member with high strength, high toughness and high reliability.
It should be understood by those skilled in the art that the above embodiments are only for illustrating the present invention and are not to be used as a limitation of the present invention, and that changes and modifications to the above described embodiments are within the scope of the claims of the present invention as long as they are within the spirit and scope of the present invention.
Claims (9)
1. A method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of a large steel structural member is characterized by comprising the following steps of:
1) determining the welding conditions of the large steel structural member;
2) normally welding a temperature measuring plate sample, observing the macroscopic morphology of a cross section profile through metallographic analysis after welding, and measuring the sizes of an actual welding seam and a heat affected zone;
3) building a thermocouple temperature measuring system, calibrating the thermocouple temperature measuring system, and calculating thermal cycle parameters of different positions of a heat affected zone;
4) carrying out three-dimensional modeling on the temperature measuring plate sample by using a finite element and dividing a grid;
5) establishing a three-wire composite welding heat source model according to the test welding condition;
6) setting relevant parameters of boundary conditions of the three-wire composite welding heat source model by referring to actual welding conditions;
7) calculating the welding temperature field distribution of the temperature measurement plate sample model, and extracting the welding thermal cycle parameters of a certain position of a heat affected zone of the temperature measurement plate sample model;
8) comparing and verifying the welding thermal cycle parameter of a certain position of the heat affected zone, which is primarily predicted in the step 7), with the actual thermal cycle parameter of the same position of the temperature measurement plate sample, which is measured by the thermocouple temperature measurement system in the step 3); if the comparison result is less than 10%, entering step 9); if the comparison result is more than 10%, returning to the step 6) to finely adjust the parameters of the three-wire composite welding heat source model, and then entering the step 7) to recalculate until the comparison result is less than 10%;
9) and newly adding boundary conditions to the temperature measurement plate sample model again, calculating the distribution of the welding temperature field, and extracting the welding heat cycle parameters of other positions of the heat affected zone of the temperature measurement plate sample model, thereby completing the prediction of the welding heat cycle parameters of the large steel structural member.
2. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 1), the welding conditions of the large steel structural part comprise a welding station, a workpiece size, an ambient temperature, a multi-wire composite submerged arc welding process, a groove form, a jointed board material and a welding wire welder material.
3. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 3), the thermocouple temperature measuring system adopts a K-type thermocouple.
4. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 3), the calibration of the thermocouple temperature measurement system is specifically to design a group of temperature measurement holes with equal spacing and equal depth difference on the front side of the welding seam position of the temperature measurement plate sample, and perform online temperature measurement recording on different positions of the heat affected zone in the welding process of the temperature measurement plate sample by adopting a thermocouple front drilling mode.
5. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 4), when the temperature measuring plate sample is modeled, the size of the temperature measuring plate sample is consistent with that of a large-scale steel structural member produced by actual welding.
6. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 5), the three-wire composite welding heat source model comprises the current density distribution of the front and the rear hot wires, the flow of the front and the rear hot wire molten drops and the flow of the middle cold wire entering the molten pool.
7. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 6, wherein the method comprises the following steps of: and the hot wire current density selects a double-ellipsoid heat source formula or a Gaussian plane heat source formula according to the welding wire power, the welding wire diameter and the thickness of the base metal plate.
8. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 6), relevant parameters of boundary conditions of the three-wire composite welding heat source model comprise welding current, voltage, arc width, molten drop and speed of a cold wire entering a molten pool.
9. The method for predicting hot and cold multi-wire composite submerged arc welding thermal cycle parameters of the large steel structural member according to claim 1, wherein the method comprises the following steps of: in the step 9), the newly added boundary conditions include thermal boundary conditions, heat dissipation boundary conditions and constraint boundary conditions.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112986325A (en) * | 2021-03-22 | 2021-06-18 | 哈尔滨焊接研究院有限公司 | Method and device for measuring welding thermal cycle curve |
| CN115358115A (en) * | 2022-08-04 | 2022-11-18 | 北京建工集团有限责任公司 | Temperature field analysis method based on actually measured welding temperature field and combined with finite element |
| CN116305667A (en) * | 2023-05-18 | 2023-06-23 | 贵州大学 | Surface shape error control method for central symmetrical convex surface shape of large-diameter sheet part |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102637235A (en) * | 2012-05-02 | 2012-08-15 | 中国石油集团渤海石油装备制造有限公司 | Determination method for heat source model parameters in multiplewire submerged-arc welding by numerical simulation |
| CN102693336A (en) * | 2012-05-09 | 2012-09-26 | 天津大学 | Method for predicting welding thermal circulation parameters of large pipelines |
| DE102012217669A1 (en) * | 2012-09-27 | 2014-03-27 | Siemens Aktiengesellschaft | Gas metal arc-narrow gap welding, comprises simultaneously using two arc plasma leading and melting welding wires and supplying third non plasma arc leading welding wire such that process energy welding wires melts the third welding wire |
| CN104985298A (en) * | 2015-07-10 | 2015-10-21 | 湘潭大学 | Method for predicting small-angle welding temperature field of rotating arc low-alloy structural steel |
| CN106363283A (en) * | 2016-11-28 | 2017-02-01 | 河海大学常州校区 | Method for determining serial double-wire submerged arc welding numerical simulation heat source model parameters |
-
2020
- 2020-10-19 CN CN202011116556.9A patent/CN112276313A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102637235A (en) * | 2012-05-02 | 2012-08-15 | 中国石油集团渤海石油装备制造有限公司 | Determination method for heat source model parameters in multiplewire submerged-arc welding by numerical simulation |
| CN102693336A (en) * | 2012-05-09 | 2012-09-26 | 天津大学 | Method for predicting welding thermal circulation parameters of large pipelines |
| DE102012217669A1 (en) * | 2012-09-27 | 2014-03-27 | Siemens Aktiengesellschaft | Gas metal arc-narrow gap welding, comprises simultaneously using two arc plasma leading and melting welding wires and supplying third non plasma arc leading welding wire such that process energy welding wires melts the third welding wire |
| CN104985298A (en) * | 2015-07-10 | 2015-10-21 | 湘潭大学 | Method for predicting small-angle welding temperature field of rotating arc low-alloy structural steel |
| CN106363283A (en) * | 2016-11-28 | 2017-02-01 | 河海大学常州校区 | Method for determining serial double-wire submerged arc welding numerical simulation heat source model parameters |
Non-Patent Citations (2)
| Title |
|---|
| 张彦华: "《热制造学引论 第2卷》", 31 July 2012 * |
| 赵兴科: "《现代焊接与连接技术》", 30 June 2016, 冶金工业出版社 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112986325A (en) * | 2021-03-22 | 2021-06-18 | 哈尔滨焊接研究院有限公司 | Method and device for measuring welding thermal cycle curve |
| CN112986325B (en) * | 2021-03-22 | 2023-08-18 | 中国机械总院集团哈尔滨焊接研究所有限公司 | Method and device for measuring welding thermal cycle curve |
| CN115358115A (en) * | 2022-08-04 | 2022-11-18 | 北京建工集团有限责任公司 | Temperature field analysis method based on actually measured welding temperature field and combined with finite element |
| CN116305667A (en) * | 2023-05-18 | 2023-06-23 | 贵州大学 | Surface shape error control method for central symmetrical convex surface shape of large-diameter sheet part |
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