A heterogeneous tube welding control method and system based on adaptive regulation

Abstract

This invention provides a welding control method and system for heterogeneous tubes based on adaptive regulation, belonging to the field of welding control technology. The method includes: selecting three characteristic positions on the current weld bead and adjacent weld beads within the welding heat-affected zone based on welding dynamic deviation signals; constructing thermal characteristic units by dividing the thermal characteristic units into heat-affected zones; simulating the fluid flow behavior and heat field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy using a pre-trained coupled calculation model of molten pool flow and heat transfer, calculating the coordinated response values ​​of temperature field, flow field, and stress field of each sub-region under welding thermal cycle, and determining the target adjustment amount. This invention improves welding quality stability and process efficiency by adaptively and dynamically adapting to the material and structural differences of heterogeneous tubes.

Description

Technical Field

[0001] This invention relates to the field of welding control technology, and in particular to a welding control method and system for heterogeneous tubes based on adaptive regulation. Background Technology

[0002] Heterogeneous pipe welding, especially when it involves pipes made of different base materials, such as austenitic stainless steel and low alloy steel, is widely used in energy, chemical and other fields. In such welding processes, due to the inherent differences in thermal conductivity, coefficient of linear expansion and metallurgical properties of the base materials, the temperature field distribution of the heat-affected zone and the dynamic behavior of the molten pool are often more complex than those of welding the same material. In actual multi-layer and multi-pass welding operations, the welding parameters, such as welding current, arc voltage and welding speed, are generally set based on preset process specifications. However, external disturbances, changes in heat dissipation conditions or interpass temperature fluctuations of the previous weld can sometimes cause the actual heat input to deviate from the expected value.

[0003] Taking the butt welding of dissimilar steel pipes made of austenitic stainless steel and low alloy steel for a certain type of pressure vessel as an example, existing control methods may rely to some extent on the operator's experience or relatively simple feedback adjustment. When the welding reaches a certain intermediate weld pass, if the heat input deviates due to changes in the local heat dissipation conditions of the workpiece, traditional methods can mostly only make lagging corrections to the overall power parameters. It may be difficult to adjust for the differences in metallurgical sensitivity and thermophysical parameters in different areas within the heat-affected zone, such as near the fusion line, coarse-grained zone and fine-grained zone. In this case, the fluid flow behavior of the molten pool under the combined action of surface tension, electromagnetic force and thermal buoyancy may change unexpectedly. There is room for further improvement in the control of weld uniformity, elemental distribution consistency and heat-affected zone microstructure stability. Summary of the Invention

[0004] This invention provides a welding control method and system for heterogeneous tubes based on adaptive regulation, which improves welding quality stability and process efficiency by adaptively and dynamically adapting to the differences in material and structure of heterogeneous tubes.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] In a first aspect, a method for controlling the welding of heterogeneous tubes based on adaptive regulation, the method comprising:

[0007] Step 1: Compare the real-time parameter set with the preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and form a welding dynamic deviation signal based on the deviation and fluctuation characteristics.

[0008] Step 2: Based on the welding dynamic deviation signal, three characteristic positions are selected on the current weld bead and adjacent weld beads within the welding heat-affected zone (HAZ). The local thermal field distribution of each of the three characteristic positions constitutes a thermal characteristic unit. This includes determining the solidification transition zone behind the molten pool of the current weld bead along the welding direction within the HAZ based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, thus obtaining the first characteristic position; determining the coarse-grained region of the HAZ of the current weld bead along the welding direction within the HAZ based on the first characteristic position, thus obtaining the second characteristic position; and determining the remelting region of the HAZ of the adjacent weld bead along the welding direction within the HAZ based on the second characteristic position, thus obtaining the third characteristic position. Temperature gradient data and cooling rate data in the thickness direction are collected at the first characteristic position to obtain the first local thermal field distribution. Based on the first local thermal field distribution and the second characteristic position, temperature gradient data and cooling rate data in the thickness direction of the second characteristic position are collected. The temperature gradient data and cooling rate data are used to obtain the second local thermal field distribution. Based on the second local thermal field distribution and the third feature position, the temperature gradient data and cooling rate data of the third feature position in the thickness direction are collected to obtain the third local thermal field distribution. Based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, the current weld bead and the adjacent weld bead are combined according to their relative spatial position relationship in the welding heat-affected zone to form thermal feature units. The thermal feature units are divided into heat-affected zones. Based on the distribution characteristics of the metallurgical properties and thermophysical parameters of the base material corresponding to each sub-region after division, the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy are simulated through a pre-trained coupled calculation model of molten pool flow and heat transfer. The coordinated response values ​​of the temperature field, flow field, and stress field of each sub-region under the welding thermal cycle are calculated to determine the target adjustment amount.

[0009] Step 3: Based on the welding dynamic deviation signal and the target adjustment amount, and combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous pipe, calculate the adjustment command of the welding equipment.

[0010] Step 4: Adjust the output parameters of the welding equipment in real time according to the adjustment instructions, and collect the feedback interpass temperature and heat input values ​​after adjustment. Compare the feedback interpass temperature and heat input values ​​with the heterogeneous tube welding process window again until the feedback interpass temperature and heat input values ​​return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

[0011] Secondly, a heterogeneous tube welding control system based on adaptive regulation includes:

[0012] The generation module is used to compare the real-time parameter set with the preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and to form a welding dynamic deviation signal based on the deviation and fluctuation characteristics.

[0013] The simulation module is used to select three characteristic locations on the current weld bead and adjacent weld beads within the weld heat-affected zone (HAZ) based on the welding dynamic deviation signal. The local thermal field distribution of each of the three characteristic locations constitutes a thermal characteristic unit. This includes determining the solidification transition zone behind the molten pool of the current weld bead along the welding direction within the HAZ based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, obtaining the first characteristic location; determining the coarse-grained region of the HAZ of the current weld bead along the welding direction within the HAZ based on the first characteristic location, obtaining the second characteristic location; determining the remelting region of the HAZ of the adjacent weld bead along the welding direction within the HAZ based on the second characteristic location, obtaining the third characteristic location; collecting temperature gradient data and cooling rate data along the thickness direction of the first characteristic location to obtain the first local thermal field distribution; and collecting temperature gradient data and cooling rate data along the thickness direction of the second characteristic location based on the first local thermal field distribution and the second characteristic location. The temperature gradient data and cooling rate data in the direction are used to obtain the second local thermal field distribution. Based on the second local thermal field distribution and the third feature position, the temperature gradient data and cooling rate data in the thickness direction of the third feature position are collected to obtain the third local thermal field distribution. Based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, the current weld bead and the adjacent weld bead are combined according to their relative spatial position relationship in the welding heat-affected zone to form a thermal feature unit. The thermal feature unit is divided into heat-affected zones. Based on the distribution characteristics of the metallurgical properties and thermophysical parameters of the base material corresponding to each sub-region after division, the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy are simulated through a pre-trained coupled calculation model of molten pool flow and heat transfer. The coordinated response values ​​of temperature field, flow field, and stress field of each sub-region under welding thermal cycle are calculated to determine the target adjustment amount.

[0014] The adjustment module is used to calculate the adjustment command of the welding equipment based on the welding dynamic deviation signal and the target adjustment amount, combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous tubes.

[0015] The control module is used to adjust the output parameters of the welding equipment in real time according to the adjustment command, and after adjustment, it collects the feedback interpass temperature and heat input value, compares the feedback interpass temperature and heat input value with the heterogeneous tube welding process window again, until the feedback interpass temperature and heat input value return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

[0016] The above-described solution of the present invention has at least the following beneficial effects:

[0017] By dynamically comparing real-time welding parameters with preset process windows, the characteristics of welding heat input deviation and temperature gradient fluctuation in the heat-affected zone are extracted to form a dynamic deviation signal that closely matches the actual welding state. This improves the real-time performance and accuracy of deviation identification during the welding of heterogeneous tubes. Considering the differences in the characteristics of heterogeneous tube base materials, thermal feature units are constructed, heat-affected sub-regions are divided, and a coupled calculation model of molten pool flow and heat transfer is used to simulate the behavior of the molten pool and the redistribution of the heat field under the action of multiple physical fields. The coordinated response values ​​of the temperature field, flow field, and stress field are calculated to determine the target adjustment amount and reduce control inaccuracies. Combined with the dynamic deviation signal, the target adjustment amount, and the different base material characteristics of the heterogeneous tube, equipment adjustment commands are generated to improve the adaptability of the welding process to heterogeneous tubes. An adaptive control mode based on the comparison of interpass temperature and heat input is adopted to correct the output parameters of the welding equipment in real time, stabilizing key welding parameters within the allowable range of the process window, thus achieving adaptive control of heterogeneous tube welding. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of a heterogeneous tube welding control method based on adaptive regulation, provided by an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of a heterogeneous tube welding control system based on adaptive regulation, provided by an embodiment of the present invention. Detailed Implementation

[0020] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0021] like Figure 1 As shown, an embodiment of the present invention proposes a welding control method for heterogeneous tubes based on adaptive regulation, the method comprising the following steps:

[0022] Step 1: Compare the real-time parameter set with the preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and form a welding dynamic deviation signal based on the deviation and fluctuation characteristics.

[0023] Step 2: Based on the welding dynamic deviation signal, three characteristic positions are selected on the current weld bead and adjacent weld beads within the welding heat-affected zone (HAZ). The local thermal field distribution of each of the three characteristic positions constitutes a thermal characteristic unit. This includes determining the solidification transition zone behind the molten pool of the current weld bead along the welding direction within the HAZ based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, thus obtaining the first characteristic position; determining the coarse-grained region of the HAZ of the current weld bead along the welding direction within the HAZ based on the first characteristic position, thus obtaining the second characteristic position; and determining the remelting region of the HAZ of the adjacent weld bead along the welding direction within the HAZ based on the second characteristic position, thus obtaining the third characteristic position. Temperature gradient data and cooling rate data in the thickness direction are collected at the first characteristic position to obtain the first local thermal field distribution. Based on the first local thermal field distribution and the second characteristic position, temperature gradient data and cooling rate data in the thickness direction of the second characteristic position are collected. The temperature gradient data and cooling rate data are used to obtain the second local thermal field distribution. Based on the second local thermal field distribution and the third feature position, the temperature gradient data and cooling rate data of the third feature position in the thickness direction are collected to obtain the third local thermal field distribution. Based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, the current weld bead and the adjacent weld bead are combined according to their relative spatial position relationship in the welding heat-affected zone to form thermal feature units. The thermal feature units are divided into heat-affected zones. Based on the distribution characteristics of the metallurgical properties and thermophysical parameters of the base material corresponding to each sub-region after division, the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy are simulated through a pre-trained coupled calculation model of molten pool flow and heat transfer. The coordinated response values ​​of the temperature field, flow field, and stress field of each sub-region under the welding thermal cycle are calculated to determine the target adjustment amount.

[0024] Step 3: Based on the welding dynamic deviation signal and the target adjustment amount, and combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous pipe, calculate the adjustment command of the welding equipment.

[0025] Step 4: Adjust the output parameters of the welding equipment in real time according to the adjustment instructions, and collect the feedback interpass temperature and heat input values ​​after adjustment. Compare the feedback interpass temperature and heat input values ​​with the heterogeneous tube welding process window again until the feedback interpass temperature and heat input values ​​return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

[0026] In this embodiment of the invention, real-time welding parameters are dynamically compared with a preset process window to extract welding heat input deviation and temperature gradient fluctuation characteristics of the heat-affected zone, forming a dynamic deviation signal that fits the actual welding state. This improves the real-time performance and accuracy of deviation identification during the welding of heterogeneous tubes. Considering the differences in characteristics between the heterogeneous base materials of the tubes, thermal feature units are constructed, heat-affected sub-regions are divided, and a coupled calculation model of molten pool flow and heat transfer is used to simulate the behavior of the molten pool and the redistribution of the heat field under the action of multiple physical fields. The coordinated response values ​​of the temperature field, flow field, and stress field are calculated to determine the target adjustment amount, reducing control inaccuracies. Combined with the dynamic deviation signal, the target adjustment amount, and the different base material characteristics of the heterogeneous tubes, equipment adjustment commands are generated to improve the adaptability of the welding process to the heterogeneous tubes. An adaptive control mode based on the comparison of interpass temperature and heat input is adopted to correct the output parameters of the welding equipment in real time, stabilizing the key welding parameters within the allowable range of the process window, thus achieving adaptive control of heterogeneous tube welding.

[0027] In a preferred embodiment of the present invention, during the welding process of heterogeneous tubes, welding current, welding voltage, welding speed, and interpass temperature are collected in real time to obtain multi-source physical field data. A real-time parameter set is then constructed based on the multi-source physical field data, which may include:

[0028] In this embodiment of the invention, for the acquisition of welding current and welding voltage, a dedicated acquisition element is connected to the output end of the welding equipment to ensure a stable connection between the acquisition element and the welding circuit, while avoiding interference areas such as welding spatter and arc radiation to prevent signal distortion. For the acquisition of welding speed, a speed acquisition component is fixed to the welding torch or workpiece clamping device to ensure that it can synchronously capture the moving speed of the welding torch, conforming to the actual operation trajectory of multi-layer and multi-pass welding. For the acquisition of interpass temperature, considering the different base materials of heterogeneous tubes, such as the different thermal conductivity and heat dissipation capacity of austenitic stainless steel and low alloy steel, multiple temperature acquisition elements are evenly arranged near the fusion line of the welding heat-affected zone, the coarse grain zone, and the junction of adjacent weld passes, taking into account the temperature distribution on different base material sides and avoiding the one-sidedness of temperature data caused by a single acquisition point. After the welding operation starts, all acquisition devices are turned on simultaneously, entering the real-time acquisition stage of multi-source physical field data. The acquisition process follows the welding progress without interruption, adapting to the continuous operation requirements of multi-layer and multi-pass welding. During current and welding voltage acquisition, the system captures instantaneous changes in current and voltage in the welding circuit in real time. At extremely short intervals, it closely matches the dynamic changes in the welding process, ensuring no critical fluctuations are missed and recording data. It focuses on capturing sudden changes in current and voltage caused by external disturbances during welding, such as changes in workpiece assembly gaps or fluctuations in heat dissipation conditions. Simultaneously, it distinguishes between current and voltage data for different weld layers and weld passes to avoid confusion. During welding speed acquisition, the system synchronously tracks the welding torch's movement trajectory, recording the movement speed at every moment. If the operator adjusts the welding torch speed during welding, or if speed fluctuations occur due to workpiece positioning deviations, the acquisition device will immediately capture and record them, ensuring that the speed data is completely synchronized with the actual welding rhythm. During interpass temperature acquisition, the system monitors instantaneous temperature changes in the heat-affected zone during welding in real time. Additionally, it collects interpass temperature data once after each weld pass is completed and before the next weld pass begins, focusing on recording the temperature difference between the heat-affected zones on different base material sides, as well as the residual temperature after heat dissipation from the previous weld pass, capturing the characteristics of interpass temperature fluctuations.

[0029] After data acquisition, the raw multi-source physical field data is initially processed to remove outliers and ensure data validity. First, abnormal values ​​caused by acquisition interference, such as spatter obstruction or poor component contact (e.g., sudden increases or decreases in instantaneous current, distorted temperature data), are identified and discarded. The remaining valid data is then categorized into four main types: welding current, welding voltage, welding speed, and interpass temperature. Each category is associated with corresponding welding sequence information, such as acquisition time, weld layer, weld pass number, and spatial location information, such as the base material type and heat-affected zone location corresponding to the acquisition point. This determines the welding condition for each data set, avoiding data confusion. Based on the overall... The processed multi-source physical field data is used to construct a real-time parameter set. The parameter set is based on the time sequence of the welding process and integrates the parameter data corresponding to each time node, each weld pass, and each weld layer according to the welding progress. Specifically, it includes the instantaneous value and real-time fluctuation range of welding current, the instantaneous value and real-time fluctuation range of welding voltage, the instantaneous value of welding speed and its adjustment, as well as the instantaneous value of interpass temperature and temperature gradient changes at different locations (different base material sides, different heat-affected zones). At the same time, the parameter set is synchronously associated with the basic information of the welding operation, such as the type of heterogeneous pipe base material and the current welding process, to ensure that the parameter set can reflect the dynamic working conditions of the current welding process.

[0030] In a preferred embodiment of the present invention, step 1 above, which compares the real-time parameter set with a preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and forms a welding dynamic deviation signal based on the deviation and fluctuation characteristics, may include:

[0031] In this embodiment of the invention, step 110 involves calculating the real-time welding heat input value based on the welding current, welding voltage, and welding speed from the real-time parameter set. Specifically, this includes extracting the instantaneous valid data of welding current, welding voltage, and welding speed corresponding to the current welding moment from the constructed real-time parameter set. The welding current extracted is the real-time stable instantaneous current value in the welding circuit; the welding voltage extracted is the real-time instantaneous voltage value at both ends of the welding arc; and the welding speed extracted is the real-time instantaneous speed of the welding torch movement or workpiece rotation. All three parameters must be free of abnormal data caused by acquisition interference, such as sudden increases or decreases in current, voltage distortion, or sudden changes in speed. The calculation is performed using the following formula. ,in This represents the real-time welding heat input value at the current moment. This is a welding thermal efficiency correction factor used to correct for arc heat loss during welding, including radiation loss, conduction loss, and convection loss. Its value is specifically set based on the base material type and welding method of the heterogeneous tube. For example, when the heterogeneous tube is a butt weld between austenitic stainless steel and low-alloy steel, the thermal conductivity of the two base materials differs significantly; the low-alloy steel has a higher thermal conductivity than austenitic stainless steel, resulting in faster heat dissipation. The value is set between 0.7 and 0.75 to ensure that the corrected heat input value matches the actual welding heat absorption. The instantaneous value of welding current at the current moment is extracted from the real-time parameter set, which directly reflects the current intensity of the welding arc; The instantaneous value of welding voltage at the current moment is extracted from the real-time parameter set, reflecting the voltage magnitude of the welding arc, and together with the welding current, it determines the power of the arc; The instantaneous welding speed value extracted from the real-time parameter set reflects the speed of the welding torch movement or workpiece rotation, directly affecting the heat accumulation per unit length of weld. During calculation, the selected instantaneous welding current value is used... Instantaneous value of welding voltage Instantaneous value of welding speed and the pre-set welding thermal efficiency correction coefficient Substitute each value into the above formula to obtain the real-time welding heat input value at the current moment. To achieve real-time control of the welding process, the extraction and calculation operations in this step are repeated after each parameter acquisition cycle to ensure real-time welding heat input values. It can be updated synchronously with the welding progress.

[0032] Step 111: Compare the real-time welding heat input value with the standard heat input range in the preset dissimilar pipe welding process window to obtain the deviation of the welding heat input. Specifically, this includes: retrieving the preset dissimilar pipe welding process window, which is determined in advance through experiments and simulations based on core parameters such as the type of base material, pipe specifications, welding materials, and welding methods of the dissimilar pipe. This window includes a standard heat input range for the current welding condition. The setting of this range must take into account the metallurgical properties and thermophysical parameters of both base materials to ensure that during welding, insufficient heat input will not lead to problems such as incomplete weld penetration, poor fusion, or insufficient joint strength, while excessive heat input will not lead to defects such as overheating, coarse grains in the heat-affected zone, or excessive residual stress. For example, when welding dissimilar pipes of austenitic stainless steel and low-alloy steel, the standard heat input range is usually set to 180 J / mm to 220 J / mm. Each real-time welding heat input value calculated in step 110... The heat input value is compared with the preset standard heat input range one by one, and the real-time welding heat input value is determined during the comparison process. The location, if If the temperature is within the standard heat input range, it indicates that the current heat input meets the process requirements; if... A value exceeding the upper limit of the standard heat input range indicates excessive heat input; if If the value is below the lower limit of the standard heat input range, it indicates that the current heat input is insufficient. After the comparison is completed, the deviation of the welding heat input is calculated. Specifically, the deviation of the welding heat input is equal to the real-time welding heat input value obtained in step 110. Subtract the median value of the preset standard heat input range. The median value of the standard heat input range is calculated by adding the upper limit value and the lower limit value of the standard heat input range, and then dividing by 2. This median value is used as the standard reference value for heat input. After the calculation is completed, record the specific value and sign of the deviation. When the deviation is positive, it means that the real-time heat input is higher than the standard reference value, and the deviation direction is excessive heat input. When the deviation is negative, it means that the real-time heat input is lower than the standard reference value, and the deviation direction is insufficient heat input. When the deviation is 0 or close to 0, it means that the real-time heat input is basically consistent with the standard reference value and there is no obvious deviation. At the same time, record the absolute value of the deviation.

[0033] Step 112: Based on the spatial distribution of interpass temperature along the welding path from the real-time parameter set, determine the spatial range of the welding heat-affected zone (HAZ), and extract the thickness-direction temperature gradient sequence within the HAZ. Perform time-series analysis based on the thickness-direction temperature gradient sequence to obtain the thickness-direction temperature gradient change rate. Specifically, this includes: extracting spatial distribution data of interpass temperature along the welding path from the real-time parameter set. This data is collected in real-time during the welding process and includes interpass temperature values ​​at different spatial locations along the welding path. Each temperature value is associated with corresponding acquisition location information, such as the coordinates of the acquisition point, its location on the base material side, and its distance from the weld center. During the extraction process, the integrity and accuracy of the data must be ensured, and data lost due to acquisition component failure or spatter must be discarded. Temperature distortion data caused by factors such as shading; combined with the extracted interpass temperature spatial distribution data, the spatial range of the weld heat-affected zone is determined. Specifically, the core range of the weld heat-affected zone is selected based on the weld center, where the interpass temperature is higher than the room temperature of the heterogeneous tube base material but lower than the phase transformation temperature of the base material. At the same time, the range is fine-tuned based on the differences in thermophysical parameters between the two base materials of the heterogeneous tube. For example, the low alloy steel side has higher thermal conductivity and faster heat dissipation, so the heat-affected zone range is relatively wider, while the austenitic stainless steel side has lower thermal conductivity and slower heat dissipation, so the heat-affected zone range is relatively narrower. This ensures that the determined weld heat-affected zone range can truly cover the area where temperature changes during welding affect the microstructure of the base material, avoiding an excessively large or small range that would lead to inaccurate temperature gradient extraction.

[0034] After determining the spatial extent of the weld heat-affected zone (HAZ), multiple temperature sampling points are evenly distributed along the thickness direction of the heterogeneous pipe, i.e., the inner and outer sides of the pipe wall. The number of sampling points is determined based on the pipe wall thickness; the thicker the wall, the more sampling points are needed, typically 5 to 8. The sampling points must be evenly distributed along the entire thickness direction from the inner to the outer wall of the pipe, and all must be located within the determined weld HAZ, with a focus on covering the middle and inner / outer regions of the pipe wall. This ensures comprehensive capture of temperature distribution differences along the thickness direction. The interpass temperature values ​​corresponding to these sampling points are extracted and arranged sequentially from the inner to the outer sampling points to form a thickness-direction temperature gradient sequence. This sequence visually reflects the weld HAZ along the pipe thickness direction. Temperature distribution; time-series analysis is performed on the formed thickness-direction temperature gradient sequence. The core of time-series analysis is to capture the dynamic change trend of the temperature gradient. The specific operation is as follows: Select thickness-direction temperature gradient sequences for two consecutive parameter acquisition cycles. Subtract the temperature value of the corresponding acquisition point in the previous acquisition cycle from the temperature value of each acquisition point in the thickness-direction temperature gradient sequence of the later acquisition cycle to obtain the temperature gradient difference for each acquisition point. Calculate the average value of all temperature gradient differences and use this average value as the total thickness-direction temperature gradient difference between the two acquisition cycles. Divide the total thickness-direction temperature gradient difference by the time interval between the two acquisition cycles, i.e., the acquisition cycle duration, to obtain the rate of change of the thickness-direction temperature gradient. This indicates that the rate of change reflects how quickly the temperature changes along the thickness of the pipe in the weld heat-affected zone. The larger the absolute value, the more drastic the temperature fluctuation in the thickness direction and the more unstable the thermal field. The smaller the absolute value, the more stable the temperature distribution in the thickness direction.

[0035] Step 113: Based on the spatial distribution of interpass temperature along the welding path in the real-time parameter set, extract the width-direction temperature gradient sequence within the welding heat-affected zone. Perform time-series analysis based on the width-direction temperature gradient sequence to obtain the width-direction temperature gradient change rate. Specifically, this includes: extracting the spatial distribution data of interpass temperature along the welding path again from the real-time parameter set, consistent with the data extracted in Step 112. Within the spatial range of the welding heat-affected zone determined in Step 112, along the width direction of the welding heat-affected zone, i.e., the direction perpendicular to the welding path, covering the core areas such as the weld center, both sides of the fusion line, the coarse-grained zone, and the fine-grained zone, evenly arrange multiple temperature acquisition points. The number of acquisition points is determined according to the width of the heat-affected zone, usually 6 to 10 acquisition points are arranged, focusing on covering the junction of the two base materials (near the fusion line) and the edge area of ​​the heat-affected zone, ensuring that the temperature distribution differences in the width direction can be fully captured, especially the temperature gradient differences on the two base material sides, which is consistent with the characteristics of the differences in the base materials of heterogeneous pipes.

[0036] Extract the interpass temperature values ​​corresponding to these sampling points, and arrange them sequentially from sampling points on one base material side to sampling points on another base material side, such as from the low alloy steel side to the austenitic stainless steel side, to form a width-direction temperature gradient sequence. This sequence can intuitively reflect the temperature distribution along the width direction of the weld heat-affected zone, especially the temperature change near the fusion line. Perform time-series analysis on the formed width-direction temperature gradient sequence. The analysis method is completely consistent with the time-series analysis method of the thickness-direction temperature gradient sequence in step 112. Select the width-direction temperature gradient sequence for two consecutive parameter sampling cycles. Subtract the temperature value of the corresponding sampling point in the previous sampling cycle from the temperature value of each sampling point in the width-direction temperature gradient sequence of the later sampling cycle to obtain the temperature gradient difference of each sampling point. Calculate the average value of the temperature gradient differences of all sampling points as the total width-direction temperature gradient difference between the two sampling cycles. Divide the total width-direction temperature gradient difference by the time interval between the two sampling cycles to obtain the width-direction temperature gradient change rate. express, It can reflect the rate of temperature change along the width of the weld heat-affected zone, and is especially able to capture temperature fluctuations near the fusion line. The larger the absolute value, the more drastic the temperature fluctuation in the width direction, and the more unstable the thermal field. The smaller the absolute value, the more stable the temperature distribution in the width direction.

[0037] Step 114: Weight and integrate the temperature gradient change rate in the thickness direction and the temperature gradient change rate in the width direction to obtain the fluctuation characteristics of the temperature gradient in the heat-affected zone; specifically, this includes: setting the temperature gradient change rate in the thickness direction according to the welding requirements and pipe characteristics of the heterogeneous pipe. and the rate of change of temperature gradient in the width direction The weighting coefficients, where the thickness direction weighting coefficient is used. This indicates that the width direction weighting coefficient is used. It means, and and The sum of these values ​​is 1. The weighting coefficients need to be set according to the actual welding conditions of the heterogeneous pipes. For example, for thick-walled heterogeneous pipes, the temperature gradient fluctuation in the thickness direction has a greater impact on the welding quality, so the weighting coefficients are set to 1. It is 0.6. The value is set to 0.4; for thin-walled heterogeneous tubes, the temperature gradient fluctuation in the width direction has a more significant impact on the welding quality, therefore, it is set to 0.4. It is 0.4. It is 0.6; for heterogeneous pipes with conventional wall thickness, it can be set to 0.6. and All values ​​are set to 0.5 to ensure the reasonableness of the weight allocation; after the weight coefficients are set, the following formula is used to... and By performing weighted integration, the fluctuation characteristic value of the temperature gradient in the heat-affected zone is calculated. During the calculation, the result obtained in step 112 is used. The result obtained in step 113 and the pre-set , By substituting each value into the above formula, the fluctuation characteristic value of the temperature gradient in the heat-affected zone can be calculated. , The magnitude of the value directly reflects the degree of fluctuation in the temperature gradient of the heat-affected zone. The larger the value, the more intense the temperature gradient fluctuation along the thickness and width of the heat-affected zone, the more unstable the welding thermal field, and the more likely it is to cause problems such as uneven weld formation and deterioration of the heat-affected zone structure. The smaller the value, the smoother the temperature gradient fluctuation in the heat-affected zone and the more stable the welding thermal field.

[0038] Step 115: Normalize the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone to obtain normalized heat input deviation and temperature gradient fluctuation. Then, linearly weight and fuse the normalized heat input deviation and temperature gradient fluctuation according to a preset dynamic deviation fusion weighting coefficient to form a welding dynamic deviation signal. Specifically, this includes: normalizing the deviation of welding heat input obtained in step 111 to eliminate the dimensional influence of the deviation, allowing it to be fused with the normalized temperature gradient fluctuation. The specific operation of the normalization process is to retrieve a preset maximum permissible deviation of welding heat input. This maximum permissible deviation is determined based on the standard heat input range of the heterogeneous tube welding process window, i.e., the difference between the upper limit and the middle value (or the difference between the middle value and the lower limit) of the standard heat input range. Divide the deviation of welding heat input obtained in step 111 by the preset maximum permissible deviation to obtain the normalized heat input deviation. This indicates the normalized heat input deviation. The numerical range of is 0 to 1, where The closer it is to 1, the closer the deviation of the current welding heat input is to the maximum allowable deviation, and the more serious the deviation is; The closer it is to 0, the smaller the deviation of the current welding heat input, and the closer it is to the standard value; if A value greater than 1 indicates that the deviation of the current welding heat input exceeds the maximum allowable range, requiring close monitoring and timely adjustment.

[0039] Simultaneously, the fluctuation characteristic value of the temperature gradient of the heat-affected zone obtained in step 114 is... Normalization is performed to eliminate the influence of its own dimensions. The specific operation of normalization is to retrieve the preset maximum allowable fluctuation characteristic value of the temperature gradient in the heat-affected zone. This maximum allowable fluctuation characteristic value is determined through previous experiments, that is, the maximum fluctuation value that the temperature gradient in the heat-affected zone can withstand without affecting the welding quality. The fluctuation characteristic value obtained in step 114 is then used as the normalization characteristic value. Dividing by the preset maximum allowable fluctuation characteristic value yields the normalized temperature gradient fluctuation, which is then used... This indicates the normalized temperature gradient fluctuation. The numerical range of is also from 0 to 1, where The closer it is to 1, the closer the fluctuation of the temperature gradient in the current heat-affected zone is to the maximum allowable range, and the more unstable the thermal field is. The closer the value is to 0, the smaller the fluctuation of the temperature gradient in the current heat-affected zone, and the more stable the thermal field; if... A value greater than 1 indicates that the fluctuation of the temperature gradient in the current heat-affected zone exceeds the maximum allowable range, which can easily lead to welding defects.

[0040] After normalization, the normalized heat input deviation is obtained. and normalized temperature gradient fluctuation Then, the two are linearly weighted and fused according to the preset dynamic deviation fusion weight coefficient. The purpose of the fusion is to comprehensively consider the influence of welding heat input deviation and temperature gradient fluctuation in the heat-affected zone on welding quality, and to form a welding dynamic deviation signal that can reflect the current welding condition deviation. First, the dynamic deviation fusion weight coefficient is set, where the normalized heat input deviation is... The fusion weight coefficient is used This indicates that the normalized temperature gradient fluctuation... The fusion weight coefficient is used It means, and and The sum of these values ​​is 1. The weighting coefficients are determined based on the core requirements of heterogeneous pipe welding. For example, when the focus is on weld fusion quality and avoiding incomplete penetration or overheating, Set to 0.6. Setting it to 0.4 emphasizes the impact of heat input deviation; when the focus is on the stability of the microstructure in the heat-affected zone and avoiding coarse grains or excessive residual stress, Set to 0.4. Setting it to 0.6 emphasizes the impact of temperature gradient fluctuations; when both are equally important, and All are set to 0.5.

[0041] The welding dynamic deviation signal value is obtained by linear weighting calculation using the following formula. During the calculation, the normalized heat input deviation is used. Normalized temperature gradient fluctuation and the pre-set fusion weight coefficients , Substitute each value into the above formula to obtain the welding dynamic deviation signal value through calculation. , The numerical range is from 0 to 1. The larger the value, the more serious the deviation in the current welding process and the more unstable the welding conditions, requiring timely adjustment of the welding parameters; The smaller the value, the smaller the deviation in the current welding process, the more stable the welding condition, and the less need for major adjustments.

[0042] By calculating real-time welding heat input values, extracting temperature gradient change rates bidirectionally, and performing weighted fusion, the heat input deviation and temperature gradient fluctuation characteristics of the heat-affected zone during the welding process can be captured. The resulting welding dynamic deviation signal reflects the real-time status of the welding condition, improving the uniformity of weld formation and the stability of the heat-affected zone structure.

[0043] In a preferred embodiment of the present invention, step 2 above involves selecting three characteristic positions on the current weld bead and adjacent weld beads within the welding heat-affected zone based on the welding dynamic deviation signal, and constructing a thermal characteristic unit from the local thermal field distribution of each of the three characteristic positions. The thermal characteristic unit is then divided into heat-affected zones. Based on the distribution characteristics of the base metallurgical properties and thermophysical parameters corresponding to each sub-region after division, a pre-trained coupled calculation model of molten pool flow and heat transfer is used to simulate the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy. The coordinated response values ​​of the temperature field, flow field, and stress field of each sub-region under the welding thermal cycle are calculated to determine the target adjustment amount, which may include:

[0044] In this embodiment of the invention, step 220 involves determining the solidification transition zone behind the molten pool of the current weld bead within the welding heat-affected zone (HAZ) along the welding direction based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, thereby obtaining the first characteristic position. Specifically, this includes: analyzing the welding dynamic deviation signal to determine its characteristic deviation direction and amplitude. The deviation direction is mainly divided into excessive heat input deviation and insufficient heat input deviation, judged by the positive or negative sign of the welding dynamic deviation signal value and the numerical characteristics of the normalized heat input deviation. The deviation amplitude is quantified by the magnitude of the welding dynamic deviation signal value, the normalized heat input deviation, and the normalized temperature gradient fluctuation. A larger signal value indicates a larger deviation amplitude and a more unstable welding thermal field. Combining the analyzed deviation direction and amplitude, and based on the spatial range of the HAZ determined in step 112, locating the solidification transition zone behind the molten pool of the current weld bead along the welding direction (i.e., the weld extension direction). The solidification transition zone behind the molten pool refers to the transition zone from a liquid state to a solidified state during the solidification process of the molten pool. The transition zone between the edge of the molten pool and the fully solidified weld, with a temperature range between the solidus and liquidus of the base metal, is one of the most active areas of microstructure transformation in the weld heat-affected zone (HAZ). Its location and extent change with the deviation in welding heat input. The specific positioning process is as follows: When the deviation is due to excessive heat input, the molten pool temperature rises, the solidification rate slows down, and the solidification transition zone behind the molten pool shifts backward in the welding direction, expanding in size. In this case, based on the deviation magnitude, within the HAZ, along the welding direction, a suitable distance is extended behind the current weld bead's molten pool, and the core area within this region, with a temperature between the solidus and liquidus of the base metal, is selected as the first characteristic location. When the deviation is due to insufficient heat input, the molten pool temperature decreases, the solidification rate accelerates, and the solidification transition zone behind the molten pool shifts forward in the welding direction, shrinking in size. In this case, based on the deviation magnitude, a core area with a temperature between the solidus and liquidus is selected near the molten pool behind the current weld bead, and this core area is selected as the first characteristic location.

[0045] Step 221: Based on the first characteristic position, determine the coarse-grained region of the heat-affected zone (HAZ) of the current weld bead along the welding direction within the HAZ, thus obtaining the second characteristic position. Specifically, this includes determining the core characteristics of the coarse-grained region. The coarse-grained region is the area within the HAZ that has been heated above the austenitizing temperature and cooled slowly, resulting in significant grain growth. The temperature range of this region is higher than the austenitizing temperature of the base metal but lower than the weld pool temperature. Its spatial location is behind the solidification transition zone (along the welding direction), adjacent to the solidification transition zone without a clear boundary, exhibiting only a transition in temperature and microstructure. The specific positioning process is as follows: using the spatial coordinates of the first characteristic position as a basis... The extension is made backward along the welding direction. The extension distance is determined based on the welding speed, heat input deviation, and base material characteristics. For example, when the welding speed is fast and the heat input deviation is small, the extension distance is set to 5 to 8 mm; when the welding speed is slow and the heat input deviation is large, the extension distance is set to 8 to 12 mm to ensure that the extension area is within the heat-affected zone of the weld. Within the extension area, temperature data and preliminary microstructure detection data are collected at different locations to screen out areas where the temperature is higher than the austenitizing temperature of the base material and the grain size is significantly larger than the original grain size of the base material. This area is the coarse grain area of ​​the heat-affected zone of the current weld bead, and the core area of ​​this coarse grain area is selected as the second characteristic position.

[0046] Step 222: Based on the second characteristic position, determine the remelting zone of the heat-affected zone of the adjacent weld bead along the welding direction within the weld heat-affected zone to obtain the third characteristic position. Specifically, this includes: determining the spatial relationship between the adjacent weld bead and the current weld bead. An adjacent weld bead refers to a weld bead that is in the same or adjacent welding layer as the current weld bead and is closely connected to the current weld bead. The heat-affected zone of the adjacent weld bead partially overlaps with the heat-affected zone of the current weld bead. The overlapping area is the remelting zone of the heat-affected zone of the adjacent weld bead. The remelting zone refers to the portion of the heat-affected zone of the current weld bead that was reheated to a molten or semi-molten state during the welding of the adjacent weld bead. The temperature range of this area is close to or reaches the liquidus line of the base material. Its location is in the overlapping area of ​​the heat-affected zone of the current weld bead and the heat-affected zone of the adjacent weld bead, and it is close to the molten pool of the adjacent weld bead. The specific positioning process is as follows: using the spatial coordinates of the second characteristic position as a reference, continue to extend backward along the welding direction. Simultaneously, the weld bead is offset towards the adjacent weld bead. The offset distance is determined according to the weld bead spacing, usually equal to 1 / 2 to 2 / 3 of the weld bead width. This ensures that the offset area is within the heat-affected zone (HAZ) of the adjacent weld bead. Within this offset extension area, temperature data and melting state detection data are collected at different locations. Areas with temperatures close to or reaching the liquidus line of the base material and with obvious remelting traces are selected. This area is the HAZ remelting zone of the adjacent weld bead. The core area of ​​this remelting zone is selected as the third feature position. The spatial coordinates, base material side, temperature data, and remelting state information of the third feature position are recorded. This ensures that the third feature position is within the HAZ of the adjacent weld bead and has a reasonable spatial relationship with the second feature position. The three feature positions are distributed sequentially along the welding direction (first feature position, second feature position, third feature position), covering the core HAZ of the current weld bead and the adjacent weld bead.

[0047] Step 223: Collect temperature gradient data and cooling rate data along the thickness direction at the first feature location to obtain the first local thermal field distribution; based on the first local thermal field distribution and the second feature location, collect temperature gradient data and cooling rate data along the thickness direction at the second feature location to obtain the second local thermal field distribution; based on the second local thermal field distribution and the third feature location, collect temperature gradient data and cooling rate data along the thickness direction at the third feature location to obtain the third local thermal field distribution; specifically, this includes: collecting the local thermal field distribution at the first feature location; at the first feature location, uniformly arranging multiple temperature sampling points along the thickness direction of the heterogeneous pipe; the number of sampling points is determined according to the pipe wall thickness and is consistent with the number of sampling points along the thickness direction in step 112 (usually 5 to 8); the sampling points are located inside the pipe. The temperature data is uniformly distributed from the wall to the outer wall and is located within the welding heat-affected zone. Temperature data at each sampling point is collected in real time. Based on the collected temperature data, the temperature difference between each sampling point is calculated and then divided by the distance between adjacent sampling points to obtain the temperature gradient data of the first characteristic position in the thickness direction. At the same time, the temperature data of each sampling point in two consecutive sampling cycles is recorded. The temperature value of the second sampling cycle is subtracted from the temperature value of the first sampling cycle and then divided by the time interval between the two sampling cycles to obtain the cooling rate data of the first characteristic position in the thickness direction. The temperature gradient data and cooling rate data are integrated in the order of sampling points in the thickness direction to obtain the first local thermal field distribution. This distribution can intuitively reflect the thermal field change along the thickness direction of the pipe at the first characteristic position (solidification transition zone behind the molten pool).

[0048] The local thermal field distribution at the second characteristic location is collected. Taking the first local thermal field distribution as a reference, and combining the spatial coordinates and temperature reference of the second characteristic location obtained in step 221, the same number of temperature acquisition points as the first characteristic location are arranged along the thickness direction of the heterogeneous tube at the second characteristic location. The arrangement of the acquisition points is consistent with that of the first characteristic location to ensure the comparability of the collected data. Referring to the temperature range of the first local thermal field distribution, the temperature data of each acquisition point is accurately collected, and the temperature gradient data of the second characteristic location in the thickness direction is calculated. Using the same method as the first characteristic location, the cooling rate data of the second characteristic location in the thickness direction is calculated. The temperature gradient data and the cooling rate data are integrated to obtain the second local thermal field distribution. This distribution reflects the thermal field change along the thickness direction at the second characteristic location (the coarse grain region of the current weld heat-affected zone) and contrasts with the first local thermal field distribution to reflect the thermal field difference between the two characteristic locations.

[0049] The local thermal field distribution at the third characteristic location is collected. Taking the second local thermal field distribution as a reference, and combining the spatial coordinates and temperature reference of the third characteristic location obtained in step 222, the same number of temperature acquisition points are arranged along the thickness direction of the heterogeneous tube at the third characteristic location. The arrangement of the acquisition points is the same as that of the first two characteristic locations. Referring to the temperature range of the second local thermal field distribution, the temperature data of each acquisition point is collected, and the temperature gradient data of the third characteristic location in the thickness direction is calculated. The cooling rate data is calculated using the same method. The two are integrated to obtain the third local thermal field distribution. This distribution reflects the thermal field change along the thickness direction at the third characteristic location (the remelting zone of the heat-affected zone of the adjacent weld bead). It forms a coherent thermal field sequence with the first two local thermal field distributions. The three local thermal field distributions all contain the temperature gradient data and cooling rate data in the thickness direction, and correspond to the three characteristic locations respectively.

[0050] Step 224: Based on the first, second, and third local thermal field distributions, and according to the relative spatial relationship between the current weld bead and the adjacent weld bead within the heat-affected zone (HAZ), a thermal feature unit is formed. Specifically, this includes: determining the relative spatial relationship between the current weld bead and the adjacent weld bead, with the current weld bead and the adjacent weld bead arranged sequentially along the welding direction, their HAZs partially overlapping; the first and second feature positions are located within the HAZ of the current weld bead and are distributed sequentially along the welding direction (the first feature position is closer to the molten pool, and the second feature position is located behind the first feature position); the third feature position is located within the HAZ of the adjacent weld bead and is close to the overlapping area of ​​the HAZs of the current weld bead and the adjacent weld bead. The three feature positions are arranged along the welding direction. The directions form a coherent spatial sequence. According to this spatial sequence, the three local thermal field distributions are combined. The first local thermal field distribution (corresponding to the solidification transition zone behind the current weld pool) is used as the front-end thermal field data of the thermal feature unit, the second local thermal field distribution (corresponding to the coarse grain zone of the current weld heat-affected zone) is used as the middle thermal field data of the thermal feature unit, and the third local thermal field distribution (corresponding to the remelting zone of the adjacent weld heat-affected zone) is used as the rear-end thermal field data of the thermal feature unit. This ensures that the combined thermal field data can reflect the coherent thermal field changes of the current weld and the adjacent weld heat-affected zone. During the combination process, the temperature gradient data, cooling rate data, spatial coordinates of each feature position, and information such as the base material side are simultaneously integrated from the three local thermal field distributions to form a complete thermal feature unit.

[0051] Step 225: Based on the local thermal field distribution at three characteristic locations in the thermal feature unit, and combined with the metallurgical bonding boundary between the current weld and adjacent welds at the base metal interface, the heat-affected zone is divided into three sub-regions: a thermal cycle sensitive zone near the current weld, a metallurgical transition zone at the base metal interface, and a thermal stress superposition zone near adjacent welds. Based on these three sub-regions, the distribution characteristics of the base metallurgical properties and thermophysical parameters corresponding to each sub-region are extracted to obtain the material property parameter set for each sub-region. Specifically, this includes determining the metallurgical bonding boundary at the base metal interface, for heterogeneous pipe welds... For example, in butt welding of austenitic stainless steel and low alloy steel, the base material interface is the joint surface of two different base materials. The metallurgical bond boundary refers to the area where the two base materials undergo a metallurgical reaction and form a metallurgical bond during the welding process. The location of this boundary can be determined by the temperature distribution data and base material composition distribution data in the thermal characteristic unit. It is usually located at the junction of the two base materials and is offset from the weld center. Combining the local thermal field distribution at three characteristic positions in the thermal characteristic unit, three sub-regions are divided. The thermal cycle sensitive area is close to the current weld bead. The sub-regions are divided by the local thermal field distribution at the first and second characteristic positions. The core region is characterized by drastic temperature cycling (rapid heating and cooling), primarily located on a single base material side, such as the low-alloy steel side or the austenitic stainless steel side. It exhibits a large temperature gradient and a high cooling rate, making it the most sensitive region to the influence of welding thermal cycles on the base material microstructure. Its extent extends from the edge of the current weld pool to a certain distance behind the second characteristic position, ensuring coverage of the thermal field areas corresponding to the first and second characteristic positions. The metallurgical transition zone is located at the base material interface, spanning two base materials. Its extent covers the metallurgical bonding boundary between the base materials. The thermal field distribution in this region is less uniform, with a temperature gradient between... Between the cyclic sensitive zone and the thermal stress superposition zone is the core area where metallurgical reactions and element diffusion occur between the two base materials. Its range is determined based on the abrupt temperature distribution areas in the thermal characteristic unit to ensure coverage of the joint between the two base materials. The thermal stress superposition zone is close to the adjacent weld bead and is centered on the local thermal field distribution at the third characteristic position. This area is simultaneously affected by the heat of the current weld bead and the adjacent weld bead, resulting in significant thermal stress superposition, relatively gentle temperature cyclic changes, and a low cooling rate. Its range extends from the third characteristic position to the edge of the molten pool of the adjacent weld bead to ensure coverage of the thermal field area corresponding to the third characteristic position.

[0052] After dividing the region into three sub-regions, the distribution characteristics of the metallurgical properties and thermophysical parameters of the parent material corresponding to each sub-region are extracted. For the thermal cycling sensitive region, the metallurgical properties of the parent material are extracted, such as phase transformation temperature, alloy element content, solid-state phase transformation behavior, and thermophysical parameters, such as thermal conductivity, specific heat capacity, and coefficient of linear expansion. Since this region is located on a single parent material side, the parameter distribution is relatively uniform, and the relevant parameters of the parent material can be directly extracted. For the metallurgical transition region, the metallurgical properties and thermophysical parameters of the two parent materials are extracted, focusing on the distribution changes of parameters along the parent material interface to reflect the transition characteristics of the two parent materials. For the thermal stress superposition region, the metallurgical properties and thermophysical parameters of the parent material are extracted and compared with the parameters of the thermal cycling sensitive region to reflect the parameter differences in different regions. The metallurgical properties and thermophysical parameters extracted from each sub-region are organized and integrated to form a set of material property parameters for each sub-region. Each parameter set contains the metallurgical property parameters and thermophysical parameters of that sub-region, as well as the distribution law of the parameters.

[0053] Step 226: Based on the material property parameter set of each sub-region and the local thermal field distribution at three characteristic locations in the thermal feature unit, determine the boundary heat flux density of each sub-region. Call the pre-trained molten pool flow and heat transfer coupling calculation model, inputting the boundary heat flux density into the model to simulate the fluid flow behavior of the molten pool under the combined effects of Marangoni convection caused by the surface tension gradient, electromagnetic force generated by the welding current, and thermal buoyancy caused by the molten pool density difference, thus obtaining the fluid flow distribution of the molten pool. Specifically, this includes: determining the boundary heat flux density of each sub-region. Boundary heat flux density refers to the heat flow per unit area through the boundary of a sub-region, and its magnitude is closely related to the material property parameters and thermal field distribution of the sub-region. Based on the thermal conductivity of the material property parameter set of each sub-region, combined with the local thermal field distribution (temperature gradient data) at three characteristic locations in the thermal feature unit, calculate the boundary heat flux density of each sub-region using Fourier's law. The calculation formula is as follows: ,in The boundary heat flux density of each sub-region, Thermal conductivity, representing the concentrated material properties of each sub-region, and different sub-regions. Since the values ​​are different, the average thermal conductivity of the two base materials must be used for calculation in the metallurgical transition zone; / The temperature gradient along the normal to the sub-region boundary is represented by the temperature gradient data at each feature location within the thermal feature unit. This is extracted from the temperature gradient data within the thermal feature unit along the boundary normal. The negative sign indicates that the heat flow direction is opposite to the temperature gradient direction, meaning heat is transferred from the high-temperature region to the low-temperature region, thus affecting the temperature gradient of each sub-region. Value and corresponding / Substituting into the formula, the boundary heat flux density of each sub-region is calculated and used as one of the input parameters for the model simulation.

[0054] Based on the pipe specifications (diameter, wall thickness), welding joint type (butt weld), and weld dimensions (width, height) of the heterogeneous pipes, a three-dimensional geometric model consistent with the actual welding conditions is constructed. The three-dimensional geometric model covers the current weld bead, adjacent weld beads, the weld heat-affected zone, and the junction area of ​​the two base materials. Simultaneously, the molten pool area is meshed more precisely, and the weld heat-affected zone and base material areas are rationally meshed, balancing simulation accuracy and computational efficiency. The model includes two core physical fields: the flow field and the temperature field, with corresponding governing equations established for each. The flow field governing equations use the Navier-Stokes equations to describe the flow behavior of the molten pool fluid, considering Marangoni convection caused by the surface tension gradient, the electromagnetic force generated by the welding current, and the thermal buoyancy caused by the density difference in the molten pool. The equations are as follows:

[0055] ,in The density of the molten pool metal, The velocity vector of the molten pool fluid. For time, The internal pressure of the molten pool The dynamic viscosity of the molten pool metal. It is the acceleration due to gravity. Electromagnetic force, For Marangoni; As the fundamental operator for multiphysics simulation of welding, the temperature field control equation uses the heat conduction equation to describe the heat transfer process in the molten pool and heat-affected zone, considering convective heat transfer caused by fluid flow. The equation is as follows:

[0056] ,in, The isobaric specific heat capacity of the molten pool metal. For temperature, The internal heat source intensity is given, and the remaining parameters are consistent with the flow field control equations.

[0057] Based on actual welding conditions, the boundary conditions of the model are set. The welding arc heat input boundary adopts the Gaussian heat source model, and the boundary heat flux density calculated in step 226 is used as the heat input boundary condition. The surface boundary of the molten pool considers the surface tension gradient and atmospheric pressure, and sets the Marangoni convection boundary condition. The bottom and side boundaries of the workpiece consider air convection and thermal radiation, and set the heat dissipation boundary condition. The welding current boundary is set according to the welding current in the real-time parameter set and is used to calculate the electromagnetic force. The model is pre-trained using experimental data. Different welding parameters (welding current, voltage, speed) are selected for the welding of heterogeneous tubes. Data such as the shape of the molten pool, temperature distribution, and fluid flow velocity during the test are collected. The experimental data are input into the model, and parameters such as dynamic viscosity, surface tension coefficient, and electromagnetic force coefficient in the model are adjusted so that the error between the model simulation results and the experimental data is controlled within 5%. The pre-training and calibration of the model are completed to ensure that the model can accurately simulate the molten pool flow and heat transfer behavior in the actual welding process.

[0058] After the model is built, the pre-trained coupled calculation model of molten pool flow and heat transfer is called. The boundary heat flux density of each sub-region calculated in step 226 is input into the model. At the same time, the material property parameter set (thermal conductivity, specific heat capacity, density, etc.) of each sub-region and the real-time welding parameters (welding current, voltage, velocity) are also input. According to the established control equations and boundary conditions, the model simulates the fluid flow behavior of the molten pool under the combined action of three forces. Marangoni convection caused by the surface tension gradient causes the fluid on the surface of the molten pool to flow from the high temperature zone to the low temperature zone. The electromagnetic force generated by the welding current causes the fluid in the molten pool to converge towards the center of the weld. The thermal buoyancy caused by the density difference of the molten pool causes the high temperature fluid to flow upward and the low temperature fluid to flow downward. The interaction of the three forces forms a complex fluid flow in the molten pool. After the simulation is completed, the fluid flow distribution of the molten pool is output. This distribution includes the magnitude and direction of the fluid flow velocity at different locations in the molten pool, clearly reflecting the flow law of the molten pool fluid, especially the fluid flow characteristics of each sub-region.

[0059] Step 227: Based on the fluid flow distribution of the molten pool, the thermal field distribution process under the influence of fluid flow is simulated again in the coupled calculation model of molten pool flow and heat transfer to obtain the thermal field redistribution results of the molten pool and heat-affected zone. Specifically, this includes: determining the influence mechanism of fluid flow on the thermal field distribution. Fluid flow in the molten pool will drive heat transfer and change the distribution pattern of the thermal field. For example, Marangoni convection will transfer the high-temperature heat from the center of the molten pool to the edge of the molten pool, electromagnetic force will cause heat to converge towards the center of the weld, and thermal buoyancy will promote heat exchange between the upper and lower regions. These flow behaviors will cause the temperature distribution of the molten pool and heat-affected zone to be readjusted, forming a new thermal field distribution; the molten pool flow obtained in step 226 is then used to calculate the thermal field distribution. The fluid flow distribution (flow velocity, flow direction) is input into the coupled calculation model of molten pool flow and heat transfer. The model combines the previously set boundary conditions, material property parameter sets of each sub-region, and temperature field control equations to perform simulation calculations again. During the simulation, the model uses the fluid flow velocity as the convection term parameter in the temperature field control equations to calculate the convective heat transfer caused by the fluid flow, and then simulates the heat field distribution process under the influence of fluid flow. The focus is on calculating the temperature changes in the molten pool and the three sub-regions. After the simulation is completed, the heat field redistribution results of the molten pool and the heat-affected zone are output. These results include the temperature values ​​at different spatial locations in the molten pool and the three sub-regions, as well as the temperature distribution patterns.

[0060] Step 228: Based on the thermal field redistribution results, calculate the peak temperature and temperature cycle change process of the temperature field in each sub-region under welding thermal cycling to obtain the temperature field calculation results for each sub-region. Specifically, this includes: for the thermal cycling sensitive area, selecting temperature data from all spatial locations within the sub-region from the thermal field redistribution results, statistically analyzing these temperature data to find the maximum value, which is the peak temperature of the temperature field in the thermal cycling sensitive area under welding thermal cycling. The peak temperature directly reflects the highest temperature heated in the region and is closely related to the phase transformation temperature and grain growth law of the base material. Extract the temperature data of a core acquisition point within the sub-region, organize it according to the time series, and obtain the temperature change process from the start to the end of welding at that acquisition point, i.e., the temperature cycle change process. This process includes the temperature change laws of the heating stage, the holding stage, and the cooling stage, which can reflect the thermal cycling characteristics of the sub-region. For the metallurgical transition zone, the same method as for the thermal cycling sensitive area is used. The method involves filtering all temperature data within a sub-region from the thermal field redistribution results, identifying the maximum temperature value, and using this as the peak temperature of the metallurgical transition zone. Temperature data from core acquisition points within this sub-region is extracted and organized according to a time series to obtain the temperature cycle change process of the metallurgical transition zone. Emphasis is placed on the temperature changes at the junction of the two base materials to reflect the temperature characteristics during the metallurgical reaction process. For the thermal stress superposition zone, the same method is used to filter temperature data from the thermal field redistribution results to determine its peak temperature. Temperature data from core acquisition points is extracted and organized to obtain the temperature cycle change process, focusing on the temperature change pattern under the superposition of thermal effects between the current weld and adjacent welds to reflect the temperature basis of thermal stress superposition. The peak temperatures and temperature cycle change processes of the three sub-regions are then organized to form the temperature field calculation results for each sub-region. Each sub-region's temperature field calculation result includes a peak temperature value and a temperature cycle change curve (or time series data).

[0061] Step 229: Based on the temperature field calculation results of each sub-region, and combined with the fluid flow distribution of the molten pool, calculate the flow velocity and flow direction distribution of the flow field in each sub-region under the welding thermal cycle, and obtain the flow field calculation results for each sub-region; specifically, this includes: determining the correlation between the temperature field and the flow field. The distribution of the temperature field affects the density and viscosity of the molten pool fluid, which in turn affects the flow velocity and direction of the fluid. For example, an increase in temperature will decrease the fluid density and viscosity, and the flow velocity will increase accordingly. Changes in the temperature gradient will change the surface tension gradient, which in turn affects the direction and intensity of Marangoni convection; for the thermal cycle sensitive area, combine the temperature field calculation results of that sub-region (peak temperature, temperature cycle...) (Circular Change Process) From the molten pool fluid flow distribution obtained in step 226, the flow velocity and flow direction data of all spatial locations in the sub-region are selected. According to the temperature distribution law of the temperature field, the flow velocity data is corrected. For the region where the temperature is 80% higher than the peak temperature, the fluid viscosity decreases and the flow velocity is multiplied by a correction factor of 1.1 to 1.2. For the region where the temperature is 50% lower than the peak temperature, the fluid viscosity increases and the flow velocity is multiplied by a correction factor of 0.8 to 0.9. The correction factor is determined according to the material property parameters (the relationship between viscosity and temperature) of the sub-region. After the correction is completed, the flow velocity and flow direction distribution of the heat cycle sensitive area under the welding heat cycle are obtained.

[0062] For the metallurgical transition zone, the same method as for the thermal cycling sensitive zone is used. Combining the temperature field calculation results for this sub-region, the flow velocity and direction data for the corresponding region are selected from the molten pool fluid flow distribution. Based on the viscosity characteristics and temperature distribution of the two base materials, the flow velocity is corrected (different correction coefficients for different base materials, tailored to their respective thermophysical parameters). The flow velocity and direction distribution of the metallurgical transition zone are then obtained, with a focus on the changes in flow velocity and direction at the junction of the two base materials, reflecting the flow dynamics of element diffusion. For the thermal stress superposition zone, combining the temperature field calculation results for this sub-region, the flow velocity and direction data for the corresponding region are selected from the molten pool fluid flow distribution. Based on the temperature cycling pattern of this region (slower cooling rate, more uniform temperature distribution), the flow velocity is corrected (correction coefficients are set between 0.95 and 1.05, with small fluctuations). The flow velocity and direction distribution of the thermal stress superposition zone are then obtained, with a focus on the impact of thermal stress superposition on flow behavior. The flow velocity and direction distributions of the three sub-regions are then compiled separately to form the flow field calculation results for each sub-region.

[0063] Step 230: Based on the temperature field calculation results and flow field calculation results of each sub-region, calculate the equivalent residual stress value of the stress field of each sub-region under the welding thermal cycle, and obtain the stress field calculation results of each sub-region; specifically, the formula for the equivalent residual stress value is as follows:

[0064] ,in This represents the equivalent residual stress value for each sub-region, used to comprehensively reflect the magnitude of residual stress within the sub-region; , , These are the normal stresses in the x, y, and z directions, respectively. The x direction is the welding direction, the y direction is the width direction of the heterogeneous tube, and the z direction is the thickness direction of the heterogeneous tube. , , These are the shear stresses in three planes. The specific calculation process is as follows: Based on the temperature field calculation results of each sub-region, combined with the material property parameter set (coefficient of linear expansion, modulus of elasticity) of the sub-region, the temperature stress is calculated. The temperature stress is equal to the modulus of elasticity multiplied by the coefficient of linear expansion, and then multiplied by the temperature difference in the temperature field calculation results (the difference between the temperature at a point in the sub-region and room temperature). That is, temperature stress = modulus of elasticity × coefficient of linear expansion × temperature difference. This temperature stress is taken as the normal stress. , , The basic components.

[0065] Based on the flow field calculation results (flow velocity, flow direction) for each sub-region, the stress caused by fluid flow is calculated. The greater the fluid flow velocity and the more drastic the change in flow direction, the greater the resulting shear stress. , , The magnitude of the shear stress is proportional to the square of the flow velocity, i.e., shear stress = flow resistance coefficient × flow velocity². The flow resistance coefficient is determined based on the material properties (viscosity) of the sub-region. The calculated normal stress is then... , , and shear stress , , Substituting into the equivalent stress formula, the equivalent residual stress values ​​of the three sub-regions are calculated respectively. In the thermal cycling sensitive region, the temperature gradient is large, the cooling rate is fast, the temperature stress is relatively large, the fluid flow velocity is moderate, and the shear stress is moderate. The equivalent residual stress value of this region is calculated using the formula, with a focus on the thermal stress generated during cooling. In the metallurgical transition region, two base materials are joined, and there are differences in the coefficient of linear expansion and elastic modulus, resulting in uneven temperature stress distribution, high fluid flow velocity, and high shear stress. The equivalent residual stress value of this region is calculated using the formula, with a focus on the stress generated by the difference in shrinkage between the two base materials. In the thermal stress superposition region, the current weld bead and adjacent weld beads have superimposed thermal effects, resulting in significant temperature stress superposition. The fluid flow velocity is relatively low, and the shear stress is relatively low. The equivalent residual stress value of this region is calculated using the formula, with a focus on the stress generated by the superposition of thermal effects. After the calculation is completed, the equivalent residual stress values ​​of the three sub-regions are organized to form the stress field calculation results for each sub-region.

[0066] Step 231: Based on the calculated results of the temperature field, flow field, and stress field of each sub-region, perform multi-physics coupling analysis to obtain the coordination response value of each sub-region under the condition of satisfying metallurgical bonding strength and thermal stress coordination. Then, determine the target adjustment amount based on the difference between the coordination response value and the preset coordination target value. Specifically, this includes performing multi-physics coupling analysis. The core of multi-physics coupling analysis is to analyze the interaction between the temperature field, flow field, and stress field, as well as the comprehensive influence of each field on welding quality. The specific analysis content is as follows: the peak temperature and temperature cycling process of the temperature field determine the microstructure transformation and grain growth of the base material, thus affecting the metallurgical bonding strength; the flow velocity and direction of the flow field determine the forming quality of the molten pool and the uniformity of element distribution, thus affecting the weld's metallurgical bonding strength. The bonding effect; the equivalent residual stress value of the stress field directly affects the strength and stability of the welded joint. Excessive residual stress can lead to weld cracking. For each sub-region, the synergistic effect of temperature field, flow field, and stress field calculations are analyzed. For example, in the thermal cycling sensitive zone, if the temperature field peak is too high, it will lead to coarse grains. At the same time, insufficient flow velocity will lead to uneven element distribution, thereby reducing the metallurgical bonding strength. Excessive equivalent residual stress will exacerbate defect generation. In the metallurgical transition zone, if the temperature field distribution is uneven, it will lead to insufficient metallurgical reaction between the two base materials. An unreasonable flow direction will lead to uneven element diffusion. Uneven stress field distribution will increase the risk of joint cracking. In the thermal stress superposition zone, if the temperature field cooling rate is too slow, residual stress will be superimposed. Insufficient flow will lead to poor weld formation.

[0067] Through the above coupling analysis, the coordination response values ​​of each sub-region under the conditions of satisfying metallurgical bonding strength and thermal stress coordination are obtained. The coordination response value is a quantitative index that comprehensively reflects the degree of synergistic adaptation of the temperature field, flow field, and stress field of each sub-region. Its value ranges from 0 to 1. The closer the value is to 1, the more the multi-physics field distribution of the sub-region meets the requirements of metallurgical bonding strength and thermal stress coordination, and the more guaranteed the welding quality. The closer the value is to 0, the more obvious the deviation of the multi-physics field distribution of the sub-region is, and parameter adjustment is required. The preset coordination target value is retrieved. This coordination target value is determined in advance through experiments based on the quality requirements of heterogeneous pipe welding. Corresponding coordination target values ​​are set for the three sub-regions, usually set to 0.8 to 0.9, to ensure the metallurgical bonding strength and thermal stress stability of the welded joint. The difference between the coordination response value of each sub-region and the preset coordination target value is calculated. The difference is calculated by subtracting the preset coordination target value from the coordination response value. If the difference is positive or negative, the difference is considered positive. A difference close to 0 indicates that the multiphysics distribution of the sub-region meets the requirements and no adjustment is needed. If the difference is negative, it indicates that there is a deviation in the multiphysics distribution of the sub-region. The larger the absolute value of the difference, the more serious the deviation, and targeted adjustments are required. Based on the differences in each sub-region, the target adjustment amount is determined. The size of the target adjustment amount is proportional to the absolute value of the difference; the larger the absolute value of the difference, the larger the target adjustment amount. The direction of the target adjustment amount is determined according to the type of deviation. For example, if the coordinated response value is low in the thermal cycling sensitive area due to an excessively high temperature peak, the target adjustment amount is to reduce the welding heat input. If the coordinated response value is low in the metallurgical transition area due to insufficient flow velocity, the target adjustment amount is to adjust the welding speed or welding current to increase the flow velocity of the molten pool. If the coordinated response value is low in the thermal stress superposition area due to excessive residual stress, the target adjustment amount is to adjust the cooling rate to reduce residual stress. The final target adjustment amount is obtained by integrating the differences in the three sub-regions.

[0068] Based on the welding dynamic deviation signal, three core feature positions are selected to construct a thermal feature unit that can reflect the thermal field correlation between weld beads. Combined with the interface characteristics of the base material, three sub-regions are divided to realize the partitioning of the heat-affected zone. A coupled calculation model of molten pool flow and heat transfer is constructed to simulate the molten pool fluid flow and heat field redistribution process. Combined with multi-physics field coupling analysis, the uniformity of weld formation and the consistency of element distribution are improved.

[0069] In a preferred embodiment of the present invention, step 3 above, which calculates the adjustment command of the welding equipment based on the welding dynamic deviation signal and the target adjustment amount, combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous tubes, may include:

[0070] In this embodiment of the invention, step 330 involves extracting the direction and magnitude of heat input deviation from the welding dynamic deviation signal, and simultaneously extracting the amplitude and frequency of temperature gradient fluctuations from the temperature gradient fluctuation characteristics of the heat-affected zone, to obtain the dynamic deviation characteristics of the welding process. Specifically, this includes: separating the welding heat input deviation from the welding dynamic deviation signal. This deviation is the raw deviation data calculated in step 111 without normalization. Two core features are extracted from this deviation: the direction and magnitude of heat input deviation. The direction of heat input deviation is determined by the sign of the deviation. If the deviation is positive, it indicates that the heat input deviation is excessive, i.e., the current... The real-time heat input is higher than the standard reference value. If the deviation is negative, it indicates that the heat input is insufficient, meaning the current real-time heat input is lower than the standard reference value. If the deviation is 0, it indicates no deviation. The deviation range is determined by the absolute value of the deviation, meaning the deviation range equals the absolute value of the deviation. The magnitude of the deviation range directly reflects the severity of the deviation from the standard reference value. The larger the deviation range, the greater the difference between the heat input and the standard value, and the more significant the impact on welding quality. For example, if the deviation is 20 J / mm, it indicates that the heat input is excessive, with a deviation range of 20 J / mm; if the deviation is -15 J / mm, it indicates that the heat input is insufficient, with a deviation range of 15 J / mm.

[0071] The fluctuation characteristics of the temperature gradient in the heat-affected zone are extracted from the welding dynamic deviation signal. These fluctuation characteristics are the original fluctuation data corresponding to the fluctuation characteristic values ​​calculated in step 114. Two core features are extracted from these fluctuation characteristics: temperature gradient fluctuation amplitude and fluctuation frequency. The temperature gradient fluctuation amplitude refers to the difference between the maximum and minimum values ​​of the temperature gradient fluctuation characteristic value within multiple consecutive parameter acquisition cycles. That is, the temperature gradient fluctuation amplitude equals the maximum value minus the minimum value of the fluctuation characteristic value. The larger the amplitude, the more violent the temperature gradient fluctuation and the less stable the welding thermal field. The fluctuation frequency refers to the number of times the temperature gradient fluctuation characteristic value exceeds the preset standard temperature gradient fluctuation range per unit time. Specifically, it is calculated by counting the number of times the fluctuation characteristic value exceeds the standard range per unit time (usually 1 minute). This number is the fluctuation frequency. The higher the frequency, the more frequent the temperature gradient fluctuation and the worse the thermal field stability. The four features extracted—heat input deviation direction, heat input deviation amplitude, temperature gradient fluctuation amplitude, and temperature gradient fluctuation frequency—are integrated to form the dynamic deviation characteristics of the welding process.

[0072] Step 331: Based on the dynamic deviation characteristics, and combined with the preset standard heat input range and standard temperature gradient range in the heterogeneous pipe welding process window, determine the heat input compensation direction and heat input compensation amount required for welding heat input, as well as the gradient compensation direction and gradient compensation amount required for the temperature gradient of the heat-affected zone, to obtain the basic compensation requirements for the welding process; specifically, this includes: retrieving the preset standard heat input range and standard temperature gradient range in the heterogeneous pipe welding process window. The standard heat input range is the heat input range preset in step 111, determined according to parameters such as the heterogeneous pipe base material type and pipe specifications, and is used to ensure welding quality; The standard temperature gradient range is a temperature gradient range determined in advance through experiments and simulations to ensure the stability of the microstructure of the weld heat-affected zone. This range matches the thermophysical parameters and phase transformation characteristics of the two base materials, avoiding defects such as coarse grains and excessive residual stress in the heat-affected zone due to excessive temperature gradient fluctuations. The direction and amount of heat input compensation for welding heat input are determined. The direction of heat input compensation is opposite to the direction of heat input deviation extracted in step 330. That is, if the heat input deviation is excessive, the compensation direction is to reduce the heat input; if the heat input deviation is insufficient, the compensation direction is to increase the heat input; if there is no deviation, no compensation is required.

[0073] The determination of the heat input compensation amount needs to consider both the heat input deviation range and the standard heat input range. Specifically, when the heat input deviation range is less than or equal to the maximum allowable deviation of the standard heat input range, the heat input compensation amount equals the heat input deviation range, ensuring that the compensation amount is exactly equal to the deviation range and that the heat input returns to the standard range after compensation. When the heat input deviation range is greater than the maximum allowable deviation of the standard heat input range, the heat input compensation amount equals the maximum allowable deviation of the standard heat input range to avoid overcompensation leading to new deviations. The maximum allowable deviation of the standard heat input range is the difference between the upper limit and the middle value (or the difference between the middle value and the lower limit) of the standard heat input range. The gradient compensation direction and amount for the temperature gradient in the heat-affected zone must be determined. The gradient compensation direction is opposite to the deviation direction of the temperature gradient fluctuation. That is, if the temperature gradient fluctuation amplitude exceeds the upper limit of the standard temperature gradient range, it indicates that the fluctuation is too large, and the compensation direction is to reduce the temperature gradient fluctuation. If the fluctuation amplitude is lower than the lower limit of the standard range, it indicates that the fluctuation is too small (usually no compensation is needed, only fine-tuning is required when it affects metallurgical bonding), and the compensation direction is to appropriately increase the fluctuation. If the fluctuation amplitude is within the standard range, no compensation is needed.

[0074] The determination of the gradient compensation amount combines the temperature gradient fluctuation amplitude and the standard temperature gradient range. Specifically, the gradient compensation amount is equal to the absolute value of the difference between the temperature gradient fluctuation amplitude and the median value of the standard temperature gradient range. That is, the gradient compensation amount is equal to the temperature gradient fluctuation amplitude minus the absolute value of the median value of the standard temperature gradient range. This ensures that the temperature gradient fluctuation amplitude returns to the standard range after compensation. At the same time, the fluctuation frequency is taken into account. The higher the frequency, the more appropriate the compensation amount can be to quickly stabilize the thermal field. The determined heat input compensation direction, heat input compensation amount, gradient compensation direction, and gradient compensation amount are integrated to form the basic compensation requirements for the welding process.

[0075] Step 332: Based on the basic compensation requirements and the target adjustment amount, extract the welding heat input compensation value and thermal field distribution correction value required for each sub-region to meet the conditions of metallurgical bonding strength and thermal stress coordination. Distribute the welding heat input compensation value and thermal field distribution correction value according to the spatial position weight of each sub-region in the welding heat-affected zone to obtain the coordination compensation characteristics of the welding process. Specifically, this includes: determining the correlation between the target adjustment amount and the basic compensation requirements. The target adjustment amount is a precise adjustment parameter determined for the multi-physics distribution deviation of the three sub-regions, while the basic compensation requirements are a preliminary compensation scheme for the overall welding condition. Combining the two, extract the specific compensation parameters for each sub-region to ensure the targeted nature of the compensation; combining the heat input compensation amount and the target adjustment amount in the basic compensation requirements, extract the compensation parameters for each sub-region... To meet the welding heat input compensation values ​​required for metallurgical bond strength and thermal stress coordination, for thermally sensitive areas, where temperature cycling is drastic and heat input is sensitive, the heat input compensation value is equal to 40% to 50% of the heat input compensation amount in the basic compensation requirement. This ensures rapid adjustment of heat input deviations in this area and avoids grain coarsening. For metallurgical transition areas, where the metallurgical reaction is complex at the junction of two base materials, the heat input compensation value is equal to 30% to 40% of the heat input compensation amount in the basic compensation requirement. This takes into account the metallurgical characteristics of the two base materials and ensures metallurgical bond strength. For thermal stress superposition areas, where thermal stress superposition is significant and the impact of heat input is relatively small, the heat input compensation value is equal to 10% to 20% of the heat input compensation amount in the basic compensation requirement. This avoids excessive adjustment that could lead to further thermal stress superposition.

[0076] Combining the gradient compensation amount and target adjustment amount in the basic compensation requirements, the required thermal field distribution correction value for each sub-region is extracted. This correction value is used to adjust the temperature gradient distribution of each sub-region, making the thermal field more stable. For the thermally sensitive zone, the thermal field distribution correction value is equal to 50% to 60% of the gradient compensation amount in the basic compensation requirements, focusing on suppressing temperature gradient fluctuations in this region. For the metallurgical transition zone, the thermal field distribution correction value is equal to 30% to 35% of the gradient compensation amount in the basic compensation requirements, focusing on optimizing the temperature gradient uniformity at the junction of the two base materials. For the thermal stress superposition zone, the thermal field distribution correction value is equal to 5% to 20% of the gradient compensation amount in the basic compensation requirements, fine-tuning the temperature gradient in this region to alleviate thermal stress superposition. Spatial position weights are set for each sub-region within the welding heat-affected zone. The weight allocation is determined based on the degree of influence of each sub-region on welding quality, and the three sub-regions... The sum of the weights of the regions is 1. The weight of the metallurgical transition zone is set to 0.4 to 0.5 because it is the junction of two base materials and directly affects the metallurgical bonding strength, thus having the highest impact. The weight of the thermal cycling sensitive zone is set to 0.3 to 0.35 because it is sensitive to heat input and prone to structural defects, thus having the second highest impact. The weight of the thermal stress superposition zone is set to 0.15 to 0.25, with a relatively low impact. The extracted welding heat input compensation value and thermal field distribution correction value are allocated according to the spatial position weight of each sub-region. Specifically, the final heat input compensation value of a sub-region is equal to the extracted heat input compensation value of that sub-region multiplied by its spatial position weight, and the final thermal field distribution correction value of a sub-region is equal to the extracted thermal field distribution correction value of that sub-region multiplied by its spatial position weight. After allocation, the final compensation values ​​of the three sub-regions are integrated to form the coordinated compensation characteristics of the welding process.

[0077] Step 333 integrates the basic compensation requirements with the coordinated compensation characteristics, and combines the phase transformation temperature range, thermal conductivity, specific heat capacity, and linear expansion coefficient of different base materials in the heterogeneous tube to calculate the incremental correction values ​​of welding current, welding voltage, and welding speed required to achieve thermal field matching at the interface between the current weld and the adjacent weld, thus obtaining the adjustment command for the welding equipment. Specifically, this includes: integrating the basic compensation requirements with the coordinated compensation characteristics to obtain the comprehensive compensation requirements, which include overall compensation parameters (basic compensation requirements) and zone compensation parameters (coordinated compensation characteristics); retrieving the phase transformation temperature range, thermal conductivity, specific heat capacity, and linear expansion coefficient of the two base materials in the heterogeneous tube, which were determined experimentally in advance and are consistent with the material property parameter set extracted in step 225; and calculating the welding... The incremental correction value for welding current is calculated as follows: First, calculate the total heat input compensation in the comprehensive compensation requirement, which is the sum of the final heat input compensation values ​​of the three sub-regions. Then, calculate the average thermal conductivity of the two base materials, which is the sum of the thermal conductivity of the two base materials divided by 2. Next, calculate the product of the welding thermal efficiency correction coefficient, the actual value of the current welding voltage, the actual value of the current welding speed, and the difference between the phase transformation temperature ranges of the two base materials. The difference between the phase transformation temperature ranges of the two base materials is the absolute value of the difference between the upper limits of the phase transformation temperature ranges of the two base materials. Multiply the total heat input compensation by the average thermal conductivity of the two base materials and divide by the above product. The result is the incremental correction value for welding current. A positive result indicates that the welding current needs to be increased, and a negative result indicates that the welding current needs to be decreased.

[0078] The incremental correction value for welding voltage is calculated as follows: Welding voltage and welding current synergistically affect welding heat input. The specific calculation method for its incremental correction value is as follows: First, calculate the total heat input compensation amount in the comprehensive compensation requirement. This value is consistent with the total heat input compensation amount used in the calculation of the incremental correction value for welding current. Then, calculate the average value of the specific heat capacity of the two base materials, which is the sum of the specific heat capacities of the two base materials divided by 2. Calculate the product of the incremental correction value for welding current, the welding thermal efficiency correction coefficient, the actual value of the current welding speed, and the average value of the linear expansion coefficients of the two base materials. The average value of the linear expansion coefficients of the two base materials is the sum of their linear expansion coefficients divided by 2. Multiply the total heat input compensation amount by the average value of the specific heat capacity of the two base materials, and then divide by the above product. The result is the incremental correction value for welding voltage. A positive result indicates that the welding voltage needs to be increased, and a negative result indicates that the welding voltage needs to be decreased.

[0079] The adjustment amount for welding speed is calculated because welding speed affects the accumulation of welding heat input and the distribution of the heat field. The specific calculation method for the adjustment amount is as follows: the adjustment amount for welding speed is directly proportional to the heat field distribution correction value in the comprehensive compensation requirement and inversely proportional to the incremental correction values ​​of welding current and voltage. Specifically, first calculate the sum of the current welding speed multiplied by the heat field distribution correction values ​​(i.e., the sum of the final heat field distribution correction values ​​for the three sub-regions), then divide it by the sum of the incremental correction values ​​of welding current and welding voltage to obtain a calculated ratio. If this ratio is greater than 1, it indicates that the welding speed needs to be increased, and the adjustment amount is the difference between the current welding speed multiplied by this ratio and 1. If this ratio is less than 1, it indicates that the welding speed needs to be decreased, and the adjustment amount is the difference between the current welding speed multiplied by 1 and this ratio. If this ratio is equal to 1, it indicates that no adjustment of the welding speed is needed. The calculated incremental correction values ​​of welding current, welding voltage, and welding speed are integrated to form the adjustment command for the welding equipment.

[0080] By extracting the dynamic deviation characteristics of the welding process and determining the basic compensation requirements by combining the standard range of the process window, and then combining the target adjustment amount and the spatial weight of the sub-region to allocate compensation parameters, the compensation requirements are partitioned. By combining the metallurgical properties and thermophysical parameters of the two base materials of the heterogeneous pipe, the adjustment values ​​of welding current, voltage and speed are calculated to achieve thermal field matching at the base material interface and reduce the incidence of welding defects.

[0081] In a preferred embodiment of the present invention, step 4 above, which involves adjusting the output parameters of the welding equipment in real time according to the adjustment command, and collecting the feedback interpass temperature and heat input values ​​after adjustment, comparing the feedback interpass temperature and heat input values ​​with the heterogeneous tube welding process window again, until the feedback interpass temperature and heat input values ​​return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding, may include:

[0082] In this embodiment of the invention, step 440 involves determining the actual output parameters of the welding equipment based on the incremental correction values ​​of the welding current, welding voltage, and welding speed in the adjustment command, thereby obtaining the adjusted actual welding current, welding voltage, and welding speed values. Specifically, this includes retrieving the original welding current, welding voltage, and welding speed values ​​that the welding equipment was executing before this parameter adjustment from the real-time operation monitoring unit of the welding equipment. These original values ​​are completely consistent with the real-time operating parameters used when calculating the adjustment command, ensuring the continuity of parameter transmission and correction calculation. Subsequently, the actual output parameters are calculated, and the original values ​​are... The initial welding current value and the incremental correction value of the welding current are superimposed to obtain the adjusted actual welding current value adapted to the current welding conditions. When the incremental correction value is positive, the welding current is increased accordingly; when it is negative, the welding current is decreased accordingly; when there is no correction value, the original current remains unchanged. The original welding voltage value and the incremental correction value of the welding voltage are superimposed to obtain the adjusted actual welding voltage value. The calculation rules are consistent with the welding current to form a coordinated matching relationship between the welding voltage and the welding current, which jointly matches the differences in thermophysical parameters between the two base materials of the heterogeneous tube. The original welding speed value and the adjustment amount of the welding speed are superimposed to obtain the adjusted actual welding speed value.

[0083] Step 441: Based on the adjusted actual welding current, actual welding voltage, and actual welding speed values, collect the spatial distribution of interpass temperature along the adjusted welding path as the feedback interpass temperature distribution. Simultaneously, calculate the adjusted real-time heat input value based on the actual welding current, actual welding voltage, and actual welding speed values ​​as the feedback heat input value. Specifically, this includes: first, collecting the feedback interpass temperature distribution; along the current welding path, deploying temperature collection points throughout the entire area covered by the welding heat-affected zone; covering the heat cycle sensitive area of ​​the current weld bead, the metallurgical transition zone at the interface between the two base materials, and the thermal stress superposition zone of adjacent weld beads; simultaneously, uniformly deploying supplementary collection points along the pipe thickness direction and the width direction of the heat-affected zone to completely cover the areas on both sides of the interface between the heterogeneous pipe wall thickness and the base material; the collection cycle is consistent with the collection cycle of the previously constructed real-time parameter set; and continuously collecting the real-time temperature data of each point during the welding process. After the interlayer temperature data is collected, all interlayer temperature data are arranged in a regular manner according to the spatial coordinates of each collection point to form an interlayer temperature spatial distribution that can completely reflect the lateral and longitudinal distribution of the thermal field. This distribution data is the feedback interlayer temperature distribution, which can intuitively reflect the real thermal field state of the heat-affected zone of the heterogeneous pipe after parameter adjustment. The feedback heat input value is calculated. Combining the thermal efficiency correction coefficient used in the welding process, the adjusted actual welding current value and actual welding voltage value are multiplied by the thermal efficiency correction coefficient. The result is then divided by the adjusted actual welding speed value. The final value is the adjusted real-time heat input value. This value serves as the feedback heat input value, reflecting the actual heat input level of the welding heat source acting on the pipe after parameter adjustment. Finally, the feedback interlayer temperature distribution and the feedback heat input value are integrated into a complete welding condition feedback dataset.

[0084] Step 442: Compare the feedback interlayer temperature distribution and feedback heat input value again with the preset standard heat input range and standard temperature gradient range in the heterogeneous tube welding process window to form the feedback deviation. Specifically, this includes: comparing and analyzing the feedback heat input value; calculating the difference between the feedback heat input value and the intermediate reference value of the standard heat input range; the difference obtained is the heat input feedback deviation. The sign of this deviation indicates whether the heat input is too high or too low, and the absolute value indicates the degree of deviation from the standard reference. At the same time, it is determined whether the feedback heat input value is within the upper and lower limits of the standard heat input range, and the feedback interlayer temperature distribution is compared and analyzed. Temperature gradient data in the thickness and width directions of the heat-affected zone are extracted from the interlayer temperature distribution. The difference between the extracted comprehensive temperature gradient value and the intermediate reference value of the standard temperature gradient range is calculated. The difference is the temperature gradient feedback deviation. This deviation reflects the degree of deviation of the temperature gradient fluctuation from the standard stable state. At the same time, it is determined whether the temperature gradient value is within the allowable range of the standard temperature gradient range. After completing the two separate deviation calculations, the heat input feedback deviation and the temperature gradient feedback deviation are integrated to form a total feedback deviation that can comprehensively reflect the overall deviation of the welding condition after parameter adjustment.

[0085] Step 443: When the feedback deviation exceeds the allowable range of the heterogeneous tube welding process window, update the real-time parameter set according to the feedback deviation and redetermine the welding dynamic deviation signal. When the feedback deviation is within the allowable range of the heterogeneous tube welding process window, complete the adaptive control of heterogeneous tube welding. Specifically, this includes: first, clarifying the judgment rules; only when the absolute values ​​of the heat input feedback deviation and the temperature gradient feedback deviation are both within the maximum allowable deviation range of the corresponding standard interval are the feedback deviation determined to meet the process requirements. If any one of the deviations exceeds the corresponding allowable range, the overall feedback deviation is determined to exceed the standard, and the welding condition has not yet reached the qualified state. When the feedback deviation exceeds the allowable range of the process window, based on the feedback deviation, the feedback interlayer temperature distribution obtained in step 441, the feedback heat input value, and the adjusted welding parameters obtained in step 440, comprehensively update the previously constructed real-time parameter set, replacing the original uncorrected parameter data, so that the real-time parameter set fully matches the latest welding condition, and proceed according to the steps. The complete process from step 110 to step 115 involves recalculating the welding heat input deviation and temperature gradient fluctuation characteristics based on the updated real-time parameter set, and determining a new welding dynamic deviation signal. After the signal is determined, the process returns to the dynamic deviation feature extraction step, and sequentially re-executes the entire process of basic compensation requirement calculation, coordinated compensation feature allocation, welding equipment adjustment command generation, parameter adjustment, and feedback acquisition, forming a continuous loop correction mechanism until the feedback deviation meets the qualification requirements. When the feedback deviation is within the allowable range of the process window, it indicates that the parameter adjustment has achieved qualified control of the welding heat input and thermal field distribution of the heterogeneous tube, the temperature field, flow field, and stress field of each sub-region of the welding heat-affected zone have reached a coordinated state, a stable thermal field matching has been achieved at the interface of the two base materials, and the welding process meets all the requirements of metallurgical bonding strength and thermal stress coordination. At this point, it is determined that the adaptive control target of the heterogeneous tube welding has been fully achieved, and the welding equipment continues to operate stably with the currently adjusted parameters until all multi-layer and multi-pass welding processes are completed, and the adaptive control process ends.

[0086] This achieves a closed-loop cycle of welding parameter adjustment, feedback verification, and deviation correction, thereby improving the quality of welded joints and reducing the incidence of welding defects.

[0087] like Figure 2 As shown, embodiments of the present invention also provide an adaptive control-based heterogeneous tube welding control system, comprising:

[0088] The generation module is used to compare the real-time parameter set with the preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and to form a welding dynamic deviation signal based on the deviation and fluctuation characteristics.

[0089] The simulation module is used to select three characteristic locations on the current weld bead and adjacent weld beads within the weld heat-affected zone (HAZ) based on the welding dynamic deviation signal. The local thermal field distribution of each of the three characteristic locations constitutes a thermal characteristic unit. This includes determining the solidification transition zone behind the molten pool of the current weld bead along the welding direction within the HAZ based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, obtaining the first characteristic location; determining the coarse-grained region of the HAZ of the current weld bead along the welding direction within the HAZ based on the first characteristic location, obtaining the second characteristic location; determining the remelting region of the HAZ of the adjacent weld bead along the welding direction within the HAZ based on the second characteristic location, obtaining the third characteristic location; collecting temperature gradient data and cooling rate data along the thickness direction of the first characteristic location to obtain the first local thermal field distribution; and collecting temperature gradient data and cooling rate data along the thickness direction of the second characteristic location based on the first local thermal field distribution and the second characteristic location. The temperature gradient data and cooling rate data in the direction are used to obtain the second local thermal field distribution. Based on the second local thermal field distribution and the third feature position, the temperature gradient data and cooling rate data in the thickness direction of the third feature position are collected to obtain the third local thermal field distribution. Based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, the current weld bead and the adjacent weld bead are combined according to their relative spatial position relationship in the welding heat-affected zone to form a thermal feature unit. The thermal feature unit is divided into heat-affected zones. Based on the distribution characteristics of the metallurgical properties and thermophysical parameters of the base material corresponding to each sub-region after division, the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy are simulated through a pre-trained coupled calculation model of molten pool flow and heat transfer. The coordinated response values ​​of temperature field, flow field, and stress field of each sub-region under welding thermal cycle are calculated to determine the target adjustment amount.

[0090] The adjustment module is used to calculate the adjustment command of the welding equipment based on the welding dynamic deviation signal and the target adjustment amount, combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous tubes.

[0091] The control module is used to adjust the output parameters of the welding equipment in real time according to the adjustment command, and after adjustment, it collects the feedback interpass temperature and heat input value, compares the feedback interpass temperature and heat input value with the heterogeneous tube welding process window again, until the feedback interpass temperature and heat input value return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

[0092] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0093] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling the welding of heterogeneous tubes based on adaptive regulation, characterized in that, The method includes: Step 1: Calculate the real-time welding heat input value based on the welding current, welding voltage, and welding speed from the real-time parameter set; compare the real-time welding heat input value with the standard heat input range in the preset heterogeneous tube welding process window to obtain the deviation of the welding heat input; determine the spatial range of the welding heat-affected zone based on the spatial distribution of interpass temperature along the welding path from the real-time parameter set, and extract the thickness-direction temperature gradient sequence within the welding heat-affected zone; perform time-series analysis based on the thickness-direction temperature gradient sequence to obtain the thickness-direction temperature gradient change rate; and calculate the spatial distribution of interpass temperature along the welding path from the real-time parameter set. The method involves extracting the width-direction temperature gradient sequence within the weld heat-affected zone (HAZ), performing time-series analysis on this sequence to obtain the width-direction temperature gradient change rate, weighting and integrating the thickness-direction temperature gradient change rate with the width-direction temperature gradient change rate to obtain the fluctuation characteristics of the HAZ temperature gradient, normalizing the welding heat input deviation and the HAZ temperature gradient fluctuation to obtain normalized heat input deviation and temperature gradient fluctuation, and then linearly weighting and fusing the normalized heat input deviation and temperature gradient fluctuation according to a preset dynamic deviation fusion weighting coefficient to form a welding dynamic deviation signal. Step 2: Based on the welding dynamic deviation signal, three characteristic positions are selected on the current weld bead and adjacent weld beads within the welding heat-affected zone (HAZ). The local thermal field distribution of each of the three characteristic positions constitutes a thermal characteristic unit. This thermal characteristic unit includes longitudinal and transverse thermal field correlation information within the HAZ. Based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, the solidification transition zone behind the molten pool of the current weld bead is determined along the welding direction within the HAZ, resulting in the first characteristic position. Based on the first characteristic position, the coarse-grained region of the HAZ of the current weld bead is determined along the welding direction within the HAZ, resulting in the second characteristic position. Based on the second characteristic position, the remelting region of the HAZ of adjacent weld beads is determined along the welding direction within the HAZ, resulting in... The third feature position; temperature gradient data and cooling rate data in the thickness direction of the first feature position are collected to obtain the first local thermal field distribution; based on the first local thermal field distribution and the second feature position, temperature gradient data and cooling rate data in the thickness direction of the second feature position are collected to obtain the second local thermal field distribution; based on the second local thermal field distribution and the third feature position, temperature gradient data and cooling rate data in the thickness direction of the third feature position are collected to obtain the third local thermal field distribution; based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, they are combined according to the relative spatial position relationship between the current weld bead and the adjacent weld bead in the welding heat-affected zone to form a thermal feature unit; based on the local thermal feature unit, the three feature positions are... Based on the thermal field distribution and the metallurgical bonding boundary between the current weld bead and adjacent weld beads at the base metal interface, the heat-affected zone is divided into three sub-regions: a thermal cycling sensitive zone near the current weld bead, a metallurgical transition zone at the base metal interface, and a thermal stress superposition zone near adjacent weld beads. For each sub-region, the distribution characteristics of the base metallurgical properties and thermophysical parameters are extracted, resulting in a set of material property parameters for each sub-region. Based on the material property parameter sets of each sub-region and the local thermal field distribution at three characteristic locations within the thermal feature unit, the boundary heat flux density of each sub-region is determined. A pre-trained coupled melt pool flow and heat transfer calculation model is then invoked, and the boundary heat flux density is input into the model to simulate the melt pool under the influence of surface tension gradients. The fluid flow behavior under the combined effects of Marangoni convection, electromagnetic force generated by welding current, and thermal buoyancy caused by the density difference of the molten pool is used to obtain the fluid flow distribution of the molten pool. Based on the fluid flow distribution of the molten pool, the thermal field distribution process under the influence of fluid flow is simulated again in the coupled calculation model of molten pool flow and heat transfer, and the thermal field redistribution results of the molten pool and heat-affected zone are obtained. Based on the thermal field redistribution results, the peak temperature and temperature cycle change process of the temperature field of each sub-region under the welding thermal cycle are calculated, and the temperature field calculation results of each sub-region are obtained. Based on the temperature field calculation results of each sub-region, combined with the fluid flow distribution of the molten pool, the flow velocity and flow direction distribution of the flow field of each sub-region under the welding thermal cycle are calculated, and the flow field calculation results of each sub-region are obtained.Based on the temperature field calculation results and flow field calculation results of each sub-region, the equivalent residual stress value of the stress field of each sub-region under the welding thermal cycle is calculated to obtain the stress field calculation results of each sub-region; based on the temperature field calculation results, flow field calculation results and stress field calculation results of each sub-region, multi-physics field coupling analysis is performed to obtain the coordination response value of each sub-region under the condition of satisfying metallurgical bonding strength and thermal stress coordination, and the target adjustment amount is determined based on the difference between the coordination response value and the preset coordination target value. Step 3: Based on the welding dynamic deviation signal and the target adjustment amount, and combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous pipe, calculate the adjustment command of the welding equipment. Step 4: Adjust the output parameters of the welding equipment in real time according to the adjustment instructions, and collect the feedback interpass temperature and heat input values ​​after adjustment. Compare the feedback interpass temperature and heat input values ​​with the heterogeneous tube welding process window again until the feedback interpass temperature and heat input values ​​return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

2. The method for controlling the welding of heterogeneous tubes based on adaptive regulation according to claim 1, characterized in that, Before step 1, during the welding process of the heterogeneous tube, welding current, welding voltage, welding speed and interpass temperature are collected in real time to obtain multi-source physical field data, and a real-time parameter set is constructed based on the multi-source physical field data.

3. The method for controlling the welding of heterogeneous tubes based on adaptive regulation according to claim 1, characterized in that, The adjustment commands include incremental correction values ​​for welding current, incremental correction values ​​for welding voltage, and adjustments to welding speed.

4. The method for controlling the welding of heterogeneous tubes based on adaptive regulation according to claim 1, characterized in that, Based on the welding dynamic deviation signal and the target adjustment amount, and combined with the metallurgical properties and thermophysical parameters of the different base materials of the heterogeneous pipes, the adjustment commands for the welding equipment are calculated, including: Based on the welding dynamic deviation signal, the direction and magnitude of heat input deviation are extracted from the deviation of welding heat input. At the same time, the amplitude and frequency of temperature gradient fluctuation are extracted from the fluctuation characteristics of temperature gradient in the heat-affected zone to obtain the dynamic deviation characteristics of the welding process. Based on the dynamic deviation characteristics, and combined with the preset standard heat input range and standard temperature gradient range in the heterogeneous tube welding process window, the heat input compensation direction and heat input compensation amount required for welding heat input, as well as the gradient compensation direction and gradient compensation amount required for the temperature gradient of the heat-affected zone, are determined respectively, so as to obtain the basic compensation requirements of the welding process. Based on the basic compensation requirements and combined with the target adjustment amount, the welding heat input compensation value and thermal field distribution correction value required for each sub-region to meet the conditions of metallurgical bonding strength and thermal stress coordination are extracted. The welding heat input compensation value and thermal field distribution correction value are then allocated according to the spatial position weight of each sub-region in the welding heat-affected zone to obtain the coordination compensation characteristics of the welding process. By integrating the basic compensation requirements with the coordinated compensation characteristics, and combining the phase change temperature range, thermal conductivity, specific heat capacity and linear expansion coefficient of different base materials in heterogeneous tubes, the incremental correction values ​​of welding current, welding voltage and welding speed required to achieve thermal field matching at the base material interface between the current weld and the adjacent weld are calculated, and the adjustment command of the welding equipment is obtained.

5. The method for controlling the welding of heterogeneous tubes based on adaptive regulation according to claim 4, characterized in that, The output parameters of the welding equipment are adjusted in real time according to the adjustment command, and the interpass temperature and heat input values ​​are collected after adjustment. The feedback interpass temperature and heat input values ​​are compared with the heterogeneous tube welding process window again until the feedback interpass temperature and heat input values ​​return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding, including: Based on the incremental correction values ​​of welding current, welding voltage, and welding speed in the adjustment instructions, the actual output parameters of the welding equipment are determined, and the adjusted actual welding current, actual welding voltage, and actual welding speed values ​​are obtained. Based on the adjusted actual welding current, actual welding voltage, and actual welding speed, the spatial distribution of interpass temperature along the adjusted welding path is collected as the feedback interpass temperature distribution. At the same time, the adjusted real-time heat input value is calculated based on the actual welding current, actual welding voltage, and actual welding speed, and is used as the feedback heat input value. The feedback interlayer temperature distribution and feedback heat input value are compared again with the standard heat input range and standard temperature gradient range in the preset heterogeneous tube welding process window to form the feedback deviation. When the feedback deviation exceeds the allowable range of the heterogeneous tube welding process window, the real-time parameter set is updated according to the feedback deviation, and the welding dynamic deviation signal is redefined. When the feedback deviation is within the allowable range of the heterogeneous tube welding process window, the adaptive control of heterogeneous tube welding is completed.

6. A heterogeneous tube welding control system based on adaptive regulation, wherein the system implements the method as described in any one of claims 1 to 5, characterized in that, include: The generation module is used to compare the real-time parameter set with the preset heterogeneous tube welding process window to obtain the deviation of welding heat input and the fluctuation characteristics of the temperature gradient in the heat-affected zone, and to form a welding dynamic deviation signal based on the deviation and fluctuation characteristics. The simulation module is used to select three characteristic locations on the current weld bead and adjacent weld beads within the weld heat-affected zone (HAZ) based on the welding dynamic deviation signal. The local thermal field distribution of each of the three characteristic locations constitutes a thermal characteristic unit. This includes determining the solidification transition zone behind the molten pool of the current weld bead along the welding direction within the HAZ based on the deviation direction and amplitude characterized by the welding dynamic deviation signal, obtaining the first characteristic location; determining the coarse-grained region of the HAZ of the current weld bead along the welding direction within the HAZ based on the first characteristic location, obtaining the second characteristic location; determining the remelting region of the HAZ of the adjacent weld bead along the welding direction within the HAZ based on the second characteristic location, obtaining the third characteristic location; collecting temperature gradient data and cooling rate data along the thickness direction of the first characteristic location to obtain the first local thermal field distribution; and collecting temperature gradient data and cooling rate data along the thickness direction of the second characteristic location based on the first local thermal field distribution and the second characteristic location. The temperature gradient data and cooling rate data in the direction are used to obtain the second local thermal field distribution. Based on the second local thermal field distribution and the third feature position, the temperature gradient data and cooling rate data in the thickness direction of the third feature position are collected to obtain the third local thermal field distribution. Based on the first local thermal field distribution, the second local thermal field distribution, and the third local thermal field distribution, the current weld bead and the adjacent weld bead are combined according to their relative spatial position relationship in the welding heat-affected zone to form a thermal feature unit. The thermal feature unit is divided into heat-affected zones. Based on the distribution characteristics of the metallurgical properties and thermophysical parameters of the base material corresponding to each sub-region after division, the fluid flow behavior and thermal field redistribution process of the molten pool under the action of surface tension, electromagnetic force, and thermal buoyancy are simulated through a pre-trained coupled calculation model of molten pool flow and heat transfer. The coordinated response values ​​of temperature field, flow field, and stress field of each sub-region under welding thermal cycle are calculated to determine the target adjustment amount. The adjustment module is used to calculate the adjustment command of the welding equipment based on the welding dynamic deviation signal and the target adjustment amount, combined with the metallurgical characteristics and thermophysical parameters of the different base materials of the heterogeneous tubes. The control module is used to adjust the output parameters of the welding equipment in real time according to the adjustment command, and after adjustment, it collects the feedback interpass temperature and heat input value, compares the feedback interpass temperature and heat input value with the heterogeneous tube welding process window again, until the feedback interpass temperature and heat input value return to the allowable range of the heterogeneous tube welding process window, thus completing the adaptive control of heterogeneous tube welding.

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