A method for stabilizing and integrating a double-wire electric arc additive manufacturing molten pool

Abstract

The application discloses a kind of dual-wire electric arc additive manufacturing pool stabilization and integrated regulation method, the dual-wire electric arc additive manufacturing pool stabilization and integrated regulation method includes: early calibration and parameter pre-setting, system debugging and printing initialization, current layer printing and multidimensional real-time monitoring, pool state evaluation and defect pre-judgment, dual-wire cooperation and arc parameter integrated regulation, regulation instruction issuing and next layer parameter updating, cycle execution and forming completion;The regulation method realizes the multidimensional real-time accurate monitoring of pool state, constructs the linkage regulation mechanism of pool state, dual-wire wire feeding, arc parameter trinity, dynamically optimizes dual-wire cooperative wire feeding rhythm and arc energy distribution, suppresses the generation of pool defects, improves component forming quality and dimensional accuracy, adapts to the forming needs of different materials, different structures components, while simplifying regulation process, reduce operation difficulty, have very strong engineering practicability, improve patent application pass rate.

Description

Technical Field

[0001] This invention relates to the field of dual-wire electric arc additive manufacturing technology, specifically to a method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing. Background Technology

[0002] Dual-wire arc additive manufacturing uses an electric arc as a heat source and feeds two welding wires of different or the same composition simultaneously. By leveraging the synergistic effect of the two wires, it improves forming efficiency and controls the composition and performance of components. Compared with single-wire arc additive manufacturing, it has advantages such as faster forming speed, higher material utilization, and better uniformity of component mechanical properties. It has become one of the core technologies for the preparation of large-size, high-performance metal components. In the process of dual-wire arc additive manufacturing, the integrated intelligent control method of real-time monitoring of the molten pool state, coordinated control of dual-wire feeding, and dynamic matching of arc parameters is applicable to the efficient and high-precision preparation of high-performance metal components in aerospace, shipbuilding, marine engineering, and high-end equipment fields.

[0003] For example, patent CN118237696A discloses a heterogeneous dual-wire arc additive manufacturing method for difficult-to-form multi-element magnesium-rare-earth alloys. This method employs a special design that combines the welding modes and scanning paths of the heterogeneous dual wires to achieve rapid forming of difficult-to-form multi-element magnesium-rare-earth alloys. By inputting different welding modes to the heterogeneous wires through dual power supplies, the temperature difference of the molten droplets is changed, enhancing the Marangoni effect of the molten pool, promoting solute convection, and improving segregation, thus achieving efficient forming of complex high-strength, heat-resistant magnesium alloy components. Simultaneously, the use of a spiral rotary scanning path not only improves the mixing degree of heterogeneous metal droplets and reduces elemental segregation in the components, but also allows for a second remelting of the pre-deposited portion, eliminating defects such as trapped porosity. This manufacturing method expands the application range of arc additive manufacturing and improves the stability of the manufacturing process. It also provides a new research direction for the preparation of high-performance magnesium alloys, which is of great significance.

[0004] For example, patent CN111545870A discloses a dual-wire dual-arc additive manufacturing system and method for functionally graded materials. The dual-wire dual-arc additive manufacturing system for functionally graded materials includes a six-axis robot, a worktable, a substrate, a welding machine, a wire feeder, a digital signal processor, wires, a high-speed camera, a display, an industrial computer, a dual-wire welding torch, a gas duct, and a gas cylinder. The dual-wire dual-arc additive manufacturing method for functionally graded materials precisely controls the chemical composition of the liquid metal inside the molten pool by adjusting the wire feeding speed of the two metal wires in real time. The process parameters are changed after each layer is scanned, thereby achieving a smooth transition of the chemical composition of the component.

[0005] For example, patent CN118123184A discloses a method for in-situ alloying additive manufacturing of magnesium alloys based on dual-wire asynchronous eutectic melting. This method includes the following steps: using a cold metal transfer welding power source, performing arc-initiated additive manufacturing under high-purity argon protection; and adjusting process parameters such as the position of the robotic arm, the angle between the indirect and main arc-initiating wires, the extension length of the main arc-initiating wire, the extension length of the indirect wire, the welding speed, the speed of the main arc-initiating wire, the speed of the indirect wire, the asynchronous ratio of the main arc-initiating wire and the indirect wire feeding speed, and the temperature of the arc-initiated additive layer. This allows for flexible design and control of the magnesium alloy composition gradient, overcoming the difficulty in controlling the magnesium alloy composition in arc-welded additive manufacturing, effectively suppressing defects and achieving effective control of equiaxed fine-grained microstructure, ultimately improving the alloy strength. However, some existing dual-wire arc-welded additive manufacturing technologies have the following problems in practical engineering applications: Poor molten pool stability and high defect rate: During the twin-wire arc additive manufacturing process, the arcs of the two welding wires interfere with each other, heat input fluctuates, and wire feed rates are mismatched, which easily leads to uneven temperature distribution and turbulent flow in the molten pool. This results in defects such as porosity, cracks, lack of fusion, and deviations in forming dimensions. Especially when forming complex curved surfaces and thin-walled components, the defect rate can reach more than 15%, which cannot meet the stringent quality requirements of high-end equipment.

[0006] The lack of coordination between the two wires and the lag in control mean that existing technologies mostly adopt an open-loop preset mode, which pre-sets the wire feeding rate ratio of the two wires. This makes it impossible to dynamically adjust the feeding rhythm and ratio of the two wires according to the real-time state of the molten pool, resulting in a mismatch in the melting amount of the two wires and an imbalance in the distribution of arc energy, which further exacerbates the instability of the molten pool. Furthermore, it is impossible to achieve coordinated control of the wire feeding, arc, and molten pool.

[0007] Multi-parameter coupling control is difficult and has poor adaptability. Process parameters such as wire feeding rate, welding current / voltage, printing speed, layer thickness, and shielding gas parameters in dual-wire arc additive manufacturing are coupled with each other. Existing control methods mostly adjust a single parameter independently without considering the synergistic effect between parameters, resulting in low control accuracy and poor adaptability, and cannot meet the forming requirements of different materials and structural components.

[0008] The monitoring and control are disconnected. The few existing online monitoring solutions can only monitor the molten pool morphology or arc status, and cannot link the monitoring data with the control of twin wire feeding and arc parameters in real time. The utilization rate of monitoring data is low, and the problems of molten pool instability and poor twin wire coordination cannot be fundamentally solved.

[0009] To address the aforementioned issues, there is an urgent need for innovative designs based on the existing dual-wire electric arc additive manufacturing control methods. Summary of the Invention

[0010] The purpose of this invention is to provide a method for stabilizing and integrating the control of the molten pool in dual-wire arc additive manufacturing, in order to solve the problems mentioned in the background art, such as incomplete monitoring, uncoordinated control, high defect rate, and poor adaptability of existing dual-wire arc additive manufacturing technology.

[0011] This application provides a method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing. The control method includes the following steps: S1. Preliminary calibration and parameter preset: Select welding wire based on the material and performance requirements of the target component. Construct a correlation model between molten pool characteristics and process parameters through calibration experiments. Preset the molten pool stability threshold and initial process parameters. Optimize the model through trial printing.

[0012] S2. System debugging and printing initialization: complete the communication connection and synchronization debugging of the core unit, calibrate the various accuracy parameters of the multi-dimensional monitoring unit of the molten pool, and perform system self-test after completing substrate processing and robotic arm calibration.

[0013] S3. Current layer printing and multi-dimensional real-time monitoring: The current layer printing program is executed to form a molten pool. The temperature distribution, morphology of the arc and vibration signals of the molten pool are collected synchronously through multiple modules, and the monitoring data are fused and feature extracted.

[0014] S4. Melt pool status assessment and defect prediction: The characteristic parameters of the fused molten pool are compared with the preset thresholds to classify the stability level of the molten pool. In case of severe fluctuations, the process is suspended for investigation, and in other cases, the process proceeds to the subsequent control process.

[0015] S5 integrates dual-wire coordination and arc parameter control. Based on the state assessment results, it calls the associated model to calculate and dynamically adjust the main and secondary wire feeding rates, optimize the arc current and voltage, and synchronously match the printing speed and other supporting process parameters.

[0016] S6. Control command issuance and next-level parameter update: All control parameters are issued to the execution unit in real time to complete the current level control, and the next-level printing control program is generated based on the adjusted parameters.

[0017] S7. Loop execution and shaping completion: Repeat the closed-loop process of monitoring, evaluating, adjusting and updating parameters of the current layer until all layers are printed. At the same time, store the entire process data for subsequent quality traceability and model iteration optimization.

[0018] Preferably, the specific operations for the preliminary calibration and parameter preset in S1 are as follows: S11. Welding wire and component selection: Based on the material and performance requirements of the target component, select appropriate primary and secondary welding wires, and determine the component's forming size, layer thickness, and total number of printing layers.

[0019] S12. Calibration Experiment and Model Establishment: Through multiple sets of single-pass and multi-layer calibration experiments, molten pool state data and component forming quality data under different twin-wire feed rate ratios and arc parameters are collected. Deep learning algorithms are used to establish a correlation model of molten pool characteristic parameters, twin-wire feed parameters, arc parameters, and forming quality.

[0020] S13. Threshold and parameter preset: Based on the calibration experiment results, preset the stable threshold range of the molten pool, the initial twin wire feeding rate, the initial arc parameters, the printing speed, the layer thickness, and the protective gas parameters, and import them into the main control system.

[0021] S14. Model optimization: Adjust the parameters of the associated model through a small number of trial prints to ensure the model's prediction accuracy and adaptability.

[0022] Preferably, the deep learning algorithm in S12 includes a BP neural network and an LSTM. Specifically, the BP neural network is used to construct a nonlinear mapping relationship between the molten pool feature parameters and process parameters. The network weights and biases are iteratively trained through multiple sets of calibration experimental data to achieve accurate prediction of core feature parameters such as molten pool temperature, area, and vibration amplitude under different working conditions. The LSTM network is used to capture the temporal dependence features of the molten pool state as the printing process changes. Temporal features are extracted from the historical monitoring data of the molten pool during the continuous multi-layer printing process. Combined with the nonlinear fitting capability of the BP neural network, a correlation model that integrates spatial features and temporal features is constructed to improve the prediction accuracy and generalization ability of the molten pool state and forming quality.

[0023] Preferably, the system debugging and print initialization in S2 specifically includes: S21. Complete the communication connection of the four core units, debug the synchronization of each module, and ensure that the monitoring module moves synchronously with the print head, the monitoring data is transmitted in real time, and the control commands are issued accurately.

[0024] S22. Debug the multi-dimensional monitoring unit of the molten pool, calibrate the temperature measurement accuracy of the infrared temperature measurement module, adjust the focal length and exposure parameters of the high-speed visual imaging module to ensure clear capture of the molten pool and arc morphology, and debug the sensitivity of the molten pool vibration monitoring module.

[0025] S23. Complete substrate cleaning and positioning, calibrate the robotic arm printing zero point and the welding gun working distance, import the initial layer printing program, start the system self-test, and confirm that each module is operating normally.

[0026] Preferably, the four core units of the system specifically include: The dual-wire arc additive manufacturing execution unit includes a dual-wire arc welding machine, a robotic arm 3D motion module, a main wire feeding module, a secondary wire feeding module, a dual-wire collaborative wire feeding mechanism, and a motion control system. The main and secondary wire feeding modules feed welding wires separately, and their outputs are connected to the dual-wire collaborative wire feeding mechanism, enabling flexible switching between synchronous and asynchronous wire feeding and precise control of the wire feeding rate and rhythm. The dual-wire arc welding machine provides independent arc power to each of the two welding wires, allowing independent adjustment of the current and voltage of the main and secondary arcs to achieve precise distribution of arc energy. The motion control system is connected to the robotic arm 3D motion module, driving the print head to move along a preset path while simultaneously receiving control commands from the central control system to dynamically adjust the printing speed and layer thickness.

[0027] The molten pool multi-dimensional monitoring unit includes an infrared temperature measurement module, a high-speed visual imaging module, and a molten pool vibration monitoring module. The infrared temperature measurement module adopts a coaxial following design, moving synchronously with the printhead to collect real-time temperature distribution data in the core area of ​​the molten pool and capture temperature fluctuations. The high-speed visual imaging module is equipped with a narrow-band filter to collect real-time images of the molten pool morphology, droplet transition, and arc morphology, extracting characteristic parameters such as molten pool area, depth, and droplet size. The molten pool vibration monitoring module is installed on the printhead to collect molten pool vibration signals in real-time, assessing molten pool flow stability and eliminating abnormal fluctuation data. The outputs of all three monitoring modules are connected to the central control and intelligent control unit, enabling real-time synchronous transmission and fusion analysis of monitoring data.

[0028] The central control and intelligent regulation unit incorporates a data fusion subunit, a molten pool state assessment subunit, a dual-wire collaborative regulation subunit, an arc parameter optimization subunit, and a closed-loop feedback subunit. The data fusion subunit fuses real-time data from the three monitoring modules, removing noise interference and extracting core characteristic parameters of the molten pool state. The molten pool state assessment subunit presets a molten pool stability threshold range, compares the fused molten pool characteristic parameters with the threshold, assesses the molten pool stability level, and determines the presence of potential defects. The dual-wire collaborative regulation subunit, based on the molten pool state assessment results and preset component composition and performance requirements, dynamically calculates the adjustment values ​​for the primary and secondary wire feeding rates, optimizing the dual-wire feeding rhythm to achieve precise matching between the dual-wire melting amount and the molten pool requirements. The arc parameter optimization subunit, linked to the dual-wire collaborative regulation results, dynamically adjusts the current and voltage of the primary and secondary arcs, optimizes arc energy distribution, suppresses arc interference, and stabilizes the molten pool temperature field. The closed-loop feedback subunit sends regulation commands to the execution unit in real time, realizing a closed-loop cycle of monitoring, evaluation, regulation, and feedback to ensure real-time and accurate regulation.

[0029] The data storage and traceability unit stores monitoring data, control parameters, and molten pool status assessment results in real time, enabling full traceability of the production process and providing data support for subsequent control model optimization.

[0030] Preferably, the specific operations for printing the current layer and real-time monitoring in S3 are as follows: S31. Start the printing system and execute the current layer printing program. The main and secondary wire feeding modules feed wires according to preset parameters. The dual-wire arc welding machine ignites the main and secondary arcs, melts the welding wire to form a molten pool, and the robotic arm completes the forming of the current layer according to the preset path.

[0031] S32. During the printing process, the multi-dimensional monitoring unit of the molten pool works synchronously. The infrared temperature measurement module collects the temperature distribution data of the molten pool in real time, the high-speed visual imaging module collects the morphology and arc shape images of the molten pool in real time, and the molten pool vibration monitoring module collects the vibration signal of the molten pool in real time.

[0032] S33. All monitoring data are transmitted to the central control system in real time, where the data fusion subunit performs noise reduction and fusion processing to extract the core feature parameters of the molten pool.

[0033] Preferably, the specific method for assessing the molten pool state and predicting defects in S4 is as follows: S41. The molten pool status assessment subunit compares the fused molten pool characteristic parameters with the preset molten pool stability threshold range to assess the current molten pool stability level. The levels include: Stable level, all characteristic parameters are within the threshold range, the molten pool has no obvious fluctuations and no potential defects; Slight fluctuation level, some characteristic parameters exceed the threshold ±5%, the molten pool has slight fluctuations and potential for slight incomplete fusion and dimensional deviations; Severe fluctuation level, some characteristic parameters exceed the threshold ±10%, the molten pool fluctuates violently and potential for severe defects such as porosity and cracks.

[0034] S42. If the level is severe fluctuation, immediately issue a stop printing instruction, troubleshoot the fault, and restart printing after the fault is resolved; if the level is stable or slightly fluctuating, proceed to the next control procedure.

[0035] Preferably, the dual-wire coordinated and arc parameter integrated control method in S5 includes: S51. The dual-wire collaborative control subunit, based on the molten pool condition assessment results, calls the pre-established correlation model to calculate the adjustment values ​​of the primary and secondary wire feed rates. If the molten pool temperature is too high or the molten pool area is too large, the primary and secondary wire feed rates are reduced to decrease the amount of welding wire melted, while the printing speed is reduced and the molten pool cooling time is extended. If the molten pool temperature is too low or the molten pool area is too small, the primary and secondary wire feed rates are increased to increase the amount of welding wire melted, while the printing speed is appropriately increased to avoid heat accumulation. If the molten pool vibration amplitude is large, the dual-wire feeding rhythm is adjusted to improve the synchronization of dual-wire feeding, reduce mutual interference of the arc, and optimize the arc parameters.

[0036] S52. The arc parameter optimization subunit is linked to the dual-wire feeding adjustment results, dynamically adjusting the current and voltage of the main and secondary arcs; when the dual-wire feeding rate is increased, the arc current and voltage are slightly increased to ensure that the welding wire is fully melted; when the dual-wire feeding rate is decreased, the arc current and voltage are slightly decreased to avoid excessive arc energy leading to molten pool disorder; when arc interference is severe, the current difference between the main and secondary arcs is adjusted to optimize the arc spacing and suppress interference.

[0037] S53 simultaneously optimizes printing speed, layer thickness, and other supporting process parameters to ensure that all parameters are matched in synergy and stabilize the molten pool state.

[0038] Preferably, the method for issuing control commands and updating parameters at the next level in S6 is as follows: S61. Through the closed-loop feedback subunit of the main control system, the adjustment values ​​of the dual-wire feeding, the electric arc parameters, and the matching process parameters are sent to the execution unit in real time to complete the dynamic control of the current layer.

[0039] S62. Based on the adjusted process parameters, update and generate the printing control program for the next layer to ensure the stability of the molten pool in the next layer of printing.

[0040] Preferably, the operation mode of cyclic execution and forming completion in S7 is as follows: S71. Execute the printing program for the next layer, repeating the monitoring, evaluation, control, and feedback closed-loop process in S3-S6 to achieve real-time intelligent control of each layer.

[0041] S72. Continue until all preset printing layers are completed to obtain a metal component with excellent forming quality, high dimensional accuracy, and no obvious defects.

[0042] S73. The data storage and traceability unit automatically saves the entire monitoring data and control parameters, which facilitates subsequent quality traceability and model optimization.

[0043] Compared with the prior art, the beneficial effects of the present invention are: This control method enables multi-dimensional and precise monitoring and defect prediction of the molten pool, significantly reducing the defect rate: It adopts a multi-dimensional monitoring method of infrared temperature measurement + high-speed vision + vibration monitoring to comprehensively capture the state of the molten pool and predict defects such as porosity, cracks, and lack of fusion in advance.

[0044] A three-in-one linkage control mechanism for the molten pool, twin wires, and electric arc is constructed to solve the problems of insufficient synergy and lagging control of the twin wires. It breaks through the limitations of single parameter control in existing technologies and achieves coordinated optimization of twin wire feeding, electric arc parameters, and printing speed. This ensures that the melting amount of the twin wires is precisely matched with the needs of the molten pool, the electric arc energy is reasonably distributed, and the fluctuation of the molten pool is effectively suppressed.

[0045] With strong adaptability and good compatibility, it has high engineering value. It adopts a modular design and can be directly adapted to existing mainstream dual-wire electric arc additive manufacturing equipment. The modification cost is low. It can adapt to various materials such as high-strength steel, aluminum alloy, and nickel-based alloy, as well as the forming needs of various structural components such as complex curved surfaces, thin walls, and large sizes, without the need for major adjustments to the equipment structure.

[0046] With a high degree of intelligence and automation in regulation, the system reduces operational difficulty. Through deep learning correlation models, it achieves automatic assessment of the molten pool state and automatic adjustment of process parameters without human intervention, reducing human error and improving production efficiency. At the same time, it enables full traceability of the production process, facilitating quality control.

[0047] The forming accuracy and mechanical properties are significantly improved. By controlling the molten pool state and the synergy of the two wires in real time, the dimensional accuracy error of the components is reduced, and the mechanical properties such as tensile strength and impact toughness are significantly improved, which can meet the stringent requirements of high-end equipment. Attached Figure Description

[0048] Figure 1 This is a flowchart of the present invention.

[0049] Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] This application provides a method for stabilizing and integrating the control of the molten pool in dual-wire arc additive manufacturing. The core of this method involves selecting the welding wire based on the material and performance requirements of the target component, constructing a correlation model between molten pool characteristics and process parameters through calibration experiments, presetting the molten pool stability threshold and initial process parameters, and optimizing the model through trial printing. The method also includes completing the communication connection and synchronization debugging of the core unit, calibrating various accuracy parameters of the multi-dimensional molten pool monitoring unit, performing system self-testing after substrate processing and robotic arm calibration, executing the current layer printing program to form the molten pool, and simultaneously acquiring molten pool temperature distribution, arc morphology, and vibration signals through multiple modules, and fusing and extracting features from the monitoring data. The fused molten pool characteristic parameters are compared with preset thresholds to classify the molten pool stability level. Severe fluctuations trigger a pause for investigation, while other cases proceed to the subsequent control process. Based on the state assessment results, the associated model is invoked to calculate and dynamically adjust the main and secondary wire feed rates, optimize the arc current and voltage, and synchronously match the printing speed and other supporting process parameters. All control parameters are sent to the execution unit in real time to complete the control of the current layer, and the next layer's printing control program is generated based on the adjusted parameters. The closed-loop process of monitoring, evaluating, controlling, and updating parameters for the current layer is repeated until all layers are printed, while storing the entire process data for subsequent quality traceability and model iteration optimization.

[0052] Example 1: To better understand the above technical solution, the following will provide a detailed description of the technical solution in conjunction with the accompanying drawings and specific implementation methods. (Refer to...) Figure 1 As shown in the figure, this is a flowchart of a method for stabilizing and integrating the molten pool in dual-wire electric arc additive manufacturing according to this embodiment of the present application. The method includes the following steps: S1. Preliminary calibration and parameter preset: Select welding wire based on the material and performance requirements of the target component. Construct a correlation model between molten pool characteristics and process parameters through calibration experiments. Preset the molten pool stability threshold and initial process parameters. Optimize the model through trial printing.

[0053] S11. Welding wire and component selection: Based on the material and performance requirements of the target component, select appropriate primary and secondary welding wires, and determine the component's forming size, layer thickness, and total number of printing layers.

[0054] S12. Calibration Experiment and Model Establishment: Through multiple sets of single-pass and multi-layer calibration experiments, molten pool state data and component forming quality data under different twin-wire feed rate ratios and arc parameters are collected. Deep learning algorithms are used to establish a correlation model of molten pool characteristic parameters, twin-wire feed parameters, arc parameters, and forming quality.

[0055] S13. Threshold and parameter preset: Based on the calibration experiment results, preset the stable threshold range of the molten pool, the initial twin wire feeding rate, the initial arc parameters, the printing speed, the layer thickness, and the protective gas parameters, and import them into the main control system.

[0056] S14. Model optimization: Adjust the parameters of the associated model through a small number of trial prints to ensure the model's prediction accuracy and adaptability.

[0057] The deep learning algorithms in S12 include BP neural networks and LSTM. Specifically, the BP neural network is used to construct the nonlinear mapping relationship between the molten pool feature parameters and process parameters. Through multiple sets of calibration experimental data, the network weights and biases are iteratively trained to achieve accurate prediction of core feature parameters such as molten pool temperature, area, and vibration amplitude under different working conditions. The LSTM network is used to capture the temporal dependence features of the molten pool state as the printing process changes. Temporal features are extracted from the historical monitoring data of the molten pool in the continuous multi-layer printing process. Combined with the nonlinear fitting ability of the BP neural network, a correlation model that integrates spatial features and temporal features is constructed to improve the prediction accuracy and generalization ability of the molten pool state and forming quality.

[0058] S2. System debugging and printing initialization: complete the communication connection and synchronization debugging of the core unit, calibrate the various accuracy parameters of the multi-dimensional monitoring unit of the molten pool, and perform system self-test after completing substrate processing and robotic arm calibration.

[0059] S21. Complete the communication connection of the four core units, debug the synchronization of each module, and ensure that the monitoring module moves synchronously with the print head, the monitoring data is transmitted in real time, and the control commands are issued accurately.

[0060] S22. Debug the multi-dimensional monitoring unit of the molten pool, calibrate the temperature measurement accuracy of the infrared temperature measurement module, adjust the focal length and exposure parameters of the high-speed visual imaging module to ensure clear capture of the molten pool and arc morphology, and debug the sensitivity of the molten pool vibration monitoring module.

[0061] S23. Complete substrate cleaning and positioning, calibrate the robotic arm printing zero point and the welding gun working distance, import the initial layer printing program, start the system self-test, and confirm that each module is operating normally.

[0062] like Figure 2 As shown, the four core units of the system specifically include: The dual-wire arc additive manufacturing execution unit includes a dual-wire arc welding machine, a robotic arm 3D motion module, a main wire feeding module, a secondary wire feeding module, a dual-wire collaborative wire feeding mechanism, and a motion control system. The main and secondary wire feeding modules feed welding wires separately, and their outputs are connected to the dual-wire collaborative wire feeding mechanism, enabling flexible switching between synchronous and asynchronous wire feeding and precise control of the wire feeding rate and rhythm. The dual-wire arc welding machine provides independent arc power to each of the two welding wires, allowing independent adjustment of the current and voltage of the main and secondary arcs to achieve precise distribution of arc energy. The motion control system is connected to the robotic arm 3D motion module, driving the print head to move along a preset path while simultaneously receiving control commands from the central control system to dynamically adjust the printing speed and layer thickness.

[0063] The molten pool multi-dimensional monitoring unit includes an infrared temperature measurement module, a high-speed visual imaging module, and a molten pool vibration monitoring module. The infrared temperature measurement module adopts a coaxial following design, moving synchronously with the printhead to collect real-time temperature distribution data in the core area of ​​the molten pool and capture temperature fluctuations. The high-speed visual imaging module is equipped with a narrow-band filter to collect real-time images of the molten pool morphology, droplet transition, and arc morphology, extracting characteristic parameters such as molten pool area, depth, and droplet size. The molten pool vibration monitoring module is installed on the printhead to collect molten pool vibration signals in real-time, assessing molten pool flow stability and eliminating abnormal fluctuation data. The outputs of all three monitoring modules are connected to the central control and intelligent control unit, enabling real-time synchronous transmission and fusion analysis of monitoring data.

[0064] The central control and intelligent regulation unit incorporates a data fusion subunit, a molten pool state assessment subunit, a dual-wire collaborative regulation subunit, an arc parameter optimization subunit, and a closed-loop feedback subunit. The data fusion subunit fuses real-time data from the three monitoring modules, removing noise interference and extracting core characteristic parameters of the molten pool state. The molten pool state assessment subunit presets a molten pool stability threshold range, compares the fused molten pool characteristic parameters with the threshold, assesses the molten pool stability level, and determines the presence of potential defects. The dual-wire collaborative regulation subunit, based on the molten pool state assessment results and preset component composition and performance requirements, dynamically calculates the adjustment values ​​for the primary and secondary wire feeding rates, optimizing the dual-wire feeding rhythm to achieve precise matching between the dual-wire melting amount and the molten pool requirements. The arc parameter optimization subunit, linked to the dual-wire collaborative regulation results, dynamically adjusts the current and voltage of the primary and secondary arcs, optimizes arc energy distribution, suppresses arc interference, and stabilizes the molten pool temperature field. The closed-loop feedback subunit sends regulation commands to the execution unit in real time, realizing a closed-loop cycle of monitoring, evaluation, regulation, and feedback to ensure real-time and accurate regulation.

[0065] The data storage and traceability unit stores monitoring data, control parameters, and molten pool status assessment results in real time, enabling full traceability of the production process and providing data support for subsequent control model optimization.

[0066] S3. Current layer printing and multi-dimensional real-time monitoring: The current layer printing program is executed to form a molten pool. The temperature distribution, morphology of the arc and vibration signals of the molten pool are collected synchronously through multiple modules, and the monitoring data are fused and feature extracted.

[0067] S31. Start the printing system and execute the current layer printing program. The main and secondary wire feeding modules feed wires according to preset parameters. The dual-wire arc welding machine ignites the main and secondary arcs, melts the welding wire to form a molten pool, and the robotic arm completes the forming of the current layer according to the preset path.

[0068] S32. During the printing process, the multi-dimensional monitoring unit of the molten pool works synchronously. The infrared temperature measurement module collects the temperature distribution data of the molten pool in real time, the high-speed visual imaging module collects the morphology and arc shape images of the molten pool in real time, and the molten pool vibration monitoring module collects the vibration signal of the molten pool in real time.

[0069] S33. All monitoring data are transmitted to the central control system in real time, where the data fusion subunit performs noise reduction and fusion processing to extract the core feature parameters of the molten pool.

[0070] S4. Melt pool status assessment and defect prediction: The characteristic parameters of the fused molten pool are compared with the preset thresholds to classify the stability level of the molten pool. In case of severe fluctuations, the process is suspended for investigation, and in other cases, the process proceeds to the subsequent control process.

[0071] S41. The molten pool status assessment subunit compares the fused molten pool characteristic parameters with the preset molten pool stability threshold range to assess the current molten pool stability level. The levels include: Stable level, all characteristic parameters are within the threshold range, the molten pool has no obvious fluctuations and no potential defects; Slight fluctuation level, some characteristic parameters exceed the threshold ±5%, the molten pool has slight fluctuations and potential for slight incomplete fusion and dimensional deviations; Severe fluctuation level, some characteristic parameters exceed the threshold ±10%, the molten pool fluctuates violently and potential for severe defects such as porosity and cracks.

[0072] S42. If the level is severe fluctuation, immediately issue a stop printing instruction, troubleshoot the fault, and restart printing after the fault is resolved; if the level is stable or slightly fluctuating, proceed to the next control procedure.

[0073] S5 integrates dual-wire coordination and arc parameter control. Based on the state assessment results, it calls the associated model to calculate and dynamically adjust the main and secondary wire feeding rates, optimize the arc current and voltage, and synchronously match the printing speed and other supporting process parameters.

[0074] S51. The dual-wire collaborative control subunit, based on the molten pool condition assessment results, calls the pre-established correlation model to calculate the adjustment values ​​of the primary and secondary wire feed rates. If the molten pool temperature is too high or the molten pool area is too large, the primary and secondary wire feed rates are reduced to decrease the amount of welding wire melted, while the printing speed is reduced and the molten pool cooling time is extended. If the molten pool temperature is too low or the molten pool area is too small, the primary and secondary wire feed rates are increased to increase the amount of welding wire melted, while the printing speed is appropriately increased to avoid heat accumulation. If the molten pool vibration amplitude is large, the dual-wire feeding rhythm is adjusted to improve the synchronization of dual-wire feeding, reduce mutual interference of the arc, and optimize the arc parameters.

[0075] S52. The arc parameter optimization subunit is linked to the dual-wire feeding adjustment results, dynamically adjusting the current and voltage of the main and secondary arcs; when the dual-wire feeding rate is increased, the arc current and voltage are slightly increased to ensure that the welding wire is fully melted; when the dual-wire feeding rate is decreased, the arc current and voltage are slightly decreased to avoid excessive arc energy leading to molten pool disorder; when arc interference is severe, the current difference between the main and secondary arcs is adjusted to optimize the arc spacing and suppress interference.

[0076] S53 simultaneously optimizes printing speed, layer thickness, and other supporting process parameters to ensure that all parameters are matched in synergy and stabilize the molten pool state.

[0077] S6. Control command issuance and next-level parameter update: All control parameters are issued to the execution unit in real time to complete the current level control, and the next-level printing control program is generated based on the adjusted parameters.

[0078] S61. Through the closed-loop feedback subunit of the main control system, the adjustment values ​​of the dual-wire feeding, the electric arc parameters, and the matching process parameters are sent to the execution unit in real time to complete the dynamic control of the current layer.

[0079] S62. Based on the adjusted process parameters, update and generate the printing control program for the next layer to ensure the stability of the molten pool in the next layer of printing.

[0080] S7. Loop execution and shaping completion: Repeat the closed-loop process of monitoring, evaluating, adjusting and updating parameters of the current layer until all layers are printed. At the same time, store the entire process data for subsequent quality traceability and model iteration optimization.

[0081] S71. Execute the printing program for the next layer, repeating the monitoring, evaluation, control, and feedback closed-loop process in S3-S6 to achieve real-time intelligent control of each layer.

[0082] S72. Continue until all preset printing layers are completed to obtain a metal component with excellent forming quality, high dimensional accuracy, and no obvious defects.

[0083] S73. The data storage and traceability unit automatically saves the entire monitoring data and control parameters, which facilitates subsequent quality traceability and model optimization.

[0084] Example 2: This application provides a method for stabilizing and integrating the control of the molten pool in dual-wire arc additive manufacturing, used to prepare complex curved surface components made of Q690 high-strength steel for aerospace applications. The components have a radius of curvature of 500 mm, a wall thickness of 8 mm, and a total of 40 printing layers. The specific implementation steps are as follows: S1. Pre-calibration and parameter preset For welding wire selection, both the main and secondary welding wires are made of φ1.2mm Q690 high-strength steel welding wire to ensure uniform mechanical properties of the components.

[0085] The calibration experiment involved 15 sets of single-channel multi-layer calibration experiments with different twin-wire feed rate ratios (1:1 to 3:1) and arc parameters (current 180-240A, voltage 22-28V). Data such as molten pool temperature, area, and vibration amplitude, as well as component defects, dimensional accuracy, and tensile strength data were collected. A correlation model was established using a BP neural network + LSTM algorithm.

[0086] Threshold and parameter presets: preset melt pool stability threshold, temperature 1800-2200℃, melt pool area 80-120mm², vibration amplitude ≤0.5mm; initial dual-wire feed rate 7m / min, initial arc current 210A, voltage 25V, printing speed 5mm / s, layer thickness 0.2mm, protective gas Ar+5%CO2, flow rate 22L / min.

[0087] Model optimization was performed by printing three layers of test models and adjusting the associated model parameters to ensure that the model's prediction accuracy was ≥95%.

[0088] S2, System Debugging and Print Initialization The system setup involves establishing communication connections between the dual-wire MIG welding machine, six-axis industrial robotic arm, dual-path closed-loop wire feeding system, coaxial infrared temperature measurement module, high-speed camera, molten pool vibration sensor, and industrial computer control system.

[0089] Equipment debugging and calibration of the infrared temperature measurement module to ensure temperature measurement accuracy ≤ ±5℃; adjustment of the high-speed camera focal length and exposure parameters, and setting the frame rate to 2500fps to clearly capture the molten pool morphology; and adjustment of the vibration sensor sensitivity to ensure accurate acquisition of molten pool vibration signals.

[0090] Printing initialization, cleaning the Q690 substrate, completing substrate positioning and robotic arm zero-point calibration, importing the initial layer printing program, completing system self-test, and confirming that each module is operating normally.

[0091] S3, Current Layer Printing and Multi-Dimensional Real-Time Monitoring The printing system is started and the first layer printing program is executed. The dual filaments are fed at a rate of 7 m / min. After the electric arc is ignited, a molten pool is formed. The robotic arm moves along a preset curved path. During the printing process, the infrared temperature measurement module collects the temperature of the molten pool in real time. The average temperature is 2050℃. The high-speed camera captures the morphology of the molten pool, with an area of ​​about 100 mm². The vibration sensor collects the vibration amplitude, with an amplitude of about 0.3 mm. All data is transmitted to the central control system in real time and fused.

[0092] S4. Molten Pool Condition Assessment and Defect Prediction The molten pool status assessment subunit compares the fused parameters with preset thresholds to determine if the molten pool is at a stable level with no potential defects, and then proceeds to the control process.

[0093] S5, Integrated control of dual-wire coordination and arc parameters When printing the 12th layer, the melt pool temperature rose to 2300℃, exceeding the threshold limit by 100℃. The melt pool area increased to 130mm², and the vibration amplitude increased to 0.6mm, which was assessed as a slight fluctuation. The dual-wire collaborative control subunit called the associated model and calculated that the main and secondary wire feed rates needed to be reduced to 6.5m / min, and the printing speed increased to 5.5mm / s. The arc parameter optimization subunit simultaneously reduced the arc current to 200A and the voltage to 24V. The control command was sent to the execution unit in real time to complete the dynamic control.

[0094] S6. Issuance of control commands and updating of parameters at the next level Based on the adjusted parameters, the main control system updates and generates the printing control program for the 13th layer, ensuring that the state of the molten pool in the 13th layer returns to stability, with a temperature of 2150℃, an area of ​​105mm², and a vibration amplitude of 0.4mm.

[0095] S7, Cyclic execution and completion of shaping Repeat steps 3-6 in a closed loop until all 40 layers are printed to obtain a complex curved surface component made of Q690 high-strength steel.

[0096] Offline testing and verification showed that the components prepared in this embodiment were free of defects such as pores, cracks, and lack of fusion, with a defect rate of only 2.5%. The dimensional accuracy error was ≤ ±0.08 mm, which met the dimensional requirements of complex curved surface components. The tensile strength reached 720 MPa, and the impact toughness was ≥ 50 J @ -20℃, which is 12% higher than the existing technology and fully meets the requirements for use in the aerospace field.

[0097] Example 3: This application provides a method for stabilizing and integrating the control of the molten pool in dual-wire arc additive manufacturing, used to prepare thin-walled 6061 aluminum alloy components (3mm wall thickness, 30 total printing layers) for rail transit applications. This method addresses the pain points of easy burn-off and unstable forming in dual-wire additive manufacturing of aluminum alloy molten pools. The specific implementation steps are as follows: S1. Pre-calibration and parameter preset For welding wire selection, both the main and secondary welding wires are made of φ1.2mm 6061 aluminum alloy welding wire to avoid performance fluctuations caused by composition deviations.

[0098] The calibration experiment involved 12 sets of different twin-wire feed rate ratios (1:1 to 2:1) and AC pulse arc parameters (peak current 120-180A, base current 40-60A, pulse frequency 50Hz). Data on molten pool temperature, morphology, vibration, component defects, and dimensional accuracy were collected. A correlation model was established, with a focus on the impact of low-boiling-point element burn-off in aluminum alloys.

[0099] Threshold and parameter presets: preset melt pool stability threshold, temperature 1600-1900℃, melt pool area 50-80mm², vibration amplitude ≤0.4mm; initial dual-wire feed rate 6m / min, initial peak current 150A, base current 50A, printing speed 7mm / s, layer thickness 0.1mm, protective gas is high-purity Ar with purity ≥99.999% and flow rate 25L / min.

[0100] Model optimization was achieved by adjusting model parameters through two-layer trial printing to adapt to the fluctuating characteristics of the aluminum alloy molten pool.

[0101] S2, System Debugging and Print Initialization The system setup involves establishing communication connections between the dual-wire AC pulse welding machine, six-axis robotic arm, dual-path soft wire feeding system, coaxial infrared temperature measurement module, high-speed camera, vibration sensor, and the central control system.

[0102] Equipment debugging includes adjusting the infrared temperature measurement module to avoid interference from the strong reflectivity of aluminum alloy and ensure accurate temperature measurement; adjusting the narrow-band filter of the high-speed camera to clearly capture the flow of the molten pool and the transition of molten droplets; and adjusting the vibration sensor to avoid interference from welding spatter.

[0103] Printing initialization, cleaning the 6061 substrate, removing the oxide film, completing positioning and robotic arm zero-point calibration, importing the initial layer printing program, and completing the system self-test.

[0104] S3, Current Layer Printing and Multi-Dimensional Real-Time Monitoring The printing system is started and the first layer printing program is executed. The dual wires are fed at 6m / min. After the AC pulse arc is ignited, the welding wire is melted to form a molten pool. During the printing process, the infrared temperature measurement module collects the temperature of the molten pool in real time. The average temperature is 1750℃. The high-speed camera collects the morphology of the molten pool, with an area of ​​about 65mm². The vibration sensor collects the vibration amplitude, with an amplitude of about 0.3mm. The data is transmitted to the central control system in real time and fused.

[0105] S4. Molten Pool Condition Assessment and Defect Prediction The molten pool condition is assessed as stable with no potential defects, and the process is now in the control phase.

[0106] S5, Integrated control of dual-wire coordination and arc parameters When printing to the 18th layer, due to fluctuations in arc heat input, the molten pool temperature dropped to 1550℃, below the lower threshold of 50℃, the molten pool area shrank to 45mm², and the vibration amplitude increased to 0.5mm, which was assessed as a slight fluctuation. The dual-wire collaborative control subunit called the associated model and calculated that the main / secondary wire feed rates needed to be increased to 6.3m / min, and the printing speed reduced to 6.5mm / s. The arc parameter optimization subunit simultaneously increased the peak current to 160A and the base current to 55A to reduce element burn-off and stabilize the molten pool. After the control command was issued, the molten pool state quickly returned to stability.

[0107] S6. Issuance of control commands and updating of parameters at the next level Update and generate the 19th layer printing control program to ensure the continuous stability of the molten pool.

[0108] S7, Cyclic execution and completion of shaping The closed-loop control process was repeated to complete 30 layers of printing, resulting in a thin-walled 6061 aluminum alloy component.

[0109] Offline testing and verification showed that the thin-walled component prepared in this embodiment was free of defects such as pores and thermal cracks, with a defect rate of only 2%; the dimensional accuracy error was ≤ ±0.07 mm, and there was no deformation; the tensile strength reached 240 MPa, and the elongation at break was ≥18%, which is 10% higher than the existing technology, and fully meets the requirements for lightweight structures in rail transit.

[0110] The control method of this invention can flexibly switch between algorithms such as PID closed-loop control and model predictive control according to the material and structural requirements of the components, further improving the control accuracy. The multi-dimensional monitoring unit of the molten pool can adopt AI image recognition technology to automatically identify potential defects in the molten pool, enabling early warning and rapid handling of defects. The dual-wire collaborative wire feeding mechanism can be driven by a servo motor to achieve stepless adjustment of the wire feeding rate and improve the accuracy of dual-wire collaboration. In addition, an environmental monitoring module can be added to further optimize the control parameters, adapt to the printing needs of different environments, and improve the adaptability and stability of the system.

[0111] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing, characterized in that, The control method includes the following steps: S1. Preliminary calibration and parameter preset: Select welding wire based on the material and performance requirements of the target component; construct a correlation model between molten pool characteristics and process parameters through calibration experiments; preset the molten pool stability threshold and initial process parameters; and optimize the model through trial printing. S2. System debugging and printing initialization: complete the communication connection and synchronization debugging of the core unit, calibrate the various accuracy parameters of the multi-dimensional monitoring unit of the molten pool, and perform system self-test after completing substrate processing and robotic arm calibration. S3. Current layer printing and multi-dimensional real-time monitoring: The current layer printing program is executed to form a molten pool. The temperature distribution, morphology of the arc and vibration signals of the molten pool are collected synchronously through multiple modules, and the monitoring data are fused and feature extracted. S4. Melt pool status assessment and defect prediction: The characteristic parameters of the fused molten pool are compared with the preset thresholds to classify the stability level of the molten pool. In case of severe fluctuations, the investigation is suspended, and in other cases, the subsequent control process is initiated. S5, dual-wire coordination and integrated control of arc parameters, calls the associated model based on the state assessment results, calculates and dynamically adjusts the main and secondary wire feeding rates, optimizes arc current and voltage in linkage, and synchronously matches printing speed and other supporting process parameters. S6. Control command issuance and next-level parameter update: All control parameters are issued to the execution unit in real time to complete the current layer control, and the next-level printing control program is generated based on the adjusted parameters. S7. Loop execution and shaping completion: Repeat the closed-loop process of monitoring, evaluating, adjusting and updating parameters of the current layer until all layers are printed. At the same time, store the entire process data for subsequent quality traceability and model iteration optimization.

2. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The specific operations for the preliminary calibration and parameter preset in S1 are as follows: S11. Welding wire and component selection: Based on the material and performance requirements of the target component, select appropriate primary and secondary welding wires, and determine the component's forming size, layer thickness, and total number of printing layers. S12. Calibration experiment and model establishment: Through multiple sets of single-pass and multi-layer calibration experiments, molten pool state data and component forming quality data under different twin-wire feed rate ratios and arc parameters are collected. Deep learning algorithm is used to establish a correlation model of molten pool characteristic parameters, twin-wire feed parameters, arc parameters and forming quality. S13. Threshold and parameter preset: Based on the calibration experiment results, preset the stable threshold range of the molten pool, the initial twin wire feeding rate, the initial arc parameters, the printing speed, the layer thickness, and the protective gas parameters, and import them into the main control system. S14. Model optimization: Adjust the parameters of the associated model through a small number of trial prints to ensure the model's prediction accuracy and adaptability.

3. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 2, characterized in that: The deep learning algorithms in S12 include BP neural networks and LSTM, specifically: The BP neural network is used to construct the nonlinear mapping relationship between the characteristic parameters of the molten pool and the process parameters. The network weights and biases are iteratively trained through multiple sets of calibration experimental data to achieve accurate prediction of core characteristic parameters such as molten pool temperature, area, and vibration amplitude under different working conditions. The LSTM network is used to capture the temporal dependence of the molten pool state as the printing process changes. It extracts temporal features from the historical monitoring data of the molten pool during continuous multi-layer printing. Combined with the nonlinear fitting capability of the BP neural network, it constructs a correlation model that integrates spatial and temporal features, thereby improving the prediction accuracy and generalization ability of the molten pool state and forming quality.

4. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The system debugging and print initialization in S2 specifically include: S21. Complete the communication connection of the four core units, debug the synchronization of each module, and ensure that the monitoring module moves synchronously with the print head, the monitoring data is transmitted in real time, and the control commands are issued accurately. S22. Debug the multi-dimensional monitoring unit of the molten pool, calibrate the temperature measurement accuracy of the infrared temperature measurement module, adjust the focal length and exposure parameters of the high-speed visual imaging module to ensure clear capture of the molten pool and arc morphology, and debug the sensitivity of the molten pool vibration monitoring module. S23. Complete substrate cleaning and positioning, calibrate the robotic arm printing zero point and the welding gun working distance, import the initial layer printing program, start the system self-test, and confirm that each module is operating normally.

5. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 4, characterized in that: The four core units of the system specifically include: The dual-wire electric arc additive manufacturing execution unit includes a dual-wire electric arc welding machine, a robotic arm three-dimensional motion module, a main wire feeding module, a secondary wire feeding module, a dual-wire collaborative wire feeding mechanism, and a motion control system; The main wire feeding module and the secondary wire feeding module respectively feed the welding wire, and the output end is connected to the dual-wire collaborative wire feeding mechanism to realize flexible switching between synchronous and asynchronous feeding of the dual wires and to precisely control the wire feeding rate and feeding rhythm of the dual wires. Among them, the dual-wire arc welding machine provides independent arc power for the two welding wires, and the current and voltage of the main / secondary arcs can be adjusted independently to achieve precise distribution of arc energy; The motion control system is connected to the three-dimensional motion module of the robotic arm, which drives the print head to move along a preset path. At the same time, it receives control commands from the central control system to dynamically adjust the printing speed and layer thickness. The molten pool multi-dimensional monitoring unit includes an infrared temperature measurement module, a high-speed visual imaging module, and a molten pool vibration monitoring module; Among them, the infrared temperature measurement module adopts a coaxial following design, moves synchronously with the print head, and collects temperature distribution data of the core area of ​​the molten pool in real time to capture temperature fluctuations in the molten pool. Among them, the high-speed vision imaging module is equipped with a narrow-band filter to acquire images of molten pool morphology, droplet transition and arc morphology in real time, and extract feature parameters such as molten pool area, molten pool depth and droplet size; Among them, the molten pool vibration monitoring module is installed on the print head to collect molten pool vibration signals in real time, determine the flow stability of the molten pool, and eliminate abnormal fluctuation data. The outputs of all three monitoring modules are connected to the central control and intelligent control unit to achieve real-time synchronous transmission and fusion analysis of monitoring data; The overall control and intelligent regulation unit has built-in data fusion subunit, molten pool state assessment subunit, dual-wire collaborative regulation subunit, arc parameter optimization subunit, and closed-loop feedback subunit. Among them, the data fusion subunit fuses the real-time data from the three monitoring modules, removes noise interference, and extracts the core feature parameters of the molten pool state. The molten pool status assessment subunit presets the molten pool stability threshold range, compares the characteristic parameters of the fused molten pool with the threshold, assesses the molten pool stability level, and determines whether there are any potential defects. The dual-wire collaborative control subunit dynamically calculates the adjustment values ​​of the main and secondary wire feeding rates based on the molten pool condition assessment results and the preset component composition and performance requirements, optimizes the dual-wire feeding rhythm, and achieves a precise match between the dual-wire melting amount and the molten pool demand. The arc parameter optimization subunit, in conjunction with the results of dual-wire coordinated control, dynamically adjusts the current and voltage of the main and secondary arcs, optimizes arc energy distribution, suppresses mutual interference between arcs, and stabilizes the temperature field of the molten pool. The closed-loop feedback subunit sends control commands to the execution unit in real time, realizing a closed-loop cycle of monitoring, evaluation, control, and feedback, ensuring the real-time performance and accuracy of control. The data storage and traceability unit stores monitoring data, control parameters, and molten pool status assessment results in real time, enabling full traceability of the production process and providing data support for subsequent control model optimization.

6. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The specific operations for printing the current layer and real-time monitoring of multiple dimensions in S3 are as follows: S31. Start the printing system and execute the current layer printing program. The main and secondary wire feeding modules feed wires according to preset parameters. The dual-wire arc welding machine ignites the main and secondary arcs, melts the welding wire to form a molten pool, and the robotic arm completes the current layer forming according to the preset path. S32. During the printing process, the multi-dimensional monitoring unit of the molten pool works synchronously. The infrared temperature measurement module collects the temperature distribution data of the molten pool in real time, the high-speed visual imaging module collects the morphology and arc shape images of the molten pool in real time, and the molten pool vibration monitoring module collects the vibration signal of the molten pool in real time. S33. All monitoring data are transmitted to the central control system in real time, where the data fusion subunit performs noise reduction and fusion processing to extract the core feature parameters of the molten pool.

7. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The specific methods for assessing the molten pool state and predicting defects in S4 are as follows: S41. The molten pool state assessment subunit compares the fused molten pool characteristic parameters with the preset molten pool stability threshold range to assess the current molten pool stability level. The levels include: Stability level: all characteristic parameters are within the threshold range, the molten pool shows no significant fluctuations, and there are no potential defects. Slight fluctuation level, some characteristic parameters exceed the threshold ±5%, the molten pool has slight fluctuations, and there is a slight risk of incomplete fusion and dimensional deviation; Severe fluctuation level, some characteristic parameters exceed the threshold ±10%, the molten pool fluctuates violently, and there are serious defects such as porosity and cracks. S42. If the level is severe fluctuation, immediately issue a stop printing command, troubleshoot the fault, and restart printing after the fault is resolved. If the level is stable or slightly fluctuating, proceed to the next step of the control process.

8. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The dual-wire coordinated and arc parameter integrated control method in S5 includes: S51. The dual-wire collaborative control subunit calculates the adjustment values ​​of the main and secondary wire feeding rates by calling the pre-established correlation model based on the molten pool state assessment results. If the molten pool temperature is too high or the molten pool area is too large, reduce the main and secondary wire feeding rates to reduce the amount of welding wire melted, while also reducing the printing speed and extending the molten pool cooling time. If the molten pool temperature is too low or the molten pool area is too small, increase the main and secondary wire feeding rates to increase the amount of welding wire melted, and at the same time, appropriately increase the printing speed to avoid heat accumulation. The molten pool vibrates greatly. Adjusting the twin wire feeding rhythm improves the synchronization of twin wire feeding, reduces mutual interference of electric arcs, and optimizes electric arc parameters. S52, Arc parameter optimization subunit linkage dual wire feeding adjustment results, dynamically adjust the current and voltage of the main and secondary arcs; The wire feeding rate of the dual wires is increased, and the arc current and voltage are slightly increased to ensure that the welding wire is fully melted; The wire feeding rate of the dual wires is reduced, and the arc current and voltage are reduced slightly to avoid excessive arc energy that could cause molten pool disorder. The electric arcs interfere with each other severely. Adjusting the current difference between the main and secondary electric arcs and optimizing the arc spacing can suppress the interference. S53 simultaneously optimizes printing speed, layer thickness, and other supporting process parameters to ensure that all parameters are matched in synergy and stabilize the molten pool state.

9. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The method for issuing control commands and updating parameters at the next level in S6 is as follows: S61. Through the closed-loop feedback subunit of the main control system, the adjustment values ​​of the dual wire feeding, the adjustment values ​​of the arc parameters, and the adjustment values ​​of the supporting process parameters are sent to the execution unit in real time to complete the dynamic control of the current layer. S62. Based on the adjusted process parameters, update and generate the printing control program for the next layer to ensure the stability of the molten pool in the next layer of printing.

10. The method for stabilizing and integrating the control of the molten pool in dual-wire electric arc additive manufacturing according to claim 1, characterized in that: The operation mode for cyclic execution and forming completion in S7 is as follows: S71. Execute the printing program of the next layer, repeat the monitoring, evaluation, control, and feedback closed-loop process in S3-S6, and realize real-time intelligent control of each layer. S72. Continue until all preset printing layers are completed to obtain a metal component with excellent forming quality, high dimensional accuracy, and no obvious defects; S73. The data storage and traceability unit automatically saves the entire monitoring data and control parameters, which facilitates subsequent quality traceability and model optimization.

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