A method and device for dynamic acoustic impedance matching and coordinated control of magnesium alloy WAAM performance by dual robotic arms

Abstract

This invention relates to the field of metal additive manufacturing and material processing technology, and discloses a method and apparatus for regulating the performance of magnesium alloy WAAM (wax arc welding) using a dual-robotic arm system with dynamic acoustic impedance matching. The method includes preprocessing and path planning of the original preparation data to obtain first execution data adapted for dual-robotic arm collaborative operation; through the dual-robotic arm collaborative operation architecture, the first robotic arm performs arc additive manufacturing deposition, simultaneously tracking the weld temperature via a temperature sensing unit, and triggering the second robotic arm to perform ultrasonic impact operation on the weld along the path of the first execution data within a preset temperature window, obtaining second operation data; through the sensing unit of the acoustic impedance dynamic matching module, the contact state and actual amplitude data during the ultrasonic impact operation are collected in real time, and after preprocessing the collected data, third monitoring data is obtained; based on a master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation.

Description

Technical Field

[0001] This invention relates to the field of metal additive manufacturing and material processing technology, specifically to a method and device for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic matching of acoustic impedance. Background Technology

[0002] Magnesium alloys have a density of only about 1.74 g / cm³. 3 Magnesium alloys are lightweight structural metal materials with outstanding advantages such as high specific strength, high specific stiffness, excellent damping performance, and good thermal and electrical conductivity. They have irreplaceable application value in the lightweighting of high-end equipment such as aerospace, rail transportation, automotive lightweighting, and defense equipment. However, magnesium alloys themselves have inherent characteristics such as poor room temperature plasticity (room temperature elongation is usually ≤10%), high tendency to hot cracking, narrow processing window, and easy oxidation at high temperatures. They face severe technical challenges in the Wire Arc Additive Manufacturing (WAAM) process: the WAAM forming process uses an electric arc as a heat source, which has concentrated and large heat input (usually 500-800 J / mm) and fast cooling rate (10 J / mm). 2 -10 3 Due to the characteristics of K / s, the forming process is accompanied by frequent thermal cycling, which can easily lead to significant residual stress of 150-250 MPa inside the component. This can cause macroscopic warping deformation (deformation ≥ 0.5 mm / m), micro-crack initiation and propagation, and seriously reduce the dimensional accuracy, fatigue life and service reliability of the component.

[0003] Currently, methods for eliminating residual stress in WAAM formed components mainly include overall heat treatment, mechanical vibration, roll forming, and shot peening. However, each method has significant technical drawbacks: overall heat treatment needs to be carried out after component forming, usually using a process of holding at 200-250℃ for 2-4 hours, which involves cumbersome procedures, energy consumption of ≥5 kWh per component, and long production cycles. Moreover, the heat treatment process can easily lead to coarsening of magnesium alloy grains. The mechanical vibration method operates at a frequency of 20-100 Hz, which has limited effect on alleviating residual stress, reducing it by only 20-30%, and cannot achieve grain refinement or improvement in microstructure uniformity. The roll forming process has poor component adaptability, only suitable for planar or simple curved surface components, and is difficult to apply to irregularly shaped components such as grids, internal cavities, and complex curved surfaces. Furthermore, the impact process can easily cause surface damage to the component, resulting in a surface roughness Ra≥1.6 μm after treatment. While existing ultrasonic-assisted additive manufacturing (WAAM) technologies attempt to address the aforementioned technical challenges, they have yet to overcome the core bottleneck of unstable ultrasonic energy transfer. Factors such as the formation of dense oxide films (≥5 μm thick) on magnesium alloy surfaces, variations in component geometry curvature, and contact stiffness fluctuations of ±15% during impact result in ultrasonic energy reflection and attenuation, leading to poor amplitude stability with deviations exceeding ±15%. This, in turn, causes impedance mismatch, resulting in uneven residual stress elimination and significant fluctuations in microstructure optimization, failing to meet the demands of stable industrial applications. Even with the introduction of PID and MPC algorithms for control, existing technologies employ only simple parallel or threshold-switching control modes, lacking data interaction and scenario adaptation capabilities. This fails to address the complex challenges of "instantaneous fluctuations in contact stiffness + drifting trends in thermal accumulation" during magnesium alloy WAAM, and still suffers from amplitude deviations ≥15% and high failure rates in adapting to complex structures. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a method and device for dynamic acoustic impedance matching and coordinated control of magnesium alloy WAAM performance using dual robotic arms, in order to solve the aforementioned technical problems.

[0005] Firstly, a method for regulating the performance of magnesium alloy WAAM (waxed acoustic acoustic impedance) through dual robotic arms in dynamic acoustic impedance matching is provided, including: Obtain the original preparation data; The original preparation data is preprocessed and path planning is performed to obtain the first execution data adapted for the collaborative operation of two robotic arms; Through a dual-arm collaborative operation architecture, the first arm performs arc additive manufacturing deposition operations, and simultaneously tracks the weld temperature through a temperature sensing unit. Within a preset temperature window, the second arm is triggered to perform ultrasonic impact operations on the weld along the path of the first execution data to obtain the second operation data. The sensor unit of the acoustic impedance dynamic matching module collects the contact state and actual amplitude data in real time during the ultrasonic impact operation. After preprocessing the collected data, the third monitoring data is obtained. Based on the master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation. The impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation are adjusted according to the control signal to complete the layer-by-layer deposition and synchronous performance regulation of the component. The forming state and microstructure of magnesium alloy components that have completed the entire deposition and performance control process are characterized to obtain magnesium alloy additive manufacturing components with optimized performance.

[0006] Furthermore, the original preparation data is preprocessed and path planning is performed to obtain the first execution data adapted for dual robotic arm collaborative operation, including: The original preparation data includes the three-dimensional model data of the magnesium alloy component to be manufactured and the matching magnesium alloy welding wire raw materials. The magnesium alloy welding wire raw material is surface treated to obtain pretreated welding wire; The 3D model data of the magnesium alloy component to be manufactured is processed by layering and slicing to formulate a layered and segmented additive manufacturing scanning path; Synchronously adapt and plan the additive manufacturing scanning path to generate an ultrasonic impact operation path that matches the timing and trajectory of the additive manufacturing path. The additive manufacturing scanning path and the ultrasonic impact operation path are imported into the central controller to complete the adaptation and calibration of the motion trajectory of the two robotic arms and obtain the first execution data.

[0007] Furthermore, through a dual-robotic arm collaborative operation architecture, the first robotic arm performs the arc additive manufacturing deposition operation, while simultaneously tracking the weld temperature through a temperature sensing unit. Within a preset temperature window, the second robotic arm is triggered to perform ultrasonic impact operation on the weld along the path of the first execution data, obtaining the second operation data, including: Based on the first execution data, the first six-axis industrial robotic arm equipped with an electric arc additive manufacturing device performs the deposition operation of magnesium alloy weld beads according to the additive manufacturing scanning path in the first execution data, thereby completing the formation of a single weld bead. By using temperature sensing units arranged along the formed weld bead, the temperature data of the weld bead after deposition is collected in real time, and the real-time temperature field information of the weld bead is obtained. When the weld temperature falls into the preset stress relief temperature window, the second six-axis industrial robotic arm equipped with an ultrasonic impact device is triggered to perform synchronous ultrasonic impact operation on the corresponding weld according to the ultrasonic impact operation path in the first execution data. The motion timing of the two robotic arms is simultaneously calibrated to obtain the second set of operational data.

[0008] Furthermore, the sensing unit of the acoustic impedance dynamic matching module collects real-time contact state and actual amplitude data during the ultrasonic impact operation. After preprocessing the collected data, the third monitoring data is obtained, including: By installing a high-frequency accelerometer near the impact head of the ultrasonic impact device, real-time amplitude and vibration acceleration data during the ultrasonic impact process are collected to obtain the amplitude time domain signal. By using a force sensor installed at the interface between the ultrasonic impact device and the robotic arm, the impact pressure and contact stiffness data during the ultrasonic impact process are collected in real time to obtain the contact state time domain signal. The amplitude time-domain signal and the contact state time-domain signal are filtered and digitally converted to obtain the pre-processed effective signal. The preprocessed effective signal is converted into standardized contact state parameters and amplitude parameters to obtain the third monitoring data.

[0009] Furthermore, based on a master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation, including: Construct a master-slave collaborative composite control architecture with adaptive PID dynamic execution as the main component and MPC global predictive optimization as the secondary component. The third monitoring data is divided into two synchronous outputs: the main data is input to the adaptive PID module, and the synchronous data stream is input to the MPC module. The MPC module performs trend prediction based on multi-source data and outputs the dynamic parameter boundaries and target amplitude range of the adaptive PID module. Within the parameter boundaries set by the MPC module, the self-adaptive PID module calculates the control quantity based on the deviation between the third monitoring data and the target amplitude, and simultaneously feeds back the execution deviation to the MPC module. Through closed-loop collaboration between the MPC module and the adaptive PID module, control signals for dynamic impedance matching and amplitude regulation are generated.

[0010] Furthermore, the impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation are adjusted according to the control signal to complete the layer-by-layer deposition and synchronous performance control of the component, including: Based on the control signal, the inductance and capacitance parameters of the matching circuit are dynamically adjusted through the LC matching circuit to obtain dynamic compensation and matching of acoustic impedance. Based on the control signal, the driving voltage, output frequency and output power parameters of the ultrasonic generator are adjusted synchronously to counteract the amplitude deviation caused by contact state fluctuations. The sensing unit of the acoustic impedance dynamic matching module provides real-time feedback of the actual amplitude and contact state data after adjustment, forming a closed-loop control of impedance matching and amplitude stabilization. By maintaining amplitude stability during ultrasonic impact through closed-loop control, the layer-by-layer deposition and performance regulation of the component are completed simultaneously until the additive manufacturing operation of the entire component is completed.

[0011] Secondly, a dual-manipulator collaborative magnesium alloy WAAM performance control device with dynamic acoustic impedance matching is provided, based on the dual-manipulator collaborative magnesium alloy WAAM performance control method with dynamic acoustic impedance matching described above, including: a dual-manipulator operation unit, an electric arc additive manufacturing unit, an ultrasonic impact unit, a temperature sensing unit, an acoustic impedance dynamic matching module, and a master-slave collaborative control unit. The dual robotic arm operation unit includes a first robotic arm and a second robotic arm. The first robotic arm is equipped with an arc additive manufacturing unit, and the second robotic arm is equipped with an ultrasonic impact unit. The temperature sensing unit is arranged along the weld bead, and its signal output terminal is connected to the master-slave collaborative control unit for collecting weld bead temperature data and transmitting it to the master-slave collaborative control unit. The sensing unit of the acoustic impedance dynamic matching module is installed on the ultrasonic impact unit, and the signal output terminal is connected to the master-slave collaborative control unit to collect the contact state and amplitude data during the ultrasonic impact process. The master-slave collaborative control unit has a built-in master-slave collaborative PID+MPC composite control architecture. The signal output segment is connected to the arc additive manufacturing unit, the ultrasonic impact unit, and the acoustic impedance dynamic matching module, respectively, and is used to output collaborative control signals and amplitude modulation signals.

[0012] Furthermore, the ultrasonic impact unit includes an ultrasonic generator and an impact head. The impact head is made of a titanium alloy substrate, the surface of which is coated with a wear-resistant coating. The working surface of the substrate is machined with a cross-shaped micro-texture structure. The end of the impact head is provided with a variety of replaceable heads with different radii of curvature. The replaceable heads are assembled with the substrate by threaded connection.

[0013] Furthermore, the acoustic impedance dynamic matching module includes a sensing unit, an amplitude calculation module, an LC matching circuit, and a driver. The signal output terminal of the sensing unit is connected to the amplitude calculation module, the signal output terminal of the amplitude calculation module is connected to the master-slave collaborative control unit, and the signal output terminal of the master-slave collaborative control unit is connected to the LC matching circuit and the ultrasonic generator through the driver.

[0014] Furthermore, the first and second robotic arms are the same type of six-axis industrial robotic arms, the temperature sensing unit uses multiple sets of thermocouples evenly arranged along the weld bead, and the master-slave collaborative control unit is communicatively connected to the dual robotic arm operation unit.

[0015] The invention employing the above technical solution has the following advantages: This invention reduces residual stress from 150-250MPa to 70-85MPa through synchronous ultrasonic impact with dual robotic arms, precise temperature window control, and dynamic impedance-amplitude compensation. This reduces the difference in residual stress in different regions, effectively preventing component warping (deformation ≤0.1 mm / m) and crack initiation, and significantly improving dimensional accuracy.

[0016] The present invention utilizes the cavitation effect of ultrasonic impact and mechanical vibration to break up coarse dendrites, reducing the average grain size from 35-36 μm to 17-18 μm, thus increasing the refinement rate, increasing the proportion of equiaxed crystals, significantly improving the uniformity of the microstructure, and eliminating interlayer bonding defects and component segregation.

[0017] The innovative acoustic impedance matching and amplitude guarantee module of this invention ensures reduced amplitude deviation and improved energy transfer efficiency through real-time monitoring, LC circuit compensation and adaptive algorithm, avoiding energy attenuation caused by impedance imbalance. It is suitable for complex geometric components and long-term continuous operation (continuous operation time ≥ 4h).

[0018] The "master-slave collaboration + scene triggering + data flow closed loop" architecture of this invention achieves three major breakthroughs compared to the simple superposition of PID+MPC without interaction in existing technologies: ① reduced amplitude deviation; ② improved success rate of adaptation to complex working conditions (grid / cavity); ③ extended stable continuous operation time. These effects all stem from the collaborative design of the architecture. Simple superposition cannot achieve the same results due to three major technical barriers: real-time interaction, scene adaptation, and closed-loop efficiency. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0020] Figure 1 This is a schematic diagram of the collaborative layout of the dual robotic arms in the dual robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 2 This is a partially enlarged schematic diagram of the ultrasonic impact head in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 3 This is a schematic diagram of the acoustic impedance matching and amplitude guarantee module in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device of the present invention. Figure 4This is a flowchart of the residual stress detection and microstructure analysis feedback process in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device of the present invention with dynamic acoustic impedance matching. Figure 5 This is a diagram of the adaptive PID+MPC composite algorithm collaborative architecture in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 6 This is a block diagram of the master-slave collaborative PID+MPC composite control architecture in the dual-robotic arm collaborative magnesium alloy WAAM performance regulation method and device for dynamic acoustic impedance matching of the present invention.

[0021] Figure 7 This is a flowchart of the method for dynamic acoustic impedance matching of dual robotic arms to regulate the performance of magnesium alloy WAAM. Figure 8 The residual stress comparison KAM diagram of AZ91 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention is shown. Figure 9 The residual stress comparison KAM diagram of GWZ1031 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention is shown. Figure 10 Figure 9 The residual stress comparison KAM diagram of GWZ931 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention is shown. Figure 11 The image shows the grain size variation of AZ91 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 12 The image shows the grain size variation of GWZ1031 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 13 The image shows the grain size variation of GWZ931 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 14 The dual Y-axis diagram shows the improvement of the mechanical properties of AZ91 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 15 The dual Y-axis diagram shows the improvement of the mechanical properties of GWZ1031 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention. Figure 16This is a dual Y-axis diagram illustrating the improvement of the mechanical properties of GWZ931 in the dual-robotic arm collaborative magnesium alloy WAAM performance control method and device for dynamic acoustic impedance matching of the present invention.

[0022] Figure label: 1. First robotic arm; 2. Second robotic arm; 3. Impact head; 4. Magnesium alloy component; 5. High-frequency accelerometer; 6. Force sensor; 7. Amplitude calculation module; 8. Central controller; 9. Driver; 10. Replaceable head. Detailed Implementation

[0023] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0024] like Figures 1 to 16 As shown, the method for controlling the acoustic impedance dynamic matching of dual robotic arms in magnesium alloy WAAM performance of the present invention includes: Step S01: Obtain raw preparation data; Step S02: Preprocess and plan the path of the original preparation data to obtain the first execution data adapted for the collaborative operation of the two robotic arms; Step S03: Through the dual-arm collaborative operation architecture, the first robotic arm 1 performs the arc additive manufacturing deposition operation, and simultaneously tracks the weld temperature through the temperature sensing unit. Within the preset temperature window, the second robotic arm 2 is triggered to perform ultrasonic impact operation on the weld along the path of the first execution data to obtain the second operation data. Step S04: The sensor unit of the acoustic impedance dynamic matching module collects the contact state and actual amplitude data in real time during the ultrasonic impact operation. After preprocessing the collected data, the third monitoring data is obtained. Step S05: Based on the master-slave collaborative PID+MPC composite control architecture, process the third monitoring data to generate control signals for dynamic impedance matching and amplitude regulation. Step S06: Adjust the impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation according to the control signal to complete the layer-by-layer deposition and synchronous performance control of the component. Step S07: Characterize the forming state and microstructure of the magnesium alloy component 4 after the completion of the entire deposition and performance control process to obtain the magnesium alloy additive manufacturing component with optimized performance.

[0025] This method is implemented based on the following hardware system. Through a closed-loop logic encompassing data input, path planning, collaborative operation, data acquisition, algorithm processing, closed-loop control, and performance verification, it achieves synchronous stress elimination and microstructure optimization in magnesium alloy WAAM components. The specific implementation steps are as follows: The three-dimensional model data of the magnesium alloy component 4 to be manufactured and the matching magnesium alloy welding wire raw materials are obtained as the original preparation data to provide basic input for subsequent process implementation.

[0026] Specifically, the 3D model data of the magnesium alloy component 4 to be manufactured is constructed using SolidWorks or UGCAD software, with a model accuracy of ±0.01mm, fully encompassing the component's geometric features, dimensional tolerances, and forming requirements. The suitable magnesium alloy welding wire raw material is high-purity magnesium alloy welding wire with a diameter of Φ1.2-1.6mm and a purity ≥99.95%. AZ91, GWZ1031, GWZ931, and Mg-Gd rare earth magnesium alloy welding wires can be selected according to the component's service performance requirements. The chemical composition of AZ91 welding wire is controlled as follows: Al 8.5-9.5wt%, Zn 0.45-0.9wt%, Mn 0.17-0.4wt%, Fe≤0.005wt%, Si≤0.01wt%, with the balance being Mg; The chemical composition of GWZ1031 welding wire is controlled as follows: Gd 10wt%, Zn 3wt%, Zr 1wt%, with the balance being Mg; The chemical composition of Mg-Gd rare earth welding wire is controlled as follows: Gd 8-10wt%, Y 2-3wt%, Zr 0.4-0.6wt%, with the balance being Mg.

[0027] The raw preparation data obtained in this step will be directly used as input for step S02 to ensure accurate matching of subsequent processes with the requirements of raw materials and components.

[0028] In this embodiment, the original preparation data is preprocessed and path planning is performed to obtain the first execution data adapted for dual robotic arm collaborative operation, including: The original preparation data includes the three-dimensional model data of the magnesium alloy component 4 to be manufactured and the suitable magnesium alloy welding wire raw materials. The magnesium alloy welding wire raw material is surface treated to obtain pretreated welding wire; The three-dimensional model data of the magnesium alloy component 4 to be manufactured is processed by layer slicing, and the additive manufacturing scanning path of layer and segment is formulated. Synchronously adapt and plan the additive manufacturing scanning path to generate an ultrasonic impact operation path that matches the timing and trajectory of the additive manufacturing path. The additive manufacturing scanning path and the ultrasonic impact operation path are imported into the central controller 8 to complete the adaptation and calibration of the motion trajectory of the two robotic arms and obtain the first execution data.

[0029] Specifically, based on the original preparation data obtained in step S01, the preprocessing of the welding wire raw material and the path planning of the three-dimensional model data are completed respectively, and finally the first execution data adapted to the collaborative operation of the two robotic arms are obtained.

[0030] Specifically, the implementation process and principle of this step are as follows: Pretreatment of welding wire raw materials: The magnesium alloy welding wire in the original preparation data is surface treated by pickling with 10% dilute hydrochloric acid solution for 1-2 minutes to remove the oxide scale on the surface of the welding wire. Then, the residual acid is rinsed with deionized water and dried in an oven at 80-100℃ for 30 minutes to obtain the pretreated welding wire. The oxide scale thickness of the pretreated welding wire surface is ≤5μm and the oil content is ≤0.02wt%, which can avoid the oxide scale and oil from affecting the welding formation quality, and at the same time reduce the energy reflection during the ultrasonic impact process to ensure the acoustic coupling efficiency. 3D Model Layering and Additive Manufacturing Path Planning: The 3D model data of the magnesium alloy component to be manufactured in the original preparation data is processed by layering and slicing to formulate a layered and segmented additive manufacturing scanning path. Among them, the layer thickness is set to 0.8-1.2mm to accurately match the welding wire diameter and welding parameters; the segment length of a single weld bead is set to 50-100mm to avoid deformation and uneven microstructure caused by heat concentration in long weld beads; the spacing between adjacent weld beads is set to 1.8-2.2mm, which is 1.2-1.8 times the welding wire diameter to ensure the fusion quality between weld beads; the scanning path adopts a reciprocating scanning method with an interlayer rotation angle of 90°, which can effectively reduce interlayer heat accumulation and anisotropy of component mechanical properties. Synchronous adaptation planning of ultrasonic impact path: Based on the above additive manufacturing scanning path, synchronous adaptation planning is carried out to generate an ultrasonic impact operation path that matches the timing and trajectory of the additive path, ensuring 100% spatial overlap between the ultrasonic impact path and the additive deposition path, with no impact omission area. Dual robotic arm trajectory adaptation calibration: The above additive manufacturing scanning path and ultrasonic impact operation path are imported into the central controller 8 of the master-slave collaborative control unit to complete the adaptation calibration of the motion trajectory of the two robotic arms, ensuring that the motion synchronization accuracy of the two robotic arms is ≤50ms, with no risk of motion interference, and finally obtaining the first execution data.

[0031] The first execution data obtained in this step will be directly used as the control basis for the collaborative operation of the two robotic arms in step S03, ensuring the precise coordination of the deposition operation and the impact operation.

[0032] In this embodiment, a dual-robotic arm collaborative operation architecture is used. The first robotic arm 1 performs the arc additive manufacturing deposition operation, and simultaneously tracks the weld temperature through a temperature sensing unit. Within a preset temperature window, the second robotic arm 2 is triggered to perform ultrasonic impact operation on the weld along the path of the first execution data, obtaining the second operation data, including: Based on the first execution data, the first six-axis industrial robotic arm equipped with an electric arc additive manufacturing device performs the deposition operation of magnesium alloy weld beads according to the additive manufacturing scanning path in the first execution data, and completes the formation of a single weld bead; By using temperature sensing units arranged along the formed weld bead, the temperature data of the weld bead after deposition is collected in real time, and the real-time temperature field information of the weld bead is obtained. When the weld temperature falls into the preset stress relief temperature window, the second six-axis industrial robotic arm equipped with an ultrasonic impact device is triggered to perform synchronous ultrasonic impact operation on the corresponding weld according to the ultrasonic impact operation path in the first execution data. The motion timing of the two robotic arms is simultaneously calibrated to obtain the second set of operational data.

[0033] Specifically, using the first execution data obtained in step S02 as the control basis, the weld deposition and ultrasonic impact operations are completed simultaneously through a dual-robotic arm collaborative operation architecture. At the same time, timing, temperature, and motion data during the operation are collected to obtain the second operation data. The specific implementation process and principle of this step are as follows: Arc additive deposition operation: The first six-axis industrial robotic arm, equipped with an arc additive manufacturing device, performs layer-by-layer deposition of magnesium alloy weld beads according to the additive manufacturing scanning path in the first execution data, completing the formation of a single weld bead; the welding parameters are precisely adapted according to the welding wire type: welding current 125-140A (135-140A for AZ91 welding wire, 125-130A for Mg-Gd welding wire), arc voltage 23-24V, welding speed 500-600mm / min, wire feed speed 10-12m / min (12m / min for Φ1.2mm welding wire, 10m / min for Φ1.6mm welding wire); the shielding gas uses Ar + 2-5 vol% He mixed gas, gas flow rate 15-20L / min, and the distance between the welding torch nozzle and the workpiece is 8-12mm, which can effectively avoid welding spatter and high-temperature oxidation of magnesium alloy, ensuring the quality of weld bead formation; Real-time tracking of weld bead temperature: Temperature sensing units arranged along the formed weld bead are used to collect temperature data of the weld bead after deposition in real time, obtain real-time temperature field information of the weld bead, and transmit the temperature data to the master-slave collaborative control unit in real time. Precise triggering of ultrasonic impact operation: The master-slave collaborative control unit judges the real-time temperature data. When the weld temperature falls into the preset stress relief temperature window of 180-220℃, the second six-axis industrial robotic arm equipped with ultrasonic impact device is immediately triggered. According to the ultrasonic impact operation path in the first execution data, synchronous ultrasonic impact operation is performed on the corresponding weld. The principle of selecting 80-220℃ as the impact temperature window in this step is that the plasticity of magnesium alloy material is moderate and the dislocation slip resistance is small in this temperature range. The residual stress can be effectively released through the plastic deformation of ultrasonic impact. At the same time, it can avoid the coarsening of magnesium alloy grains caused by excessive temperature and ensure the microstructure optimization effect. The ultrasonic impact parameters are precisely controlled according to the type of welding wire and the wall thickness of the component: impact frequency 25-28kHz (26-27kHz for AZ91 welding wire, 25-26kHz for Mg-Gd welding wire), target amplitude 20-30μm (20-25μm for thin-walled components, 25-30μm for thick-walled components), ultrasonic power 800-1200W, pulse duty cycle 50-70%, impact spacing 1.5-2.0mm, impact speed 400-500mm / min, impact pressure 0.3-0.6MPa, and the contact angle between the impact head 3 and the workpiece is 90°±5° to ensure that the impact covers the entire weld area without any blind spots. Dual robotic arm timing synchronization calibration: During deposition and impact operations, the master-slave collaborative control unit synchronously calibrates the motion timing of the two robotic arms to ensure spatial position matching and timing synchronization between deposition and ultrasonic impact operations, avoid motion interference, and finally record all motion parameters, temperature parameters, and process parameters during the operation to obtain the second operation data.

[0034] The second set of operational data obtained in this step corresponds to the entire process of ultrasonic shock operation and will provide a basis for the operational scenario for impedance matching and amplitude stabilization in subsequent steps.

[0035] In this embodiment, the sensing unit of the acoustic impedance dynamic matching module collects the contact state and actual amplitude data in real time during the ultrasonic impact operation. After preprocessing the collected data, the third monitoring data is obtained, including: The high-frequency accelerometer 5 installed near the impact head 3 of the ultrasonic impact device collects real-time amplitude and vibration acceleration data during the ultrasonic impact process, and obtains the amplitude time domain signal. By using force sensor 6 installed at the interface between the ultrasonic impact device and the robotic arm, the impact pressure and contact stiffness data during the ultrasonic impact process are collected in real time to obtain the contact state time domain signal. The amplitude time-domain signal and the contact state time-domain signal are filtered and digitally converted to obtain the pre-processed effective signal. The preprocessed effective signal is converted into standardized contact state parameters and amplitude parameters to obtain the third monitoring data.

[0036] Specifically, for the ultrasonic impact operation process corresponding to the second operational data in step S03, the sensing unit of the acoustic impedance dynamic matching module collects multi-source data in real time during the impact process and performs preprocessing to finally obtain standardized third monitoring data. The implementation process and principle of this step are as follows: Multi-source data synchronous acquisition: The high-frequency accelerometer 5 installed near the impact head 3 of the ultrasonic impact device acquires the actual amplitude and vibration acceleration data during the ultrasonic impact process in real time, and obtains the amplitude time domain signal; the force sensor 6 installed at the interface between the ultrasonic impact device and the second robotic arm 2 acquires the impact pressure and contact stiffness data during the ultrasonic impact process in real time, and obtains the contact state time domain signal; the synchronous sampling frequency of the two sets of sensors is ≥20kHz to ensure the time synchronization and accuracy of the acquired data, and to fully capture the instantaneous fluctuations in contact stiffness and amplitude changes; Data preprocessing: The amplitude calculation module 7 performs Fast Fourier Transform (FFT) and digital filtering on the collected amplitude time-domain signal and contact state time-domain signal. The filtering frequency is set to 50kHz to remove noise signals caused by environmental interference and mechanical vibration, and obtain the preprocessed effective signal. Data standardization and conversion: The preprocessed effective signal is converted into standardized contact state parameters, contact stiffness parameters and amplitude parameters. The parameter range covers the impedance monitoring range of 10-200 N·s / m and the target amplitude of 20-30 μm, and finally the third monitoring data is obtained.

[0037] The third monitoring data obtained in this step is the sole input to the subsequent composite control algorithm, providing accurate data support for impedance dynamic matching and amplitude stabilization.

[0038] In this embodiment, based on a master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation, including: Construct a master-slave collaborative composite control architecture with adaptive PID dynamic execution as the main component and MPC global predictive optimization as the secondary component. The third monitoring data is divided into two synchronous outputs: the main data is input to the adaptive PID module, and the synchronous data stream is input to the MPC module. The MPC module performs trend prediction based on multi-source data and outputs the dynamic parameter boundaries and target amplitude range of the adaptive PID module. Within the parameter boundaries set by the MPC module, the self-adaptive PID module calculates the control quantity based on the deviation between the third monitoring data and the target amplitude, and simultaneously feeds back the execution deviation to the MPC module. Through closed-loop collaboration between the MPC module and the adaptive PID module, control signals for dynamic impedance matching and amplitude regulation are generated.

[0039] Specifically, using the third monitoring data obtained in step S04 as input, data processing and optimization calculations are performed based on a master-slave collaborative PID+MPC composite control architecture to ultimately generate control signals for dynamic impedance matching and amplitude regulation. Specifically, the core implementation principle of this step is: constructing a master-slave collaborative composite control architecture with "adaptive PID dynamic execution as the master and MPC global prediction optimization as the slave" to resolve the core contradiction between "real-time response to high-frequency fluctuations" and "global optimization of low-frequency trends" in magnesium alloy WAAM ultrasonic impact. The PID module is responsible for rapid response to high-frequency instantaneous fluctuations, while the MPC module is responsible for global trend prediction and parameter constraints. The two form a closed-loop collaboration of prediction-execution-feedback-optimization. The specific implementation process is as follows: Architecture initialization and data splitting: Construct the master-slave collaborative composite control architecture described above, and split the third monitoring data obtained in step S04 into two synchronous outputs. The master data stream is input to the adaptive PID module, and the synchronous data stream is input to the MPC module to ensure that the input data of the two modules are completely synchronized. MPC Global Prediction Optimization: Based on the received third-party monitoring data, combined with the component geometry model, weld temperature trend, and historical data stream of the past 100ms, the MPC module performs low-frequency trend prediction with a prediction step size of 5-10 steps and a prediction time domain of 50-100ms. Through prediction calculation, it outputs the dynamic parameter boundaries (dynamic adjustment range of Kp=5.0-8.0, Ki=0.1-0.3, Kd=0.5-1.0) and target amplitude range (20-30μm) of the adaptive PID module, providing optimization constraints for the PID module and avoiding overshoot and instability in PID control. Adaptive PID Dynamic Execution: Within the parameter boundaries set by the MPC module, the adaptive PID module quickly calculates the control quantity based on the deviation between the actual amplitude and the target amplitude in the third monitoring data, with a response time ≤10ms. It can quickly offset the amplitude deviation caused by instantaneous fluctuations in contact stiffness and slight temperature drift. At the same time, the adaptive PID module feeds back the actual execution deviation (amplitude deviation, adjustment amount) to the MPC module in real time to update the weight coefficients of the prediction model and optimize the subsequent prediction accuracy. Control signal generation: Through the closed-loop collaboration of the MPC module and the adaptive PID module, the control signals for dynamic impedance matching and amplitude regulation are finally generated, including the inductor and capacitor adjustment signals of the LC matching circuit, the driving voltage of the ultrasonic generator, and the output frequency and output power adjustment signals.

[0040] The control signal generated in this step will be used directly as the basis for parameter adjustment in step S06, so as to achieve precise execution of impedance matching and amplitude stabilization.

[0041] In this embodiment, the impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation are adjusted according to the control signal to complete the layer-by-layer deposition and synchronous performance control of the component, including: Based on the control signal, the inductance and capacitance parameters of the matching circuit are dynamically adjusted through the LC matching circuit to obtain dynamic compensation and matching of acoustic impedance. Based on the control signal, the driving voltage, output frequency and output power parameters of the ultrasonic generator are adjusted synchronously to offset the amplitude deviation caused by contact state fluctuations; The sensing unit of the acoustic impedance dynamic matching module provides real-time feedback of the actual amplitude and contact state data after adjustment, forming a closed-loop control of impedance matching and amplitude stabilization. By maintaining amplitude stability during ultrasonic impact through closed-loop control, the layer-by-layer deposition and performance regulation of the component are completed simultaneously until the additive manufacturing operation of the entire component is completed.

[0042] Specifically, based on the control signal generated in step S05, the acoustic impedance matching parameters and ultrasonic output parameters are adjusted synchronously to form a closed-loop control, maintaining amplitude stability during ultrasonic impact and simultaneously completing the layer-by-layer deposition and performance regulation of the component until the additive manufacturing operation of the entire component is completed. The specific implementation process and principle of this step are as follows: Acoustic impedance dynamic matching: Through the LC matching circuit, the inductance and capacitance parameters of the matching circuit are dynamically adjusted according to the control signal, with a dynamic adjustment step of 1μH / 10pF. When a contact stiffness fluctuation of ±10% is detected, the impedance compensation mechanism is immediately activated to realize the dynamic compensation and matching of acoustic impedance, and eliminate the ultrasonic energy reflection and attenuation caused by impedance mismatch. Dynamic adjustment of ultrasonic output parameters: The driving voltage, output frequency and output power parameters of the ultrasonic generator are adjusted synchronously according to the control signal to offset the amplitude deviation caused by contact state fluctuations and heat accumulation drift, and to stabilize the actual amplitude within the target range. Full closed-loop feedback control: Through the sensing unit of the acoustic impedance dynamic matching module, the actual amplitude and contact state data after adjustment are fed back in real time, and the data acquisition and preprocessing stage of step S04 is re-entered, forming a full closed-loop control of impedance matching and amplitude stabilization of acquisition-calculation-adjustment-feedback, ensuring that the amplitude deviation during ultrasonic impact is ≤±5%, the steady-state error is ≤±2%, and the energy transfer efficiency is improved to ≥85%; Layer-by-layer operation cycle: The amplitude is kept stable during the ultrasonic impact process by maintaining the closed-loop control described above. Steps S03 to S06 are repeated synchronously to complete the layer-by-layer deposition and synchronous performance regulation of the component until the additive manufacturing operation of the entire component is completed.

[0043] The magnesium alloy component 4, after completing the entire deposition and performance control process in step S06, is comprehensively characterized in terms of its forming state, residual stress, microstructure, and mechanical properties to verify the technical effectiveness of the present invention, ultimately obtaining a magnesium alloy additive manufacturing component with optimized performance. Specifically, the characterization method in this step is as follows: Forming state characterization: The dimensional accuracy and warpage deformation of the component are detected by a coordinate measuring machine, and the surface roughness of the component is detected by a surface roughness meter; Residual stress detection: The residual stress of the component is detected by X-ray diffraction, with a diffraction angle of 2θ = 30-120° and a step size of 0.02°. The residual stress values ​​and uniformity of different regions of the component are detected. Microstructure characterization: The grain size and microstructure of the component were detected by electron backscatter diffraction (EBSD) with a scanning step size of 2 μm. The average grain size and the proportion of equiaxed grains were statistically analyzed. Mechanical property testing: The tensile strength, yield strength and elongation of the component were tested using a universal testing machine at a tensile speed of 1 mm / min, and the microhardness of the component was tested using a Vickers hardness tester.

[0044] One of the core innovations of this invention lies in the PID+MPC composite control architecture of master-slave collaboration + scenario triggering + data flow closed loop. In its specific implementation, a default working mode and an MPC triggering intervention mode are set, and the triggering priority is clearly defined. The specific implementation rules are as follows: 1. Default operating mode: PID independent control When the following steady-state conditions are met simultaneously, the MPC module only synchronously collects data and updates the prediction model, without interfering with the output of the PID module. The adaptive PID module independently leads the control, ensuring the control response speed: Contact stiffness fluctuation ≤ ±5%; Actual amplitude deviation ≤ ±3%; There are no sudden changes in the working conditions of the components, that is, the type of impact head remains unchanged, the curvature of the components changes by ≤5° / mm, and the weld temperature remains stable at 190-210℃.

[0045] 2. MPC Triggered Intervention Mode When the following dynamic operating conditions occur, the MPC module will trigger intervention in order of priority: sudden change in operating condition > deviation exceeding limit > trend warning. The specific intervention methods are as follows: Table 1 By switching between the two modes mentioned above, the present invention can simultaneously take into account the rapid response to high-frequency fluctuations and the global optimization of low-frequency trends. Compared with the control mode of simple parallel operation of PID and MPC without data interaction in the prior art, the amplitude deviation can be reduced from more than ±15% to ≤±5%, the success rate of adapting to complex working conditions can be increased from 60% to 100%, and the continuous operation stability time can be extended from 1 hour to ≥4 hours.

[0046] In other embodiments, a dual-manipulator collaborative magnesium alloy WAAM performance control device with dynamic acoustic impedance matching is provided, based on the dual-manipulator collaborative magnesium alloy WAAM performance control method with dynamic acoustic impedance matching described above, including: a dual-manipulator operation unit, an electric arc additive manufacturing unit, an ultrasonic impact unit, a temperature sensing unit, an acoustic impedance dynamic matching module, and a master-slave collaborative control unit. The dual robotic arm work unit includes a first robotic arm 1 and a second robotic arm 2. The first robotic arm 1 is equipped with an electric arc additive manufacturing unit, and the second robotic arm 2 is equipped with an ultrasonic impact unit. The temperature sensing unit is arranged along the weld bead, and its signal output terminal is connected to the master-slave collaborative control unit to collect weld bead temperature data and transmit it to the master-slave collaborative control unit. The sensing unit of the acoustic impedance dynamic matching module is installed in the ultrasonic shock unit, and the signal output terminal is connected to the master-slave collaborative control unit to collect contact state and amplitude data during the ultrasonic shock process. The master-slave collaborative control unit has a built-in master-slave collaborative PID+MPC composite control architecture. The signal output section is connected to the arc additive manufacturing unit, the ultrasonic impact unit, and the acoustic impedance dynamic matching module, respectively, to output collaborative control signals and amplitude modulation signals.

[0047] In this embodiment, the first robotic arm 1 and the second robotic arm 2 are six-axis industrial robotic arms of the same model. The temperature sensing unit uses multiple sets of thermocouples evenly arranged along the weld bead. The master-slave collaborative control unit is communicatively connected to the dual robotic arm operation unit.

[0048] Specifically, the dual-arm robotic unit includes a first six-axis industrial robotic arm and a second six-axis industrial robotic arm of the same model. The repeatability of both robotic arms is ±0.03mm, and the working radius is 1.5-2.0m. They are arranged opposite each other on both sides of the forming station, and the motion space completely covers the forming range of the component to be manufactured. The first robotic arm 1 is equipped with an arc additive manufacturing unit for performing layer-by-layer deposition of magnesium alloy weld beads. The second robotic arm 2 is equipped with an ultrasonic impact unit for performing synchronous ultrasonic impact on the deposited weld beads. Both robotic arms are connected to the master-slave collaborative control unit to achieve synchronous calibration and timing matching of motion trajectories, with a motion synchronization accuracy of ≤50ms.

[0049] Specifically, the arc additive manufacturing unit uses a CMT pulse arc welding machine, equipped with a wire feeding mechanism, welding torch, and shielding gas system. The welding machine has a current adjustment range of 50-200A and a voltage adjustment range of 10-30V, and is compatible with Φ1.2-1.6mm magnesium alloy welding wire. The shielding gas system can output Ar+2-5vol%He mixed shielding gas, with a gas flow rate adjustment range of 10-30L / min. The distance between the welding torch nozzle and the workpiece can be precisely controlled by a robotic arm. During the welding process, the workpiece grounding resistance is ≤0.5Ω, avoiding defects such as arc instability, oxidation, and spatter during welding.

[0050] Specifically, the temperature sensing unit uses 3-5 sets of K-type thermocouples, equipped with an industrial-grade data acquisition card, with a temperature measurement accuracy of ±1℃, a temperature acquisition frequency of 10Hz, and a data acquisition card sampling rate of 100Hz. The thermocouples are evenly arranged along the length of the weld bead, with the temperature measurement point 3-5mm away from the edge of the weld bead. The signal output end is connected to the master-slave collaborative control unit to collect the temperature data of the weld bead after deposition in real time, providing accurate temperature judgment basis for triggering ultrasonic impact operation, and providing weld bead heat accumulation trend data for composite control algorithm.

[0051] Specifically, the master-slave collaborative control unit adopts an industrial-grade PLC controller with a human-machine interface. It has a built-in master-slave collaborative PID+MPC composite control architecture. The signal input terminals are connected to the temperature sensing unit and the acoustic impedance dynamic matching module, respectively. The signal output terminals are connected to the dual robotic arm operation unit, the arc additive manufacturing unit, the ultrasonic impact unit, and the acoustic impedance dynamic matching module, respectively. It can receive multi-source sensor data and complete the collaborative motion control of the dual robotic arms, welding parameter adjustment, ultrasonic impact triggering and parameter adjustment, and closed-loop control of impedance matching and amplitude stabilization. It is the core control area of ​​the entire device.

[0052] In this embodiment, the ultrasonic impact unit includes an ultrasonic generator and an impact head 3. The impact head 3 is made of a titanium alloy substrate, the surface of which is coated with a wear-resistant coating. The working surface of the substrate is machined with a cross-shaped micro-texture structure. The end of the impact head 3 is provided with a variety of replaceable heads 10 with different radii of curvature. The replaceable heads 10 are assembled with the substrate by threaded connection.

[0053] Specifically, the ultrasonic impact unit includes an ultrasonic generator and an impact head 3. The ultrasonic generator is a high-frequency ultrasonic generator with an output power of 800-1200W, a frequency adjustment range of 20-30kHz, and a frequency stability of ±0.1kHz. It is linked with the acoustic impedance dynamic matching module and the master-slave collaborative control unit, and can adjust the output parameters in real time. The substrate of the impact head 3 is made of Ti-6Al-4V alloy with a hardness ≥32HRC and a sound velocity ≥5000m / s, possessing both high strength and excellent acoustic conductivity. The substrate surface is coated with a 2-5μm DLC diamond-like carbon coating with a coating hardness ≥25G. With an adhesion of ≤5N, the impact head 3 can improve its wear resistance and surface flexibility, and reduce impact wear. The working surface of the substrate is machined with cross-shaped micro-textures with a depth of 5-10μm, a spacing of 50-100μm, and a width of 2-3μm, which can enhance the acoustic coupling stability between the impact head 3 and the component surface and reduce ultrasonic energy reflection. The end of the impact head 3 is provided with a replaceable head 10 with a curvature radius of 5mm, 10mm, and 20mm. The replaceable head 10 is assembled with the substrate through an M8×1.25 thread with a coaxiality of ≤0.02mm, which can be quickly replaced to adapt to the impact requirements of components with different geometric structures.

[0054] In this embodiment, the acoustic impedance dynamic matching module includes a sensing unit, an amplitude calculation module 7, an LC matching circuit, and a driver 9. The signal output terminal of the sensing unit is connected to the amplitude calculation module 7, the signal output terminal of the amplitude calculation module 7 is connected to the master-slave collaborative control unit, and the signal output terminal of the master-slave collaborative control unit is connected to the LC matching circuit and the ultrasonic generator through the driver 9.

[0055] Specifically, the sensing unit includes a high-frequency accelerometer 5 and a force sensor 6. The high-frequency accelerometer 5 has a range of ±50g, a frequency response range of 1-50kHz, and a sensitivity of 100mV / g. It is installed 15-20mm from the end face of the impact head 3, at a 0° angle to the axis of the impact head 3, and is used to collect the actual amplitude and vibration acceleration data during the ultrasonic impact process in real time. The force sensor 6 has a range of 0-500N, a resolution of 0.1N, and a sampling frequency of ≥10kHz. It is installed at the interface between the impact head 3 and the second robotic arm 2, adopts a strain gauge structure, and has a linear error of ≤0.5%. It is used to collect the impact pressure and contact stiffness data during the ultrasonic impact process in real time. The amplitude calculation module 7 adopts the Fast Fourier Transform (FFT) algorithm with a frequency resolution of 0.1 kHz. It can filter the acquired time-domain signal, remove interference noise, and convert it into standardized contact state parameters, impedance parameters, and amplitude parameters. The impedance monitoring range covers 10-200 N·s / m, adapting to impedance changes under different contact states of magnesium alloys. The LC matching circuit has a matching inductor adjustment range of 10-50 μH and a capacitance value of 100-500 pF, with a dynamic adjustment step of 1 μH / 10 pF. It can dynamically adjust the inductor and capacitance parameters according to the control signal to achieve dynamic compensation and matching of acoustic impedance, and offset the impedance mismatch caused by contact state fluctuations.

[0056] Example 1: Manufacturing of thin-walled components from GWZ1031 magnesium alloy (wall thickness 3mm) Original preparation data: The three-dimensional model of the component to be manufactured has dimensions of 300mm (length) × 100mm (width) × 3mm (thickness), with a model accuracy of ±0.01mm; GWZ1031 magnesium alloy welding wire with a diameter of 1.2mm is selected, containing 10wt% Gd, 3wt% Zn, and 1wt% Zr, with the balance being Mg, and a purity ≥99.95%; Welding wire pretreatment: pickle with 10% dilute hydrochloric acid for 1.5 min, rinse with deionized water, and dry at 80℃ for 30 min. After pretreatment, the oxide scale thickness on the surface of the welding wire is ≤3μm. Path planning: layer thickness 1.0mm, segment length 80mm, adjacent weld spacing 2.0mm, reciprocating scanning path, interlayer rotation 90°, complete dual robotic arm trajectory adaptation calibration, synchronization accuracy ≤50ms, and obtain the first execution data; Welding parameters: current 125A, voltage 23V, welding speed 600mm / min, wire feed speed 12m / min; shielding gas is Ar+3vol%He, flow rate 18L / min, nozzle distance from workpiece 10mm; Ultrasonic impact parameters: frequency 27kHz, target amplitude 24μm, ultrasonic power 1000W, pulse duty cycle 60%, impact spacing 1.8mm, impact velocity 450mm / min, impact pressure 0.4MPa; impact head 3 curvature radius 10mm, surface cross-shaped microtexture depth 8μm, spacing 80μm; Control parameters: Temperature trigger window 190-220℃, using 3 K-type thermocouples arranged, temperature measurement point 4mm from weld edge; impedance monitoring range 10200N・s / m, sampling frequency 20kHz, PID parameter initial values ​​Kp=6.5, Ki=0.2, Kd=0.8, response time ≤10ms; operating environment temperature 22℃, humidity 50%; Test results: The residual stress of the component decreased from 205MPa to 72MPa, a reduction of 65%, with the difference in residual stress between different regions ≤8%; the average grain size was refined from 36μm to 18μm, a refinement of 50%, with equiaxed grains accounting for 92%; the tensile strength increased from 260MPa to 291MPa, an increase of 12%; the elongation increased from 8.2% to 9.7%, an increase of 18.3%; the warping deformation of the component was ≤0.1mm / m, and the surface roughness Ra=0.8μm.

[0057] Example 2: Manufacturing of AZ91 magnesium alloy grating components (wall thickness 5mm) Original preparation data: The three-dimensional model of the component to be manufactured has dimensions of 400mm (length) × 200mm (width) × 5mm (thickness), with a grid spacing of 20mm and a model accuracy of ±0.01mm; AZ91 magnesium alloy welding wire with a diameter of 1.6mm is selected, with a composition of Al 9.0wt%, Zn 0.6wt%, Mn 0.3wt%, Fe ≤ 0.005wt%, and the balance being Mg, with a purity ≥ 99.95%; Welding wire pretreatment: pickle with 10% dilute hydrochloric acid for 2 min, rinse with deionized water, and dry at 90℃ for 30 min. After pretreatment, the oxide scale thickness on the surface of the welding wire is ≤4μm. Path planning: layer thickness 1.2mm, segment length 50mm, adjacent weld spacing 2.2mm, reciprocating scanning path, interlayer rotation 90°, path adaptation for grille corners, completion of dual robotic arm trajectory adaptation calibration, synchronization accuracy ≤50ms, and obtaining the first execution data; Welding parameters: current 135A, voltage 24V, welding speed 550mm / min, wire feed speed 10m / min; shielding gas is Ar+5vol%He, flow rate 20L / min, nozzle distance from workpiece 12mm; Ultrasonic impact parameters: frequency 26kHz, target amplitude 25μm, ultrasonic power 1100W, pulse duty cycle 65%, impact row spacing 1.8mm, impact velocity 400mm / min, impact pressure 0.5MPa; impact head 3 with a curvature radius of 10mm is used in the planar area, and a 5mm curvature head is used at the corner of the grid; the surface cross-shaped micro-texture has a depth of 10μm and a spacing of 100μm. Control parameters: Temperature trigger window 190-220℃, using 5 K-type thermocouples, with the temperature measuring point 3mm from the weld edge; during operation, the grid overhang structure causes contact stiffness fluctuations of ±8%, triggering the MPC deviation over-limit intervention mode, automatically adjusting the drive voltage ±8V and frequency ±0.3kHz to maintain amplitude deviation ≤±4%; operating environment temperature 23℃, humidity 55%; Test results: The residual stress of the component decreased from 210MPa to 74MPa, a reduction of 64.8%, with the difference in residual stress between different regions ≤10%; the average grain size was refined from 35.5μm to 17.8μm, a refinement of 50.2%, with equiaxed grains accounting for 91%; the tensile strength increased from 250MPa to 280MPa, an increase of 12%; the elongation increased from 8.0% to 9.5%, an increase of 18.7%; the component showed no warping deformation, and the dimensional accuracy was ±0.05mm.

[0058] Example 3: Manufacturing of Mg-Gd rare earth magnesium alloy thick-walled plates (wall thickness 10mm) Original preparation data: The three-dimensional model of the component to be manufactured has dimensions of 500mm (length) × 300mm (width) × 10mm (thickness), with a model accuracy of ±0.01mm; Mg-Gd rare earth magnesium alloy welding wire with a diameter of 1.4mm is selected, containing 9wt% Gd, 2.5wt% Y, 0.5wt% Zr, and the balance being Mg, with a purity ≥99.95%; Welding wire pretreatment: pickle with 10% dilute hydrochloric acid for 1 min, rinse with deionized water, and dry at 100℃ for 30 min. After pretreatment, the oxide scale thickness on the surface of the welding wire is ≤2μm. Path planning: layer thickness 1.2mm, segment length 100mm, adjacent weld spacing 1.8mm, reciprocating scanning path, interlayer rotation 90°, complete dual robotic arm trajectory adaptation calibration, synchronization accuracy ≤50ms, and obtain the first execution data; Welding parameters: current 140A, voltage 24V, welding speed 500mm / min, wire feed speed 11m / min; shielding gas is Ar+2vol%He, flow rate 15L / min, nozzle distance from workpiece 8mm; Ultrasonic impact parameters: frequency 25kHz, target amplitude 26μm, ultrasonic power 1200W, pulse duty cycle 70%, impact spacing 1.6mm, impact velocity 480mm / min, impact pressure 0.6MPa; impact head 3 curvature radius 20mm, surface cross-shaped microtexture depth 5μm, spacing 50μm; Control parameters: Temperature trigger window 185-215℃, using 4 K-type thermocouples arranged, temperature measurement point 5mm from weld edge; initial impedance matching values: inductance 30μH, capacitance 300pF, sampling frequency 25kHz, initial PID parameters Kp=8.0, Ki=0.3, Kd=1.0, response time 8ms; during operation, MPC predicts an 8% impedance increase within 50ms, triggering trend warning intervention mode, reducing Ki from 0.3 to 0.25 in advance to maintain amplitude stability; Test results: The residual stress of the component decreased from 220MPa to 70MPa, a reduction of 68.2%, with the difference in residual stress between different regions ≤9%; the average grain size was refined from 35μm to 17μm, a refinement of 51.4%, with equiaxed grains accounting for 93%; the tensile strength increased from 255MPa to 290MPa, an increase of 14%; the elongation increased from 7.8% to 9.3%, an increase of 19.2%; the microhardness HV increased from 88 to 105, an increase of 19.3%, and there was no component segregation in the microstructure.

[0059] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for performance regulation of magnesium alloy WAAM by acoustic impedance dynamic matching of dual-robot arms, characterized in that, include: Obtain the original preparation data; The original preparation data is preprocessed and path planning is performed to obtain the first execution data adapted for the collaborative operation of two robotic arms; Through a dual-arm collaborative operation architecture, the first arm performs arc additive manufacturing deposition operations, and simultaneously tracks the weld temperature through a temperature sensing unit. Within a preset temperature window, the second arm is triggered to perform ultrasonic impact operations on the weld along the path of the first execution data to obtain the second operation data. The sensor unit of the acoustic impedance dynamic matching module collects the contact state and actual amplitude data in real time during the ultrasonic impact operation. After preprocessing the collected data, the third monitoring data is obtained. Based on the master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation. The impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation are adjusted according to the control signal to complete the layer-by-layer deposition and synchronous performance regulation of the component. The forming state and microstructure of magnesium alloy components that have completed the entire deposition and performance control process are characterized to obtain magnesium alloy additive manufacturing components with optimized performance.

2. The method for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic acoustic impedance matching according to claim 1, characterized in that, The original preparation data is preprocessed and path planning is performed to obtain the first execution data adapted for collaborative operation of two robotic arms. include: The original preparation data includes the three-dimensional model data of the magnesium alloy component to be manufactured and the matching magnesium alloy welding wire raw materials. The magnesium alloy welding wire raw material is surface treated to obtain pretreated welding wire; The 3D model data of the magnesium alloy component to be manufactured is processed by layering and slicing to formulate a layered and segmented additive manufacturing scanning path; Synchronously adapt and plan the additive manufacturing scanning path to generate an ultrasonic impact operation path that matches the timing and trajectory of the additive manufacturing path. The additive manufacturing scanning path and the ultrasonic impact operation path are imported into the central controller to complete the adaptation and calibration of the motion trajectory of the two robotic arms and obtain the first execution data.

3. The method for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic acoustic impedance matching according to claim 1, characterized in that, Through a dual-robotic arm collaborative operation architecture, the first robotic arm performs arc additive manufacturing deposition operations, while simultaneously tracking the weld temperature via a temperature sensing unit. Within a preset temperature window, the second robotic arm is triggered to perform ultrasonic impact operations on the weld along the path of the first execution data, obtaining second operation data, including: Based on the first execution data, the first six-axis industrial robotic arm equipped with an electric arc additive manufacturing device performs the deposition operation of magnesium alloy weld beads according to the additive manufacturing scanning path in the first execution data, thereby completing the formation of a single weld bead. By using temperature sensing units arranged along the formed weld bead, the temperature data of the weld bead after deposition is collected in real time to obtain the real-time temperature field information of the weld bead. When the weld temperature falls into the preset stress relief temperature window, the second six-axis industrial robotic arm equipped with an ultrasonic impact device is triggered to perform synchronous ultrasonic impact operation on the corresponding weld according to the ultrasonic impact operation path in the first execution data. The motion timing of the two robotic arms is simultaneously calibrated to obtain the second set of operational data.

4. The method for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic acoustic impedance matching according to claim 1, characterized in that, The sensing unit of the acoustic impedance dynamic matching module collects real-time contact state and actual amplitude data during ultrasonic impact operations. After preprocessing the collected data, the third monitoring data is obtained, including: By installing a high-frequency accelerometer near the impact head of the ultrasonic impact device, real-time amplitude and vibration acceleration data during the ultrasonic impact process are collected to obtain the amplitude time domain signal. By using a force sensor installed at the interface between the ultrasonic impact device and the robotic arm, the impact pressure and contact stiffness data during the ultrasonic impact process are collected in real time to obtain the contact state time domain signal. The amplitude time-domain signal and the contact state time-domain signal are filtered and digitally converted to obtain the pre-processed effective signal. The preprocessed effective signal is converted into standardized contact state parameters and amplitude parameters to obtain the third monitoring data.

5. The method for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic acoustic impedance matching according to claim 1, characterized in that, Based on a master-slave collaborative PID+MPC composite control architecture, the third monitoring data is processed to generate control signals for dynamic impedance matching and amplitude regulation, including: Construct a master-slave collaborative composite control architecture with adaptive PID dynamic execution as the main component and MPC global predictive optimization as the secondary component. The third monitoring data is divided into two synchronous outputs: the main data is input to the adaptive PID module, and the synchronous data stream is input to the MPC module. The MPC module performs trend prediction based on multi-source data and outputs the dynamic parameter boundaries and target amplitude range of the adaptive PID module. Within the parameter boundaries set by the MPC module, the self-adaptive PID module calculates the control quantity based on the deviation between the third monitoring data and the target amplitude, and simultaneously feeds back the execution deviation to the MPC module. Through closed-loop collaboration between the MPC module and the adaptive PID module, control signals for dynamic impedance matching and amplitude regulation are generated.

6. The method for controlling the performance of magnesium alloy WAAM by dual robotic arms in dynamic acoustic impedance matching according to claim 1, characterized in that, Adjusting the impedance matching parameters and ultrasonic output parameters of the ultrasonic impact operation according to the control signal completes the layer-by-layer deposition and synchronous performance control of the component, including: Based on the control signal, the inductance and capacitance parameters of the matching circuit are dynamically adjusted through the LC matching circuit to obtain dynamic compensation and matching of acoustic impedance. Based on the control signal, the driving voltage, output frequency and output power parameters of the ultrasonic generator are adjusted synchronously to counteract the amplitude deviation caused by contact state fluctuations. The sensing unit of the acoustic impedance dynamic matching module provides real-time feedback of the adjusted actual amplitude and contact state data, forming a closed-loop control for impedance matching and amplitude stabilization. By maintaining amplitude stability during ultrasonic impact through closed-loop control, the layer-by-layer deposition and performance regulation of the component are completed simultaneously until the additive manufacturing operation of the entire component is completed.

7. A dual-robotic arm collaborative magnesium alloy WAAM performance control device with dynamic acoustic impedance matching, characterized in that, The method for controlling the performance of magnesium alloy WAAM by dual robotic arms based on dynamic acoustic impedance matching according to any one of claims 1 to 6 includes: a dual robotic arm operation unit, an electric arc additive manufacturing unit, an ultrasonic impact unit, a temperature sensing unit, a dynamic acoustic impedance matching module, and a master-slave collaborative control unit. The dual robotic arm operation unit includes a first robotic arm and a second robotic arm. The first robotic arm is equipped with an electric arc additive manufacturing unit, and the second robotic arm is equipped with an ultrasonic impact unit. The temperature sensing unit is arranged along the weld bead, and its signal output terminal is connected to the master-slave collaborative control unit for collecting weld bead temperature data and transmitting it to the master-slave collaborative control unit. The sensing unit of the acoustic impedance dynamic matching module is installed on the ultrasonic impact unit, and the signal output terminal is connected to the master-slave collaborative control unit to collect the contact state and amplitude data during the ultrasonic impact process. The master-slave collaborative control unit has a built-in master-slave collaborative PID+MPC composite control architecture. The signal output segment is connected to the arc additive manufacturing unit, the ultrasonic impact unit, and the acoustic impedance dynamic matching module, respectively, and is used to output collaborative control signals and amplitude modulation signals.

8. The dual-robotic arm collaborative magnesium alloy WAAM performance control device for dynamic acoustic impedance matching according to claim 7, characterized in that, The ultrasonic impact unit includes an ultrasonic generator and an impact head. The impact head is made of a titanium alloy substrate with a wear-resistant coating on the surface. The working surface of the substrate is machined with a cross-shaped micro-texture structure. The end of the impact head is equipped with a variety of replaceable heads with different radii of curvature. The replaceable heads are assembled with the substrate by threaded connection.

9. The dual-robotic arm collaborative magnesium alloy WAAM performance control device for dynamic acoustic impedance matching according to claim 7, characterized in that, The acoustic impedance dynamic matching module includes a sensing unit, an amplitude calculation module, an LC matching circuit, and a driver. The signal output terminal of the sensing unit is connected to the amplitude calculation module, the signal output terminal of the amplitude calculation module is connected to the master-slave collaborative control unit, and the signal output terminal of the master-slave collaborative control unit is connected to the LC matching circuit and the ultrasonic generator through the driver.

10. The dual-robotic arm collaborative magnesium alloy WAAM performance control device for dynamic acoustic impedance matching according to claim 7, characterized in that, The first and second robotic arms are the same type of six-axis industrial robotic arms. The temperature sensing unit uses multiple sets of thermocouples evenly arranged along the weld bead. The master-slave collaborative control unit is communicatively connected to the dual robotic arm operation unit.

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