Ultrasonic field-magnetic field coupled multi-energy field regulation mobile additive manufacturing device

Abstract

The application relates to a mobile additive manufacturing device for ultrasonic field-magnetic field coupling multi-energy field regulation, comprising: a first actuator connected with a wire feeding device to drive the wire feeding device to move; a second actuator connected with a laser to drive the laser to move; an ultrasonic module for applying an ultrasonic vibration field to a molten pool and a heat affected zone thereof; a magnetic field applying module arranged corresponding to the molten pool to apply a magnetic field to the molten pool area; a regulation module connected with the first actuator, the second actuator, the ultrasonic module and the magnetic field applying module to regulate the first actuator, the second actuator, the ultrasonic module and the magnetic field applying module based on temperature field, molten pool morphology, deposition height and environmental data in the additive process. The application can realize multi-energy field collaborative regulation of the additive manufacturing process, and then realize accurate regulation of molten pool flow and organization evolution, and can significantly improve the organization performance, forming quality and on-site adaptability of the additive component.

Description

Technical Field

[0001] This application relates to the technical field of metal additive manufacturing equipment, specifically to a multi-energy field-controlled mobile additive manufacturing device with ultrasonic field-magnetic field coupling. Background Technology

[0002] With the rapid development of aerospace, shipbuilding equipment, energy equipment, and large components, more and more key components are characterized by large size, high complexity, and non-removability. Traditional fixed additive manufacturing equipment usually requires a constant environment and large workshop space, making it difficult to repair or remanufacture damaged components on-site under actual working conditions, resulting in long maintenance cycles, high costs, and high downtime risks.

[0003] To improve the on-site repairability of components, some studies have proposed follow-up additive manufacturing systems or portable additive manufacturing equipment, but existing technologies still have the following main problems:

[0004] Firstly, the energy field regulation is singular and has limited effect: for example, a single ultrasonic (or magnetic field) assisted additive manufacturing device can only affect local layers or limited areas, making it difficult to achieve stable and uniform tissue regulation under field conditions.

[0005] Secondly, the equipment has poor mobility and poor adaptability to working conditions: Most additive manufacturing equipment is used in factories, and is large and heavy, making it unsuitable for on-site processing of outdoor, confined spaces or immovable components.

[0006] Third, the multi-energy field coordination is insufficient: existing technologies are mostly based on single control methods such as ultrasound or electromagnetics, which makes it difficult to achieve real-time coordinated control for problems such as uneven organization and internal defects in complex structures.

[0007] Fourth, there is a lack of intelligent real-time control mechanisms: the on-site environment is subject to large disturbances, and the temperature field, stress field and deposition quality change at any time. Existing equipment generally lacks environmental sensing modules and online closed-loop control strategies, making it impossible to achieve precise control and adaptive manufacturing.

[0008] Therefore, there is an urgent need for a mobile additive manufacturing equipment that can perform precise additive manufacturing and remanufacturing in the field environment and has multi-energy field synergy. Summary of the Invention

[0009] To address the problems existing in the prior art, this application aims to provide a multi-energy field-controlled mobile additive manufacturing device with ultrasonic field-magnetic field coupling. This application can achieve multi-energy field synergistic control of the additive manufacturing process, thereby enabling precise control of molten pool flow and microstructure evolution, which can significantly improve the microstructure properties, forming quality, and on-site adaptability of additive components.

[0010] The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device described in this application includes:

[0011] The first actuator is linked with the wire feeding device to drive the wire feeding device to move.

[0012] The second actuator is linked to the laser and is used to move the laser.

[0013] An ultrasonic module, which is positioned corresponding to the molten pool, is used to apply an ultrasonic vibration field to the molten pool and its heat-affected zone.

[0014] A magnetic field application module, which corresponds to the molten pool setting, is used to apply a magnetic field to the molten pool area;

[0015] The control module is connected to the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module respectively, and is used to control the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module based on the temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process.

[0016] The control module controls the coordinated action of the first and second actuators through a coordinated control strategy. In the coordinated control strategy, an energy field interference-offset mapping model is established between energy field interference and the offset of the execution ends of the first and second actuators. Based on the energy field interference-offset mapping model, the action compensation amount for the first and second actuators is calculated. Based on the action compensation amount, the action commands of the first and second actuators are corrected. The energy field interference represents the influence of real-time ultrasonic power and magnetic field strength on the action of the execution ends of the first and second actuators.

[0017] Preferably, the ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device further includes:

[0018] A movable support platform, on which the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are all mounted.

[0019] Preferably, both the first actuator and the second actuator are multi-joint robotic arms.

[0020] Preferably, the collaborative control strategy includes the following steps:

[0021] Sa1. Establish a global coordinate system and collect the execution end coordinates of the first executor and the second executor respectively, and record them as the first end coordinates and the second end coordinates;

[0022] Sa2. Establish and calibrate the transformation relationship between the joint space of the first and second actuators and the global coordinate system;

[0023] Sa3. Import the target component model into the coordinate system, and generate a discrete point set for each deposition path based on the processing requirements.Path ={ P 1 ，P 2 ，...P n}, where each discrete point P i All include coordinates ( x i ，y i ，z i ), sedimentation rate v i Laser power matching value P laser,i ;

[0024] Sa4, based on the discrete point set of the deposition path. Path A first action command is assigned to the first actuator to perform a wire feeding-laser cladding action. Based on the first action command, a second action command is assigned to the second actuator to enable the second actuator to follow and assist the first actuator in performing the wire feeding-laser cladding action. The first action command and the second action command are both corrected by the action compensation amount.

[0025] Sa5. Based on the first action instruction and the second action instruction, perform path pre-simulation and conflict detection on the first executor and the second executor, and adjust the first action instruction and the second action instruction based on the results of the path pre-simulation and conflict detection;

[0026] Sa6. Establish a dual-actuator collaborative control model:

[0027] The state equation is expressed as: ;

[0028] The output equation is expressed as: ;

[0029] in, Represents the variable t The first-order derivative operation,

[0030] ,

[0031] x A ，y A ，z A This indicates the coordinates of the execution end of the first executor. θ A1 ,...,θ A6 This represents the joint angle state vector of the first actuator. xB ，y B ，z B This indicates the coordinates of the execution end of the second executor. θ B1 ,...,θ B6 Represents the joint angle state vectors of the second actuator;

[0032] ,

[0033] in, v A ，α A , ω A These represent the velocity, acceleration, and angular velocity of the actuating end of the first actuator, respectively. v B ，α B , ω B These represent the velocity, acceleration, and angular velocity of the actuating end of the second actuator, respectively. T Indicates the transpose operation;

[0034] △(t) represents the disturbance vector, which includes ground vibration disturbance and energy field disturbance; A, B, C, D, E All are system matrices;

[0035] Sa7. Based on the dual-actuator collaborative control model, the first and second actuators are collaboratively controlled to perform wire feeding-laser cladding actions.

[0036] Preferably, the dual-actuator cooperative control model executes an obstacle avoidance cooperative strategy, which includes the following steps:

[0037] Real-time acquisition of point cloud data of the surrounding environment of the first and second actuators;

[0038] The point cloud data is simplified to generate an obstacle-occupied grid map;

[0039] Based on the obstacle-occupied grid map, a time-dimensional cost function is introduced for dynamic obstacle avoidance path planning.

[0040] Preferably, in the cooperative control strategy, establishing an energy field interference-offset mapping model between energy field interference and the execution end offsets of the first and second actuators includes:

[0041] Real-time ultrasonic power acquisition of the molten pool region P ult and magnetic field strength BThe energy field interference-offset mapping model is established as follows:

[0042] ,

[0043] Among them, △ P This indicates the offset caused by energy field disturbance. k 1 、k 2 and k 3 represents the ultrasonic power-offset coefficient, magnetic field strength-offset coefficient, and ultrasonic-magnetic field coupling interference coefficient, respectively.

[0044] Preferably, the control module regulates one or more of the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module based on temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process, including the following steps:

[0045] Sb1. Collect the initial temperature of the molten pool region and perform filtering to obtain temperature data. , Indicates the first k Temperature value at any given time;

[0046] Acquire optical images of the molten pool region, and calculate the dimensional parameters of the molten pool based on the optical images. W, L, S ),in W, L, S These represent the width, length, and area of ​​the molten pool, respectively.

[0047] The initial deposition layer height of the melt pool region was collected and filtered to obtain filtered deposition layer height data. ;

[0048] Sb2, Constructing Feature Vectors F :

[0049] ,

[0050] in, T ave The average temperature of the molten pool over a certain period of time. T max The highest temperature of the molten pool. W, L, S These represent the width, length, and area of ​​the molten pool, respectively. H Indicates the layer height of the sedimentary layer in the molten pool region. σ H The standard deviation of the layer height of the sedimentary layer in the molten pool region. P ult This indicates the real-time ultrasonic power in the molten pool region. B This indicates the real-time magnetic field strength in the molten pool region. α r This represents the root mean square value of environmental vibration.

[0051] Sb3, Calculation of sedimentation quality assessment index Q :

[0052] ,

[0053] in, Q T Temperature assessment index:

[0054] ,

[0055] ave The average temperature of the molten pool over a certain period of time. T set The set temperature for the molten pool;

[0056] Q shape Shape evaluation index:

[0057] ,

[0058] set The set area of ​​the molten pool. S Let be the area of ​​the molten pool. W , L These represent the width and length of the molten pool, respectively.

[0059] Q H For floor height assessment index:

[0060] ,

[0061] H set The set height of the sedimentary layer, H This refers to the height of the sedimentary layer in the molten pool region;

[0062] Q env Indicators of environmental disturbance assessment index:

[0063] ,

[0064] α r This represents the root mean square value of environmental vibration. α max To allow the maximum vibration acceleration;

[0065] ω 1. ω 2. ω 3 and ω 4 represents the temperature assessment index. QT Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env The corresponding weighting coefficients;

[0066] Sb4. A quality assessment threshold is preset for the deposition quality assessment index. The deposition quality assessment index is compared with the quality assessment threshold. The first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted according to the comparison result.

[0067] Preferably, the quality assessment threshold includes a first interval that is non-overlapping and increases sequentially. C 1. Second interval C 2. Third interval C 3 and the fourth interval C 4;

[0068] In response to the aforementioned sediment quality assessment index Q Belongs to the first interval C 1. If the operation process is determined to be in an unqualified state, the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module shall all stop operating.

[0069] In response to the aforementioned sediment quality assessment index Q Belongs to the second interval C 2. If the operation is determined to be in an early warning state, the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted in the first amplitude and the data acquisition frequency is increased.

[0070] In response to the aforementioned sediment quality assessment index Q Belonging to the third interval C 3. Determine that the operation process is in a qualified state, and adjust the key parameters of the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module by a second amplitude, wherein the first amplitude is greater than the second amplitude;

[0071] In response to the aforementioned sediment quality assessment index Q Belonging to the fourth interval C 4. If the operation process is determined to be in a good condition, no adjustments are made to the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module.

[0072] Preferably, in step Sb4, in response to the deposition quality assessment index Q Not belonging to the fourth interval C 4. The temperature evaluation index QT Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env The data is input into a preset classification model to obtain the cause of the sedimentation quality anomaly. Based on the cause of the sedimentation quality anomaly, one or more of the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted.

[0073] Preferably, in the classification model, a preset temperature assessment index is included. Q T Temperature assessment threshold Thr T Regarding the shape evaluation index Q shape Shape evaluation threshold Thr shape Regarding the aforementioned floor height evaluation index Q H Floor height assessment threshold Thr H And regarding the aforementioned environmental disturbance assessment index Q env Environmental disturbance assessment threshold Thr env ,

[0074] If the temperature evaluation index is satisfied Q T Less than the temperature assessment threshold Thr T And the shape evaluation index Q shape Not less than the shape evaluation threshold Thr shape If the result is an abnormal deposition quality, the cause will be an abnormal temperature.

[0075] If the shape evaluation index is satisfied Q shape Less than the shape evaluation threshold Thr shape And the temperature assessment index Q T Not less than the temperature assessment threshold Thr T The output then states that the cause of the abnormal deposition quality is abnormal melt pool flow.

[0076] If the floor height evaluation index is satisfied Q H Less than the floor height evaluation threshold Thr H And the temperature assessment indexQ T Not less than the temperature assessment threshold Thr T The shape evaluation index Q shape Not less than the shape evaluation threshold Thr shape If the cause of the abnormal deposition quality is found to be a mismatch between the wire feed speed or laser power and the moving speed of the actuator, then the output will be...

[0077] If the environmental disturbance assessment index is met Q env Less than the environmental disturbance assessment threshold Thr env And the temperature assessment index Q T Not less than the temperature assessment threshold Thr T The shape evaluation index Q shape Not less than the shape evaluation threshold Thr shape The floor height evaluation index Q H Not less than the floor height assessment threshold Thr H If so, the cause of the abnormal deposition quality is output as abnormal environmental vibration;

[0078] When adjusting the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module, the adjustment priority is ordered from high to low as follows: laser power. P L Wire feeding speed v f Ultrasonic power P ult magnetic field strength B Execution end movement speed v m .

[0079] The advantages of the ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device described in this application are as follows:

[0080] This application can simultaneously apply a magnetic field and an ultrasonic vibration field. Through coordinated control, the two energy fields can be adjusted in real time according to the state of the molten pool, avoiding the bottleneck of a single energy field (such as the easy introduction of pores by a single ultrasonic field and insufficient strengthening of the structure by a single magnetic field). This significantly enhances the synergistic effect of multiple energy fields, effectively improving the ability to refine grains and homogenize the structure. Furthermore, it can effectively suppress common additive manufacturing defects such as porosity, cracks, and segregation during the manufacturing process, making the quality of on-site manufacturing approach or even reach the laboratory level.

[0081] This application fully considers the influence of the energy field on the actuator end during additive manufacturing. By establishing an energy field interference-offset mapping model, it calculates the motion compensation amount of the energy field interference on the offset of the actuator end, and compensates and corrects the movement of the actuator end, making the movement control of the actuator end more precise.

[0082] This application establishes a quantitative evaluation system for deposition quality based on four main evaluation indicators of the additive manufacturing process: temperature, shape, deposition layer height, and environmental interference. This system can accurately assess deposition quality and then adjust processing parameters in real time during the additive manufacturing process based on the deposition quality, thereby achieving real-time and precise control of the additive manufacturing process. This helps to further improve the accuracy and controllability of the additive manufacturing process.

[0083] This application features a movable support platform that can enter complex environments such as the field, ship cabins, and equipment platforms. Simultaneously, the dual robotic arms work together to add material, resulting in a wider range of posture coverage. In addition, it has automatic leveling, vibration resistance, and mobile deployment capabilities, enabling in-situ repair of large, non-removable components, which is impossible with traditional additive manufacturing equipment. Attached Figure Description

[0084] Figure 1 This is a schematic diagram of the structure of a multi-energy field-controlled mobile additive manufacturing device with ultrasonic field-magnetic field coupling as described in this application;

[0085] Figure 2 This is a microstructure diagram of the component obtained in Example 1;

[0086] Figure 3 This is a microstructure diagram of the component obtained in Comparative Example 1.

[0087] Explanation of reference numerals in the attached drawings: 101-First actuator, 102-Second actuator, 103-Ultrasonic module, 104-Magnetic field application module, 105-Wire feeding device, 106-Laser, 107-Stabilization system, 108-Support platform, 109-Sensor, 110-Power supply. Detailed Implementation

[0088] like Figure 1 As shown, the ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device of this application includes:

[0089] The first actuator 101 is linked with the wire feeding device 105 to drive the wire feeding device 105 to move.

[0090] The second actuator 102 is linked with the laser 106 to drive the laser 106 to move.

[0091] The ultrasonic module 103, which is positioned corresponding to the molten pool, is used to apply an ultrasonic vibration field to the molten pool and its heat-affected zone.

[0092] The magnetic field application module 104 is configured to apply a magnetic field to the molten pool area, corresponding to the molten pool setting.

[0093] The control module is connected to the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 respectively, and is used to control the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 based on the temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process.

[0094] A movable support platform 108 is provided, on which the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 are all mounted. A horizontally adjustable support leg and a stabilization system 107 can be installed between the actuators and the support platform 108. For example, the stabilization system 107 is a hydropneumatic suspension shock absorption system, model Komodo-05, used to automatically maintain equipment stability in field or complex working conditions, reducing the impact of uneven ground on additive manufacturing accuracy.

[0095] For example, the movable support 108 is specifically a tracked mobile platform used for the movement, positioning and support of the device.

[0096] Both the first actuator 101 and the second actuator 102 can be six-axis or seven-axis robotic arms. The first actuator 101 and the second actuator 102 are respectively located on both sides of the support platform 108. The first actuator 101 is used to drive the wire feeding device 105 to move and feed wire. The wire feeding device 105 can be at least one of two wire feeding methods: side wire feeding and coaxial wire feeding. The second actuator 102 is used to drive the laser 106 to move. The second actuator 102 can be equipped with an infrared thermometer and a vision system to collect temperature data and optical images of the molten pool area. It can also be equipped with any one of an air cooling nozzle or a surface cleaning tool to assist the additive manufacturing process.

[0097] The ultrasonic module 103 is used to be disposed below or on the back of the additive substrate and is used to apply an ultrasonic vibration field to the molten pool and its heat-affected zone during the deposition process. Specifically, the ultrasonic module 103 includes an ultrasonic transducer, an ultrasonic amplifier, and a conductive coupling structure. Installing the ultrasonic module 103 below or on the back of the additive substrate to apply an ultrasonic vibration field to the additive area is prior art. It can be understood by referring to the existing ultrasonic module 103 and its mounting structure. This embodiment does not limit it.

[0098] The magnetic field application module 104 includes a magnetic field coil, an electromagnetic field controller, and a cooling device. Two magnetic field application modules 104 are respectively disposed on both sides of the additive path, with the magnetic field direction pointing towards the molten pool area. They are used to apply a controllable magnetic field to the molten pool area during the additive process. Similarly, installing the magnetic field application module 104 on both sides of the additive path to apply a controllable magnetic field to the additive area is prior art, and this embodiment does not limit it.

[0099] The acquisition module includes multiple temperature sensors and optical sensors. For example, the optical sensors can be installed near the execution end of the first actuator 101 and the second actuator 102 to acquire optical images of the molten pool region during the additive manufacturing process. The temperature sensors can be located in the molten pool region to acquire temperature information of the molten pool region. Optionally, the acquisition module can be part of this device or can acquire optical images and temperature information externally. This embodiment does not limit the data acquisition method.

[0100] The acquisition module is signal-connected to the control module, used to input the acquired optical images and temperature information into the control module. The control module is signal-connected to the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104, respectively, and is used to control the parameters of each module according to the acquired optical images and temperature information, thereby controlling the additive manufacturing process. More specifically, it is used to perform real-time adaptive control of ultrasonic power, magnetic field strength, and laser / wire feeding process parameters based on temperature field, melt pool morphology, deposition height, and environmental data.

[0101] For example, the ultrasonic module 103 has an ultrasonic frequency of 20-40kHz and an ultrasonic amplitude that can be adjusted within the range of 5-30µm. The ultrasonic module 103 is in close contact with the bottom surface of the substrate through a titanium alloy or aluminum alloy coupling block, so that the ultrasonic vibration energy is directly transmitted to the molten pool area.

[0102] The magnetic field application module 104 adopts a double-sided opposing electromagnetic coil structure, and its magnetic field strength is adjustable in the range of 0.05-0.5T. The distance between the two magnetic field application modules 104 and the molten pool is maintained at 5-15mm to ensure that the magnetic field exerts a Lorentz force on the conductive liquid inside the molten pool.

[0103] The appropriate ultrasonic module 103 and magnetic field application module 104 can be selected according to the processing requirements, but this embodiment does not impose any restrictions on them.

[0104] Furthermore, in this embodiment, the control module controls the first actuator 101 and the second actuator 102 to work together through a collaborative control strategy.

[0105] The collaborative control strategy includes the following steps:

[0106] Sa1. Establish a global coordinate system and collect the execution end coordinates of the first executor 101 and the second executor 102 respectively, and record them as the first end coordinates and the second end coordinates.

[0107] Specifically, an O-XYZ global coordinate system is established using the platform surface of the support table 108 as a horizontal reference plane, and the coordinates of the center points of the execution ends of the first actuator 101 and the second actuator 102 are collected by a laser tracker (measurement accuracy ±0.01mm).

[0108] Sa2. Establish and calibrate the transformation relationship between the joint space of the first actuator 101 and the second actuator 102 and the global coordinate system;

[0109] Specifically, the absolute positioning error of the actuator is eliminated through a hand-eye calibration algorithm. The calibration formula is as follows:

[0110] ,

[0111] in, Represents the global coordinates of the executable. Let be the homogeneous transformation matrix of the actuator base relative to the global coordinate system. The transformation matrix from the joint space of the actuator to the tool coordinate system. The coordinates of the tool's end point in its own coordinate system.

[0112] The calibration results were optimized using the least squares method, so that the positioning error of the dual actuator ends in the global coordinate system was ≤0.05mm.

[0113] Sa3. Import the target component model into the coordinate system, and generate a discrete point set for each deposition path based on the processing requirements. Path ={ P 1 ，P 2 ，...P n}, where each discrete point P i All include coordinates ( x i ，y i ，z i ), sedimentation rate v i Laser power matching value P laser,i , ;

[0114] Specifically, the target component model is imported into the global coordinate system using the STL format, and a discrete point set for each deposition path is generated using a slicing algorithm. Path .

[0115] Sa4, based on the discrete point set of the deposition path. Path The first actuator 101 is assigned a first action command to perform the wire feeding-laser cladding action, which requires real-time tracking of the center of the molten pool.

[0116] Based on the first action command, a second action command is assigned to the second actuator 102 to enable the second actuator 102 to follow and assist the first actuator 101 in performing the wire feeding-laser cladding action. If an infrared thermometer is installed, the angle between the measurement direction and the normal of the molten pool should be ≤15°. Attitude correction amount. Calculated by the attitude coordination algorithm.

[0117] For example, the steps of the pose coordination algorithm are as follows:

[0118] By collecting the following key data: real-time values ​​of robotic arm joint angles θ A1 ,...,θ A6 Acquired through the encoder built into the robotic arm. to These represent the six joints of the robotic arm; the real-time coordinates of the molten pool center. The real-time value of ultrasonic power is obtained through sensor identification and extraction. P ult The frequency range is 20-40 kHz, and the real-time magnetic field strength B is 0.05-0.5 T; the vibration acceleration of the support platform 108 is... The attitude angles of the robotic arm's end effector include: pitch angle. α Roll angle β and yaw angle γ Preset process attitude parameters α 0 、β 0 , γ 0. Based on the deposition path and material properties, ensure that the angle between the laser beam and the normal to the deposition surface is ≤5°, and define the three-dimensional attitude correction as follows:

[0119] ,

[0120] in, These correspond to the correction values ​​for pitch angle, roll angle, and yaw angle, respectively. Indicates to Perform a transpose operation and use a weighted fusion algorithm to calculate the final correction:

[0121] ,

[0122] ,

[0123] ,

[0124] in, ω 1. ω 2. ω 3 represents the weighting coefficient, which was determined through process experimentation and optimization; △ θ 1 、 △ θ 2 、 △ θ 3 represents the partial error components in the directions of pitch, roll, and yaw angles, respectively. A constraint boundary is set for all corrections. This is to avoid instability in the molten pool due to sudden changes in attitude.

[0125] The first action command and the second action command are both corrected by the action compensation amount.

[0126] Sa5. Based on the first action command and the second action command, perform path pre-simulation and conflict detection on the first executor 101 and the second executor 102, and adjust the first action command and the second action command based on the results of the path pre-simulation and conflict detection.

[0127] For example, the motion trajectory of the two actuators is simulated using the Monte Carlo algorithm, traversing the joint angle space (joint angle range of a six-axis robotic arm: -π to π), detecting potential collision points. If a conflict exists, the motion trajectory of the second actuator 102 is adjusted using a path offset algorithm, with the offset amount... δ satisfy: ( d safe The minimum safe distance between actuators is 50mm (for example).

[0128] Sa6, the control module establishes a dual-actuator collaborative control model based on the model predictive control (MPC) algorithm:

[0129] The state equation is expressed as: ;

[0130] The output equation is expressed as: ;

[0131] in, , x A ，y A ，z A This indicates the coordinates of the execution end of the first executor 101. θ A1 ,...,θ A6 This represents the joint angle state vector of the first actuator 101. x B ，yB ，z B This indicates the coordinates of the execution end of the second executor 102. θ B1 ,...,θ B6 This represents the joint angle state vector of the second actuator 102.

[0132] ,

[0133] in, v A ，α A , ω A These represent the velocity, acceleration, and angular velocity of the actuator end of the first actuator 101, respectively. v B ，α B ， ω B These represent the velocity, acceleration, and angular velocity of the actuator end of the second actuator 102, respectively. T Indicates the transpose operation;

[0134] △(t) represents the disturbance vector at time t, which includes ground vibration disturbance and energy field disturbance. A, B, C, D, E All are system matrices, determined through system identification experiments, and modeled offline using MATLAB / Simulink, with online iterative optimization. Time t refers to the continuous, equally timed real-time sampling moments during the additive manufacturing process; each acquisition / calculation point is a time t, and the time interval between two adjacent time t is a fixed sampling period.

[0135] The calculation of the aforementioned perturbation vector Δ(t) is as follows:

[0136] ,

[0137] in, This represents the disturbance component of ground vibration on the dual actuators at time t; The disturbance components of the ultrasonic field-magnetic field coupling on the dual actuators at time t are represented, and they are obtained in the following ways:

[0138] ,

[0139] ,

[0140] in, They represent time t at which time t is ... x ,y , z Vibration acceleration in three directions; k vib =0.03 is the vibration-displacement conversion coefficient, which was calibrated through a ground unevenness simulation experiment;

[0141]

[0142]

[0143] ,

[0144] After calibration through orthogonal experiments; and The final perturbation vector Δ(t) is obtained by fusing the vectors with each vector having a weight of 50%.

[0145] Feedback correction is applied to the coordination error between the two actuators, specifically as follows:

[0146] Define the cooperative error vector: ,

[0147] in, For the desired state, This is the actual state;

[0148] The control quantity correction value is calculated using a PID-PWM composite control algorithm:

[0149]

[0150] in, K p = 5.2、 K i = 0.8、 K d = 1.5, which is based on the PID parameter settings optimized for mobile scenarios. In the formula, PWM(e(t)) is the pulse width modulation term, which is used to quickly suppress high-frequency disturbances, such as position fluctuations caused by ground vibration.

[0151] The dual-actuator cooperative control model executes an obstacle avoidance cooperative strategy, which includes the following steps:

[0152] Real-time acquisition of point cloud data of the surrounding environment of the first actuator 101 and the second actuator 102;

[0153] The point cloud data is simplified to generate an obstacle-occupied grid map;

[0154] Based on the obstacle-occupied grid map, a time-dimensional cost function is introduced for dynamic obstacle avoidance path planning.

[0155] Specifically, point cloud data of the surrounding environment is collected in real time using LiDAR, and a voxel filtering algorithm is used to simplify the point cloud (voxel size 0.5mm × 0.5mm × 0.5mm) to generate an obstacle occupancy grid map. Based on A The improved dynamic obstacle avoidance path planning algorithm introduces a time-dimensional cost function:

[0156]

[0157] in L path △ is the path length. t To avoid the time delay caused by obstacle avoidance, △ E This is to increase the energy consumption of the robotic arm joints. α =0.6、 β = 0.3、 γ = 0.1 is the weighting coefficient; when an obstacle is detected, the control module completes path replanning within 10ms and simultaneously issues new motion commands to the dual actuators to ensure that the relative position deviation between the molten pool and the energy field during obstacle avoidance is ≤0.1mm.

[0158] Sa7. Based on the dual-actuator collaborative control model, the first actuator 101 and the second actuator 102 are collaboratively controlled to perform wire feeding-laser cladding actions.

[0159] Furthermore, in this embodiment, the energy field interference-offset mapping model established in the cooperative control strategy, which relates energy field interference to the execution end offsets of the first actuator 101 and the second actuator 102, includes:

[0160] Real-time ultrasonic power acquisition of the molten pool region P ult and magnetic field strength B A mapping model of energy field interference and offset was established. The core principle of this model is to quantify the linear contribution of the individual and coupled effects of ultrasonic and magnetic fields to the offset of the actuator. Based on the logic of "linear influence of a single energy field + superposition of synergistic interference from multiple energy fields", a quantitative correlation between energy field parameters and the offset of the actuator is established, providing a precise calculation basis for motion compensation, and can be expressed as:

[0161] ,

[0162] Among them, △ P Indicates the amount of motion compensation. k 1 、k 2 and k 3 represents the ultrasonic power-offset coefficient, magnetic field strength-offset coefficient, and ultrasonic-magnetic field coupling interference coefficient, respectively. In a preferred embodiment, k 1 = 2.5 × 10 -6 mm / W,k 2 = 0.02 mm / T k 3 = 1.8×10 -7 mm / (W·T), obtained through orthogonal experimental calibration.

[0163] The control module corrects the motion commands of the first actuator 101 and the second actuator 102 based on the calculated motion compensation amount, in order to counteract the minor deformation or vibration interference of the actuators caused by the energy field. The motion compensation amount Δ P Represented by the XYZ three-dimensional spatial displacement vector, it is directly superimposed with the original target coordinates of the first / second actuator during control to achieve position correction and ensure that the actuator is accurately aligned with the center of the molten pool.

[0164] Furthermore, in this embodiment, the control module adjusts one or more of the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 based on the temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process, including the following steps:

[0165] Sb1. Collect the initial temperature of the molten pool region and perform filtering to obtain temperature data. , Indicates the first k The temperature value at any given time; specifically, temperature data of the molten pool area is collected, and Kalman filtering is used to eliminate ambient light interference. The filtering equation is as follows:

[0166] State prediction: ,

[0167] Covariance prediction: ,

[0168] Kalman gain: ,

[0169] Status Update: ,

[0170] in, Indicates the first k The temperature value after filtering at any given time, Z k The original temperature measurement value. Q = 0.01 represents the process noise covariance. R = 0.1 represents the measurement noise covariance.

[0171] Acquire optical images of the molten pool region, and calculate the dimensional parameters of the molten pool based on the optical images. W, L, S ),in W, L, S These represent the width, length, and area of ​​the molten pool, respectively.

[0172] Specifically, optical images of the molten pool region are acquired using a window size of 3. The median filtering algorithm in step 3 removes salt-and-pepper noise, and histogram equalization enhances the contrast of the molten pool edges. The molten pool contour is extracted based on the Canny edge detection algorithm, and the width W, length L, and area S of the molten pool are calculated. The contour extraction threshold is adaptively determined using the maximum inter-class variance method, such as the Otsu algorithm.

[0173] The initial deposition layer height of the melt pool region was collected and filtered to obtain filtered deposition layer height data. ;

[0174] Specifically, the initial deposition layer height data of the molten pool region was acquired using a "laser displacement sensor + dynamic tracking acquisition" method, with a window length of [missing information]. N The moving average filtering algorithm with a value of 5 eliminates vibration interference. An exemplary filtering formula is expressed as follows:

[0175] ,

[0176] in, H k This represents the filtered deposition layer height data after filtering. Initial sedimentary layer height data collected.

[0177] Sb2, based on the aforementioned temperature data Filtering deposition layer high data H k The width W, length L, and area S of the molten pool are used to construct a feature vector, which is represented as follows:

[0178] ,

[0179] in, T ave The average temperature of the molten pool over a certain period of time, such as 50ms. T set The highest temperature of the molten pool. σ H The standard deviation of the layer height of the sedimentary layer in the molten pool region. α r This represents the root mean square value of environmental vibration.

[0180] Sb3, Calculation of sedimentation quality assessment index Q :

[0181] ,

[0182] in, Q T Temperature assessment index:

[0183] ,

[0184] T set This is the set temperature for the molten pool, with a range of 1500℃ to 2200℃. .

[0185] Q shape Shape evaluation index:

[0186] ,

[0187] S set The set area of ​​the molten pool; .

[0188] Q H For floor height assessment index:

[0189] ,

[0190] H set Set the height of the sedimentary layer; .

[0191] Q env Indicators of environmental disturbance assessment index:

[0192] ,

[0193] α max Example values ​​for the maximum permissible vibration acceleration. α max =0.05g , Specifically, the vibration acceleration was obtained by installing a vibration sensor at the support platform 108.

[0194] ω 1. ω 2. ω 3 and ω 4 represents the temperature assessment index. Q T Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env The corresponding weight coefficients; for example, the values ​​of each weight coefficient are determined by the analytic hierarchy process. ω 1 = 0.35 ω 2 = 0.3, ω3 = 0.25 ω 4 = 0.1.

[0195] Specifically, the Analytic Hierarchy Process (AHP) is a systematic analysis method that decomposes complex decision-making problems into multiple levels (objective level, criterion level, and alternative level). It determines the relative importance of each factor through pairwise comparisons and then calculates the weights. Its core principles include three points: ① Decomposition: The overall objective of "optimizing deposition quality" is decomposed into four criterion levels (corresponding to four evaluation indices): "temperature stability," "melt pool shape rationality," "layer height uniformity," and "environmental interference suppression." ② Comparability: By comparing the influence of each factor in the criterion level on the overall objective pairwise, a judgment matrix is ​​constructed, transforming qualitative judgments into quantitative data. ③ Consistency: The logical rationality of the judgment matrix is ​​verified through consistency checks to avoid contradictions such as "A is more important than B, B is more important than C, and C is more important than A," ensuring the reliability of the weighting results. The weights are allocated based on the characteristics of the additive manufacturing field conditions.

[0196] Sb4. A quality assessment threshold is preset for the deposition quality assessment index. The deposition quality assessment index is compared with the quality assessment threshold. The first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 are adjusted according to the comparison result.

[0197] Furthermore, in this embodiment, the quality assessment threshold includes a first interval that is non-overlapping and increases sequentially. C 1. Second interval C 2. Third interval C 3 and the fourth interval C 4;

[0198] For example, setting a first interval C 1=[0,0.5), second interval C 2 = [0.5, 0.7), the third interval C 3 = [0.7, 0.9) and the fourth interval C 4 = [0.9, 1.0].

[0199] In response to the aforementioned sediment quality assessment index Q Belongs to the first interval C 1. If the operation process is determined to be in an unqualified state, the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 shall all stop operating and the cause shall be investigated.

[0200] In response to the aforementioned sediment quality assessment index Q Belongs to the second interval C2. If the operation process is determined to be in an early warning state, the first actuator 101, the second actuator 102, the ultrasonic module 103 and the magnetic field application module 104 are adjusted in the first amplitude and the data acquisition frequency is increased; that is, the parameters are moderately adjusted and the monitoring is strengthened.

[0201] In response to the aforementioned sediment quality assessment index Q Belonging to the third interval C 3. Determine that the operation process is in a qualified state, and make a second amplitude adjustment to the key parameters of the first actuator 101, the second actuator 102, the ultrasonic module 103 and the magnetic field application module 104, wherein the first amplitude is greater than the second amplitude; that is, make fine adjustments to the key parameters.

[0202] Among them, the key parameters of the first actuator 101 and the second actuator 102 are the moving speed of the actuator end, the key parameters of the ultrasonic module 103 are the ultrasonic frequency and ultrasonic power, and the key parameters of the magnetic field application module 104 are the magnetic field strength and application direction.

[0203] In response to the aforementioned sediment quality assessment index Q Belonging to the fourth interval C 4. If the operation process is determined to be in a high-quality state, no adjustments are made to the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104.

[0204] Furthermore, in this embodiment, in step Sb4, in response to the deposition quality assessment index... Q Not belonging to the fourth interval C 4. The temperature evaluation index Q T Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env The data is input into a preset classification model to obtain the cause of the sedimentation quality anomaly. Based on the cause of the sedimentation quality anomaly, one or more of the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104 are adjusted.

[0205] For example, the decision tree algorithm is used to locate the root cause of quality anomalies. The decision tree algorithm is obtained through pre-training. Specifically, multiple sets of laser additive manufacturing data with anomalies are obtained as sample data, and the temperature assessment index of each set of sample data is calculated using the formula mentioned above. Q T Shape evaluation index Q shape Floor height assessment indexQ H Environmental disturbance assessment index Q env Each set of sample data is labeled with the corresponding abnormal cause by manual calibration, such as abnormal melt pool temperature, abnormal melt pool flow, mismatch between wire feeding speed or laser power and the movement speed of the actuator, excessive environmental vibration, etc.

[0206] Using the above sample data, the decision tree model can be trained through multiple iterations to obtain a model capable of evaluating indices based on temperature. Q T Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env A decision tree model for classifying the causes of anomalies.

[0207] In actual manufacturing, optical images and temperature data of the molten pool region are obtained through optical and temperature sensors. After preprocessing, the aforementioned temperature assessment index can be calculated. Q T Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env .

[0208] The obtained temperature assessment index Q T Shape evaluation index Q shape Floor height assessment index Q H Environmental disturbance assessment index Q env The input is fed into the aforementioned decision tree model, which classifies the causes of anomalies based on the input indices, thereby obtaining the causes of anomalies.

[0209] Furthermore, in this embodiment, the classification rules in the classification model are as follows:

[0210] Preset temperature evaluation index Q T Temperature assessment threshold Thr T Regarding the shape evaluation index Q shape Shape evaluation threshold Thr shape Regarding the aforementioned floor height evaluation index QH Floor height assessment threshold Thr H And regarding the aforementioned environmental disturbance assessment index Q env Environmental disturbance assessment threshold Thr env ,

[0211] If the temperature evaluation index is satisfied Q T Less than the temperature assessment threshold Thr T And the shape evaluation index Q shape Not less than the shape evaluation threshold Thr shape If the result is an abnormal deposition quality, the cause will be an abnormal temperature.

[0212] If the shape evaluation index is satisfied Q shape Less than the shape evaluation threshold Thr shape And the temperature assessment index Q T Not less than the temperature assessment threshold Thr T The output then states that the cause of the abnormal deposition quality is abnormal melt pool flow.

[0213] If the floor height evaluation index is satisfied Q H Less than the floor height evaluation threshold Thr H And the temperature assessment index Q T Not less than the temperature assessment threshold Thr T The shape evaluation index Q shape Not less than the shape evaluation threshold Thr shape If the cause of the abnormal deposition quality is found to be a mismatch between the wire feed speed or laser power and the moving speed of the actuator, then the output will be...

[0214] If the environmental disturbance assessment index is met Q env Less than the environmental disturbance assessment threshold Thr env And the temperature assessment index Q T Not less than the temperature assessment threshold Thr T The shape evaluation index Q shape Not less than the shape evaluation thresholdThr shape The floor height evaluation index Q H Not less than the floor height assessment threshold Thr H If the result is positive, the cause of the abnormal deposition quality is abnormal environmental vibration.

[0215] For example, temperature assessment threshold Thr T Shape evaluation threshold Thr shape Floor height evaluation threshold Thr H Environmental disturbance assessment index Thr env All values ​​are taken as 0.7.

[0216] If satisfied Q T <0.7 and Q shape If the value is ≥0.7, the output error is due to an abnormal temperature, specifically a temperature that is higher or lower than the standard range.

[0217] If satisfied Q shape <0.7 and Q T If the output value is ≥0.7, the cause of the abnormal output is abnormal molten pool flow affected by the energy field or wire feeding.

[0218] If satisfied Q H <0.7 and Q T ≥0.7、 Q shape If the output wire feeding speed or laser power is ≥0.7, then the output wire feeding speed or laser power does not match the moving speed of the actuator.

[0219] If satisfied Q env <0.7, and Q H ≥0.7、 Q T ≥0.7、 Q shape If the value is ≥0.7, the vibration of the output environment is too large, and the chassis stabilization system 107 needs to be adjusted.

[0220] Based on the weight of their impact on deposition quality, when regulating the first actuator 101, the second actuator 102, the ultrasonic module 103, and the magnetic field application module 104, the regulation priority is ordered from high to low as follows: laser power. P L Wire feeding speed vf Ultrasonic power P ult magnetic field strength B Execution end movement speed v m In other words, during the parameter control process of additive manufacturing, priority is given to controlling parameters with high priority in order to quickly and efficiently adjust the deposition quality.

[0221] The implementation process and technical effects of the device of this application will be described below with reference to comparative examples and embodiments:

[0222] Example 1

[0223] Start the support platform 108 and move the device to the vicinity of the target component. Stabilize the device by using the automatic horizontal adjustment legs of the support platform 108. Activate the lidar / visual navigation system to determine the relative position of the device and the component.

[0224] Import two-dimensional slices of the target component to plan the laser scanning path, and set the additive manufacturing process parameters and parameters for different energy fields.

[0225] The ultrasonic module 103 is tightly coupled to the substrate, and the distance between the two magnetic field application modules 104 is adjusted so that the magnetic field direction points to the molten pool, thus completing the calibration of the energy field device.

[0226] The first actuator 101 is positioned at the initial deposition point, and the second actuator 102 is fixed in an auxiliary posture; the two actuators work together through a control module to perform the additive manufacturing process.

[0227] Laser fused deposition is initiated; simultaneously, the ultrasonic and magnetic fields are activated, the ultrasonic transducer begins high-frequency vibration, and the dual electromagnetic coils apply a directional magnetic field.

[0228] The sensor acquires real-time information on melt pool temperature, optical images, and layer height, and can adjust parameters in real time according to the deposition quality.

[0229] After the deposition process is complete, turn off all power supplies 110 and then disassemble the device.

[0230] Comparative Example 1

[0231] Start the support platform 108 and move the device to the vicinity of the target component. Stabilize the device by using the automatic horizontal adjustment legs of the support platform 108. Activate the lidar / visual navigation system to determine the relative position of the device and the component.

[0232] Import two-dimensional slices of the target component to plan the laser scanning path, and set the additive manufacturing process parameters at the same time;

[0233] The first actuator 101 is positioned at the initial deposition point, and the second actuator 102 is fixed in an auxiliary posture; the two actuators coordinate and control each other to carry out the additive manufacturing process.

[0234] The sensor acquires real-time information on melt pool temperature, optical images, and layer height, and can adjust parameters in real time according to the deposition quality.

[0235] After the deposition process is complete, turn off all power supplies 110 and then disassemble the device.

[0236] Comparative Example 2

[0237] Consistent with Embodiment 1, it includes a support platform, dual actuators, wire feeding device, and laser, but only retains the ultrasonic module 103 and shuts down the magnetic field application module 104;

[0238] The steps for moving, positioning, and leveling the equipment are the same as in Example 1;

[0239] Import the component model and plan the deposition path, setting only the ultrasonic parameters and basic laser / wire feeding process parameters, without magnetic field parameters;

[0240] The ultrasonic module is coupled to the substrate, and laser fused deposition is initiated while the ultrasonic field is simultaneously activated.

[0241] It only collects temperature data, has no real-time control logic, and keeps the parameters unchanged from the initial settings until the operation is completed.

[0242] Comparative Example 3

[0243] Consistent with Example 1, only the magnetic field application module 104 is retained, while the ultrasonic module 103 is turned off;

[0244] The steps for moving, positioning, and leveling the equipment are the same as in Example 1;

[0245] Import the component model and plan the deposition path, setting only the magnetic field parameters and basic laser / wire feeding process parameters, without ultrasonic parameters;

[0246] Adjust the position of the magnetic field application module, initiate laser filament deposition, and apply the magnetic field simultaneously;

[0247] It only collects temperature data, has no real-time control logic, and keeps the parameters unchanged from the initial settings until the operation is completed.

[0248] Comparative Example 4

[0249] Completely consistent with Example 1, the dual actuators, ultrasonic module, and magnetic field module are all enabled, while the real-time collaborative control function of the control module is disabled;

[0250] The steps for moving, positioning, leveling, and calibrating the energy field device are the same as in Example 1.

[0251] Import the component model and plan the deposition path, and set the ultrasonic, magnetic field, and laser / wire feeding process parameters consistent with the initial values ​​in Example 1;

[0252] Initiate laser fused filament deposition while simultaneously activating the ultrasonic and magnetic fields;

[0253] The sensor collects data on the temperature, morphology, and layer height of the molten pool, but does not adjust the parameters; it only records the data. All process parameters remain unchanged from their initial settings until the operation is completed.

[0254] Performance testing

[0255] Mechanical properties were tested on the deposited samples of Example 1 and Comparative Examples 1-4. Tensile strength, yield strength and elongation after fracture were tested according to the standard ASTM E8 / E8M−16a tensile test method for metallic materials. The test results are shown in Table 1.

[0256] Table 1: Mechanical properties of titanium alloys prepared in Example 1 and Comparative Examples 1-4

[0257]

[0258] As shown in Table 1, the microstructure of the sample prepared in Comparative Example 1 is as follows: Figure 3 As shown) compared to Example 1 (microstructure as shown) Figure 2 As shown in the figure, due to the lack of ultrasonic-magnetic field coupling, the grain size was not refined through cavitation and magnetic field stirring, and the degree of microstructure homogeneity was relatively low, thus reducing the overall mechanical properties of the sample. The samples of Comparative Example 2 and Comparative Example 3, due to the presence of only a single energy field, had limited grain refinement, insufficient melt pool flow stability, and local segregation. Their mechanical properties were slightly better than the sample without an energy field but weaker than the sample with coupled energy field. The sample of Comparative Example 4 had multi-energy field coupling but no real-time control, which could not compensate for on-site disturbances. Fluctuations in the melt pool state led to a decrease in microstructure homogeneity, resulting in slightly weaker performance than Example 1.

[0259] This application can simultaneously apply a magnetic field and an ultrasonic vibration field. Through coordinated control, the two energy fields can be adjusted in real time according to the state of the molten pool, avoiding the bottleneck of a single energy field (such as the easy introduction of pores by a single ultrasonic field and insufficient strengthening of the structure by a single magnetic field). This significantly enhances the synergistic effect of multiple energy fields, effectively improving the ability to refine grains and homogenize the structure. Furthermore, it can effectively suppress common additive manufacturing defects such as porosity, cracks, and segregation during the manufacturing process, making the quality of on-site manufacturing approach or even reach the laboratory level.

[0260] This application achieves anomaly detection (splashing, molten pool fluctuations, porosity trends, etc.) by real-time acquisition of key data such as molten pool temperature, morphology, flow, and layer height. The deposition process can be adjusted based on real-time data to further improve the quality of additive manufacturing or repair.

[0261] In the description of this application, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is usually based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this application and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this application.

[0262] For those skilled in the art, various other corresponding changes and modifications can be made based on the technical solutions and concepts described above, and all such changes and modifications should fall within the protection scope of the claims of this application.

Claims

1. A multi-energy field-controlled mobile additive manufacturing device with ultrasonic field-magnetic field coupling, characterized in that, include: The first actuator is linked with the wire feeding device to drive the wire feeding device to move. The second actuator is linked to the laser and is used to move the laser. An ultrasonic module, which is positioned corresponding to the molten pool, is used to apply an ultrasonic vibration field to the molten pool and its heat-affected zone. A magnetic field application module, which corresponds to the molten pool setting, is used to apply a magnetic field to the molten pool area; The control module is connected to the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module respectively, and is used to control the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module based on the temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process. The control module controls the coordinated action of the first and second actuators through a coordinated control strategy. In the coordinated control strategy, an energy field interference-offset mapping model is established between energy field interference and the offset of the execution ends of the first and second actuators. Based on the energy field interference-offset mapping model, the action compensation amount for the first and second actuators is calculated. Based on the action compensation amount, the action commands of the first and second actuators are corrected. The energy field interference represents the influence of real-time ultrasonic power and magnetic field strength on the action of the execution ends of the first and second actuators. The control module, based on temperature field, melt pool morphology, deposition height, and environmental data during the additive manufacturing process, controls one or more of the first actuator, second actuator, ultrasonic module, and magnetic field application module, including the following steps: Sb1. Collect the initial temperature of the molten pool region and perform filtering to obtain temperature data. , Indicates the first Temperature value at any given time; Acquire optical images of the molten pool region, and calculate the dimensional parameters of the molten pool based on the optical images. ,in These represent the width, length, and area of ​​the molten pool, respectively. The initial deposition layer height of the melt pool region was collected and filtered to obtain filtered deposition layer height data. ; Sb2, Constructing Feature Vectors : ， in, The average temperature of the molten pool over a certain period of time. The highest temperature of the molten pool. These represent the width, length, and area of ​​the molten pool, respectively. Indicates the layer height of the sedimentary layer in the molten pool region. The standard deviation of the layer height of the sedimentary layer in the molten pool region. This indicates the real-time ultrasonic power in the molten pool region. This indicates the real-time magnetic field strength in the molten pool region. This represents the root mean square value of environmental vibration. Sb3, Calculation of sedimentation quality assessment index : ， in, Temperature assessment index: ， The average temperature of the molten pool over a certain period of time. The set temperature for the molten pool; Shape evaluation index: ， The set area of ​​the molten pool. Let be the area of ​​the molten pool. These represent the width and length of the molten pool, respectively. For floor height assessment index: ， The set height of the sedimentary layer, This refers to the height of the sedimentary layer in the molten pool region; Indicators of environmental disturbance assessment index: ， This represents the root mean square value of environmental vibration. To allow the maximum vibration acceleration; , , and Temperature assessment index Shape evaluation index Floor height assessment index Environmental disturbance assessment index The corresponding weight coefficients; Sb4. A quality assessment threshold is preset for the deposition quality assessment index. The deposition quality assessment index is compared with the quality assessment threshold. The first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted according to the comparison result.

2. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 1, characterized in that, Also includes: A movable support platform, on which the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are all mounted.

3. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 1, characterized in that, Both the first actuator and the second actuator are multi-joint robotic arms.

4. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 1, characterized in that, The collaborative control strategy includes the following steps: Sa1. Establish a global coordinate system and collect the execution end coordinates of the first executor and the second executor respectively, and record them as the first end coordinates and the second end coordinates; Sa2. Establish and calibrate the transformation relationship between the joint space of the first and second actuators and the global coordinate system; Sa3. Import the target component model into the global coordinate system, and generate a discrete point set for each deposition path based on the processing requirements. , where each discrete point All include coordinates Deposition rate Laser power matching value ; Sa4, based on the discrete point set of the deposition path. A first action command is assigned to the first actuator to perform a wire feeding-laser cladding action. Based on the first action command, a second action command is assigned to the second actuator to enable the second actuator to follow and assist the first actuator in performing the wire feeding-laser cladding action. The first action command and the second action command are both corrected by the action compensation amount. Sa5. Based on the first action instruction and the second action instruction, perform path pre-simulation and conflict detection on the first executor and the second executor, and adjust the first action instruction and the second action instruction based on the results of the path pre-simulation and conflict detection; Sa6. Establish a dual-actuator collaborative control model: The state equation is expressed as: ; The output equation is expressed as: ; in, Represents the variable The first-order derivative operation, ， This indicates the coordinates of the execution end of the first executor. This represents the joint angle state vector of the first actuator. This indicates the coordinates of the execution end of the second executor. Represents the joint angle state vectors of the second actuator; , These represent the velocity, acceleration, and angular velocity of the actuating end of the first actuator, respectively. These represent the velocity, acceleration, and angular velocity of the actuating end of the second actuator, respectively. Indicates the transpose operation; This represents the disturbance vector, which includes ground vibration disturbance and energy field disturbance; All are system matrices; Sa7. Based on the dual-actuator collaborative control model, the first and second actuators are collaboratively controlled to perform wire feeding-laser cladding actions.

5. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 4, characterized in that, The dual-actuator cooperative control model executes an obstacle avoidance cooperative strategy, which includes the following steps: Real-time acquisition of point cloud data of the surrounding environment of the first and second actuators; The point cloud data is simplified to generate an obstacle-occupied grid map; Based on the obstacle-occupied grid map, a time-dimensional cost function is introduced for dynamic obstacle avoidance path planning.

6. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing apparatus according to any one of claims 1-5, characterized in that, In the cooperative control strategy, the energy field interference-offset mapping model for establishing the energy field interference and the execution end offsets of the first and second actuators includes: Real-time ultrasonic power acquisition of the molten pool region and magnetic field strength The energy field interference-offset mapping model is established as follows: ， in, This indicates the offset caused by energy field disturbance. , and These represent the ultrasonic power-offset coefficient, magnetic field strength-offset coefficient, and ultrasonic-magnetic field coupling interference coefficient, respectively.

7. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 1, characterized in that, The quality assessment thresholds include a first interval that is non-overlapping and increases sequentially. Second interval Third interval and the fourth interval ; In response to the aforementioned sedimentation quality assessment index Belongs to the first interval If the operation is determined to be in an unqualified state, the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module will all stop operating. In response to the aforementioned sedimentation quality assessment index Belongs to the second interval If the operation is determined to be in an early warning state, the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted in the first amplitude and the data acquisition frequency is increased. In response to the aforementioned sedimentation quality assessment index Belonging to the third interval If the operation process is deemed to be in a qualified state, the key parameters of the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted to a second amplitude, wherein the first amplitude is greater than the second amplitude. In response to the aforementioned sedimentation quality assessment index Belonging to the fourth interval If the operation is determined to be in a high-quality state, no adjustments will be made to the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module.

8. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 7, characterized in that, In step Sb4, in response to the deposition quality assessment index Not belonging to the fourth interval The temperature assessment index Shape evaluation index Floor height assessment index Environmental disturbance assessment index The data is input into a preset classification model to obtain the cause of the sedimentation quality anomaly. Based on the cause of the sedimentation quality anomaly, one or more of the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module are adjusted.

9. The ultrasonic field-magnetic field coupled multi-energy field controlled mobile additive manufacturing device according to claim 8, characterized in that, In the classification model, a preset temperature assessment index is provided. Temperature assessment threshold Regarding the shape evaluation index Shape evaluation threshold Regarding the aforementioned floor height evaluation index Floor height assessment threshold And regarding the aforementioned environmental disturbance assessment index Environmental disturbance assessment threshold , If the temperature evaluation index is satisfied Less than the temperature assessment threshold And the shape evaluation index Not less than the shape evaluation threshold If the result is an abnormal deposition quality, the cause will be an abnormal temperature. If the shape evaluation index is satisfied Less than the shape evaluation threshold And the temperature assessment index Not less than the temperature assessment threshold The output then states that the cause of the abnormal deposition quality is abnormal melt pool flow. If the floor height evaluation index is satisfied Less than the floor height evaluation threshold And the temperature assessment index Not less than the temperature assessment threshold The shape evaluation index Not less than the shape evaluation threshold If the cause of the abnormal deposition quality is found to be a mismatch between the wire feed speed or laser power and the moving speed of the actuator, then the output will be... If the environmental disturbance assessment index is met Less than the environmental disturbance assessment threshold And the temperature assessment index Not less than the temperature assessment threshold The shape evaluation index Not less than the shape evaluation threshold The floor height evaluation index Not less than the floor height assessment threshold If so, the cause of the abnormal deposition quality is output as abnormal environmental vibration; When adjusting the first actuator, the second actuator, the ultrasonic module, and the magnetic field application module, the adjustment priority is ordered from high to low as follows: laser power. Wire feeding speed Ultrasonic power magnetic field strength Execution end movement speed .

Images