Ultrasonic field assisted laser deposition system for metal parts of unmanned aerial vehicle

Abstract

The invention relates to the technical field of laser deposition control, in particular to an unmanned aerial vehicle metal part ultrasonic field auxiliary laser deposition system which comprises the following modules: a data acquisition module for acquiring a molten pool thermal field signal, a sound field signal and a laser scattering signal, and performing sampling, filtering and synchronous processing to obtain molten pool original data; the micro-flow digital twinning module is used for establishing a molten pool micro-flow digital twinning model according to the molten pool original data and simulating molten pool micro-flow behavior to obtain micro-flow prediction data; and the microflow ultrasonic regulation and control module is used for generating an ultrasonic pulse sequence according to the microflow prediction data and applying the ultrasonic pulse sequence to the molten pool to regulate and control the flow field. According to the invention, through the molten pool microflow digital twinning module and the microflow ultrasonic regulation and control module, real-time modeling and regulation and control of the molten pool microflow structure in the complex geometric part deposition process are realized, the problem that local vortexes, shear layer differences and flow field anomalies cannot be identified in real time in the traditional technology is solved, and the molten pool microflow evolution can be actively reconstructed.

Description

Technical Field

[0001] This invention relates to the field of laser deposition control technology, and in particular to an ultrasonic field-assisted laser deposition system for metal parts of unmanned aerial vehicles. Background Technology

[0002] Laser deposition systems for UAV metal parts primarily use laser beams to melt metal powder or wires, achieving layer-by-layer deposition and shaping on the surface of UAV metal parts. This is used to manufacture or repair metal parts with complex structures. The system is typically equipped with temperature sensors, optical sensors, and laser power control devices to monitor the molten pool state and adjust the laser power, thereby achieving precise deposition and geometric control of metal materials. It is suitable for the manufacturing and repair of aerospace, precision machinery, and high-performance components.

[0003] When depositing complex geometric parts, existing technologies can generate local eddies or shear layer differences inside the molten pool, leading to abnormal micropores and grain orientations, making it impossible to identify and control these microfluidic structures in real time. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides an ultrasonic field-assisted laser deposition system for metal parts of unmanned aerial vehicles, which aims to improve the problem that the microfluidic structure of the molten pool cannot be identified and controlled in real time during the deposition of complex geometric parts, resulting in abnormal micropores and grain orientation.

[0005] In a first aspect, the present invention provides the following technical solution: an ultrasonic field-assisted laser deposition system for metal parts of unmanned aerial vehicles (UAVs), comprising the following modules: The data acquisition module collects the molten pool thermal field signal, acoustic field signal, and laser scattering signal, and obtains the raw data of the molten pool through sampling, filtering, and synchronization processing. The microfluidic digital twin module establishes a microfluidic digital twin model of the molten pool based on the original data of the molten pool, and simulates the microfluidic behavior of the molten pool to obtain microfluidic prediction data; The microfluidic ultrasonic control module generates an ultrasonic pulse sequence based on microfluidic prediction data and applies it to the molten pool to control the flow field. The phase-change pulse modulation module, based on microfluidic prediction data and ultrasonic pulse sequences, adjusts the ultrasonic pulse sequence through local thermodynamic phase change calculations and generates a laser power modulation sequence. The heterogeneous interface collaboration module inputs the ultrasonic pulse sequence, laser power modulation sequence and heterogeneous interface parameters into the interface flow state prediction model to obtain the local ultrasonic pulse mode and laser scanning strategy. The control and scheduling module generates deposition control commands based on the local ultrasonic pulse pattern and laser scanning strategy, and performs laser deposition operations on the metal parts of the UAV.

[0006] By adopting the above technical solution, real-time modeling, prediction and active control of the microfluidic structure of the molten pool during the deposition of complex geometric parts are realized, thereby effectively intervening in local eddies and shear layer differences, and avoiding problems such as micropore formation and abnormal grain orientation.

[0007] Preferably, the sampling, filtering, and synchronization processing includes: The molten pool thermal field signal, acoustic field signal, and laser scattering signal were sampled separately using frequency division, with the sampling frequency divided into multiple frequency bands based on the characteristics of the signal source. Adaptive bandpass filtering is performed on the sampled signal, and combined with a time-frequency domain multi-scale filtering algorithm to achieve signal component separation; A synchronous time axis is established based on timestamps for the filtered multi-source signals, and the sampling phase is corrected by a dynamic time warping algorithm; The synchronized signals are uniformly mapped to a preset spatial coordinate system to form the original data of the molten pool.

[0008] Preferably, establishing a digital twin model of the molten pool microfluidics includes: Based on the raw data of the molten pool, parameters such as temperature field distribution, sound pressure distribution, and metal flow velocity distribution within the molten pool area are extracted. A three-dimensional microfluidic finite element simulation domain is constructed based on the extracted parameters, and thermal boundary conditions, acoustic boundary conditions, and flow boundary conditions are set in this simulation domain. A control model based on the coupling equations of fluid dynamics and acoustic flow is introduced in the simulation domain to characterize the transient microfluidic properties inside the molten pool. A microfluidic state evolution sequence is generated through a multi-step iterative solution algorithm, and a digital twin mapping relationship corresponding to the physical melt pool state is established based on the evolution sequence to form a melt pool microfluidic digital twin model.

[0009] Preferably, obtaining the microfluidic prediction data includes: The collected raw data of the molten pool is input into the microfluidic digital twin model; The temperature field boundary conditions and sound pressure boundary conditions in the model are updated in a time-varying manner based on the input data. Under the updated boundary conditions, the transient velocity field and temperature distribution within the molten pool region are calculated using the acoustic-thermal-fluid multiphysics coupling solution method. The calculated velocity field data is reconstructed over time and features are extracted to form microfluidic prediction data that reflects the microfluidic evolution characteristics of the molten pool.

[0010] Preferably, the generation of the ultrasonic pulse sequence includes: Import the microfluidic prediction data into the nonlinear modulation algorithm model; Based on the local velocity field and vortex structure characteristics of the microfluidic prediction data, the initial amplitude, frequency and pulse width of the ultrasonic pulse are set. The initial ultrasonic pulse parameters are iteratively optimized using a nonlinear modulation algorithm to obtain an ultrasonic pulse sequence that can match the predicted microflow behavior.

[0011] Preferably, adjusting the ultrasound pulse sequence includes: Microfluidic prediction data and ultrasonic pulse sequences are input into a local thermodynamic phase transition model; In the local thermodynamic phase transition model, the temperature gradient, latent heat of phase transition, and changes in the local molten solid interface in the micro-region of the molten pool are calculated. Based on the calculation results, determine the adjustment parameters for the amplitude and duration of the ultrasonic pulse in each local area; The adjusted parameters are applied to the original ultrasound pulse sequence to obtain the adjusted ultrasound pulse sequence.

[0012] Preferably, generating the laser power modulation sequence includes: Based on the calculation results of local thermodynamic phase transitions and the adjusted ultrasonic pulse sequence, the required laser power for each region of the molten pool is determined; A short-time pulse generation algorithm is used to distribute the laser power into a continuous pulse sequence to form a controllable laser power modulation mode, and the laser power modulation sequence is output.

[0013] Preferably, the parameters of the dissimilar material interface include: Interface geometric parameters are obtained by measuring the shape, roughness, and slope distribution of the material contact surface through 3D scanning or microscopic imaging. Interfacial thermal properties are obtained through experimental measurements or by consulting material handbooks, including thermal conductivity, specific heat capacity, melting point, and interfacial thermal resistance of each material. Interface acoustic parameters, such as acoustic impedance, sound velocity, and absorption coefficient, are obtained through acoustic testing or material databases. Interfacial chemical parameters, including material surface composition, oxide film thickness, and wettability, were determined using surface analysis methods. The parameters are integrated to form the parameters of the heterogeneous material interface.

[0014] Preferred interface flow prediction models include: A finite element mesh is established to divide the heterogeneous material interface region into multiple computational units; Microfluidic prediction data, ultrasonic pulse sequences, laser power modulation sequences, and heterogeneous interface parameters are used as model inputs to form boundary and initial conditions. A multiphysics coupling calculation method was used to simulate the local velocity, eddy current distribution and shear layer characteristics of the molten pool fluid in the heterogeneous material interface region. By using a local optimization algorithm, the interface flow state under different input conditions is analyzed, and local ultrasonic pulse patterns and laser scanning strategies for control are generated.

[0015] Preferably, the deposition control instructions include: The local ultrasound pulse mode and laser scanning strategy are transformed into a deposition path sequence, including laser power, scanning speed, scanning trajectory and pulse trigger timing parameters; The deposition path sequence was scheduled and optimized, including scanning order adjustment and time series sorting, to match the actual deposition layout of UAV metal parts; Generate standardized control command data formats to drive laser deposition equipment to perform operations.

[0016] The present invention has the following beneficial effects: 1. In this invention, the molten pool microfluidic digital twin module and the microfluidic ultrasonic control module realize real-time modeling and control of the molten pool microfluidic structure during the deposition of complex geometric parts. This solves the problem that traditional technologies cannot identify local eddies, shear layer differences and flow field anomalies in real time, and enables the molten pool microfluidic evolution to be actively reconstructed, thereby improving the deposition quality and reducing the risk of micropore and grain orientation anomalies.

[0017] 2. In this invention, the phase change pulse modulation module realizes the dynamic adjustment of ultrasonic pulse sequence and laser power based on local thermodynamic phase change model, which solves the problems of uneven transient phase change rate, easy formation of microcracks and grain coarsening when high-strength metals are deposited in local abrupt thickness change regions. It enables precise compensation of local phase change, ensures dynamic matching of molten pool temperature, flow rate and phase change rate during deposition, thereby improving the uniformity of material structure and overall mechanical properties.

[0018] 3. In this invention, through the heterogeneous material interface coordination module and the control scheduling module, the flow state of the molten pool at the heterogeneous material interface is predicted and the local ultrasonic pulse mode and laser scanning strategy are dynamically generated and scheduled for control. This solves the problems of large differences in molten pool flow and solidification rate, and easy generation of micropores and interface cracks during the deposition of heterogeneous materials such as titanium / aluminum. It enables the deposition path, laser power and ultrasonic action to achieve coordinated matching in the interface region, thereby improving the bonding quality of heterogeneous materials and enhancing the reliability of the interface. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of an ultrasonic field-assisted laser deposition system for UAV metal parts proposed in this invention. Figure 2 This is a flowchart of an ultrasonic field-assisted laser deposition system for metal parts of unmanned aerial vehicles (UAVs) proposed in this invention. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1: In a first embodiment of the present invention, an ultrasonic field-assisted laser deposition system for unmanned aerial vehicle (UAV) metal parts is provided, such as... Figures 1-2 As shown, it includes the following modules: The data acquisition module collects the molten pool thermal field signal, acoustic field signal, and laser scattering signal, and obtains the raw data of the molten pool through sampling, filtering, and synchronization processing. Furthermore, sampling, filtering, and synchronization processing includes: The molten pool thermal field signal, acoustic field signal, and laser scattering signal were sampled separately using frequency division, with the sampling frequency divided into multiple frequency bands based on the characteristics of the signal source. Adaptive bandpass filtering is performed on the sampled signal, and combined with a time-frequency domain multi-scale filtering algorithm to achieve signal component separation; A synchronous time axis is established based on timestamps for the filtered multi-source signals, and the sampling phase is corrected by a dynamic time warping algorithm; The synchronized signals are uniformly mapped to a preset spatial coordinate system to form the original data of the molten pool.

[0022] Specifically, the data acquisition module is used to acquire multi-source signals generated by the molten pool during laser deposition, including molten pool thermal field signals, acoustic field signals, and laser scattering signals. In the specific implementation process, these signals are continuously acquired to form raw data of the molten pool state. In the specific implementation process, the molten pool thermal field signal, acoustic field signal and laser scattering signal are sampled by frequency division. The sampling frequency is divided into different frequency bands according to the characteristics of the signal source to ensure that the dynamic changes of various signals can be completely captured. Sampling can be completed through optional sensor interface or digital acquisition device to obtain discrete signal sequence, which provides basic data for subsequent filtering and synchronization processing. An adaptive bandpass filter is applied to the sampled signal, and a time-frequency domain multi-scale filtering algorithm is used to separate the signal components. This processing allows for the separation of signal features across different frequency bands, extracting key information from the molten pool's thermal, acoustic, and scattering signals for subsequent microfluidic prediction and ultrasonic control. Optionally, for some key features, the following filtering formula can be used to represent signal reconstruction: in, Represents the original sampled signal. This represents the filtered signal. These are the filter coefficients. The filter order; A synchronized time axis is established for the filtered multi-source signals based on timestamps, and the sampling phase is corrected by a dynamic time warping algorithm; this ensures that different signal sources are accurately aligned in the time dimension, providing a unified time reference for the microfluidic digital twin model; The synchronized signal is mapped to a preset spatial coordinate system to form the original data of the molten pool. During the mapping process, the sensor installation position, laser scanning path and molten pool geometry can be considered. The discrete time signal is converted into a spatial representation through coordinate transformation or interpolation algorithm to realize the integration of three-dimensional information of the molten pool state. Through the above sampling, filtering, synchronization and spatial mapping process, the complete acquisition and processing of the molten pool thermal field, acoustic field and laser scattering signals are realized, providing reliable raw data input for subsequent microfluidic prediction, ultrasonic pulse control and laser power modulation, and ensuring the consistency and controllability of system operation.

[0023] The microfluidic digital twin module establishes a microfluidic digital twin model of the molten pool based on the original data of the molten pool, and simulates the microfluidic behavior of the molten pool to obtain microfluidic prediction data; Furthermore, establishing a digital twin model of the molten pool microfluidics includes: Based on the raw data of the molten pool, parameters such as temperature field distribution, sound pressure distribution, and metal flow velocity distribution within the molten pool area are extracted. A three-dimensional microfluidic finite element simulation domain is constructed based on the extracted parameters, and thermal boundary conditions, acoustic boundary conditions, and flow boundary conditions are set in this simulation domain. A control model based on the coupling equations of fluid dynamics and acoustic flow is introduced in the simulation domain to characterize the transient microfluidic properties inside the molten pool. A microfluidic state evolution sequence is generated through a multi-step iterative solution algorithm, and a digital twin mapping relationship corresponding to the physical melt pool state is established based on the evolution sequence to form a melt pool microfluidic digital twin model.

[0024] Furthermore, obtaining microfluidic prediction data includes: The collected raw data of the molten pool is input into the microfluidic digital twin model; The temperature field boundary conditions and sound pressure boundary conditions in the model are updated in a time-varying manner based on the input data. Under the updated boundary conditions, the transient velocity field and temperature distribution within the molten pool region are calculated using the acoustic-thermal-fluid multiphysics coupling solution method. The calculated velocity field data is reconstructed over time and features are extracted to form microfluidic prediction data that reflects the microfluidic evolution characteristics of the molten pool.

[0025] Specifically, the microfluidic digital twin module is used to build a microfluidic digital twin model of the molten pool based on the original data of the molten pool, and further simulate the microfluidic behavior inside the molten pool to obtain microfluidic prediction data for control. In the specific implementation process, the temperature field distribution within the molten pool area is first extracted based on the collected raw data of the molten pool. Sound pressure distribution and metal flow velocity distribution Parameters; where Represents the spatial coordinates of the molten pool. Indicates time, Indicates local temperature. Indicates sound field pressure, These parameters represent the metal flow velocity vector; they reflect the transient thermo-acoustic-fluid coupling characteristics inside the molten pool, providing initial boundary conditions and constraints for the construction of the digital twin model. A three-dimensional microfluidic finite element simulation domain is constructed based on the extracted temperature, sound pressure, and flow velocity parameters. Thermal boundary conditions, acoustic boundary conditions, and flow boundary conditions are set in this simulation domain. The thermal boundary conditions are used to describe the thermal conduction constraints of the molten pool surface and surrounding materials, the acoustic boundary conditions are used to describe the acoustic impedance characteristics of the ultrasonic application and the molten pool interface, and the flow boundary conditions are used to constrain the flow mode and boundary layer characteristics of the molten metal liquid. The discrete partitioning of the simulation domain can be carried out using the finite element method or the finite volume method to ensure the stability of the numerical solution of the boundary conditions and internal control equations. A control model based on the coupled equations of fluid dynamics and acoustic flow is introduced into the simulation domain; this model can be expressed as: in, Indicates the density of a molten metal. Indicates the dynamic viscosity coefficient. This refers to the acoustic fluid force induced by ultrasound. Indicates the thermal diffusivity. The heat source term represents the laser input; this model is used to characterize the transient microfluidic properties and thermo-acoustic-fluid interactions within the molten pool. Microfluidic state evolution sequences are generated using a multi-step iterative solution algorithm. In each iteration, the boundary conditions of the control model are updated based on the local temperature, sound pressure and flow velocity calculated in the previous step, and the flow equation and heat conduction equation are solved again. A digital twin mapping relationship is established on the basis of the evolution sequence to correspond the transient microfluidic state calculated in the simulation domain with the actual physical molten pool state, forming a molten pool microfluidic digital twin model that can be used for prediction and control. The collected raw data of the molten pool is input into the digital twin model, and the temperature field boundary conditions and sound pressure boundary conditions in the model are updated in a time-varying manner based on the input data; the updated boundary conditions are used to calculate the transient velocity field within the molten pool region. With temperature distribution The time evolution sequence of microflow behavior inside the molten pool can be obtained by using the acoustic-thermal-fluid multiphysics coupling solution method. The calculated velocity field data is reconstructed over time and features are extracted to form microfluidic prediction data. This predicted data can reflect the microfluidic evolution characteristics of the molten pool, providing input information for subsequent ultrasonic pulse modulation, laser power modulation, and deposition path optimization. Through the above process, the microfluidic digital twin module can achieve high-fidelity simulation and prediction of molten pool microfluidics, ensuring a stable mapping relationship between the digital twin model and the actual molten pool behavior, and providing basic data support for precise microfluidic control during UAV laser deposition.

[0026] The microfluidic ultrasonic control module generates an ultrasonic pulse sequence based on microfluidic prediction data and applies it to the molten pool to control the flow field. Furthermore, generating the ultrasound pulse sequence includes: Import the microfluidic prediction data into the nonlinear modulation algorithm model; Based on the local velocity field and vortex structure characteristics of the microfluidic prediction data, the initial amplitude, frequency and pulse width of the ultrasonic pulse are set. The initial ultrasonic pulse parameters are iteratively optimized using a nonlinear modulation algorithm to obtain an ultrasonic pulse sequence that can match the predicted microflow behavior.

[0027] Specifically, the microfluidic ultrasonic control module is used to generate an ultrasonic pulse sequence based on microfluidic prediction data and apply the generated ultrasonic pulses to the molten pool to control the flow field inside the molten pool. In the specific implementation process, the microfluidic prediction data output by the microfluidic digital twin module is first... and local vortex structure characteristics Input the nonlinear modulation algorithm model; where, This represents the predicted local transient velocity vector. The local vortex intensity is used to reflect the rotation and shear characteristics of the molten pool microfluidic flow. The purpose of this step is to map the microfluidic characteristics to a controllable ultrasonic excitation parameter space using a nonlinear modulation model. Based on the input microfluidic prediction data and vortex characteristics, the initial parameters of the ultrasonic pulse sequence are set, including amplitude. ,frequency and pulse width These initial parameters can be initially matched based on the distribution of the local velocity field, vortex intensity, and flow field gradient information to ensure that the initial influence direction and intensity of the ultrasonic pulse on the molten pool microfluidic are consistent with the predicted microfluidic characteristics. The initial ultrasonic pulse parameters are imported into a nonlinear modulation algorithm for iterative optimization; the nonlinear modulation algorithm can be described by the following formula: in, They represent the first The ultrasonic amplitude, frequency, and pulse width are iterated step by step. Indicates the first Flow rate deviation in each iteration Indicates the deviation in vortex intensity. The step size coefficient is adjusted to control the parameter iteration amplitude; the iteration process continues until the ultrasonic pulse parameter sequence and the microfluidic prediction behavior reach the preset matching condition; Optimized ultrasound pulse sequence The pulses are mapped to the physical location of the molten pool and applied to the molten pool by a microfluidic ultrasonic control device. During the application process, the spatial distribution and temporal triggering sequence of the pulses are executed according to the iterative optimization results to achieve dynamic control of the local flow field of the molten pool. Through the above process, the microfluidic ultrasonic control module can establish a direct correlation between microfluidic prediction data and ultrasonic pulse sequence, enabling ultrasonic excitation to form controllable flow field disturbances inside the molten pool. This provides accurate input information for subsequent laser power modulation and deposition path optimization, and ensures that the microfluidic behavior of the molten pool is consistent with the expected digital twin model.

[0028] The phase-change pulse modulation module, based on microfluidic prediction data and ultrasonic pulse sequences, adjusts the ultrasonic pulse sequence through local thermodynamic phase change calculations and generates a laser power modulation sequence. Furthermore, adjusting the ultrasound pulse sequence includes: Microfluidic prediction data and ultrasonic pulse sequences are input into a local thermodynamic phase transition model; In the local thermodynamic phase transition model, the temperature gradient, latent heat of phase transition, and changes in the local molten solid interface in the micro-region of the molten pool are calculated. Based on the calculation results, determine the adjustment parameters for the amplitude and duration of the ultrasonic pulse in each local area; The adjusted parameters are applied to the original ultrasound pulse sequence to obtain the adjusted ultrasound pulse sequence.

[0029] Furthermore, generating the laser power modulation sequence includes: Based on the calculation results of local thermodynamic phase transitions and the adjusted ultrasonic pulse sequence, the required laser power for each region of the molten pool is determined; A short-time pulse generation algorithm is used to distribute laser power into a continuous pulse sequence to form a controllable laser power modulation mode, and the laser power modulation sequence is output.

[0030] Specifically, the phase change pulse modulation module is used to adjust the ultrasonic pulse sequence based on microfluidic prediction data and ultrasonic pulse sequence through local thermodynamic phase change calculation, and generate a corresponding laser power modulation sequence to achieve dynamic control of the microscopic thermal-fluid-phase change state of the molten pool. In the specific implementation process, microfluidic prediction data will be used. The ultrasonic pulse sequence output by the microfluidic ultrasonic control module Input a local thermodynamic phase transition model; this model is used to simulate heat conduction, latent heat absorption / release during phase transition, and local fusion-solid interface motion behavior within a micro-region of the molten pool; wherein, the temperature field... Satisfies the energy conservation equation: In the formula, For material density, For specific heat capacity, Thermal conductivity, For the power density of the laser input heat source, The ultrasonic pulse power is densely distributed. For latent heat of phase transition, The solid fraction is represented by this equation, which is used to calculate the temperature distribution and phase transition state of each micro-region of the molten pool over time. The temperature gradient of each micro-region was calculated using a local thermodynamic phase transition model. Phase change latent heat absorption / release and the displacement of the solidification interface Based on the calculation results, determine the amplitude correction amount of the ultrasonic pulse in each micro-region. and adjustment of action time The adjustment parameter is applied to the original ultrasound pulse sequence to generate the adjusted ultrasound pulse sequence. ; Based on the calculation results of local thermodynamic phase transitions and the adjusted ultrasonic pulse sequence, the required laser power for each micro-region of the molten pool was further determined. The continuous laser power signal is discretized into a controllable pulse sequence using a short-time pulse generation algorithm. And ensure that the power amplitude, duration and triggering time of each pulse match the local thermodynamic state and microfluidic control requirements; the generated laser power modulation sequence serves as the input to the laser emission control device, realizing precise control of the local thermal-fluid-phase transition state of the molten pool; Through the above process, the phase change pulse modulation module can closely integrate microfluidic prediction data with ultrasonic pulse sequences and local thermodynamic phase change states, thereby achieving dynamic adjustment of the microscopic phase change and flow field inside the molten pool. This provides precise input for laser power pulse generation and ensures that the molten pool can evolve as expected under the coupling effect of multiple physical fields.

[0031] The heterogeneous interface collaboration module inputs the ultrasonic pulse sequence, laser power modulation sequence and heterogeneous interface parameters into the interface flow state prediction model to obtain the local ultrasonic pulse mode and laser scanning strategy. Furthermore, the parameters of the dissimilar material interface include: Interface geometric parameters are obtained by measuring the shape, roughness, and slope distribution of the material contact surface through 3D scanning or microscopic imaging. Interfacial thermal properties are obtained through experimental measurements or by consulting material handbooks, including thermal conductivity, specific heat capacity, melting point, and interfacial thermal resistance of each material. Interface acoustic parameters, such as acoustic impedance, sound velocity, and absorption coefficient, are obtained through acoustic testing or material databases. Interfacial chemical parameters, including material surface composition, oxide film thickness, and wettability, were determined using surface analysis methods. The parameters are integrated to form the parameters of the heterogeneous material interface.

[0032] Furthermore, the interface flow prediction model includes: A finite element mesh is established to divide the heterogeneous material interface region into multiple computational units; Microfluidic prediction data, ultrasonic pulse sequences, laser power modulation sequences, and heterogeneous interface parameters are used as model inputs to form boundary and initial conditions. A multiphysics coupling calculation method was used to simulate the local velocity, eddy current distribution and shear layer characteristics of the molten pool fluid in the heterogeneous material interface region. By using a local optimization algorithm, the interface flow state under different input conditions is analyzed, and local ultrasonic pulse patterns and laser scanning strategies for control are generated.

[0033] Specifically, the heterogeneous interface collaboration module is used to input the ultrasonic pulse sequence, laser power modulation sequence and heterogeneous interface parameters into the interface flow state prediction model to obtain the local ultrasonic pulse mode and laser scanning strategy, thereby achieving fine control of the molten pool flow state at the heterogeneous interface. In the specific implementation process, the geometric parameters of the heterogeneous material interface, including the contact surface shape, roughness, and slope distribution, are obtained through 3D scanning or microscopic imaging. Interfacial thermophysical parameters, such as thermal conductivity, specific heat capacity, melting point, and interfacial thermal resistance, are obtained through experimental measurement or by consulting material handbooks. Simultaneously, interfacial acoustic parameters, such as acoustic impedance, sound velocity, and absorption coefficient, are obtained through acoustic testing or material databases. Furthermore, interfacial chemical parameters, including surface composition, oxide film thickness, and wettability, are determined using surface analysis methods. All of these parameters are integrated to form complete heterogeneous material interface parameters, which are used for interfacial flow prediction. A finite element mesh was established to divide the dissimilar material interface region into multiple computational cells to accurately simulate the local behavior of the molten pool fluid at the interface. Microfluidic prediction data, ultrasonic pulse sequences, laser power modulation sequences, and dissimilar material interface parameters were input into the model as boundary and initial conditions to describe the thermal-fluid-acoustic multiphysics state within the interface region. The velocity field of the fluid in the dissimilar material interface region was also analyzed. With vortex field Satisfying the incompressible Navier-Stokes equations and the heat flux coupling equations: In the formula, For material density, For dynamic viscosity, For pressure field, The volume force under the action of ultrasound. For interfacial surface tension, For local temperature fields, Thermal conductivity, and These are the power densities of the laser and ultrasonic input heat sources, respectively. A multiphysics coupled computational method was used to simulate the local flow velocity, eddy current distribution, and shear layer characteristics of the molten pool at the dissimilar material interface. A local optimization algorithm was employed to analyze the interface flow regime changes under different ultrasonic pulse sequences and laser power modulation strategies, yielding a local ultrasonic pulse mode for control. and laser scanning strategy This strategy can be used to guide the laser scanning path and adjust the ultrasonic pulse action to achieve coordinated control of the molten pool flow field and thermal field in the dissimilar material interface region. Through the above process, the heterogeneous interface collaborative module can closely integrate the microfluidic prediction results, ultrasonic control signals, and laser power modulation information with the multi-physical properties of the heterogeneous interface, realize the fine adjustment of the local flow state at the interface, and provide a precise control basis for subsequent laser scanning and ultrasonic action, thereby accurately controlling the flow and heat distribution of the molten pool at the heterogeneous interface under the coupling effect of multi-physical fields.

[0034] The control and scheduling module generates deposition control commands based on the local ultrasonic pulse pattern and laser scanning strategy, and performs laser deposition operations on the metal parts of the UAV.

[0035] Furthermore, the generation of deposition control instructions includes: The local ultrasound pulse mode and laser scanning strategy are transformed into a deposition path sequence, including laser power, scanning speed, scanning trajectory and pulse trigger timing parameters; The deposition path sequence was scheduled and optimized, including scanning order adjustment and time series sorting, to match the actual deposition layout of UAV metal parts; Generate standardized control command data formats to drive laser deposition equipment to perform operations.

[0036] Specifically, the control and scheduling module is used to generate deposition control commands based on the local ultrasonic pulse pattern and laser scanning strategy, and to perform precise laser deposition operations on the surface of the UAV's metal parts; Local ultrasound pulse mode With laser scanning strategy The process is transformed into a deposition path sequence, which includes parameters such as laser power, scanning speed, scanning trajectory, and pulse trigger timing. These parameters describe the power input and scanning motion of each micro-region during laser deposition. During the generation of the path sequence, the aforementioned microfluidic prediction data and phase transition control results are combined to ensure that the deposition path matches the local thermal-fluid-acoustic field conditions, thereby achieving precise control over the microfluidic state and deposition morphology of the molten pool. The generated deposition path sequence is scheduled and optimized, including scanning order adjustment and time series sorting, to ensure that the deposition paths are reasonably distributed on the surface of UAV metal parts, avoiding path overlap or omissions, and ensuring that the deposition layout is consistent with the geometry and functional area requirements of the parts. Path smoothing algorithms and time constraint algorithms can be used during the scheduling optimization process to control the laser scanning speed. With power Continuous processing is implemented to ensure a smooth deposition process that is synchronized with the actual operation of the UAV; The optimized deposition path sequence is converted into a standardized control command data format, including laser control commands, ultrasonic pulse control signals, and scanning platform motion commands. The control commands can interact with the laser deposition equipment and UAV motion platform in real time via a digital communication interface to achieve precise driving. At the same time, a feedback acquisition module can be optionally introduced to monitor the actual deposition state and fine-tune the subsequent path sequence based on the monitoring data to further ensure deposition consistency and accuracy. Through the above process, the control and scheduling module can effectively convert local ultrasonic pulse modes and laser scanning strategies into executable deposition control commands, realize the coordinated control of laser deposition on UAV metal parts, and make the laser deposition process highly matched with the microfluidics, thermal field and phase transformation characteristics of the molten pool, thereby providing an operable technical foundation for high-precision metal additive manufacturing.

[0037] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An ultrasonic field-assisted laser deposition system for metal parts of unmanned aerial vehicles (UAVs), characterized in that, Includes the following modules: The data acquisition module collects the molten pool thermal field signal, acoustic field signal, and laser scattering signal, and obtains the raw data of the molten pool through sampling, filtering, and synchronization processing. The microfluidic digital twin module establishes a microfluidic digital twin model of the molten pool based on the original data of the molten pool, and simulates the microfluidic behavior of the molten pool to obtain microfluidic prediction data; The microfluidic ultrasonic control module generates an ultrasonic pulse sequence based on microfluidic prediction data and applies it to the molten pool to control the flow field. The phase change pulse modulation module, based on microfluidic prediction data and ultrasonic pulse sequences, adjusts the ultrasonic pulse sequence through local thermodynamic phase change calculations and generates a laser power modulation sequence. The heterogeneous interface collaboration module inputs the ultrasonic pulse sequence, laser power modulation sequence and heterogeneous interface parameters into the interface flow state prediction model to obtain the local ultrasonic pulse mode and laser scanning strategy. The control and scheduling module generates deposition control commands based on the local ultrasonic pulse pattern and laser scanning strategy, and performs laser deposition operations on the metal parts of the UAV.

2. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The sampling, filtering, and synchronization processing includes: The molten pool thermal field signal, acoustic field signal, and laser scattering signal were sampled separately using frequency division, with the sampling frequency divided into multiple frequency bands based on the characteristics of the signal source. Adaptive bandpass filtering is performed on the sampled signal, and combined with a time-frequency domain multi-scale filtering algorithm to achieve signal component separation; A synchronous time axis is established based on timestamps for the filtered multi-source signals, and the sampling phase is corrected by a dynamic time warping algorithm; The synchronized signals are uniformly mapped to a preset spatial coordinate system to form the original data of the molten pool.

3. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, Establishing a digital twin model of the molten pool microfluidics includes: Based on the raw data of the molten pool, parameters such as temperature field distribution, sound pressure distribution, and metal flow velocity distribution within the molten pool area are extracted. A three-dimensional microfluidic finite element simulation domain is constructed based on the extracted parameters, and thermal boundary conditions, acoustic boundary conditions, and flow boundary conditions are set in this simulation domain. A control model based on the coupling equations of fluid dynamics and acoustic flow is introduced in the simulation domain to characterize the transient microfluidic properties inside the molten pool. A microfluidic state evolution sequence is generated through a multi-step iterative solution algorithm, and a digital twin mapping relationship corresponding to the physical melt pool state is established based on the evolution sequence to form a melt pool microfluidic digital twin model.

4. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The obtained microfluidic prediction data includes: The collected raw data of the molten pool is input into the microfluidic digital twin model; The temperature field boundary conditions and sound pressure boundary conditions in the model are updated in a time-varying manner based on the input data. Under the updated boundary conditions, the transient velocity field and temperature distribution within the molten pool region are calculated using the acoustic-thermal-fluid multiphysics coupling solution method. The calculated velocity field data is reconstructed over time and features are extracted to form microfluidic prediction data that reflects the microfluidic evolution characteristics of the molten pool.

5. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The generated ultrasound pulse sequence includes: Import the microfluidic prediction data into the nonlinear modulation algorithm model; Based on the local velocity field and vortex structure characteristics of the microfluidic prediction data, the initial amplitude, frequency and pulse width of the ultrasonic pulse are set. The initial ultrasonic pulse parameters are iteratively optimized using a nonlinear modulation algorithm to obtain an ultrasonic pulse sequence that can match the predicted microflow behavior.

6. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, Adjusting the ultrasound pulse sequence includes: Microfluidic prediction data and ultrasonic pulse sequences are input into a local thermodynamic phase transition model; In the local thermodynamic phase transition model, the temperature gradient, latent heat of phase transition, and changes in the local molten solid interface in the micro-region of the molten pool are calculated. Based on the calculation results, determine the adjustment parameters for the amplitude and duration of the ultrasonic pulse in each local area; The adjusted parameters are applied to the original ultrasound pulse sequence to obtain the adjusted ultrasound pulse sequence.

7. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The generation of the laser power modulation sequence includes: Based on the calculation results of local thermodynamic phase transitions and the adjusted ultrasonic pulse sequence, the required laser power for each region of the molten pool is determined; A short-time pulse generation algorithm is used to distribute the laser power into a continuous pulse sequence to form a controllable laser power modulation mode, and the laser power modulation sequence is output.

8. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The parameters of the dissimilar material interface include: Interface geometric parameters are obtained by measuring the shape, roughness, and slope distribution of the material contact surface through 3D scanning or microscopic imaging. Interfacial thermal properties are obtained through experimental measurements or by consulting material handbooks, including thermal conductivity, specific heat capacity, melting point, and interfacial thermal resistance of each material. Interface acoustic parameters, such as acoustic impedance, sound velocity, and absorption coefficient, are obtained through acoustic testing or material databases. Interfacial chemical parameters, including material surface composition, oxide film thickness, and wettability, were determined using surface analysis methods. The parameters are integrated to form the parameters of the heterogeneous material interface.

9. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, Interface flow prediction models include: A finite element mesh is established to divide the heterogeneous material interface region into multiple computational units; Microfluidic prediction data, ultrasonic pulse sequences, laser power modulation sequences, and heterogeneous interface parameters are used as model inputs to form boundary and initial conditions. A multiphysics coupling calculation method was used to simulate the local velocity, eddy current distribution and shear layer characteristics of the molten pool fluid in the heterogeneous material interface region. By using a local optimization algorithm, the interface flow state under different input conditions is analyzed, and local ultrasonic pulse patterns and laser scanning strategies for control are generated.

10. The ultrasonic field-assisted laser deposition system for UAV metal parts according to claim 1, characterized in that, The generated deposition control instructions include: The local ultrasound pulse mode and laser scanning strategy are transformed into a deposition path sequence, including laser power, scanning speed, scanning trajectory and pulse trigger timing parameters; The deposition path sequence was scheduled and optimized, including scanning order adjustment and time series sorting, to match the actual deposition layout of UAV metal parts; Generate standardized control command data formats to drive laser deposition equipment to perform operations.

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