Prediction method for energy distribution of laser swing welding track

Abstract

The invention discloses a method for predicting energy distribution of a laser swing welding track, and belongs to the technical field of laser welding processes. The method comprises the following steps: defining welding process parameters; establishing a mathematical model of the instantaneous motion trail of the laser spot; constructing an energy source model based on Gaussian distribution; dividing the surface of the workpiece into grids through space-time discretization, and calculating the position of a light spot and the energy contribution of the light spot to the surrounding grids in each time step length; iteratively accumulating to obtain accumulated energy distribution; and finally, a visual energy distribution diagram is output, and welding parameters are optimized based on the diagram. According to the method, the energy distribution forms under different swing parameters can be quickly and accurately predicted, digital mapping of the process parameters and the energy distribution is realized, a scientific basis is provided for process development and optimization of laser swing welding, and the test cost and the test period are remarkably reduced.

Description

Technical Field

[0001] This invention relates to the field of laser welding technology, and more particularly to a method for predicting the energy distribution of a laser oscillating welding trajectory. Background Technology

[0002] Laser welding technology, with its advantages of high energy density, high precision, and high speed, has been widely used in modern manufacturing. However, the energy of traditional linear laser welding is distributed in a Gaussian pattern, with the energy being too concentrated in the center of the weld, which easily leads to various welding defects, such as weld center collapse, severe spatter, porosity, and poor tolerance for gaps.

[0003] To address these issues, laser oscillation welding technology has emerged. In laser oscillation welding, due to the complexity of the oscillation trajectory, the actual distribution of laser energy on the workpiece surface is difficult to obtain visually. An unreasonable trajectory can lead to welding defects. Different combinations of oscillation parameters, including different oscillation trajectories, frequencies, and amplitudes, will produce drastically different energy distribution patterns at the weld center. The uniformity, peak position, and magnitude of the energy distribution directly affect the flow behavior of the molten pool, the solidification process, and the final weld formation quality and mechanical properties. Current technologies lack a rapid, accurate, low-cost, and effective prediction method, forcing process development to rely on trial and error, resulting in long development cycles and high costs.

[0004] Existing technologies typically employ Gaussian or double-ellipsoidal heat sources to simulate the temperature or stress fields of the linear welding process. However, these existing technologies suffer from several drawbacks. First, they simplify the oscillation trajectory into a static, enlarged laser spot, completely ignoring the differences in residence time and energy superposition effects at different spatial locations during high-speed oscillation. Second, they are detached from actual control processes; their simulations are intended for theoretical analysis rather than directly guiding process parameter optimization. They fail to establish a complete technical loop from "trajectory parameter equations" to "energy distribution visualization" and then to "process parameter optimization decisions." Third, they are computationally complex and inefficient, often employing general-purpose finite element software for multiphysics coupling calculations. While accurate, this is extremely time-consuming and cannot meet the demands of rapid process development and testing in production settings. Existing solutions either sacrifice accuracy due to overly simplified models or efficiency due to excessive computational complexity, failing to provide a method for predicting the energy distribution of laser oscillation welding that balances accuracy, computational efficiency, and universality. Summary of the Invention

[0005] To address the aforementioned technical problems, a method for predicting the energy distribution of laser oscillating welding trajectories is provided. This method abandons complex finite element simulations and overly simplified analytical integrations, employing an efficient numerical calculation strategy that can accurately predict the actual trajectory motion diagram and two-dimensional energy density distribution diagram under any given process parameters within seconds. This method can quickly, accurately, and cost-effectively predict the cumulative energy distribution pattern on the workpiece surface under any given laser and oscillation parameters, transforming abstract process parameters into intuitive energy distribution images. This provides a scientific basis for process development, parameter optimization, and pre-control of welding quality, solving the problems of blindness and inefficiency in current laser oscillating welding process development.

[0006] The technical means employed in this invention are as follows: A method for predicting the energy distribution of a laser oscillating welding trajectory includes the following steps: Step 1: Define the welding process parameters, which include the total laser power P, beam waist radius r, welding speed V, laser oscillation trajectory type SM, oscillation amplitude A, and oscillation frequency f; Step 2: Establish a mathematical model of the instantaneous motion trajectory of the laser spot. Based on the welding motion parameters and laser welding oscillation parameters from Step 1, construct the kinematic equations (x(t), y(t)) of the laser spot center in the two-dimensional workpiece coordinate system as a function of time t. The kinematic equations are vector synthesis of the welding linear motion and the oscillation trajectory motion. Step 3: Establish an instantaneous energy source model. Assume that the energy of the laser beam has a two-dimensional Gaussian distribution inside the spot. Calculate the instantaneous power density at any point around the spot at any time t based on the center coordinates of the spot. Step 4: Calculate the cumulative energy distribution based on spatial and spatiotemporal discretization. Define the computational region on the workpiece surface and divide it into a two-dimensional mesh matrix G. Divide the total welding time into small time steps. ; Step 5: Perform iterative calculations and energy accumulation, initializing time t=0, and at each time step... The instantaneous position and energy increment of the light spot are calculated sequentially, and the cumulative energy of the mesh cells is updated until the total welding time T is reached. Step 6: Generate and output the energy distribution map, and visualize the two-dimensional grid matrix G to obtain a two-dimensional or three-dimensional energy density distribution map; Step 7: Optimize welding parameters based on the energy distribution map, identify risk areas based on the uniformity of energy distribution, adjust process parameters, and return to step 1 to recalculate until the energy distribution meets the requirements.

[0007] Furthermore, the laser oscillation trajectory type SM mentioned in step 1 includes clockwise circular oscillation (CW), counterclockwise circular oscillation (CCW), linear oscillation, figure-eight oscillation, infinity oscillation, and conventional laser welding mode (SLW).

[0008] Furthermore, the number of grid cells in the X direction of the two-dimensional grid matrix G mentioned in step 4... = 550, number of grid cells in the Y direction = 550, the resolution of the grid cells is adjusted according to the prediction accuracy and computation time requirements.

[0009] Furthermore, in step 4 s, to ensure that within a time step, the moving distance of the light spot is much smaller than the light spot radius r.

[0010] Furthermore, the expression for the instantaneous power density q(x,y,t) in step 3 is: .

[0011] Furthermore, the parameter adjustment rules in step 7 include: when the edge energy is insufficient, increasing the laser oscillation amplitude A or reducing the welding speed V; when the center energy is too high, reducing the laser power P, increasing the oscillation frequency f, or changing the laser oscillation mode.

[0012] Furthermore, the visualization process described in step 6 includes generating a pseudo-color two-dimensional map or a three-dimensional surface map, using different colors or heights to represent different energy density values.

[0013] Furthermore, the kinematic equations described in step 2 are applicable to swing trajectories described by any parametric equation, and are not limited to CW, CCW, Linear, Eight, Infinity, and SLW modes.

[0014] This invention provides a method for rapidly, accurately, and cost-effectively predicting the cumulative energy distribution pattern on a workpiece surface under arbitrary given laser and oscillation parameters. This method should be able to transform abstract laser process parameters into intuitive energy distribution images, providing a strong scientific basis for process development, parameter optimization, and pre-control of welding quality, thereby solving the problems of blindness and inefficiency in current laser oscillation welding process development.

[0015] Compared with the prior art, the present invention has the following advantages: 1. Compared to FEM, this method does not involve complex physics field solutions, but only performs numerical iteration and accumulation, resulting in extremely fast computation speed. For typical laser oscillating welding scenarios, prediction can be completed within seconds on a regular computer, achieving rapid "what you see is what you get" feedback; 2. Through precise kinematic modeling and discretized accumulation in time and space, this method can accurately express the non-uniform energy accumulation effect caused by changes in spot velocity (especially at trajectory turning points), and the prediction results are closer to physical reality.

[0016] 3. The framework of this method is highly flexible and can be easily adapted to any parametrically described swing trajectory. Only the kinematic model in step two needs to be replaced, which greatly expands its application range.

[0017] 4. Before actual welding, users can quickly try different parameter combinations using this method, observe their corresponding energy distribution diagrams, intuitively predict the welding effect, and thus select process parameters that can produce an ideal energy distribution (such as a saddle-shaped distribution with "high on both sides and low in the middle" to suppress center collapse), thereby achieving positive design and optimization of the welding process.

[0018] Comprehensive analysis shows that this prediction method achieves digital forward prediction of process parameters, energy distribution field, and weld quality. In practical applications, it allows for rapid optimization of oscillation parameters and trajectories through simulation before welding, replacing traditional trial-and-error methods and significantly reducing R&D costs and timelines. This method provides a crucial process design tool, especially for irregularly shaped welds or materials sensitive to heat input. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This represents the instantaneous trajectory of the laser spot.

[0021] Figure 2 The image shows the laser energy distribution for six laser oscillation modes (SLW, CW, CCW, Linear, Eight, Infinity).

[0022] Figure 3 The image shows the laser energy distribution for six laser oscillation modes (SLW, CW, CCW, Linear, Eight, Infinity).

[0023] Figure 4 Laser energy distribution diagrams for different laser oscillation frequencies (0Hz, 50Hz, 100Hz, 150Hz, 200Hz, 250Hz).

[0024] Figure 5Laser energy distribution diagrams for different laser oscillation frequencies (0Hz, 50Hz, 100Hz, 150Hz, 200Hz, 250Hz).

[0025] Figure 6 Laser energy distribution diagrams for different laser oscillation amplitudes (0mm, 0.4mm, 0.8mm, 1.2mm, 1.6mm, 2.0mm).

[0026] Figure 7 Laser energy distribution diagrams for different laser oscillation amplitudes (0mm, 0.4mm, 0.8mm, 1.2mm, 1.6mm, 2.0mm).

[0027] Figure 8 Table 1 shows the weld formation structure under different laser oscillation modes.

[0028] Figure 9 Table 1 shows the weld formation structure under different laser oscillation modes.

[0029] Figure 10 Table 1 shows the weld formation structure under different laser oscillation modes. Detailed Implementation

[0030] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. 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.

[0032] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0033] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0034] In the description of this invention, 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 generally based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this invention 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 invention. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0035] For ease of description, spatial relative terms such as "above," "over," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation besides the orientation of the device as described in the figures. For example, if the device in the figures is inverted, a device described as "above" or "above" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0036] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0037] This invention discloses a method for predicting the energy distribution of a laser oscillating welding trajectory, comprising the following steps: Step 1: Define the welding process parameters, which include the total laser power P, beam waist radius r, welding speed V, laser oscillation trajectory type SM, oscillation amplitude A, and oscillation frequency f; Step 2: Establish a mathematical model of the instantaneous motion trajectory of the laser spot. Based on the welding motion parameters and laser welding oscillation parameters from Step 1, construct the kinematic equations (x(t), y(t)) of the laser spot center in the two-dimensional workpiece coordinate system as a function of time t. The kinematic equations are vector synthesis of the welding linear motion and the oscillation trajectory motion. Step 3: Establish an instantaneous energy source model. Assume that the energy of the laser beam has a two-dimensional Gaussian distribution inside the spot. Calculate the instantaneous power density at any point around the spot at any time t based on the center coordinates of the spot. Step 4: Calculate the cumulative energy distribution based on spatial and spatiotemporal discretization. Define the computational region on the workpiece surface and divide it into a two-dimensional mesh matrix G. Divide the total welding time into small time steps. ; Step 5: Perform iterative calculations and energy accumulation, initializing time t=0, and at each time step... The instantaneous position and energy increment of the light spot are calculated sequentially, and the cumulative energy of the mesh cells is updated until the total welding time T is reached. Step 6: Generate and output the energy distribution map, and visualize the two-dimensional grid matrix G to obtain a two-dimensional or three-dimensional energy density distribution map; Step 7: Optimize welding parameters based on the energy distribution map, identify risk areas based on the uniformity of energy distribution, adjust process parameters, and return to step 1 to recalculate until the energy distribution meets the requirements.

[0038] Furthermore, the laser oscillation trajectory type SM mentioned in step 1 includes clockwise circular oscillation (CW), counterclockwise circular oscillation (CCW), linear oscillation, figure-eight oscillation, infinity oscillation, and conventional laser welding mode (SLW).

[0039] Furthermore, the number of grid cells in the X direction of the two-dimensional grid matrix G mentioned in step 4... = 550, number of grid cells in the Y direction = 550, the resolution of the grid cells is adjusted according to the prediction accuracy and computation time requirements.

[0040] Furthermore, in step 4 s, to ensure that within a time step, the moving distance of the light spot is much smaller than the light spot radius r.

[0041] Furthermore, the expression for the instantaneous power density q(x,y,t) in step 3 is: .

[0042] Furthermore, the parameter adjustment rules in step 7 include: when the edge energy is insufficient, increasing the laser oscillation amplitude A or reducing the welding speed V; when the center energy is too high, reducing the laser power P, increasing the oscillation frequency f, or changing the laser oscillation mode.

[0043] Furthermore, the visualization process described in step 6 includes generating a pseudo-color two-dimensional map or a three-dimensional surface map, using different colors or heights to represent different energy density values.

[0044] Furthermore, the kinematic equations described in step 2 are applicable to swing trajectories described by any parametric equation, and are not limited to CW, CCW, Linear, Eight, Infinity, and SLW modes.

[0045] Example 1 This invention discloses a method for predicting the energy distribution of a laser oscillating welding trajectory, comprising the following steps: Step 1: Definition of Welding Process Parameters. First, a set of clearly defined welding process parameters needs to be obtained as input for the calculation. These parameters mainly include: total laser power P (W), beam waist radius r (mm), usually assumed to be a Gaussian spot size, welding speed V (mm / min), laser oscillation trajectory type SM (CW, CCW, Linear, Eight, Infinity), oscillation amplitude A (mm), and oscillation frequency f (Hz). The five different laser beam oscillation modes are: clockwise circular oscillation (CW mode), counterclockwise circular oscillation (CCW mode), figure-eight oscillation (Eight mode), infinity oscillation (Infinity mode), and single laser welding (SLW mode).

[0046] Step 2: Mathematical modeling of the instantaneous motion trajectory of the laser spot. Based on the input welding motion parameters and laser welding oscillation parameters, establish the precise kinematic equations (x(t), y(t)) of the laser spot center changing with time t in the two-dimensional workpiece coordinate system. This is a vector synthesis process of velocity and displacement, that is, the superposition of welding linear motion and oscillation trajectory motion. For example, the kinematic models of the six modes can be represented as shown in (3-1) to (3-6).

[0047] SLW mode: (3-1) CW mode: (3-2) CCW mode: (3-3) Linear mode: (3-4) Eight Mode: (3-5) Infinity mode: (3-6) like Figure 1 As shown, where, The origin of the light spot path curve is taken as the welding start point. v The welding speed is defined as the welding direction along the positive X-axis, the Y-axis represents the molten pool width, A is the laser amplitude, and f is the frequency. t represents the initial phase angle and t represents the welding time.

[0048] This invention is not limited to the specific motion trajectories mentioned above, such as CW, CCW, Linear, Eight, and Infinity. It can establish a kinematic model for trajectories described by any parameterized equation. This step is fundamental to accurately describing the energy input path, ensuring that a specific laser beam trajectory is generated on each defined path.

[0049] Step 3: Establishing the instantaneous energy source model. It is assumed that the energy of the laser beam follows a two-dimensional Gaussian distribution within the laser spot, which is consistent with the physical reality of most single-mode fiber lasers. At any time t, with the center of the laser spot... Let O be the origin, and any point around it. instantaneous power density It can be represented as: (3-7) This two-dimensional Gaussian distribution model describes how, at any given instant, energy is distributed on the two-dimensional surface of the workpiece centered on the laser spot.

[0050] Step 4: Calculation of cumulative energy distribution based on spatial and spatiotemporal discretization. This step is the core innovation of this invention, as it efficiently simulates the accumulation process of energy in time and space using numerical methods.

[0051] Spatial discretization: Define a computational region on the workpiece surface, typically a rectangular region along the weld direction. Divide this region into a fine two-dimensional mesh matrix G, which can be used... Representation. Each grid cell. This represents a tiny area with an initial energy value of 0. The grid resolution determines the accuracy of the final predicted image and the computation time; it is generally selected as... Number of grids in direction = 550, select Number of grids in direction = 550.

[0052] Time discretization: the total time of the entire welding process (To ensure this total time covers multiple oscillation cycles) it is divided into a large number of tiny time steps. . The value of needs to be small enough, generally taking 100%. The value of s is used to ensure that the movement distance of the light spot within a time step is much smaller than the light spot radius r = 0.13 mm, thereby ensuring the accuracy of the calculation.

[0053] (5) Iterative calculation and energy accumulation. When performing iterative accumulation calculation, the initialization time is defined. =0. Enter the loop, for each time step The following steps are performed sequentially: calculate the instantaneous position of the light spot, calculate the energy increment, and update the accumulated energy.

[0054] Calculate the instantaneous position of the laser spot: Based on the mathematical modeling equation of the instantaneous motion trajectory of the laser spot in step (2), calculate the coordinates of the laser spot relative to the laser center at the current moment, i.e. The center coordinates of the laser spot are It can be done Calculate the center coordinates of the light spot in the x-direction by... Calculate the center coordinates of the light spot in the y-direction.

[0055] Calculate the energy increment: Based on the energy source model in step (3), calculate the energy increment for each affected grid cell in the grid matrix G at the current spot position. The power density contributed .

[0056] Update accumulated energy: calculate the power density Multiply by time step The energy increment within that time step is obtained. Then it is added to the accumulated energy value of the corresponding grid cell. ,in This represents the accumulated energy value of the corresponding new grid cell. This represents the energy value of the corresponding new grid cell before accumulation. This cycle is repeated until... Reaching the total welding time The entire welding process is completed, and at the same time, the cumulative energy distribution calculation is completed.

[0057] Step 6: Generation and output of the energy distribution map. After the iterative calculation is complete, the values ​​stored in the two-dimensional grid matrix G... This represents the energy distribution along the actual trajectory path during the entire welding process, showing the total cumulative energy density received by each tiny region. The matrix G is then visualized to generate a two-dimensional or three-dimensional surface plot. Different colors or heights in the plot represent different energy density values. This energy distribution prediction map visually displays the energy distribution characteristics in the weld area, such as the location of energy peaks, peak-valley differences, and the uniformity of distribution.

[0058] Specifically, based on common laser oscillation parameters, several typical laser energy distribution maps are predicted.

[0059] ① Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation frequency f=100Hz, and laser oscillation amplitude A=1.0mm, generate laser energy distribution maps for six laser oscillation modes (SLW, CW, CCW, Linear, Eight, Infinity), as follows. Figure 2 , Figure 3 As shown.

[0060] ② Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation amplitude A=1.0mm, and laser oscillation mode SM=Infinity, generate laser energy distribution maps for six laser oscillation frequencies (0Hz, 50Hz, 100Hz, 150Hz, 200Hz, 250Hz), as shown below. Figure 4 , 5 As shown.

[0061] ③ Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation frequency f=100Hz, and laser oscillation mode SM=Infinity, generate laser energy distribution maps for six laser oscillation amplitudes (0mm, 0.4mm, 0.8mm, 1.2mm, 1.6mm, 2.0mm), as shown below. Figure 6 , 7 As shown.

[0062] Step 7: Optimize the energy distribution map based on the energy distribution parameters calculated in Step 6, and optimize the welding parameters accordingly. By assessing the overall uniformity of the energy distribution, determine whether there are areas with energy density below the threshold (indicating a risk of incomplete fusion) and areas with energy density above the threshold (indicating a risk of overheating or undercut). If a risk area is found, adjust the process parameters according to the following rules: If insufficient edge energy is found, increase the laser oscillation amplitude A or decrease the welding speed V; if the center energy is found to be too high, decrease the laser power P, increase the oscillation frequency f, or change different laser oscillation modes to disperse the center energy. Use the adjusted parameters as new inputs, return to step (1), and recalculate the energy distribution state under the specified process parameters until the energy distribution meets the requirements. After multiple calculations using different process parameter model data, finally output the optimized welding process parameter combination that meets the requirements.

[0063] Step 8: Specifically, based on common laser oscillation parameters, welding tests are conducted using process parameter combinations of three predicted typical laser energy distribution diagrams.

[0064] ① Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation frequency f=100Hz, and laser oscillation amplitude A=1.0mm, welding tests were conducted for six laser oscillation modes (SLW, CW, CCW, Linear, Eight, Infinity). Table 1 shows the weld formation under different laser oscillation modes.

[0065] Table 1 Weld formation under different laser oscillation modes

[0066] ② Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation amplitude A=1.0mm, and laser oscillation mode SM=Infinity, welding tests were conducted at six laser oscillation frequencies (0Hz, 50Hz, 100Hz, 150Hz, 200Hz, 250Hz). Table 2 shows the weld formation under different laser oscillation frequencies.

[0067] Table 2 Weld formation at different laser oscillation frequencies

[0068] ③ Under the conditions of laser power P=5.5kW, welding speed V=25mm / s, beam waist radius r=0.13mm, laser oscillation frequency f=100Hz, and laser oscillation mode SM=Infinity, laser welding experiments were conducted with six laser oscillation amplitudes (0mm, 0.4mm, 0.8mm, 1.2mm, 1.6mm, 2.0mm). Table 3 shows the weld formation under different laser oscillation amplitudes.

[0069] Table 3 Weld formation under different laser oscillation amplitudes

[0070] Comparison of weld formation and laser energy distribution simulation results in Tables 1, 2, and 3, and... Figures 8-10 The results show that as the laser beam oscillation amplitude increases, the laser energy distribution changes from concentrated to dispersed on both sides. Simultaneously, the weld width increases, while the penetration depth decreases. With increasing laser oscillation frequency, welding spatter initially increases and then decreases, with energy concentration on both sides, leading to increased undercut on both sides of the weld surface. Among laser oscillation welding with different oscillation modes, linear oscillation shows energy concentration on both sides with a peak value, while other oscillation modes show a more uniform energy distribution on both sides, resulting in a smooth weld transition. Users can quickly try different combinations of laser oscillation welding parameters using this method before actual welding, observe their corresponding energy distribution diagrams, intuitively predict the welding effect, and thus select process parameters that produce an ideal energy distribution. Then, using this combination of process parameters for actual welding, users can achieve positive design and optimization of the welding process, improving the application and development of new products and materials.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting the energy distribution of a laser oscillating welding trajectory, characterized in that, Includes the following steps: Step 1: Define the welding process parameters, which include the total laser power P, beam waist radius r, welding speed V, laser oscillation trajectory type SM, oscillation amplitude A, and oscillation frequency f; Step 2: Establish a mathematical model of the instantaneous motion trajectory of the laser spot. Based on the welding motion parameters and laser welding oscillation parameters from Step 1, construct the kinematic equations (x(t), y(t)) of the laser spot center in the two-dimensional workpiece coordinate system as a function of time t. The kinematic equations are vector synthesis of the welding linear motion and the oscillation trajectory motion. Step 3: Establish an instantaneous energy source model. Assume that the energy of the laser beam has a two-dimensional Gaussian distribution inside the spot. Calculate the instantaneous power density at any point around the spot at any time t based on the center coordinates of the spot. Step 4: Calculate the cumulative energy distribution based on spatial and spatiotemporal discretization. Define the computational region on the workpiece surface and divide it into a two-dimensional mesh matrix G. Divide the total welding time into small time steps. ; Step 5: Perform iterative calculations and energy accumulation, initializing time t=0, and at each time step... The instantaneous position and energy increment of the light spot are calculated sequentially, and the cumulative energy of the mesh cells is updated until the total welding time T is reached. Step 6: Generate and output the energy distribution map, and visualize the two-dimensional grid matrix G to obtain a two-dimensional or three-dimensional energy density distribution map; Step 7: Optimize welding parameters based on the energy distribution map, identify risk areas based on the uniformity of energy distribution, adjust process parameters, and return to step 1 to recalculate until the energy distribution meets the requirements.

2. The prediction method according to claim 1, characterized in that, The laser oscillation trajectory type SM mentioned in step 1 includes clockwise circular oscillation (CW), counterclockwise circular oscillation (CCW), linear oscillation, figure-eight oscillation, infinity oscillation, and conventional laser welding mode (SLW).

3. The prediction method according to claim 1, characterized in that, The number of grid cells in the X direction of the two-dimensional grid matrix G mentioned in step 4 = 550, number of grid cells in the Y direction = 550, the resolution of the grid cells is adjusted according to the prediction accuracy and computation time requirements.

4. The prediction method according to claim 1, characterized in that, In step 4 s, to ensure that within a time step, the moving distance of the light spot is much smaller than the light spot radius r.

5. The prediction method according to claim 1, characterized in that, The expression for the instantaneous power density q(x,y,t) mentioned in step 3 is: .

6. The prediction method according to claim 1, characterized in that, The parameter adjustment rules in step 7 include: when the edge energy is insufficient, increase the laser oscillation amplitude A or reduce the welding speed V; when the center energy is too high, reduce the laser power P, increase the oscillation frequency f, or change the laser oscillation mode.

7. The prediction method according to claim 1, characterized in that, The visualization process described in step 6 includes generating a pseudo-color two-dimensional map or a three-dimensional surface map, using different colors or heights to represent different energy density values.

8. The prediction method according to claim 1, characterized in that, The kinematic equations described in step 2 are applicable to swing trajectories described by any parametric equation, and are not limited to CW, CCW, Linear, Eight, Infinity and SLW modes.

Images