Robot spraying track optimization method and system for liquid cooling plate

Abstract

The invention relates to the technical field of robot spraying, in particular to a robot spraying track optimization method and system for a liquid cooling plate. The method comprises the following steps: acquiring a cross section contour height set of the surface of the liquid cooling plate by using a line laser contour sensor; determining a first-order morphology slope and a second-order morphology curvature corresponding to each preset track center line through differential processing; then, in combination with a preset basic geometric compensation coefficient, a tension migration gain coefficient and a sensitivity response coefficient, calculating to obtain a surface topography coupling compensation index reflecting the paint migration risk and the projection expansion effect; based on a product relationship between the index and a preset reference plane line spacing, adaptively determining a dynamic line spacing of a next track; and finally, the robot is driven to execute variable-pitch spraying operation based on the dynamic line spacing. According to the scheme, the film thickness deficiency is compensated by increasing the physical overlapping rate, and the uniformity of the complex topological surface coating is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of robotic spraying technology, and more particularly to a method and system for optimizing robotic spraying trajectories for liquid-cooled plates. Background Technology

[0002] In the manufacturing process of thermal management systems for power batteries in new energy vehicles, the liquid cooling plate, as a core heat dissipation component, directly determines the heat exchange efficiency and insulation reliability of the battery pack due to its surface quality. To ensure the corrosion resistance of the liquid cooling plate under extreme operating conditions, a polymer coating is typically applied to its complex flow channel surface. Currently, the industry mainly relies on offline ultrasonic thickness measurement or cross-sectional sampling to detect coating thickness. While these methods offer high measurement accuracy, the equipment is expensive and cannot be run in real-time on the production line, making it difficult to meet the online quality control requirements of large-scale automated spraying.

[0003] To improve production efficiency, current automated spraying operations generally employ industrial robots equipped with automatic spray guns for reciprocating scanning. Conventional trajectory planning schemes typically assume the liquid cooling plate surface is an ideally flat surface and set a fixed row spacing for spraying. However, the surface of the liquid cooling plate has numerous serpentine flow channels and protruding structures, resulting in significant morphological variations. In actual operation, when the spray gun sweeps across the slope of the flow channel sidewalls, the amount of paint deposited per unit area is diluted due to the increased projected area caused by the tilt of the substrate surface, leading to a thinner coating. A more serious problem arises at the ridges or rounded corners of the flow channels. Driven by liquid surface tension, the wet paint spontaneously migrates from the high-curvature apex to the low-curvature flat area. This physical migration further exacerbates film thickness loss at the rounded corners.

[0004] Existing trajectory planning technologies cannot adjust spraying parameters in real time based on the microscopic morphology of the surface. Due to the lack of consideration for the effects of slope and curvature, the preset spraying parameters do not match the actual deposition requirements when dealing with complex flow channels. This is the physical root cause of thin coatings, exposed substrate, and even corrosion failure at the flow channel edges. Therefore, how to achieve adaptive optimization of the spraying trajectory for complex morphologies of liquid cooling plates under low-cost conditions is a pressing technical problem that needs to be solved to improve the spraying quality of liquid cooling plates. Summary of the Invention

[0005] To address the issue of uneven coating thickness in the flow channel region of liquid cooling plates due to complex surface morphology, this invention provides a method and system for optimizing the robotic spraying trajectory for liquid cooling plates.

[0006] In a first aspect, the present invention provides a method for optimizing the robotic spraying trajectory for liquid-cooled plates, employing the following technical solution: A method for optimizing the robotic spraying trajectory for liquid-cooled plates includes the following steps: A line laser profile sensor is used to sample the surface of the liquid cooling plate to be sprayed, and a set of cross-sectional profile heights characterizing the surface morphology is obtained. The cross-sectional profile height set is processed to obtain the first-order topography slope and second-order topography curvature corresponding to each preset trajectory centerline. Based on the preset basic geometric compensation coefficient, tension migration gain coefficient and sensitivity response coefficient, the first-order morphology slope and the second-order morphology curvature are weighted and fused to obtain a surface morphology coupling compensation index that reflects the coating migration risk and projection unfolding effect. The dynamic line spacing of the next trajectory is determined based on the product of the surface topography coupling compensation index and the preset reference plane line spacing, wherein the dynamic line spacing of the next trajectory decreases as the first-order topography slope or the second-order topography curvature increases. The execution coordinate vector of the next trajectory is generated based on the dynamic line spacing of the next trajectory, and the robot is driven to perform variable pitch spraying to compensate for the coating thinning defect caused by the coupling of geometric projection effect and surface tension migration effect in the flow channel corner area of ​​the liquid cooling plate surface.

[0007] This invention introduces slope and curvature as compensation indicators to achieve physical linkage between the spraying trajectory and the surface morphology, effectively solving the problem of film thickness deficiency at complex curved surfaces.

[0008] Preferably, the calculation of the first-order topographic slope satisfies the following relationship:

[0009] In the formula, For the first The first-order topographic slope corresponding to the center line of the preset trajectory; This is the preset total number of sampling points; For sampling point index; For the first The first preset trajectory The contour height of each sampling point; For the first The first preset trajectory The contour height of each sampling point; This is the preset horizontal sampling step size; This is the preset zero-prevention parameter.

[0010] This invention transforms complex surface features into quantifiable geometric features by calculating the height difference between discrete points, providing a data foundation for subsequent accurate compensation.

[0011] Preferably, the calculation of the second-order topographic curvature satisfies the following relationship:

[0012] In the formula, , and The first The first preset trajectory The, the The and the first The contour height value of the sampling point, Indicates the lateral sampling step size. Indicates the number of sampling points. For the zero-prevention parameter, For the first The second-order topographic curvature corresponding to the center line of the trajectory.

[0013] Preferably, the calculation of the surface morphology coupling compensation index satisfies the following relationship:

[0014] In the formula, For the first The surface morphology coupling compensation index corresponding to the center line of the preset trajectory; The basic geometric compensation coefficient; The tension migration gain coefficient is mentioned above; The sensitivity response coefficient is mentioned above; For the first The second-order topographic curvature corresponding to the center line of the trajectory; For the first The first-order topographic slope corresponding to the centerline of the trajectory. Let represent the hyperbolic tangent function as the nonlinear mapping function.

[0015] This invention constructs a compensation model that takes into account both geometric projection and surface tension thinning effects, and uses a nonlinear mapping function to ensure the rationality of the compensation intensity, thus avoiding excessive local coating buildup.

[0016] Preferably, the calculation of the dynamic line spacing of the next trajectory satisfies the following relationship: , The dynamic line spacing for the next trajectory; The row spacing of the reference plane; For the first The surface morphology coupling compensation index corresponds to the center line of the preset trajectory.

[0017] Preferably, the method for determining the numerical value of the basic geometric compensation coefficient includes the following steps: A flat slope sample block with zero curvature was selected, and a constant speed and constant flow spraying experiment was carried out on the flat slope sample block; The average film thickness at the flat slope sample block and the plane reference film thickness were measured. Calculate the ratio of the average film thickness to the planar reference film thickness, subtract the ratio from 1 to obtain the natural geometric attenuation rate, and use the natural geometric attenuation rate as the basic geometric compensation coefficient.

[0018] This invention can establish a benchmark compensation standard based on the deposition characteristics of specific coatings, thereby improving the accuracy of the solution's adaptation to different coating materials.

[0019] Preferably, the method for determining the tension migration gain coefficient includes the following steps: Select a boss sample block with a standard rounded corner, wherein the standard rounded corner has a known theoretical curvature; A spraying experiment was conducted on the boss sample block to measure the actual film thickness attenuation rate at the standard rounded corner apex. The difference between the actual film thickness attenuation rate and the basic geometric compensation coefficient is calculated and denoted as the additional attenuation. The rheological feature length corresponding to the boss sample is obtained by dividing the additional attenuation by the theoretical curvature, and the rheological feature length is used as the tension migration gain coefficient.

[0020] This invention transforms rheological characteristics that are difficult to measure directly into specific parameter gains, thereby achieving precise compensation for coating migration caused by surface tension.

[0021] Preferably, the calculation of the execution coordinate vector satisfies the following relationship: , The execution coordinate vector for the next trajectory; For the first The execution coordinate vector corresponding to the center line of the preset trajectory; Extend the direction vector of the preset trajectory; This is the dynamic line spacing for the next trajectory.

[0022] Preferably, in the sampling process, the preset lateral sampling step size ranges from 0.2 mm to 0.5 mm.

[0023] Secondly, the present invention provides a robotic spraying trajectory optimization system for liquid-cooled plates, employing the following technical solution: A robotic spraying trajectory optimization system for liquid-cooled plates includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-described robotic spraying trajectory optimization method for liquid-cooled plates is implemented.

[0024] By adopting the above technical solution, the above-mentioned robot spraying trajectory optimization method for liquid cooling plates is generated into a computer program and stored in a memory so that it can be loaded and executed by a processor. In this way, a terminal device can be made based on the memory and the processor for convenient use.

[0025] The present invention has the following technical effects: This scheme utilizes the combined compensation of first-order slope and second-order curvature to successfully counteract the local thinning effect caused by geometric projection and surface tension, thereby significantly improving the film thickness compliance rate at the R-corner of the flow channel.

[0026] Furthermore, by introducing a saturation suppression function and a safety threshold limit, thickness compensation is achieved while avoiding physical interference between the spray gun and the workpiece, thus balancing work quality and system stability. Compared to traditional fixed-spacing spraying, this invention can dynamically adjust the paint mist overlap rate according to the actual morphology, significantly reducing the rework rate of the liquid-cooled plate flow channel, and has extremely high application value in automated production. Attached Figure Description

[0027] Figure 1 This is a flowchart of a method in the robot spraying trajectory optimization method for liquid-cooled plates provided in an embodiment of the present invention; Figure 2 The morphological feature image provided in the embodiments of the present invention; Figure 3 This is a schematic diagram of the spraying spacing curve provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the spraying effect provided in an embodiment of the present invention. Detailed Implementation

[0028] This invention discloses a method for optimizing the robotic spraying trajectory for liquid-cooled plates, referring to... Figure 1 This includes steps S1-S5: S1: The surface of the liquid cooling plate to be sprayed is sampled using a line laser profile sensor to obtain a set of cross-sectional profile heights that characterize the surface morphology.

[0029] It should be noted that in automated spraying scenarios for liquid-cooled plates, the workpiece surface exhibits microscopic undulations and flow channel angles. This characteristic means that the actual distance between the nozzle and the workpiece surface, as well as the spraying angle, are dynamically changing. If conventional static path planning is used, it is highly likely that the amount of paint adhered in local areas will deviate from the theoretical value. To solve this problem, it is necessary to first obtain the geometric structure data of the surface to be sprayed.

[0030] Preferably, as an example, a line laser profile sensor is used to sample the surface of the liquid-cooled plate to be sprayed, obtaining a set of cross-sectional profile heights characterizing the surface morphology, including: First, a line laser profile sensor is used to scan the surface of the liquid cooling plate to obtain physical depth data characterizing the surface morphology.

[0031] Next, using the mechanical center of the liquid cooling plate as the origin of the coordinate system, discrete sampling was performed on each position of the liquid cooling plate to obtain a two-dimensional sampling matrix. It should be noted that the lateral sampling step size during the sampling process ranges from 0.2 mm to 0.5 mm.

[0032] Subsequently, the physical depth values ​​at each location in the two-dimensional sampling matrix are denoised using a median filtering algorithm to obtain the cross-sectional profile height set. For ease of understanding, the denoised physical depth values ​​at each location in the cross-sectional profile height set will be denoted as the profile height values.

[0033] Understandably, the obtained cross-sectional profile height set reflects the true undulation state of the liquid cooling plate surface, thus providing underlying data support for subsequent identification of the projection unfolding area and effectively eliminating the blind spots in the coating caused by unknown morphology.

[0034] S2: Process the set of cross-sectional contour heights to obtain the first-order morphological slope and second-order morphological curvature corresponding to each preset trajectory centerline.

[0035] It should be noted that the projection dilution effect on the surface of the liquid cooling plate is mainly affected by the slope, while the coating migration effect is mainly driven by the curvature. This characteristic requires that the morphological feature data reflecting the slope and curvature information of the liquid cooling plate surface must be separated from the height data. Therefore, the core purpose of this step is to extract a morphological description that can reflect the slope and curvature information of the liquid cooling plate surface.

[0036] Preferably, as an example, the cross-sectional profile height set is processed to obtain the first-order topographic slope and second-order topographic curvature corresponding to each preset trajectory centerline, including:

[0037]

[0038] In the formula, , and The first The first preset trajectory The, the The and the first The contour height value of the sampling point, Indicates the lateral sampling step size. Indicates the number of sampling points. For example, the zero-prevention parameter is... Take 0.001, For the first The second-order topographic curvature corresponding to the center line of the trajectory.

[0039] Understandably, the first-order topographic slope reflects the gradient of the liquid cooling plate surface; a larger value indicates a steeper gradient. The second-order topographic curvature reflects the curvature of the liquid cooling plate surface; a larger value indicates a steeper curvature.

[0040] S3: Based on the preset basic geometric compensation coefficient, tension migration gain coefficient and sensitivity response coefficient, the first-order morphology slope and the second-order morphology curvature are weighted and fused to obtain the surface morphology coupling compensation index that reflects the coating migration risk and projection unfolding effect.

[0041] It should be noted that the effects of projection dilution and tension migration on film thickness have different weights and exhibit nonlinear saturation characteristics. This physical characteristic means that they cannot be simply superimposed linearly. Direct accumulation can easily lead to compensation overload at abrupt changes in morphology. Therefore, the core objective of this step is to determine a numerical index that comprehensively reflects the risk of morphological thinning.

[0042] Preferably, as an example, based on preset basic geometric compensation coefficients, tension migration gain coefficients, and sensitivity response coefficients, a weighted fusion calculation is performed on the first-order morphology slope and the second-order morphology curvature to obtain a surface morphology coupling compensation index reflecting the coating migration risk and projection unfolding effect, including:

[0043] In the formula, For the first The surface morphology coupling compensation index corresponding to the center line of the preset trajectory; The basic geometric compensation coefficient; The tension migration gain coefficient is mentioned above; The sensitivity response coefficient is mentioned above; For the first The second-order topographic curvature corresponding to the center line of the trajectory; For the first The first-order topographic slope corresponding to the centerline of the trajectory. Let represent the hyperbolic tangent function as the nonlinear mapping function.

[0044] Understandably, using the slope The saturation mapping function of the variables serves as the overall adjustment weight for variables containing curvature. The gain term is scaled overall. This logic simulates the real physical process, where the projection unfolding effect is the primary influencing factor of coating distribution, while tension migration is a secondary variable superimposed on the projection change. Only when the surface has a certain slope will the migration effect caused by curvature have a more threatening superimposed impact on the final film thickness.

[0045] It should be noted that the basic geometric compensation coefficient Methods for obtaining [the information] include: A flat slope sample block with zero curvature was selected, and a constant speed and constant flow spraying experiment was carried out on the flat slope sample block; The average film thickness at the flat slope sample block and the plane reference film thickness were measured. Calculate the ratio of the average film thickness to the planar reference film thickness, subtract the ratio from 1 to obtain the natural geometric attenuation rate, and use the natural geometric attenuation rate as the basic geometric compensation coefficient.

[0046] It should also be noted that the tension migration gain coefficient Methods for obtaining [the information] include: Select a boss sample block with a standard rounded corner, wherein the standard rounded corner has a known theoretical curvature; A spraying experiment was conducted on the boss sample block to measure the actual film thickness attenuation rate at the standard rounded corner apex. The difference between the actual film thickness attenuation rate and the basic geometric compensation coefficient is calculated and denoted as the additional attenuation. The rheological feature length corresponding to the boss sample is obtained by dividing the additional attenuation by the theoretical curvature, and the rheological feature length is used as the tension migration gain coefficient.

[0047] It should also be noted that the sensitivity response coefficient The methods for obtaining it include: First, a continuous gradient spraying experiment was conducted on a group of slope samples with different tilt angles using a spraying system to obtain different slope values. Based on the actual film thickness attenuation rate data points, a discrete dataset of morphological response is constructed.

[0048] Next, the discrete dataset of the morphological response is substituted into a preset saturation exponential model using the nonlinear least squares method. The residual iterative calculation is performed to obtain the sensitivity response coefficient. .

[0049] S4: Determine the dynamic line spacing of the next trajectory based on the product of the surface morphology coupling compensation index and the preset reference plane line spacing.

[0050] It should be noted that the overlap rate of the spraying trajectory is the main factor controlling the film thickness, and adjusting the geometric spacing of the trajectory can adjust the overlap rate. Therefore, the geometric spacing of the trajectory can be adjusted according to the compensation requirements at different locations on the liquid cooling plate. The core purpose of this step is to determine the spacing between the spraying trajectories.

[0051] Preferably, as an example, the dynamic line spacing of the next trajectory is determined based on the product of the surface topography coupling compensation index and the preset reference plane line spacing, including: Obtain the preset reference plane line spacing.

[0052] Next, the dynamic line spacing is obtained by correcting the line spacing of the reference plane using the surface topography coupling compensation index. , The dynamic line spacing for the next trajectory; The reference plane row spacing is the spray trajectory spacing set by the conventional method; For the first The surface morphology coupling compensation index corresponds to the preset trajectory centerline. This allows for dynamic adjustment of the spraying spacing based on the surface morphology, effectively suppressing uneven spraying defects caused by surface morphology.

[0053] Subsequently, if the dynamic line spacing is less than a preset minimum threshold, the dynamic line spacing is forcibly locked to the minimum threshold using a numerical truncation method. This limit processing ensures that the wet film thickness remains within a safe range during high-intensity compensation, effectively eliminating process defects such as sagging, material buildup, and drying cracking caused by excessive trajectory stacking. For example, the preset range of the minimum threshold is 2mm to 4mm.

[0054] S5: Generate the execution coordinate vector of the next trajectory based on the dynamic line spacing of the next trajectory, and drive the robot to perform variable pitch spraying operation.

[0055] It should be noted that the calculated dynamic row spacing must be converted into a spatial coordinate sequence that the robot controller can recognize in order to achieve effective control of the painting robot. Therefore, the core purpose of this step is to execute the physical drive for variable pitch operations.

[0056] Preferably, as an example, generating the execution coordinate vector of the next trajectory based on the dynamic line spacing of the next trajectory, and driving the robot to perform variable pitch spraying operations, includes: First, obtain the unit normal vector of the trajectory extension direction. .

[0057] Next, the execution coordinate vector of the next trajectory is calculated based on the unit normal vector of the trajectory extension direction, the execution coordinate vector of the current trajectory, and the dynamic line spacing of the next trajectory, specifically satisfying the following relationship: , The execution coordinate vector for the next trajectory; For the first The execution coordinate vector corresponding to the center line of the preset trajectory; Extend the direction vector of the preset trajectory; This is the dynamic line spacing for the next trajectory.

[0058] It should be noted that the number here will be... The preset trajectory is used as the current trajectory, the first... Each preset trajectory is described as the next preset trajectory.

[0059] Finally, based on the execution coordinate vector of the next trajectory, the robot motion control interface is used to drive the end effector to perform the spraying operation.

[0060] To demonstrate the effectiveness of the solution, relevant experiments were conducted. Below are the images obtained from the experiments: Figure 2 This is a topographic feature image. The thick solid line in the image represents the cross-sectional profile height, which visually reflects the actual undulations of the liquid cooling plate surface. The obliquely shaded area is the shaded portion below the profile height set, representing the physical entity region of the liquid cooling plate. The dashed curve represents the extracted first-order topographic slope. The dotted thin curves represent the identified second-order topographic curvature.

[0061] Figure 3 This is a schematic diagram of the spraying spacing curve. The thin horizontal dashed line represents the fixed reference value in traditional processes, i.e., the row spacing on the reference plane. The continuously fluctuating solid line represents the dynamic row spacing of the next trajectory calculated by this invention. The "+" markers represent the spatial coordinate vector sampling points of the robot control system when performing variable pitch operations. The image shows that... Figure 2 In the coordinate range where the second-order morphological curvature reaches its peak, the dynamic row spacing curve in this figure shows a significant downward shift. This demonstrates that the proposed solution can accurately identify the risk of paint migration at the corners of the liquid-cooled plate and proactively increase the local coating overlap rate by reducing the trajectory spacing in a timely manner.

[0062] Figure 4 This diagram illustrates the spraying effect. The rectangular transparent filler band represents the preset high-precision process qualification range, i.e., the ideal paint film thickness tolerance zone. The thin horizontal line in the center represents the standard target film thickness line. The dotted line represents the measured paint film thickness curve obtained using traditional equal-pitch spraying. The dark, thick solid line represents the measured paint film thickness curve obtained using the variable-pitch spraying proposed in this invention, showing the final quality after compensation. The image shows that the traditional equal-pitch spraying curve exhibits a sharp dip at the coordinate position corresponding to the high curvature angle, indicating that the traditional method cannot overcome the thinning caused by projection dilution. In contrast, the thick solid line corresponding to this solution, through dynamic compensation at the same position, keeps the paint film thickness consistently within the qualification range, demonstrating the significant improvement effect of the surface morphology coupling compensation index on paint film thickness consistency.

[0063] This invention also discloses a robotic spraying trajectory optimization system for liquid-cooled plates, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the robotic spraying trajectory optimization method for liquid-cooled plates according to the present invention.

[0064] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0065] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (DRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (DRAM), high-bandwidth memory, hybrid memory cube, etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device.

Claims

1. A method for optimizing the robotic spraying trajectory for liquid-cooled plates, characterized in that, Including the following steps: A line laser profile sensor is used to sample the surface of the liquid cooling plate to be sprayed, and a set of cross-sectional profile heights characterizing the surface morphology is obtained. The cross-sectional profile height set is processed to obtain the first-order topography slope and second-order topography curvature corresponding to each preset trajectory centerline. Based on the preset basic geometric compensation coefficient, tension migration gain coefficient and sensitivity response coefficient, the first-order morphology slope and the second-order morphology curvature are weighted and fused to obtain a surface morphology coupling compensation index that reflects the coating migration risk and projection unfolding effect. The dynamic line spacing of the next trajectory is determined based on the product of the surface topography coupling compensation index and the preset reference plane line spacing, wherein the dynamic line spacing of the next trajectory decreases as the first-order topography slope or the second-order topography curvature increases. The execution coordinate vector of the next trajectory is generated based on the dynamic line spacing of the next trajectory, and the robot is driven to perform variable pitch spraying to compensate for the coating thinning defect caused by the coupling of geometric projection effect and surface tension migration effect in the flow channel corner area of ​​the liquid cooling plate surface.

2. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, The calculation of the first-order topographic slope satisfies the following relationship: In the formula, For the first The first-order topographic slope corresponding to the center line of the preset trajectory; This is the preset total number of sampling points; For sampling point index; For the first The first preset trajectory The contour height of each sampling point; For the first The first preset trajectory The contour height of each sampling point; This is the preset horizontal sampling step size; This is the preset zero-prevention parameter.

3. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, The calculation of the second-order topographic curvature satisfies the following relationship: In the formula, , and The first The first preset trajectory The, the The and the first The contour height value of the sampling point, Indicates the lateral sampling step size. Indicates the number of sampling points. For the zero-prevention parameter, For the first The second-order topographic curvature corresponding to the center line of the trajectory.

4. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, The calculation of the surface morphology coupling compensation index satisfies the following relationship: In the formula, For the first The surface morphology coupling compensation index corresponding to the center line of the preset trajectory; The basic geometric compensation coefficient; The tension migration gain coefficient is mentioned above. The sensitivity response coefficient is mentioned above; For the first The second-order topographic curvature corresponding to the center line of the trajectory; For the first The first-order topographic slope corresponding to the centerline of the trajectory. Let represent the hyperbolic tangent function as the nonlinear mapping function.

5. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 4, characterized in that, The calculation of the dynamic line spacing of the next trajectory satisfies the following relationship: , The dynamic line spacing for the next trajectory; The line spacing of the reference plane; For the first The surface morphology coupling compensation index corresponds to the center line of the preset trajectory.

6. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, The method for determining the numerical value of the basic geometric compensation coefficient includes the following steps: A flat slope sample block with zero curvature was selected, and a constant speed and constant flow spraying experiment was carried out on the flat slope sample block; The average film thickness at the flat slope sample block and the plane reference film thickness were measured. Calculate the ratio of the average film thickness to the planar reference film thickness, subtract the ratio from 1 to obtain the natural geometric attenuation rate, and use the natural geometric attenuation rate as the basic geometric compensation coefficient.

7. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 5, characterized in that, The method for determining the tension migration gain coefficient includes the following steps: Select a boss sample block with a standard rounded corner, wherein the standard rounded corner has a known theoretical curvature; A spraying experiment was conducted on the boss sample block to measure the actual film thickness attenuation rate at the standard rounded corner apex. The difference between the actual film thickness attenuation rate and the basic geometric compensation coefficient is calculated and denoted as the additional attenuation. The rheological feature length corresponding to the boss sample is obtained by dividing the additional attenuation by the theoretical curvature, and the rheological feature length is used as the tension migration gain coefficient.

8. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, The calculation of the execution coordinate vector satisfies the following relationship: , The execution coordinate vector for the next trajectory; For the first The execution coordinate vector corresponding to the center line of the preset trajectory; Extend the direction vector of the preset trajectory; This is the dynamic line spacing for the next trajectory.

9. The method for optimizing the robot spraying trajectory for liquid-cooled plates according to claim 1, characterized in that, In the sampling process, the preset horizontal sampling step size ranges from 0.2 mm to 0.5 mm.

10. A robotic spraying trajectory optimization system for liquid-cooled plates, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the robotic spraying trajectory optimization method for liquid-cooled plates according to any one of claims 1-9.

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