Laser energy adaptation method and system for white oil blocks with different types and thicknesses

Abstract

The invention relates to the technical field of PCBs, in particular to a laser energy adaptation method and system for white oil blocks with different types and thicknesses. The laser energy is accurately adapted according to the characteristics of white oil blocks of different types and thicknesses by combining pre-adjustment and real-time correction of laser parameters, so that the engraving process is finer and more efficient, heat accumulation in the engraving process is effectively controlled by collecting temperature values of a plurality of areas in real time and establishing a temperature field distribution model, and the engraving precision is improved. According to the method, local overheating caused by the fact that too high heat is concentrated at a certain position is avoided, the engraving quality and efficiency are further improved by optimizing and adjusting a scanning path, unnecessary heat transfer risks are reduced, an accurate laser energy adaptation model can be generated for a laser engraving system based on an engraving effect evaluation index, and the laser engraving efficiency is improved. And the characteristics of different white oil blocks can be adapted, and the heat distribution balance in the processing process is ensured, so that the engraving effect is improved, and the reliability and stability of the PCB substrate are ensured.

Description

Technical Field

[0001] This invention relates to the field of PCB technology, and in particular to a method and system for adapting laser energy to different types and thicknesses of white solder mask blocks. Background Technology

[0002] During PCB manufacturing, customers sometimes request the printing of white ink blocks on the PCB board for easy laser engraving of barcodes. White ink blocks typically refer to a material that covers the PCB surface to protect or reinforce the circuit board. Its main function is to provide surface protection and facilitate subsequent laser processing. Different types of white ink blocks may have different physical and chemical properties (such as thickness, density, light absorption characteristics, etc.). Therefore, during laser processing, it is necessary to adjust the laser parameters according to these characteristics. The core of the laser energy adaptation method is to precisely control the laser power, frequency, wavelength, etc., based on the light absorption characteristics and thickness of the white ink block, to ensure that the laser can effectively engrave or mark without damaging the PCB board itself. The key factors for laser energy adaptation are the thickness of the white ink block, the type of white ink block, and the control of the laser energy.

[0003] Currently, laser energy adaptation methods for white paint blocks of different types and thicknesses are widely used in industrial production. Existing technologies mainly combine laser power adjustment and scanning speed control. By adjusting the laser power and scanning speed, different thicknesses and types of white paint blocks can be adapted to ensure the accuracy of the laser engraving effect and avoid damage to the PCB board itself. However, in the above methods, the adjustment of laser power and scanning speed during laser engraving is mainly accomplished by locally heating the white paint block and the PCB surface. However, when the laser acts on a certain area for a long time, heat may accumulate. This accumulated heat not only affects the engraving effect of the white paint block, but may also be further transferred to the PCB substrate, causing the substrate to overheat, deform, and even affect the performance and reliability of the circuit. Summary of the Invention

[0004] The main objective of this invention is to provide a laser energy adaptation method for different types and thicknesses of white oil blocks, aiming to solve the technical problems in the prior art.

[0005] This invention proposes a method for adapting laser energy to different types and thicknesses of white oil blocks, including: The initial laser parameters, initial laser engraving path, and type and thickness parameters of the white paint block of the laser engraving system are obtained, and the initial laser parameters are pre-adjusted according to the type and thickness parameters to obtain the pre-adjusted laser parameters. Based on the pre-adjusted laser parameters, the laser engraving system is started to collect the temperature values ​​of multiple areas on the surface of the white oil block and the energy density value of each laser action point on the initial laser engraving path in real time, and a real-time temperature field distribution model is constructed based on the multiple area temperature values. Based on the real-time temperature field distribution model and each energy density value, obtain the corresponding heat accumulation risk coefficient, and determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the thermal accumulation risk coefficient exceeds the preset risk threshold, the pre-adjusted laser parameters are corrected and adjusted according to the thermal accumulation risk coefficient to obtain the corrected laser parameters; The scanning path adjustment parameters are obtained based on the heat accumulation risk coefficient, and the initial laser engraving path is replanned based on the scanning path adjustment parameters to obtain the adjusted laser engraving path. The scanning path adjustment parameters include scanning direction angle, hot spot avoidance distance and scanning spacing. Based on the corrected laser parameters and adjusted laser engraving path, the depth information and grayscale image information of the white oil block engraving area are collected in real time, and the engraving effect evaluation index is obtained based on the depth information and grayscale image information. Based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, a laser energy adaptation model is generated so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

[0006] Preferably, the step of pre-adjusting the initial laser parameters according to the type parameter and thickness parameter to obtain the pre-adjusted laser parameters includes: The substrate type of the white oil block is obtained according to the type parameters, and the corresponding thermal conductivity and upper limit of heat resistance temperature are obtained according to the substrate type. Obtain the laser incident angle of the laser engraving system; The thickness value of the white oil block is obtained based on the thickness parameter, and the length of the heat conduction path is obtained based on the thickness value and the laser incident angle. The density, specific heat capacity, and ambient temperature of the white oil block are obtained, and the inertia coefficient of the heat conduction path is obtained based on the density, specific heat capacity, and heat conduction path length. The temperature difference is obtained based on the ambient temperature and the upper limit of the heat resistance temperature, and the first power correction coefficient is obtained based on the temperature difference, the thermal conductivity and the inertia coefficient of the heat conduction path. The first scanning speed correction coefficient is obtained based on the thickness value, and the initial scanning speed and initial laser power in the initial laser parameters are pre-adjusted based on the first scanning speed correction coefficient and the first power correction coefficient, respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

[0007] Preferably, the step of obtaining the corresponding thermal accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value includes: Obtain the substrate type of the white oil block, and obtain the energy tolerance threshold based on the substrate type; The corresponding energy exceedance coefficient is obtained based on each energy density value and energy tolerance threshold. The location information of the corresponding laser action point is obtained based on each energy density value, and the location of the corresponding region is determined based on each location information. Each of the aforementioned regions is input into the real-time temperature field distribution model to obtain the corresponding region temperature value, and the corresponding temperature risk coefficient is obtained based on each region temperature value and energy tolerance threshold. Obtain the total surface area of ​​the white oil block; The area of ​​the corresponding region is obtained based on the location of the region, and the area ratio coefficient is obtained based on the area of ​​each region and the total surface area. The corresponding thermal accumulation risk coefficient is obtained based on each of the area proportion coefficient, temperature risk coefficient, and energy excess coefficient.

[0008] Preferably, the step of obtaining the scanning path adjustment parameters based on the thermal accumulation risk coefficient, and replanning the initial laser engraving path based on the scanning path adjustment parameters to obtain the adjusted laser engraving path includes: The thermal conductivity, thickness, and upper limit of the heat resistance temperature of the white oil block are obtained, and the scanning interval is obtained based on the thickness value and the heat accumulation risk coefficient. Based on the heat accumulation risk coefficient, obtain the location and temperature information of the corresponding laser impact point, and obtain the temperature gradient vector of the laser impact point based on the temperature and location information; The temperature gradient direction angle is obtained based on the temperature gradient vector, and the scanning direction angle is obtained based on the temperature gradient direction angle and the heat accumulation risk coefficient. The temperature coefficient ratio is obtained based on the temperature information and the upper limit of the heat resistance temperature, and the hot spot avoidance distance is obtained based on the thermal conductivity and the temperature coefficient ratio. The direction of the new scan line is determined according to the scan direction angle, and the spacing of the new scan line is arranged according to the scan spacing. Based on the hotspot avoidance distance, a new jump path is planned between the planned areas, and the initial laser engraving path is replanned based on the new jump path, the new scan line direction, and the new scan line spacing to obtain an adjusted laser engraving path.

[0009] Preferably, the step of obtaining the carving effect evaluation index based on the depth information and grayscale image information includes: The actual depth and preset standard depth of the white oil block carving area are obtained based on the depth information, and the scratch depth deviation rate is obtained based on the actual depth and preset standard depth. Obtain the standard carving edge line of the white oil block carving area, and obtain the standard edge length based on the standard carving edge line; The edge contour lines are extracted from the grayscale image information, and the coordinates of multiple sampling points on the edge contour lines are extracted; Obtain the vertical distance from the coordinates of each sampling point to the standard engraved edge line, and obtain the average deviation distance based on multiple vertical distances; The edge flatness deviation rate is obtained based on the average deviation distance and standard edge length, and the engraving effect evaluation index is obtained based on the edge flatness deviation rate and the scratch depth deviation rate.

[0010] Preferably, the step of generating a laser energy adaptation model based on the engraving effect evaluation index, the real-time temperature field distribution model, the corrected laser parameters, and the adjusted laser engraving path includes: The highest temperature value is obtained based on the real-time temperature field distribution model, and the scanning path parameters are obtained based on the adjustment of the laser engraving path. Multiple sets of engraving data for white oil blocks of different types and thicknesses are obtained, and the multiple sets of engraving data are divided into training set and validation set. The engraving data includes engraving effect evaluation index, maximum temperature value, corrected laser parameters and scanning path parameters. An initial fitting model was constructed using the random forest algorithm, and the training set was input into the initial fitting model for training. The hyperparameters of the model were then optimized using the grid search method to obtain the preliminary fitting model. The validation set data is input into the initial adaptation model for validation, and the model output result is obtained. It is then determined whether the model output result is within a preset threshold range. If the model output is not within the preset threshold range, return to the step of inputting the training set into the initial adapted model for training and optimizing the hyperparameters of the model using the grid search method until the model output is within the preset threshold range. If the output of the model is within a preset threshold range, then the preliminary adaptation model is determined as the laser energy adaptation model.

[0011] This application also provides a laser energy adaptation system for different types and thicknesses of white oil blocks, including: The pre-adjustment module is used to acquire the initial laser parameters, initial laser engraving path, and type and thickness parameters of the white oil block of the laser engraving system, and to pre-adjust the initial laser parameters according to the type and thickness parameters to obtain the pre-adjusted laser parameters. The module is used to start the laser engraving system based on the pre-adjusted laser parameters to collect the temperature values ​​of multiple areas on the surface of the white oil block and the energy density value of each laser action point on the initial laser engraving path in real time, and to construct a real-time temperature field distribution model based on the multiple area temperature values. The judgment module is used to obtain the corresponding heat accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value, and to determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the thermal accumulation risk coefficient exceeds the preset risk threshold, the pre-adjusted laser parameters are corrected and adjusted according to the thermal accumulation risk coefficient to obtain the corrected laser parameters; The planning module is used to obtain scanning path adjustment parameters based on the heat accumulation risk coefficient, and to replan the initial laser engraving path based on the scanning path adjustment parameters to obtain an adjusted laser engraving path. The scanning path adjustment parameters include scanning direction angle, hot spot avoidance distance, and scanning spacing. The acquisition module is used to acquire depth information and grayscale image information of the white oil block engraving area in real time based on the corrected laser parameters and adjusted laser engraving path, and to obtain an engraving effect evaluation index based on the depth information and grayscale image information; The generation module is used to generate a laser energy adaptation model based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

[0012] Preferably, the pre-adjustment module includes: The first acquisition unit is used to acquire the substrate type of the white oil block according to the type parameter, and to acquire the corresponding thermal conductivity and upper limit of heat resistance temperature according to the substrate type. The second acquisition unit is used to acquire the laser incident angle of the laser engraving system; The third acquisition unit is used to acquire the thickness value of the white oil block according to the thickness parameter, and to acquire the heat conduction path length according to the thickness value and the laser incident angle. The fourth acquisition unit is used to acquire the density, specific heat capacity and ambient temperature of the white oil block, and to acquire the inertia coefficient of the heat conduction path based on the density, specific heat capacity and heat conduction path length. The fifth acquisition unit is used to acquire the temperature difference based on the ambient temperature and the upper limit of the heat resistance temperature, and to acquire the first power correction coefficient based on the temperature difference, thermal conductivity and heat conduction path inertia coefficient. The pre-adjustment unit is used to obtain a first scanning speed correction coefficient based on the thickness value, and to pre-adjust the initial scanning speed and initial laser power in the initial laser parameters based on the first scanning speed correction coefficient and the first power correction coefficient, respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

[0013] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the laser energy adaptation method for different types and thicknesses of white oil blocks described above.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the laser energy adaptation method for different types and thicknesses of white oil blocks described above.

[0015] The beneficial effects of this invention are as follows: By real-time monitoring and dynamic adjustment of the risk of heat accumulation during laser engraving, this invention can effectively solve the problems of unstable engraving quality and PCB substrate overheating and deformation caused by heat accumulation during laser engraving in the prior art. By combining the pre-adjustment and real-time correction of laser parameters, the laser energy is precisely adapted according to the characteristics of white paint blocks of different types and thicknesses, making the engraving process more precise and efficient. This invention ensures that heat accumulation during the engraving process is effectively controlled by collecting temperature values ​​of multiple areas in real time and establishing a temperature field distribution model, avoiding excessive heat concentration in a certain place and causing local overheating. By optimizing and adjusting the scanning path, the engraving quality and efficiency are further improved, and unnecessary heat transfer risks are reduced. Based on the engraving effect evaluation index, a precise laser energy adaptation model can be generated for the laser engraving system, enabling it to adapt to the characteristics of different white paint blocks, ensuring a balanced heat distribution during processing, thereby improving the engraving effect and ensuring the reliability and stability of the PCB substrate. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of this application.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0021] like Figure 1 As shown, this application provides a laser energy adaptation method for different types and thicknesses of white oil blocks, including: S1. Obtain the initial laser parameters, initial laser engraving path, and type and thickness parameters of the white oil block of the laser engraving system, and pre-adjust the initial laser parameters according to the type and thickness parameters to obtain the pre-adjusted laser parameters; S2. Based on the pre-adjusted laser parameters, start the laser engraving system to collect the temperature values ​​of multiple areas on the surface of the white oil block and the energy density value of each laser action point on the initial laser engraving path in real time, and construct a real-time temperature field distribution model based on the multiple area temperature values. S3. Obtain the corresponding heat accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value, and determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the heat accumulation risk coefficient exceeds the preset risk threshold, it is determined that the heat accumulation at the laser action point is serious, and the pre-adjusted laser parameters are corrected according to the heat accumulation risk coefficient to obtain the corrected laser parameters. S4. Obtain the scanning path adjustment parameters based on the thermal accumulation risk coefficient, and replan the initial laser engraving path based on the scanning path adjustment parameters to obtain the adjusted laser engraving path; S5. Based on the corrected laser parameters and adjusted laser engraving path, the depth information and grayscale image information of the white oil block engraving area are collected in real time, and the engraving effect evaluation index is obtained according to the depth information and grayscale image information. S6. Generate a laser energy adaptation model based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

[0022] As described in steps S1-S6 above, this invention obtains the initial laser parameters, initial laser engraving path, and type and thickness parameters of the white paint block of the laser engraving system. Based on these type and thickness parameters, the initial laser parameters are pre-adjusted to obtain pre-adjusted laser parameters. The initial laser parameters, engraving path, and the type and thickness of the white paint block are core factors affecting engraving quality and precision. Different types and thicknesses of the white paint block significantly affect laser absorption characteristics and thermal conductivity. Therefore, obtaining these basic parameters is fundamental for subsequent precise adjustment and optimization of the engraving effect. By comprehensively considering the type and thickness of the white paint block, specific basis can be provided for subsequent laser parameter adjustments. Existing methods often only rely on rough laser power and scanning... Speed ​​adjustments are used to accommodate white paint blocks of varying thicknesses, but this ignores the differences in white paint block types and their specific impact on the engraving process. Different types of white paint blocks have different thermal properties and surface conditions. Simple power adjustment cannot accommodate all types of white paint blocks. Therefore, adjustments need to be made based on the initial laser parameters and the specific type and thickness. By pre-adjusting the laser parameters, problems caused by material differences can be avoided before engraving, reducing repeated adjustments during the experimental stage. This leads to more precise engraving results, ensures stable engraving quality, and improves the intelligence level of the laser engraving system. The system can be personalized according to the characteristics of different materials, thereby achieving higher processing efficiency and quality. This is achieved by starting the system with pre-adjusted laser parameters. The laser engraving system collects real-time temperature values ​​from multiple areas on the surface of the white paint block, as well as the energy density values ​​at each laser point along the initial laser engraving path. By monitoring temperature and energy density in real time, the system can reflect the actual effect of the laser on the material surface, avoiding overheating caused by localized high temperatures. Temperature changes at different locations also help identify potential heat accumulation areas, providing timely feedback for adjusting laser parameters. Real-time temperature monitoring helps the system instantly grasp the thermal state of the engraving area, preventing overheating that could damage the white paint block or lead to over-engraving. Real-time monitoring of energy density allows for precise control of the uniformity of laser action, ensuring consistent engraving results. By monitoring temperature and energy density in real time, the system can more accurately control heat distribution, avoiding... To avoid quality issues caused by uneven laser energy density, a real-time temperature field distribution model is constructed based on temperature values ​​from multiple regions. This model reflects the thermal changes throughout the engraving area, helping the system understand the heat accumulation trend and distribution after laser action, thus enabling appropriate adjustments. The real-time generated temperature field distribution model provides data support for subsequent assessment of heat accumulation risks, helping to avoid engraving quality degradation due to heat accumulation. The temperature field distribution model can effectively predict heat propagation trends, thereby avoiding over-engraving, overheating, or heat transfer to the PCB substrate. The real-time temperature field distribution model can dynamically simulate heat changes, improving the accuracy and efficiency of handling heat accumulation problems and reducing the need for errors and repeated adjustments.

[0023] By using a real-time temperature field distribution model and each energy density value, a corresponding heat accumulation risk coefficient is obtained. It is then determined whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the risk coefficient exceeds the threshold, the heat accumulation at that laser point is considered severe. Based on the heat accumulation risk coefficient, the pre-adjusted laser parameters are adjusted to obtain the corrected laser parameters. The scanning path adjustment parameters are also obtained from the heat accumulation risk coefficient, and the initial laser engraving path is replanned based on these parameters to obtain the adjusted laser engraving path. The heat accumulation risk coefficient quantitatively assesses the degree of heat accumulation at each laser point, ensuring the system can promptly identify overheating phenomena and make adjustments. Determining whether a risk threshold is exceeded provides a clear standard for subsequent processing. By quantifying the heat accumulation risk coefficient, the system can make intelligent decisions based on the actual risk situation, avoiding damage caused by local overheating. Setting a risk threshold helps avoid over-adjustment, ensuring the engraving effect remains within an acceptable heat range. Through a quantified heat accumulation risk coefficient, the system can make more accurate and reliable decisions, improving the safety and stability of the engraving process. Correcting laser parameters and replanning the engraving path can effectively address local heat accumulation, preventing further heat diffusion or concentration, thus ensuring the engraving effect is unaffected. Correcting laser parameters helps balance heat distribution and reduce local overheating, while replanning the engraving path avoids areas of heat accumulation, ensuring a more uniform heat distribution during the engraving process. Traditional methods typically only address problems after they are detected. Traditional methods only allow for adjusting power or speed, but this invention achieves more precise engraving by simultaneously adjusting laser parameters and path, while avoiding overheating issues on the white paint block and PCB substrate. By correcting laser parameters and adjusting the laser engraving path, it acquires depth and grayscale image information of the engraving area in real time, and obtains an engraving effect evaluation index based on this information. Depth and grayscale images are crucial indicators for judging engraving quality, providing real-time feedback on engraving accuracy and effect. Combined with the engraving effect evaluation index, it helps optimize the engraving process in real time. Real-time monitoring of depth and grayscale information ensures engraving accuracy, avoiding uneven engraving depth or image blurring. The engraving effect evaluation index helps the system compare engraving results. Unlike traditional manual inspection, automated depth and grayscale information acquisition significantly improves detection accuracy and efficiency, avoiding human error and ensuring consistent, high-quality engraving results. The system generates a laser energy adaptation model by using an engraving effect evaluation index, a real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving paths. This model allows the laser engraving system to adapt its laser energy to different types and thicknesses of white paint blocks. The laser energy adaptation model intelligently adjusts the system's parameters to suit various types and thicknesses of white paint blocks, preventing engraving defects caused by mismatched laser parameters. The laser energy adaptation model is continuously adjusted and optimized in real time.This allows the system to adapt to various material types, ensuring stable and efficient engraving results. The laser energy adaptation model has excellent adaptability, quickly responding to the needs of different materials. This avoids the hassle of repeated manual adjustments required in traditional techniques, which typically rely on manual adjustments. The laser energy adaptation model, however, can automatically adapt to different material types through intelligent adjustment, improving the automation level and production efficiency of the processing.

[0024] In one embodiment, step S1, which pre-adjusts the initial laser parameters according to the type parameter and the thickness parameter to obtain the pre-adjusted laser parameters, includes: S11. Obtain the substrate type of the white oil block according to the type parameter, and obtain the corresponding thermal conductivity and upper limit of heat resistance temperature according to the substrate type. The substrate type includes silicone-based white oil block, resin-based white oil block and rubber-based white oil block. S12. Obtain the laser incident angle of the laser engraving system; S13. Obtain the thickness value of the white oil block according to the thickness parameter, and obtain the heat conduction path length according to the thickness value and the sine value of the laser incident angle. S14. Obtain the density, specific heat capacity and ambient temperature of the white oil block, and obtain the heat conduction path inertia coefficient based on the product of the density, specific heat capacity and heat conduction path length. S15. Obtain the temperature difference based on the ambient temperature and the upper limit of the heat resistance temperature, and obtain the first power correction coefficient by dividing the product of the temperature difference and the thermal conductivity by the inertia coefficient of the heat conduction path. S16. Obtain a first scanning speed correction coefficient based on the thickness value, and pre-adjust the initial scanning speed and initial laser power in the initial laser parameters based on the first scanning speed correction coefficient and the first power correction coefficient respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

[0025] As described in steps S11-S16 above, the calculation of the heat conduction path length, heat conduction path inertia coefficient, and first power correction coefficient are all performed by normalizing the corresponding output current and preliminary adjustment parameters beforehand to eliminate dimensional differences between different variables. The purpose is to ensure that all variables are on the same order of magnitude, thereby making the calculation more stable and effective. The heat conduction path inertia coefficient represents the thermal inertia parameter of the white oil block per unit area along the heat conduction path. Its essence is the ability of the white oil block to store heat and hinder heat conduction during laser engraving (or the total heat potential that a unit area of ​​white oil block can store when laser heat is transferred along the conduction path). The larger the heat conduction path inertia coefficient, the greater the heat conduction potential. The stronger the ability of the white oil block to store heat during the process, the more difficult it is for heat to dissipate quickly (it tends to accumulate); conversely, the less heat is stored, the easier it is to conduct and diffuse (it is not easy to accumulate). The length of the heat conduction path represents the actual path length of the laser heat conduction from the surface of the white oil block to its interior. The greater the thickness and the more inclined the laser incident angle, the longer the heat conduction path, and the easier it is for heat to accumulate on the surface. This invention obtains the substrate type of the white oil block through type parameters, and obtains the corresponding thermal conductivity and upper limit of heat resistance temperature according to the substrate type. The substrate types include silicone-based white oil blocks, resin-based white oil blocks, and rubber-based white oil blocks. By clearly obtaining the substrate type of the white oil block, adjustments can be made according to the different thermal properties (thermal conductivity and upper limit of heat resistance temperature) of each material, thus ensuring the laser engraving process. Precise thermal management during the process prevents heat buildup, overheating, and deformation on different substrates during laser engraving. Existing technologies often overlook substrate type differences, leading to an inability to precisely adjust laser power and scanning speed, affecting engraving results and quality. By obtaining the laser incident angle of the laser engraving system, which directly impacts the heat conduction path length, precise control of the incident angle optimizes heat distribution and conduction, preventing localized overheating, improving heat treatment uniformity, and avoiding the impact of localized overheating on the white paint block and PCB substrate. Compared to existing technologies, this angle consideration effectively avoids the risk of excessively high concentrated laser power causing heat buildup. The thickness of the white paint block is obtained through thickness parameters. The heat conduction path length is obtained by calculating the thickness and the sine of the laser incident angle. The thickness of the white oil block directly affects the heat conduction path length. Accurately measuring the thickness and combining it with the sine of the incident angle helps to accurately calculate the actual distance of heat conduction, thereby optimizing the adjustment of laser power and scanning speed. This ensures a more uniform heat distribution during the engraving process and reduces the risk of heat accumulation. Existing technologies typically do not consider this factor, leading to inaccurate heat control and affecting engraving quality. By obtaining the density, specific heat capacity, and ambient temperature of the white oil block, and calculating the heat conduction path inertia coefficient based on the product of density, specific heat capacity, and heat conduction path length, the density and specific heat capacity of the white oil block reflect the material's heat storage capacity.The inertia coefficient of the heat conduction path reflects the speed and efficiency of heat conduction within the white oil block. By accurately calculating this inertia coefficient, the rate of heat accumulation can be more accurately predicted and controlled, thereby better regulating heat control during laser engraving. This invention can significantly improve the accuracy of thermal management, avoiding quality problems caused by excessive heat accumulation. The temperature difference between the ambient temperature and the upper limit of the material's heat resistance temperature is obtained. This temperature difference directly relates to the heat exchange rate between the white oil block and its surroundings, reflecting whether the material will deform or be damaged due to excessive heat. By calculating the temperature difference between the ambient temperature and the upper limit of the material's heat resistance temperature, it is possible to better predict and control the rate of heat accumulation during laser engraving. This invention provides a more precise reference for heat regulation, ensuring the stability of the white oil block during the engraving process. Existing technologies often rely solely on fixed working conditions, neglecting changes in environmental factors, thus lacking flexibility and easily leading to unnecessary damage. The first power correction coefficient is obtained by dividing the product of temperature difference and thermal conductivity by the inertia coefficient of the heat conduction path. By calculating the power correction coefficient, the laser power can be dynamically adjusted according to different working conditions and material properties, thereby achieving more precise heat control. Existing technologies typically have static laser power adjustment, failing to respond quickly to changes in different environments and materials. This invention effectively solves the problem of laser... Problems caused by inaccurate power adjustment during the engraving process are addressed by obtaining a first scanning speed correction coefficient based on the thickness value. The initial scanning speed and initial laser power in the initial laser parameters are then pre-adjusted based on these coefficients, resulting in pre-adjusted scanning speed and pre-adjusted laser power. Scanning speed directly affects the rate of heat accumulation during heat conduction; the greater the thickness, the faster the heat accumulation. Therefore, adjusting the scanning speed correction coefficient effectively controls the rate of heat conduction, preventing excessive heat accumulation. This invention allows for flexible adjustment of the scanning speed based on the actual thickness of the white oil block, avoiding overheating or excessively rapid heat transfer. By pre-adjusting the laser parameters, optimal laser power and scanning speed settings can be ensured before engraving begins, avoiding frequent adjustments during the engraving process, reducing the load on the laser system, and improving engraving efficiency and quality. Existing methods often require repeated trials and adjustments, wasting time and resources. This invention provides more precise initial parameter settings, improving overall work efficiency. Through precise heat conduction control, this invention avoids problems such as white oil block deformation and poor engraving results caused by excessive heat accumulation. It not only improves the stability and accuracy of the engraving process but also effectively increases production efficiency and reduces damage to equipment and materials. ,

[0026] In one embodiment, step S2, which involves constructing a real-time temperature field distribution model based on multiple regional temperature values, includes: S21. Divide the surface of the white oil block into multiple grid units, and set a corresponding temperature acquisition point in each grid unit; S22. Collect the first real-time temperature value of each temperature acquisition point using an infrared thermal imager; S23. Obtain the first coordinate information of each temperature acquisition point and the second coordinate information of each non-temperature acquisition point, and obtain the corresponding Euclidean distance for each first coordinate information and second coordinate information; S24. Based on the first real-time temperature values ​​and Euclidean distances of all temperature acquisition points within each grid cell, the second real-time temperature value of each non-temperature acquisition point within the corresponding grid cell is calculated using an inverse distance weighted interpolation algorithm. The calculation formula is as follows: ; Where D(WD2) represents the second real-time temperature value, and D(WD1) represents the second real-time temperature value. n O(JL) represents the nth first real-time temperature value. n This represents the nth Euclidean distance, where n represents the index of the temperature sampling point, and N represents the number of temperature sampling points. S25. Construct a real-time temperature field distribution model based on the coordinate information of each temperature acquisition point, the first real-time temperature value, and the second real-time temperature value, and supplement the temperature field data at different times through time series interpolation.

[0027] As described in steps S21-S25 above, the calculation formula for the second real-time temperature value is pre-normalized for parameters such as the corresponding output current and preliminary adjustment parameters to eliminate dimensional differences between different variables. The purpose is to ensure that all variables are on the same order of magnitude, thereby making the calculation more stable and effective. The regional temperature value of each grid cell includes the first real-time temperature value from multiple temperature acquisition points and the second real-time temperature value from non-temperature acquisition points. This invention, through inverse distance weighted interpolation, can accurately estimate the temperature of all areas on the surface of the white oil block (including areas not directly acquired) using limited temperature data from acquisition points, thus constructing a continuous and complete real-time temperature field distribution model. This provides a basis for subsequent assessment of heat accumulation risk and adjustment of the laser. The parameters provide comprehensive temperature data support. The above formula indicates that the second real-time temperature value of any non-temperature acquisition point is equal to the sum of the products of the first real-time temperature values ​​of all temperature acquisition points surrounding that non-temperature acquisition point within the same grid cell and their corresponding weights, divided by the sum of all weights, where the weights are the Euclidean distance. This invention divides the surface of the white oil block into multiple grid cells and sets a corresponding temperature acquisition point in each grid cell. By dividing the surface of the white oil block into multiple grid cells, more refined and localized monitoring of the surface temperature of the white oil block can be achieved. Existing technologies typically only monitor temperature in local areas or on the entire surface, making it difficult to obtain fine temperature changes within local areas. However, this invention, through gridding, can obtain... Real-time temperature data for each region provides a more accurate data foundation for subsequent temperature field distribution models, avoiding overheating and deformation problems caused by localized heat accumulation. Setting temperature acquisition points for each grid cell helps to monitor temperature changes in each region more evenly and accurately. This refined design can capture more details of temperature changes, especially in localized high-temperature areas generated during laser engraving. Traditional technologies typically only set temperature sensors at a few points, and the collected temperature data may not be comprehensive enough to reflect the heat distribution of the entire processing area. This invention, by increasing the number of temperature acquisition points and combining them with a gridded design, can obtain higher resolution and more comprehensive temperature data, thereby more effectively avoiding localized heat accumulation. To address the issue of temperature accumulation, this method involves acquiring the first real-time temperature value at each temperature acquisition point using an infrared thermal imager. It then obtains the first coordinate information of each temperature acquisition point and the second coordinate information of each non-temperature acquisition point, and calculates the corresponding Euclidean distance for each of these coordinates. Finally, it uses an inverse distance weighted interpolation algorithm to calculate the second real-time temperature value of each non-temperature acquisition point within each grid cell, based on the first real-time temperature values ​​and Euclidean distances of all temperature acquisition points within that grid cell. By acquiring the coordinate information of both temperature and non-temperature acquisition points, the temperature data can be correlated with spatial location, providing necessary spatial information for subsequent interpolation algorithms. This gives the temperature data not only a temporal dimension but also a spatial dimension. In existing technologies...Temperature data may be separated from spatial location, making it difficult to accurately represent the spatial distribution of the temperature field. By acquiring coordinate information, this invention can more accurately depict the spatial distribution of the temperature field, solving the problem of mismatch between temperature data and physical location in existing technologies. The inverse distance weighted interpolation algorithm can obtain smoother and more accurate temperature interpolation results by weighting the Euclidean distance between different temperature acquisition points. The closer the acquisition points are, the greater their influence on the interpolation results, thus better reflecting local temperature changes. In contrast, existing temperature interpolation algorithms may not fully consider spatial distance factors, resulting in lower accuracy of temperature prediction results. This invention, by employing Euclidean distance and inverse distance weighted algorithms, can accurately weight the influence of each sampling point on surrounding points, thereby improving the prediction accuracy of the temperature field distribution and avoiding the problem of excessive local heat accumulation. A real-time temperature field distribution model is constructed based on the coordinate information of each temperature sampling point, the first real-time temperature value, and the second real-time temperature value. Time series interpolation is used to supplement the temperature field data at different times. By constructing the real-time temperature field distribution model, the heat conduction process between the white oil block surface and the PCB substrate can be described more accurately. The real-time temperature field distribution model can not only be updated in real time but also provide data for subsequent temperature control design and optimization. Traditional methods typically only provide local or average temperature data, making it difficult to form a global temperature field model. This invention, however, constructs a real-time temperature field distribution model, dynamically reflecting temperature changes during laser engraving and providing more accurate feedback data for the thermal control system. This reduces the risks of overheating, deformation, and performance degradation. Time-series interpolation technology supplements missing data between different time points, forming a continuous temperature change curve, which helps to accurately predict temperature change trends and identify potential temperature control problems early. Traditional technologies, due to limitations in time intervals and acquisition frequencies, may not be able to obtain accurate temperature data between different time points. This invention, through time-series interpolation, supplements the temperature data at each moment, making the temperature field model more complete and providing a more accurate basis for real-time temperature control, ensuring the stability and reliability of the laser engraving process. This invention, by combining innovative methods such as mesh generation, temperature acquisition point setting, infrared thermal imaging technology, Euclidean distance weighted interpolation, and time-series interpolation, achieves more accurate and comprehensive temperature field distribution monitoring and optimization. Compared to existing technologies, it effectively solves the problem of heat accumulation during laser engraving, avoiding adverse consequences such as overheating and deformation, while improving engraving effects and the reliability of the circuit board.

[0028] In one embodiment, step S3, which involves obtaining the corresponding thermal accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value, includes: S31. Obtain the substrate type of the white oil block, and obtain the energy tolerance threshold based on the substrate type; S32. Obtain the corresponding energy exceedance coefficient based on the ratio of each energy density value to the energy tolerance threshold; S33. Obtain the position information of the corresponding laser action point according to each energy density value, and determine the position of the corresponding region according to each position information; S34. Input each of the regions into the real-time temperature field distribution model to obtain the corresponding region temperature value, and obtain the corresponding temperature risk coefficient based on the ratio of each region temperature value to the energy tolerance threshold. S35. Obtain the total surface area of ​​the white oil block; S36. Obtain the area of ​​the corresponding region according to the location of the region, and obtain the corresponding area ratio coefficient according to the ratio of the area of ​​each region to the total surface area; S37. Obtain the corresponding thermal accumulation risk coefficient by multiplying each of the area ratio coefficient, temperature risk coefficient, and energy excess coefficient.

[0029] As described in steps S31-S37 above, the substrate types include silicone-based white oil blocks, resin-based white oil blocks, and rubber-based white oil blocks. The silicone-based white oil blocks, resin-based white oil blocks, and rubber-based white oil blocks each have different energy tolerance thresholds. For example, the energy tolerance threshold for silicone-based white oil blocks is 5 J / cm², for resin-based white oil blocks it is 3.5 J / cm², and for rubber-based white oil blocks it is 4 J / cm². Based on the location information, the specific location of the laser application point can be determined. The location is determined by dividing the surface of the white oil block into multiple grid units, each corresponding to a different location. After determining the grid units, their coordinate information is input to the real-time temperature... In the temperature field distribution model, the corresponding regional temperature value can be obtained. This invention obtains the substrate type of the white oil block and the energy tolerance threshold based on the substrate type. By first identifying the substrate type of the white oil block and obtaining the energy tolerance threshold of that substrate, it is possible to ensure that the laser energy applied is within the tolerance range of the material. Different substrates have different energy tolerance limits. If the special properties of the substrate are not considered, laser treatment may cause the substrate to overheat or be damaged. This invention provides basic data for subsequent laser energy control by accurately determining the energy tolerance threshold of the substrate. The corresponding energy exceedance coefficient is obtained by the ratio of each energy density value to the energy tolerance threshold. By calculating the ratio of the energy density value to the energy tolerance threshold, the laser's effect on each region can be quantified. The energy applied to the area is assessed to determine if it exceeds the area's energy tolerance range. The energy exceedance coefficient provides a quantitative standard for subsequent risk prediction, effectively preventing excessive heat accumulation that could lead to material overheating and deformation. Compared to the simple adjustment methods of existing technologies, this meticulous energy control method can more precisely control the safety of laser action and reduce unnecessary heat accumulation. By obtaining the location information of the corresponding laser action point for each energy density value, and determining the corresponding area location based on each location information, the location information of the laser action point can be accurately tracked, thus revealing the heat distribution on the surface of the white oil block. This is crucial for subsequent temperature field modeling, ensuring that the heat distribution at each location can be accurately determined. Unlike existing technologies that do not consider laser heat distribution, this step effectively predicts the temperature of the laser processing area. By precisely locating the heat distribution region, the heat generated during laser processing is controlled more evenly. Determining the location of the corresponding region based on the laser's point of action helps to accurately divide different processing areas during temperature field modeling. This allows for precise calculation of temperature changes in each area, ensuring zoned management of the laser processing area. This effectively avoids localized overheating or heat accumulation, improving the precision of thermal management. By inputting the location of each area into the real-time temperature field distribution model, the corresponding temperature value is obtained. Through this real-time temperature field distribution model, temperature changes in each area can be predicted and controlled in real time during laser processing.Compared to existing technologies that typically rely on coarse control of laser parameters, this invention, by calculating temperature changes in different regions, can more accurately monitor the thermal impact of the laser on the material surface, thereby avoiding adverse effects due to overheating. It obtains a temperature risk coefficient based on the ratio of each region's temperature value to its energy tolerance threshold. This temperature risk coefficient provides a quantitative risk assessment of heat accumulation in different regions. If the region's temperature exceeds the substrate's energy tolerance threshold, the temperature risk coefficient increases, indicating a potential overheating problem in that region. Compared to traditional empirical adjustments, this method offers higher accuracy, enabling real-time prevention of thermal damage in actual production and improving the safety of the entire processing. The invention obtains the total surface area of ​​the white oil block, the area of ​​each corresponding region based on its location, and the area ratio coefficient based on the ratio of each region's area to the total surface area. The total surface area of ​​the white oil block serves as the foundation for calculating overall heat distribution and regional allocation. The ratio of the region's area to the total surface area reflects the proportion of heat distribution in different regions, and the area ratio coefficient represents the temperature risk and energy tolerance level. This invention provides a more refined area division, facilitating the adoption of different control measures for different areas during laser engraving. This avoids damage to the overall engraving effect due to localized overheating. The corresponding heat accumulation risk coefficient is obtained by multiplying each area proportion coefficient, temperature risk coefficient, and energy exceedance coefficient. By multiplying multiple risk coefficients (area proportion coefficient, temperature risk coefficient, and energy exceedance coefficient), a comprehensive heat accumulation risk coefficient is obtained, enabling a comprehensive assessment of the risk of heat accumulation. This comprehensive method is more comprehensive and precise than single control methods, allowing for dynamic adjustment of the processing strategy during laser engraving to avoid localized overheating and material deformation, ensuring both engraving effect and substrate safety. By accurately acquiring multiple parameters such as the substrate type, heat density, laser action location, and area of ​​the white oil block, and combining them with a real-time temperature field distribution model, this invention achieves more refined temperature control management, preventing material deformation, overheating, and performance degradation caused by heat accumulation. Compared to the coarse adjustment methods in existing technologies, this provides a more precise and efficient thermal management solution, improving the engraving effect and substrate reliability.

[0030] In one embodiment, step S3, which involves correcting the pre-adjusted laser parameters based on the thermal accumulation risk coefficient to obtain the corrected laser parameters, includes: S38. Obtain a preset risk threshold and a thermal accumulation risk coefficient, and obtain the risk coefficient difference based on the preset risk threshold and the thermal accumulation risk coefficient; S39. Obtain the linkage coefficient between laser power and scanning speed in the laser engraving system, and obtain the second scanning speed correction coefficient and the second power correction coefficient based on the difference between the linkage coefficient and the risk coefficient. S310. Obtain the pre-adjusted scanning speed and pre-adjusted laser power of the pre-adjusted laser parameters, and obtain the laser power adjustment amount according to the pre-adjusted laser power and the second power correction coefficient; S311. Obtain the scanning speed adjustment amount based on the pre-adjusted scanning speed and the second scanning speed correction coefficient, and correct and adjust the pre-adjusted scanning speed and pre-adjusted laser power in the pre-adjusted laser parameters based on the scanning speed adjustment amount and the laser power adjustment amount to obtain the corrected scanning speed and corrected laser power.

[0031] As described in steps S38-S311 above, this invention obtains a preset risk threshold and a heat accumulation risk coefficient, and then obtains a risk coefficient difference based on these two factors. By setting the preset risk threshold and heat accumulation risk coefficient, this invention can fundamentally quantify and control the heat accumulation during laser engraving. The risk coefficient difference allows for precise assessment of the gap between the current heat accumulation risk and the preset standard. Existing technologies typically lack a systematic risk assessment mechanism, while the calculation of the risk coefficient difference provides specific data support for subsequent adjustments. This quantitative difference can effectively guide the adjustment of laser power and scanning speed, thereby precisely controlling heat accumulation and avoiding damage to the PCB substrate. This invention addresses thermal damage by obtaining the linkage coefficient between laser power and scanning speed in a laser engraving system. Based on the difference between the linkage coefficient and the risk coefficient, a second scanning speed correction coefficient and a second power correction coefficient are derived. The linkage relationship between laser power and scanning speed is the core of laser engraving technology. This invention uses the linkage coefficient to accurately describe the relationship between power and scanning speed changes. In existing technologies, the linkage effect between the two is usually ignored or static settings are used. The linkage coefficient of this invention, through a dynamic feedback mechanism, can adjust the laser power and scanning speed in real time during the engraving process, thereby improving processing efficiency and accuracy, and avoiding overheating or localized heat accumulation. The second scanning speed is dynamically adjusted based on the difference between the linkage coefficient and the risk coefficient. The invention incorporates a degree correction coefficient and a second power correction coefficient. In practical operation, this invention can correct laser parameters in real time, reducing processing instability caused by heat buildup. Compared to the fixed settings of traditional technologies, this invention introduces an adaptive correction mechanism, making the engraving process more flexible and precise. Especially when handling different materials or processing scenarios, it can intelligently adjust to ensure the consistency and stability of the engraving effect. This is achieved by acquiring the pre-adjusted scanning speed and pre-adjusted laser power parameters, and obtaining the laser power adjustment amount based on the pre-adjusted laser power and the second power correction coefficient. Similarly, the scanning speed adjustment amount is obtained through the pre-adjusted scanning speed and the second scanning speed correction coefficient. The calculation of the laser power adjustment amount combines the pre-adjusted parameters and... A correction factor ensures that the laser power remains within a suitable range, preventing heat buildup caused by excessive power. In existing technologies, power is often set based on experience and rough adjustments, lacking a real-time feedback mechanism. This invention automatically and precisely adjusts the power, improving the stability of engraving quality and preventing PCB substrate damage caused by excessive or insufficient power. Through calculation of the scanning speed adjustment, it ensures coordinated adjustment of laser scanning speed and power. Existing technologies typically rely solely on experience to set the scanning speed, potentially leading to excessive heat buildup. The intelligent adjustment in this invention not only avoids dependence on a single factor but also effectively controls the scanning speed, reducing heat accumulation in localized areas and ensuring engraving quality.The pre-adjusted scanning speed and laser power in the pre-adjusted laser parameters are corrected based on the adjustment amounts of scanning speed and laser power to obtain corrected scanning speed and corrected laser power. Based on these adjustments, the preset parameters are precisely corrected to obtain corrected scanning speed and corrected laser power. This adjustment ensures optimization throughout the engraving process, avoiding the negative impacts of localized heat buildup. Compared to the simple fixed parameter adjustments in existing technologies, the adjustment mechanism of this invention is more flexible and precise, capable of optimization based on real-time feedback. This reduces material damage and substrate deformation caused by overheating, improving production efficiency and processing quality. By comprehensively controlling multiple factors such as laser power, scanning speed, and heat buildup, and introducing linkage and correction coefficients, this invention achieves automated and precise parameter adjustment, significantly improving the quality, efficiency, and safety of laser engraving. Compared to existing technologies, this invention not only solves the problems of white paint blocks and PCB substrate deformation caused by heat buildup but also improves processing adaptability and accuracy, reduces risks in the production process, and enhances the overall system reliability.

[0032] In one embodiment, step S4, which involves obtaining scanning path adjustment parameters based on the thermal accumulation risk coefficient and replanning the initial laser engraving path based on the scanning path adjustment parameters to obtain an adjusted laser engraving path, includes: S41. Obtain the thermal conductivity, thickness, and upper limit of heat resistance temperature of the white oil block, and obtain the scanning interval based on the thickness and heat accumulation risk coefficient. S42. Obtain the position and temperature information of the corresponding laser point of action based on the heat accumulation risk coefficient, and obtain the temperature gradient vector of the laser point of action based on the temperature and position information. S43. Obtain the temperature gradient direction angle based on the temperature gradient vector, and obtain the scanning direction angle based on the temperature gradient direction angle and the heat accumulation risk coefficient; S44. Obtain the temperature coefficient ratio based on the temperature information and the upper limit of the heat resistance temperature, and obtain the hot spot avoidance distance based on the thermal conductivity and the temperature coefficient ratio; S45. Determine the direction of the new scan line according to the scan direction angle, and arrange the spacing of the new scan line according to the scan spacing. S46. Based on the hotspot avoidance distance, plan a new jump path between areas, and based on the new jump path, new scan line direction and new scan line spacing, replan the initial laser engraving path to obtain an adjusted laser engraving path.

[0033] As described in steps S41-S46 above, the calculation of the hotspot avoidance distance involves normalizing parameters such as the corresponding output current and preliminary adjustment parameters beforehand to eliminate dimensional differences between different variables. The purpose is to ensure that all variables are on the same order of magnitude, thereby making the calculation more stable and effective. The hotspot avoidance distance refers to the minimum distance that the laser must maintain when jumping from the current engraving area to the next area (to avoid passing through high-risk hotspot areas). The scanning direction angle refers to the angle between the scanning line and the positive x-axis (controlling the direction of the scanning line extension to reduce heat accumulation in a single direction). The scanning spacing refers to the perpendicular distance between two adjacent scanning lines (controlling the number of laser actions per unit area; the higher the risk, the larger the spacing to disperse heat). Planning... The specific method involves initial path transitions between regions typically being straight lines (potentially passing through hotspot areas). Therefore, the transition path needs to be adjusted based on hotspot avoidance distances. Safe engraving zones are defined based on these distances, eliminating high-risk areas. Initial laser engraving paths are usually planned according to continuous coverage principles (e.g., from left to right, top to bottom), which may include areas with high heat accumulation risk. Therefore, safe zones must first be selected based on hotspot avoidance distances. High-risk hotspot areas are marked according to a real-time temperature field distribution model. The shortest distance between all engraving points and hotspot areas in the initial path is calculated. If the distance between an engraving point and a hotspot area is less than the hotspot avoidance distance, that point is removed from the initial path (or marked as a temporarily unengaged area). The remaining area is the safe engraving zone. The basic scope of path replanning (ensuring that the laser action area is outside the hotspot avoidance distance of the hotspot area to avoid heat conduction superposition); the initial path scanning direction is usually fixed (e.g., along the X-axis), which easily leads to heat accumulation along the scanning direction. Therefore, the scanning line direction needs to be adjusted according to the scanning direction angle. For each safe engraving area, the extension direction of the scanning line is determined according to its scanning direction angle to ensure that the scanning direction is oblique to the temperature gradient direction; the initial path scanning spacing is usually fixed, which cannot adapt to the heat tolerance of different risk areas. Therefore, it needs to be dynamically adjusted according to the scanning spacing. When arranging the scanning lines, it is necessary to ensure that they cover the entire safe engraving area and that adjacent scanning lines do not overlap (the length of the scanning line at the edge is truncated according to the area contour). This invention obtains the white oil block This invention optimizes the scanning spacing by quantifying the thermal conductivity, thickness, and upper limit of heat resistance temperature. The scanning spacing is determined based on the thickness and a thermal accumulation risk coefficient, which are closely related. By combining these two factors, the scanning spacing can be precisely adjusted. Thinner areas have a lower risk of thermal accumulation, thus allowing for a smaller scanning spacing to improve processing efficiency. Thicker areas may require a larger scanning spacing to avoid overheating. This improves the accuracy of thermal management and the engraving effect. The thermal accumulation risk coefficient is used to obtain the position and temperature information of the corresponding laser point, and the temperature gradient vector of that laser point is then calculated based on the temperature and position information.By using a thermal accumulation risk coefficient to pinpoint the precise location of the laser's point of impact, the laser engraving process becomes more efficient and targeted. The positioning of the laser point no longer relies on simple rules but is dynamically adjusted based on actual thermal accumulation risks. Obtaining temperature information helps to adjust the laser engraving process in real time, avoiding localized overheating and reducing thermal damage. This information allows for more precise control of heat distribution, thereby ensuring both engraving quality and material safety. Traditional techniques typically cannot monitor the temperature of the laser's point of impact in real time or can only use localized temperature sensors. This invention, guided by a thermal accumulation risk coefficient, makes the laser point of impact more accurate, avoiding the overheating risks of traditional methods. The temperature gradient reflects the changes in heat within the engraving area, and through calculation... A temperature gradient vector provides a clearer picture of the direction and speed of heat propagation, allowing for precise adjustment of the laser's action. Utilizing temperature gradients can prevent overheating of localized areas, avoid concentrated heat buildup, and reduce the risk of thermal damage. Unlike existing technologies that simply control laser power to prevent heat accumulation, the introduction of a temperature gradient vector refines the heat distribution, making thermal management more precise and better controlling heat diffusion, thus avoiding uneven heating. The temperature gradient vector is used to obtain the temperature gradient direction angle, and based on this angle and a heat accumulation risk coefficient, the scanning direction angle is determined. This temperature gradient direction angle then determines the direction of heat propagation, effectively controlling the laser's scanning path to minimize the possibility of heat accumulation. By clearly defining the direction of heat propagation, the laser engraving path can be optimized based on the heat propagation trend, thereby avoiding prolonged laser action on the same area and reducing the risk of overheating. Compared to traditional fixed scanning paths or experience-based path adjustments, this invention can dynamically plan the scanning path based on real-time temperature information, significantly improving processing accuracy and heat management efficiency. By dynamically adjusting the scanning direction through the temperature gradient direction angle and the heat accumulation risk coefficient, it ensures that heat does not concentrate in one point or area for a long time, avoiding problems such as overheating and damage of white oil blocks caused by heat accumulation. In contrast, the scanning direction in traditional technologies is often fixed and fails to fully consider the influence of heat accumulation and temperature gradient. This invention can dynamically adjust the scanning direction to ensure more precise laser engraving. Furthermore, it is highly efficient. By obtaining the temperature coefficient ratio from temperature information and the upper limit of heat resistance temperature, and calculating the hotspot avoidance distance based on thermal conductivity and the temperature coefficient ratio, the laser's working state can be adjusted according to the material's heat resistance characteristics and the actual processing temperature. This prevents overheating from affecting the material itself or downstream components. The combination of the upper limit of heat resistance temperature and the temperature coefficient ratio allows for a more scientific determination of the temperature control range, avoiding material damage caused by excessively high temperatures. More precise control of the processing temperature through the temperature coefficient ratio not only improves processing quality but also significantly enhances the system's safety and reliability. Calculating the hotspot avoidance distance using thermal conductivity and the temperature coefficient ratio allows for better control of heat distribution, preventing irreversible damage caused by heat concentration in small areas.This invention effectively prevents overheating of white oil blocks due to heat concentration, thereby improving engraving accuracy and material lifespan. Existing technologies typically employ fixed avoidance strategies, while this invention allows for more precise adjustment of the calculated avoidance distance, significantly improving the rationality of the engraving path and reducing unnecessary thermal damage. The new scan line direction is determined by the scanning direction angle, and the new scan line spacing is arranged according to the scanning interval. New jump paths between areas are planned using hotspot avoidance distances, and the initial laser engraving path is replanned based on the new jump paths, new scan line directions, and new scan line spacing to obtain an adjusted laser engraving path. Through dynamic adjustments of the scanning direction angle and scanning interval, the laser engraving path can be controlled more flexibly and precisely, avoiding overheating or engraving errors. The rational arrangement of line spacing can improve processing efficiency, reduce processing time, and ensure engraving quality. Compared with traditional fixed-path engraving techniques, this invention can adjust in real time according to the processing situation, making the engraving process more efficient and precise while avoiding material damage. The replanned jump path can effectively avoid heat accumulation and unnecessary thermal damage. By rationally adjusting the jump path, the heat distribution during processing can be controlled more precisely. Through path replanning, more efficient and accurate engraving can be achieved in different areas and on different materials, further improving product quality. The path planning in traditional technologies is usually relatively fixed and lacks dynamic adjustment for heat accumulation and material properties. This invention can flexibly adjust based on real-time data, thereby significantly improving processing efficiency and accuracy.

[0034] In one embodiment, step S5, which involves obtaining the carving effect evaluation index based on the depth information and grayscale image information, includes: S51. Obtain the actual depth and preset standard depth of the white oil block carving area based on the depth information, and calculate the scratch depth deviation rate by dividing the difference between the actual depth and the preset standard depth by the preset standard depth. S52. Obtain the standard carving edge line of the white oil block carving area, and obtain the standard edge length based on the standard carving edge line; S53. Extract edge contour lines from the grayscale image information, and extract the coordinates of multiple sampling points on the edge contour lines; S54. Obtain the vertical distance from the coordinates of each sampling point to the standard engraved edge line, and obtain the average deviation distance based on the multiple vertical distances; S55. Obtain the edge flatness deviation rate based on the ratio of the average deviation distance to the standard edge length, and calculate the carving effect evaluation index by weighted summation based on the edge flatness deviation rate and the scratch depth deviation rate.

[0035] As described in steps S51-S55 above, this invention obtains the actual depth and preset standard depth of the white oil block carving area through depth information. Obtaining the actual depth of the white oil block carving area is to ensure the accuracy of the carving process. By comparing it with the preset standard depth, depth errors can be detected, allowing for necessary adjustments and avoiding over-carving or shallow carving. Existing technologies often control carving depth by adjusting laser power and scanning speed, but lack a mechanism for directly obtaining depth information. This depth information acquisition method has higher precision, accurately assessing the difference between the actual carving depth and the standard depth. This invention can quantify deviations in carving effects, promptly detect depth problems, and effectively avoid issues caused by inadequate depth control. This invention addresses carving quality issues caused by inaccuracies, improving the consistency and precision of carved products. It calculates the score depth deviation rate by dividing the difference between the actual depth and the preset standard depth by the preset standard depth. This deviation rate quantitatively describes the degree of error in carving depth, providing a clear basis for subsequent adjustments. In existing technologies, adjustments may rely solely on experience, while this invention uses a numerical deviation rate to more scientifically and accurately measure carving quality. This allows for rapid assessment of the carving process's precision, ensuring that the carving meets predetermined standards, reducing errors from human judgment, and improving the reliability of the carving process. The invention also obtains the standard carving edge line of the white oil block carving area and calculates the standard edge length based on this standard edge line. A straight line serves as a baseline, providing a reference for subsequent measurements of edge smoothness and deviation. Existing technologies may only focus on depth adjustment, neglecting the precision of edge morphology. This invention, by defining a standard edge line, provides an accurate benchmark for edge morphology evaluation, ensuring structural consistency of the carved area's edges, thus improving the overall carving effect and avoiding irregular edge shapes. The standard edge length provides a necessary reference for subsequent calculations of edge smoothness deviation rate, clearly defining the actual edge length and providing a quantitative standard for edge smoothness. By obtaining the standard edge length, the morphology of the carved edge can be quantified, helping to improve edge standardization during the carving process and avoid defects caused by deviations. Edges are extracted from grayscale image information. The contour line is extracted, and the coordinates of multiple sampling points on the edge contour line are obtained. By acquiring the vertical distance from each sampling point coordinate to the standard sculpted edge line, and calculating the average deviation distance based on multiple vertical distances, the edge contour line is extracted through grayscale image analysis. This allows for precise capture of the edge morphology of the sculpted area, providing data support for subsequent deviation analysis. Uniform sampling along the edge contour line yields more detailed edge information, resulting in more accurate flatness analysis. The introduction of multiple sampling points improves the accuracy of edge evaluation, capturing more subtle edge morphological changes and providing more accurate flatness analysis results. The deviation between the sampling point and the standard edge is measured by the vertical distance, providing a numerical basis for subsequent edge flatness calculations.This allows for the quantification of the deviation of each sampling point from the standard edge, making the evaluation of edge morphology deviation more accurate and avoiding vague manual estimation. By calculating the average of multiple vertical distances, the overall smoothness of the edge can be evaluated more comprehensively and objectively. The average deviation distance allows for a comprehensive evaluation of the edge smoothness of the entire carving area, thereby improving the consistency and stability of carving quality. The edge smoothness deviation rate is obtained by the ratio of the average deviation distance to the standard edge length. A carving effect evaluation index is obtained by weighted summation of the edge smoothness deviation rate and the scratch depth deviation rate. The calculation of the edge smoothness deviation rate visually displays the edge smoothness deviation during the carving process, guiding subsequent optimization. This invention provides a quantitative assessment of edge smoothness, offering precise guidance for subsequent carving quality control. This invention provides accurate reference and avoids the adverse effects of irregular edges. By calculating a weighted summation index, it comprehensively considers both depth and edge errors, resulting in a comprehensive and accurate engraving quality score. Existing technologies often focus only on a single parameter such as engraving depth or edge accuracy. This invention, by comprehensively considering the deviations of both, provides a more comprehensive evaluation. This comprehensive evaluation avoids the biases that may arise from a single indicator, reflecting the engraving effect more fully and facilitating timely adjustments during production to improve overall processing quality. This invention offers efficient and precise engraving quality control, avoiding the thermal deformation problems caused by heat accumulation during laser engraving in existing technologies. It also effectively improves the stability and accuracy of engraving depth and edge flatness, thereby enhancing the processing effect and reliability of white paint blocks and PCB substrates.

[0036] In one embodiment, step S6, which generates a laser energy adaptation model based on the engraving effect evaluation index, the real-time temperature field distribution model, the corrected laser parameters, and the adjusted laser engraving path, includes: S61. Obtain the highest temperature value according to the real-time temperature field distribution model, and obtain the scanning path parameters according to the laser engraving path adjustment. S62. Obtain multiple sets of engraving data for white oil blocks of different types and thicknesses, and divide the multiple sets of engraving data into training set and validation set, wherein the engraving data includes engraving effect evaluation index, maximum temperature value, corrected laser parameters and scanning path parameters; S63. The initial adaptation model is constructed using the random forest algorithm, and the training set is input into the initial adaptation model for training. The hyperparameters of the model are optimized by the grid search method to obtain the preliminary adaptation model. S64. Input the validation set data into the initial adaptation model for validation, obtain the model output result, and determine whether the model output result is within the preset threshold range. If the model output is not within the preset threshold range, return to the step of inputting the training set into the initial adapted model for training and optimizing the hyperparameters of the model using the grid search method until the model output is within the preset threshold range. If the output of the model is within a preset threshold range, then the preliminary adaptation model is determined as the laser energy adaptation model.

[0037] As described in steps S61-S64 above, the optimization of model hyperparameters using the grid search method is specifically because hyperparameters directly affect model performance. Therefore, it is necessary to determine the optimal combination through grid search. First, the hyperparameters to be optimized and their range are determined. The hyperparameters to be optimized include the number of decision trees (affecting the model's fitting ability), the maximum depth (controlling the complexity of the trees and avoiding overfitting), and the minimum number of leaf node samples (controlling the precision of the leaf nodes). Then, a random forest model is trained for each combination of hyperparameters. The parameter prediction error of each model on the training set is calculated (error = |predicted value - actual value| / actual value). Finally, the combination with the smallest error is selected as the final hyperparameters.

[0038] This invention obtains the maximum temperature value through a real-time temperature field distribution model and acquires scanning path parameters based on adjustments to the laser engraving path. It obtains multiple sets of engraving data for white oil blocks of different types and thicknesses, dividing these data into training and validation sets. The engraving data includes an engraving effect evaluation index, the maximum temperature value, corrected laser parameters, and scanning path parameters. An initial adaptation model is constructed using a random forest algorithm. By acquiring multiple sets of engraving data and dividing them into training and validation sets, diverse working condition data can be provided, ensuring the model can adapt to white oil blocks of different thicknesses and types. By comprehensively considering the engraving effect evaluation index, maximum temperature value, corrected laser parameters, and scanning path parameters in the data, the model... Training doesn't rely solely on single process parameters but considers comprehensive influencing factors. This makes the model training process more holistic, fully reflecting the combined impact of multiple factors on the carving effect, improving the model's prediction accuracy. The training set is input into the initial fitted model for training, and the model's hyperparameters are optimized using a grid search method to obtain the preliminary fitted model. The grid search method automatically adjusts the model's hyperparameters, enabling the model to reach optimal performance during training. Compared to traditional manual parameter tuning, it significantly improves the model's optimization efficiency. By automatically searching for optimal hyperparameters, it not only reduces the cost of manual intervention but also finds the optimal parameter combination through multiple experiments, thereby improving the model's accuracy and... Compared to the fixed parameter settings in traditional techniques, the grid search method significantly improves the adaptability and consistency of the laser engraving process, especially when dealing with white oil blocks of varying thicknesses and types, ensuring better engraving quality. The process involves inputting validation set data into the initial adaptation model for verification, obtaining the model output, and determining if the output falls within a preset threshold range. If the output is not within this range, the process returns to inputting the training set into the initial adaptation model for training and optimizing the hyperparameters using the grid search method until the output falls within the preset threshold range. If the output is within the preset threshold range, the initial adaptation model is determined to be the laser energy... The adaptive model, by inputting validation set data into the initial adaptive model for verification, can test the model's generalization ability on unseen data. It can effectively determine whether the model exhibits ideal adaptability in actual working conditions. By judging whether the model output is within a preset threshold range, it can ensure the quality control of the engraving process. If the output result does not meet the requirements, the model can be optimized by retraining and adjusting hyperparameters, thereby continuously improving the engraving accuracy, ensuring the model's adaptability, and gradually approaching the ideal output result. It avoids the accumulation of engraving errors caused by the imperfection of the initial model, significantly improves the engraving accuracy, avoids overheating, and ensures the stability of the PCB substrate, ultimately improving the performance and reliability of the product.

[0039] like Figure 2As shown, this application also provides a laser energy adaptation system for different types and thicknesses of white oil blocks, including: The pre-adjustment module is used to acquire the initial laser parameters, initial laser engraving path, and type and thickness parameters of the white oil block of the laser engraving system, and to pre-adjust the initial laser parameters according to the type and thickness parameters to obtain the pre-adjusted laser parameters. The module is used to start the laser engraving system based on the pre-adjusted laser parameters to collect the temperature values ​​of multiple areas on the surface of the white oil block and the energy density value of each laser action point on the initial laser engraving path in real time, and to construct a real-time temperature field distribution model based on the multiple area temperature values. The judgment module is used to obtain the corresponding heat accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value, and to determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the heat accumulation risk coefficient exceeds the preset risk threshold, it is determined that the heat accumulation at the laser action point is serious, and the pre-adjusted laser parameters are corrected according to the heat accumulation risk coefficient to obtain the corrected laser parameters. The planning module is used to obtain scanning path adjustment parameters based on the heat accumulation risk coefficient, and to replan the initial laser engraving path based on the scanning path adjustment parameters to obtain an adjusted laser engraving path. The scanning path adjustment parameters include scanning direction angle, hot spot avoidance distance, and scanning spacing. The acquisition module is used to acquire depth information and grayscale image information of the white oil block engraving area in real time based on the corrected laser parameters and adjusted laser engraving path, and to obtain an engraving effect evaluation index based on the depth information and grayscale image information; The generation module is used to generate a laser energy adaptation model based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

[0040] In one embodiment, the pre-adjustment module includes: The first acquisition unit is used to acquire the substrate type of the white oil block according to the type parameter, and to acquire the corresponding thermal conductivity and upper limit of heat resistance temperature according to the substrate type. The second acquisition unit is used to acquire the laser incident angle of the laser engraving system; The third acquisition unit is used to acquire the thickness value of the white oil block according to the thickness parameter, and to acquire the heat conduction path length according to the thickness value and the laser incident angle. The fourth acquisition unit is used to acquire the density, specific heat capacity and ambient temperature of the white oil block, and to acquire the inertia coefficient of the heat conduction path based on the density, specific heat capacity and heat conduction path length. The fifth acquisition unit is used to acquire the temperature difference based on the ambient temperature and the upper limit of the heat resistance temperature, and to acquire the first power correction coefficient based on the temperature difference, thermal conductivity and heat conduction path inertia coefficient. The pre-adjustment unit is used to obtain a first scanning speed correction coefficient based on the thickness value, and to pre-adjust the initial scanning speed and initial laser power in the initial laser parameters based on the first scanning speed correction coefficient and the first power correction coefficient, respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

[0041] It should be noted that each module and unit in the laser energy adaptation system for different types and thicknesses of white oil blocks corresponds one-to-one with the steps in the laser energy adaptation method for different types and thicknesses of white oil blocks.

[0042] like Figure 3 As shown, this application also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores all data required for the laser energy adaptation method for different types and thicknesses of white oil blocks. The network interface is used for communication with external terminals via a network connection. When the processor executes the computer program, it implements the laser energy adaptation method for different types and thicknesses of white oil blocks.

[0043] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment on which the present application is applied.

[0044] An embodiment of this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the laser energy adaptation method for different types and thicknesses of any of the above-mentioned white oil blocks.

[0045] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0046] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0047] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for adapting laser energy to different types and thicknesses of white oil blocks, characterized in that, include: The initial laser parameters, initial laser engraving path, and type and thickness parameters of the white paint block of the laser engraving system are obtained, and the initial laser parameters are pre-adjusted according to the type and thickness parameters to obtain the pre-adjusted laser parameters. The laser engraving system is started based on the pre-adjusted laser parameters, and the temperature values ​​of multiple areas on the surface of the white oil block and the energy density values ​​of each laser action point on the initial laser engraving path are collected in real time. A real-time temperature field distribution model is constructed based on the multiple temperature values ​​of the areas. Based on the real-time temperature field distribution model and each energy density value, obtain the corresponding heat accumulation risk coefficient, and determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the thermal accumulation risk coefficient exceeds the preset risk threshold, the pre-adjusted laser parameters are corrected and adjusted according to the thermal accumulation risk coefficient to obtain the corrected laser parameters; The scanning path adjustment parameters are obtained based on the heat accumulation risk coefficient, and the initial laser engraving path is replanned based on the scanning path adjustment parameters to obtain the adjusted laser engraving path. The scanning path adjustment parameters include scanning direction angle, hot spot avoidance distance and scanning spacing. Based on the corrected laser parameters and adjusted laser engraving path, the depth information and grayscale image information of the white oil block engraving area are collected in real time, and the engraving effect evaluation index is obtained based on the depth information and grayscale image information. Based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, a laser energy adaptation model is generated so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

2. The laser energy adaptation method for different types and thicknesses of white oil blocks according to claim 1, characterized in that, The step of pre-adjusting the initial laser parameters according to the type parameters and thickness parameters to obtain the pre-adjusted laser parameters includes: The substrate type of the white oil block is obtained according to the type parameters, and the corresponding thermal conductivity and upper limit of heat resistance temperature are obtained according to the substrate type. Obtain the laser incident angle of the laser engraving system; The thickness value of the white oil block is obtained based on the thickness parameter, and the length of the heat conduction path is obtained based on the thickness value and the laser incident angle. The density, specific heat capacity, and ambient temperature of the white oil block are obtained, and the inertia coefficient of the heat conduction path is obtained based on the density, specific heat capacity, and heat conduction path length. The temperature difference is obtained based on the ambient temperature and the upper limit of the heat resistance temperature, and the first power correction coefficient is obtained based on the temperature difference, the thermal conductivity and the inertia coefficient of the heat conduction path. The first scanning speed correction coefficient is obtained based on the thickness value, and the initial scanning speed and initial laser power in the initial laser parameters are pre-adjusted based on the first scanning speed correction coefficient and the first power correction coefficient, respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

3. The laser energy adaptation method for different types and thicknesses of white oil blocks according to claim 1, characterized in that, The step of obtaining the corresponding thermal accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value includes: Obtain the substrate type of the white oil block, and obtain the energy tolerance threshold based on the substrate type; The corresponding energy exceedance coefficient is obtained based on each energy density value and energy tolerance threshold. The location information of the corresponding laser action point is obtained based on each energy density value, and the location of the corresponding region is determined based on each location information. Each of the aforementioned regions is input into the real-time temperature field distribution model to obtain the corresponding region temperature value, and the corresponding temperature risk coefficient is obtained based on each region temperature value and energy tolerance threshold. Obtain the total surface area of ​​the white oil block; The area of ​​the corresponding region is obtained based on the location of the region, and the area ratio coefficient is obtained based on the area of ​​each region and the total surface area. The corresponding thermal accumulation risk coefficient is obtained based on each of the area proportion coefficient, temperature risk coefficient, and energy excess coefficient.

4. The laser energy adaptation method for different types and thicknesses of white oil blocks according to claim 1, characterized in that, The step of obtaining the scanning path adjustment parameters based on the thermal accumulation risk coefficient, and replanning the initial laser engraving path based on the scanning path adjustment parameters to obtain the adjusted laser engraving path includes: The thermal conductivity, thickness, and upper limit of the heat resistance temperature of the white oil block are obtained, and the scanning interval is obtained based on the thickness value and the heat accumulation risk coefficient. Based on the heat accumulation risk coefficient, obtain the location and temperature information of the corresponding laser impact point, and obtain the temperature gradient vector of the laser impact point based on the temperature and location information; The temperature gradient direction angle is obtained based on the temperature gradient vector, and the scanning direction angle is obtained based on the temperature gradient direction angle and the heat accumulation risk coefficient. The temperature coefficient ratio is obtained based on the temperature information and the upper limit of the heat resistance temperature, and the hot spot avoidance distance is obtained based on the thermal conductivity and the temperature coefficient ratio. The direction of the new scan line is determined according to the scan direction angle, and the spacing of the new scan line is arranged according to the scan spacing. Based on the hotspot avoidance distance, a new jump path is planned between the planned areas, and the initial laser engraving path is replanned based on the new jump path, the new scan line direction, and the new scan line spacing to obtain an adjusted laser engraving path.

5. The laser energy adaptation method for different types and thicknesses of white oil blocks according to claim 1, characterized in that, The step of obtaining the carving effect evaluation index based on the depth information and grayscale image information includes: The actual depth and preset standard depth of the white oil block carving area are obtained based on the depth information, and the scratch depth deviation rate is obtained based on the actual depth and preset standard depth. Obtain the standard carving edge line of the white oil block carving area, and obtain the standard edge length based on the standard carving edge line; The edge contour lines are extracted from the grayscale image information, and the coordinates of multiple sampling points on the edge contour lines are extracted; Obtain the vertical distance from the coordinates of each sampling point to the standard engraved edge line, and obtain the average deviation distance based on multiple vertical distances; The edge flatness deviation rate is obtained based on the average deviation distance and standard edge length, and the engraving effect evaluation index is obtained based on the edge flatness deviation rate and the scratch depth deviation rate.

6. The laser energy adaptation method for different types and thicknesses of white oil blocks according to claim 1, characterized in that, The step of generating a laser energy adaptation model based on the engraving effect evaluation index, the real-time temperature field distribution model, the corrected laser parameters, and the adjusted laser engraving path includes: The highest temperature value is obtained based on the real-time temperature field distribution model, and the scanning path parameters are obtained based on the adjustment of the laser engraving path. Multiple sets of engraving data for white oil blocks of different types and thicknesses are obtained, and the multiple sets of engraving data are divided into training set and validation set. The engraving data includes engraving effect evaluation index, maximum temperature value, corrected laser parameters and scanning path parameters. An initial fitting model was constructed using the random forest algorithm, and the training set was input into the initial fitting model for training. The hyperparameters of the model were then optimized using the grid search method to obtain the preliminary fitting model. The validation set data is input into the initial adaptation model for validation, and the model output result is obtained. It is then determined whether the model output result is within a preset threshold range. If the model output is not within the preset threshold range, return to the step of inputting the training set into the initial adapted model for training and optimizing the hyperparameters of the model using the grid search method until the model output is within the preset threshold range. If the output of the model is within a preset threshold range, then the preliminary adaptation model is determined as the laser energy adaptation model.

7. A laser energy adaptation system for different types and thicknesses of white oil blocks, characterized in that, include The pre-adjustment module is used to acquire the initial laser parameters, initial laser engraving path, and type and thickness parameters of the white oil block of the laser engraving system, and to pre-adjust the initial laser parameters according to the type and thickness parameters to obtain the pre-adjusted laser parameters. The module is used to start the laser engraving system based on the pre-adjusted laser parameters to collect the temperature values ​​of multiple areas on the surface of the white oil block and the energy density value of each laser action point on the initial laser engraving path in real time, and to construct a real-time temperature field distribution model based on the multiple area temperature values. The judgment module is used to obtain the corresponding heat accumulation risk coefficient based on the real-time temperature field distribution model and each energy density value, and to determine whether each heat accumulation risk coefficient exceeds a preset risk threshold. If the thermal accumulation risk coefficient exceeds the preset risk threshold, the pre-adjusted laser parameters are corrected and adjusted according to the thermal accumulation risk coefficient to obtain the corrected laser parameters; The planning module is used to obtain scanning path adjustment parameters based on the heat accumulation risk coefficient, and to replan the initial laser engraving path based on the scanning path adjustment parameters to obtain an adjusted laser engraving path. The scanning path adjustment parameters include scanning direction angle, hot spot avoidance distance, and scanning spacing. The acquisition module is used to acquire depth information and grayscale image information of the white oil block engraving area in real time based on the corrected laser parameters and adjusted laser engraving path, and to obtain an engraving effect evaluation index based on the depth information and grayscale image information; The generation module is used to generate a laser energy adaptation model based on the engraving effect evaluation index, real-time temperature field distribution model, corrected laser parameters, and adjusted laser engraving path, so that the laser engraving system can adapt the laser energy to white oil blocks of different types and thicknesses according to the laser energy adaptation model.

8. The laser energy adaptation system for different types and thicknesses of white oil blocks according to claim 7, characterized in that, The pre-adjustment module includes: The first acquisition unit is used to acquire the substrate type of the white oil block according to the type parameter, and to acquire the corresponding thermal conductivity and upper limit of heat resistance temperature according to the substrate type. The second acquisition unit is used to acquire the laser incident angle of the laser engraving system; The third acquisition unit is used to acquire the thickness value of the white oil block according to the thickness parameter, and to acquire the heat conduction path length according to the thickness value and the laser incident angle. The fourth acquisition unit is used to acquire the density, specific heat capacity and ambient temperature of the white oil block, and to acquire the inertia coefficient of the heat conduction path based on the density, specific heat capacity and heat conduction path length. The fifth acquisition unit is used to acquire the temperature difference based on the ambient temperature and the upper limit of the heat resistance temperature, and to acquire the first power correction coefficient based on the temperature difference, thermal conductivity and heat conduction path inertia coefficient. The pre-adjustment unit is used to obtain a first scanning speed correction coefficient based on the thickness value, and to pre-adjust the initial scanning speed and initial laser power in the initial laser parameters based on the first scanning speed correction coefficient and the first power correction coefficient, respectively, to obtain the pre-adjusted scanning speed and pre-adjusted laser power.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images