Light beam focusing control method and device for laser cutting equipment

Abstract

The invention discloses a light beam focusing control method and device for laser cutting equipment, and relates to the technical field of laser processing, and the method comprises the following steps: monitoring a laser beam of the laser cutting equipment in real time, and carrying out light beam quality analysis to obtain a light beam quality parameter; carrying out material thickness detection on the to-be-cut workpiece to obtain actual thickness data, and calculating a target focal depth numerical interval based on the actual thickness data in combination with the cutting process parameters; performing focusing dynamic adjustment according to the light beam quality parameter and the target focal depth numerical interval, and determining focusing lens group control data; and performing continuous cutting monitoring on the laser cutting equipment according to the focus lens group control data, and performing closed-loop correction on the focus lens group control data according to a monitoring result. The technical problem that traditional laser cutting focusing control cannot accurately adapt to workpiece thickness difference and laser beam quality fluctuation is solved, and the technical effects that laser cutting beam focusing is accurately adapted, and the cutting quality and stability are effectively improved are achieved.

Description

Technical Field

[0001] This invention relates to the field of laser processing technology, and in particular to a method and apparatus for beam focusing control of laser cutting equipment. Background Technology

[0002] The precision and quality of metal cutting are of great significance to industrial production. Laser cutting, as a highly efficient metal cutting method, relies heavily on beam focusing control. Currently, laser cutting equipment often uses fixed parameters or single-dimensional adjustment modes for beam focusing, such as controlling based on preset workpiece thickness or beam power. While these methods are effective in simple scenarios, as the requirements for precision and adaptability in metal cutting increase, traditional technologies become limited in complex conditions. Due to variations in metal workpiece thickness and fluctuations in laser beam quality, traditional focusing control cannot accurately adapt to the actual needs of different cutting areas, resulting in uneven surface roughness and insufficient cut precision, failing to meet the dual demands of quality and efficiency in high-end metal cutting. Summary of the Invention

[0003] This application provides a laser cutting equipment beam focusing control method and device, which solves the technical problem that traditional laser cutting focusing control cannot accurately adapt to differences in workpiece thickness and fluctuations in laser beam quality.

[0004] The first aspect of this application provides a beam focusing control method for a laser cutting device. The method includes: real-time monitoring of the laser beam of the laser cutting device to perform beam quality analysis and obtain beam quality parameters; detecting the material thickness of the workpiece to be cut to obtain actual thickness data, and calculating a target focal depth range based on the actual thickness data and cutting process parameters; dynamically adjusting the focus according to the beam quality parameters and the target focal depth range to determine focusing lens group control data; continuously monitoring the laser cutting device according to the focusing lens group control data, and performing closed-loop correction of the focusing lens group control data based on the monitoring results.

[0005] A second aspect of this application provides a beam focusing control device for a laser cutting equipment. The device includes: a beam quality parameter acquisition module for real-time monitoring of the laser beam of the laser cutting equipment to perform beam quality analysis and obtain beam quality parameters; a target focal depth range acquisition module for detecting the material thickness of the workpiece to be cut, obtaining actual thickness data, and calculating the target focal depth range based on the actual thickness data and cutting process parameters; a focusing lens group control data acquisition module for dynamically adjusting the focus according to the beam quality parameters and the target focal depth range to determine the focusing lens group control data; and a closed-loop correction execution module for continuously monitoring the laser cutting equipment according to the focusing lens group control data and performing closed-loop correction on the focusing lens group control data based on the monitoring results.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application collects and analyzes the laser beam quality and the thickness of the workpiece to be cut by the laser cutting equipment. After processing such as depth of focus calculation and dynamic adjustment of the focusing lens group control data, precise focusing parameters are obtained. Combined with continuous monitoring and closed-loop correction of the cutting process, dynamic adaptation of laser cutting beam focusing is achieved, making the focusing accuracy and cutting quality of laser cutting more stable and reliable. This achieves the technical effect of precise adaptation of laser cutting beam focusing and effectively improving cutting quality and stability. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a schematic flowchart of a beam focusing control method for a laser cutting device provided in an embodiment of this application.

[0009] Figure 2 This is a schematic diagram of the structure of a beam focusing control device for a laser cutting equipment provided in an embodiment of this application.

[0010] Figure labeling: Beam quality parameter acquisition module 10, target focal depth numerical range acquisition module 20, focusing lens group control data acquisition module 30, closed-loop correction execution module 40. Detailed Implementation

[0011] This application provides a laser cutting equipment beam focusing control method and device, which solves the technical problem that traditional laser cutting focusing control cannot accurately adapt to differences in workpiece thickness and fluctuations in laser beam quality.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, a method for beam focusing control of a laser cutting device includes: Real-time monitoring of the laser beam of the laser cutting equipment is used to analyze the beam quality and obtain beam quality parameters.

[0015] Specifically, firstly, multiple monitoring points are set based on the laser cutting equipment. By traversing these monitoring points and randomly selecting one, the first monitoring point is determined. Next, the laser cutting equipment is activated according to the first monitoring point to generate a laser beam. When the laser beam passes through the focusing lens group, the propagation path of the laser beam is traversed to perform spot analysis, thereby determining the spot area. Finally, based on this spot area, multi-dimensional beam quality analysis is performed to obtain beam quality parameters.

[0016] The material thickness of the workpiece to be cut is measured to obtain the actual thickness data. Based on the actual thickness data and the cutting process parameters, the target focal depth range is calculated.

[0017] Optionally, the workpiece to be cut is first fixed on the positioning fixture of the laser cutting equipment's worktable. The fixture's limiting structure ensures the workpiece remains stable during inspection, preventing displacement from affecting inspection accuracy. Next, based on the workpiece's dimensions and the cutting area, multiple evenly distributed thickness detection points are planned on the workpiece surface, covering key areas prone to thickness differences, such as the workpiece's edges and center, forming a preset inspection path. Then, the laser displacement sensor on the laser cutting equipment is activated, controlling the sensor to move along the preset inspection path. At each detection point, the sensor emits a laser beam towards the workpiece surface. The laser beam is reflected by the workpiece surface and received by the sensor. Based on the time difference between laser emission and reception, and the known speed of light, the sensor calculates the distance from the sensor to the workpiece surface at the current detection point. Then, the reference distance value from the laser displacement sensor to the worktable surface is retrieved. The distance from the sensor to the workpiece surface at each detection point is subtracted from the reference distance value to obtain the local thickness data of the workpiece at each detection point. Finally, the local thickness data of all detection points are summarized to form a dataset containing the coordinates of the detection points and their corresponding thickness values. This dataset represents the actual thickness data of the workpiece to be cut.

[0018] Next, thickness distribution processing is performed based on the actual thickness data to obtain thickness variation gradient values. Then, the material physical property data of the workpiece to be cut is retrieved, and feature analysis is conducted based on the thickness variation gradient values ​​and material physical property data to construct thickness feature parameters. Subsequently, cutting analysis is performed based on the laser cutting equipment to construct a cutting process parameter database. Then, the material physical property data is used as an index to search the cutting process parameter database to determine the cutting process parameters. The depth of focus is calculated according to the cutting process parameters and the thickness feature parameters to finally determine the target depth of focus range. This step will be explained in detail later.

[0019] Based on the beam quality parameters and the target depth of focus range, dynamic focusing adjustments are made to determine the focusing lens group control data.

[0020] In one embodiment of this application, the beam quality parameters are first matched with the target depth of focus range. Based on the matching results, focusing analysis is performed, and standard focusing quality data is set. Next, the beam quality parameters are compared and evaluated with the standard focusing quality data to generate a focusing state evaluation result. Then, the real-time position parameters of the focusing lens assembly are retrieved. Based on the focusing state evaluation result, the target depth of focus range, and the real-time position parameters, dynamic focusing calculations are performed to generate multiple adjustment values. Finally, the focusing lens assembly is dynamically adjusted according to these adjustment values ​​to determine the focusing lens assembly control data.

[0021] The laser cutting equipment is continuously monitored for cutting according to the focusing lens group control data, and the focusing lens group control data is corrected in a closed loop based on the monitoring results.

[0022] Specifically, firstly, continuous cutting monitoring is performed on the laser cutting equipment based on the focusing lens group control data to obtain cutting quality data. Then, deviation analysis is performed on the focusing lens group control data based on the cutting quality data to generate deviation correction data. Next, the deviation correction data is correlated with historical correction data to obtain multiple correction combinations. These correction combinations are then optimized to determine the optimal correction combination. This optimal correction combination is then added to the focusing lens group control data, and feedback optimization is performed on the focusing lens group control data based on this optimal correction combination to generate an optimization signal. Finally, closed-loop control of the laser cutting equipment's beam focusing is implemented according to the optimization signal.

[0023] Furthermore, the method provided in this application embodiment includes: Multiple monitoring points are set based on the laser cutting equipment. The multiple monitoring points are traversed and randomly selected to determine the first monitoring point. The laser cutting equipment is activated to generate a laser beam according to the first monitoring point. When the laser beam passes through the focusing lens group, the propagation path of the laser beam is traversed to perform spot analysis and determine the spot area. Based on the spot area, multi-dimensional beam quality analysis is performed to obtain the beam quality parameters.

[0024] Specifically, firstly, based on key optical nodes such as the beam output end, focusing lens inlet and outlet of the laser cutting equipment, multiple monitoring points are set using a spatial grid division method. By dividing the key spatial region of beam propagation according to a preset grid size, it is ensured that the monitoring points can cover the main area of ​​beam energy distribution. Subsequently, the multiple set monitoring points are traversed, and one is randomly selected from all the monitoring points as the first monitoring point. This avoids local data deviations that may be caused by fixed monitoring points and ensures the representativeness of subsequent monitoring data.

[0025] After determining the first monitoring point, the laser cutting equipment is activated by its beam trigger control module according to the spatial coordinate parameters of the first monitoring point, enabling the laser cutting equipment to generate a laser beam that meets the preset power and wavelength parameters. When the laser beam propagates along the preset path and passes through the focusing lens group, the entire propagation path of the beam from the output end, through the focusing lens group, to the workpiece processing surface is traversed. Simultaneously, during the path traversal, spot images at key locations along the complete propagation path are captured in real time. Then, the contours of the acquired spot images are extracted through image edge detection, and pixel areas with effective energy distribution are selected by combining grayscale value analysis. Finally, the spot area that reflects the actual shape of the beam is determined.

[0026] Finally, beam filtering is performed based on the beam spot area. After extracting the effective beams, feature analysis is conducted to determine their characteristic parameters. Next, beam spot morphology analysis is performed based on these parameters to calculate the beam spot deviation. Then, beam quality analysis is performed according to the deviation, resulting in multiple beam quality levels. These levels are then matched with the effective beam characteristic parameters to generate beam quality parameters; this step will be explained in detail later.

[0027] Furthermore, the method provided in this application embodiment includes: Based on the light spot region, beam filtering is performed to extract effective beams for feature analysis and determine the effective beam feature parameters; based on the effective beam feature parameters, light spot morphology analysis is performed to calculate the light spot deviation; according to the light spot deviation, beam quality analysis is performed to divide multiple beam quality levels; the multiple beam quality levels are matched with the effective beam feature parameters to generate the beam quality parameters.

[0028] Optionally, grayscale image data of the laser spot area is first acquired. Based on the difference in grayscale values ​​between the laser beam and ambient stray light, a fixed grayscale threshold is set. Areas with grayscale values ​​below this threshold are identified as stray light interference areas and removed, while areas with grayscale values ​​above the threshold are retained as effective beam areas. Subsequently, image pixel statistics are used to analyze the pixel distribution of the effective beam area, extracting quantitative indicators such as spot diameter, spot roundness, and energy concentration. These indicators together constitute the characteristic parameters of the effective beam.

[0029] Next, the standard spot parameters for the corresponding cutting process of the laser cutting equipment are retrieved. These standard parameters include the standard spot diameter, standard spot roundness, and standard energy concentration. The extracted effective beam characteristic parameters are then compared with the standard spot parameters one by one to calculate the difference, resulting in diameter deviation, roundness deviation, and energy concentration deviation values. Then, based on the weight of each parameter's influence on beam quality, the three deviation values ​​are weighted and summed. For example, the weight of the diameter deviation is set to 0.4, the roundness deviation to 0.3, and the energy concentration deviation to 0.3. The result obtained through this weighted calculation is the spot deviation degree, which directly reflects the degree of difference between the actual beam and the standard beam.

[0030] Then, based on the industry's general evaluation standards for laser cutting beam quality and combined with the actual cutting requirements of the equipment, multiple beam deviation ranges are preset. For example, a deviation of 0-0.1 is set as the first level, 0.1-0.3 as the second level, 0.3-0.5 as the third level, and greater than 0.5 as the fourth level. Different ranges correspond to different beam quality levels. Next, the calculated beam deviation is substituted into the preset range to determine its range, thereby determining the beam quality level corresponding to the laser beam and achieving a qualitative evaluation of the beam quality.

[0031] Finally, the identified beam quality levels are correlated one-to-one with the effective beam characteristic parameters extracted in the above steps. The effective beam characteristic parameters specifically include the beam diameter, beam circularity, and energy concentration, thereby forming a complete data set containing "quality level - beam diameter - beam circularity - energy concentration". This data set is the final beam quality parameter, which can comprehensively reflect the actual quality state of the laser beam.

[0032] By gradually applying image thresholding, parameter comparison, interval division, and data association methods, the spot area data is processed in layers to obtain beam quality parameters that have both qualitative and quantitative indicators, providing accurate and reliable data support for the subsequent dynamic adjustment of the laser cutting equipment's focus.

[0033] Furthermore, the method provided in this application embodiment includes: Based on the actual thickness data, the thickness distribution is calculated to obtain the thickness variation gradient value; the material physical property data of the workpiece to be cut is retrieved, and feature analysis is performed based on the thickness variation gradient value and the material physical property data to construct thickness feature parameters; cutting analysis is performed based on the laser cutting equipment to construct a cutting process parameter database; the material physical property data is used as an index to search the cutting process parameter database to determine the cutting process parameters; the focal depth is calculated according to the cutting process parameters and the thickness feature parameters to determine the target focal depth value range.

[0034] Specifically, the actual thickness data of the workpiece to be cut is first processed into a grid according to the workpiece surface coordinates, and the workpiece surface is divided into several uniform grid units. Each grid unit corresponds to a thickness data point. Then, the thickness difference between adjacent grid units is calculated. This thickness difference is divided by the spatial distance between adjacent grid units on the workpiece surface to obtain the thickness change rate between adjacent grid units. The thickness change rates between all adjacent units are summarized to form a thickness change gradient value that can reflect the spatial change trend of the workpiece thickness.

[0035] Next, material physical property data consistent with the material of the workpiece to be cut is retrieved from the material property database pre-stored in the laser cutting equipment. This data includes key parameters such as material density, melting point, and thermal conductivity. Then, the thickness change gradient value is correlated with these material physical property data to extract the maximum value, average value, and spatial distribution trend parameters of the thickness change gradient value. These parameters are then integrated with core indicators such as thermal conductivity and density in the material physical property data to construct thickness feature parameters that can reflect the synergistic characteristics of workpiece thickness distribution and material properties.

[0036] Subsequently, various commonly used materials to be cut and workpiece samples of different thicknesses were selected, and multiple sets of cutting tests were carried out on these samples using laser cutting equipment. During the tests, process parameters such as different laser power, cutting speed, auxiliary gas pressure, and laser frequency were recorded. At the same time, cutting quality data such as the surface roughness and kerf width corresponding to each set of process parameters were detected and recorded. The material type, workpiece thickness, process parameters, and cutting quality data obtained from the tests were classified and organized, and a data index was established according to material type and thickness specifications to build a cutting process parameter database covering parameters suitable for multiple scenarios.

[0037] Subsequently, the material name, density, and other uniquely identifiable parameters from the material physical property data of the workpiece to be cut are used as search indexes. A matching search is performed in the constructed cutting process parameter database to filter out process parameter entries that completely match the material physical property data. Then, combined with the actual thickness range of the workpiece to be cut, parameters such as laser power, cutting speed, and auxiliary gas pressure that are suitable for the current thickness are further filtered from the matching entries and determined as the cutting process parameters corresponding to this laser cutting operation.

[0038] Finally, a depth-of-focus correlation analysis is performed between the thickness characteristic parameters and the cutting process parameters to construct a thickness-process-depth-of-focus correlation array. Then, depth-of-focus calculation is performed according to this array to determine the expected depth-of-focus value. Subsequently, historical cutting quality data is retrieved to set target cutting quality data, and depth-of-focus deviation analysis is performed based on this data to determine the tolerance range for depth-of-focus deviation. Using the expected depth-of-focus value as the target value within this tolerance range, the target depth-of-focus value range is calculated, ultimately defining the target depth-of-focus value range. This step will be explained in detail later.

[0039] Furthermore, the method provided in this application embodiment includes: The thickness characteristic parameters and the cutting process parameters are correlated with focal depth to construct a thickness-process-focal depth correlation array. Focal depth is calculated according to the thickness-process-focal depth correlation array to determine the expected focal depth value. Historical cutting quality data is retrieved to set target cutting quality data. Focal depth deviation analysis is performed according to the target cutting quality data to determine the focal depth deviation tolerance range. The expected focal depth value is used as the target value according to the focal depth deviation tolerance range to calculate the focal depth range and define the target focal depth value range.

[0040] Specifically, the core dimensions of the thickness characteristic parameters are first clarified, including the maximum value, average value, and spatial distribution uniformity of the thickness variation gradient. Simultaneously, key indicators of the cutting process parameters are determined, covering laser power, cutting speed, auxiliary gas pressure, and laser frequency. Then, a two-dimensional parameter framework is constructed, using different values ​​of the thickness characteristic parameters as the row dimension of a matrix and different values ​​of the cutting process parameters as the column dimension. Next, through multiple sets of comparative cutting experiments as described in the previous steps, for each combination of "thickness characteristic parameters - cutting process parameters," the depth of focus (DOC) value that achieves the optimal cutting quality—i.e., a smooth cut without slag—is measured and recorded. This DOC value is then filled into the corresponding row and column cells of the matrix, ultimately forming a thickness-process-DOC correlation array containing parameter correspondences and DOC data.

[0041] Next, in the constructed thickness-process-focus depth correlation array, a row and column combination that perfectly matches the actual thickness characteristic parameters and determined cutting process parameters of the workpiece to be cut is retrieved. If a perfectly matching combination is found, the focus depth value in the corresponding cell is directly extracted as the expected focus depth value. If no perfectly matching combination is found, the 3-5 adjacent parameter combinations closest to the current parameters are selected, and the focus depth values ​​corresponding to these combinations are extracted. The expected focus depth value under the current parameter combination is calculated using a linear interpolation formula with weighted average interpolation, ensuring that the result closely matches the actual parameter requirements.

[0042] Then, from the historical database of the laser cutting equipment, historical cutting quality data within the past 6 months with the same workpiece material, similar thickness range, and similar cutting process parameters are retrieved. Valid records that meet the cutting quality standards are selected. The indicators for meeting the cutting quality standards are set by those skilled in the art based on the actual requirements of the cutting equipment, such as a surface roughness ≤ Ra3.2μm and a kerf width deviation ≤ 0.2mm. Next, the actual depth of focus (DOF) value and the corresponding expected DDF value are extracted from these valid records, and the DDF deviation value for each set of data is calculated as: Actual DDF value - Expected DDF value. Subsequently, all DDF deviation values ​​are statistically analyzed, and the standard deviation and maximum reasonable deviation of the DDF deviation values ​​are calculated. After removing outliers and extreme values, combined with the set target cutting quality data, such as requiring a cutting quality compliance rate of 90%, the range of ±1.5 times the standard deviation of the DDF deviation value is determined as the DDF deviation tolerance range, ensuring that the range can cover normal process fluctuations.

[0043] Finally, using the desired depth of focus determined in the above steps as a baseline, add the upper limit of the depth of focus deviation tolerance range to this baseline to obtain the maximum value of the target depth of focus range. Subtract the lower limit of the depth of focus deviation tolerance range from the baseline to obtain the minimum value of the target depth of focus range. Arrange the maximum and minimum values ​​into the form of "minimum value - maximum value" to obtain the final defined target depth of focus range, providing a clear parameter range for subsequent focus adjustments.

[0044] Through the above steps, a complete process from parameter association to range definition was achieved, and the target focal depth range that fits the current cutting requirements was accurately determined. This provides a reliable parameter basis for the dynamic adjustment of the laser cutting equipment's beam focusing, ensuring the stability and consistency of the cutting quality.

[0045] Furthermore, the method provided in this application embodiment includes: The beam quality parameters are matched with the target depth of focus range, and focusing analysis is performed based on the matching results to set focusing quality standard data. The beam quality parameters are compared and evaluated with the focusing quality standard data to generate a focusing state evaluation result. The real-time position parameters of the focusing lens group are retrieved, and focusing dynamic calculation is performed based on the focusing state evaluation result, the target depth of focus range, and the real-time position parameters to generate multiple adjustment values. The focusing lens group is dynamically adjusted according to the multiple adjustment values ​​to determine the focusing lens group control data.

[0046] Specifically, the core indicators of beam quality parameters are first identified as beam deviation and beam quality level. Then, the key parameters for the target focal depth range are identified as the upper and lower limits and the median. A parameter matching method is used to establish the correlation rules between the two. For example, when the beam quality level is first, the median of the target focal depth range corresponds to a range of ±0.1 mm; when the beam quality level is second, the median of the target focal depth range corresponds to a range of ±0.2 mm. Subsequently, based on the actual matching results between the current beam quality parameters and the target focal depth range, focus quality standard data is set, including a standard beam deviation ≤0.05 and a standard focal depth position that is the median of the target focal depth range.

[0047] Next, the currently acquired beam quality parameters are compared one by one with the set focus quality standard data. The difference between the actual spot deviation and the standard spot deviation is calculated. If the difference is ≤0, the focus is considered to be up to standard. If 0 < difference ≤0.05, the focus is considered to be slightly deviated. If the difference is >0.05, the focus is considered to be seriously deviated. Based on the judgment result, the focus status evaluation result is generated.

[0048] Next, the real-time position parameters of the focusing lens group, i.e. the current axial coordinate value of the focusing lens group, are retrieved by the displacement sensor on the laser cutting equipment. A multi-parameter weighted calculation method is used to determine the weighting coefficients based on the focusing state evaluation results. The focusing compliance coefficient is 1.0, the slight deviation coefficient is 1.2, and the severe deviation coefficient is 1.5. The median value of the target focal depth range is taken as the target position and substituted into the formula: Adjustment value = (Target position - Real-time axial coordinate value) × Weighting coefficient. The adjustment values ​​corresponding to different cutting areas of the workpiece to be cut are calculated separately, and finally multiple adjustment values ​​are generated.

[0049] Finally, the adjustment data of the focusing lens assembly is quantified according to multiple adjustment values ​​to determine the adjustment amount of the focusing lens assembly. Next, cluster analysis is performed on the adjustment amount of the focusing lens assembly based on multiple adjustment values ​​to determine multiple adjustment categories. Then, the impact of these adjustment categories on beam focusing of the focusing lens assembly is analyzed, and multiple impact levels are set. Next, the multiple adjustment categories and multiple impact levels are correlated to construct an adjustment strategy list. Finally, the focusing lens assembly is controlled and matched according to the adjustment strategy list to determine the control data of the focusing lens assembly; this step will be explained in detail later.

[0050] Furthermore, the method provided in this application embodiment includes: The focusing lens assembly is quantified according to the multiple adjustment values ​​to determine the adjustment amount of the focusing lens assembly; the adjustment amount of the focusing lens assembly is clustered based on the multiple adjustment values ​​to determine multiple adjustment categories; the impact of the multiple adjustment categories on the beam focusing of the focusing lens assembly is analyzed to set multiple impact levels; the multiple adjustment categories and the multiple impact levels are correlated to construct an adjustment strategy list; the focusing lens assembly is controlled and matched according to the adjustment strategy list to determine the control data of the focusing lens assembly.

[0051] In one embodiment, the maximum and minimum values ​​of all adjustment values ​​are first counted to determine the range of adjustment values. Then, the standardization coefficient of each adjustment value is calculated using the formula: (single adjustment value - minimum adjustment value) / (maximum adjustment value - minimum adjustment value). This standardization coefficient is multiplied by the preset maximum adjustable travel of the focusing lens group to obtain the physical displacement corresponding to each adjustment value. This displacement is the adjustment amount of the focusing lens group.

[0052] Next, based on the adjustment amounts corresponding to multiple adjustment values, K-means clustering is used to perform cluster analysis to determine multiple adjustment classes. First, according to the numerical distribution of the adjustment amounts, three cluster sizes are preset and correspond to small, medium, and large adjustment ranges. The average value of all adjustment amounts is calculated as the initial cluster center. Then, the Euclidean distance between each adjustment amount and each initial cluster center is calculated, and the adjustment amount is assigned to the category of the nearest cluster center. After that, the average value of the adjustment amount of each category is recalculated as the new cluster center. The above distance calculation and classification steps are repeated until the cluster centers no longer change, and finally multiple adjustment classes are formed.

[0053] Subsequently, based on multiple adjustment categories, the impact factor assessment method was used to analyze the beam focusing of the focusing lens group to set multiple impact levels. For each adjustment category, two key indicators, energy concentration and depth-of-focus deviation after beam focusing, were selected as impact assessment items. Through controlled variable experiments, other process parameters were fixed, and beam focusing was performed using only the adjustment amount of that adjustment category. The deviation rate between the actual value of energy concentration and the standard value (e.g., standard energy concentration ≥ 90%) and the deviation rate between the actual value of depth-of-focus deviation and the standard value (e.g., standard depth-of-focus deviation ≤ 0.1 mm) were measured and recorded. If both deviation rates were ≤ 5%, the impact level was set as low impact; if 5% < both deviation rates ≤ 15%, it was set as medium impact; and if both deviation rates > 15%, it was set as high impact.

[0054] Subsequently, a key-value mapping method is used to associate multiple adjustment classes with multiple impact levels. Each adjustment class identifier (e.g., small adjustment class, medium adjustment class) is used as the "key," and the corresponding impact level (e.g., low impact, medium impact) and the adjustment range for that class are used as the "value," establishing a one-to-one mapping relationship. For example, small adjustment class: adjustment amount 0-2mm, impact level: low impact; medium adjustment class: adjustment amount 2-5mm, impact level: medium impact. All mapping relationships are then organized into a structured list in ascending order of adjustment amount; this list constitutes the adjustment strategy list.

[0055] Finally, the beam quality parameter is determined according to the adjustment strategy list to see if it is within the list. If it is, a first-level adjustment command is generated to adjust the focusing lens assembly to the first control data. If it is not, a second-level adjustment command is generated to adjust the focusing lens assembly to the second control data. This step will be explained in detail later.

[0056] Furthermore, the method provided in this application embodiment includes: The beam quality parameter is determined according to the adjustment strategy list to determine whether the beam quality parameter is in the adjustment strategy list; if the beam quality parameter is in the adjustment strategy list, a first-level adjustment command is generated, and the focusing lens group is adjusted to the first control data by the first-level adjustment command; if the beam quality parameter is not in the adjustment strategy list, a second-level adjustment command is generated, and the focusing lens group is adjusted to the second control data by the second-level adjustment command.

[0057] Optionally, a preset beam quality parameter judgment range is first extracted from the adjustment strategy list. This range includes key indicators such as beam deviation threshold, beam quality level range, and energy concentration standard value. For example, the list presets "beam deviation ≤ 0.05, beam quality level excellent, energy concentration ≥ 90%" as valid judgment items. Then, actual beam quality parameters are extracted from the current laser beam detection data, including the real-time calculated beam deviation, the classified beam quality level, and the measured energy concentration. Finally, the actual beam quality parameters are compared numerically with each preset judgment range in the list. If all actual parameters fall within any preset judgment range, the beam quality parameter is determined to be in the adjustment strategy list; otherwise, it is determined not to be in the list.

[0058] If the beam quality parameters are in the adjustment strategy list, the preset first control data matching the current beam quality parameters is retrieved from the list. This data includes specific control parameters such as the axial displacement of the focusing lens assembly and the lens tilt angle. Next, the first control data is encoded according to the control protocol of the laser cutting equipment to generate a standardized first-level adjustment command. This command includes a command type identifier and the corresponding control parameters; for example, LV1 represents a first-level adjustment command. Finally, the first-level adjustment command is sent to the focusing lens assembly's drive control system. After receiving the command, the drive system parses the control parameters and drives the focusing lens assembly's motor and transmission mechanism to adjust the focusing lens assembly to the position and state corresponding to the first control data.

[0059] If the beam quality parameter is not in the adjustment strategy list, the deviation value between the current beam quality parameter and the closest preset range in the adjustment strategy list is analyzed. For example, if the current spot deviation is 0.07 and the closest threshold in the list is 0.05, the deviation value is 0.02. Next, the compensation amount is calculated based on the deviation value. Using a preset compensation coefficient of deviation value × 2, the additional adjustment amount for the focusing lens group is determined. For example, a deviation of 0.02 corresponds to a compensation amount of 0.04mm. Then, the compensation amount is superimposed on the basic control parameter, i.e., the first control data of the closest entry in the list, to obtain the second control data. For example, a basic axial displacement of 2.5mm superimposed with a compensation amount of 0.04mm results in a second control data of 2.54mm. Finally, the second control data is encoded to generate a secondary adjustment command, identified as LV2, which is sent to the drive control system to drive the focusing lens group to adjust to the state corresponding to the second control data.

[0060] The beam quality parameters are quickly determined by data comparison. First-level and second-level adjustment commands adapted to different scenarios are generated by command encoding and parameter compensation methods, respectively. Finally, the precise matching and dynamic adjustment of the focusing lens group control data are realized, which effectively ensures the stability and adaptability of the beam focusing state during laser cutting.

[0061] Furthermore, the method provided in this application embodiment includes: The laser cutting equipment is continuously monitored for cutting quality based on the focusing lens group control data to obtain cutting quality data. Deviation analysis is then performed on the focusing lens group control data based on the cutting quality data to generate deviation correction data. This deviation correction data is correlated with historical correction data to obtain multiple correction combinations. These multiple correction combinations are then optimized to obtain an optimized correction combination. This optimized correction combination is added to the focusing lens group control data, and the focusing lens group control data is then optimized based on the optimized correction combination to generate an optimization signal. Finally, closed-loop control of the laser cutting equipment's beam focusing is performed based on the optimization signal.

[0062] In one embodiment, an industrial camera is first installed next to the cutting station of the laser cutting equipment. The camera lens is aimed at the cutting area of ​​the workpiece, and the camera's sampling frequency is set to 3 frames per second to ensure real-time capture of the cutting process. When the laser cutting equipment starts cutting according to the focusing lens group control data, the industrial camera acquires image data of the cutting surface at a preset frequency. Image preprocessing, including grayscale conversion and noise reduction, removes interference information from the image. Subsequently, key quality indicators such as the roughness of the cutting surface, the kerf width, and the slag area are extracted from the image and converted into quantified values, such as roughness represented by Ra values ​​and kerf width represented by millimeters. These quantified values ​​together constitute the cutting quality data.

[0063] Next, standard cutting quality data matching the current workpiece material and thickness is retrieved from the laser cutting equipment's process standard library. Examples include a standard roughness Ra ≤ 3.2 μm and a standard kerf width of 0.1-0.2 mm. The actual cutting quality data is then compared with the standard cutting quality data to calculate the deviation value for each quality indicator. For example, if the actual roughness Ra = 4.0 μm, the deviation value = 4.0 - 3.2 = 0.8 μm. According to a pre-defined quality deviation-focusing parameter correlation table, for example, a 0.05 mm deviation in kerf width corresponds to a 0.1 mm adjustment in focal depth. The deviation values ​​of the quality indicators are then converted into correction amounts for the focal depth and lens position control parameters of the focusing lens group. These correction amounts are the deviation correction data.

[0064] Subsequently, historical cutting records from the past three months with the same workpiece type and cutting process as the current one are retrieved, and historical deviation correction data is extracted from them. For example, in a certain record, the depth-of-focus correction is 0.15mm and the lens group position correction is 0.05mm. The currently generated deviation correction data is combined with each historical deviation correction data according to the dimension of depth-of-focus correction minus lens group position correction. For example, the current depth-of-focus correction of 0.1mm is combined with the historical depth-of-focus correction of 0.15mm, and the current lens group position correction of 0.03mm is combined with the historical lens group position correction of 0.05mm, forming multiple sets of correction combinations containing current and historical correction information.

[0065] Next, a greedy optimization algorithm is used. The optimization objective is to maximize the cut quality compliance rate while minimizing the correction amount. Weights are assigned to the depth-of-focus correction and lens position correction in each correction combination; for example, depth-of-focus correction has a weight of 0.6, and lens position correction has a weight of 0.4. A comprehensive score is calculated for each correction combination, such as: Comprehensive Score = (1 - Total Corrections / Maximum Correction) × 0.7 + Historical Quality Compliance Rate of This Combination × 0.3. All correction combinations are iterated through, and the combination with the highest comprehensive score is selected as the optimized correction combination.

[0066] Next, parameters such as the depth-of-focus correction and lens position correction are extracted from the optimized correction combination. These parameters are then superimposed with the corresponding parameters in the currently used focusing lens control data. For example, if the current depth-of-focus control value is 5.0mm and the optimized correction is 0.1mm, the superimposed value is 5.1mm, completing the update of the focusing lens control data. Subsequently, according to the RS485 communication protocol of the laser cutting equipment, the updated focusing lens control data is encoded into an electrical signal that the equipment can recognize; this electrical signal is the optimization signal.

[0067] Finally, combining PID (Proportional-Integral-Derivative) closed-loop control, the target focal depth and target lens group position in the optimization signal are used as the setpoints for the PID controller. The PID controller collects the actual position of the focusing lens group in real time through a displacement sensor and the actual focal depth of the laser beam through a beam analyzer. The deviation between the actual parameters and the setpoints is calculated, and the adjustment amount is calculated using the PID algorithm. This adjustment amount is then sent to the drive motor of the focusing lens group. The drive motor adjusts the position of the focusing lens group according to the adjustment amount, and simultaneously feeds back the adjusted actual parameters to the PID controller in real time, forming a closed-loop cycle of "setting-monitoring-adjustment-feedback" to continuously maintain the beam focusing state in accordance with the optimization requirements.

[0068] Through the gradual implementation of the above steps, a complete process of monitoring and analyzing focusing lens group control data, optimizing and correcting it, and then implementing closed-loop control was achieved, ultimately resulting in a continuous improvement in the stability of laser cutting quality.

[0069] In summary, the beam focusing control method for laser cutting equipment provided in this application has the following technical effects: This application obtains beam quality parameters by real-time monitoring and analysis of the laser cutting equipment beam, calculates the target focal depth range by detecting the workpiece thickness and combining it with the cutting process parameters, dynamically adjusts the focusing lens group control data accordingly, continuously monitors the cutting process and corrects the data in a closed loop, precisely controls the beam focusing, improves the cutting quality, and makes laser cutting more stable and reliable. It achieves the technical effect of precise matching of laser cutting beam focusing and effectively improving cutting quality and stability.

[0070] Example 2, as Figure 2 As shown, based on the same inventive concept as the aforementioned Embodiment 1, this application provides a beam focusing control device for a laser cutting equipment, the device comprising: The beam quality parameter acquisition module 10 is used to monitor the laser beam of the laser cutting equipment in real time, perform beam quality analysis, and obtain beam quality parameters.

[0071] The target focal depth value range acquisition module 20 is used to detect the material thickness of the workpiece to be cut, obtain the actual thickness data, and calculate the target focal depth value range based on the actual thickness data and cutting process parameters.

[0072] The focusing lens group control data acquisition module 30 is used to dynamically adjust the focus based on the beam quality parameters and the target depth of focus range, and determine the focusing lens group control data.

[0073] The closed-loop correction execution module 40 is used to continuously monitor the laser cutting equipment according to the focusing lens group control data, and to perform closed-loop correction on the focusing lens group control data based on the monitoring results.

[0074] Furthermore, the beam quality parameter acquisition module 10 is used to perform the following steps: Multiple monitoring points are set based on the laser cutting equipment. The multiple monitoring points are traversed and randomly selected to determine the first monitoring point. The laser cutting equipment is activated to generate a laser beam according to the first monitoring point. When the laser beam passes through the focusing lens group, the propagation path of the laser beam is traversed to perform spot analysis and determine the spot area. Based on the spot area, multi-dimensional beam quality analysis is performed to obtain the beam quality parameters.

[0075] Furthermore, the beam quality parameter acquisition module 10 is used to perform the following steps: Based on the light spot region, beam filtering is performed to extract effective beams for feature analysis and determine the effective beam feature parameters; based on the effective beam feature parameters, light spot morphology analysis is performed to calculate the light spot deviation; according to the light spot deviation, beam quality analysis is performed to divide multiple beam quality levels; the multiple beam quality levels are matched with the effective beam feature parameters to generate the beam quality parameters.

[0076] Furthermore, the target focal depth numerical range acquisition module 20 is used to perform the following steps: Based on the actual thickness data, the thickness distribution is calculated to obtain the thickness variation gradient value; the material physical property data of the workpiece to be cut is retrieved, and feature analysis is performed based on the thickness variation gradient value and the material physical property data to construct thickness feature parameters; cutting analysis is performed based on the laser cutting equipment to construct a cutting process parameter database; the material physical property data is used as an index to search the cutting process parameter database to determine the cutting process parameters; the focal depth is calculated according to the cutting process parameters and the thickness feature parameters to determine the target focal depth value range.

[0077] Furthermore, the target focal depth numerical range acquisition module 20 is used to perform the following steps: The thickness characteristic parameters and the cutting process parameters are correlated with focal depth to construct a thickness-process-focal depth correlation array. Focal depth is calculated according to the thickness-process-focal depth correlation array to determine the expected focal depth value. Historical cutting quality data is retrieved to set target cutting quality data. Focal depth deviation analysis is performed according to the target cutting quality data to determine the focal depth deviation tolerance range. The expected focal depth value is used as the target value according to the focal depth deviation tolerance range to calculate the focal depth range and define the target focal depth value range.

[0078] Furthermore, the focusing lens group control data acquisition module 30 is used to perform the following steps: The beam quality parameters are matched with the target depth of focus range, and focusing analysis is performed based on the matching results to set focusing quality standard data. The beam quality parameters are compared and evaluated with the focusing quality standard data to generate a focusing state evaluation result. The real-time position parameters of the focusing lens group are retrieved, and focusing dynamic calculation is performed based on the focusing state evaluation result, the target depth of focus range, and the real-time position parameters to generate multiple adjustment values. The focusing lens group is dynamically adjusted according to the multiple adjustment values ​​to determine the focusing lens group control data.

[0079] Furthermore, the focusing lens group control data acquisition module 30 is used to perform the following steps: The focusing lens assembly is quantified according to the multiple adjustment values ​​to determine the adjustment amount of the focusing lens assembly; the adjustment amount of the focusing lens assembly is clustered based on the multiple adjustment values ​​to determine multiple adjustment categories; the impact of the multiple adjustment categories on the beam focusing of the focusing lens assembly is analyzed to set multiple impact levels; the multiple adjustment categories and the multiple impact levels are correlated to construct an adjustment strategy list; the focusing lens assembly is controlled and matched according to the adjustment strategy list to determine the control data of the focusing lens assembly.

[0080] Furthermore, the focusing lens group control data acquisition module 30 is used to perform the following steps: The beam quality parameter is determined according to the adjustment strategy list to determine whether the beam quality parameter is in the adjustment strategy list; if the beam quality parameter is in the adjustment strategy list, a first-level adjustment command is generated, and the focusing lens group is adjusted to the first control data by the first-level adjustment command; if the beam quality parameter is not in the adjustment strategy list, a second-level adjustment command is generated, and the focusing lens group is adjusted to the second control data by the second-level adjustment command.

[0081] Furthermore, the closed-loop correction execution module 40 is used to perform the following steps: The laser cutting equipment is continuously monitored for cutting quality based on the focusing lens group control data to obtain cutting quality data. Deviation analysis is then performed on the focusing lens group control data based on the cutting quality data to generate deviation correction data. This deviation correction data is correlated with historical correction data to obtain multiple correction combinations. These multiple correction combinations are then optimized to obtain an optimized correction combination. This optimized correction combination is added to the focusing lens group control data, and the focusing lens group control data is then optimized based on the optimized correction combination to generate an optimization signal. Finally, closed-loop control of the laser cutting equipment's beam focusing is performed based on the optimization signal.

[0082] The beam focusing control device for a laser cutting equipment provided in this embodiment of the invention can execute the beam focusing control method for a laser cutting equipment provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0083] Although this application makes various references to certain modules in the apparatus according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not intended to limit the scope of protection of this invention.

[0084] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for beam focusing control in laser cutting equipment, characterized in that, The method includes: Real-time monitoring of the laser beam of the laser cutting equipment is used to analyze the beam quality and obtain beam quality parameters. The material thickness of the workpiece to be cut is measured to obtain the actual thickness data. Based on the actual thickness data and the cutting process parameters, the target focal depth range is calculated. Based on the beam quality parameters and the target depth of focus range, dynamic focusing adjustment is performed to determine the focusing lens group control data; The laser cutting equipment is continuously monitored for cutting according to the focusing lens group control data, and the focusing lens group control data is corrected in a closed loop based on the monitoring results.

2. The beam focusing control method for a laser cutting device as described in claim 1, characterized in that, Real-time monitoring of the laser beam from a laser cutting equipment to perform beam quality analysis and obtain beam quality parameters; methods include: Based on the laser cutting equipment, multiple monitoring points are set, and the first monitoring point is determined by randomly selecting from the multiple monitoring points. The laser cutting equipment is activated according to the first monitoring point to generate a laser beam. When the laser beam passes through the focusing lens group, the beam propagation path is traversed to perform spot analysis and determine the spot area. Multi-dimensional beam quality analysis is performed based on the beam spot region to obtain the beam quality parameters.

3. The beam focusing control method for a laser cutting device as described in claim 2, characterized in that, The method for obtaining the beam quality parameters by performing multi-dimensional beam quality analysis based on the beam spot region includes: Based on the light spot area, beam filtering is performed, effective beams are extracted for feature analysis, and the characteristic parameters of the effective beams are determined. Based on the effective beam characteristic parameters, the beam morphology is analyzed and the beam deviation is calculated. Beam quality analysis is performed based on the aforementioned spot deviation, and multiple beam quality levels are defined. The beam quality parameters are generated by matching the multiple beam quality levels with the effective beam characteristic parameters.

4. The beam focusing control method for a laser cutting device as described in claim 1, characterized in that, The method for calculating the target focal depth range based on the actual thickness data and cutting process parameters includes: Based on the actual thickness data, the thickness distribution is calculated to obtain the thickness variation gradient value; Retrieve the material physical property data of the workpiece to be cut, and perform feature analysis based on the thickness change gradient value and the material physical property data to construct thickness feature parameters; Based on laser cutting equipment, a cutting process parameter database is constructed; The material physical property data is used as an index to search the cutting process parameter database and determine the cutting process parameters. The focal depth is calculated based on the cutting process parameters and thickness characteristic parameters to determine the target focal depth range.

5. The beam focusing control method for a laser cutting device as described in claim 4, characterized in that, The target focal depth range is determined by calculating the focal depth based on the cutting process parameters and thickness characteristic parameters, using the following method: The thickness feature parameters and the cutting process parameters are subjected to a focal depth correlation analysis to construct a thickness-process-focal depth correlation array. The desired value of the focal depth is determined by calculating the focal depth according to the thickness-process-focal depth correlation array. Historical cutting quality data is retrieved to set target cutting quality data. Based on the target cutting quality data, a focus depth deviation analysis is performed to determine the focus depth deviation tolerance range. The expected value of focal depth is used as the target value to calculate the focal depth range according to the focal depth deviation tolerance range, and the target focal depth value range is defined.

6. The beam focusing control method for a laser cutting device as described in claim 1, characterized in that, Based on the beam quality parameters and the target depth of focus range, dynamic focusing adjustments are performed to determine the focusing lens group control data. The method includes: The beam quality parameters are matched with the target focal depth range, and focusing analysis is performed based on the matching results to set the focusing quality standard data. The beam quality parameters are compared and evaluated with the focusing quality standard data to generate a focusing status evaluation result; The real-time position parameters of the focusing lens group are retrieved, and dynamic focusing calculations are performed based on the focusing state evaluation results, the target depth of focus range, and the real-time position parameters to generate multiple adjustment values. The focusing lens group is dynamically adjusted based on the multiple adjustment values ​​to determine the focusing lens group control data.

7. The beam focusing control method for a laser cutting device as described in claim 6, characterized in that, The focusing lens group is dynamically adjusted based on the multiple adjustment values ​​to determine the control data of the focusing lens group. The method includes: The adjustment data of the focusing lens group is quantified according to the multiple adjustment values ​​to determine the adjustment amount of the focusing lens group; Based on the multiple adjustment values, cluster analysis is performed on the adjustment amount of the focusing lens group to determine multiple adjustment categories; The impact of the multiple adjustment categories on the beam focusing of the focusing lens group is analyzed, and multiple impact levels are set. The multiple adjustment categories are associated with the multiple impact levels to construct an adjustment strategy list; The focusing lens group is controlled and matched according to the adjustment strategy list to determine the focusing lens group control data.

8. The beam focusing control method for a laser cutting device as described in claim 7, characterized in that, The focusing lens group is controlled and matched according to the adjustment strategy list to determine the control data of the focusing lens group, the method including: The beam quality parameters are determined according to the adjustment strategy list to determine whether the beam quality parameters are in the adjustment strategy list; If the beam quality parameter is in the adjustment strategy list, a first-level adjustment command is generated, and the focusing lens group is adjusted to the first control data through the first-level adjustment command; If the beam quality parameter is not in the adjustment strategy list, a secondary adjustment command is generated to adjust the focusing lens group to the second control data.

9. The beam focusing control method for a laser cutting device as described in claim 1, characterized in that, The laser cutting equipment is continuously monitored according to the focusing lens group control data, and closed-loop correction is performed on the focusing lens group control data based on the monitoring results. The method includes: The laser cutting equipment is continuously monitored based on the focusing lens group control data to obtain cutting quality data. Based on the cutting quality data, deviation analysis is performed on the focusing lens group control data to generate deviation correction data; The deviation correction data is correlated with historical correction data to obtain multiple correction combinations; The multiple correction combinations are optimized and mined to obtain optimized correction combinations; The optimized correction combination is added to the focusing lens group control data, and the focusing lens group control data is optimized based on the optimized correction combination to generate an optimized signal; Closed-loop control of the laser cutting equipment for beam focusing is performed according to the optimized signal.

10. A beam focusing control device for laser cutting equipment, characterized in that, A beam focusing control method for implementing a laser cutting apparatus according to any one of claims 1-9, the apparatus comprising: The beam quality parameter acquisition module is used to monitor the laser beam of the laser cutting equipment in real time, perform beam quality analysis, and obtain beam quality parameters. The target focal depth numerical range acquisition module is used to detect the material thickness of the workpiece to be cut, obtain the actual thickness data, and calculate the target focal depth numerical range based on the actual thickness data and cutting process parameters. The focusing lens group control data acquisition module is used to dynamically adjust the focus based on the beam quality parameters and the target focal depth range, and determine the focusing lens group control data. The closed-loop correction execution module is used to continuously monitor the laser cutting equipment according to the focusing lens group control data, and to perform closed-loop correction on the focusing lens group control data based on the monitoring results.

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