A high-integration variable focus laser engraving control method and system

Abstract

The application relates to the technical field of manufacturing, and discloses a high-integration variable-focus laser engraving control method and system. The surface of a workpiece is subjected to high-frequency data acquisition through a sensor array to obtain an initial surface state data set. A feature extraction model is used to analyze the surface micro-differences and determine a dynamic trend distribution map. Real-time monitoring technology is used to track surface changes, and when the height fluctuation is detected to exceed a threshold value, the focal point position is corrected. The focal point position is adjusted according to a deviation correction algorithm, and the actuator is driven to perform real-time correction. The processing effect is evaluated through data comparison and analysis, parameter optimization instructions are generated, a dynamic adjustment control model is called to fine-tune the operating parameters. Finally, the processing quality evaluation result is output, and a complete log file is generated. The application realizes real-time precision monitoring and dynamic adjustment in the complex surface processing process, improves the processing precision and stability, and meets the requirements of high-end manufacturing standards.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of manufacturing, and in particular to a high-integration variable-focus laser engraving control method and system. BACKGROUND

[0002] At present, in modern manufacturing, the improvement of workpiece surface machining precision is of great significance to product quality and performance, and the research in this field is directly related to the efficiency and reliability of industrial production. However, the current mainstream processing method often has difficulty in achieving real-time monitoring and dynamic adjustment of high precision when facing complex surface changes, and generally has the problems of slow response speed and insufficient precision, resulting in unstable processing effect and difficulty in meeting the needs of high-end manufacturing.

[0003] In the prior art, the core challenge in this field mainly focuses on how to realize real-time monitoring and accurate control of the workpiece surface. First, due to the small and complex changes of the workpiece surface during the machining process, the traditional monitoring means is difficult to capture these subtle differences, resulting in information acquisition lag. This lag further causes the machining equipment to be unable to adjust the parameters in time, resulting in deviation of the focal point position from the actual demand. The deviation of the focal point position directly affects the stability of the machining precision, especially in the scene requiring micro-nanometer level precision, this problem is particularly prominent. These interlocking technical problems make it extremely difficult to achieve the best processing effect in a dynamic environment.

[0004] Therefore, how to monitor the small changes of the workpiece surface in real time during the machining process, and through high-precision step control and dynamic adjustment technology, to ensure the accurate matching of the focal point position, has become a key problem that needs to be solved in this research. SUMMARY

[0005] The present application provides a high-integration variable-focus laser engraving control method and system to ensure accurate matching of small changes in the workpiece surface.

[0006] In a first aspect, to solve the above technical problems, the present application provides a high-integration variable-focus laser engraving control method, comprising:

[0007] Obtaining an initial surface state data set of workpiece surface changes and obtaining a dynamic trend distribution map;

[0008] According to the dynamic trend distribution map, obtaining a current focal point position deviation value and an adjusted focal point position coordinate value to drive the actuator of the machining equipment to perform real-time position correction, and judging whether the correction meets the preset precision standard;

[0009] If the correction is successful, the fluctuation of the processing effect is evaluated, and if it is found that the fluctuation value exceeds the preset fluctuation threshold, a parameter optimization instruction is generated;

[0010] According to the parameter optimization instruction, the operation parameters of the machining equipment are fine-tuned to obtain an optimized machining effect record, and whether the high-end manufacturing standard requirement is met is judged in combination with historical machining data and a current surface state, and a final machining quality evaluation result is output.

[0011] According to the final machining quality evaluation result, a complete log file of the machining process is generated, and reference information of iteration is determined through key data points in the complete log file.

[0012] Preferably, the initial surface state data set of the workpiece surface change is obtained, including:

[0013] The workpiece surface is collected at a high frequency through a sensor array, and data of the topographic features of each micro area are obtained by using a multi-point synchronous scanning mode, the data including surface height, roughness value and local curvature, and a preliminary surface state record is obtained.

[0014] According to the preliminary surface state record, the topographic features of each micro area are classified and arranged, a feature matrix is established according to the surface height, the roughness value and the local curvature, and the feature distribution of each micro area is determined.

[0015] If the roughness value of one of the micro areas in the feature matrix exceeds a preset roughness threshold, the surface height and the local curvature of the one micro area are corrected, and corrected feature data are obtained.

[0016] The corrected feature data are compared with the initial data set, the topographic feature information of the one micro area is integrated, a complete workpiece surface state description is generated, and a final surface state data set is obtained.

[0017] Preferably, the dynamic trend distribution diagram is obtained, including:

[0018] According to the initial surface state data set, the height fluctuation and the curvature change are obtained, the fluctuation amplitude and the change rate of each micro area are recorded, and a preliminary difference feature set is obtained.

[0019] The preliminary difference feature set is matched with a pre-established feature extraction template, and a surface state change range of each area is obtained.

[0020] If the height fluctuation or the curvature change of one of the areas in the surface state change range exceeds a preset threshold, the surface state of the one area is corrected, and a local feature of a dynamic trend is obtained from the corrected data.

[0021] According to the local feature, a dynamic trend distribution map is generated, data mapping of surface difference and slight change is performed, and a complete surface state change distribution description is obtained.

[0022] Preferably, the current focal point position deviation value is obtained according to the dynamic trend distribution map, comprising:

[0023] According to the monitoring data of the dynamic trend distribution map, the instantaneous state of the surface change is continuously tracked and compared, the high fluctuation change value is obtained, and it is determined whether the change value exceeds the preset change threshold range;

[0024] If the high fluctuation change value exceeds the preset threshold range, the focal point position is detected for deviation, the deviation value of the current focal point position is obtained, and the deviation distribution condition is obtained.

[0025] The deviation distribution condition is calculated for correction parameters, the focal point position is updated in real time, and it is determined whether the corrected state meets the preset standard.

[0026] If yes, according to the corrected focal point position, the data of the instantaneous state is mapped into the dynamic trend distribution map, the latest situation of the surface change is recorded, and the updated atlas data is obtained.

[0027] Preferably, the adjusted focal point position coordinate value is obtained, comprising:

[0028] The data of focal point deviation and corresponding position coordinates are compared point by point, the specific condition of deviation distribution is obtained, and the key area of focal point deviation is determined.

[0029] According to the deviation data of the key area, combined with the preset deviation correction rule, the focal point control parameter is dynamically adjusted, and the updated parameter value is obtained.

[0030] If there is a difference between the updated parameter value and the actual demand of the workpiece surface, the real-time updated focal point position coordinate is compared with the actual demand of the workpiece surface, the final adjustment data is obtained, and the latest state of the focal point position is determined.

[0031] Preferably, the real-time position correction is performed on the driving mechanism of the machining equipment, and it is determined whether the correction meets the preset precision standard, comprising:

[0032] According to the record data of the focal point coordinates, the focal point coordinate value and the target position are verified, the specific condition of deviation distribution is obtained, the key point of correction is determined from the specific condition, and a correction data set is obtained.

[0033] According to the correction data set, send adjustment instructions to the actuator, and obtain the running state of the actuator through the state monitoring tool during adjustment, determine whether the preliminary position correction is completed from the running state, and obtain the preliminary corrected state data;

[0034] If the preliminary corrected state data deviates from the accuracy standard, record the state data through the feedback data acquisition tool, perform secondary verification, determine whether the correction reaches the preset threshold, and determine the correction compliance data;

[0035] According to the correction compliance data, perform final adjustment on the focal point coordinates to generate a correction signal, and obtain the final running state from the correction signal.

[0036] Preferably, if the correction is successful, the fluctuation of the machining effect is evaluated, and if the fluctuation value exceeds the preset fluctuation threshold, a parameter optimization instruction is generated, including:

[0037] Classify and process the stability indicators in the correction signal to obtain core data of machining precision, and obtain a preliminary comparison result of the core data;

[0038] According to the preliminary comparison result, check the fluctuation of the machining precision, obtain specific information of the fluctuation evaluation, and determine the detailed distribution of the fluctuation evaluation;

[0039] According to the detailed distribution of the fluctuation evaluation, real-time monitor the running state in the machining process, obtain a key adjustment point, and determine the optimization direction of the key adjustment point;

[0040] Refine the optimization direction by using an instruction generation tool to obtain a final parameter adjustment scheme.

[0041] Preferably, according to the parameter optimization instruction, fine-tune the running parameters of the machining equipment to obtain an optimized machining effect record, combine historical machining data and the current surface state, determine whether the requirements of high-end manufacturing standards are met, and output a final machining quality evaluation result, including:

[0042] According to a pre-established storage library, integrate the surface state of a complex surface with historical data, obtain at least one key state indicator, compare the key state indicator with the machining effect record, and obtain initial data of state comparison;

[0043] According to the initial data of state comparison, associate the comparison data with the performance of machining quality, and if the association result deviates from a preset association threshold, adjust the comparison parameters to determine an intermediate result of adaptability analysis;

[0044] According to the intermediate result, the processing quality is compared with a standard value item by item, at least one mismatch point is obtained, and a deviation range of the point is judged;

[0045] According to a judgment result of the deviation range, the mismatch point is comprehensively arranged with the processing effect record, and a final report of the processing quality is output.

[0046] Preferably, according to the final processing quality evaluation result, a complete log file of the processing process is generated, reference information of iteration is determined through key data points in the complete log file, including:

[0047] According to a pre-established storage library, at least one key data point is obtained from a processing log, the key data point is compared and arranged with a process record, and a complete data set of the processing process is obtained;

[0048] Through the complete data set, according to the demand of real-time monitoring, a monitoring index is matched with an actual value in the processing log item by item;

[0049] If the matching result deviates from a preset matching threshold, the related parameters are adjusted, and a deviation range of the monitoring index is determined;

[0050] According to the deviation range and in combination with a dynamic adjustment target, a correlation analysis is performed on the adjustment parameters and the control performance, at least one mismatch point is obtained, and a specific influence degree of the mismatch point is judged;

[0051] According to a judgment result of the specific influence degree, the mismatch point is comprehensively processed with a result of performance analysis, and a backtracking data report is obtained.

[0052] In a second aspect, the present application provides a high-integration variable-focus laser engraving control system, comprising:

[0053] An acquisition module is configured to acquire an initial surface state data set of surface changes of a workpiece and obtain a dynamic trend distribution map;

[0054] A judgment module is configured to acquire a current focal point position deviation value and an adjusted focal point position coordinate value according to the dynamic trend distribution map, to drive an execution mechanism of a processing device to perform real-time position correction, and to judge whether the correction reaches a preset precision standard;

[0055] A generation module is configured to, if the correction is successful, evaluate fluctuation of a processing effect, and if it is found that a fluctuation value exceeds a preset fluctuation threshold, generate a parameter optimization instruction;

[0056] An output module is configured to fine-tune the operation parameters of the machining equipment according to the parameter optimization instruction, obtain an optimized machining effect record, determine whether the high-end manufacturing standard requirement is met in combination with historical machining data and a current surface state, and output a final machining quality evaluation result.

[0057] A determination module is configured to generate a complete log file of a machining process according to the final machining quality evaluation result, and determine reference information of iteration through a key data point in the complete log file.

[0058] Compared with the prior art, the present application provides a high-integration variable-focus laser engraving control method and system. The workpiece surface is subjected to high-frequency data acquisition by a sensor array to obtain an initial surface state data set. A feature extraction model is used to analyze the surface micro-differences and determine a dynamic trend distribution map. Real-time monitoring technology is used to track the surface changes. When the height fluctuation is detected to exceed a threshold, the focal point position is corrected. The focal point position is adjusted according to a deviation correction algorithm, and the actuator is driven for real-time correction. The machining effect is evaluated through data comparison and analysis, parameter optimization instructions are generated, and a dynamic adjustment control model is called to fine-tune the operation parameters. Finally, the machining quality evaluation result is output, and a complete log file is generated. The present application realizes real-time precision monitoring and dynamic adjustment in the complex surface machining process, improves the machining precision and stability, and meets the requirements of high-end manufacturing standards. BRIEF DESCRIPTION OF DRAWINGS

[0059] Figure 1 is a high-integration variable-focus laser engraving control method flowchart provided by the first embodiment of the present application;

[0060] Figure 2 is a high-integration variable-focus laser engraving control system structure schematic diagram provided by the second embodiment of the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0062] With reference to Figure 1 , the first embodiment of the present application provides a high-integration variable-focus laser engraving control method flowchart, including the following steps:

[0063] S11, obtaining an initial surface state data set of workpiece surface changes and obtaining a dynamic trend distribution map;

[0064] S12, obtaining a current focus position deviation value and an adjusted focus position coordinate value according to the dynamic trend distribution map, to drive an actuator of the machining device to perform real-time position correction, and determining whether the correction meets a preset accuracy standard;

[0065] S13, if the correction is successful, evaluating a fluctuation of a machining effect, and if a fluctuation value exceeds a preset fluctuation threshold, generating a parameter optimization instruction;

[0066] S14, fine-tuning running parameters of the machining device according to the parameter optimization instruction, obtaining an optimized machining effect record, combining historical machining data and a current surface state, determining whether a high-end manufacturing standard requirement is met, and outputting a final machining quality evaluation result;

[0067] S15, generating a complete log file of a machining process according to the final machining quality evaluation result, and determining iterative reference information through key data points in the complete log file.

[0068] In step S11, an initial surface state data set of workpiece surface changes is obtained, and a dynamic trend distribution map is obtained.

[0069] The initial surface state data set of workpiece surface changes comprises:

[0070] The workpiece surface is collected at a high frequency by a sensor array, and data of the topographic features of each micro area are obtained by using a multi-point synchronous scanning mode, wherein the data comprises surface height, roughness value and local curvature, and a preliminary surface state record is obtained;

[0071] According to the preliminary surface state record, the topographic features of each micro area are classified and arranged, a feature matrix is established according to the surface height, the roughness value and the local curvature, and a feature distribution condition of each micro area is determined;

[0072] If the roughness value of one of the micro areas in the feature matrix exceeds a preset roughness threshold, the surface height and the local curvature of the one micro area are corrected, and corrected feature data are obtained;

[0073] The corrected feature data are compared with the initial data set, the topographic feature information of the one micro area is integrated, a complete workpiece surface state description is generated, and a final surface state data set is obtained.

[0074] For example, when collecting high-frequency data on the surface of a workpiece using a sensor array, one can imagine a scenario of precision machining, where the workpiece is a metal plate, and the sensor array scans the surface at a frequency of 1000 times per second, covering a tiny area of 1 square centimeter. Each region has up to 100 collection points, ensuring high-density coverage of data. This multi-point synchronous scanning method can capture subtle changes in the surface, such as small bumps or scratches, providing reliable basic data for subsequent analysis. The surface height data obtained in this way may show that the height variation in a certain area is between 0.01 millimeters and 0.05 millimeters, the roughness value is 1.2 microns, and the local curvature reflects the smoothness or mutation of the area.

[0075] Specifically, when processing data based on the initial surface state record, data processing tools can be used to classify and organize the topographic features of each tiny area. Suppose the height data of a certain area shows significant fluctuations, with a roughness value Ra of 2.5 microns, exceeding the preset threshold of 1.5 microns, and the local curvature shows sharp changes. At this time, when constructing the feature matrix, this area can be marked as an "abnormal area" and its feature distribution recorded. This matrix processing helps quickly locate problem areas and provides a basis for subsequent correction. The technical effect of such a method is to improve the efficiency and accuracy of data analysis, avoiding the tediousness of manual inspection one by one.

[0076] For example, when correcting areas with excessive roughness values, data smoothing tools can be used to adjust the surface height and local curvature. Suppose the height data of a certain area fluctuates greatly, and after smoothing, the height variation is reduced to within 0.02 millimeters, the local curvature is also smoothed, and the corrected roughness value is reduced to 1.3 microns, meeting the processing standard. This correction not only improves the accuracy of the data, but also provides a more reliable reference for subsequent processing, avoiding processing errors caused by surface defects and significantly improving product quality.

[0077] Specifically, in the data fusion stage, the corrected feature data can be compared with the initial data set to integrate the topographic feature information of all tiny areas. Suppose a workpiece surface contains 1000 tiny areas, and after fusion, a complete surface state description is generated, showing that the overall roughness mean is 1.1 microns, the height distribution is uniform, and there are no abnormal mutations in the local curvature. This complete data set can intuitively reflect the processing quality of the workpiece surface and provide an important basis for subsequent process optimization. The beneficial effect is that through data fusion, not only the details of the original data are preserved, but also the overall consistency of the data is improved through correction and integration, providing strong support for quality control.

[0078] For example, when judging whether the area meets the processing standard, multi-dimensional standards can be set, such as the roughness value being lower than 1.5 microns and the height variation range being within 0.03 millimeters. In this way, unqualified areas can be quickly screened and targeted processing can be performed to ensure that the workpiece surface quality meets the expectations. This multi-dimensional judgment method can effectively reduce the misjudgment rate and improve the reliability of detection.

[0079] The obtained dynamic trend distribution map includes:

[0080] According to the initial surface state data set, the height fluctuation and curvature change are obtained, and the fluctuation amplitude and change rate of each micro area are recorded to obtain a preliminary difference feature set;

[0081] The preliminary difference feature set is matched with a pre-established feature extraction template to obtain the surface state change range of each area;

[0082] If the height fluctuation or curvature change of one of the areas in the surface state change range exceeds a preset threshold, the surface state of the one area is corrected, and the local feature of the dynamic trend is obtained from the corrected data;

[0083] According to the local feature, a dynamic trend distribution map is generated, and the surface difference and micro change are data mapped to obtain a complete surface state change distribution description.

[0084] For example, when data processing is performed based on the initial surface state data set, the application principle of the data screening tool can be first focused on. The core of the data screening tool is to layer process the complex surface difference and micro change, and separate the related data of the height fluctuation and curvature change. This layered processing can classify the data according to different feature dimensions, such as fluctuation amplitude and change rate, to form a preliminary difference feature set. Assuming that in a precision metal plate processing scene, the surface height fluctuation amplitude of a certain area is recorded as 0.03 millimeters to 0.08 millimeters, and the curvature change rate shows a local mutation trend, the screening tool can quickly extract these key data to lay a foundation for subsequent analysis.

[0085] For example, when the data comparison tool is used for feature matching, the preliminary difference feature set can be compared with a pre-established feature extraction template to quantitatively analyze the key value domain and change feature. Assuming that the template sets the height fluctuation threshold to 0.05 millimeters and the curvature change rate threshold to a certain specific value, if the data of a certain area exceeds these thresholds, the area is marked as an area that needs to be focused on. This comparison method can accurately locate the surface state change range, which helps to quickly identify potential problem areas and improve the pertinence of data processing.

[0086] For example, data interpolation tools are particularly important for areas exceeding thresholds. Interpolation tools correct the surface conditions of abnormal areas, filling in missing data or smoothing out unusual fluctuations to capture local characteristics of dynamic trends. For example, consider an area with large height fluctuations. After interpolation, the fluctuations are reduced to within 0.02 mm, and the dynamic trend shows a distribution that is more consistent with expectations. This correction method effectively improves data continuity and provides a more reliable basis for subsequent judgments.

[0087] For example, when generating dynamic trend distribution graphs, data visualization tools can map surface differences and subtle changes into intuitive graphics, forming a complete depiction of the distribution of surface state variations. For example, if a metal sheet's surface consists of multiple tiny regions, the graph generated by the visualization tool clearly shows that areas with large height fluctuations are concentrated at the edges, while areas with more gradual curvature changes are located in the center. This graph intuitively reflects the distribution of surface conditions, helping to quickly identify problem areas and develop targeted improvement measures. It also provides an important reference for evaluating processing quality.

[0088] For example, from an overall process perspective, the close integration of the aforementioned steps significantly improves the efficiency and reliability of surface condition analysis. Data screening ensures effective classification of raw data, comparison tools pinpoint problem areas, interpolation correction optimizes data quality, and visualization provides an intuitive basis for the final analysis. Each step revolves around the precise description of the surface condition, collectively supporting a comprehensive assessment of the workpiece's surface quality. This systematic approach not only improves data utilization but also provides strong support for subsequent optimization of machining processes.

[0089] In step S12, the current focus position deviation value and the adjusted focus position coordinate value are obtained according to the dynamic trend distribution diagram to drive the actuator of the processing equipment to perform real-time position correction and determine whether the correction meets the preset accuracy standard.

[0090] The obtaining of the current focus position deviation value according to the dynamic trend distribution graph includes:

[0091] Based on the monitoring data of the dynamic trend distribution diagram, the instantaneous state of the surface change is continuously tracked and compared to obtain a change value of the height fluctuation, and determine whether the change value exceeds a preset change threshold range;

[0092] If the change value of the height fluctuation exceeds a preset threshold range, a deviation detection is performed on the focus position to obtain a deviation value of the current focus position and obtain the deviation distribution status;

[0093] The deviation distribution state is corrected by parameter calculation, and the focal position is updated in real time. Whether the corrected state meets the preset standard is determined.

[0094] If yes, the data of the instantaneous state is mapped into the dynamic trend distribution map according to the corrected focal position, the latest situation of the surface change is recorded, and updated atlas data is obtained.

[0095] For example, when monitoring the surface change by using the dynamic trend distribution map, the application principle of the real-time monitoring tool can be used first. The real-time monitoring tool can capture subtle changes of high fluctuations by continuously tracking the surface instantaneous state. Assuming that in a precision metal plate processing scene, the monitoring tool records the surface height data once per second, and finds that a certain area fluctuates from 0.02 mm to 0.07 mm in a short time, which obviously deviates from the normal range. This real-time data acquisition method provides a timely basis for subsequent comparison.

[0096] For example, for the judgment of whether the height fluctuation change value exceeds the preset threshold, a threshold range of 0.05 mm can be set.

[0097] In a possible implementation, if it is monitored that the fluctuation value of a certain area reaches 0.06 mm, the system will automatically mark the area as abnormal and generate a prompt signal. This threshold comparison mechanism can quickly screen out the areas that need attention, and ensure that the problem will not be ignored.

[0098] For example, after triggering the correction signal generation tool, the deviation detection of the focal position is particularly important. Assuming that the focal position deviation value of a certain area is 0.03 mm, and the distribution presents a local concentration trend. By analyzing the deviation distribution state, the direction and key of correction can be determined. This detection method lays a foundation for subsequent parameter adjustment.

[0099] For example, the role of the deviation numerical processing tool in the correction parameter calculation cannot be ignored.

[0100] In a possible implementation, the system calculates the parameter value that needs to be adjusted according to the deviation value 0.03 mm and the surface characteristics, and generates a correction instruction. This parameter calculation process can ensure the accuracy of the correction and avoid over-adjustment or insufficient adjustment.

[0101] For example, the real-time update of the focal position by the parameter adjustment tool is an important part of the whole process. Assuming that after adjustment, the focal position deviation is reduced from 0.03 mm to 0.01 mm, and the corrected state meets the expected standard. This real-time updating method can timely correct the surface state and ensure the stability in the processing process.

[0102] For example, the state update tool maps the instantaneous state data into a dynamic trend chart, which intuitively reflects the latest situation of surface changes. Assuming that the height fluctuation of a certain area is stabilized within 0.02 millimeters after correction, the updated chart shows that the area has returned to normal. This recording method helps to track the trend of surface state changes over a long period of time.

[0103] For example, for the updated chart data, the overall distribution of surface changes can be further analyzed. Assuming that the chart shows that the edge area fluctuation is still slightly higher than the center area, but both are within the threshold range, indicating that the correction measures have taken effect. This chart updating mechanism provides an important reference for subsequent process improvement, ensuring the continuous optimization of surface quality.

[0104] The adjusted focal point position coordinate value includes:

[0105] The focal point deviation data is compared point by point with the corresponding position coordinates to obtain the specific situation of the deviation distribution and determine the key area of the focal point deviation;

[0106] According to the deviation data of the key area, the focal point control parameter is dynamically adjusted in combination with a preset deviation correction rule to obtain an updated parameter value;

[0107] If the updated parameter value differs from the actual requirements of the workpiece surface, the real-time updated focal point position coordinate is compared with the actual requirements of the workpiece surface to obtain final adjustment data and determine the latest state of the focal point position.

[0108] For example, when analyzing the focal point deviation data record, the basic principle of the deviation analysis tool can be used first. The deviation analysis tool can reveal the specific situation of the deviation distribution through point-by-point comparison of the position coordinates. Assuming that the focal point position coordinates of the workpiece surface are recorded as a series of data points in a precision machining scene, the analysis tool finds that the deviation value of a certain area fluctuates between 0.04 millimeters and 0.08 millimeters, and is obviously concentrated at the edge position of the workpiece. Through this point-by-point comparison method, the key area of the deviation distribution can be clearly located, providing accurate basis for subsequent processing.

[0109] For example, for the deviation data of the key area, the parameter calculation tool dynamically adjusts in combination with a preset deviation correction rule. Assuming that the preset rule specifies that the area with a deviation value exceeding 0.05 millimeters needs to be adjusted first, the system will dynamically calculate the adjustment amplitude of the control parameter according to the deviation data of the edge area to obtain an updated parameter value. This method can ensure that the adjustment process is targeted and avoid interference with normal areas.

[0110] For example, when assessing the degree of matching between the updated parameter value and the actual requirements of the workpiece surface, the application of the state detection tool is crucial. Assuming that the adjusted parameter value reduces the deviation to 0.02 millimeters, but some areas of the workpiece surface have higher precision requirements, needing to be within 0.01 millimeters. The state detection tool can assess the degree of matching by comparing the actual requirements with the current state, and determine whether the adjustment meets the expected standards. This evaluation mechanism helps to discover potential problems in a timely manner and ensures machining precision.

[0111] For example, for the evaluation results, the data mapping tool compares the real-time updated focal point position coordinates with the actual requirements of the workpiece surface to obtain the final adjustment data. Assuming that through mapping comparison, it is found that the focal point position of the edge area still needs to be fine-tuned by 0.01 millimeters, the system will generate final adjustment data according to the comparison results to determine the latest state of the focal point position. This mapping method can intuitively reflect the gap between the deviation and the requirements, providing a reliable reference for subsequent process optimization.

[0112] For example, throughout the process, the coordinated work of various tools reflects the advantages of technology integration. Assuming that from deviation analysis to parameter adjustment, to state evaluation and data mapping, each step is closely linked to ensure accurate control of the focal point position. This interlocking process not only improves the machining consistency of the workpiece surface, but also effectively reduces the defect rate caused by deviation, providing protection for high-quality production.

[0113] For example, for the determination of the deviation distribution status, the analysis tool can also conduct in-depth analysis from different angles. Assuming that after finding that the deviation is concentrated in the edge area, the system further analyzes the frequency and trend of deviation changes and finds that fluctuations are mainly concentrated in the early stages of processing. This multi-dimensional analysis helps to better understand the causes of deviation and provides support for developing targeted correction strategies.

[0114] For example, when dynamically adjusting the control parameters, the system can also make personalized settings according to the material characteristics of the workpiece. Assuming that for workpieces made of harder materials, the adjustment amplitude needs to be appropriately reduced to avoid overcorrection, while for softer materials, the adjustment force can be slightly increased. This flexibility can better adapt to different processing requirements and ensure that the adjustment effect reaches the best state.

[0115] The real-time position correction of the actuator driving the machining equipment to determine whether the correction meets the preset precision standard includes:

[0116] According to the recorded data of the focal point coordinates, the focal point coordinate values are verified with the target position to obtain the specific status of the deviation distribution, the key point positions of the correction are determined from the specific status, and a correction data set is obtained;

[0117] According to the correction data set, send adjustment instructions to the actuator, and obtain the running state of the actuator through the state monitoring tool during adjustment, determine whether the preliminary position correction is completed from the running state, and obtain the preliminary corrected state data;

[0118] If the preliminary corrected state data has differences with the accuracy standard, record the state data through the feedback data acquisition tool, perform secondary verification, determine whether the correction reaches the preset threshold, and determine the correction compliance data;

[0119] According to the correction compliance data, perform final adjustment on the focal point coordinates to generate a correction signal, and obtain the final running state from the correction signal.

[0120] For example, in the verification process of processing focal point coordinate record data, the basic function of the data comparison tool can be used first. The data comparison tool can clearly reveal the specific distribution of deviations by matching the recorded coordinate values with the target position one by one. Assuming that in a precision machining scene, the focal point coordinate data record shows that the deviation value of a certain area is between 0.05 mm and 0.1 mm, and mainly concentrates in the center area of the workpiece, through this comparison method, the key point position that needs to be corrected can be quickly locked, forming a data set of correction requirements, providing a basis for subsequent adjustment.

[0121] For example, for the data set of correction requirements, the application of real-time driving tools is particularly critical. Real-time driving tools will send adjustment instructions to the actuator according to the deviation data to ensure that the focal point position gradually approaches the target value. Assuming that for the deviation of the center area, the instruction requires the actuator to move the focal point position upward by 0.03 mm, and at the same time, the running state of the actuator is obtained in real time through the state monitoring tool to determine whether the preliminary correction is completed. The state monitoring tool may show that the adjusted deviation has been reduced to 0.02 mm, and the preliminary correction state data is thus generated, laying a foundation for subsequent verification.

[0122] For example, if the preliminary corrected state data still has differences with the accuracy standard, the feedback data acquisition tool plays a prominent role. Assuming that the accuracy standard requires the deviation to be less than 0.015 mm, and the current state data is 0.02 mm, the feedback data acquisition tool will record this difference in detail, and perform secondary verification through the data comparison tool. The verification process may find that the deviation of some point positions still exceeds the threshold, and the correction compliance data is thus generated, clearly indicating which areas need further adjustment. This secondary verification mechanism can effectively improve the accuracy of correction.

[0123] For example, during the final adjustment phase, the parameter updating tool optimizes the focus coordinates based on the correction compliance data and generates correction signals through the signal output tool. Assuming that the final adjustment controls the deviation within 0.01 millimeters, the signal output tool feeds back the final running state, indicating that the correction process is complete. This signal generation and state confirmation method ensures the traceability of the entire correction process and provides reliable support for subsequent processing tasks.

[0124] For example, from the overall process, the coordination of the above tools demonstrates the advantages of technology integration. Assuming that from data verification to instruction sending, to state monitoring and final adjustment, each link is closely connected to ensure accurate control of the focus position. This interlocking design not only improves the stability of the processing task, but also effectively reduces processing errors caused by deviation, providing protection for high-quality production.

[0125] For example, the analysis of correction compliance data can also be further explored from different angles. Assuming that the secondary verification finds that the deviation is concentrated in a specific processing stage, the system can further analyze the causes of the deviation, which may be caused by the instability of the equipment during the initial operation. This multi-dimensional analysis helps to develop more targeted correction strategies and improve the adaptability of the overall process.

[0126] At step S13, if the correction is successful, the fluctuation of the processing effect is evaluated, and if the fluctuation value exceeds the preset fluctuation threshold, a parameter optimization instruction is generated.

[0127] If the correction is successful, the fluctuation of the processing effect is evaluated, and if the fluctuation value exceeds the preset fluctuation threshold, a parameter optimization instruction is generated, including:

[0128] Classify the stability indicators in the correction signal to obtain core data of processing precision, and obtain a preliminary comparison result of the core data;

[0129] According to the preliminary comparison result, the fluctuation of the processing precision is checked to obtain specific information of the fluctuation evaluation and determine the detailed distribution of the fluctuation evaluation;

[0130] According to the detailed distribution of the fluctuation evaluation, the running state in the processing process is monitored in real time to obtain a key adjustment point and determine the optimization direction of the key adjustment point;

[0131] Refine the optimization direction to obtain a final parameter adjustment scheme.

[0132] For example, when processing the recorded data of the correction signal, the stable indicators in the signal can be classified first through a data extraction tool. The data extraction tool groups the signal data by time period or processing area and extracts key indicators such as signal strength and duration. Assuming that in a certain precision machining scenario, the recorded data shows that the fluctuation range of the stable indicator of the signal within a certain period of time is between 0.02 and 0.05, through classification processing, the data segment with larger fluctuation can be quickly screened out, forming the core data of processing precision, providing a basis for subsequent comparison.

[0133] For example, the preliminary comparison result of the core data can use a comparison analysis tool to check the fluctuation condition of the processing precision. The tool will compare the core data with the preset standard value one by one, analyze the specific time point and area where the fluctuation occurs. Assuming that the comparison result shows that the fluctuation of a certain processing stage is concentrated in the edge area of the workpiece, and the fluctuation value reaches 0.04, the detailed fluctuation evaluation information can be generated after checking, and the fluctuation distribution is concentrated in the initial stage of edge processing, providing accurate basis for subsequent adjustment.

[0134] For example, according to the detailed distribution of the fluctuation evaluation, the parameter adjustment tool can be used to monitor the running state of the processing process in real time. The tool will continuously track the running parameters of the equipment in different processing areas and record key data such as speed and pressure. Assuming that the monitoring finds that the running speed of the equipment is too high when processing the edge area, which may cause fluctuation, through analysis, it can be determined that the key adjustment point is the speed control parameter, and the optimization direction is to appropriately reduce the speed to reduce the influence of fluctuation.

[0135] For example, from the overall process, the coordinated application of the above tools can effectively improve the stability in the processing process. Assuming that from the extraction of signal data to the fluctuation check, to the parameter monitoring and instruction generation, each link is closely connected, ensuring the continuous optimization of processing precision. Especially for the fluctuation problem of the edge area, through the cooperation of multiple tools, the root cause of the problem can be quickly located and targeted solutions can be developed.

[0136] For example, in specific implementation, in addition to the distribution information of the fluctuation evaluation, supplementary analysis can also be made from the perspective of the processing environment. Assuming that it is found that the fluctuation of the edge area is related to the change of the processing environment temperature, a temperature compensation mechanism can be added when adjusting the parameters to further reduce the interference of environmental factors. This multi-angle analysis ensures the comprehensiveness of the adjustment scheme.

[0137] For example, the refinement of the instruction generation tool can also consider the hardware limitations of the processing equipment. Assuming that the speed adjustment range of the equipment is limited, the tool will preferentially select parameter values within the feasible range when generating instructions to ensure that the scheme can be implemented. This detailed consideration can effectively improve the practicality of the adjustment scheme.

[0138] In step S14, the running parameters of the machining equipment are fine-tuned according to the parameter optimization instruction, an optimized machining effect record is obtained, historical machining data and the current surface state are combined, it is judged whether the requirements of the high-end manufacturing standard are met, and a final machining quality evaluation result is output.

[0139] The fine-tuning of the running parameters of the machining equipment according to the parameter optimization instruction, the obtaining of the optimized machining effect record, the combination of historical machining data and the current surface state, the judgment of whether the requirements of the high-end manufacturing standard are met, and the output of the final machining quality evaluation result include:

[0140] According to the pre-established repository, the surface state of the complex surface is integrated with the historical data, at least one key state indicator is obtained, the key state indicator is compared with the machining effect record, and initial data of state comparison is obtained.

[0141] According to the initial data of state comparison, the comparison data is associated with the performance of the machining quality, and if the association result deviates from the pre-set association threshold, the comparison parameters are adjusted to determine the intermediate result of adaptive analysis.

[0142] According to the intermediate result, the machining quality and the standard value are compared item by item, at least one mismatch point is obtained, and the deviation range of the point is judged.

[0143] According to the judgment result of the deviation range, the mismatch point and the machining effect record are comprehensively arranged, and a final report of the machining quality is output.

[0144] For example, in the preliminary analysis process of the running parameters of the machining equipment, the key running data of the equipment can be systematically disassembled through the pre-established instruction calling tool. Assuming that in the precision machining scene, the tool will focus on the running speed, machining pressure and other parameters of the equipment, and analyze the potential problem points that may affect the machining precision. When analyzing, the tool will process the data in segments, identify that the running speed is high in some time period, preliminarily determine that the speed parameter is the key point that needs to be fine-tuned, and according to the influence degree, arrange the speed adjustment in the priority order.

[0145] For example, for the adjustment order of the key point, the dynamic adjustment tool introduces a pre-set threshold for comparison analysis. Assuming that the ideal threshold range of the speed parameter is 30 to 45 units per minute, and the actual running data shows that the speed reaches 48 units in a certain period of time, which exceeds the upper limit of the threshold. According to the comparison result, the tool automatically triggers the fine-tuning mechanism, gradually reduces the speed parameter to 42 units, and forms the adjusted parameter combination. This way can respond to abnormal data in time and ensure the pertinence of parameter adjustment.

[0146] For example, after parameter adjustment, the real-time monitoring tool continuously collects the state feedback information of the processing equipment, focusing on the stability indicators of processing precision. Suppose during monitoring, it is found that when the adjusted speed parameter is running, the flatness index of the processing surface has improved from the original fluctuation of 0.03 to 0.02, indicating that the stability index has improved. The tool will further analyze the matching degree of the index with the preset standard to determine whether the current parameter combination meets the expectations, providing data support for subsequent optimization.

[0147] For example, from the analysis of key points to the determination of the final scheme path, the whole process embodies the systematicness and dynamics of parameter adjustment. Suppose that in the running of the processing equipment, the fine-tuning of the speed parameter not only improves the surface flatness, but also indirectly reduces the vibration problem in the running of the equipment. Such a feedback mechanism can help operators more accurately grasp the state of the equipment and improve the reliability of the processing process.

[0148] For example, in specific implementation, in addition to monitoring the stability indicators, real-time changes in the processing environment can also be supplemented and analyzed. Suppose that it is found that the processing precision still has slight fluctuations at certain times, which may be due to environmental humidity, and the monitoring tool will record relevant data for subsequent optimization. This multi-angle data collection method ensures the comprehensiveness and adaptability of the optimization scheme.

[0149] In step S15, according to the final processing quality evaluation result, a complete log file of the processing process is generated, and the reference information of iteration is determined through the key data points in the complete log file.

[0150] According to the final processing quality evaluation result, a complete log file of the processing process is generated, and the reference information of iteration is determined through the key data points in the complete log file, including:

[0151] According to the pre-established repository, at least one key data point is obtained from the processing log, and the key data point is compared and arranged with the process record to obtain a complete data set of the processing process;

[0152] According to the real-time monitoring requirements, the monitoring indicators are matched with the actual values in the processing log item by item through the complete data set;

[0153] If the matching result deviates from the preset matching threshold, adjust the related parameters to determine the deviation range of the monitoring indicators;

[0154] According to the deviation range and in combination with the target of dynamic adjustment, the performance of the adjustment parameters and the control performance is associated analyzed to obtain at least one mismatch point, and the specific influence degree of the mismatch point is judged;

[0155] According to the judgment result of the specific influence degree, the unmatched point is comprehensively processed with the result of performance analysis to obtain a backtracking data report.

[0156] For example, for the quality evaluation target, the output tool integrates and arranges the unmatched points and the machining effect record to generate a final report. Assuming that the report indicates that the roughness deviation is related to temperature fluctuation and equipment pressure setting in the machining process, it is suggested to optimize the temperature control range to within plus or minus 2 degrees Celsius and adjust the pressure parameter. Through multi-dimensional arrangement, the report not only reveals the root cause of the problem, but also provides feasible suggestions for subsequent improvement. This comprehensive output mode can effectively support decision-making and improve the stability of machining quality.

[0157] For example, for the data backtracking target, the arrangement tool is used to comprehensively process the unmatched points and the performance analysis results to generate a backtracking data report. Assuming that the report indicates that the local flatness deviation is related to the environmental humidity during machining, it is suggested to strengthen humidity control in subsequent machining and maintain it between 40% and 50%. Through backtracking analysis, the root cause of the problem can be clearly traced, providing data support for improvement measures. This comprehensive processing method not only sorts out historical problems, but also lays a foundation for the stability of future machining quality.

[0158] For example, from the perspective of dynamic adjustment, the parameter optimization tool can also perform extended analysis by combining other environmental factors when analyzing the unmatched points. Assuming that it is found that the ventilation conditions of the machining area may also affect the flatness, it is suggested to optimize the ventilation settings in the report. This multi-dimensional analysis further enriches the comprehensiveness of the backtracking data, ensuring that the quality evaluation covers more potential influencing factors.

[0159] For example, in specific implementation, the processing method for each technical topic is closely related to the quality improvement of complex surface treatment. From data extraction to parameter adjustment, to the generation of backtracking reports, each link forms a closed loop, ensuring the controllability and consistency of the machining process. The benefits brought by this rigorous logic are that it can continuously improve the machining process and provide strong support for high-end manufacturing standards.

[0160] The above describes only the preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can make equivalent replacements or changes to the technical solutions and inventive concepts of the present application within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

[0161] In summary, the application discloses a high-integration variable-focus laser engraving control method and system, which acquires an initial surface state data set through high-frequency data acquisition of a workpiece surface by a sensor array. A feature extraction model is used to analyze the surface micro-differences and determine a dynamic trend distribution map. Real-time monitoring technology is used to track surface changes, and when the height fluctuation exceeds the threshold, the focal point position is corrected. The focal point position is adjusted according to the deviation correction algorithm, and the actuator is driven for real-time correction. The processing effect is evaluated through data comparison and analysis, parameter optimization instructions are generated, and the dynamic adjustment control model is called to fine-tune the operating parameters. Finally, the processing quality evaluation result is output, and a complete log file is generated. The application realizes real-time precision monitoring and dynamic adjustment in complex surface processing, improves processing precision and stability, and meets high-end manufacturing standards.

[0162] Reference Figure 2 The second embodiment of the application provides a high-integration variable-focus laser engraving control system, comprising:

[0163] The acquisition module 201 is configured to acquire an initial surface state data set of the surface change of the workpiece and obtain a dynamic trend distribution map.

[0164] The judgment module 202 is configured to acquire a current focal point position deviation value and an adjusted focal point position coordinate value according to the dynamic trend distribution map, drive the actuator of the processing equipment to perform real-time position correction, and judge whether the correction meets the preset precision standard.

[0165] The generation module 203 is configured to evaluate the fluctuation of the processing effect if the correction is successful, and generate parameter optimization instructions if the fluctuation value exceeds the preset fluctuation threshold.

[0166] The output module 204 is configured to fine-tune the operating parameters of the processing equipment according to the parameter optimization instructions, obtain an optimized processing effect record, combine historical processing data and the current surface state, judge whether the high-end manufacturing standard requirement is met, and output the final processing quality evaluation result.

[0167] The determination module 205 is configured to generate a complete log file of the processing process according to the final processing quality evaluation result, and determine the reference information of iteration through the key data points in the complete log file.

[0168] It should be noted that the high-integration variable-focus laser engraving control system provided by the embodiments of the application is used to execute all process steps of the high-integration variable-focus laser engraving control method of the above-mentioned embodiments, and the working principles and beneficial effects of the two are one-to-one corresponding, so they will not be repeated.

[0169] The embodiment of the present application further provides an electronic device. The electronic device comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, for example, a high-integration variable-focus laser engraving control program. The processor executes the computer program to implement the steps in each of the above high-integration variable-focus laser engraving control method embodiments, for example Figure 1 The processor executes the computer program to implement the functions of each module / unit in each of the above device embodiments, for example, an acquisition module.

[0170] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the electronic device.

[0171] The electronic device can be a desktop computer, a notebook computer, a palm computer, a smart tablet, and the like. The electronic device can comprise, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above components are only examples of the electronic device and do not limit the electronic device, and the electronic device can comprise more or fewer components than the above, or combine certain components, or different components, for example, the electronic device can further comprise an input / output device, a network access device, a bus, and the like.

[0172] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, or the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like. The processor is a control center of the electronic device, and connects all parts of the electronic device through various interfaces and lines.

[0173] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the electronic device by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function (such as a sound playing function, an image playing function, etc.), and the like; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), and the like. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0174] The modules / units integrated in the electronic device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can realize the steps of the above-mentioned various method embodiments when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the contents included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0175] It should be noted that the apparatus embodiments described above are merely illustrative, and the units described as separate units can or can not be physically separate, and the units displayed as units can or can not be physical units, i.e. can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. In addition, the connection relationship between the modules in the apparatus embodiment provided by the present application indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0176] The above specific embodiments further illustrate the purpose, technical scheme and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the protection scope of the present application. It is particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A highly integrated variable focus laser engraving control method, characterized in that: include: Obtaining an initial surface state data set of workpiece surface changes and obtaining a dynamic trend distribution diagram; Obtaining the current focus position deviation value and the adjusted focus position coordinate value based on the dynamic trend distribution graph to drive the actuator of the processing equipment to perform real-time position correction and determine whether the correction meets the preset accuracy standard; if the correction is successful, evaluating the fluctuation of the processing effect; if it is found that the fluctuation value exceeds the preset fluctuation threshold, generating a parameter optimization instruction; Fine-tune the operating parameters of the processing equipment according to the parameter optimization instructions, obtain optimized processing effect records, combine historical processing data and current surface conditions to determine whether the requirements of high-end manufacturing standards are met, and output the final processing quality evaluation results; generating a complete log file of the machining process according to the final machining quality assessment result, and determining iterative reference information through key data points in the complete log file; Wherein, the obtaining of an initial surface state data set of workpiece surface changes includes: The workpiece surface is collected at high frequency by a sensor array, and a multi-point synchronous scanning method is used to obtain data on the topographic features of each tiny area. The data includes surface height, roughness value and local curvature, and a preliminary surface state record is obtained; Classifying and arranging the topographical features of each micro-region according to the preliminary surface state record, establishing a feature matrix according to the surface height, the roughness value and the local curvature, and determining the feature distribution of each micro-region; If the roughness value of one of the micro areas in the feature matrix exceeds a preset roughness threshold, the surface height and local curvature of the one of the micro areas are corrected to obtain corrected feature data; Comparing the corrected feature data with the initial data set, integrating the topographic feature information of one of the micro-regions, generating a complete description of the workpiece surface state, and obtaining a final surface state data set; The step of obtaining a dynamic trend distribution diagram includes: The height fluctuation and curvature change are obtained based on the initial surface state data set, and the fluctuation amplitude and change rate of each small area are recorded to obtain a preliminary set of difference features; Matching the preliminary difference feature set with a pre-established feature extraction template to obtain the surface state variation range of each area; If the height fluctuation or curvature change of one of the regions within the surface state change range exceeds a preset threshold, the surface state of the one of the regions is corrected, and a local feature of the dynamic trend is obtained from the corrected data; A dynamic trend distribution diagram is generated based on the local features, and data mapping is performed on surface differences and minor changes to obtain a complete distribution description of surface state changes.

2. The highly integrated variable focus laser engraving control method according to claim 1, characterized in that: The obtaining of the current focus position deviation value according to the dynamic trend distribution graph includes: Based on the monitoring data of the dynamic trend distribution diagram, the instantaneous state of the surface change is continuously tracked and compared to obtain a change value of the height fluctuation, and determine whether the change value exceeds a preset change threshold range; If the change value of the height fluctuation exceeds a preset threshold range, a deviation detection is performed on the focus position to obtain a deviation value of the current focus position and obtain a deviation distribution status; Calculating correction parameters for the deviation distribution, updating the focus position in real time, and determining whether the corrected state meets preset standards; If so, the instantaneous state data is mapped to the dynamic trend distribution map according to the corrected focus position, and the latest situation of the surface change is recorded to obtain updated map data.

3. The highly integrated variable focus laser engraving control method according to claim 2, characterized in that: The step of obtaining the adjusted focus position coordinate value includes: Compare the focus deviation data with the corresponding position coordinates point by point to obtain the specific situation of the deviation distribution and determine the key areas of focus deviation; According to the deviation data of the key area, combined with the preset deviation correction rules, the focus control parameters are dynamically adjusted to obtain updated parameter values; If there is a difference between the updated parameter value and the actual requirement of the workpiece surface, the real-time updated focus position coordinates are compared with the actual requirement of the workpiece surface to obtain the final adjustment data and determine the latest state of the focus position.

4. The highly integrated variable focus laser engraving control method according to claim 3, characterized in that: The method of performing real-time position correction on the actuator of the driving processing equipment and determining whether the correction reaches a preset accuracy standard includes: Verifying the focus coordinate value and the target position based on the recorded data of the focus coordinates, obtaining a specific condition of the deviation distribution, determining the key points of correction from the specific condition, and obtaining a correction data set; sending an adjustment instruction to the actuator according to the correction data set, obtaining the operating status of the actuator through a status monitoring tool during the adjustment, determining whether the preliminary position correction is completed based on the operating status, and obtaining status data after preliminary correction; If the status data after the preliminary correction is different from the accuracy standard, the status data is recorded through the feedback data collection tool, and a secondary verification is performed to determine whether the correction reaches the preset threshold and determine the correction compliance data; The focus coordinates are finally adjusted according to the correction compliance data to generate a correction signal, and a final operating state is obtained from the correction signal.

5. The highly integrated variable focus laser engraving control method according to claim 1, characterized in that: If the correction is successful, the fluctuation of the processing effect is evaluated. If the fluctuation value exceeds the preset fluctuation threshold, a parameter optimization instruction is generated, including: Classifying and processing the stability indicators in the correction signal to obtain core data of the machining accuracy and obtaining a preliminary comparison result of the core data; According to the preliminary comparison results, the fluctuation of the processing accuracy is checked to obtain specific information of the fluctuation assessment and determine the detailed distribution of the fluctuation assessment; Based on the detailed distribution of the fluctuation assessment, the operating status of the processing process is monitored in real time, key adjustment points are obtained, and the optimization direction of the key adjustment points is determined; The optimization direction is refined to obtain a final parameter adjustment solution.

6. The highly integrated variable focus laser engraving control method according to claim 1, characterized in that: The operating parameters of the processing equipment are fine-tuned according to the parameter optimization instructions to obtain optimized processing effect records. Combined with historical processing data and current surface conditions, it is determined whether the requirements of high-end manufacturing standards are met and the final processing quality evaluation results are output, including: Integrate the surface state of the complex surface with historical data according to a pre-established repository to obtain at least one key state indicator, compare the key state indicator with the processing effect record, and obtain initial data for state comparison; Correlating the comparison data with the performance of the processing quality based on the initial data of the state comparison, and adjusting the comparison parameters if the correlation result deviates from a preset correlation threshold to determine an intermediate result of the adaptability analysis; According to the intermediate results, the processing quality is compared with the standard value item by item to obtain at least one mismatching point, and the deviation range of the mismatching point is determined; According to the judgment result of the deviation range, the mismatching points and the processing effect records are comprehensively sorted out, and the final report of the processing quality is output.

7. The highly integrated variable focus laser engraving control method according to claim 1, characterized in that: Generating a complete log file of the machining process according to the final machining quality assessment result, and determining iterative reference information through key data points in the complete log file, including: Obtaining at least one key data point from the processing log according to a pre-established repository, and comparing and collating the key data point with the process record to obtain a complete data set of the processing process; Using the complete data set, the monitoring indicators are matched item by item with the actual values ​​in the processing log according to the requirements of real-time monitoring; If the matching result deviates from the preset matching threshold, relevant parameters are adjusted to determine the deviation range of the monitoring indicator; Based on the deviation range and in combination with the dynamic adjustment target, correlation analysis is performed on the adjustment parameter and the control performance, at least one mismatch point is obtained, and the specific impact of the mismatch point is determined; According to the determination result of the specific impact degree, the mismatch points and the results of the performance analysis are comprehensively processed to obtain a retrospective data report.

8. A highly integrated variable-focus laser engraving control system, used to implement the highly integrated variable-focus laser engraving control method according to any one of claims 1 to 7, characterized in that: include: An acquisition module is used to obtain an initial surface state data set of workpiece surface changes and obtain a dynamic trend distribution diagram; a judgment module, configured to obtain a current focus position deviation value and an adjusted focus position coordinate value based on the dynamic trend distribution diagram, so as to drive an actuator of the processing equipment to perform real-time position correction and determine whether the correction meets a preset accuracy standard; A generation module is used to evaluate the fluctuation of the processing effect if the correction is successful, and generate parameter optimization instructions if the fluctuation value exceeds a preset fluctuation threshold; An output module is used to fine-tune the operating parameters of the processing equipment according to the parameter optimization instructions, obtain a record of the optimized processing effect, combine historical processing data and current surface conditions, determine whether the requirements of high-end manufacturing standards are met, and output a final processing quality evaluation result; The determination module is used to generate a complete log file of the processing process according to the final processing quality evaluation result, and determine iterative reference information through key data points in the complete log file.

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