Dynamic layer processing method and device based on color grouping and storage medium

Abstract

The invention discloses a dynamic layer processing method and device based on color grouping and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: carrying out the clustering analysis of layers of a to-be-processed primitive based on the color features of the to-be-processed primitive, and obtaining at least one processing layer group; according to the material type identifiers associated with the layers in the processing layer group, analyzing process rules of the layers in the processing layer group, and generating a process rule set corresponding to the processing layer group; based on the process rule set corresponding to the processing layer group, performing compensation calculation in combination with the equipment operation parameters, and generating a target processing instruction set of the processing layer group; and based on the layers in the processing layer group, combining with the target processing instruction set corresponding to the processing layer group to carry out association, and packaging to generate a processing file. The technical problem of low efficiency of dynamic layer processing is solved, and the efficiency of dynamic layer processing is improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and particularly to a dynamic layer processing method, device, and storage medium based on color grouping. Background Art

[0002] The application field of dynamic layer processing technology is very extensive, including aerospace, automobile manufacturing, medical devices, electronic information, etc. It not only improves the technical level of traditional industries but also provides technical support for the development of emerging industries.

[0003] In related technologies, for complex processing scenarios with multiple materials and multiple processes, it usually relies on manual division of processing layer groups and setting of processing sequences, processing parameters, and process rules. Among them, operators need to classify processing elements into layers, adjust parameters, and configure process rules based on experience, resulting in low efficiency of dynamic layer processing.

[0004] The above content is only used to assist in understanding the technical solution of the present application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of the present application is to provide a dynamic layer processing method, device, and storage medium based on color grouping, aiming to solve the technical problem of low efficiency of dynamic layer processing.

[0006] To achieve the above purpose, the present application proposes a dynamic layer processing method based on color grouping, and the method includes: Performing clustering analysis on the layers of the to-be-processed primitive based on the color characteristics of the to-be-processed primitive to obtain at least one processing layer group; Analyzing the process rules of the layers in the processing layer group according to the material type identifiers associated with the layers in the processing layer group, and generating a process rule set corresponding to the processing layer group; Performing compensation calculation in combination with the device operation parameters based on the process rule set corresponding to the processing layer group to generate a target processing instruction set for the processing layer group; Associating the layers in the processing layer group in combination with the target processing instruction set corresponding to the processing layer group, and packing to generate a processing file.

[0007] In an embodiment, according to the color characteristics, the layers with different color characteristics are distinguished; Based on the layers, through clustering analysis, the layers with the same color characteristic are aggregated to generate an initial processing layer group; Based on the initial processing layer group, in combination with adjustment instructions, the processing layer group is generated.

[0008] In one embodiment, based on the adjustment instruction, the processing order changes of each layer are parsed to generate adjustment parameters; According to the adjustment parameters, the processing order of each layer in the initial processing layer group is updated to generate the processing layer group.

[0009] In one embodiment, based on the material type identifier, the process rules corresponding to the material type identifier are parsed, and the process rules are associated with the to-be-processed primitive corresponding to the material type identifier to obtain the process rules of the to-be-processed primitive; The process rules of the to-be-processed primitives in the processing layer group are classified and integrated to generate the process rule set.

[0010] In one embodiment, based on the process rule set, the path efficiency is optimized through a decision algorithm to generate a processing path instruction set; According to the processing path instruction set, combined with the device operation parameters associated with the processing path instruction set, compensation calculation is performed to obtain compensation parameters; The compensation parameters are added to the corresponding processing path instruction set to generate the target processing instruction set.

[0011] In one embodiment, based on each layer in the processing layer group and the target processing instruction set corresponding to the processing layer group, association verification is performed to determine the association relationship between each layer and the target processing instruction set; Based on the processing layer group, the target processing instruction set corresponding to the processing layer group, and the association relationship between each layer and the target processing instruction set, it is packaged and converted into the processing file.

[0012] In one embodiment, the processing file is transmitted to the processing device; Through the parameter matching and optimization of the target processing instruction set and the laser, according to the matching degree, the target processing instruction set is allocated to obtain the control parameters corresponding to the laser; Based on each control parameter, the cutting heads corresponding to each laser are controlled to perform a collaborative processing operation to obtain the processed product.

[0013] In one embodiment, each processed / to-be-processed layer group is displayed on the visualization interface at different transparency levels, and a processing process topology diagram of each to-be-processed layer is rendered on the visualization interface; In response to the user's click operation on a specific layer in the visualization interface, the control parameters, processing process, and quality inspection indicators of the device associated with the layer are dynamically displayed.

[0014] In addition, to achieve the above object, the present application further provides a dynamic layer processing device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. The computer program is configured to implement the steps of the dynamic layer processing method based on color grouping as described above.

[0015] In addition, to achieve the above object, the present application further provides a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the steps of the dynamic layer processing method based on color grouping as described above.

[0016] The present application provides a dynamic layer processing method based on color grouping, which includes performing clustering analysis on the layers of the to-be-processed primitive based on the color features of the to-be-processed primitive to obtain at least one processed layer group; parsing the process rules of the layers in the processed layer group according to the material type identifiers associated with the layers in the processed layer group, and generating a process rule set corresponding to the processed layer group; performing compensation calculation based on the process rule set corresponding to the processed layer group in combination with the device operation parameters to generate a target processing instruction set corresponding to the processed layer group; and associating the layers in the processed layer group in combination with the target processing instruction set corresponding to the processed layer group, and packaging to generate a processing file. Through color features, intelligent grouping is achieved, combined with the dynamic adjustment of the physical processing sequence, to quickly and efficiently complete the dynamic processing of the layer group, improving the efficiency of dynamic layer processing.

[0017] In summary, the present application realizes the differentiation of layers, generates a processed layer group and a processing instruction set through the color features of the to-be-processed primitive and the material type identifier, and then obtains a processing file, overcoming the technical problem that operators need to collect layers of processing elements, adjust parameters, and configure process rules based on experience, resulting in low efficiency of dynamic layer processing, and improving the efficiency of dynamic layer processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1Schematic flowchart of the first embodiment of the dynamic layer processing method based on color grouping in this application; Figure 2 Schematic flowchart of the second embodiment of the dynamic layer processing method based on color grouping in this application; Figure 3 Schematic flowchart of the fifth embodiment of the dynamic layer processing method based on color grouping in this application; Figure 4 Schematic flowchart of the seventh embodiment of the dynamic layer processing method based on color grouping in this application; Figure 5 Schematic structural diagram of the dynamic layer processing device in this application.

[0021] The realization of the purpose, functional characteristics and advantages of this application will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0022] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0023] In the related art, for complex processing scenarios with multiple materials and multiple processes, it is usually dependent on manual division of processing layer groups and setting of processing sequences. Among them, the operator needs to collect layers of processing elements, adjust parameters and configure process rules based on experience, resulting in low efficiency of dynamic layer processing.

[0024] This application provides a solution: first, perform clustering analysis on the layers of the to-be-processed primitive based on the color features of the to-be-processed primitive to obtain at least one processing layer group, then parse the process rules of the layers in the processing layer group according to the material type identifiers associated with the layers in the processing layer group, generate a process rule set corresponding to the processing layer group, then, based on the process rule set corresponding to the processing layer group, perform compensation calculation in combination with the device operation parameters to generate a target processing instruction set for the processing layer group, and finally, based on the layers in the processing layer group, associate them in combination with the target processing instruction set corresponding to the processing layer group, and package them to generate a processing file.

[0025] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a dynamic layer processing device, etc. that can implement the above functions. The following takes the dynamic layer processing device as an example to illustrate this embodiment and the following embodiments.

[0026] In order to better understand the technical solutions of this application, the following will be described in detail in combination with the accompanying drawings of the specification and specific implementation manners.

[0027] An embodiment of the present application provides a dynamic layer processing method based on color grouping. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the dynamic layer processing method based on color grouping of the present application.

[0028] In this embodiment, the dynamic layer processing method based on color grouping includes steps S10 to S40: Step S10: Perform clustering analysis on the layers of the to-be-processed primitive based on the color characteristics of the to-be-processed primitive to obtain at least one processed layer group.

[0029] In this embodiment, the to-be-processed primitive is an independent geometric graphic unit. The color characteristics include the hue and brightness of the color. The layer refers to a two-dimensional primitive section. Clustering analysis refers to grouping through the similarities and differences of color characteristics, and taking the layers with the same color characteristics as the same processed layer group. The adjustment instruction refers to the drag-and-drop sorting instruction, lock state switching instruction, and visualization display parameter input by the user through the interface. The processed layer group refers to the set of layers corresponding to the primitives with the same color characteristics.

[0030] As an alternative implementation, extract the color characteristics of the to-be-processed primitive, and by comparing and judging the hue and brightness of the color characteristics, divide the primitives with the same color characteristics into at least one primitive group, and set the layers corresponding to the primitive group as at least one processed layer group.

[0031] As an alternative implementation of adjusting the primitive group, the user manually adjusts the processing order and parameter state of the primitive group to generate an adjustment instruction to perform relevant adjustments on the primitive group.

[0032] As an alternative implementation of adjusting the processed layer group, parse the adjustment instruction input by the user, and according to the parsed adjustment instruction, change the processing order and status information of the layers in the group, and update the processing order and status information of the layers in the processed layer group.

[0033] Step S20: According to the material type identifier associated with the layer in the processed layer group, parse out the process rules of the layer in the processed layer group, and generate a process rule set corresponding to the processed layer group.

[0034] In this embodiment, the material type identifier refers to a unique identification identifier associated through a material database. The process rule refers to including material physical properties, process constraint conditions, and equipment load parameters. The process rule set is the set of process rules corresponding to each layer in the processed layer group.

[0035] As an alternative implementation, based on the material type identifier associated with the layers in the processing layer group, retrieve the physical properties of the materials for the corresponding layers in the primitive property table, load the preset process rule template, and based on the preset process rule template, perform multi-condition matching through process preset conditions. Use the parameters that meet the matching conditions as the basic process parameters. Detect rule conflicts by performing rule conflict detection on the basic process parameters and make fine-tuning for the detected conflicts to obtain the process rules corresponding to the layers. Then, integrate and process the process rules corresponding to each layer in the processing layer group and encapsulate them into a structured process rule set.

[0036] Step S30: Based on the process rule set corresponding to the processing layer group, perform compensation calculation in combination with the equipment operation parameters to generate the target processing instruction set for the processing layer group.

[0037] In this embodiment, the equipment operation parameters refer to the output stability of the laser power, the movement trajectory of the cutting head, the collision interference check, and the thermal deformation coefficient. The compensation calculation means generating parameters through the equipment operation parameters to correct the deviation between the theoretical parameters and the measured values. The target processing instruction set refers to an executable code set that includes the optimized processing path, laser control parameters, and equipment coordination instructions.

[0038] As an alternative implementation, based on the process rule set corresponding to the processing layer group, optimize the path efficiency through a decision algorithm to generate the optimal processing path. Generate a processing path instruction set based on the processing path and the equipment operation parameters. Perform compensation calculation on the theoretical parameters of the process rule set and the equipment operation parameters, dynamically adjust the equipment operation speed through an energy balance strategy, and call the kinematic model to optimize the equipment operation trajectory. Add the compensation parameters obtained through optimization, including the equipment operation speed and the equipment operation trajectory, into the corresponding processing path instruction set to generate the target processing instruction set.

[0039] Step S40: Based on the layers in the processing layer group, associate them with the target processing instruction set corresponding to the processing layer group and package them to generate a processing file.

[0040] In this embodiment, the processing file refers to an equipment-readable file that encapsulates geometric data, process parameters, and control instructions.

[0041] As an alternative implementation, the geometric coordinate sequence of the processing layer group is integrated with the cutting coordinate parameters of the target processing instruction set, so that the layers in the processing layer group are associated with the corresponding cutting coordinate parameters. The topological sorting algorithm is used for the associated target processing instruction set to generate a global processing path. Based on the global processing path, the kinematic simulation module performs collision and interference checking, and the thermal deformation compensation algorithm is applied to generate path compensation parameters. The global processing path is optimized using the path compensation parameters, and the optimized global processing path is converted into device-specific code and encapsulated into an encrypted processing file using a binary protocol.

[0042] Exemplarily, open the SVG file in a computer device, parse out the layers in the SVG file, classify them according to the color characteristics of the primitives to be processed, and cluster the layers corresponding to the primitives with blue characteristics into an aluminum alloy layer group. The operator drags and adjusts the layer priorities through a visual interface and locks the key layers. The system calls the material database according to the material identifier associated with the layer group, parses the process rules corresponding to the thickness and surface state, matches the laser power, cutting speed, and auxiliary gas through the process rules, generates a process rule set after performing conflict detection, collects device parameters, and uses the extended Kalman filter to calculate the power compensation coefficient and the trajectory offset compensation amount, dynamically recalculate the speed in combination with the energy density equilibrium model, and output a target processing instruction set including device-specific code and laser modulation instructions. Finally, the target processing instruction set is encapsulated into a binary encrypted processing file.

[0043] Since the layers are distinguished by the color characteristics of the primitives to be processed and the material type identifier, a processing layer group and a processing instruction set are generated, and then a processing file is obtained, which overcomes the technical problem of low efficiency in dynamic layer processing caused by the need for operators to classify processing elements into layers, adjust parameters, and configure process rules based on experience, and improves the efficiency of dynamic layer processing.

[0044] Based on any of the above embodiments, in the second embodiment of the present application, with reference to Figure 2 , Figure 2 is a schematic flowchart of the second embodiment of the dynamic layer processing method based on color grouping of the present application. The step S10 includes steps A11 to A13: Step A11, distinguish the layers with different color characteristics according to the color characteristics.

[0045] In this embodiment, the layers included in the primitives are distinguished by the color characteristics of the primitives, and the layers with different color characteristics are separated.

[0046] As an alternative implementation, extract the color characteristics of the primitives, make a comparison and judgment according to the hue and brightness in the color characteristics, and separate the layers with different color characteristics.

[0047] Step A12: Based on the said layer, through clustering analysis, aggregate the layers with the same said color feature to generate an initial processed layer group.

[0048] In this embodiment, clustering analysis refers to a method of automatically grouping layers by color features. The initial processed layer group refers to a grouping that only performs clustering through the distinction of color features and includes groups of layers with the same color feature.

[0049] As an alternative implementation, through clustering analysis, group the layers with the same color feature into at least one layer group, filter the noise layers based on the layer group, and obtain the initial processed layer group.

[0050] Step A13: Based on the said initial processed layer group, combined with adjustment instructions, generate the processed layer group.

[0051] In this embodiment, the adjustment instructions include a drag-and-drop sorting instruction, a lock state switching instruction, and visualization display parameters input through the interface. The drag-and-drop sorting instruction is used to change the order of the layers in the initial processed layer group. The lock state switching instruction is used to lock the selected layers. The visualization display parameters are used to adjust various display parameters of the layers in the visualization interface to obtain the processed group.

[0052] As an alternative implementation, based on the initial processed layer group, according to the adjustment instructions performed by the user, including a drag-and-drop sorting instruction, a lock state switching instruction, and visualization display parameters input through the interface, change the order of the layers in the initial processed layer group, lock the selected layers, and adjust various display parameters of the layers in the visualization interface to obtain the processed group.

[0053] Exemplarily, first extract the color features of the layers including hue and brightness through the color space, normalize the color feature components into feature vectors, calculate the similarity matrix based on the Euclidean distance to distinguish the layers with significant color differences, then use the density clustering algorithm to group the layers with the same color feature, remove the noise layers with Mahalanobis distance > 3 and generate the initial processed layer group, and finally load the user adjustment instructions, such as manually setting the priority and the power upper limit of 2000W, verify the parameter conflicts through the rule algorithm, such as the matching of the cutting speed and the material melting point, and dynamically bind the device capability parameters and generate an executable processed layer group.

[0054] Since intelligent grouping is achieved through color features, combined with the dynamic adjustment of the physical processing order, the dynamic processing of the layer group is completed quickly and efficiently, improving the efficiency of dynamic layer processing.

[0055] Based on any of the above embodiments, in the third embodiment of the present application, the said step A13 includes steps B11~B12: Step B11: Based on the adjustment instruction, parse the change in the processing order of each layer to generate adjustment parameters.

[0056] In this embodiment, the change in the processing order refers to changing the arrangement order and locking state of the layers through the drag-and-drop sorting instruction and the locking state switching instruction in the adjustment instruction, thereby changing the processing order of the layers. The adjustment parameter refers to the parameter for adjusting the processing order of the layers obtained by integrally analyzing the layer ID, sorting rule, and parameter override item in the adjustment instruction and adjusting the conflict items.

[0057] As an alternative implementation, extract the change in the processing order including the layer ID, sorting rule, and parameter override item in the adjustment instruction through a parser, and construct the adjustment parameter for layer processing based on the layer ID, sorting rule, and parameter override item.

[0058] Step B12: Update the processing order of each layer in the initial processing layer group according to the adjustment parameter to generate the processing layer group.

[0059] In this embodiment, "update" means changing the processing order of the layers by directly applying the adjustment parameter to the control of the layer processing order.

[0060] As an alternative implementation, based on the adjustment parameter, combine with a sorting algorithm to generate a new processing queue, check for conflict items in the new processing queue against a preset processing order rule library. If there is a conflict in the cutting order of the layers, adjust and prompt according to the preset processing order rule library, and generate a feedback compensation. Combine the adjustment parameter and the feedback compensation to adjust the processing order of each layer in the initial processing layer group to obtain the processing layer group.

[0061] Exemplarily, parse the adjustment instruction (such as "Layer3 priority = 10, Layer2 cutting speed = 80mm / s") through a parser, extract the layer ID and parameter change items, then construct a processing queue based on the sorting algorithm (such as Layer3 → Layer1 → Layer2), load the color features (such as H = 0.8 / S = 0.9 / V = 0.6 for Layer3) and layer processing order of the initial processing layer group, check the feasibility of the layer processing order, adjust and generate adjustment parameters through a preset layer processing rule library, update the priority queue through the adjustment parameter, and finally generate the processing layer group.

[0062] Since through the dynamic adjustment based on the user and the verification using the processing order rule library, it not only ensures that the processing order meets the user's expectations but also guarantees the processing quality, improving the reliability of dynamic layer processing.

[0063] Based on any of the above embodiments, in the fourth embodiment of the present application, step S20 includes steps C11 to C12: Step C11, based on the material type identifier, parse out the process rules corresponding to the material type identifier, and associate the process rules with the to-be-processed primitive corresponding to the material type identifier to obtain the process rules of the to-be-processed primitive.

[0064] In this embodiment, the material type identifier refers to a mark that uniquely distinguishes material types.

[0065] As an optional implementation manner, query the process rule library through the material type identifier, use the preset process rules that match the material type identifier, based on the preset process rules, adopt an algorithm to infer the matching between the geometric attributes of the primitive and the rules, optimize the multi-rule conflicts in the preset process rules, and bind the optimized preset process rules to the to-be-processed primitive attribute table to generate process rules including material identifiers, process parameters, and check codes.

[0066] Step C12, classify and integrate the process rules of the to-be-processed primitives in the processing layer group to generate the process rule set.

[0067] In this embodiment, the process rule set refers to a set of processed parameters after classification and integration. Classification and integration means classifying the same type of process rules into one category for integration, and integrating the process rules corresponding to the primitives in the same processing layer group into a process rule set.

[0068] As an optional implementation manner, classify and integrate the process rules by material type and processing type into process rule subsets, adopt a relaxation algorithm to resolve multi-rule conflicts based on the process rule subsets, and encapsulate the process rules corresponding to the primitives in the same processing layer group into a process rule set.

[0069] Exemplarily, query the process rule library through the material type identifier, match the corresponding rules (power ≥ 1800W, speed ≤ 100mm / s, gas = N 2 ), use the rule engine to parse the geometric attributes of the primitive (thickness 2mm, contour length 150mm) and the rule constraint conditions. When it is detected that there is a conflict between the speed setting of 120mm / s and the power of 1800W (inability to cut through due to insufficient heat input), trigger the relaxation algorithm, automatically increase the power to 2200W to give priority to ensuring the cutting quality, dynamically bind the resolved parameters to all #304-identified primitives in the layer group, classify and integrate them into process rule subsets by material type (stainless steel / aluminum alloy) and processing type (cutting / engraving), and generate a process rule set including a parameter template (power = 2310W, speed = 110mm / s), material identifier, and version number V3.2 in combination with the real-time state of the equipment (laser temperature 40°C triggers a power compensation of +5%).

[0070] Since the material processing type corresponding to the layer is identified through the material type identifier of each layer, and the process rules of the material corresponding to the layer are parsed, it is possible to quickly select the processing method applicable to the material and make corresponding adjustments, improving the efficiency of dynamic layer processing.

[0071] Based on any of the above embodiments, in the fifth embodiment of the present application, referring to Figure 3 , Figure 3 is a schematic flowchart of the fifth embodiment of the dynamic layer processing method based on color grouping of the present application. The step S30 includes steps D11 to D13: Step D11, based on the process rule set, optimize the path efficiency through a decision algorithm to generate a processing path instruction set.

[0072] In this embodiment, the decision algorithm refers to an optimization method based on heuristic rules or machine learning models. Path efficiency refers to the minimization goal of processing time / energy consumption achieved by reducing non-cutting travel and optimizing the processing sequence. The processing path instruction set refers to the instruction sequence that can be executed by the device.

[0073] As an alternative implementation, extract the device operation parameters corresponding to the material type identifier from the process rule set, load the processing path topology graph constructed based on the primitive geometric data, and based on the processing path topology graph, combine the device operation parameters to evaluate the processing time and energy consumption of different path combinations through a search algorithm, and adopt optimizing path continuity and avoiding kinematic constraints, and combine a dynamic priority queue to adjust the processing order of the emergency layer, and adjust the multi-objective conflict, and finally generate a processing path instruction set including process parameter dynamic compensation items and exception handling logic.

[0074] Step D12, according to the processing path instruction set, combine the device operation parameters associated with the processing path instruction set to perform compensation calculation to obtain compensation parameters.

[0075] In this embodiment, the device operation parameters refer to the processing status data collected in real time. Compensation calculation refers to the mathematical modeling of dynamically correcting processing parameters based on the deviation between the device status and the theoretical value.

[0076] As an alternative implementation, based on the processing path instruction set, and combined with the device operation parameters, through a linear regression model, use the processing path data set to regulate the device operation parameters, perform a cutting operation, and compare and calculate with the expected cutting path to obtain the compensation amount. Based on the compensation amount, combine the theoretical parameters in the processing path instruction set to generate a compensated instruction, and add a check code to ensure data integrity, and generate compensation parameters including the compensation amount, the compensated instruction, and the check code.

[0077] Step D13, add the compensation parameters into the corresponding processing path instruction set to generate the target processing instruction set.

[0078] In this embodiment, the target processing instruction set is the final executable instruction file generated after integrating compensation parameters.

[0079] As an alternative implementation, the check code in the compensation parameters is parsed. Based on the check code, the compensation parameters are added to the processing path instruction set corresponding to the check code, and based on the timestamp, the compensation parameters are aligned with the processing path instruction set to obtain the target processing instruction set.

[0080] Exemplarily, the cutting parameters of stainless steel (#304) (power ≥ 2000W, speed ≤ 100mm / s) are loaded from the process rule set. Based on the ant colony algorithm, the processing order of the primitive elements is optimized, and the paths of 25 scattered circular primitive elements are reconstructed into a spiral continuous processing trajectory, with the idle stroke reduced by 58%. An initial G-code instruction set (G02 circular interpolation instruction, F10000 speed, S2000 power) is generated. The temperature of the device laser (45°C) and the acceleration of the galvanometer X-axis (1.5g) data are collected in real time. The spot offset (+0.02mm) is predicted through Kalman filtering, and the dynamic compensation parameters (power +5% to 2100W, speed -4% to 9600mm / min, focus compensation +0.02mm) are calculated. The compensation values are embedded in the G-code (G01 X500 Y300 F9600 S2100), and a synchronous clock timestamp (T = 1625097123.456789) and a CRC32 check code (0x8A6B1F) are added, and finally a target processing instruction set with version number V3.5 is generated.

[0081] Since the generation of compensation parameters is combined with the processing equipment and the corresponding processing instruction set is compensated, the processing quality can be guaranteed during the processing, and the reliability of dynamic layer processing is improved.

[0082] Based on any of the above embodiments, in the sixth embodiment of the present application, step S40 includes steps E11 to E12: Step E11, based on each of the layers in the processing layer group and the target processing instruction set corresponding to the processing layer group, perform an association verification to determine the association relationship between each of the layers and the target processing instruction set.

[0083] In this embodiment, the association verification refers to confirming the correspondence between the layer and the instruction through hash value matching, coordinate space registration, or parameter logic verification.

[0084] As an alternative implementation, extract the unique identifier, geometric bounding box, and process parameters of each layer from the processing layer group, parse the coordinate range in the code from the target processing instruction set, perform spatial registration verification based on the processing layer group and the target processing instruction set, match the layer parameters and instruction parameters using a rule algorithm, establish an initial association relationship between the layers in the processing layer group and the target processing instruction set corresponding to the processing layer group, review the initial association relationship, and determine the association relationship between the layers and the target processing instruction set.

[0085] Step E12, based on the processing layer group, the target processing instruction set corresponding to the processing layer group, and the association relationship between each layer and the target processing instruction set, package and convert them into the processing file.

[0086] In this embodiment, packaging and conversion means serializing the layer metadata, instruction set, and association table into a structured file that can be recognized by the device.

[0087] As an alternative implementation, based on the association relationship between the processing layer group and the target processing instruction set corresponding to the processing layer group and the association relationship between each layer and the target processing instruction set, form a mapping relationship table, and perform conversion based on the mapping relationship table, the processing layer group, and the target processing instruction set, and package them into a processing file that conforms to the device standard.

[0088] Exemplarily, calculate the feature identifier of each layer in the processing layer group through a hash algorithm, extract the G-code coordinate range and process parameters of the target processing instruction set, align the layer coordinate system and the instruction physical coordinate system using an affine transformation matrix, verify whether the elliptical primitive of Layer2 matches the G02 circular interpolation instruction, detect a parameter conflict in Layer3 (the speed setting of 110 mm / s exceeds the stainless steel rule threshold of 100 mm / s) and trigger an exception annotation (error code E102), generate a layer-instruction association table (Layer1 → G-code lines 10 - 25, Layer2 → lines 26 - 40) and attach a timing synchronization tag (Layer2 processing needs to be executed after Layer1 is completed), serialize the layer group data, instruction set, association table, and version stamp V2.3 into a JSON file, embed a digital signature and a check code (0x5A6B3F), and encapsulate it into a binary processing file with a block index according to the protocol.

[0089] Since the association and packaging of each processing layer group and the corresponding instruction set are converted into a processing file, the relevance between the instruction set and the processing layer is ensured, and the device can recognize and run, improving the reliability and efficiency of dynamic layer processing.

[0090] Based on any of the above embodiments, in the seventh embodiment of the present application, refer to Figure 4 , Figure 4This is a schematic flowchart of the seventh embodiment of the dynamic layer processing method based on color grouping in the present application. After step S40, steps F11 to F13 are further included: Step F11: Transmit the processing file to the processing device.

[0091] In this embodiment, the processing device refers to a device that processes products based on a processing layer group and an associated target processing instruction set.

[0092] As an alternative implementation, connect to the device control terminal through an encrypted channel, transmit the processing file in block order, and after each group is received, the device side returns an acknowledgment signal. If no feedback is received after the timeout, an exception retry is triggered. After all blocks are transmitted, the device side verifies the integrity of the overall file and generates a receipt message. If the verification fails, resume transmission from the breakpoint to complete the process of transmitting the processing file to the processing device.

[0093] Step F12: Optimize the parameter matching between the target processing instruction set and the laser, and allocate the target processing instruction set according to the matching degree to obtain the control parameters corresponding to the laser.

[0094] In this embodiment, laser parameter matching optimization refers to analyzing and optimizing according to the compatibility between device capabilities and instruction requirements. The matching degree refers to a numerical index that quantifies the degree of fit between device capabilities and instruction requirements. Allocation refers to dividing instructions to the optimal laser through a load balancing algorithm.

[0095] As an alternative implementation, extract process parameters and geometric path data from the target processing instruction set, load the laser capability model according to the process parameters and geometric path data, calculate the matching degree between the process parameters, geometric path data and the laser capability model, evaluate the adaptability of the target processing instruction set to the laser device to obtain an adaptation result, based on the adaptation result, use a multi-objective optimization algorithm to select the laser with the best adaptation result in the laser cluster, and perform a relaxation algorithm on the conflict items between the laser with the best adaptation result and the target processing instruction set to obtain adjusted instruction parameters. Based on the target processing instruction set and the adjusted instruction parameters, generate the control parameters corresponding to the laser device.

[0096] Step F13: Based on each control parameter, control the cutting heads corresponding to each laser to perform a collaborative processing operation to obtain the processed product.

[0097] In this embodiment, the collaborative processing operation refers to a parallel processing mode of multiple lasers based on time sequence synchronization and path planning.

[0098] As an alternative implementation, based on the control parameters corresponding to each laser, synchronize the control parameters of multiple lasers with the kinematic axis clock, load the three-dimensional machining path, and use the kinematic chain algorithm to solve the linkage trajectory. According to the linkage trajectory, perform a collision detection model to predict the interference risk of the cutting head, and dynamically update the linkage trajectory. After starting the machining, the visual sensor is used to collect the cutting seam width in real time. When the detected deviation is greater than the preset threshold, trigger the closed-loop control, adjust the control parameters of each laser to obtain the updated control parameters, and complete the machining operation based on the updated linkage trajectory and the updated control parameters corresponding to each laser to obtain the processed product.

[0099] Exemplarily, the machining file (including G-code instruction set, layer hash mapping table, and CRC32 checksum 0x5A6B3F) is encrypted and transmitted to the laser cluster control terminal. After successful handshake, the corresponding instruction set is loaded in blocks according to the machining layer components. Based on the laser capabilities (model A maximum power 2000W / model B pulse frequency 50kHz), an algorithm is used to match the instruction requirements (power 2100W → trigger dynamic power derating to 1900W and associate with model B), generate device-specific control parameters (power = 1900W, frequency = 45kHz, focus compensation +0.03mm), start multi-machine collaborative machining through the clock synchronization protocol, and the five-axis linkage interpolation algorithm drives the cutting head to machine the stainless steel workpiece along a spiral path, and the cutting seam width (0.12mm ± 0.015mm) is monitored in real time. After machining, a quality inspection report and the processed product are generated.

[0100] Since cutting is achieved by controlling different types of lasers, a collaborative control strategy for different lasers is realized, the problems of power matching and switching timing control are solved, and the efficiency of dynamic layer machining is improved.

[0101] Based on any of the above embodiments, in the eighth embodiment of the present application, after step F14, steps G11 to G12 are further included: Step G11, display each processed / to-be-processed layer group in different transparency levels on the visualization interface, and render the machining process topology diagram of each to-be-processed layer on the visualization interface.

[0102] In this embodiment, the processed / to-be-processed layer group refers to a set of layers classified according to color characteristics or process attributes and marked with machining states. The transparency level refers to a visualization parameter that distinguishes the display priority of layers through opacity values. The machining process topology diagram refers to a directed graph structure that shows the machining sequence and dependency relationship between layers.

[0103] As an alternative implementation, load the geometric data and process parameters of the processed layer group and the layer group to be processed from the database, construct a 3D scene on the computer side based on the geometric data and process parameters of the processed layer group and the layer group to be processed, render the layer contours according to the preset hierarchical transparency rules for the 3D scene, display each processed / to-be-processed layer group at different transparency levels in the visualization interface, and draw and render the processing progress topology diagram in the visualization interface based on the completion status of the processing progress.

[0104] Step G12: In response to the user's click operation on a specific layer in the visualization interface, dynamically display the control parameters, processing progress, and quality inspection indicators of the device associated with the layer.

[0105] In this embodiment, the click operation refers to an event triggered by the user through a mouse / touch screen. The specific layer refers to the selected layer with a unique identifier. The quality inspection indicator refers to the measured value quantifying the processing quality.

[0106] As an alternative implementation, listen for the user's click operation to obtain the target layer ID, highlight the selected layer contour in the visualization interface scene based on the layer corresponding to the click operation, and pop up a modal panel to dynamically load the parameter table, processing progress, and quality inspection indicators.

[0107] As an alternative implementation, the mobile terminal controls the processing device through the Internet. The user can perform the processing of dynamic layers by logging in to an account. After logging in, access the database to obtain the color characteristics and material type identifiers of the to-be-processed primitive elements, perform clustering analysis based on the color characteristics to generate the initial processed layer group, dynamically update the layer processing priority queue based on the user's drag-and-drop sorting instructions, lock state switching instructions, and visualization display parameters for the layer group, analyze the material physical properties, process constraint conditions, and device load parameters of the elements within each layer group, generate the initial processing path based on the decision model, monitor the stability of the laser power output and the movement trajectory of the cutting head in real time, perform collision interference checking and thermal deformation compensation calculation on the initial processing path sequence, generate the target processing instruction set, associate the target processing instruction set with the corresponding processed layer group, package and convert it into the processing file, send the processing file to the processing device management terminal through the Internet, and the processing device management terminal synchronously controls at least two different types of lasers and the corresponding cutting heads to perform cooperative processing operations according to the optimized processing instruction set.

[0108] Exemplarily, in the visualization interface, the processed layer group (transparency = 0.2) and the layer group to be processed (transparency = 0.7) are loaded. The geometric contours of the stainless-steel cutting layer (red) and the aluminum alloy engraving layer (blue) are rendered through the visualization interface. A processing sequence dependency graph is generated based on the topological sorting algorithm, and the status of the topological graph nodes is updated in real time by receiving device-side data (for example, when the progress of Layer3 reaches 45%, the filling color gradually changes to orange). After the user clicks on the Layer3 node, the front end queries the real-time parameters of the bound laser #L505 (power = 1900W, frequency = 45kHz, focus Z = +0.03mm), extracts the timing data of the processing progress of this layer (current progress 45%, remaining duration 12 minutes) and the quality inspection indicators (dimension error = 0.03mm, roughness Ra = 0.9μm), and dynamically renders a line chart (showing an error fluctuation of 0.02 - 0.05mm) and a heat map (highlighting the corner out-of-tolerance area) in the modal panel. The operation log records the user ID = admin, the viewing time = 2025-03-31 15:22, and the parameter hash value. The final pass rate is increased to 98.5%, and the processing time is optimized from 50 minutes to 38 minutes.

[0109] Due to the settings in the visualization interface, users can timely understand the processing progress through the visualization interface and adjust the processing parameters, observe various processing processes better and more intuitively, and improve the reliability of dynamic layer processing.

[0110] This application provides a dynamic layer processing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the dynamic layer processing method based on color grouping in the first embodiment above.

[0111] Refer to the following Figure 5 , which shows a schematic structural diagram of a dynamic layer processing device suitable for implementing the embodiments of this application. The dynamic layer processing device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, fiber optic cutters, personal digital assistants (PDAs), tablet computers (PADs), portable multimedia players (PMPs), laser cutters, etc., and fixed terminals such as laser cutting control terminals, desktop computers, etc. Figure 5 The shown dynamic layer processing device is only an example and should not impose any limitation on the functions and usage scope of the embodiments of this application.

[0112] As Figure 5 shown, the dynamic layer processing device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. In the random access memory 1004, various programs and data required for the operation of the dynamic layer processing device are also stored. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the dynamic layer processing device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a dynamic layer processing device having various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0113] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the read-only memory 1002. When the computer program is executed by the processing device 1001, the above functions defined in the methods of the embodiments disclosed in the present application are executed.

[0114] The dynamic layer processing device provided by this application adopts the dynamic layer processing method based on color grouping in the above-mentioned embodiment, which can solve the technical problem that operators need to group layers, adjust parameters, and configure process rules for processing elements based on experience, resulting in low efficiency of dynamic layer processing. Compared with the prior art, the beneficial effects of the dynamic layer processing device provided by this application are the same as those of the dynamic layer processing method based on color grouping provided by the above-mentioned embodiment, and other technical features in this dynamic layer processing device are the same as those disclosed in the method of the previous embodiment, which will not be elaborated here.

[0115] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0116] As mentioned above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0117] This application provides a computer-readable storage medium with computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the dynamic layer processing method based on color grouping in the above-mentioned embodiment.

[0118] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination of the above.

[0119] The above computer-readable storage medium can be included in a dynamic layer processing device; or it can exist separately and not be assembled into the dynamic layer processing device.

[0120] The above computer-readable storage medium carries one or more programs. When the one or more programs are executed by a dynamic layer processing device, the dynamic layer processing device is caused to: perform clustering analysis on the layers of the to-be-processed primitive based on the color characteristics of the to-be-processed primitive to obtain at least one processed layer group; parse the process rules of the layers in the processed layer group according to the material type identifiers associated with the layers in the processed layer group to generate a process rule set corresponding to the processed layer group; perform compensation calculation in combination with the device operation parameters based on the process rule set corresponding to the processed layer group to generate a target processing instruction set for the processed layer group; associate the layers in the processed layer group in combination with the target processing instruction set corresponding to the processed layer group and package them to generate a processing file.

[0121] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0123] The modules described in the embodiments of this application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation to the unit itself in some cases.

[0124] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned dynamic layer processing method based on color grouping, which can solve the technical problem that operators need to group layers, adjust parameters, and configure process rules for processing elements based on experience, resulting in low efficiency of dynamic layer processing. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the dynamic layer processing method based on color grouping provided in the above embodiments, and will not be elaborated here.

[0125] The above are only partial embodiments of this application, and do not limit the patent scope of this application. Any equivalent structural transformation made by using the content of the specification and drawings of this application under the technical concept of this application, or any direct / indirect application in other related technical fields, is included in the patent protection scope of this application.

Claims

1. A dynamic layer processing method based on color grouping, characterized in that: The method comprises: Performing cluster analysis on the layers of the graphics element to be processed based on the color characteristics of the graphics element to be processed, to obtain at least one processing layer group; parsing the process rules of the layers in the processing layer group according to the material type identifier associated with the layers in the processing layer group, and generating a process rule set corresponding to the processing layer group; Based on the process rule set corresponding to the processing layer group, compensation calculation is performed in combination with equipment operation parameters to generate a target processing instruction set for the processing layer group; Based on the layers in the processing layer group, the target processing instruction set corresponding to the processing layer group is associated and packaged to generate a processing file.

2. The color grouping-based dynamic layer processing method according to claim 1, characterized in that: The step of performing cluster analysis on the layers of the to-be-processed graphics primitives based on the color features of the to-be-processed graphics primitives to obtain at least one processing layer group comprises: Distinguishing the layers having different color characteristics according to the color characteristics; Based on the layers, the layers having the same color feature are aggregated through cluster analysis to generate an initial processing layer group; Based on the initial processing layer group and in combination with the adjustment instruction, the processing layer group is generated.

3. The color grouping-based dynamic layer processing method according to claim 2, characterized in that: The step of generating the processing layer group based on the initial processing layer group and in combination with the adjustment instruction includes: Based on the adjustment instruction, analyzing the processing order change of each layer, and generating adjustment parameters; According to the adjustment parameters, the processing order of each layer in the initial processing layer group is updated to generate the processing layer group.

4. The color grouping-based dynamic layer processing method according to claim 1, characterized in that: The step of parsing the process rules of the layers in the processing layer group according to the material type identifier associated with the layers in the processing layer group and generating a process rule set corresponding to the processing layer group includes: Based on the material type identifier, a process rule corresponding to the material type identifier is parsed, and the process rule is associated with the to-be-processed graphic element corresponding to the material type identifier to obtain the process rule of the to-be-processed graphic element; The process rules of the to-be-processed graphics elements in the processing layer group are classified and integrated to generate the process rule set.

5. The method for processing a dynamic layer based on color grouping according to claim 1, characterized in that: The step of performing compensation calculation based on the process rule set corresponding to the processing layer group and combining the equipment operation parameters to generate the target processing instruction set of the processing layer group includes: Based on the process rule set, the path efficiency is optimized by a decision algorithm to generate a processing path instruction set; According to the machining path instruction set, combined with the equipment operation parameters associated with the machining path instruction set, compensation calculation is performed to obtain compensation parameters; The compensation parameters are added into the corresponding machining path instruction set to generate the target machining instruction set.

6. The method for processing a dynamic layer based on color grouping according to claim 1, characterized in that: The step of associating the layers in the processing layer group with the target processing instruction set corresponding to the processing layer group and packaging to generate a processing file comprises: Performing association verification based on each of the layers in the processing layer group and the target processing instruction set corresponding to the processing layer group to determine the association relationship between each of the layers and the target processing instruction set; Based on the processing layer group, the target processing instruction set corresponding to the processing layer group, and the association relationship between each of the layers and the target processing instruction set, the processing files are packaged and converted into the processing files.

7. The method for processing a dynamic layer based on color grouping according to claim 1, characterized in that: After the step of associating the target processing instruction set corresponding to the processing layer group based on the layer in the processing layer group and packaging and generating a processing file, the method further includes: transmitting the processing file to the processing equipment; By optimizing the matching between the target processing instruction set and the parameters of the laser, the target processing instruction set is allocated according to the matching degree to obtain the control parameters corresponding to the laser; Based on the control parameters, the cutting heads corresponding to the lasers are controlled to perform collaborative processing operations to obtain the processed products.

8. The color grouping-based dynamic layer processing method according to claim 7, characterized in that: After the step of controlling the cutting heads corresponding to the lasers to perform the collaborative processing operation based on the control parameters to obtain the processed product, the method further includes: Displaying each processed / to-be-processed layer group in a visualization interface with different transparency levels, and rendering a processing process topology diagram of each to-be-processed layer in the visualization interface; In response to a user clicking operation on a specific layer in the visualization interface, control parameters, processing progress and quality inspection indicators of the equipment associated with the layer are dynamically displayed.

9. A dynamic layer processing device, characterized in that: The dynamic layer processing device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the color grouping-based dynamic layer processing method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the dynamic layer processing method based on color grouping as described in any one of claims 1 to 8 are implemented.

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