Data processing method and device based on laser processing equipment, equipment and medium

Abstract

Embodiments of the present application disclose a data processing method and device based on a laser processing equipment, an equipment and a medium. The method comprises: generating a processing parameter group corresponding to a material to be processed, and performing laser processing on a local area of a to-be-processed region of the material to be processed based on the processing parameter group to obtain a micro processing effect diagram; and then based on the micro processing effect diagram and a processing strategy corresponding to the to-be-processed region, predicting a macro effect of the to-be-processed region to obtain a macro processing effect diagram, wherein the macro processing effect diagram is used to provide a preview of the processing effect of the material to be processed. The technical solution of the present application improves the simplicity of laser processing effect prediction, has high reliability of laser processing, and greatly increases the stickiness between the laser processing equipment and the user.

Description

Technical Field

[0001] This application relates to the field of laser processing technology, specifically to a data processing method based on laser processing equipment, a data processing device based on laser processing equipment, an electronic device, and a computer-readable medium. Background Technology

[0002] As laser processing equipment evolves from industrial applications to end-user applications, it will no longer be limited to industrial use. Laser processing equipment has gradually become intelligent hardware that users can use at the end, enabling them to perform laser processing on materials.

[0003] Currently, to achieve better processing of materials, the laser processing effect is usually predicted. Related technologies employ big data prediction and physical model-based effect prediction methods, among which:

[0004] Big data prediction refers to the prediction of laser processing effects using collected hardware information, material information, and parameter variable combination information. It focuses on mining from the data. In practical applications, big data prediction relies on a large amount of accurate data, which is difficult and hard to implement.

[0005] Physical model-based effect prediction refers to using the principles of applied physics to describe the interaction between lasers and materials. By analyzing these processes, key factors and mechanisms in laser processing can be understood, thereby enabling the prediction of processing results. It focuses on a deep understanding of the physical principles in laser processing. In practical applications, physical model-based effect prediction relies on experts with specialized knowledge, is highly complex, requires a large amount of computing resources and accurate data, and is difficult to implement.

[0006] Therefore, improving the ease of predicting laser processing effects to ensure the reliability of laser processing is an urgent problem to be solved. Summary of the Invention

[0007] To address the aforementioned technical problems, embodiments of this application provide a data processing method, apparatus, electronic device, computer-readable storage medium, and computer program product based on laser processing equipment. Embodiments of this application improve the ease of predicting laser processing effects and ensure the reliability of laser processing.

[0008] One aspect of this application provides a data processing method based on a laser processing device. The method includes: generating a processing parameter set corresponding to a material to be processed; performing laser processing on a local area of ​​the material to be processed based on the processing parameter set to obtain a microscopic processing effect image; and predicting the macroscopic effect of the material to be processed based on the microscopic processing effect image and the processing strategy corresponding to the area to be processed to obtain a macroscopic processing effect image; wherein the macroscopic processing effect image is used to provide a preview of the processing effect on the material to be processed.

[0009] In another aspect of this application, a data processing apparatus based on a laser processing device is provided. The apparatus includes: a generation module configured to generate a set of processing parameters corresponding to a material to be processed; a processing module configured to perform laser processing on a local area of ​​the material to be processed based on the set of processing parameters to obtain a microscopic processing effect image; and a prediction module configured to predict the macroscopic effect of the area to be processed based on the microscopic processing effect image and the processing strategy corresponding to the area to be processed to obtain a macroscopic processing effect image; wherein the macroscopic processing effect image is used to provide a preview of the processing effect on the material to be processed.

[0010] In another aspect of this application, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device enables the data processing method based on laser processing equipment as described above.

[0011] In another aspect of this application, a computer-readable storage medium is provided, on which computer-readable instructions are stored, which, when executed by a computer's processor, cause the computer to perform the data processing method based on a laser processing device as described above.

[0012] In another aspect of the embodiments of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the data processing method based on laser processing equipment as described above.

[0013] In the technical solution provided in the embodiments of this application, a portion of the area to be processed in the material to be processed is first laser-processed using a set of processing parameters to obtain a microscopic processing effect image. Then, the macroscopic processing effect image and the processing strategy for the area to be processed are used to predict the macroscopic effect of the area to be processed, thus providing a preview of the processing effect on the material to be processed. This method of predicting the macroscopic processing effect image from the microscopic processing effect image, compared to prediction methods in related technologies, does not require the collection of large amounts of accurate data, and is less complex and easier to implement. Therefore, it greatly improves the simplicity of laser processing effect prediction, enhances the reliability of laser processing, and increases the stickiness between laser processing equipment and users. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of an exemplary implementation environment of this application;

[0015] Figure 2 This is a flowchart illustrating a data processing method based on laser processing equipment, as shown in an exemplary embodiment of this application;

[0016] Figures 3a to 3c This is a schematic diagram illustrating an exemplary micro-processing effect;

[0017] Figure 4 This is an example of a schematic diagram illustrating the origin of a macroscopic processing effect diagram;

[0018] Figures 5a to 5b This is a schematic diagram of an exemplary display interface;

[0019] Figure 6 This is an example of a schematic diagram illustrating the origin of a macroscopic processing effect diagram;

[0020] Figure 7 Is Figure 2 A flowchart of a data processing method based on laser processing equipment is further proposed, building upon the example embodiments;

[0021] Figures 8a to 8b This is a schematic diagram of an exemplary display interface;

[0022] Figure 9 Is Figure 7 A flowchart of a data processing method based on laser processing equipment is further proposed, building upon the example embodiments;

[0023] Figure 10 This is a block diagram illustrating a data processing apparatus based on laser processing equipment, as shown in an exemplary embodiment of this application;

[0024] Figure 11 This is a schematic diagram of the structure of a computer system suitable for implementing the electronic devices of the present application embodiments. Detailed Implementation

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0026] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0028] In this application, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0029] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0030] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0031] First refer to Figure 1 , Figure 1 This is a schematic diagram of an exemplary implementation environment of this application. With the development of laser processing equipment from industrial applications to end-user applications, laser processing equipment is becoming increasingly intelligent and convenient. Users can easily use the laser processing equipment to perform laser processing on the materials to be processed by operating the host computer software installed on the terminal equipment. For example... Figure 1 As shown, the terminal device 101 is equipped with the host computer software of the laser processing equipment 102. The host computer software provides a device control interface. Users can control the laser processing equipment to perform laser processing on the material to be processed by performing relevant trigger operations on the device control interface.

[0032] Before operating laser processing equipment to perform laser processing on the material to be processed, it is usually necessary to predict the laser processing effect on the material. Related technologies employ big data prediction methods and physical model-based effect prediction methods, among which:

[0033] Big data prediction refers to the prediction of laser processing effects using collected hardware information, material information, and parameter variable combination information. It focuses on mining from the data. In practical applications, big data prediction relies on a large amount of accurate data, which is difficult and hard to implement.

[0034] Physical model-based effect prediction refers to using the principles of applied physics to describe the interaction between lasers and materials. By analyzing these processes, key factors and mechanisms in laser processing can be understood, thereby enabling the prediction of processing results. It focuses on a deep understanding of the physical principles in laser processing. In practical applications, physical model-based effect prediction relies on experts with specialized knowledge, is highly complex, requires a large amount of computing resources and accurate data, and is difficult to implement.

[0035] Therefore, in order to improve the ease of predicting laser processing effects and ensure the reliability of laser processing, this application provides a data processing scheme based on laser processing equipment.

[0036] In one embodiment of this application, the data processing method based on the laser processing equipment can be executed by the laser processing equipment 102. Specifically, the laser processing equipment 102 generates a set of processing parameters corresponding to the material to be processed; then, based on the set of processing parameters, laser processing is performed on the local area of ​​the material to be processed to obtain a microscopic processing effect image; then, based on the microscopic processing effect image and the processing strategy corresponding to the area to be processed, the macroscopic effect of the area to be processed is predicted to obtain a macroscopic processing effect image, wherein the macroscopic processing effect image is used to provide a preview of the processing effect on the material to be processed.

[0037] In one embodiment of this application, the data processing method based on the laser processing equipment can also be interactively executed by the laser processing equipment 102 and the terminal device 101. Specifically: the laser processing equipment 102 generates a set of processing parameters corresponding to the material to be processed; then, based on the processing parameter set, it performs laser processing on a local area of ​​the material to be processed to obtain a microscopic processing effect image; then, based on the microscopic processing effect image and the processing strategy corresponding to the area to be processed, it predicts the macroscopic effect of the area to be processed to obtain a macroscopic processing effect image, wherein the macroscopic processing effect image is used to provide a preview of the processing effect on the material to be processed; then, multiple macroscopic processing effects are sent to the terminal device 101. Accordingly, the terminal device 101 receives multiple macroscopic processing effects sent by the laser processing equipment 102 and displays multiple macroscopic processing effects, etc.

[0038] The method of predicting macroscopic processing effect diagrams through microscopic processing effect diagrams in this embodiment of the application, compared with the prediction methods in related technologies, does not require the collection of a large amount of accurate data, and is less complex and easier to implement. Therefore, it greatly improves the simplicity of laser processing effect prediction, enhances the reliability of laser processing, and increases the stickiness between laser processing equipment and users.

[0039] It should be noted that the aforementioned terminal devices 101 include, but are not limited to, smartphones, computers (tablets, laptops, desktop computers, etc.), smart home devices (televisions, refrigerators, air conditioners, washing machines, robot vacuums, etc.), and smart wearable devices (wristbands, watches, etc.); the laser processing equipment 102 includes, but is not limited to, laser engraving machines, laser cutting machines, and laser printers. Furthermore, the number of terminal devices 101 and laser processing equipment 102 is merely illustrative; any number of terminal devices 101 and laser processing equipment 102 can be used as needed.

[0040] It is understood that in the specific implementation of this application, user-related data is involved. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0041] The following details the various implementation details of the technical solutions in the embodiments of this application:

[0042] Please see Figure 2 , Figure 2 This is a flowchart illustrating a data processing method based on a laser processing device, as shown in one embodiment of this application. This data processing method can be executed by the laser processing device 102. Figure 2 As shown, this data processing method based on laser processing equipment includes at least S201 to S203, which are described in detail below:

[0043] S201, Generate the processing parameter set corresponding to the material to be processed.

[0044] In the embodiments of this application, the materials to be processed include, but are not limited to, at least one of the following: metallic materials (e.g., steel, aluminum alloy, copper alloy, etc.), non-metallic materials (e.g., plastic, wood, glass, ceramic, etc.), composite materials (e.g., carbon fiber composite materials, glass fiber composite materials, etc.), and other materials (e.g., leather, rubber, paper, and cellulose-based materials, etc.). In practical applications, the materials to be processed can be flexibly adjusted according to the specific application scenario.

[0045] For example, the material to be processed can be the material itself that needs to be laser-processed into the target product / ideal product (e.g., 1 meter * 1 meter of wood). In the actual laser processing of the product, a portion of the wood is first laser-processed to obtain a microscopic processing effect image. Based on the microscopic processing effect image, a macroscopic processing effect image is obtained. Then, the final processing parameters and / or processing strategy are determined, thereby continuing the subsequent laser processing process.

[0046] For example, the material to be processed can be the same type of material as the material to be laser-processed into the target / ideal product (e.g., 1 meter * 1 meter of wood). However, this same type of material is used in the testing phase to test and obtain the final processing parameters and / or processing strategy. Then, in the actual laser processing of the product, the material itself to be laser-processed into the target / ideal product is laser-processed based on the processing parameters and / or processing strategy determined in the testing phase.

[0047] In this embodiment, the processing parameter group refers to a combination of multiple (two or more, the same below) processing parameters. Processing parameters are the operating parameters of the laser processing equipment used to laser process the material to be processed, and they are usually related to the specific type of laser processing equipment. These processing parameters include, but are not limited to, at least one of the following: laser power, scan speed, laser beam diameter, pulse frequency, beam mode, gas type and flow, and focal length. In practical applications, processing parameters can be flexibly adjusted according to specific application scenarios.

[0048] In one embodiment of this application, the process of generating the processing parameter set corresponding to the material to be processed in S201 may include:

[0049] Determine multiple processing parameters for laser processing of the material to be processed;

[0050] Multiple candidate parameter groups are generated based on multiple processing parameters, and each candidate parameter group has multiple processing parameters.

[0051] For each candidate parameter group, the processing parameters contained in the candidate parameter group are assigned values ​​to obtain the processing parameter group corresponding to the candidate parameter group; among them, at least one processing parameter in different processing parameter groups has a different assigned value.

[0052] That is, in the optional embodiment, there are multiple processing parameter groups. The process of generating multiple processing parameter groups is to first determine multiple processing parameters for laser processing of the material to be processed, and then use the multiple processing parameters to generate multiple candidate parameter groups. Each candidate parameter group has multiple processing parameters. Then, the processing parameters contained in each candidate parameter group are assigned values ​​to obtain the processing parameter group corresponding to each candidate parameter group.

[0053] In one optional embodiment, the difference between the candidate parameter group and the processing parameter group is that the processing parameters in the candidate parameter group are unassigned, while the processing parameters in the processing parameter group are assigned values. That is, the processing parameters in the candidate parameter group are referred to as the processing parameter group after being assigned values. Optionally, when assigning values ​​to the processing parameters in the candidate parameter group, the same processing parameter can be assigned values ​​according to a preset gradient algorithm, thereby achieving regular assignment.

[0054] For example, suppose the parameters used for laser processing of the material "wood" are A, B, C, D, and E, and three candidate parameter sets are generated. Specifically, candidate parameter set Cps1 = {A, B, C, D, E}, candidate parameter set Cps2 = {A, B, C, D, E}, and candidate parameter set Cps3 = {A, B, C, D, E}. Then, candidate parameter sets Cps1, Cps2, and Cps3 are processed respectively. By performing the assignment operation, we can obtain the machining parameter set Pps1 = {A:a1, B:b1, C:c1, D:d1, E:e1} corresponding to the candidate parameter set Cps1, the machining parameter set Pps2 = {A:a2, B:b2, C:c2, D:d2, E:e2} corresponding to the candidate parameter set Cps2, and the machining parameter set Pps3 = {A:a3, B:b3, C:c3, D:d3, E:e3} corresponding to the candidate parameter set Cps3.

[0055] Optionally, in the above examples, different processing parameter groups may assign different values ​​to the same processing parameter, for example, a1≠a2≠a3; alternatively, in the above examples, different processing parameter groups may assign the same value to the same processing parameter, for example, a1=a2=a3, but it must be ensured that at least one processing parameter in different processing parameter groups has a different value.

[0056] For example, the generation process of the processing parameter set can involve human intervention, such as the user selecting processing parameters and / or assigning values ​​to the processing parameters; for example, the generation process of the processing parameter set can also be done without human intervention, that is, the laser processing equipment automatically selects and assigns values ​​to the processing parameters, which can be achieved by training a model. In practical applications, the degree of automation of the generation process of the processing parameter set can be flexibly adjusted according to the specific application scenario.

[0057] By implementing this optional embodiment, the processing parameter set corresponding to the material to be processed can be generated easily and accurately, providing strong support for obtaining microscopic processing effect images of subsequent local laser processing.

[0058] S202, based on the processing parameter set, performs laser processing on the local area of ​​the material to be processed, and obtains a micro-processing effect image.

[0059] In this embodiment, a processing parameter set is generated. Then, the processing parameter set can be used to perform laser processing on the local area of ​​the material to be processed, thereby obtaining a microscopic processing effect image.

[0060] In this embodiment, the "processing area" refers to the area where the material to be processed needs to become the target / ideal product, i.e., all areas requiring laser processing. Conversely, the "local area" refers to the portion of the material requiring laser processing. Correspondingly, the "microscopic processing effect diagram" refers to the effect diagram corresponding to the portion of the laser-processed area. By observing the microscopic processing effect diagram, the laser processing effect / condition of that portion of the area can be clearly understood, thereby predicting the macroscopic processing effect. Please refer to [link to relevant documentation]. Figure 3a , Figure 3b and Figure 3c The images show three exemplary micro-processing effects.

[0061] In one embodiment of this application, the process in S202, which involves performing laser processing on a localized area of ​​the material to be processed based on a set of processing parameters to obtain a microscopic processing effect image, may include:

[0062] Laser processing equipment is controlled based on a set of processing parameters. Laser processing is performed on localized areas of the material to be processed, and microscopic processing effect images corresponding to the set of processing parameters are collected during or after the laser processing process.

[0063] In one optional embodiment, the laser processing equipment is controlled to operate in the working state corresponding to the processing parameter set. The laser processing equipment then performs laser processing on a localized area of ​​the material to be processed, and simultaneously acquires a microscopic processing effect image corresponding to the processing parameter set in real time during the laser processing. By acquiring the microscopic processing effect image corresponding to the processing parameter set during the laser processing, the acquisition efficiency of the microscopic processing effect image can be improved quickly.

[0064] In one optional embodiment, the laser processing equipment is controlled to operate in the working state corresponding to the processing parameter set. The laser processing equipment then performs targeted laser processing on a localized area of ​​the material to be processed, and a microscopic processing effect image corresponding to the processing parameter set is acquired after the laser processing process. By acquiring the microscopic processing effect image corresponding to the processing parameter set after the laser processing process, the accuracy of the microscopic processing effect image acquisition can be improved.

[0065] In one embodiment of this application, the process of acquiring microscopic processing effect images corresponding to processing parameter sets may include:

[0066] By using an imaging device to capture images of a localized area processed by laser, a microscopic processing effect image corresponding to the processing parameter set can be obtained.

[0067] In other words, in an optional embodiment, a local area of ​​laser processing is captured by an imaging device to obtain a microscopic processing effect image corresponding to the processing parameter set. The imaging device has a magnification function and may include a regular camera and a magnifying lens with a corresponding magnification. Furthermore, the magnification of the magnifying lens is adjustable, making the magnification of the imaging device highly flexible.

[0068] For example, the imaging device can be positioned near the laser head of the laser processing equipment to acquire microscopic processing images during the laser processing process. Alternatively, the imaging device can be positioned at other locations on the laser processing equipment, such as on the main body component, where it can be rotated to acquire microscopic processing images. In practical applications, the position of the imaging device can be flexibly adjusted according to the specific application scenario, as long as it can acquire microscopic processing images.

[0069] By using imaging devices to capture images of localized areas of laser processing, microscopic processing effect images can be obtained quickly and accurately, improving the efficiency and accuracy of image acquisition.

[0070] In one embodiment of this application, the process of acquiring microscopic processing effect images corresponding to processing parameter sets may include:

[0071] A local area of ​​laser processing is scanned by a linear image sensor, and the scanned images are stitched together to obtain a microscopic processing effect image corresponding to the processing parameter set.

[0072] In other words, in an optional embodiment, a linear image sensor is used to scan a local area of ​​laser processing, and the scanned images are stitched together to obtain a microscopic processing effect image corresponding to the processing parameter set. The linear image sensor comprises multiple photosensitive elements arranged in a line, therefore the scanned images need to be stitched together.

[0073] By scanning and stitching together local areas of laser processing using linear image sensors, microscopic processing effect images can be obtained quickly and accurately, improving the efficiency and accuracy of microscopic processing effect image acquisition.

[0074] In one embodiment of this application, there are multiple processing parameter groups, and these multiple processing parameter groups are arranged sequentially to form a parameter group sequence. For example, in the aforementioned example, there are processing parameter groups Pps1, Pps2, and Pps3, and the parameter group sequence P = {Pps1, Pps2, Pps3}.

[0075] Accordingly, the process in S202, which involves performing laser processing on a localized area of ​​the material to be processed based on a set of processing parameters to obtain a microscopic processing effect image, may include:

[0076] Traverse the first processing parameter group in the parameter group sequence, control the laser processing equipment based on the first processing parameter group, perform laser processing on the position corresponding to the first processing parameter group in the processing area of ​​the material to be processed, and obtain the micro-processing effect image corresponding to the first processing parameter group;

[0077] Iterate through the next processing parameter group adjacent to the first processing parameter group to obtain the microscopic processing effect diagram corresponding to the next processing parameter group, until the parameter group sequence is completely traversed and the microscopic processing effect diagram corresponding to each processing parameter group is obtained.

[0078] That is, in an optional embodiment, the microscopic processing effect diagram corresponding to each processing parameter group is obtained by traversing each processing parameter group sequence.

[0079] For example, continuing from the previous example of parameter set sequence P = {Pps1, Pps2, Pps3}, specifically:

[0080] First, the first processing parameter group Pps1 in the parameter group sequence is traversed, and the laser processing equipment is controlled by the first processing parameter group Pps1 to perform laser processing on the position corresponding to the first processing parameter group Pps1 in the processing area of ​​the material to be processed, so as to obtain the micro-processing effect diagram Miei1 corresponding to the first processing parameter group Pps1.

[0081] Then, the second processing parameter group Pps2 is traversed, and the laser processing equipment is controlled by the second processing parameter group Pps2 to perform laser processing on the position corresponding to the second processing parameter group Pps2 in the processing area of ​​the material to be processed, so as to obtain the micro-processing effect diagram Miei2 corresponding to the second processing parameter group Pps2.

[0082] Then, the third processing parameter group Pps3 is traversed, and the laser processing equipment is controlled by the third processing parameter group Pps3 to perform laser processing on the position in the processing area of ​​the material to be processed that corresponds to the third processing parameter group Pps3, so as to obtain the micro-processing effect diagram Miei3 corresponding to the third processing parameter group Pps3.

[0083] By traversing the parameter group sequence in this way, the microscopic processing effect image corresponding to each processing parameter group in the parameter group sequence can be accurately obtained, thus improving the accuracy of the acquisition of microscopic processing effect images.

[0084] S203, based on the micro-processing effect diagram and the processing strategy corresponding to the area to be processed, predict the macro-effect of the area to be processed to obtain the macro-processing effect diagram; wherein, the macro-processing effect diagram is used to provide a preview of the processing effect of the material to be processed.

[0085] In the embodiments of this application, the processing strategy corresponds to the area to be processed. It refers to the processing strategy set for the material to be processed to become the target product / ideal product, including but not limited to at least one of the following: layout strategy (also known as layout information, which is closely related to point and line layout), path planning strategy (also known as path planning information, which is related to path optimization), pulse control strategy (related to laser pulse frequency and energy adjustment), and speed control strategy (related to laser processing speed).

[0086] In this application embodiment, the macroscopic processing effect diagram refers to the effect diagram corresponding to all areas of laser processing. By observing the macroscopic processing effect diagram, the laser processing effect / condition of all areas can be clearly understood, which helps users select processing parameters and / or processing strategies that meet their laser processing effect expectations.

[0087] In one embodiment of this application, the processing strategy includes layout information and path planning information; correspondingly, the process in S203 of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, to obtain the macroscopic processing effect diagram, may include:

[0088] Based on the micro-processing effect diagram and layout information, generate multiple layout effect diagrams;

[0089] Multiple layout renderings are stitched together based on path planning information to obtain a macro-processing rendering, thereby enabling the prediction of the macro-effects for the area to be processed.

[0090] That is, in the optional embodiment, multiple layout effect diagrams are first generated using the micro-processing effect diagram and layout information (the density of each point and line in the micro-processing effect diagram can be adjusted according to the layout information to generate multiple layout effect diagrams). Then, the multiple layout effect diagrams are spliced ​​according to the path planning information to obtain the macro-processing effect diagram, thereby realizing the prediction of the macro-effect of the area to be processed.

[0091] By implementing this optional embodiment, macroscopic processing effect diagrams can be obtained easily and accurately.

[0092] For example, in an optional embodiment, there are multiple processing parameter groups but only one processing strategy, thereby finding the optimal / relatively optimal processing parameters under a specific processing strategy through a macroscopic processing effect diagram.

[0093] For example, in an optional embodiment, there is one set of processing parameters but multiple processing strategies, thereby finding the optimal / relatively optimal processing strategy under specific processing parameters through a macroscopic processing effect diagram.

[0094] For example, in an optional embodiment, there are multiple processing parameter groups and multiple processing strategies, and the optimal / relatively optimal processing strategy and processing parameters are found through macroscopic processing effect diagrams.

[0095] It should be noted that in practical applications, the number of processing parameter groups and the number of processing strategies can be flexibly adjusted according to the specific application scenario. For ease of understanding, this embodiment is described with multiple processing parameter groups and multiple processing strategies.

[0096] In one embodiment of this application, the process in S203 of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, and obtaining the macroscopic processing effect diagram, may include:

[0097] Based on the microscopic processing effect diagram corresponding to each processing parameter group, the target processing parameter group is selected from multiple processing parameter groups;

[0098] Based on the target processing parameter set and multiple processing strategies, the macroscopic effect of the area to be processed is predicted, and the macroscopic processing effect map corresponding to each processing strategy is obtained.

[0099] In other words, in the optional embodiment, the target processing parameter group is first selected from multiple processing parameter groups using the micro-processing effect map corresponding to each processing parameter group, that is, the processing parameter group screening operation is performed to select the better processing parameter group. Then, the macro-processing effect map corresponding to the target processing parameter group and each processing strategy are used to predict the macro-processing effect on the area to be processed, thereby obtaining the macro-processing effect map corresponding to each processing strategy.

[0100] For example, please refer to [link / reference]. Figure 4 Continuing from the previous example, we have processing parameter groups Pps1, Pps2, and Pps3. The target processing parameter group (usually one) is selected from these three groups. We also have processing strategies Pa1, Pa2, and Pa3. The macroscopic processing effect map corresponding to the target processing parameter group and processing strategy Pa1 are used to predict the macroscopic effect on the area to be processed, resulting in the macroscopic processing effect map Maei corresponding to processing strategy Pa1. 1’ Using the microscopic processing effect map corresponding to the target processing parameter set and the processing strategy Pa2, the macroscopic effect of the area to be processed is predicted, and the macroscopic processing effect map Maei corresponding to the processing strategy Pa2 is obtained. 2’ Using the microscopic processing effect map corresponding to the target processing parameter set and the processing strategy Pa3, the macroscopic effect of the area to be processed is predicted, and the macroscopic processing effect map Maei corresponding to the processing strategy Pa3 is obtained. 3’ .

[0101] In one optional embodiment, the process of selecting a target processing parameter group from multiple processing parameter groups based on the microscopic processing effect diagram corresponding to each processing parameter group may include:

[0102] Displays multiple micro-processing effect images;

[0103] In response to a selection operation for multiple micro-machining effect images, the target machining parameter group corresponding to the micro-machining effect image selected in the selection operation is selected from multiple machining parameter groups.

[0104] That is, in the optional embodiment, the target processing parameter set is selected by the user. For example, please refer to... Figure 5a This is a schematic diagram showing multiple micro-processing effect images, and the selected micro-processing effect image ( Figure 5a The processing parameter set shown in Figure 3 (which illustrates the micro-processing effect) is determined as the target processing parameter set.

[0105] It should be noted that in other embodiments, the target processing parameter set can also be selected by the laser processing equipment. Specifically, a training model can be used to analyze the user's historical laser processing data to select the processing parameter set that the user might choose.

[0106] In one embodiment of this application, the process in S203 of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, and obtaining the macroscopic processing effect diagram, may include:

[0107] Multiple processing parameter groups and multiple processing strategies are combined one by one to obtain multiple process parameter sets; each process parameter set includes a processing parameter group and a processing strategy, and there are at least one difference between the processing parameter group and the processing strategy among different process parameter sets;

[0108] For each set of process parameters, based on the processing strategy in the set of process parameters and the micro-processing effect diagram corresponding to the processing parameter group in the set of process parameters, the macro-effect of the area to be processed is predicted, and the macro-processing effect diagram corresponding to the set of process parameters is obtained.

[0109] That is, in the optional embodiment, multiple processing parameter groups and multiple processing strategies are first combined one by one to obtain multiple process parameter sets, wherein each process parameter set includes a processing parameter group and a processing strategy. There is at least one difference between the processing parameter group and the processing strategy in different process parameter sets. Then, using the processing strategy in each process parameter set and the micro-processing effect map corresponding to the processing parameter group in each process parameter set, the macro-effect of the area to be processed is predicted to obtain the macro-processing effect map corresponding to each process parameter set.

[0110] For example, please refer to [link / reference]. Figure 6 Continuing from the previous example, we have processing parameter groups Pps1, Pps2, and Pps3, and processing strategies Pa1, Pa2, and Pa3. Then, any pairwise combination of processing parameter groups and processing strategies, without repetition, yields the following results: Figure 6 The diagram shows nine sets of process parameters. Then, using the processing strategy within each set and the corresponding microscopic processing effect diagram of each set's processing parameter group, the macroscopic effect on the area to be processed is predicted, resulting in a macroscopic processing effect diagram corresponding to each set of process parameters. For example, using the process parameter set PP... 11 The processing strategy Pps1 and the set of process parameters PP in 11 The microscopic processing effect diagram corresponding to the processing parameter group Pa1 in the diagram is used to predict the macroscopic effect on the area to be processed, thus obtaining the process parameter set PP. 11 Corresponding macroscopic processing effect diagram Maei 11 The same principle applies to other macroscopic processing effect diagrams.

[0111] The method of predicting macroscopic processing effect diagrams through microscopic processing effect diagrams in this embodiment of the application, compared with the prediction methods in related technologies, does not require the collection of a large amount of accurate data, and is less complex and easier to implement. Therefore, it greatly improves the simplicity of laser processing effect prediction, enhances the reliability of laser processing, and increases the stickiness between laser processing equipment and users.

[0112] In one embodiment of this application, another data processing method based on laser processing equipment is provided, which can be executed by laser processing equipment 102. For example... Figure 7 As shown, the data processing method based on laser processing equipment may also include S701 to S702 after S203.

[0113] Detailed introductions of S701 to S702 are as follows:

[0114] S701, obtain the target process parameter set based on the macroscopic processing effect diagram; wherein, the target process parameter set includes at least one of the target processing parameter group and the target processing strategy, the target processing parameter group is any one of multiple processing parameter groups, and the target processing strategy is any one of multiple processing strategies.

[0115] In this embodiment, there are multiple processing parameter groups and multiple processing strategies, resulting in multiple macroscopic processing strategies. Therefore, the target process parameter set can be obtained using multiple macroscopic processing effect diagrams. In this embodiment, the target process parameter set includes at least one of a target processing parameter group and a target processing strategy, where the target processing parameter group refers to any one of the multiple processing parameter groups, and the target processing strategy refers to any one of the multiple processing strategies.

[0116] As described in the foregoing embodiments, a macroscopic processing effect diagram corresponding to each processing strategy can be obtained; correspondingly, the process of obtaining the target process parameter set based on the macroscopic processing effect diagram in S701 may include:

[0117] Based on the macroscopic processing effect diagram corresponding to each processing strategy, the target processing strategy is selected from multiple processing strategies;

[0118] The target processing parameter set and the target processing strategy are combined to generate the target process parameter set.

[0119] That is, in the optional embodiment, after obtaining the macroscopic processing effect diagram corresponding to each processing strategy, the target processing strategy can be selected from multiple processing strategies using the macroscopic processing effect diagram corresponding to each processing strategy, and the target processing parameter group and the target processing strategy can be combined to generate the target process parameter set.

[0120] In one optional embodiment, the process of selecting a target processing strategy from multiple processing strategies based on the macroscopic processing effect diagram corresponding to each processing strategy may include:

[0121] Displays multiple macroscopic processing effect diagrams;

[0122] In response to a selection operation for multiple macro-processing effect diagrams, the target processing strategy corresponding to the macro-processing effect diagram selected by the selection operation is chosen from multiple processing strategies.

[0123] That is, in the optional embodiment, the target processing strategy is selected by the user. For example, please refer to... Figure 5b This is a schematic diagram showing multiple macroscopic processing effect images, and the selected macroscopic processing effect image ( Figure 5b The image shows the macroscopic processing effect. Figure 2 The corresponding processing strategy is determined as the target processing strategy.

[0124] It should be noted that in other embodiments, the target processing strategy can also be selected by the laser processing equipment. Specifically, a training model can be used to analyze the user's historical processing data to select the target processing strategy that the user might choose.

[0125] By implementing this optional embodiment, the processing parameter group is first screened accordingly, and then the macroscopic processing effect is predicted using the microscopic processing effect map corresponding to the screened processing parameter group and multiple processing strategies. This can accelerate the prediction efficiency, improve the acquisition efficiency of macroscopic processing effect map, and reduce the computing resources required for prediction.

[0126] As described in the foregoing embodiments, a macroscopic processing effect diagram corresponding to the set of process parameters can be obtained; correspondingly, the process of obtaining the target set of process parameters based on the macroscopic processing effect diagram in S701 may include:

[0127] Based on the macroscopic processing effect diagram corresponding to each set of process parameters, the target set of process parameters is selected from multiple sets of process parameters.

[0128] That is, in the optional embodiment, after obtaining the macroscopic processing effect diagram corresponding to each set of process parameters, the target process parameter set can be selected from multiple sets of process parameters using the macroscopic processing effect diagram corresponding to each set of process parameters.

[0129] In one optional embodiment, the process of selecting a target process parameter set from multiple process parameter sets based on the macroscopic processing effect diagram corresponding to each process parameter set may include:

[0130] Displays multiple macroscopic processing effect diagrams;

[0131] In response to a selection operation for multiple macroscopic processing effect diagrams, the target process parameter set corresponding to the macroscopic processing effect diagram selected by the selection operation is selected from multiple process parameter sets.

[0132] That is, in the optional embodiment, the set of target process parameters is selected by the user. For example, please refer to... Figure 8a This is a schematic diagram showing multiple macroscopic processing effect images, and the selected macroscopic processing effect image ( Figure 8a The image shows the macroscopic processing effect. Figure 1 The set of process parameters corresponding to ) is determined as the target process parameter set.

[0133] It should be noted that in other embodiments, the target process parameter set can also be selected by the laser processing equipment. Specifically, a training model can be used to analyze the user's historical processing data to select the target process parameter set that the user might choose.

[0134] By implementing optional embodiments, multiple sets of process parameters and processing strategies are combined to obtain the macroscopic processing effect corresponding to each set of process parameters. The prediction is highly comprehensive, improving the comprehensiveness of the collection of macroscopic processing effects, and thus providing users with more comprehensive auxiliary opinions.

[0135] S702 performs laser processing on the area to be processed based on the target set of process parameters.

[0136] In this embodiment, a set of target process parameters is obtained, and then the set of target process parameters can be used to perform laser processing on the area to be processed.

[0137] In one embodiment of this application, the laser processing of the area to be processed based on the target process parameter set in S702 can include two cases:

[0138] Case 1: If there is only one set of target process parameters, then in response to the confirmation operation for the set of target process parameters, laser processing is performed on the area to be processed based on the set of target process parameters.

[0139] That is, in the optional embodiment, if there is only one set of target process parameters, then after receiving a confirmation operation for the set of target process parameters, the laser processing of the area to be processed can be performed using the set of target process parameters in response to the confirmation operation, so as to obtain the target product expected by the user.

[0140] Case 2: If there are multiple target process parameter sets, then in response to the selection operation for multiple target process parameter sets, laser processing is performed on the area to be processed based on the target process parameter set selected by the selection operation.

[0141] That is, in the optional embodiment, if there are multiple target process parameter sets, after receiving a selection operation for multiple target process parameter sets, the laser processing of the area to be processed can be performed using the target process parameter set selected by the selection operation in response to the selection operation, so as to obtain the target product expected by the user.

[0142] Optionally, when there are multiple target process parameter sets, the advantages and disadvantages of each set can be displayed, providing users with appropriate selection options and enhancing the user experience. Please refer to [link / reference]. Figure 8b This is a schematic diagram displaying the advantages and disadvantages of two sets of process parameters. Figure 8b These are just two examples; in practical applications, adjustments can be made flexibly according to specific application scenarios.

[0143] By implementing this optional embodiment, when there are one or more target process parameters, laser processing can be performed on the area to be processed using the target process parameter set corresponding to the corresponding trigger operation after receiving the user's corresponding trigger operation. This results in good interactivity with the user, lowers the barrier to entry for using laser processing equipment, and thus improves the user experience.

[0144] It should be noted that, Figure 7For detailed information on S201 to S203 shown, please refer to [link / reference]. Figure 2 S201 to S203 shown will not be described again here.

[0145] In this embodiment, a set of target process parameters is obtained by utilizing a macroscopic processing effect diagram. Then, the set of target process parameters can be used to easily and accurately perform laser processing on the area to be processed, which is applicable to many laser processing scenarios.

[0146] In one embodiment of this application, another data processing method based on laser processing equipment is provided, which can be executed by laser processing equipment 102. For example... Figure 9 As shown, the data processing method based on laser processing equipment may also include S901 to S903 after S702.

[0147] Detailed introductions of S901 to S903 are as follows:

[0148] S901, Obtain the set of target process parameters for laser processing of the area to be processed to obtain the target product.

[0149] S902, associate and store the identification information of the material to be processed with the obtained set of target process parameters.

[0150] In this embodiment of the application, after laser processing of the area to be processed using the target process parameter set, the target process parameter set can be obtained and associated with the identification information of the material to be processed (corresponding to the material before laser processing) and stored. The identification information of the material to be processed refers to the information used to uniquely identify the material to be processed, which includes, but is not limited to, at least one of the following: name, model, chemical composition, physical properties, mechanical properties, thermal properties, optical properties, electrical properties, and environmental adaptability. In practical applications, the identification information of the material to be processed can be flexibly adjusted according to the specific application scenario.

[0151] Optionally, the identification information and target process parameter set of the associated stored materials to be processed can be updated periodically or irregularly to ensure their timeliness and accuracy.

[0152] S903: If, within a specified time period, another material to be processed that matches the identification information is detected and needs to be laser-processed into the target product, then the laser processing equipment is controlled to perform laser processing on the other material to be processed based on the stored set of target process parameters.

[0153] In this embodiment of the application, if another material to be processed is detected that matches the identification information in the associated storage, and the other material to be processed also needs to be processed into the product processed by the aforementioned material to be processed, that is, the user wants to obtain the same product again, then the laser processing equipment can be controlled to perform laser processing on the other material to be processed by using the set of target process parameters associated with the identification information in the associated storage.

[0154] Optionally, before controlling the laser processing equipment to perform laser processing on another material to be processed using the set of target process parameters associated with the identification information in the associated storage, the user can be reminded in any form (such as a visual interface, SMS, application notification message, etc.) and laser processing can be performed only after obtaining the user's confirmation, thereby avoiding misoperation.

[0155] It should be noted that, Figure 9 For detailed information on S201 to S203 shown, please refer to [link / reference]. Figure 2 As shown in S201 to S203, Figure 9 For detailed information on S701 to S702 shown, please refer to [link / reference]. Figure 7 S701 to S702 shown will not be described again here.

[0156] In this embodiment, the material to be processed is associated with and stored with the set of target process parameters for processing it. Thus, when a user has a need to make the same product, the step of determining the set of target process parameters is omitted, improving the efficiency of laser processing and providing a better user experience.

[0157] Figure 10 This is a block diagram illustrating a data processing apparatus based on a laser processing device, as shown in an exemplary embodiment of this application. The apparatus includes:

[0158] The generation module 1001 is configured to generate a set of processing parameters corresponding to the material to be processed.

[0159] The processing module 1002 is configured to perform laser processing on a local area of ​​the material to be processed based on the processing parameter set, so as to obtain a microscopic processing effect image.

[0160] The prediction module 1003 is configured to predict the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, and obtain a macroscopic processing effect diagram; wherein, the macroscopic processing effect diagram is used to provide a preview of the processing effect of the material to be processed.

[0161] In one embodiment of this application, the processing strategy includes layout information and path planning information; the prediction module 1003 is specifically configured as follows:

[0162] Based on the micro-processing effect diagram and the layout information, multiple layout effect diagrams are generated;

[0163] The multiple layout effect diagrams are stitched together according to the path planning information to obtain a macro processing effect diagram, so as to predict the macro effect of the area to be processed.

[0164] In one embodiment of this application, the processing module 1002 is specifically configured as follows:

[0165] The laser processing equipment is controlled based on the processing parameter set to perform laser processing on the processing area of ​​the material to be processed, and microscopic processing effect images corresponding to the processing parameter set are collected during or after the laser processing process.

[0166] In one embodiment of this application, the processing module 1002 is further configured as follows:

[0167] By capturing images of a localized area processed by laser using an imaging device, a microscopic processing effect image corresponding to the set of processing parameters can be obtained; or

[0168] A local area of ​​laser processing is scanned by a linear image sensor, and the scanned images are stitched together to obtain a microscopic processing effect image corresponding to the processing parameter set.

[0169] In one embodiment of this application, there are multiple processing parameter groups, which are arranged sequentially to form a parameter group sequence; the processing module 1002 is specifically configured as follows:

[0170] Traverse the first processing parameter group in the parameter group sequence, control the laser processing equipment based on the first processing parameter group, perform laser processing on the position corresponding to the first processing parameter group in the processing area of ​​the material to be processed, and obtain the microscopic processing effect image corresponding to the first processing parameter group;

[0171] The process iterates through the next processing parameter group adjacent to the first processing parameter group to obtain the microscopic processing effect diagram corresponding to the next processing parameter group, until the parameter group sequence is completely traversed to obtain the microscopic processing effect diagram corresponding to each processing parameter group.

[0172] In one embodiment of this application, the generation module 1001 is specifically configured as follows:

[0173] Determine multiple processing parameters for laser processing of the material to be processed;

[0174] Multiple candidate parameter groups are generated based on the multiple processing parameters, and each candidate parameter group has the multiple processing parameters;

[0175] For each candidate parameter group, the processing parameters contained in the candidate parameter group are assigned values ​​to obtain the processing parameter group corresponding to the candidate parameter group; wherein, at least one processing parameter in different processing parameter groups has a different assigned value.

[0176] In one embodiment of this application, there are multiple processing parameter groups and multiple processing strategies; the prediction module 1003 is specifically configured as follows:

[0177] Based on the microscopic processing effect diagram corresponding to each processing parameter group, a target processing parameter group is selected from the plurality of processing parameter groups;

[0178] Based on the target processing parameter set and the multiple processing strategies, the macroscopic effect on the area to be processed is predicted, and the macroscopic processing effect map corresponding to each processing strategy is obtained.

[0179] In one embodiment of this application, there are multiple processing parameter groups and multiple processing strategies; the prediction module 1003 is specifically configured as follows:

[0180] The multiple processing parameter groups and multiple processing strategies are combined one by one to obtain multiple process parameter sets; wherein, each process parameter set includes a processing parameter group and a processing strategy, and there are at least one difference between the processing parameter group and the processing strategy among different process parameter sets;

[0181] For each set of process parameters, based on the processing strategy in the set of process parameters and the micro-processing effect diagram corresponding to the processing parameter group in the set of process parameters, the macro-effect of the area to be processed is predicted, and the macro-processing effect diagram corresponding to the set of process parameters is obtained.

[0182] In one embodiment of this application, the device further includes:

[0183] The module is configured to obtain a set of target process parameters based on the macroscopic processing effect diagram; wherein, the set of target process parameters includes at least one of a set of target processing parameters and a target processing strategy, the set of target processing parameters being any one of multiple processing parameter sets, and the target processing strategy being any one of multiple processing strategies;

[0184] The processing module is configured to perform laser processing on the area to be processed based on the target process parameter set.

[0185] In one embodiment of this application, the obtained module is specifically configured as follows:

[0186] Based on the macroscopic processing effect diagram corresponding to each processing strategy, a target processing strategy is selected from the multiple processing strategies;

[0187] The target processing parameter set and the target processing strategy are combined to generate a target process parameter set.

[0188] In one embodiment of this application, the obtained module is specifically configured as follows:

[0189] Based on the macroscopic processing effect diagram corresponding to each set of process parameters, a target set of process parameters is selected from the multiple sets of process parameters.

[0190] In one embodiment of this application, the processing module is specifically configured as follows:

[0191] If the target process parameter set is a single value, then in response to the confirmation operation for the target process parameter set, laser processing is performed on the area to be processed based on the target process parameter set.

[0192] If there are multiple target process parameter sets, then in response to a selection operation for multiple target process parameter sets, laser processing is performed on the area to be processed based on the target process parameter set selected by the selection operation.

[0193] In one embodiment of this application, the device further includes:

[0194] The acquisition module is configured to acquire a set of target process parameters for laser processing of the area to be processed to obtain the target product;

[0195] The storage module is configured to associate and store the identification information of the material to be processed with the acquired set of target process parameters.

[0196] The third processing module is configured to control the laser processing equipment to perform laser processing on the other material if it is detected within a specified time period that matches the identification information and needs to be laser-processed into the target product.

[0197] It should be noted that the data processing device based on laser processing equipment provided in the above embodiments and the data processing method based on laser processing equipment provided in the above embodiments belong to the same concept. The specific way in which each module and unit performs operations has been described in detail in the method embodiments, and will not be repeated here.

[0198] The data processing device based on laser processing equipment provided in the above embodiments predicts macroscopic processing effect images from microscopic processing effect images. Compared with prediction methods in related technologies, it does not require the collection of a large amount of accurate data, and is less complex and easier to implement. Therefore, it greatly improves the ease of laser processing effect prediction, enhances the reliability of laser processing, and increases the stickiness between laser processing equipment and users.

[0199] Embodiments of this application also provide an electronic device, including: one or more processors; and a memory for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the data processing method based on laser processing equipment provided in the various embodiments above. Exemplarily, the electronic device is a laser processing equipment.

[0200] Figure 11 This is a schematic diagram of the structure of a computer system suitable for implementing the electronic devices of the embodiments of this application. It should be noted that... Figure 11 The computer system 1100 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0201] like Figure 11 As shown, the computer system 1100 includes a Central Processing Unit (CPU) 1101, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 1102 or programs loaded from storage portion 1108 into Random Access Memory (RAM) 1103, such as performing the methods described in the above embodiments. Various programs and data required for system operation are also stored in RAM 1103. The CPU 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. An Input / Output (I / O) interface 1105 is also connected to bus 1104.

[0202] The following components are connected to I / O interface 1105: an input section 1106 including a keyboard, mouse, etc.; an output section 1107 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a local area network (LAN) card, modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. Drive 1110 is also connected to I / O interface 1105 as needed. Removable media 1111, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1110 as needed so that computer programs read from them can be installed into storage section 1108 as needed.

[0203] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1109, and / or installed from removable medium 1111. When the computer program is executed by central processing unit (CPU) 1101, it performs various functions defined in the system of this application.

[0204] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0205] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0206] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0207] Another aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the data processing method based on laser processing equipment as described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0208] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the data processing method based on laser processing equipment provided in the various embodiments above.

[0209] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. A data processing method based on laser processing equipment, characterized in that, include: Generate the processing parameter set corresponding to the material to be processed; Based on the processing parameter set, laser processing is performed on a localized area of ​​the material to be processed to obtain a microscopic processing effect image. Based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, the macroscopic effect of the area to be processed is predicted to obtain a macroscopic processing effect diagram; wherein, the macroscopic processing effect diagram is used to provide a preview of the processing effect of the material to be processed; The processing strategy includes layout information and path planning information. The step of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, to obtain a macroscopic processing effect diagram, includes: generating multiple layout effect diagrams based on the microscopic processing effect diagram and the layout information; and stitching the multiple layout effect diagrams together according to the path planning information to obtain a macroscopic processing effect diagram, thereby achieving the prediction of the macroscopic effect of the area to be processed. The process includes multiple processing parameter groups and multiple processing strategies. The step of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, to obtain a macroscopic processing effect diagram, includes: combining the multiple processing parameter groups and multiple processing strategies one by one to obtain multiple process parameter sets; wherein each process parameter set includes one processing parameter group and one processing strategy, and at least one of the processing parameter groups and processing strategies differs between different process parameter sets; for each process parameter set, based on the processing strategy in the process parameter set and the microscopic processing effect diagram corresponding to the processing parameter group in the process parameter set, predicting the macroscopic effect of the area to be processed, to obtain a macroscopic processing effect diagram corresponding to the process parameter set.

2. The method according to claim 1, characterized in that, The process of performing laser processing on a localized area of ​​the material to be processed based on the processing parameter set to obtain a microscopic processing effect image includes: The laser processing equipment is controlled based on the processing parameter set to perform laser processing on the processing area of ​​the material to be processed, so as to collect the microscopic processing effect image corresponding to the processing parameter set during or after the laser processing process.

3. The method according to claim 2, characterized in that, The acquisition of the microscopic processing effect images corresponding to the processing parameter set includes: By capturing images of a localized area processed by laser using an imaging device, a microscopic processing effect image corresponding to the set of processing parameters can be obtained; or A local area of ​​laser processing is scanned by a linear image sensor, and the scanned images are stitched together to obtain a microscopic processing effect image corresponding to the processing parameter set.

4. The method according to claim 1, characterized in that, Multiple processing parameter groups are arranged sequentially to form a parameter group sequence; The process of performing laser processing on a localized area of ​​the material to be processed based on the processing parameter set to obtain a microscopic processing effect image includes: Traverse the first processing parameter group in the parameter group sequence, control the laser processing equipment based on the first processing parameter group, perform laser processing on the position corresponding to the first processing parameter group in the processing area of ​​the material to be processed, and obtain the microscopic processing effect image corresponding to the first processing parameter group; The process iterates through the next processing parameter group adjacent to the first processing parameter group to obtain the microscopic processing effect diagram corresponding to the next processing parameter group, until the parameter group sequence is completely traversed to obtain the microscopic processing effect diagram corresponding to each processing parameter group.

5. The method according to claim 1, characterized in that, The processing parameter set corresponding to the material to be processed includes: Determine multiple processing parameters for laser processing of the material to be processed; Multiple candidate parameter groups are generated based on the multiple processing parameters, and each candidate parameter group has the multiple processing parameters; For each candidate parameter group, the processing parameters contained in the candidate parameter group are assigned values ​​to obtain the processing parameter group corresponding to the candidate parameter group; wherein, at least one processing parameter in different processing parameter groups has a different assigned value.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Based on the aforementioned macroscopic processing effect diagram, a set of target process parameters is obtained; wherein, the set of target process parameters includes at least one of a set of target processing parameters and a target processing strategy, the set of target processing parameters being any one of multiple processing parameter sets, and the target processing strategy being any one of multiple processing strategies; Laser processing is performed on the area to be processed based on the target process parameter set.

7. The method according to claim 6, characterized in that, The set of target process parameters obtained based on the macroscopic processing effect diagram includes: Based on the macroscopic processing effect diagram corresponding to each set of process parameters, a target set of process parameters is selected from the multiple sets of process parameters.

8. The method according to claim 6, characterized in that, The laser processing of the area to be processed based on the target process parameter set includes: If the target process parameter set is a single set, then in response to the confirmation operation for the target process parameter set, laser processing is performed on the area to be processed based on the target process parameter set; If there are multiple target process parameter sets, then in response to a selection operation for multiple target process parameter sets, laser processing is performed on the area to be processed based on the target process parameter set selected by the selection operation.

9. The method according to claim 6, characterized in that, After performing laser processing on the area to be processed based on the target process parameter set, the method further includes: Obtain a set of target process parameters for laser processing of the area to be processed to obtain the target product; The identification information of the material to be processed is associated and stored with the obtained set of target process parameters; If, within a specified time period, another material to be processed that matches the identification information is detected and needs to be laser-processed into the target product, then the laser processing equipment is controlled to perform laser processing on the other material to be processed based on the stored set of target process parameters.

10. A data processing method based on laser processing equipment, characterized in that, include: Generate the processing parameter set corresponding to the material to be processed; Based on the processing parameter set, laser processing is performed on a localized area of ​​the material to be processed to obtain a microscopic processing effect image. Based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, the macroscopic effect of the area to be processed is predicted to obtain a macroscopic processing effect diagram; wherein, the macroscopic processing effect diagram is used to provide a preview of the processing effect of the material to be processed; The processing strategy includes layout information and path planning information. The step of predicting the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, to obtain a macroscopic processing effect diagram, includes: generating multiple layout effect diagrams based on the microscopic processing effect diagram and the layout information; and stitching the multiple layout effect diagrams together according to the path planning information to obtain a macroscopic processing effect diagram, thereby achieving the prediction of the macroscopic effect of the area to be processed. The process includes multiple processing parameter groups and multiple processing strategies. The step of predicting the macroscopic effect on the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, to obtain a macroscopic processing effect diagram, includes: selecting a target processing parameter group from the multiple processing parameter groups based on the microscopic processing effect diagram corresponding to each processing parameter group; and predicting the macroscopic effect on the area to be processed based on the target processing parameter group and the multiple processing strategies, to obtain a macroscopic processing effect diagram corresponding to each processing strategy.

11. The method according to claim 10, characterized in that, The process of performing laser processing on a localized area of ​​the material to be processed based on the processing parameter set to obtain a microscopic processing effect image includes: The laser processing equipment is controlled based on the processing parameter set to perform laser processing on the processing area of ​​the material to be processed, so as to collect the microscopic processing effect image corresponding to the processing parameter set during or after the laser processing process.

12. The method according to claim 11, characterized in that, The acquisition of the microscopic processing effect images corresponding to the processing parameter set includes: By capturing images of a localized area processed by laser using an imaging device, a microscopic processing effect image corresponding to the set of processing parameters can be obtained; or A local area of ​​laser processing is scanned by a linear image sensor, and the scanned images are stitched together to obtain a microscopic processing effect image corresponding to the processing parameter set.

13. The method according to claim 10, characterized in that, Multiple processing parameter groups are arranged sequentially to form a parameter group sequence; The process of performing laser processing on a localized area of ​​the material to be processed based on the processing parameter set to obtain a microscopic processing effect image includes: Traverse the first processing parameter group in the parameter group sequence, control the laser processing equipment based on the first processing parameter group, perform laser processing on the position corresponding to the first processing parameter group in the processing area of ​​the material to be processed, and obtain the microscopic processing effect image corresponding to the first processing parameter group; The process iterates through the next processing parameter group adjacent to the first processing parameter group to obtain the microscopic processing effect diagram corresponding to the next processing parameter group, until the parameter group sequence is completely traversed to obtain the microscopic processing effect diagram corresponding to each processing parameter group.

14. The method according to claim 10, characterized in that, The processing parameter set corresponding to the material to be processed includes: Determine multiple processing parameters for laser processing of the material to be processed; Multiple candidate parameter groups are generated based on the multiple processing parameters, and each candidate parameter group has the multiple processing parameters; For each candidate parameter group, the processing parameters contained in the candidate parameter group are assigned values ​​to obtain the processing parameter group corresponding to the candidate parameter group; wherein, at least one processing parameter in different processing parameter groups has a different assigned value.

15. The method according to any one of claims 10 to 14, characterized in that, The method further includes: Based on the aforementioned macroscopic processing effect diagram, a set of target process parameters is obtained; wherein, the set of target process parameters includes at least one of a set of target processing parameters and a target processing strategy, the set of target processing parameters being any one of multiple processing parameter sets, and the target processing strategy being any one of multiple processing strategies; Laser processing is performed on the area to be processed based on the target process parameter set.

16. The method according to claim 15, characterized in that, The set of target process parameters obtained based on the macroscopic processing effect diagram includes: Based on the macroscopic processing effect diagram corresponding to each processing strategy, a target processing strategy is selected from the multiple processing strategies; The target processing parameter set and the target processing strategy are combined to generate a target process parameter set.

17. The method according to claim 15, characterized in that, The laser processing of the area to be processed based on the target process parameter set includes: If the target process parameter set is a single set, then in response to the confirmation operation for the target process parameter set, laser processing is performed on the area to be processed based on the target process parameter set; If there are multiple target process parameter sets, then in response to a selection operation for multiple target process parameter sets, laser processing is performed on the area to be processed based on the target process parameter set selected by the selection operation.

18. The method according to claim 15, characterized in that, After performing laser processing on the area to be processed based on the target process parameter set, the method further includes: Obtain a set of target process parameters for laser processing of the area to be processed to obtain the target product; The identification information of the material to be processed is associated and stored with the obtained set of target process parameters; If, within a specified time period, another material to be processed that matches the identification information is detected and needs to be laser-processed into the target product, then the laser processing equipment is controlled to perform laser processing on the other material to be processed based on the stored set of target process parameters.

19. A data processing device based on laser processing equipment, characterized in that, A data processing method based on a laser processing device for performing any one of claims 1 to 18 includes: The generation module is configured to generate a set of processing parameters corresponding to the material to be processed. The processing module is configured to perform laser processing on a localized area of ​​the material to be processed based on the processing parameter set, thereby obtaining a microscopic processing effect image. The prediction module is configured to predict the macroscopic effect of the area to be processed based on the microscopic processing effect diagram and the processing strategy corresponding to the area to be processed, and obtain a macroscopic processing effect diagram; wherein, the macroscopic processing effect diagram is used to provide a preview of the processing effect of the material to be processed.

20. An electronic device, characterized in that, include: One or more processors; A memory for storing one or more programs, which, when executed by the electronic device, cause the electronic device to implement the data processing method based on a laser processing device as described in any one of claims 1 to 18.

21. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the data processing method based on the laser processing equipment as described in any one of claims 1 to 18.

22. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the data processing method based on the laser processing equipment as described in any one of claims 1 to 18.

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