A Laser Cutting Control System and Method

Abstract

The present invention provides a laser cutting control method and system, belonging to the technical field of laser control. Specifically, when it is determined that the distribution dispersion degree of the cutting risk positions of the fabric processing object meets the requirements based on the distribution data of different cutting risk positions, according to the cutting processing program, the power switching type of the laser device of the embroidery machine at different cutting risk positions is determined, and the switching abnormal coefficient of different cutting risk positions is determined by using the switching abnormal data corresponding to the power switching type. Based on the distribution data of the cutting risk positions and the switching abnormal coefficient of the cutting risk positions, the cutting control strategy of the laser device of the embroidery machine is determined, reducing the probability of damaging the positioning auxiliary materials.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser control, and particularly relates to a laser cutting control system and method. Background Art

[0002] Laser cutting devices have been widely applied in embroidery machines. Through the layering method of the laser control system, it is possible to "embroider" transition colors with different shades and a sense of hierarchy in the fabric background color on the same-colored fabric. Specifically, in the patent application for invention CN202211026064.X "Dual Laser Device, Embroidery Machine, Control Method, Storage Medium and Electronic Device" and CN202210675150.7 "Embroidery Machine and Its Smoke Exhaust Method", devices for embroidery processing of embroidery machines using laser cutting devices are provided. However, the following technical defects exist in the above devices:

[0003] During the laser cutting control process of the embroidery machine, once the output power of the laser cannot be effectively controlled, it may damage the positioning auxiliary materials under the fabric. Therefore, how to achieve power control of the laser during the cutting process and avoid damaging the positioning auxiliary materials has become a technical problem to be solved urgently.

[0004] In view of the above technical problems, specifically, the present application provides a laser cutting control system and method. Summary of the Invention

[0005] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present application provides a laser cutting control method, which specifically includes:

[0007] S1 Based on the cutting treatment type of the fabric treatment object of the embroidery machine, determine the historical damage data of the positioning auxiliary materials under different cutting treatment types, and when using the historical damage data to determine the cutting risk positions of the fabric treatment object, obtain the distribution data of different cutting risk positions;

[0008] S2 Based on the distribution data of different cutting risk positions, when it is determined that the distribution dispersion degree of the cutting risk positions of the fabric treatment object meets the requirements, proceed to the next step;

[0009] S3 According to the cutting treatment program, determine the power switching type of the laser device of the embroidery machine at different cutting risk positions, and use the switching abnormal data corresponding to the power switching type to determine the switching abnormal coefficient of different cutting risk positions;

[0010] S4 Based on the distribution data of the cutting risk positions and the switching abnormal coefficient of the cutting risk positions, determine the cutting control strategy of the laser device of the embroidery machine.

[0011] The beneficial effects of the present invention are as follows:

[0012] Based on the distribution data of different cutting risk positions, it is determined whether the distribution dispersion degree of the cutting risk positions of the fabric processing object meets the requirements, thereby realizing the determination of the distribution dispersion degree of the cutting risk positions from the number of cutting risk positions and the distance between different cutting risk positions. This avoids the influence of frequent power switching on the service life of the laser device caused by the fixed cutting processing program for fabric processing objects with a relatively high distribution dispersion degree. At the same time, it also avoids the problem that frequent power switching makes it impossible to accurately and reliably control the output power of the laser device, improves the reliability and safety of cutting processing, and also reduces the damage probability of positioning accessories to a certain extent.

[0013] Based on the distribution data of cutting risk positions and the switching abnormality coefficient of cutting risk positions, the cutting control strategy of the laser device of the embroidery machine is determined. It not only takes into account the differences in the number of power switching processes due to differences in distribution data, but also comprehensively considers the differences in the probability of switching abnormalities occurring during the switching process due to power switching differences at different cutting risk positions. This not only ensures the safety and reliability of fabric cutting processing, but also realizes the reliable and accurate control of the output power of the laser device.

[0014] A further technical solution lies in that the cutting processing type is divided according to the cutting processing depth at different positions.

[0015] A further technical solution lies in that the historical damage data includes the historical damage times of positioning accessories under the cutting processing type and the damage depths of different historical damage times.

[0016] A further technical solution lies in that the method for determining the cutting risk position is as follows:

[0017] Based on the historical damage data corresponding to the cutting processing type corresponding to the processing position, determine the historical damage times under the same fabric type of the fabric processing object;

[0018] Based on the ratio of the historical damage times to the historical processing times of the same fabric type under the cutting processing type, determine the damage risk probability;

[0019] Use the damage risk probability to determine whether the processing position is a cutting risk position.

[0020] A further technical solution lies in that when the damage risk probability is greater than the preset probability threshold, it is determined that the processing position belongs to the cutting risk position.

[0021] A further technical solution is that when there is no cutting risk position, continuous cutting processing is performed using a cutting processing program and cutting processing types corresponding to different processing positions.

[0022] A further technical solution is that the method for determining the cutting control strategy of the laser device of the embroidery machine is as follows:

[0023] Based on the distribution data of the cutting risk positions, determine the number of power switching processes of the laser device of the embroidery machine;

[0024] Based on the product of the switching abnormality coefficient of different switching risk positions and a preset proportional factor, determine the switching abnormality weight coefficient of different switching risk positions;

[0025] Determine the switching processing abnormality coefficient according to the sum of the switching abnormality weight coefficients of different numbers of power switching processes, and use the switching processing abnormality coefficient to determine the cutting control strategy of the laser device of the embroidery machine.

[0026] A further technical solution is that using the switching processing abnormality coefficient to determine the cutting control strategy of the laser device of the embroidery machine specifically includes:

[0027] When the switching processing abnormality coefficient is greater than a preset switching abnormality coefficient threshold, first perform cutting processing to remove the cutting risk positions, and then perform unified cutting processing on all cutting risk positions;

[0028] When the switching processing abnormality coefficient is not greater than the preset switching abnormality coefficient threshold, continuous cutting processing is performed using a cutting processing program and cutting processing types corresponding to different processing positions.

[0029] In a second aspect, the present invention provides a laser cutting control system, which adopts the above-mentioned laser cutting control method, and specifically includes:

[0030] A risk position identification module, a distribution discrete evaluation module, and a switching strategy determination module;

[0031] Wherein the risk position identification module is responsible for determining the cutting risk positions of the fabric processing object;

[0032] The distribution discrete evaluation module is responsible for determining whether the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements;

[0033] The switching strategy determination module is responsible for determining the cutting control strategy of the laser device of the embroidery machine.

[0034] Other features and advantages will be described in the subsequent specification. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0035] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following specifically gives preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. Description of the Drawings

[0036] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above and other features and advantages of the present invention will become more obvious.

[0037] Figure 1 is a flowchart of a laser cutting control method;

[0038] Figure 2 is a flowchart of a method for determining the cutting risk position;

[0039] Figure 3 is a flowchart for determining that the distribution dispersion degree of the cutting risk positions of the fabric processing object meets the requirements;

[0040] Figure 4 is a flowchart of a method for determining the switching abnormality coefficient of the cutting risk position;

[0041] Figure 5 is a flowchart of a method for determining the cutting control strategy of the laser device of the embroidery machine;

[0042] Figure 6 is a framework diagram of a laser cutting control system. Detailed Embodiments

[0043] In order to enable those skilled in the art to better understand the technical solutions in this specification, the following will clearly and completely describe the technical solutions in the embodiments of this specification in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0044] In this application, using the distribution data of the cutting risk positions, the number of power switches of the laser device during the processing is determined. According to the number of power switches and the abnormal conditions during the switching process, a differentiated cutting control strategy for the laser device of the embroidery machine is generated, that is, the cutting process is carried out in sequence according to the cutting process or, after the cutting of other positions is completed, the unified cutting of the cutting risk positions is carried out, ensuring the reliability of the power control of the laser device.

[0045] The ratio of the historical number of damages to the historical number of treatments of the same fabric type under the cutting treatment type is used to determine the damage risk probability. When the damage risk probability is greater than 0.3, the treatment position is determined as the cutting risk position.

[0046] When the distances between different cutting risk positions are all less than the preset distance, it is determined that the distribution dispersion degree of the cutting risk positions of the fabric treatment object meets the requirements.

[0047] Based on the abnormal switching data of the power switching type at the cutting risk position, the number of switching anomalies is determined, the historical number of switches of the power switching type is obtained, and the switching anomaly coefficient of the cutting risk position is determined according to the ratio of the number of switching anomalies to the historical number of switches.

[0048] Based on the distribution data of the cutting risk position, the number of power switching treatments of the laser device of the embroidery machine is determined. Based on the product of the switching anomaly coefficient of different switching risk positions and the preset proportional factor, the switching anomaly weight coefficient of different switching risk positions is determined. The switching treatment anomaly coefficient is determined according to the sum of the switching anomaly weight coefficients of different power switching treatment numbers, and the cutting control strategy of the laser device of the embroidery machine is determined using the switching treatment anomaly coefficient.

[0049] Embodiment 1

[0050] As Figure 1 shown, in the first aspect provided by the present application, a laser cutting control method is provided, which specifically includes:

[0051] S1 Based on the cutting treatment type of the fabric treatment object of the embroidery machine, the historical damage data of the positioning auxiliary materials under different cutting treatment types is determined. When it is determined that the fabric treatment object has a cutting risk position using the historical damage data, the distribution data of different cutting risk positions is obtained;

[0052] Furthermore, the cutting treatment type is divided according to the cutting treatment depth at different positions.

[0053] It should be noted that the historical damage data includes the historical number of damages to the positioning auxiliary materials under the cutting treatment type and the damage depth of different historical numbers of damages.

[0054] It can be understood that, as Figure 2 shown, the method for determining the cutting risk position is:

[0055] Based on the historical damage data corresponding to the cutting treatment type of the treatment position, the historical number of damages of the same fabric type of the fabric treatment object is determined;

[0056] Determine the damage risk probability based on the ratio of the historical number of damages to the historical number of treatments of the same fabric type under the cutting treatment type;

[0057] Use the damage risk probability to determine whether the treatment location is a cutting risk location.

[0058] It should be noted that when the damage risk probability is greater than the preset probability threshold, it is determined that the treatment location belongs to the cutting risk location.

[0059] Specifically, when there is no cutting risk location, continuous cutting treatment is performed using the cutting treatment program and the cutting treatment types corresponding to different treatment locations.

[0060] In another possible embodiment, the method for determining the cutting risk location is as follows:

[0061] Based on the historical damage data corresponding to the cutting treatment type of the treatment location, determine the historical number of damages under the same fabric type of the fabric treatment object;

[0062] Based on the similarity between the cutting treatment data corresponding to different historical numbers of damages and the cutting treatment data of the cutting treatment location, determine the similar number of damages;

[0063] Use the maximum value of the damage depth of the similar number of damages to determine whether the treatment location is a cutting risk location.

[0064] Furthermore, the similar number of damages is the historical number of damages whose similarity degree with the cutting treatment data of the cutting treatment location meets the requirements.

[0065] It should be noted that the similarity degree is determined according to the difference between the preset value and the deviation rate of the treatment duration.

[0066] Optionally, the method for determining the cutting risk location is as follows:

[0067] Based on the historical damage data corresponding to the cutting treatment type of the treatment location, if it is determined that there is no historical number of damages under the same fabric type of the fabric treatment object, then it is determined that the treatment location does not belong to the cutting risk location;

[0068] When there is a historical number of damages under the same fabric type of the fabric treatment object:

[0069] When the historical number of damages or the maximum value of the damage depth of different historical numbers of damages does not meet the requirements, it is determined that the treatment location belongs to the cutting risk location;

[0070] When both the historical number of damages and the maximum value of the damage depths corresponding to different historical numbers of damages meet the requirements:

[0071] Based on the similarity between the cutting process data corresponding to different numbers of processes and the cutting process data at the cutting process position, determine the similarity degree between different numbers of processes and the cutting process position. When there is no historical number of damages with a similarity degree meeting the requirements, it is determined that the process position does not belong to the cutting risk position;

[0072] When there is a historical number of damages with a similarity degree meeting the requirements: Take the historical number of damages with a similarity degree meeting the requirements as the similar damage number. When any one of the similar damage number and the maximum value of the damage depth of the similar damage number does not meet the requirements, it is determined that the process position belongs to the cutting risk position;

[0073] When both the similar damage number and the maximum value of the damage depth of the similar damage number meet the requirements:

[0074] Obtain the proportion of the similar damage number among the numbers of processes with a similarity degree meeting the requirements, and combine the damage depths of different similar damage numbers to determine the similar damage outlier. When the similar damage outlier does not meet the requirements, it is determined that the process position belongs to the cutting risk position;

[0075] When the similar damage outlier meets the requirements:

[0076] Determine the damage reference coefficients for different similarity degree intervals based on the proportions of the historical numbers of damages in different similarity degree intervals, and combine the preset weight coefficients corresponding to different similarity degree intervals to determine the damage anomaly probability, and use the damage anomaly probability to determine whether the process position belongs to the cutting risk position.

[0077] S2 When it is determined that the distribution dispersion degree of the cutting risk positions of the fabric processing object meets the requirements based on the distribution data of different cutting risk positions, proceed to the next step;

[0078] Further, as Figure 3 shown, determining that the distribution dispersion degree of the cutting risk positions of the fabric processing object meets the requirements specifically includes:

[0079] Based on the distribution data of the cutting risk positions of the fabric cutting object, determine the distances between different cutting risk positions;

[0080] Determine the distribution dispersion value based on the preset dispersion coefficient corresponding to the average value of the distances between the cutting risk positions;

[0081] Determine the risk weight coefficients of different cutting risk positions based on the proportion of the processing duration of the cutting risk positions in the duration of the fabric cutting object, determine the distribution discrete risk value according to the product of the average value of the risk weight coefficients of different cutting risk positions and the distribution discrete value, and use the distribution discrete risk value to determine whether the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements.

[0082] Further, when the distribution discrete risk value is not within the preset discrete risk value interval, it is determined that the distribution discreteness degree of the cutting risk positions of the fabric processing object does not meet the requirements.

[0083] It should be noted that determining that the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements specifically includes:

[0084] Determine the distances between different cutting risk positions based on the distribution data of the cutting risk positions of the fabric cutting object;

[0085] Based on the average value of the distances between the cutting risk positions and the number of the cutting risk positions, determine whether the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements.

[0086] It can be understood that when the average value of the distances between the cutting risk positions is greater than the preset distance threshold and the number of the cutting risk positions is not within the preset risk position number interval, it is determined that the distribution discreteness degree of the cutting risk positions of the fabric processing object does not meet the requirements.

[0087] Specifically, when the distribution discreteness degree of the cutting risk positions of the fabric processing object does not meet the requirements, first perform the cutting process of removing the cutting risk positions, and then perform the unified cutting process of all the cutting risk positions.

[0088] Optionally, determining that the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements specifically includes:

[0089] S21 Determine the distances between different cutting risk positions based on the distribution data of the cutting risk positions of the fabric cutting object, and use the distances between different cutting risk positions and other cutting risk positions to determine the distribution discrete coefficients of different cutting risk positions;

[0090] S22 Determine the risk weight coefficients of different cutting risk positions based on the proportion of the processing duration of the cutting risk positions, and determine the corrected discrete coefficients of different cutting risk positions according to the product of the risk weight coefficients of different cutting risk positions and the distribution discrete coefficients;

[0091] S23 determines the distribution discrete risk value based on the sum of the corrected discrete coefficients of different cutting risk positions, and uses the distribution discrete risk value to determine whether the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements.

[0092] It should be noted that the distribution discrete coefficient of the cutting risk positions is determined according to the preset discrete coefficient corresponding to the average value of the distances between the cutting risk positions and other cutting risk positions.

[0093] Optionally, the above step S21 includes the following content:

[0094] S211 If, based on the distribution data of the cutting risk positions of the fabric cutting object, it is determined that the number of the cutting risk positions does not meet the requirements, then it is determined that the distribution discreteness degree of the cutting risk positions of the fabric processing object does not meet the requirements. When the number of the cutting risk positions meets the requirements, proceed to step S212;

[0095] S212 When the number of the cutting risk positions is less than the preset number of risk positions, proceed to step S213. When the number of the cutting risk positions is not less than the preset number of risk positions, proceed to step S214;

[0096] S213 If the distances between different cutting risk positions are all less than the preset interval distance threshold, then it is determined that the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements. When there are cutting risk positions with distances not less than the preset interval distance threshold, proceed to step S214;

[0097] S214 Use the distances between different cutting risk positions and other cutting risk positions to determine the distribution discrete coefficients of different cutting risk positions. When there are cutting risk positions with distribution discrete coefficients not meeting the requirements, proceed to step S215. When there are no cutting risk positions with distribution discrete coefficients not meeting the requirements, proceed to step S22;

[0098] S215 If the number of cutting risk positions with distribution discrete coefficients not meeting the requirements is greater than the set value of the position number, then it is determined that the distribution discreteness degree of the cutting risk positions of the fabric processing object does not meet the requirements. When the number of cutting risk positions with distribution discrete coefficients not meeting the requirements is not greater than the set value of the position number, proceed to step S22.

[0099] Optionally, the above step S22 includes the following content:

[0100] S221 If, based on the processing duration of the cutting risk positions, it is determined that there are cutting risk positions with processing durations greater than the preset processing duration, proceed to step S222. When there are no cutting risk positions with processing durations greater than the preset processing duration, proceed to step S223;

[0101] S222 takes the cutting risk positions with processing duration greater than the preset processing duration as the screened risk positions, determines the screening dispersion coefficient based on the number of the screened risk positions and the interval distance between different screened risk positions. When the screening dispersion coefficient does not meet the requirements, it is determined that the distribution dispersion degree of the cutting risk positions of the fabric processing object does not meet the requirements. When the screening dispersion coefficient meets the requirements, it proceeds to step S223;

[0102] S223 determines the risk weight coefficients of different cutting risk positions based on the proportion of the processing duration of the cutting risk positions, and determines the corrected dispersion coefficients of different cutting risk positions according to the product of the risk weight coefficients of different cutting risk positions and the distribution dispersion coefficient. When the number of cutting risk positions with corrected dispersion coefficients not meeting the requirements is greater than the set value of the position number, it is determined that the distribution dispersion degree of the cutting risk positions of the fabric processing object does not meet the requirements. When the number of cutting risk positions with corrected dispersion coefficients not meeting the requirements is not greater than the set value of the position number, it proceeds to step S232.

[0103] S3 determines the power switching types of the laser devices of the embroidery machines at different cutting risk positions according to the cutting processing program, and determines the switching abnormality coefficients of different cutting risk positions by using the switching abnormality data corresponding to the power switching types;

[0104] Further, the power switching types are classified according to the powers of the laser devices before and after the switching.

[0105] It can be understood that the switching abnormality data includes the number of switching abnormalities, and the number of switching abnormalities includes the number of switching failures and the number of switching timeouts.

[0106] Specifically, as Figure 4 shown, the method for determining the switching abnormality coefficient of the cutting risk position is:

[0107] Based on the switching abnormality data of the power switching type of the cutting risk position, determine the number of switching abnormalities, and obtain the historical number of switches of the power switching type;

[0108] Determine the switching abnormality coefficient of the cutting risk position according to the ratio of the number of switching abnormalities to the historical number of switches.

[0109] S4 determines the cutting control strategy of the laser device of the embroidery machine based on the distribution data of the cutting risk positions and the switching abnormality coefficients of the cutting risk positions.

[0110] Further, as Figure 5 shown, the method for determining the cutting control strategy of the laser device of the embroidery machine is:

[0111] Based on the distribution data of the cutting risk positions, determine the number of power switching processes of the laser device of the embroidery machine;

[0112] Based on the product of the switching abnormality coefficient of different switching risk positions and the preset proportional factor, determine the switching abnormality weight coefficient of different switching risk positions;

[0113] Determine the switching process abnormality coefficient according to the sum of the switching abnormality weight coefficients of different numbers of power switching processes, and use the switching process abnormality coefficient to determine the cutting control strategy of the laser device of the embroidery machine.

[0114] It can be understood that using the switching process abnormality coefficient to determine the cutting control strategy of the laser device of the embroidery machine specifically includes:

[0115] When the switching process abnormality coefficient is greater than the preset switching abnormality coefficient threshold, first perform the cutting process for removing the cutting risk positions, and then perform the unified cutting process for all the cutting risk positions;

[0116] When the switching process abnormality coefficient is not greater than the preset switching abnormality coefficient threshold, perform continuous cutting using the cutting process and the cutting process types corresponding to different processing positions.

[0117] In another possible embodiment, the method for determining the cutting control strategy of the laser device of the embroidery machine is:

[0118] Based on the distribution data of the cutting risk positions, determine the number of power switching processes of the laser device of the embroidery machine. When the number of power switching processes of the laser device of the embroidery machine does not meet the requirements, first perform the cutting process for removing the cutting risk positions, and then perform the unified cutting process for all the cutting risk positions;

[0119] When the number of power switching processes of the laser device of the embroidery machine meets the requirements:

[0120] Based on the switching abnormality coefficients of different switching processes, when it is determined that there is a switching process number with a switching abnormality coefficient greater than the preset switching abnormality coefficient threshold, first perform the cutting process for removing the cutting risk positions, and then perform the unified cutting process for all the cutting risk positions;

[0121] When there is no switching process number with a switching abnormality coefficient greater than the preset abnormality coefficient threshold:

[0122] When the number of switching processes is within a preset process number range and the switching anomaly coefficients for different numbers of switching processes are all within a preset anomaly coefficient range: continuous cutting processing is performed using a cutting processing program and cutting processing types corresponding to different processing positions;

[0123] When the number of switching processes is not within the preset process number range or the switching anomaly coefficients for different numbers of switching processes are not within the preset anomaly coefficient range:

[0124] When the number of switching processes with a switching anomaly coefficient not within the preset anomaly coefficient range is greater than a preset switching process number threshold, first perform cutting processing to remove the cutting risk positions, and then perform unified cutting processing on all the cutting risk positions;

[0125] When the number of switching processes with a switching anomaly coefficient not within the preset anomaly coefficient range is not greater than the preset switching process number threshold:

[0126] Based on the product of the switching anomaly coefficients of different switching risk positions and a preset proportionality factor, determine the switching anomaly weight coefficients of different switching risk positions;

[0127] Determine the switching processing anomaly coefficient based on the sum of the switching anomaly weight coefficients of different power switching process numbers, and use the switching processing anomaly coefficient to determine the cutting control strategy of the laser device of the embroidery machine.

[0128] Embodiment 2

[0129] In a second aspect, as Figure 6 shown, the present invention provides a laser cutting control system, adopting the above-mentioned laser cutting control method, specifically including:

[0130] A risk position identification module, a distribution discrete evaluation module, and a switching strategy determination module;

[0131] Among them, the risk position identification module is responsible for determining the cutting risk positions of the fabric processing object;

[0132] The distribution discrete evaluation module is responsible for determining whether the distribution discrete degree of the cutting risk positions of the fabric processing object meets the requirements;

[0133] The switching strategy determination module is responsible for determining the cutting control strategy of the laser device of the embroidery machine.

[0134] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the description of the method embodiments.

[0135] The specific embodiments of this specification are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0136] The above description is only for one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various changes and modifications can be made to one or more embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A laser cutting control method, characterized in that, Specifically, it includes: Based on the cutting treatment type of the fabric treatment object of the embroidery machine, determine the historical damage data of the positioning auxiliary materials under different cutting treatment types, and when using the historical damage data to determine the cutting risk positions of the fabric treatment object, obtain the distribution data of different cutting risk positions; Based on the distribution data of different cutting risk positions, when it is determined that the distribution dispersion degree of the cutting risk positions of the fabric treatment object meets the requirements, proceed to the next step; According to the cutting treatment program, determine the power switching type of the laser device of the embroidery machine at different cutting risk positions, and use the switching abnormal data corresponding to the power switching type to determine the switching abnormal coefficient of different cutting risk positions; Based on the distribution data of the cutting risk positions and the switching abnormal coefficient of the cutting risk positions, determine the cutting control strategy of the laser device of the embroidery machine; The method for determining the cutting risk positions is as follows: Based on the historical damage data corresponding to the cutting treatment type of the processing position, determine the historical damage times under the same fabric type of the fabric treatment object; Based on the ratio of the historical damage times to the historical processing times of the same fabric type under the cutting treatment type, determine the damage risk probability; Use the damage risk probability to determine whether the processing position is a cutting risk position.

2. The laser cutting control method according to claim 1, wherein The cutting treatment type is divided according to the cutting treatment depth of different positions.

3. The laser cutting control method according to claim 1, characterized in that The historical damage data includes the historical damage times of the positioning auxiliary materials under the cutting treatment type and the damage depths of different historical damage times.

4. The laser cutting control method according to claim 1, wherein When the damage risk probability is greater than the preset probability threshold, it is determined that the processing position belongs to the cutting risk position.

5. The laser cutting control method according to claim 1, wherein When there is no cutting risk position, continuous cutting treatment is performed using the cutting treatment program and the cutting treatment types corresponding to different processing positions.

6. The laser cutting control method according to claim 1, wherein Determining that the distribution dispersion degree of the cutting risk positions of the fabric treatment object meets the requirements specifically includes: Based on the distribution data of the cutting risk positions of the fabric cutting object, determine the distances between different cutting risk positions; Based on the average value of the distances between the cutting risk positions and the number of the cutting risk positions, determine whether the distribution dispersion degree of the cutting risk positions of the fabric treatment object meets the requirements.

7. The laser cutting control method according to claim 1, characterized in that, The method for determining the cutting control strategy of the laser device of the embroidery machine is as follows: Based on the distribution data of the cutting risk positions, determine the number of power switching processes of the laser device of the embroidery machine; Based on the product of the switching abnormal coefficient of different switching risk positions and the preset proportional factor, determine the switching abnormal weight coefficient of different switching risk positions; Determine the switching process abnormal coefficient according to the sum of the switching abnormal weight coefficients of different power switching process numbers, and use the switching process abnormal coefficient to determine the cutting control strategy of the laser device of the embroidery machine.

8. The laser cutting control method according to claim 7, characterized in that, Using the switching process abnormal coefficient to determine the cutting control strategy of the laser device of the embroidery machine specifically includes: When the switching processing exception coefficient is greater than the preset switching exception coefficient threshold, first perform the cutting process of removing the cutting risk positions, and then perform the unified cutting process of all the cutting risk positions; When the switching processing exception coefficient is not greater than the preset switching exception coefficient threshold, use the cutting processing program and the cutting processing types corresponding to different processing positions to perform continuous cutting processing.

9. A laser cutting control system, adopting a laser cutting control method according to any one of claims 1-8, characterized in that, Specifically, it includes: Risk position identification module, distribution discrete evaluation module, switching strategy determination module; Among them, the risk position identification module is responsible for determining the cutting risk positions of the fabric processing object; The distribution discrete evaluation module is responsible for determining whether the distribution discreteness degree of the cutting risk positions of the fabric processing object meets the requirements; The switching strategy determination module is responsible for determining the cutting control strategy of the laser device of the embroidery machine.

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