Laser cutting control system and method

Abstract

The invention provides a laser cutting control method and system, and belongs to the technical field of laser control, and the method specifically comprises the steps that based on distribution data of different cutting risk positions, when it is determined that the distribution discrete degree of the cutting risk positions of a cloth processing object meets the requirement, according to a cutting processing program, the cutting risk positions of the cloth processing object are determined; power switching types of laser devices of the embroidery machine at different cutting risk positions are determined, switching abnormal coefficients of the different cutting risk positions are determined by using switching abnormal data corresponding to the power switching types, and the cutting risk positions are determined on the basis of the distribution data of the cutting risk positions and the switching abnormal coefficients of the cutting risk positions. And the cutting control strategy of the laser device of the embroidery machine is determined, so that the probability of damage to the positioning auxiliary material is reduced.

Description

Technical Field

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

[0002] Laser cutting devices have been widely used in embroidery machines. Through the layering method of the laser control system, the fabric of the same color can be "embroidered" with different shades of the base color of the fabric, with transitional colors with a sense of hierarchy. Specifically, the invention patent application CN202211026064.X "Dual laser device, embroidery machine, control method, storage medium and electronic equipment" and CN202210675150.7 "Embroidery machine and smoke exhaust method thereof" both provide devices that use laser cutting devices to perform embroidery processing on embroidery machines. However, the above devices all have the following technical defects: During the laser cutting control process of the embroidery machine, once the output power of the laser cannot be effectively controlled, it may cause damage to the positioning auxiliary materials under the fabric. Therefore, how to achieve power control of the laser during the cutting process to avoid damage to the positioning auxiliary materials has become a technical problem that needs to be solved urgently.

[0003] In response to the above technical problems, the present application specifically provides a laser cutting control system and method. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides a laser cutting control method, which specifically includes: S1 determines historical damage data of positioning auxiliary materials under different cutting processing types based on the cutting processing type of the fabric processing object of the embroidery machine, and obtains distribution data of different cutting risk positions when determining that the fabric processing object has a cutting risk position using the historical damage data; S2: when the distribution discreteness of the cutting risk position of the cloth processing object meets the requirement based on the distribution data of different cutting risk positions, proceed to the next step; S3 determines the power switching type of the laser device of the embroidery machine at different cutting risk positions according to the cutting processing program, and determines the switching abnormality coefficients of the different cutting risk positions using the switching abnormality data corresponding to the power switching type; S4 determines the cutting control strategy of the laser device of the embroidery machine based on the distribution data of the cutting risk position and the switching abnormality coefficient of the cutting risk position.

[0005] The beneficial effects of the present invention are: Based on the distribution data of different cutting risk positions, it is determined whether the distribution discreteness of the cutting risk positions of the fabric processing object meets the requirements, thereby realizing the determination of the distribution discreteness of the cutting risk positions from the number of cutting risk positions and the distances between different cutting risk positions, avoiding the influence of frequent power switching on the service life of the laser device caused by the use of a fixed cutting processing program for fabric processing objects with a high degree of distribution discreteness, and also avoiding the problem of frequent power switching leading to the inability to accurately achieve reliable control of the output power of the laser device, thereby improving the reliability and safety of the cutting process and reducing the probability of damage to the positioning auxiliary materials to a certain extent.

[0006] The cutting control strategy of the laser device of the embroidery machine is determined based on the distribution data of the cutting risk position and the switching abnormality coefficient of the cutting risk position. Not only the difference in the number of power switching processing times caused by the difference in distribution data is taken into account, but also the difference in the probability of switching abnormality occurring during the switching process due to the difference in power switching at different cutting risk positions is comprehensively considered. This not only ensures the safety and reliability of the fabric cutting process, but also realizes reliable and accurate control of the output power of the laser device.

[0007] A further technical solution is that the cutting processing types are divided according to the cutting processing depths at different positions.

[0008] A further technical solution is that the historical damage data includes the number of historical damages to the positioning auxiliary material under the cutting processing type and the damage depths at different historical damage times.

[0009] A further technical solution is that the method for determining the cutting risk position is: Determining the number of historical destructions of the same cloth type of the cloth processing object based on the historical destruction data corresponding to the cutting processing type corresponding to the processing position; Determining a probability of damage risk based on a ratio of the historical damage count to the historical processing count of the same fabric type under the cutting processing type; The damage risk probability is used to determine whether the processing position is a cutting risk position.

[0010] A further technical solution is that when the damage risk probability is greater than a preset probability threshold, it is determined that the processing position belongs to a cutting risk position.

[0011] 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.

[0012] A further technical solution is that the method for determining the cutting control strategy of the laser device of the embroidery machine is: Determining the number of power switching processes of the laser device of the embroidery machine based on the distribution data of the cutting risk position; Determining switching anomaly weight coefficients of different switching risk positions based on the product of the switching anomaly coefficients of different switching risk positions and a preset proportional factor; The switching process abnormality coefficient is determined according to the sum of the switching abnormality weight coefficients of different power switching process times, and the cutting control strategy of the laser device of the embroidery machine is determined by using the switching process abnormality coefficient.

[0013] A further technical solution is to use the switching processing abnormality coefficient to determine the cutting control strategy of the laser device of the embroidery machine, which specifically includes: When the switching process abnormality coefficient is greater than a preset switching process abnormality coefficient threshold, a cutting process is first performed to remove the cutting risk position, and then a unified cutting process is performed on all cutting risk positions; When the switching process abnormality coefficient is not greater than a preset switching process abnormality coefficient threshold, continuous cutting processing is performed using the cutting processing program and the cutting processing types corresponding to different processing positions.

[0014] In a second aspect, the present invention provides a laser cutting control system, which adopts the above-mentioned laser cutting control method, specifically comprising: Risk location identification module, distribution discrete assessment module, switching strategy determination module; The risk position identification module is responsible for determining the cutting risk position of the cloth processing object; The distribution discreteness evaluation module is responsible for determining whether the distribution discreteness of the cutting risk position of the cloth 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.

[0015] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0018] Figure 1is a flow chart of a laser cutting control method; Figure 2 is a flow chart of a method for determining a cutting risk location; Figure 3 It is a flow chart for determining whether the distribution discreteness of the cutting risk position of the cloth processing object meets the requirements; Figure 4 is a flow chart of a method for determining a switching anomaly coefficient of a cutting risk position; Figure 5 It is a flow chart of a method for determining a cutting control strategy of a laser device of an embroidery machine; Figure 6 It is a framework diagram of a laser cutting control system. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0020] In the present application, the distribution data of cutting risk positions is used to determine the number of power switching times of the laser device during the processing process. According to the number of power switching times and 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 performed in sequence according to the cutting process procedure, or after the cutting of other positions is completed, the unified cutting process of the cutting risk positions is performed to ensure the reliability of the power control of the laser device.

[0021] The ratio of the historical damage times to the historical processing times of the same fabric type under the cutting processing type determines the damage risk probability. When the damage risk probability is greater than 0.3, the processing position is determined to be a cutting risk position.

[0022] When the distances between different cutting risk positions are all less than the preset distances, it is determined that the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirements.

[0023] Based on the switching abnormality data of the power switching type at the cutting risk position, the number of switching abnormalities is determined, the historical switching number of the power switching type is obtained, and the switching abnormality coefficient of the cutting risk position is determined according to the ratio of the switching abnormality number to the historical switching number.

[0024] Based on the distribution data of the cutting risk position, the power switching processing times of the laser device of the embroidery machine are determined, and the switching abnormality weight coefficients of different switching risk positions are determined based on the product of the switching abnormality coefficients of different switching risk positions and the preset proportional factor. The switching processing abnormality coefficient is determined according to the sum of the switching abnormality weight coefficients of different power switching processing times, and the cutting control strategy of the laser device of the embroidery machine is determined using the switching processing abnormality coefficient.

[0025] Example 1 like Figure 1 As shown, the present application provides a first aspect, the present application provides a first aspect, the present application provides a laser cutting control method, specifically including: S1 determines historical damage data of positioning auxiliary materials under different cutting processing types based on the cutting processing type of the fabric processing object of the embroidery machine, and obtains distribution data of different cutting risk positions when determining that the fabric processing object has a cutting risk position using the historical damage data; Furthermore, the cutting processing types are divided according to the cutting processing depths at different positions.

[0026] It should be noted that the historical damage data includes the number of historical damages to the positioning auxiliary material under the cutting processing type and the damage depths at different historical damage times.

[0027] It is understandable that if Figure 2 As shown, the method for determining the cutting risk position is: Determining the number of historical destructions of the same cloth type of the cloth processing object based on the historical destruction data corresponding to the cutting processing type corresponding to the processing position; Determining a probability of damage risk based on a ratio of the historical damage count to the historical processing count of the same fabric type under the cutting processing type; The damage risk probability is used to determine whether the processing position is a cutting risk position.

[0028] It should be noted that when the damage risk probability is greater than a preset probability threshold, it is determined that the processing position is a cutting risk position.

[0029] Specifically, when there is no cutting risk position, continuous cutting processing is performed using the cutting processing program and the cutting processing types corresponding to different processing positions.

[0030] In another possible embodiment, the method for determining the cutting risk position is: Determining the number of historical destructions of the same cloth type of the cloth processing object based on the historical destruction data corresponding to the cutting processing type corresponding to the processing position; Determining similar destruction times based on similarities between cutting process data corresponding to different historical destruction times and cutting process data at the cutting process position; Whether the processing position is a cutting risk position is determined by using the maximum value of the destruction depths of the similar destruction times.

[0031] Furthermore, the similar destruction times are historical destruction times whose similarity with the cutting process data of the cutting process position meets the requirements.

[0032] It should also be noted that the similarity is determined based on the difference between the preset value and the deviation rate of the processing duration.

[0033] Optionally, the method for determining the cutting risk position is: When it is determined that there is no historical damage number under the same fabric type of the fabric processing object based on the historical damage data corresponding to the cutting processing type corresponding to the processing position, it is determined that the processing position does not belong to the cutting risk position; When there is a historical destruction count under the same cloth type of the cloth processing object: When the maximum value of the historical destruction times or the destruction depths of different historical destruction times does not meet the requirements, it is determined that the processing position belongs to a cutting risk position; When the maximum values ​​of the historical destruction times and the destruction depths of different historical destruction times meet the requirements: Determine the similarity between different processing times and the cutting processing position based on the similarity between the cutting processing data corresponding to different processing times and the cutting processing data of the cutting processing position; when there is no historical destruction times that meets the requirement of similarity, determine that the processing position does not belong to the cutting risk position; When there are historical destruction times that meet the requirements of similarity: the historical destruction times that meet the requirements of similarity are taken as similar destruction times, and when any of the maximum values ​​of the similar destruction times and the destruction depths of the similar destruction times do not meet the requirements, it is determined that the processing position belongs to the cutting risk position; When the maximum values ​​of the similar destruction times and the destruction depths of similar destruction times meet the requirements: Obtaining the proportion of the number of similar destruction times in the number of processing times whose similarity degree meets the requirements, and determining the similar destruction abnormal value in combination with the destruction depths of different similar destruction times; when the similar destruction abnormal value does not meet the requirements, determining that the processing position belongs to the cutting risk position; When the similarity destruction outlier value meets the requirements: The destruction reference coefficients of different similarity intervals are determined by the proportion of historical destruction times in different similarity intervals, and the destruction anomaly probability is determined in combination with the preset weight coefficients corresponding to the different similarity intervals, and the destruction anomaly probability is used to determine whether the processing position belongs to a cutting risk position.

[0034] S2: when the distribution discreteness of the cutting risk position of the cloth processing object meets the requirement based on the distribution data of different cutting risk positions, proceed to the next step; Further, such as Figure 3 As shown, determining whether the distribution discreteness of the cutting risk position of the cloth processing object meets the requirements specifically includes: Determining distances between different cutting risk positions based on the distribution data of the cutting risk positions of the cloth cutting object; Determining a distribution discrete value based on a preset discrete coefficient corresponding to an average value of the distances between the cutting risk positions; The risk weight coefficients of different cutting risk positions are determined according to the proportion of the processing time of the cutting risk position to the time of the cloth cutting object, the distribution discrete risk value is determined according to the product of the average value of the risk weight coefficients of different cutting risk positions and the distribution discrete value, and the distribution discrete risk value is used to determine whether the distribution discrete degree of the cutting risk position of the cloth processing object meets the requirements.

[0035] Further, when the distribution discrete risk value is not within a preset discrete risk value interval, it is determined that the distribution discrete degree of the cutting risk position of the cloth processing object does not meet the requirement.

[0036] It should be noted that determining that the distribution discreteness of the cutting risk position of the cloth processing object meets the requirements specifically includes: Determining distances between different cutting risk positions based on the distribution data of the cutting risk positions of the cloth cutting object; Based on the average value of the distances between the cutting risk positions and the number of the cutting risk positions, it is determined whether the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirement.

[0037] It can be understood that when the average value of the distances between the cutting risk positions is greater than a preset distance threshold and the number of the cutting risk positions is not within a preset risk position number interval, it is determined that the distribution discreteness of the cutting risk positions of the cloth processing object does not meet the requirements.

[0038] Specifically, when the distribution discreteness of the cutting risk positions of the cloth processing object does not meet the requirement, the cutting process of removing the cutting risk positions is first performed, and then all the cutting risk positions are uniformly cut.

[0039] Optionally, determining whether the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirement specifically includes: S21, determining the distances between different cutting risk positions based on the distribution data of the cutting risk positions of the cloth cutting object, and determining the distribution dispersion coefficients of different cutting risk positions based on the distances between different cutting risk positions and other cutting risk positions; S22: determining risk weight coefficients of different cutting risk positions based on the processing time ratio of the cutting risk positions, and determining modified 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 coefficient; S23 determines a distribution discrete risk value according to the sum of the corrected discrete coefficients of different cutting risk positions, and uses the distribution discrete risk value to determine whether the distribution discrete degree of the cutting risk position of the cloth processing object meets the requirement.

[0040] It should be noted that the distribution dispersion coefficient of the cutting risk position is determined according to a preset dispersion coefficient corresponding to the average value of the distance between the cutting risk position and other cutting risk positions.

[0041] Optionally, the above step S21 includes the following contents: S211: when it is determined based on the distribution data of the cutting risk positions of the cloth cutting object that the number of the cutting risk positions does not meet the requirement, it is determined that the distribution discreteness of the cutting risk positions of the cloth processing object does not meet the requirement; when the number of the cutting risk positions meets the requirement, the process proceeds to step S212; S212: When the number of the cutting risk positions is less than the preset number of risk positions, the process proceeds to step S213; when the number of the cutting risk positions is not less than the preset number of risk positions, the process proceeds to step S214; S213: When the distances between different cutting risk positions are all less than the preset interval distance threshold, it is determined that the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirement; when there are cutting risk positions whose distances are not less than the preset interval distance threshold, the process proceeds to step S214; S214 determines the distribution dispersion coefficients of different cutting risk positions by using the distances between different cutting risk positions and other cutting risk positions. When there is a cutting risk position whose distribution dispersion coefficient does not meet the requirements, the process proceeds to step S215. When there is no cutting risk position whose distribution dispersion coefficient does not meet the requirements, the process proceeds to step S22. S215: When the number of cutting risk positions whose distribution dispersion coefficient does not meet the requirements is greater than the position quantity setting value, it is determined that the distribution dispersion degree of the cutting risk positions of the cloth processing object does not meet the requirements; when the number of cutting risk positions whose distribution dispersion coefficient does not meet the requirements is not greater than the position quantity setting value, the process proceeds to step S22.

[0042] Optionally, the above step S22 includes the following contents: S221: When it is determined based on the processing time of the cutting risk position that there is a cutting risk position whose processing time is longer than the preset processing time, the process goes to step S222; when there is no cutting risk position whose processing time is longer than the preset processing time, the process goes to step S223; S222: taking the cutting risk position whose processing time is longer than the preset processing time as the screening risk position, determining the screening dispersion coefficient based on the number of the screening risk positions and the interval distances between different screening risk positions; when the screening dispersion coefficient does not meet the requirement, determining that the distribution dispersion degree of the cutting risk position of the fabric processing object does not meet the requirement; when the screening dispersion coefficient meets the requirement, proceeding to step S223; S223 determines the risk weight coefficients of different cutting risk positions based on the proportion of processing time of the cutting risk positions, and determines 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. When the number of cutting risk positions whose corrected discrete coefficients do not meet the requirements is greater than the position quantity setting value, it is determined that the distribution discrete degree of the cutting risk positions of the fabric processing object does not meet the requirements. When the number of cutting risk positions whose corrected discrete coefficients do not meet the requirements is not greater than the position quantity setting value, proceed to step S232.

[0043] S3 determines the power switching type of the laser device of the embroidery machine at different cutting risk positions according to the cutting processing program, and determines the switching abnormality coefficients of the different cutting risk positions using the switching abnormality data corresponding to the power switching type; Furthermore, the power switching type is divided according to the power of the laser device before and after switching.

[0044] It can be understood that the switching abnormality data includes the number of switching abnormalities, wherein the number of switching abnormalities includes the number of switching failures and the number of switching timeouts.

[0045] Specifically, Figure 4 As shown, the method for determining the switching abnormality coefficient of the cutting risk position is: Based on the switching abnormality data of the power switching type at the cutting risk position, determining the number of switching abnormalities, and obtaining the historical switching number of the power switching type; The switching abnormality coefficient of the cutting risk position is determined according to the ratio of the switching abnormality number to the historical switching number.

[0046] S4 determines the cutting control strategy of the laser device of the embroidery machine based on the distribution data of the cutting risk position and the switching abnormality coefficient of the cutting risk position.

[0047] Further, such as Figure 5 As shown, the method for determining the cutting control strategy of the laser device of the embroidery machine is: Determining the number of power switching processes of the laser device of the embroidery machine based on the distribution data of the cutting risk position; Determining switching anomaly weight coefficients of different switching risk positions based on the product of the switching anomaly coefficients of different switching risk positions and a preset proportional factor; The switching process abnormality coefficient is determined according to the sum of the switching abnormality weight coefficients of different power switching process times, and the cutting control strategy of the laser device of the embroidery machine is determined by using the switching process abnormality coefficient.

[0048] It can be understood that the cutting control strategy of the laser device of the embroidery machine is determined by using the switching processing abnormality coefficient, which specifically includes: When the switching process abnormality coefficient is greater than a preset switching process abnormality coefficient threshold, a cutting process is first performed to remove the cutting risk position, and then a unified cutting process is performed on all cutting risk positions; When the switching process abnormality coefficient is not greater than a preset switching process abnormality coefficient threshold, continuous cutting processing is performed using the cutting processing program and the cutting processing types corresponding to different processing positions.

[0049] In another possible embodiment, the method for determining the cutting control strategy of the laser device of the embroidery machine is: Based on the distribution data of the cutting risk positions, the number of power switching processing times of the laser device of the embroidery machine is determined. When the number of power switching processing times of the laser device of the embroidery machine does not meet the requirement, the cutting processing of removing the cutting risk positions is first performed, and then the uniform cutting processing of all the cutting risk positions is performed; When the power switching processing times of the laser device of the embroidery machine meet the requirements: Based on the switching abnormality coefficients of different switching processing times, when it is determined that there is a switching processing number with a switching abnormality coefficient greater than a preset switching abnormality coefficient threshold, a cutting process is first performed to remove the cutting risk position, and then a unified cutting process is performed on all cutting risk positions; When there is no switching process with a switching abnormality coefficient greater than the preset abnormality coefficient threshold: When the switching processing times are within the preset processing times interval and the switching abnormality coefficients of different switching processing times are all within the preset abnormality coefficient interval: then a continuous cutting process is performed using the cutting process program and the cutting process types corresponding to different processing positions; When the switching processing times are not within the preset processing times range or the switching abnormality coefficients of different switching processing times are not within the preset abnormality coefficient range: When the number of switching processing times for which the switching abnormality coefficient is not within the preset abnormality coefficient interval is greater than the preset switching processing times threshold, a cutting process is first performed to remove the cutting risk position, and then a unified cutting process is performed for all cutting risk positions; When the switching abnormality coefficient is not within the preset abnormality coefficient range and the number of switching processing times is not greater than the preset switching processing times threshold: Determining switching anomaly weight coefficients of different switching risk positions based on the product of the switching anomaly coefficients of different switching risk positions and a preset proportional factor; The switching process abnormality coefficient is determined according to the sum of the switching abnormality weight coefficients of different power switching process times, and the cutting control strategy of the laser device of the embroidery machine is determined by using the switching process abnormality coefficient.

[0050] Example 2 Second, as Figure 6 As shown, the present invention provides a laser cutting control system, which adopts the above-mentioned laser cutting control method, specifically comprising: Risk location identification module, distribution discrete assessment module, switching strategy determination module; The risk position identification module is responsible for determining the cutting risk position of the cloth processing object; The distribution discreteness evaluation module is responsible for determining whether the distribution discreteness of the cutting risk position of the cloth 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.

[0051] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0052] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A laser cutting control method, characterized in that: Specifically include: Based on the cutting processing type of the fabric processing object of the embroidery machine, historical damage data of the positioning auxiliary material under different cutting processing types is determined, and when the cutting risk position of the fabric processing object is determined by using the historical damage data, distribution data of different cutting risk positions are obtained; When it is determined based on the distribution data of different cutting risk positions that the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirements, proceed to the next step; 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 abnormality coefficients of the different cutting risk positions are determined by using the switching abnormality data corresponding to the power switching type; Based on the distribution data of the cutting risk position and the switching abnormality coefficient of the cutting risk position, a cutting control strategy of the laser device of the embroidery machine is determined.

2. The laser cutting control method according to claim 1, characterized in that: The cutting process types are divided according to the cutting process depths at different locations.

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 material under the cutting processing type and the damage depths at different historical damage times.

4. The laser cutting control method according to claim 1, characterized in that: The method for determining the cutting risk position is: Determining the number of historical destructions of the same cloth type of the cloth processing object based on the historical destruction data corresponding to the cutting processing type corresponding to the processing position; Determining a probability of damage risk based on a ratio of the historical damage count to the historical processing count of the same fabric type under the cutting processing type; The damage risk probability is used to determine whether the processing position is a cutting risk position.

5. The laser cutting control method according to claim 4, characterized in that: When the damage risk probability is greater than a preset probability threshold, it is determined that the processing position belongs to a cutting risk position.

6. The laser cutting control method according to claim 1, characterized in that: When there is no cutting risk position, continuous cutting processing is performed using the cutting processing program and the cutting processing types corresponding to different processing positions.

7. The laser cutting control method according to claim 1, characterized in that: Determining whether the distribution discreteness of the cutting risk position of the cloth processing object meets the requirements specifically includes: Determining distances between different cutting risk positions based on the distribution data of the cutting risk positions of the cloth cutting object; Based on the average value of the distances between the cutting risk positions and the number of the cutting risk positions, it is determined whether the distribution discreteness of the cutting risk positions of the cloth processing object meets the requirement.

8. 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: Determining the number of power switching processes of the laser device of the embroidery machine based on the distribution data of the cutting risk position; Determining switching anomaly weight coefficients of different switching risk positions based on the product of the switching anomaly coefficients of different switching risk positions and a preset proportional factor; The switching process abnormality coefficient is determined according to the sum of the switching abnormality weight coefficients of different power switching process times, and the cutting control strategy of the laser device of the embroidery machine is determined by using the switching process abnormality coefficient.

9. The laser cutting control method according to claim 8, characterized in that: The cutting control strategy of the laser device of the embroidery machine is determined by using the switching processing abnormality coefficient, which specifically includes: When the switching process abnormality coefficient is greater than a preset switching process abnormality coefficient threshold, a cutting process is first performed to remove the cutting risk position, and then a unified cutting process is performed on all cutting risk positions; When the switching process abnormality coefficient is not greater than a preset switching process abnormality coefficient threshold, continuous cutting processing is performed using the cutting processing program and the cutting processing types corresponding to different processing positions.

10. A laser cutting control system, using a laser cutting control method according to any one of claims 1 to 9, characterized in that: Specifically include: Risk location identification module, distribution discrete assessment module, switching strategy determination module; The risk position identification module is responsible for determining the cutting risk position of the cloth processing object; The distribution discreteness evaluation module is responsible for determining whether the distribution discreteness of the cutting risk position of the cloth 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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