An adaptive intelligent control method for template machines

Abstract

The present invention discloses an adaptive intelligent control method for a template machine, which relates to the technical field of template machine control. The method comprises the following steps: performing deviation correction calculation on the coordinates of the to-be-sewn track points in each sub-area of a preset sewing track of a garment to be sewn, combined with the deviation distance of each sub-area, to obtain the deviation correction point coordinates of each to-be-sewn track point, inputting the deviation correction track into a control module of the template sewing machine, causing the template sewing machine to perform sewing operations according to the deviation correction track, accurately analyzing the deviation conditions of the template sewing machine in each sub-area of a work surface, and performing targeted deviation correction on the preset sewing track of the current garment to be sewn accordingly, transmitting the generated deviation correction track to the control module of the template sewing machine, causing the template sewing machine to sew according to the deviation correction track, thereby improving the sewing accuracy and stability of the template sewing machine, and reducing the sewing deviation caused by the discrepancy between the preset sewing track and the actual sewing situation.

Description

Technical Field

[0001] The invention belongs to the technical field of template machine control, and in particular is an adaptive intelligent control method for a template machine. Background Art

[0002] Template sewing machines are machines that combine clothing template CAD software, clothing template sewing CAD software, and advanced numerical control technology to fully automate application template production, improving production efficiency and product quality while reducing the technical requirements of skilled workers. They replace the original manually operated sewing machines with more automated computer-controlled machines, reducing the reliance on highly skilled personnel. While ensuring quality, they also address the labor shortage and skill deficiencies of industrial workers, fully automate garment sewing, and promote the streamlined processing of garment templates.

[0003] Template sewing machines play an important role in clothing manufacturing and other related industries. They can perform sewing operations according to pre-set trajectories, significantly improving production efficiency and product quality stability.

[0004] However, the current template sewing machine still faces many challenges in its actual operation. On the one hand, the template sewing machine itself has errors in its mechanical structure. After long-term use, the mechanical parts will wear and loosen, resulting in a deviation between the movement trajectory of the sewing head and the preset trajectory; on the other hand, fabrics from different batches and different materials have differences in physical properties, such as thickness, elasticity, hardness, etc. These differences will cause different degrees of deformation of the fabric during the sewing process, which in turn affects the actual sewing trajectory and causes the actual sewing trajectory to deviate from the preset trajectory.

[0005] In most cases, during the use of template sewing machines, the control module can only perform sewing operations simply according to the preset sewing trajectory, and it is impossible to adjust the sewing trajectory in real time according to the actual deviation. As a result, during the production process, the quality of products is uneven and the defective rate is high, which increases production costs and reduces production efficiency, affecting the sewing effect of clothing. Based on this, an adaptive intelligent control method for template machines is proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide an adaptive intelligent control method for a template sewing machine, which solves the technical problem that during use of the template sewing machine, the sewing operation can only be performed simply according to a preset sewing trajectory through a control module, and the sewing trajectory cannot be adjusted in real time according to the actual deviation.

[0007] A method for adaptive intelligent control of a template machine comprises the following steps:

[0008] Step 1: Create the sewing machine work surface according to the boundary line of the template sewing machine work table;

[0009] Step 2: Evenly divide the working surface of the template sewing machine into multiple sub-areas;

[0010] Step 3: Calibrate the positioning points of each sub-area and determine the calibration lines of each sub-area based on the positioning points;

[0011] Step 4: Obtain a plurality of historical sewing data including preset sewing trajectories and actual sewing trajectories of the template sewing machine within a predetermined time period T, where 180 days ≥ T ≥ 1 day;

[0012] Step 5: Analyze the preset sewing trajectory and the actual sewing trajectory of each historical sewing data in each sub-area to obtain the deviation distance of each sub-area;

[0013] Step 6: Obtain the coordinates of the track points to be sewn in each sub-area of the preset sewing track of the garment to be sewn, and perform correction calculation based on the coordinates of the coordinates of the points to be sewn in combination with the deviation distance of each sub-area to obtain the correction point coordinates of each track point to be sewn, and splice the correction points in order from top to bottom to generate a correction track;

[0014] Step 7: Input the deviation correction track into the template sewing machine control module, so that the template sewing machine performs sewing operations according to the deviation correction track.

[0015] As a further solution of the present invention, the specific method of determining the demarcation line of each sub-region is:

[0016] The center point of each sub-region is marked as the positioning point corresponding to each sub-region, and the horizontal center line of each sub-region is used as the calibration line corresponding to each sub-region.

[0017] As a further solution of the present invention, the specific method of obtaining the deviation distance of each sub-region is:

[0018] S1: Randomly select one of the sub-areas on the working surface of the template sewing machine without replacement as the target area;

[0019] S2: Randomly select one of the historical sewing data without replacement as the target data: take the positioning point of the target area as the origin, the horizontal center line of the target area as the abscissa axis, and the vertical center line of the target area as the ordinate axis, and then construct a two-dimensional coordinate system of the target area, obtain the coordinates of the preset track point and the actual track point corresponding to the preset sewing track of the target data and the actual sewing track in the target area, respectively, and take the absolute value of the difference between the abscissa of the preset track point and the actual track point as the deviation value P1 of the target data in the target area;

[0020] S3: Repeat step S2 to obtain the deviation value Pn corresponding to each historical sewing data in the target area, and obtain the standard deviation value W of the deviation value Pn. When the standard deviation value W is less than the preset value Y1, the mean value Pp of Pn is used as the pre-difference value Q1 corresponding to the target area. When the standard deviation value W is greater than or equal to the preset value Y1, the mean of the maximum and minimum values in Pn is used as the pre-difference value Q1 corresponding to the target area, where n refers to different historical sewing data, n=2, ..., d, d is the number of historical sewing data, and d≥2;

[0021] S4: Analyze the positional relationship between each preset sewing trajectory in each historical sewing data and its corresponding actual sewing trajectory in the target area to obtain a deviation distance Z1 corresponding to the target area;

[0022] S5: Repeat steps S1-S4 to obtain the deviation distance Zi corresponding to each sub-region, where i refers to a different sub-region, i=2, 3, ..., a, a is the number of sub-regions, a≥2.

[0023] As a further solution of the present invention, the specific method of obtaining the deviation distance corresponding to the target area is:

[0024] The numbers R and L of the preset sewing tracks in each historical sewing data that are respectively located on the right and left sides of the actual sewing track in the target area are obtained. When the ratio between the numbers R and L is greater than the preset threshold value Y2, the product between the corresponding leading difference Q1 in the target area and negative one is used as the deviation distance Z1 corresponding to the target area. When the ratio between the numbers R and L is less than or equal to the preset threshold value Y2 and greater than or equal to the preset threshold value Y3, zero is used as the deviation distance Z1 corresponding to the target area. When the ratio between the numbers R and L is less than the preset threshold value Y3, the absolute value of the leading difference Q1 corresponding to the target area is used as the deviation distance Z1 corresponding to the target area. Here, Y2>1.15>Y3>0.95.

[0025] As a further solution of the present invention, a specific method for obtaining the coordinates of the track points to be sewn in each sub-area of the preset sewing track of the garment to be sewn is:

[0026] Obtain the intersection points between the preset sewing trajectory of the garment to be sewn and the calibration lines in each sub-area, and mark them as the trajectory points to be sewn corresponding to the preset sewing trajectory of the garment to be sewn in each sub-area, and obtain the coordinates Fi(FXi, FYi) of each trajectory point to be sewn.

[0027] As a further solution of the present invention: the specific method of obtaining the coordinates of the correction points of each track point to be sewn is:

[0028] Obtain the sum of the horizontal coordinate FXi in the coordinates of the sewing trajectory points in each sub-area and the deviation distance Zi of its corresponding sub-area, and use it as the horizontal coordinate of the coordinates of each correction point. At the same time, use the vertical coordinate FYi in the coordinates of the sewing trajectory points in each sub-area as the vertical coordinate of the coordinates of each correction point, and you can get the correction point coordinates Hi(HXi+Zi, FYi) of each trajectory point to be sewn.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention uses historical sewing data to accurately analyze the deviation of the template sewing machine in each sub-area of the work surface, and accordingly performs targeted correction on the preset sewing trajectory of the current garment to be sewn, and transmits the generated correction trajectory to the control module of the template sewing machine, so that the template machine sews according to the correction trajectory. The correction strategy previously obtained through data analysis and calculation is implemented in the actual production process to realize the correction of the preset sewing trajectory deviation, thereby improving the accuracy and quality of garment sewing, reducing the sewing deviation caused by the discrepancy between the preset sewing trajectory and the actual sewing situation, and further improving the quality of garment products, reducing the defective rate, and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the framework structure of the method of the present invention;

[0032] Figure 2 A schematic diagram of a two-dimensional coordinate system within the target area of the present invention;

[0033] Figure 3 This is a schematic diagram of the preset sewing trajectory, actual sewing trajectory, preset trajectory points and actual trajectory points of the present invention. DETAILED DESCRIPTION

[0034] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] Example 1: Please refer to Figure 1-Figure 3 , the present application provides a template machine adaptive intelligent control method, comprising the following steps:

[0036] Step 1: Obtain the boundary line of the template sewing machine workbench and build the sewing machine workbench;

[0037] It should be noted that the boundary line of the template sewing machine worktable can be obtained by manual measurement and drawing or by using high-precision measuring equipment such as laser rangefinders, optical sensors, etc. The above are all existing and mature technologies, so no further details will be given here.

[0038] Step 2: Evenly divide the working surface of the template sewing machine into multiple sub-areas;

[0039] The area of each sub-area is not greater than the preset area threshold Y3 and is greater than 0. The specific value of the preset area threshold Y3 is formulated by relevant personnel based on actual needs. Here, Y3 is 1 / 80 of the work surface area;

[0040] It should be noted that when segmenting, the work surface should be divided into multiple sub-areas as much as possible, that is, the size of the sub-areas should be as small as possible. Smaller sub-areas can make the center point coordinates more closely represent the sub-area coordinates, thereby effectively reducing measurement errors, providing a more accurate data basis for subsequent deviation analysis and correction calculations, and reducing measurement errors.

[0041] Subdividing a large work surface into multiple small sub-areas, on the one hand, smaller sub-areas can make the center point coordinates more closely represent the sub-area coordinates, reduce measurement errors, and provide a basis for subsequent accurate analysis of deviations and calculation of correction data; on the other hand, different sub-areas may have different degrees of deviations. Subdivision helps to more carefully identify and handle local deviations, thereby improving the pertinence and accuracy of overall correction.

[0042] Step 3: Mark the center point of each sub-area as the corresponding positioning point of each sub-area, and establish the corresponding calibration line in each sub-area;

[0043] The calibration lines in each sub-area are established as follows:

[0044] The horizontal center line of each sub-region is used as the calibration line corresponding to each sub-region;

[0045] The positioning point provides a clear reference center for each sub-area, which facilitates the determination of the position benchmark when constructing the coordinate system and analyzing the trajectory. The calibration line, that is, the horizontal center line, serves as a specific reference line. It provides a unified and stable measurement basis when subsequently obtaining the coordinates of the preset trajectory points and the actual trajectory points, making the deviation calculation more consistent and comparable.

[0046] Step 4: The template sewing machine control system acquires a plurality of historical sewing data of the template sewing machine within a predetermined time period T, wherein the historical sewing data includes a preset sewing trajectory and an actual sewing trajectory;

[0047] The specific value of the predicted time period T is the period of 180 days from the moment the data is obtained, that is, 180 days ≥ T ≥ 1 day;

[0048] Historical sewing data includes information on preset and actual sewing trajectories during past actual sewing processes. These historical sewing data are an important basis for analyzing the current working status and deviation of the template machine. By mining and analyzing historical sewing data, we can discover the deviation patterns of the template machine under different times and different sewing tasks, providing data support and experience reference for subsequent deviation analysis and correction.

[0049] Step 5: Place the preset sewing trajectory and actual sewing trajectory in each historical sewing data on the work surface of the template sewing machine for analysis, and obtain the coordinates of the preset trajectory points and actual trajectory points corresponding to each historical sewing data in each sub-area. According to the coordinates of the preset trajectory points and actual trajectory points corresponding to each historical sewing data in each sub-area, analyze and obtain the deviation distance corresponding to each sub-area on the work surface of the template sewing machine. The specific method is as follows:

[0050] S1: Randomly select one of the sub-areas on the working surface of the template sewing machine without replacement as the target area;

[0051] S2: Randomly select one of the historical sewing data without replacement as the target data;

[0052] The preset sewing trajectory and the actual sewing trajectory of the target data are obtained, and the coordinates of the preset track points and the actual track points corresponding to the preset sewing trajectory and the actual sewing trajectory in the target area are obtained in the following manner:

[0053] A two-dimensional coordinate system is constructed based on the positioning point, horizontal center line, and vertical center line of the target area. The specific construction method is as follows: the positioning point of the target area is used as the origin, the horizontal center line of the target area is used as the abscissa axis, and the vertical center line of the target area is used as the ordinate axis, thereby constructing the two-dimensional coordinate system of the target area;

[0054] Obtaining the intersection points of the preset sewing trajectory of the target data and the actual sewing trajectory with the target area calibration line in the target area, respectively, and using them as the preset trajectory points and actual trajectory points of the target data in the target area, obtaining the coordinates of the preset trajectory points and the actual trajectory points in the two-dimensional coordinate system, and marking them as GA (GAX, GAY) and GB (GBX, GBY), respectively;

[0055] The absolute value of the difference between the horizontal coordinates of the preset track point and the actual track point is used as the deviation value P1 of the preset track point and the actual track point in the target area of the target data, that is: P1 = |GAX-GBX|;

[0056] S3: Repeat step S2 to obtain the deviation value Pn corresponding to each historical sewing data in the target area, where n refers to different historical sewing data, n=2, 3, ..., d, d is the number of historical sewing data, d≥2;

[0057] The standard deviation is calculated using the formula: Calculate the standard deviation value W corresponding to the deviation value Pn, where Pc is any value in Pn, Pp is the mean of Pn, and n≥c≥1;

[0058] Analyze the standard deviation value W corresponding to the deviation value Pn. When the standard deviation value W is less than the preset value Y1, the mean value Pp of Pn is used as the leading difference value Q1 corresponding to the target area. When the standard deviation value W is greater than or equal to the preset value Y1, the mean of the maximum and minimum values in Pn is used as the leading difference value Q1 corresponding to the target area. The specific value of the preset value Y1 is set by relevant personnel according to specific application scenarios and requirements.

[0059] S4: Analyze the positional relationship between each preset sewing track in each historical sewing data and its corresponding actual sewing track, and then obtain the number R and L of the preset sewing tracks in each historical sewing data in the target area that are respectively located on the right and left sides of the actual sewing track. When the ratio between the number R and L is greater than the preset threshold value Y2, the product between the corresponding preceding difference Q1 in the target area and negative one is used as the deviation distance Z1 corresponding to the target area. When the ratio between the number R and L is less than or equal to the preset threshold value Y2 and greater than or equal to the preset threshold value Y3, the product between the corresponding preceding difference Q1 in the target area and zero is used as the deviation distance Z1 corresponding to the target area. When the ratio between the number R and L is less than the preset threshold value Y3, the absolute value of the preceding difference Q1 corresponding to the target area is used as the deviation distance Z1 corresponding to the target area. Here, the specific values of the preset threshold value Y2 and the preset threshold value Y3 are formulated by relevant personnel according to actual needs, and Y2>1.15>Y3>0.95;

[0060] S5: Repeat steps S1-S4 to obtain the deviation distance Zi corresponding to each sub-area on the worktable of the template sewing machine, where i refers to a different sub-area, i=2, 3, ..., a, a is the number of sub-areas, a≥2;

[0061] By specifically analyzing the preset and actual trajectories in each sub-area on the work surface, the deviation distance corresponding to each sub-area is accurately obtained. The deviation distance reflects the degree of difference between the actual sewing and the preset sewing of the template machine in each sub-area, providing key data for subsequent targeted correction of the preset sewing trajectory.

[0062] Step 6: When the template sewing machine is sewing the garment, the preset sewing track of the garment to be sewn is placed on the work surface of the template sewing machine, and the coordinates of the track points to be sewn corresponding to the preset sewing track of the garment to be sewn in each sub-area are obtained. According to the deviation distances corresponding to the sub-areas on the work surface, the coordinates of the track points to be sewn corresponding to the preset sewing track of the garment to be sewn in each sub-area are sequentially corrected, thereby obtaining the coordinates of the correction points after correction processing in each sub-area, marking the correction points after correction processing in each sub-area according to the correction point coordinates, and then sequentially splicing the correction points after correction processing in each sub-area, thereby generating a correction track;

[0063] The specific method of obtaining the coordinates of the track points to be sewn corresponding to the preset sewing track of the garment to be sewn in each sub-area is as follows:

[0064] Obtaining the intersection points between the preset sewing trajectory of the garment to be sewn and the calibration lines in each sub-region, and using them as the trajectory points to be sewn corresponding to the preset sewing trajectory of the garment to be sewn in each sub-region, and obtaining the coordinates Fi(FXi, FYi) of each trajectory point to be sewn;

[0065] The specific method of obtaining the coordinates of the correction points after the correction processing in each sub-area is as follows: the sum of the horizontal coordinates FXi in the coordinates of the sewing track points in each sub-area and the deviation distances Zi of the corresponding sub-areas is used as the horizontal coordinates of the coordinates of the correction points after the correction processing in each sub-area, and the vertical coordinates FYi in the coordinates of the sewing track points in each sub-area is also used as the vertical coordinates of the coordinates of the correction points after the correction processing in each sub-area, so as to obtain the coordinates Hi(HXi+Zi, FYi) of the correction points after the correction processing in each sub-area; the correction points after the correction processing are marked in each sub-area according to the correction point coordinates, and then the correction points after the correction processing in each sub-area are sequentially spliced in order from top to bottom to generate the correction trajectory;

[0066] By performing correction calculations on the coordinates of the preset trajectory points, the previously calculated deviation distances of each sub-area are applied to the actual preset trajectory of the garment to be sewn to obtain the corrected point coordinates, and then these points are spliced together to form a correction trajectory. The correction trajectory is an optimization of the preset sewing trajectory, guiding the template sewing machine to perform sewing operations more accurately and reduce actual sewing deviations.

[0067] Step 7: Re-inputting the correction trajectory into the control module of the template sewing machine, so that the template sewing machine performs sewing operations on the garment to be sewn according to the correction trajectory, thereby reducing the sewing deviation caused by the preset sewing trajectory;

[0068] The generated correction trajectory is transmitted to the control module of the template sewing machine. The template sewing machine sews according to the correction trajectory, and implements the correction strategy previously obtained through data analysis and calculation into the actual production process to correct the deviation of the preset sewing trajectory, thereby improving the accuracy and quality of garment sewing.

[0069] Through comprehensive analysis and data processing of the working process of the template sewing machine, adaptive intelligent control of the sewing trajectory is achieved. By utilizing historical sewing data, the deviation of the template sewing machine in each sub-area of the work surface is accurately analyzed, and the preset sewing trajectory of the current garment to be sewn is targetedly corrected accordingly. The generated correction trajectory is transmitted to the control module of the template sewing machine, so that the template sewing machine sews according to the correction trajectory, thereby improving the accuracy and stability of the template sewing machine's sewing, reducing the sewing deviation caused by the discrepancy between the preset sewing trajectory and the actual sewing situation, thereby improving the quality of clothing products, reducing the defective rate, and improving production efficiency. At the same time, the adaptive characteristics of this solution enable it to adapt to the sewing needs of different materials and different types of clothing, and it has strong versatility and flexibility.

[0070] It should be noted that in the control systems of modern high-precision template sewing machines, the control accuracy of the horizontal axis is crucial. A large number of key operations are concentrated in the horizontal direction, while the vertical axis is controlled by a high-precision stepper or servo motor, which has a relatively small impact on the trajectory. At the same time, many key actions of the sewing machine, such as turning corners and sewing path changes, mainly occur in the horizontal direction, while the vertical changes are stable, mostly feeding and returning actions. Therefore, ignoring the vertical axis deviation is consistent with the actual operating characteristics of the sewing machine and can greatly reduce the calculation complexity. Without significantly affecting the sewing accuracy, it effectively improves the efficiency of deviation calculation and correction, making the solution more simple and efficient while ensuring practicality.

[0071] At the same time, choosing the horizontal center line as the calibration line can effectively reflect the main movement trajectory of the sewing machine in the horizontal direction. In the operation of most template sewing machines, the horizontal direction is the most important control direction, because most sewing paths and trajectory changes occur in this direction. Using the horizontal center line as the calibration line simplifies the deviation calculation. By calculating the horizontal coordinate deviation between the preset trajectory point and the actual trajectory point and the horizontal center line, the lateral deviation value can be directly obtained, avoiding the calculation of the vertical coordinate deviation, further reducing the complexity of the algorithm, and improving the calculation efficiency. The horizontal center line is used as the standard line to make the deviation correction process more intuitive and efficient. Regardless of any changes in the sewing path, the horizontal center line can be used as a reference to ensure the accuracy of the overall sewing trajectory by adjusting the lateral deviation;

[0072] At the same time, due to the small size of each sub-area, the horizontal coordinate deviation between the preset trajectory point and the actual trajectory point is usually small. Therefore, the deviation of the local area can be approximated as the horizontal deviation of the overall sewing trajectory. This approximate assumption reduces computational overhead and complexity while maintaining high precision. By analyzing the deviation of each sub-area, the overall sewing trajectory can be effectively corrected. The correction calculation for each sub-area is performed independently. Based on the horizontal coordinate deviation within the sub-area, the system can fine-tune the sewing trajectory. After performing corrections on multiple sub-areas, the overall sewing trajectory error will be significantly reduced, thereby ensuring sewing accuracy.

[0073] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0074] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A template machine adaptive intelligent control method, characterized in that: The following steps are involved: Step 1: Create the sewing machine work surface according to the boundary line of the template sewing machine work table; Step 2: Divide the template sewing machine work surface evenly into multiple sub-areas; Step 3: Calibrate the positioning points of each sub-area and determine the calibration lines of each sub-area based on the positioning points; Step 4: Obtain a plurality of historical sewing data including preset sewing trajectories and actual sewing trajectories of the template sewing machine within a predetermined time period T, where 180 days ≥ T ≥ 1 day; Step 5: Analyze the preset sewing trajectory and the actual sewing trajectory of each historical sewing data in each sub-area to obtain the deviation distance of each sub-area; Step 6: Obtain the intersection points between the preset sewing trajectory of the garment to be sewn and the calibration lines in each sub-area, and mark the intersection points as the trajectory points to be sewn of the preset sewing trajectory in each sub-area, and use the sum of the deviation distances between the abscissas of the sewing trajectory points in each sub-area and the corresponding sub-area as the abscissas of the coordinates of each correction point, and use the ordinates of the sewing trajectory points in each sub-area as the ordinates of the coordinates of each correction point, so as to obtain the correction point coordinates of each trajectory point to be sewn, and splice the correction points in order from top to bottom to generate a correction trajectory; Step 7: Input the deviation correction track into the template sewing machine control module, so that the template sewing machine performs sewing operations according to the deviation correction track.

2. The method for adaptive intelligent control of a template machine according to claim 1, characterized in that: The specific method for determining the demarcation line of each sub-area is: The center point of each sub-region is marked as the positioning point corresponding to each sub-region, and the horizontal center line of each sub-region is used as the calibration line corresponding to each region.

3. The adaptive intelligent control method of a template machine according to claim 2, characterized in that: The specific method of obtaining the deviation distance of each sub-region is: S1: Randomly select one of the sub-areas on the working surface of the template sewing machine without replacement as the target area; S2: Randomly select one of the historical sewing data without replacement as the target data: Construct a two-dimensional coordinate system in the target area, obtain the coordinates of the preset track point and the actual track point corresponding to the preset sewing track of the target data and the actual sewing track in the target area, and use the absolute value of the difference between the horizontal coordinates of the preset track point and the actual track point as the deviation value P1 of the target data in the target area; S3: Repeat step S2 to obtain the deviation value Pn corresponding to each historical sewing data in the target area, obtain the standard deviation value W of the deviation value Pn, and analyze the standard deviation value W to obtain the leading difference value Q1 corresponding to the target area, where n refers to different historical sewing data, n=2, ..., d, d is the number of historical sewing data, and d≥2; S4: Analyze the positional relationship between each preset sewing trajectory in each historical sewing data and its corresponding actual sewing trajectory in the target area to obtain a deviation distance Z1 corresponding to the target area; S5: Repeat steps S1-S4 to obtain the deviation distance Zi corresponding to each sub-region, where i refers to a different sub-region, i=2, 3, ..., a, a is the number of sub-regions, a≥2.

4. The method for adaptive intelligent control of a template machine according to claim 3, characterized in that: The specific method of constructing a two-dimensional coordinate system in the target area is: The positioning point of the target area is taken as the origin, the horizontal center line of the target area is taken as the abscissa axis, and the vertical center line of the target area is taken as the ordinate axis, thereby constructing a two-dimensional coordinate system of the target area.

5. The method for adaptive intelligent control of a template machine according to claim 3, characterized in that: The specific method of analyzing the standard deviation value W to obtain the corresponding pre-difference value of the target area is: When the standard deviation value W is less than the preset value Y1, the mean Pp of Pn is used as the leading difference Q1 corresponding to the target area. When the standard deviation value W is greater than or equal to the preset value Y1, the mean of the maximum and minimum values in Pn is used as the leading difference Q1 corresponding to the target area.

6. The method for adaptive intelligent control of a template machine according to claim 3, characterized in that: The specific method of obtaining the deviation distance corresponding to the target area is: The numbers R and L of the preset sewing tracks in each historical sewing data that are respectively located on the right and left sides of the actual sewing track in the target area are obtained. When the ratio between the numbers R and L is greater than the preset threshold value Y2, the product between the corresponding leading difference Q1 in the target area and negative one is used as the deviation distance Z1 corresponding to the target area. When the ratio between the numbers R and L is less than or equal to the preset threshold value Y2 and greater than or equal to the preset threshold value Y3, zero is used as the deviation distance Z1 corresponding to the target area. When the ratio between the numbers R and L is less than the preset threshold value Y3, the absolute value of the leading difference Q1 corresponding to the target area is used as the deviation distance Z1 corresponding to the target area. Here, Y2>1.15>Y3>0.

95.

7. The method for adaptive intelligent control of a template machine according to claim 1, characterized in that: The area of the sub-region is not greater than a preset area threshold and is greater than 0. Here, the preset area threshold is 1 / 80 of the area of the work surface.

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