Garment fabric tailoring path optimization analysis method and system

Abstract

The invention belongs to the technical field of garment fabric processing, and relates to a garment fabric tailoring path optimization analysis method and system.The garment fabric tailoring path optimization analysis method comprises the steps that a reference tailoring path of garment fabric is determined according to the edge contour of a garment template, and stress data of monitoring nodes on the reference tailoring path are collected through a stress sensor; according to the stress data of the current cutting monitoring node and the stress data of the previous monitoring node, predicting the stress change of the next monitoring node to be cut, quantifying the deformation parameters of the garment fabric under the influence of the stress change, and inputting the deformation parameters of the garment fabric into a cutting path offset model, and determining the cutting path offset corresponding to the garment fabric deformation trend of the next to-be-cut monitoring node, so as to carry out dynamic path compensation on a garment fabric reference cutting path, and meanwhile, carrying out vacuum adsorption mechanism trigger judgment and dynamic cutting speed adjustment, so that high-precision and self-adaptive dynamic path optimization is realized. The cutting quality and efficiency are remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of fabric processing and relates to a method and system for optimizing and analyzing the cutting path of clothing fabrics. Background Art

[0002] In the clothing production industry, fabric cutting is a key step in determining clothing quality and production efficiency. As clothing styles become increasingly diversified and personalized, higher requirements are placed on the accuracy and efficiency of fabric cutting. However, in the actual production process, the problem of cutting path deviation is prone to occur. This problem not only leads to fabric waste, but also affects the overall quality and production efficiency of clothing. Therefore, in order to ensure cutting accuracy and improve cutting efficiency, it is urgent to optimize and analyze the fabric cutting path.

[0003] In the existing technology, there are also some related solutions involving fabric cutting path optimization. For example, China Patent Publication No. CN115908435A is a vision-based clothing cutting path planning method and system. It uses image acquisition technology to obtain basic data of the object to be cut, analyzes the original cutting data and preview images for users to fine-tune, and generates corresponding cutting plans and preview images, which makes it easier for users to intuitively distinguish the design effects and improve path planning efficiency.

[0004] Another Chinese patent, CN109523074A, discloses a method for optimizing clothing cutting paths based on a nearest neighbor genetic hybrid algorithm. The method uses cutting software to arrange clothing samples to obtain cutting data files, uses Matlab software to parse the point coordinates of the clothing samples and reproduce the vector diagrams of the clothing samples, analyzes the cutting sequence through a genetic algorithm, calculates the entry point of the sample, compares the cutting path data before and after optimization, analyzes the optimization effect, and improves the accuracy of cutting path planning.

[0005] Although the above schemes propose some solutions for optimizing the fabric cutting path, the existing technology still has the following limitations, specifically:

[0006] (1) Existing technologies mostly rely on static data for path planning, but are unable to perceive the stress changes, deformation trends and dynamic characteristics of the fabric during the cutting process in real time. As a result, the cutting path cannot be dynamically adjusted according to the actual state of the fabric. It is difficult to cope with local deformation caused by uneven stress distribution, fabric elasticity or the force of the cutting tool, thus causing cutting errors.

[0007] (2) The existing technology does not link the vacuum adsorption mechanism with the fabric deformation and cutting status in real time. The control of the adsorption force is mostly fixed or manually intervened, and it cannot be dynamically adjusted according to the actual needs of the fabric. As a result, the fabric is deformed due to insufficient adsorption during the cutting process, affecting the cutting accuracy and efficiency.

[0008] (3) The operating speed parameters of the existing cutting equipment are usually set to constant values, and there is a lack of an adjustment mechanism based on the geometric complexity of the cutting path. This fixed speed control will lead to problems such as cutting trajectory offset and edge burrs when cutting paths with sudden changes in curvature and multiple node turns. For simple paths such as straight lines, it will cause a loss of overall production efficiency. Summary of the Invention

[0009] In view of this, in order to solve the problems raised in the above background technology, a method and system for optimizing and analyzing the cutting path of clothing fabrics are proposed.

[0010] The objectives of the present invention can be achieved through the following technical solutions: In the first aspect, the present invention provides a method for optimizing and analyzing the cutting path of clothing fabrics, comprising: S1. fixing a cutting pattern on the fabric to be cut, and determining a reference cutting path of the fabric according to the edge contour of the pattern.

[0011] S2. Based on the patch stress sensors arranged on the edge of the template, the stress data of each monitoring node on the reference cutting path is sensed in real time, including the stress amplitude and direction angle.

[0012] S3. Based on the stress data of the currently cut monitoring node and the previous monitoring node, predict the stress change of the next monitoring node to be cut, and quantify the fabric deformation parameters under the influence of the stress change.

[0013] S4. Input the deformation parameters of the fabric at the next monitoring node to be cut into the established cutting path offset model, determine the cutting path offset corresponding to the deformation trend of the fabric at the next monitoring node to be cut, including the offset modulus and the offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path.

[0014] S5. Generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism.

[0015] S6. Dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

[0016] In a second aspect, the present invention provides a fabric cutting path optimization analysis system, comprising: a rigid template fixing module, a stress data acquisition module, a fabric deformation analysis module, a dynamic path compensation module, a vacuum adsorption control module and a cutting speed adjustment module.

[0017] The rigid template fixing module is connected to the stress data acquisition module, the stress data acquisition module is connected to the fabric deformation analysis module, the fabric deformation analysis module is respectively connected to the dynamic path compensation module, and the dynamic path compensation module is respectively connected to the cutting speed adjustment module and the vacuum adsorption control module.

[0018] The rigid template fixing module is used to fix the cutting template on the fabric to be cut and determine the reference cutting path of the fabric according to the edge contour of the template.

[0019] The stress data acquisition module is used to sense the stress data of each monitoring node on the reference cutting path in real time based on the patch stress sensor arranged on the edge of the template, including the stress amplitude and direction angle.

[0020] The fabric deformation analysis module is used to predict the stress change of the next monitoring node to be cut based on the stress data of the currently cut monitoring node and its previous monitoring node, and quantify the fabric deformation parameters under the influence of the stress change.

[0021] The dynamic path compensation module is used to input the fabric deformation parameters of the next monitoring node to be cut into the constructed cutting path offset model, determine the cutting path offset corresponding to the fabric deformation trend of the next monitoring node to be cut, including the offset modulus and offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path.

[0022] The vacuum adsorption control module is used to generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism.

[0023] The cutting speed adjustment module is used to dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] (1) The present invention installs patch stress sensors on the edge of the sample to collect stress magnitude and direction data in real time, quantitatively analyze fabric deformation parameters, and use a path offset model to determine the cutting path offset. The cutting path is then dynamically adjusted to ensure that the cutting line always fits the actual state of the fabric, avoiding cutting errors caused by local deformation of the fabric, improving fabric cutting efficiency, and reducing human errors.

[0026] (2) The present invention uses the predicted fabric deformation impact area as a deformation evaluation index to determine whether to trigger the vacuum adsorption mechanism. When the predicted fabric deformation impact area is too large, the vacuum adsorption mechanism is triggered to fix the fabric to prevent it from further displacement or distortion, thereby improving the fabric cutting accuracy and efficiency.

[0027] (3) The present invention dynamically adjusts the cutting speed of the fabric according to the curvature change rate of adjacent monitoring nodes, which not only ensures the cutting efficiency but also avoids problems such as cutting trajectory deviation and edge burrs caused by too fast or too slow speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 The present invention is a flowchart of the steps for implementing the method.

[0030] Figure 2 This is a schematic diagram of module connection of the present invention.

[0031] Figure 3 This is a logic flow chart for dynamically adjusting the fabric cutting speed in step S6 of the present invention.

[0032] Figure 4 Schematic diagram of the cutting operation device of the present invention.

[0033] Reference numerals: 1. Vacuum adsorption mechanism; 2. Cutting pattern; 3. Fabric to be cut. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the 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] Reference Figure 1 and Figure 4 As shown, the present invention provides a method for optimizing and analyzing the cutting path of clothing fabrics, comprising: S1. fixing a cutting pattern on the fabric to be cut, and determining a reference cutting path of the fabric according to the edge contour of the pattern.

[0036] S2. Based on the patch stress sensors arranged on the edge of the template, the stress data of each monitoring node on the reference cutting path is sensed in real time, including the stress amplitude and direction angle.

[0037] It should be noted that the specific deployment process of the above-mentioned patch stress sensor includes: according to the preset sampling spacing parameters, an equidistant dispersion strategy is adopted to divide the reference cutting path into multiple monitoring node positions, and the patch stress sensor is pasted on the surface of each monitoring node along the cutting direction to achieve accurate measurement in a single direction.

[0038] It should be noted that the above-mentioned preset sampling interval parameters are determined by combining the sample size and historical stress gradient analysis, and can be set to 5 mm for example.

[0039] S3. Based on the stress data of the currently cut monitoring node and the previous monitoring node, predict the stress change of the next monitoring node to be cut, and quantify the fabric deformation parameters under the influence of the stress change.

[0040] As a preferred embodiment, the stress change of the next monitoring node to be trimmed is predicted, and the specific acquisition method is as follows: respectively obtain the path lengths from the current trimming monitoring node to its preceding and succeeding adjacent monitoring nodes, which are recorded as the preceding path length and the succeeding path length.

[0041] The stress vectors of the currently clipped monitoring node and its previous monitoring node are obtained, and the stress vectors are decomposed into normal stress and tangential stress according to the clipping path direction. The normal stress difference and normal stress ratio of the currently clipped monitoring node and its previous monitoring node are quantified respectively, and the ratio of the normal stress difference to the length of the previous path is used as the normal stress change rate per unit length.

[0042] The normal stress change rate per unit length, the subsequent path length, and the normal stress ratio are cumulatively calculated to obtain the normal stress prediction value of the next monitoring node. Similarly, the tangential stress prediction value of the next monitoring node can be obtained. The normal stress prediction value and the tangential stress prediction value of the next monitoring node are substituted into the Euclidean norm formula to obtain the stress prediction amplitude of the next monitoring node to be trimmed.

[0043] Substitute the ratio of the predicted value of the tangential stress and the vertical component of the next monitoring node into the inverse tangent function to calculate the stress prediction direction angle of the next monitoring node to be trimmed.

[0044] It should be noted that the above process of obtaining the path length from the current cutting monitoring node to its front and rear adjacent monitoring nodes includes: taking the current monitoring node as the starting point, moving the laser tracker along the reference cutting path to its front and rear adjacent monitoring nodes, and obtaining the path length from the current cutting monitoring node to its front and rear adjacent monitoring nodes based on the built-in algorithm through the real-time collected three-dimensional spatial coordinate data.

[0045] As a preferred embodiment, the quantification process of the fabric deformation parameters under the influence of the stress change includes: obtaining a preset elastic modulus of the target fabric, and calculating the fabric deformation prediction modulus based on Hooke's law according to the stress prediction amplitude.

[0046] The stress prediction direction angle of the next monitoring node to be cut is used as the fabric deformation prediction angle.

[0047] It should be noted that the preset elastic modulus of the above-mentioned target fabric can be obtained from the elasticity standard table of clothing materials.

[0048] It should be noted that the above-mentioned calculation of the fabric deformation prediction modulus based on Hooke's law specifically includes: Hooke's law states that within the elastic limit, the deformation of an object is proportional to the external force causing the deformation. Based on this law, the fabric deformation prediction modulus is obtained by calculating the ratio of the stress prediction amplitude to the preset elastic modulus of the target fabric.

[0049] S4. Input the deformation parameters of the fabric at the next monitoring node to be cut into the established cutting path offset model, determine the cutting path offset corresponding to the deformation trend of the fabric at the next monitoring node to be cut, including the offset modulus and the offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path.

[0050] As a preferred embodiment, the construction process of the clipping path offset model includes: obtaining historical fabric deformation modulus data and historical fabric deformation angle data, and preprocessing and normalizing the historical fabric deformation modulus data and historical fabric deformation angle data.

[0051] The processed historical fabric deformation modulus data and historical fabric deformation angle data are divided into a training set and a test set.

[0052] The model is trained based on the machine learning algorithm using the training set and the weights of the historical fabric deformation modulus data and the historical fabric deformation angle data are automatically adjusted. By capturing the relationship between the historical stress amplitude data and stress direction angle data and the cutting path offset, a cutting path offset model is constructed. The model is then verified and evaluated using the test set to obtain a trained model.

[0053] As a preferred embodiment, the specific calculation method of the clipping path offset model is as follows: , Calculate the clipping path offset modulus and offset direction angle respectively, where 、 are the normalized fabric deformation prediction modulus and fabric deformation prediction angle, 、 、 、 、 、 、 The weight coefficient set by model training.

[0054] It should be noted that the normalized predicted fabric deformation amplitude and predicted deformation angle are dimensionless values ​​that only represent the relative magnitude of fabric deformation without any specific physical dimensions.

[0055] It should be noted that the specific calculation method of the cutting path offset model integrates the mathematical logic of linear correlation and interaction effects. In the calculation formula of the cutting path offset modulus and offset direction angle, the fabric deformation prediction modulus reflects the stiffness of the fabric. The larger the fabric deformation prediction modulus, the greater the stiffness of the fabric. During cutting, a larger offset modulus will be generated due to factors such as stress transfer, and irregular deformation of the fabric will be caused. This deformation will cause the actual cutting path to deviate from the reference cutting path, resulting in an increase in the offset direction angle.

[0056] On the other hand, the fabric deformation prediction angle reflects the degree of fabric deformation in the cutting direction. The larger the fabric deformation prediction angle, the more significant the degree of deviation of the fabric from the original state in the cutting direction. This significant deformation will interfere with the cutting trajectory, causing the cutting tool to deviate from the cutting direction, resulting in an increase in the offset direction angle between the actual cutting path and the reference cutting path. In addition, this significant deformation will produce a stress concentration area inside the fabric, which will produce a greater reaction force on the cutting tool, increasing the offset modulus value.

[0057] It should be noted that in the clipping path offset modulus and offset direction angle calculation formula, each parameter has a specific role: In the clipping path offset modulus calculation formula, 、 Respectively reflects the linear contribution of fabric deformation prediction modulus and prediction angle to cutting path offset modulus, through It reflects the nonlinear contribution of the interaction between the fabric deformation prediction modulus and the prediction angle to the offset modulus.

[0058] In the clipping path offset angle calculation formula, and The nonlinear effects of the fabric deformation angle and deformation amplitude on the offset direction angle of the cutting path are reflected respectively. The influence of the interaction between the deformation prediction angle and the deformation prediction modulus on the offset direction angle is reflected through the ratio operation. The inverse tangent function is used to map the ratio to a limited range, thereby more accurately describing the offset direction angle.

[0059] It should be noted that, for example, if the normalized deformation amplitude and deformation angle of the next monitoring node to be cut are 0.9 and 0.5 respectively, they are input into the cutting path offset model, and the output cutting path offset modulus and offset direction angle are 0.69 and 0.45 rad respectively, where the weight coefficient in the cutting path offset model is 、 、 、 、 、 、 They are 0.5, 0.3, 0.2, 0.7, 0.3, 0.8 and 0.2 respectively.

[0060] The fabric deformation parameters of the next monitoring node to be cut are input into the constructed cutting path offset model to determine the cutting path offset corresponding to the fabric deformation trend of the next monitoring node to be cut, including the offset modulus and offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path.

[0061] As a preferred embodiment, the dynamic path compensation is performed on the fabric reference cutting path, and the specific acquisition method is as follows: the cutting path offset module value is used as the cutting path compensation module value.

[0062] The half-circle angle corresponding to the offset direction angle is used as the clipping path compensation angle.

[0063] The compensation modulus is decomposed into the compensation values ​​of the horizontal and vertical coordinates through the sine and cosine values ​​corresponding to the compensation angle. The coordinates of the next monitoring node to be cut are combined with the corresponding compensation value to obtain the corrected coordinates of the next monitoring node to be cut.

[0064] Calculate the unit normal vector corresponding to the corrected coordinates of the next monitoring node to be cut, and calculate the final cutting correction coordinates of the next monitoring node based on the preset seam reserve width. In this way, the final cutting correction coordinates of each monitoring node on the fabric reference cutting path are obtained one by one, realizing dynamic path compensation of the fabric reference cutting path.

[0065] It should be noted that the above-mentioned seam allowance width can be set to 3 mm by way of example. This seam allowance width is set based on industry standards and empirical data and has good applicability in conventional clothing production scenarios.

[0066] The embodiment of the present invention installs patch stress sensors on the edge of the sample to collect stress magnitude and direction data in real time, quantitatively analyzes fabric deformation parameters, and uses a path offset model to determine the cutting path offset. The cutting path is then dynamically adjusted to ensure that the cutting line always fits the actual state of the fabric, avoiding cutting errors caused by local deformation of the fabric, improving fabric cutting efficiency, and reducing human errors.

[0067] S5. Generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism.

[0068] As a preferred embodiment, the judgment of whether to trigger the vacuum adsorption mechanism includes: converting the rectangular coordinate system into a polar coordinate system, using the predicted amplitude and predicted angle of the fabric deformation as the radius and central angle of the predicted deformation affected area respectively, calculating the predicted deformation affected area based on the fan area formula, and using it as a deformation evaluation indicator.

[0069] If the deformation evaluation index is greater than the preset deformation threshold, the vacuum adsorption mechanism is triggered, otherwise the vacuum adsorption mechanism is kept in a dormant state.

[0070] The embodiment of the present invention uses the predicted fabric deformation impact area as a deformation evaluation indicator to determine whether to trigger the vacuum adsorption mechanism. When the predicted deformation impact area of ​​the fabric is too large, the vacuum adsorption mechanism is triggered to fix the fabric to prevent it from further displacement or distortion, thereby improving the fabric cutting accuracy and efficiency.

[0071] S6. Dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

[0072] Reference Figure 3 As shown, as a preferred embodiment, the fabric cutting speed is dynamically adjusted according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process. The specific acquisition method is as follows: the final cutting correction trajectory is determined based on the final cutting correction coordinates of the currently cut monitoring node and its next monitoring node.

[0073] The arc length and the corresponding central angle of the final clipping correction trajectory are calculated, and the curvature of the final clipping correction trajectory of the currently clipped monitoring node and its next monitoring node is obtained based on the curvature calculation formula.

[0074] Similarly, the curvature of the clipping trajectory of the currently clipped monitoring node and its previous monitoring node can be obtained and recorded as the reference curvature.

[0075] The difference between the curvature of the final clipped corrected trajectory and the reference curvature is compared with the reference curvature to obtain the curvature change rate.

[0076] Determine whether the absolute value of the curvature change rate is greater than a preset curvature change threshold. If so, calculate the fabric cutting adjustment speed based on the speed adjustment formula; otherwise, keep the current cutting speed unchanged.

[0077] In this way, the fabric cutting speed can be dynamically adjusted according to the curvature change rate of each monitoring node and the next monitoring node.

[0078] It should be noted that the above-mentioned preset deformation threshold and preset curvature change threshold are obtained by calibration through multiple test experiments on actual cutting equipment in the early stage of method development based on the material type and material characteristics of the fabric. For example, the preset deformation threshold and preset curvature change threshold of light and thin fabrics can be set to 0.5 respectively. , 0.1, set the preset deformation threshold and preset curvature change threshold of heavy fabrics to 2 respectively , 0.2, is used to balance the cropping accuracy and cropping efficiency.

[0079] As a preferred embodiment, the speed adjustment formula is: The fabric cutting adjustment speed is calculated, where 、 are the preset initial speed of fabric cutting and the preset curvature change threshold, is the curvature change rate of the clipping trajectory from the current clipped monitoring node to the next monitoring node, is the preset adjustment coefficient, 、 They are the current fabric cutting speed and the fabric cutting adjustment speed of the next monitoring node respectively.

[0080] It should be noted that the above-mentioned preset adjustment coefficient can also be obtained through experimental calibration and can be exemplarily set to 0.7.

[0081] The embodiment of the present invention dynamically adjusts the cutting speed of the fabric according to the curvature change rate of adjacent monitoring nodes, which not only ensures the cutting efficiency but also avoids problems such as cutting track deviation and edge burrs caused by too fast or too slow speed.

[0082] Reference Figure 2 As shown, the present invention provides a fabric cutting path optimization analysis system, including: a rigid template fixing module, a stress data acquisition module, a fabric deformation analysis module, a dynamic path compensation module, a vacuum adsorption control module and a cutting speed adjustment module.

[0083] The rigid template fixing module is connected to the stress data acquisition module, the stress data acquisition module is connected to the fabric deformation analysis module, the fabric deformation analysis module is respectively connected to the dynamic path compensation module, and the dynamic path compensation module is respectively connected to the cutting speed adjustment module and the vacuum adsorption control module.

[0084] The stress data acquisition module is used to sense the stress data of each monitoring node on the reference cutting path in real time based on the patch stress sensor arranged on the edge of the template, including the stress amplitude and direction angle.

[0085] The fabric deformation analysis module is used to predict the stress change of the next monitoring node to be cut based on the stress data of the currently cut monitoring node and its previous monitoring node, and quantify the fabric deformation parameters under the influence of the stress change.

[0086] The dynamic path compensation module is used to input the fabric deformation parameters of the next monitoring node to be cut into the constructed cutting path offset model, determine the cutting path offset corresponding to the fabric deformation trend of the next monitoring node to be cut, including the offset modulus and offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path.

[0087] The vacuum adsorption control module is used to generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism.

[0088] The cutting speed adjustment module is used to dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

[0089] 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 in the formulas are set by technicians in this field according to actual conditions.

[0090] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0091] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0092] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0093] 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.

[0094] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for optimizing and analyzing cutting paths of clothing fabrics, characterized in that: include: S1. Fix the cutting template on the fabric to be cut and determine the base cutting path of the fabric according to the edge contour of the template; S2. Based on the patch stress sensor arranged on the edge of the template, the stress data of each monitoring node on the reference cutting path is perceived in real time, including the stress amplitude and direction angle; S3. Based on the stress data of the current monitoring node and the previous monitoring node, the stress change of the next monitoring node to be cut is predicted, and the deformation parameters of the fabric under the influence of stress changes are analyzed; S4. Input the deformation parameters of the fabric to be cut into the preset cutting path offset model to determine the deformation trend of the fabric to be cut corresponding to the next monitoring node, including the offset modulus and offset direction angle, so as to perform dynamic path compensation on the fabric reference cutting path; S5. Generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism; S6. Dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

2. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 1, characterized in that: The specific method for predicting the stress change of the next monitoring node to be cut is as follows: Obtain the path lengths from the current trimmed monitoring node to its preceding and following adjacent monitoring nodes, respectively, and record them as the preceding path length and the following path length; Obtain the stress vectors of the currently clipped monitoring node and its previous monitoring node, decompose the stress vectors into normal stress and tangential stress according to the clipping path direction, calculate the normal stress difference and normal stress ratio of the currently clipped monitoring node and its previous monitoring node, and use the ratio of the normal stress difference to the previous path length as the normal stress change rate per unit length; Based on the normal stress change rate per unit length, the subsequent path length, and the normal stress ratio, a cumulative operation is performed to obtain a normal stress prediction value of the next monitoring node. Similarly, a tangential stress prediction value of the next monitoring node can be obtained. The normal stress prediction value and the tangential stress prediction value of the next monitoring node are substituted into the Euclidean norm formula to obtain a stress prediction amplitude of the next monitoring node to be trimmed. Substitute the ratio of the predicted value of the tangential stress and the vertical component of the next monitoring node into the inverse tangent function to calculate the stress prediction direction angle of the next monitoring node to be trimmed.

3. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 2, characterized in that: The quantification process of the fabric deformation parameters under the influence of the stress change includes: Obtaining the elastic modulus of the target fabric, and calculating the fabric deformation prediction modulus based on the stress prediction amplitude and Hooke's law; The stress prediction direction angle of the next monitoring node to be cut is used as the fabric deformation prediction angle.

4. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 1, characterized in that: The construction process of the clipping path offset model includes: Obtain historical fabric deformation modulus data and historical fabric deformation angle data, and normalize them; Dividing the processed historical fabric deformation modulus data and historical fabric deformation angle data into a training set and a test set; The model is trained based on the machine learning algorithm using the training set and the weights of the historical fabric deformation modulus data and the historical fabric deformation angle data are automatically adjusted. By capturing the relationship between the historical stress amplitude data and stress direction angle data and the cutting path offset, a cutting path offset model is constructed. The model is then verified and evaluated using the test set to obtain a trained model.

5. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 4, characterized in that: The specific calculation method of the clipping path offset model is as follows: The clipping path offset model calculation formula is: , , the clipping path offset modulus and offset direction angle can be calculated respectively through the clipping path offset model, where 、 are the normalized fabric deformation prediction modulus and fabric deformation prediction angle, 、 、 、 、 、 、 The weight coefficient set by model training.

6. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 1, characterized in that: The specific method for obtaining the dynamic path compensation for the fabric reference cutting path is as follows: Using the clipping path offset modulus as a clipping path compensation modulus; The half-circle angle corresponding to the offset direction angle is used as the clipping path compensation angle; The compensation modulus is decomposed into the compensation values ​​of the horizontal and vertical coordinates through the sine and cosine values ​​corresponding to the compensation angle. The coordinates of the next monitoring node to be cut are combined with the corresponding compensation values ​​to obtain the corrected coordinates of the next monitoring node to be cut. Calculate the unit normal vector corresponding to the corrected coordinates of the next monitoring node to be cut, and calculate the final cutting correction coordinates of the next monitoring node based on the preset seam reserve width. In this way, the final cutting correction coordinates of each monitoring node on the fabric reference cutting path are obtained one by one, realizing dynamic path compensation of the fabric reference cutting path.

7. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 3, characterized in that: The determining whether to trigger the vacuum adsorption mechanism includes: The rectangular coordinate system is converted into a polar coordinate system, and the predicted deformation amplitude and predicted angle of the fabric are used as the radius and central angle of the predicted deformation affected area respectively. The predicted deformation affected area is calculated based on the sector area formula and used as the deformation evaluation index; If the deformation evaluation index is greater than the preset deformation threshold, the vacuum adsorption mechanism is triggered, otherwise the vacuum adsorption mechanism is kept in a dormant state.

8. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 6, characterized in that: The fabric cutting speed is dynamically adjusted according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process. The specific acquisition method is as follows: Determine the final clipping correction trajectory based on the final clipping correction coordinates of the currently clipped monitoring node and its next monitoring node; Calculate the arc length and the corresponding central angle of the final clipping correction trajectory, and obtain the curvature of the final clipping correction trajectory of the current clipped monitoring node and its next monitoring node based on the curvature calculation formula; Similarly, the curvature of the clipping trajectory of the currently clipped monitoring node and its previous monitoring node can be obtained and recorded as the reference curvature; Compare the difference between the curvature of the final clipped corrected trajectory and the reference curvature with the reference curvature to obtain the curvature change rate; Determine whether the absolute value of the curvature change rate is greater than a preset curvature change threshold. If so, calculate the fabric cutting adjustment speed based on the speed adjustment formula; otherwise, keep the current cutting speed unchanged.

9. The method for optimizing and analyzing cutting paths of clothing fabrics according to claim 8 is characterized in that: The speed adjustment formula is: By the formula The fabric cutting adjustment speed is calculated, where 、 are the preset initial speed of fabric cutting and the preset curvature change threshold, is the curvature change rate of the clipping trajectory from the current clipped monitoring node to the next monitoring node, is the preset adjustment coefficient, 、 They are the current fabric cutting speed and the fabric cutting adjustment speed of the next monitoring node respectively.

10. A clothing fabric cutting path optimization analysis system, characterized in that: include: A rigid template fixing module is used to fix a rigid template showing the shape of the target garment piece on the fabric to be cut, and determine the reference cutting path of the fabric according to the edge contour of the template; A stress data acquisition module is used to sense the stress data of each monitoring node on the reference cutting path in real time based on the patch stress sensors arranged on the edge of the template, including the stress amplitude and direction angle; The fabric deformation analysis module is used to predict the stress change of the next monitoring node to be cut based on the stress data of the current monitoring node and the previous monitoring node, and quantify the fabric deformation parameters under the influence of the stress change; A dynamic path compensation module is used to input the deformation parameters of the fabric at the next monitoring node to be cut into a preset cutting path offset model, determine the cutting path offset corresponding to the deformation trend of the fabric at the next monitoring node to be cut, including the offset modulus and offset direction angle, and thereby perform dynamic path compensation on the fabric reference cutting path; The vacuum adsorption control module is used to generate a deformation evaluation index based on the fabric deformation parameters predicted by each monitoring node to determine whether to trigger the vacuum adsorption mechanism; The cutting speed adjustment module is used to dynamically adjust the fabric cutting speed according to the curvature change rate of adjacent monitoring nodes during the fabric cutting process.

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