An intelligent cutting method for fabrics used in the production of arc-proof clothing

Abstract

The present invention relates to the field of image processing technology, and particularly to an intelligent cutting method for fabrics used in the production of arc-proof clothing. The acquisition method includes: obtaining all the point clouds of the fabric to be cut for the arc-proof clothing, preliminarily determining the overall deformation amount of the fabric to be cut, dynamically setting the local range of each point cloud of the fabric to be cut through the overall deformation amount, determining the local surface based on the local range, calculating the local deformation possibility of each point cloud, and in response to the determination result of whether the fabric to be cut deforms according to the local deformation possibilities of all the point clouds, executing different cutting strategies to achieve intelligent cutting of the fabric to be cut for the arc-proof clothing. This method avoids the disadvantages of traditional image processing being susceptible to the influence of perspective, light, and the interference of complex fabric textures, improves the accuracy of judging fabric deformation, and improves the cutting accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing. Specifically, it relates to an intelligent cutting method for fabrics used in the production of arc-proof clothing. Background Art

[0002] In various electric power operation scenarios, arc-proof clothing is a key piece of equipment to ensure the safety of operators. The cutting process in its manufacturing process is crucial. Currently, the cutting of arc-proof clothing mostly adopts traditional processes. Workers set the cutting paths of the cutting tools in professional cutting software according to the design drawings, convert the shapes and sizes of the protective clothing components into digital instructions, and then place the fabric on the workbench of the cutting equipment. The cutting tool cuts according to the preset paths, speeds, and pressures.

[0003] However, since the fabric of arc-proof clothing needs to have heat resistance and arc resistance properties, it is relatively thick and heavy, and is extremely prone to deformation problems such as deformation, stretching, or shrinkage during the cutting process. If the deformation problem is not detected and cutting is directly carried out, it is easy to use the fabric with deformation problems for subsequent sewing, which will affect the quality of the arc-proof clothing.

[0004] During the cutting process, the traditional method of detecting whether there are deformation problems in the fabric mainly relies on image processing algorithms. The images of the fabric before and after cutting are obtained through an image acquisition device, and the edge detection algorithm is used to identify the edge contour of the fabric, and it is compared with the preset standard contour to determine whether deformation has occurred.

[0005] However, due to the fact that traditional image processing methods are easily affected by factors such as perspective and lighting, the accuracy of deformation detection is affected. For example, when detecting fabric wrinkles, the wrinkle shadows under different lighting conditions will interfere with the judgment of the depth and shape of the wrinkles. And because the fabric fiber structure of arc-proof clothing is complex, the surface texture is rich and irregular, when using traditional image processing methods to identify edges and contours, these complex textures are prone to interference, and the texture is easily misjudged as a deformation edge, resulting in inaccurate judgment of the fabric deformation situation and affecting the cutting accuracy. Summary of the Invention

[0006] To solve the problem that in the cutting process of arc-proof clothing fabric, due to the fact that traditional image processing methods are easily affected by the environment, and the fabric fiber structure of arc-proof clothing is complex, resulting in inaccurate judgment of the fabric deformation situation, and further affecting the cutting accuracy. The present invention proposes an intelligent cutting method for fabrics used in the production of arc-proof clothing, including:

[0007] All point clouds of the fabric to be cut of the arc-proof clothing are obtained by laser scanning, and the overall deformation amount of the fabric to be cut is determined according to the size difference between the minimum bounding box of all point clouds of the fabric to be cut and the minimum bounding box of all point clouds of the standard fabric;

[0008] Dynamically set the local range of each point cloud of the cloth to be cut through the overall deformation amount, determine the local surface based on the local range, and calculate the local deformation possibility of each point cloud:

[0009] ;

[0010] In the formula, is the local deformation possibility of the th point cloud, is the total number of point clouds within the local range of the th point cloud, is the curvature of the local surface of the th point cloud, is the average curvature within the local range of the th point cloud, is the normal vector of the th point cloud, is the normal vector of the th point cloud within the local range of the th point cloud, is and cosine value of the included angle between, is the point cloud density of the local range of the th point cloud, is the average point cloud density within the local range of the th point cloud, is the roughness of the local surface of the th point cloud, is the preset curvature difference threshold, is the absolute value symbol;

[0011] Respond to the determination result of whether the cloth to be cut deforms according to the local deformation possibilities of all point clouds, and execute different cutting strategies to achieve intelligent cutting of the cloth to be cut for the arc-proof clothing.

[0012] The above technical solution obtains point cloud data through laser scanning, which can comprehensively and accurately reflect the three-dimensional shape information of the fabric. Compared with traditional two-dimensional image processing, it can avoid the interference of factors such as viewing angle and illumination, and obtain the actual shape of the fabric more accurately. By comparing the size differences of the minimum bounding boxes of the point clouds of the fabric to be cut and the standard fabric, the overall deformation amount is determined, providing a quantitative basis at the macroscopic level for subsequent analysis of the fabric deformation. And further, the local range of each point cloud is dynamically set according to the overall deformation amount, which can more flexibly adapt to the deformation of different regions of the fabric. And further, based on the local range of each point cloud, local detail features are extracted from the microscopic level. These local detail features are based on the three-dimensional geometric features of the fabric, rather than relying on image gray level and edges like traditional image processing, and can more accurately reflect the true deformation of the fabric, effectively avoiding the interference of complex fabric textures, thereby improving the accuracy of judging fabric deformation. And further, according to the local deformation possibility, the deformation situation of the fabric is determined, and different cutting strategies are executed, realizing intelligent cutting and improving the accuracy and efficiency of fabric cutting in the production process of arc-proof clothing.

[0013] Further, the method for dynamically setting the local range of each point cloud of the fabric to be cut is as follows;

[0014] Calculate the size of the local range of each point cloud;

[0015] , where is the size of the local range of each point cloud, is the size of the minimum bounding box of all point clouds of the fabric to be collected, is an adjustment coefficient greater than 0, is the magnification factor, is the ceiling symbol, is the overall deformation amount of the fabric to be cut, is the threshold value of is the natural exponential function;

[0016] Taking each point cloud as the center, the local range of each point cloud is determined according to the size of the local range of each point cloud.

[0017] Starting from the perspectives of material mechanics and geometric deformation, considering that the arc-proof clothing fabric is a flexible material and the overall deformation is closely related to the local deformation, the size of the local range of each point cloud is dynamically set according to the size of the overall deformation amount, which can not only flexibly control the influence degree of the overall deformation amount on the local range, but also ensure the rationality of the local range setting.

[0018] Further, the result of determining whether the cloth to be cut is deformed according to the local deformation possibility of all point clouds includes: determining whether there is a suspected deformed point cloud in all point clouds in response to the comparison result of the local deformation possibility of each point cloud and a preset local deformation possibility threshold; if there is no suspected deformed point cloud, determining that the cloth to be cut is not deformed; if there is a suspected deformed point cloud, clustering all suspected deformed point clouds to obtain multiple clusters, and taking the area where each cluster is located as a suspected deformation area;

[0019] If the area ratio of all suspected deformation areas in the cloth to be cut is greater than the preset area ratio threshold, it is determined that the cloth to be cut is deformed, and all suspected deformation areas are determined as deformation areas; if the area ratio of all suspected deformation areas in the cloth to be cut is not greater than the preset area ratio threshold, it is determined that the cloth to be cut is not deformed, and there is no deformation area in the cloth to be cut.

[0020] The above technical solution uses a progressive deformation judgment strategy to first locate potential problem areas to clarify the direction for subsequent analysis, then cluster the suspected deformation point clouds and determine the overall deformation based on the area ratio, taking into account both local details and overall status, and comprehensively and accurately grasping the deformation of the fabric. Finally, it provides a direct basis for formulating cutting strategies, allowing cutting to be targetedly adjusted according to the actual status of the fabric, thereby ensuring cutting quality.

[0021] Furthermore, the average curvature in the local range of the point cloud and the average point cloud density in the local range of the point cloud are determined as follows:

[0022] Get the The local range of the point cloud The curvature of each local surface of the point cloud is calculated The mean curvature of all local surfaces of the point cloud is taken as The average curvature in the local range of a point cloud;

[0023] Get the The local range of the point cloud The point cloud density of each local area of ​​the point cloud is calculated The mean of the point cloud density of all local ranges of the point cloud is taken as the The average point cloud density within the local range of a point cloud.

[0024] Furthermore, the method for determining the local surface based on the local range is:

[0025] The surface fitting technology is used to perform surface fitting on all point clouds within the local range of each point cloud to obtain the local surface of the point cloud.

[0026] Further, the method for determining the overall deformation amount of the cloth to be cut is as follows:

[0027] Calculate the deformation rate of the cloth to be cut in the length direction according to the size difference between the minimum bounding box of all the point clouds of the cloth to be cut and the minimum bounding box of all the point clouds of the standard cloth , the deformation rate in the width direction and the deformation rate in the height direction ;

[0028] Calculate the overall deformation amount of the cloth to be cut:

[0029]

[0030] In the formula, is the overall deformation amount of the cloth to be cut, , , are the deformation weights of the cloth to be cut in the length, width, and height directions respectively.

[0031] The above technical solution comprehensively considers the deformation of the cloth in three-dimensional space, and based on the analysis of the force characteristics of the cloth material, introduces the deformation weights of the cloth in different directions, which can more accurately reflect the true deformation state of the cloth and avoid inaccurate judgment of the overall deformation due to ignoring the deformation in a certain direction.

[0032] Further, the method for determining whether there are suspected deformed point clouds in all the point clouds is as follows:

[0033] Preset a local deformation possibility threshold;

[0034] If the local deformation possibility of a certain point cloud is greater than the local deformation possibility threshold, regard this point cloud as a suspected deformed point cloud. If the local deformation possibility of a certain point cloud is not greater than the local deformation possibility threshold, regard this point cloud as a normal point cloud.

[0035] Further, the method for executing different cutting strategies is as follows:

[0036] If the cloth to be cut is deformed, adjust the cutting path to avoid the deformed area; if the cloth to be cut is not deformed, execute the preset cutting path.

[0037] Further, the method for determining the roughness of the local surface is as follows:

[0038] Calculate the variance of the Euclidean distances from all the point clouds within the local range of each point cloud to the local surface of this point cloud, and use this variance as the roughness of the local surface of this point cloud.

[0039] Further, the method for obtaining the deformation weights of the cloth to be cut in the length, width, and height directions is as follows:

[0040] Prepare cloth samples of the same material as the cloth to be cut in advance, apply different tensile forces to the cloth samples in the length, width, and height directions respectively, and record the deformation amounts generated under each tensile force.

[0041] Use curve fitting technology to obtain the relationship curve between the tensile force and the deformation amount of the cloth sample in each direction. Based on the relationship curve, obtain the ratio of the average deformation rate change and the average tensile force change rate of the cloth sample in each direction as the tensile sensitivity of the cloth sample in each direction, and take the sum of the tensile sensitivities in each direction as the total tensile sensitivity.

[0042] Take the ratio of the tensile sensitivities of the cloth sample in the length, width, and height directions and the total tensile sensitivity as the deformation weights of the cloth to be cut in the length, width, and height directions respectively.

[0043] The above technical solution takes into account that the fiber structures and weaving methods of arc-proof clothing fabrics of different materials are different, and there are also differences in the tensile properties in each direction. By conducting tensile tests on cloth samples of the same material, it is possible to deeply understand the tensile characteristics of the cloth to be cut in different directions, and determine the deformation weights based on the physical properties of the cloth in essence, so that the subsequent calculation of the overall deformation amount can better reflect the actual deformation of the cloth.

[0044] The present invention has the following effects:

[0045] The present invention uses laser scanning to obtain point cloud data, avoiding the disadvantages of traditional image processing being easily affected by the viewing angle, illumination, and the interference of complex cloth textures. Through multi-dimensional point cloud data analysis, using the method of first overall and then local, based on the three-dimensional geometric characteristics of the cloth, the actual deformation of the cloth is accurately analyzed, avoiding the interference of complex cloth textures, thereby improving the accuracy of cloth deformation judgment, and adjusting the cutting path according to the accurate deformation judgment result, improving the cutting accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention.

[0048] Refer to Figure 1 , an intelligent cloth cutting method for arc-proof clothing production provided by the present invention includes steps S1 - step S5:

[0049] S1: Three-dimensional point cloud acquisition and preprocessing of the cloth to be cut for arc-proof clothing.

[0050] Use a high-precision laser line scanner to perform a full-range scan on the fabric to be cut for the arc-proof clothing. Given that the fabric of the arc-proof clothing is relatively thick, local occlusion may occur during the scanning process. To ensure the acquisition of complete and accurate point cloud data, the fabric needs to be scanned from multiple angles.

[0051] During the scanning process, due to the influence of various factors, the point cloud data may exhibit abnormal fluctuations, including outliers or noise data. Therefore, to improve the stability and reliability of the data, after the scanning is completed, preprocessing operations need to be performed on all the point cloud data of the fabric to be cut: including using a filtering and denoising algorithm to denoise it, which can effectively avoid the interference of individual outliers, ensure the stability of the point cloud data, and thus ensure the accuracy and reliability of the entire detection scheme, providing high-quality data support for subsequent fabric deformation detection and intelligent cutting.

[0052] S2: Conduct a preliminary overall deformation analysis on the fabric to be cut to determine the overall deformation amount of the fabric to be cut.

[0053] The minimum bounding box is the smallest cuboid that can completely enclose all the point cloud data in three-dimensional point cloud data. It is used to describe the spatial range and shape characteristics of the point cloud data as a whole. Therefore, by analyzing the minimum bounding box of all the point cloud data of the fabric to be cut, the overall deformation situation of the fabric to be cut can be obtained.

[0054] Specifically, it includes the following steps:

[0055] S21: Obtain the minimum bounding boxes of all the point cloud data of the fabric to be cut and the standard fabric respectively.

[0056] Pre-obtain a fabric with the same size as the fabric to be cut and meeting the standards (no deformation on the surface) as the standard fabric, and obtain all the point cloud data of the standard fabric according to the operations in step S1.

[0057] Obtain the minimum bounding box of all the point cloud data of the fabric to be cut, and record its length, width, and height as 、 、 , and obtain the minimum bounding box of all the point cloud data of the standard fabric, and its length, width, and height are 、 、 .

[0058] S22: Determine the overall deformation amount of the fabric to be cut according to the differences between the dimensions of the minimum bounding box of all the point cloud data of the fabric to be cut and the dimensions of the minimum bounding box of all the point cloud data of the standard fabric.

[0059] Specifically, it includes:

[0060] S221: Calculate the deformation rates of the cloth to be cut in each direction.

[0061] Calculate the deformation rate of the cloth to be cut in the length direction:

[0062]

[0063] In this formula, is the deformation rate of the cloth to be cut in the length direction, is the absolute value symbol.

[0064] Calculate the deformation rate of the cloth to be cut in the width direction:

[0065]

[0066] In this formula, is the deformation rate of the cloth to be cut in the width direction, is the absolute value symbol.

[0067] Calculate the deformation rate of the cloth to be cut in the height direction:

[0068]

[0069] In this formula, is the deformation rate of the cloth to be cut in the height direction, is the absolute value symbol.

[0070] S222: Determine the deformation weights of the cloth to be cut in each direction.

[0071] The deformation weights of the cloth to be cut in each direction are determined according to the stretching sensitivities of the cloth to be cut in each direction. When analyzing the possibility of local deformation of the cloth, the stretching sensitivity is an important reference. The higher the stretching sensitivity of the cloth to be cut in a certain direction, it means that the cloth to be cut is more likely to deform when stressed in that direction. In the case of complex stress in the local area, the possible deformation trend of the local area can be judged more accurately based on the stretching sensitivities in each direction, improving the accuracy of local deformation analysis.

[0072] Prepare in advance a cloth sample of the same material as the cloth to be cut, apply different tensile forces (gradually increasing tensile forces) to the cloth sample in the length, width, and height directions respectively, and record the deformation amounts generated by the cloth sample under each tensile force in each direction.

[0073] First, the curve fitting technique is used to obtain the relationship curve between the tensile force and the deformation amount of the fabric sample in each direction (hereinafter simply referred to as the relationship curve in each direction). Since there are a total of the length direction, the width direction, and the height direction, 3 relationship curves in 3 directions will be obtained. Moreover, the horizontal axis of the relationship curve in each direction is the gradually increasing tensile force, and the vertical axis is the deformation amount generated by the fabric sample under each tensile force.

[0074] Then, on the relationship curve in each direction, a deformation rate change is calculated for every two deformation amounts, and a tensile force change rate is calculated for every two tensile forces. According to this logic, all the deformation rate changes and all the tensile force change rates in the relationship curve in each direction can be obtained. Further, the average deformation rate change and the average tensile force change rate are obtained, and the ratio of the average deformation rate change to the average tensile force change rate is used as the tensile sensitivity of the fabric sample in each direction. Since the fabric to be cut and the fabric sample are of the same material, the tensile sensitivity of the fabric sample in each direction is also the tensile sensitivity of the fabric to be cut in each direction.

[0075] Here, considering that the arc-proof fabric has special fiber structures and weaving methods, and there are differences in the tensile properties in each direction, by conducting tensile tests on fabric samples of the same material in different directions, the tensile sensitivities of the fabric to be cut in the length, width, and height directions can be accurately obtained, and then the deformation weights can be determined, effectively reflecting the anisotropy of the fabric and making up for the overall deformation judgment error that may be caused by not considering the direction differences.

[0076] Finally, the tensile sensitivity of the fabric sample in the length direction, the tensile sensitivity of the fabric sample in the width direction, and the tensile sensitivity of the fabric sample in the height direction are respectively denoted as 、 and . Calculate the deformation weights of the fabric to be cut in the length, width, and height directions respectively:

[0077]

[0078] In this formula, is the deformation weight of the fabric to be cut in the length direction.

[0079]

[0080] In this formula, is the deformation weight of the fabric to be cut in the width direction.

[0081]

[0082] In this formula, is the deformation weight of the fabric to be cut in the height direction.

[0083] Here, the stretching sensitivity of the cloth to be cut in each direction is divided by the total stretching sensitivity to obtain the deformation weight in each direction, which can reflect the relative proportion of the stretching sensitivity in each direction in the whole. The contributions of the cloth in different directions to the overall deformation are different, and this calculation method can reasonably reflect the relative importance of the stretching sensitivity in each direction in the overall deformation. For example, if the stretching sensitivity in the length direction accounts for a relatively large proportion in the total stretching sensitivity, it indicates that the length direction has a greater impact on the overall deformation, and a higher weight is assigned to it when calculating the overall deformation amount, making the result more in line with the actual situation.

[0084] S223: Obtain the overall deformation amount of the cloth to be cut by integrating the deformation rates and deformation weights in each direction of the cloth to be cut.

[0085] Specifically, the overall deformation amount of the cloth to be cut is determined based on the following formula:

[0086]

[0087] In this formula, is the overall deformation amount of the cloth to be cut, , , are the deformation weights of the cloth to be cut in the length, width, and height directions. Since the value of the deformation rate is in the interval, and the value of the deformation weight is in the interval, , then by performing a weighted average operation on the deformation rates of the cloth to be cut in each direction, it can be ensured that is in the interval.

[0088] Since the cloth to be cut of the arc-proof clothing may deform in the length, width, and height directions during the cutting process, it is necessary to comprehensively consider the deformation rates of the cloth to be cut in each direction to avoid only focusing on the deformation in a single direction and ignoring the influence of other directions. This formula comprehensively presents the deformation situation of the cloth in three-dimensional space and provides a basis for accurately grasping the overall morphological changes of the cloth.

[0089] S3: Conduct a local deformation analysis on the cloth to be cut to obtain the local deformation possibility of each point cloud.

[0090] Arc-proof clothing fabrics have the characteristics of diverse fiber composition, special weaving method, and complex surface texture to meet special performance requirements such as arc protection and high temperature resistance. This complex structure makes it easy for the overall deformation of the fabric to be cut to be within an acceptable range during the cutting process, but local areas of the fabric to be cut are still deformed. For example, some parts of the fabric to be cut may have slight misalignment, wrinkles or stretching between fibers due to uneven local force. If these local deformations are not detected, quality problems may occur in the subsequent production of arc-proof clothing.

[0091] The overall deformation and local deformation of the fabric to be cut for arc protection clothing are closely related:

[0092] From the perspective of material mechanics, when the fabric to be cut for arc protection clothing has a large overall deformation, it is largely because some local areas of the fabric have undergone significant deformation. Since the fabric of arc protection clothing is composed of multiple fibers through a special weaving method, its internal structure is not completely uniform. When subjected to external forces, the fibers in local areas are more likely to be dislocated, slipped or broken. These local changes accumulate and lead to an increase in the overall deformation. For example, at some weaving nodes of the fabric, the fibers are interwoven to different degrees of tightness. When subjected to force, the fibers near these nodes may first undergo small displacements. As the external force continues to act, these local small displacements gradually accumulate and eventually manifest as a large overall deformation. The significant deformation of these local areas will become a potential hidden danger that affects the protective performance of arc protection clothing. The protection principle of arc protection clothing depends on the integrity of its fabric structure. Abnormal changes in fibers in local areas will destroy the original tight structure of the fabric, making it easier for arcs and high temperatures to penetrate the fabric, thereby reducing the arc protection clothing's ability to block arcs and high temperatures.

[0093] From the perspective of geometric deformation, when the overall deformation of the fabric to be cut for arc protection clothing is large, it usually means that it is subjected to a large external force. Due to the diverse fiber composition and special weaving method of arc protection clothing fabrics, it has obvious unevenness when subjected to force. In the process of being subjected to external forces such as stretching, bending or torsion, the stress and strain borne by different parts of the fabric are not the same. For example, during the stretching process, some fiber bundles may be subjected to greater tension, while the fiber bundles in adjacent areas are relatively less stressed, which leads to large differences in tensile and compressive deformations in different parts. In this case, local areas are more likely to have concentrated and obvious deformations. Such concentrated and obvious deformations in local areas will have an adverse effect on the durability and protective effect of arc protection clothing.

[0094] It can be seen that the overall deformation amount of the cloth to be cut can, to a certain extent, reflect the possibility of its local deformation. There is a close mutual relationship between the overall deformation and the local deformation. Considering this relationship fully during the deformation analysis is of great significance for accurately detecting the cloth deformation, optimizing the cutting process, and ensuring the quality and performance of the arc-proof clothing.

[0095] Therefore, in this step, fine local deformation analysis is performed on each point cloud to determine whether there are minor local deformations in the cloth to be cut, so as to improve the accuracy of deformation analysis and subsequent cutting.

[0096] Specifically, it includes the following steps:

[0097] S31: Dynamically set the local range of each point cloud according to the magnitude of the overall deformation amount of the cloth to be cut.

[0098] The local range of the point cloud provides a reasonable spatial boundary for extracting local detail features. When analyzing the local detail features of each point cloud, a reasonable local range can reflect the true deformation situation near the point cloud. If the local range is too large, the interference from distant point clouds will cause the calculated features to deviate from the actual situation; if the local range is too small, the data information contained is insufficient and the feature representativeness is poor. Therefore, it is necessary to set an appropriate local range to provide a reliable reference range for accurate local deformation analysis.

[0099] Therefore, when performing deformation analysis on the cloth to be cut, first set the threshold of the overall deformation amount of the cloth to be cut as (empirical value).

[0100] When it indicates that the overall deformation of the cloth to be cut is in a relatively small state. In this case, the local deformation of the cloth to be cut shows relatively uniform and minor characteristics, and the complexity of the deformation in the local area is relatively low. At this time, it is a more reasonable strategy to set a larger local range for each point cloud. The reason is that under the condition of relatively small overall deformation, within a larger local range for each point cloud, the point cloud data changes relatively smoothly and will not be interfered by local abnormal changes to the analysis results. By setting a larger local range, more point cloud data can be covered in one analysis process. This means that there is no need to analyze each small neighborhood of each point cloud individually, thereby reducing the total number of analyses and improving the calculation efficiency. For example, in the cloth to be cut, there is a local area with uniform deformation. The deformation characteristics reflected by each point cloud within a larger neighborhood in this local area are similar. Therefore, it is suitable to analyze with a larger local range, thus saving computing resources and time costs.

[0101] When When it is, it indicates that the overall deformation of the cloth to be cut has reached a relatively large degree. In this case, it often means that there are more complex local deformations in the cloth to be cut. In order to improve the analysis accuracy of local deformations, a smaller local range should be set for each point cloud. Since the overall deformation amount is large, it indicates that the deformation differences between different regions inside the cloth to be cut may be very significant, and complex situations such as stress concentration and fiber misalignment are very likely to occur in local regions. At this time, a smaller local range can more accurately focus on the local features around each point cloud, effectively avoiding being interfered by other larger deformation differences, and then more accurately analyzing the local deformation situation. For example, in the concentrated areas of deformations such as wrinkles, stretching, or compression of the cloth to be cut, a smaller local range can more carefully capture the detailed information of these local deformations.

[0102] Therefore, based on the above content, for each point cloud of the cloth to be cut, the size of the local range of each point cloud is determined according to the following formula:

[0103]

[0104] In the formula, is the size of the local range of each point cloud (the size of length or width or height), is the size of the minimum bounding box of all point clouds of the cloth to be collected (the size of length or width or height), and and both represent the sizes in the same dimension, that is, when calculating the length of the local range of each point cloud, represents the length of the local range of each point cloud, is the length of the minimum bounding box of all point clouds of the cloth to be collected; when calculating the width of the local range of each point cloud, represents the width of the local range of each point cloud, is the width of the minimum bounding box of all point clouds of the cloth to be collected; when calculating the height of the local range of each point cloud, represents the height of the local range of each point cloud, is the height of the minimum bounding box of all point clouds of the cloth to be collected. is an adjustment coefficient greater than 0, used to control the degree of influence of the overall deformation amount on the size of the local range of each point cloud. Here, (empirical value), is a magnification coefficient, used to ensure that the local range of each point cloud is much smaller than the size of the minimum bounding box of all point clouds of the cloth to be cut, The value range of (empirical value), is the ceiling symbol, is the overall deformation amount of the cloth to be cut, is the threshold value of is the natural exponential function.

[0105] In this formula, reflects the difference between the overall deformation of the cloth to be cut and the threshold value. According to the magnitude of this difference, the size of the local range of each point cloud is dynamically adjusted. And during the setting process, taking the size of the minimum bounding box as a reference point, while ensuring that the size of the local range of each point cloud is much smaller than the size of the minimum bounding box, when the overall deformation is large, a smaller local range is set for each point cloud; when the overall deformation is small, a larger local range is set for each point cloud.

[0106] Specifically:

[0107] When it indicates that the overall deformation of the cloth to be cut is large, and there may be complex local deformations in the cloth to be cut. At this time , will increase as increases. Due to 's amplification effect, the value of will increase rapidly, so that 's value will decrease significantly as increases, making the calculated smaller at this time (the size of the local range of each point cloud is much smaller than the size of the minimum bounding box), and smaller than the calculated when , which conforms to the logic of setting a smaller overall deformation when the overall deformation of the cloth to be cut is large.

[0108] For example, when ; ;

[0109] ; ;

[0110] At this time, the size of the local range of each point cloud is set to times the size of the minimum bounding box of all point clouds of the cloth to be cut and rounded up. Compared with the calculated when the overall deformation of the cloth to be cut is small , it is still smaller.

[0111] When it indicates that the overall deformation of the cloth to be cut is small. At this time, the local deformation of the cloth is relatively uniform and small, and the deformation of the local area is not complex. At this time, , as decreases, The absolute value of increases. Since for the natural exponential function . Therefore, will approach 0 as decreases. At this time, the amplification effect of is relatively weak, and the value of will increase as decreases (approach 1 and be greater than 1). Then the value of will slightly decrease as decreases, making the calculated at this time also slightly decrease. At this time, the calculated is still larger compared to the

[0112] For example, when . .

[0113] . .

[0114] At this time, set the size of the local range of each point cloud to be rounded up to 0.15 times the size of the minimum bounding box of all the point clouds of the cloth to be cut. When the overall deformation of the cloth to be cut is relatively large The calculated is still relatively large compared to

[0115] Through the above solution, when the overall deformation of the cloth to be cut is small, a relatively large local range is set. This can not only utilize the characteristic of stable change of point cloud data, cover more point clouds, reduce the number of analyses to improve the calculation efficiency, but also ensure that the local range is much smaller than the size of the minimum bounding box, avoiding interference from too many distant point clouds and ensuring the accuracy of the analysis. When the overall deformation is large, a small local range is set, precisely focusing on the local complex deformation area, effectively avoiding interference from large deformation differences outside the neighborhood, improving the analysis accuracy, and also meeting the requirement that the local range is much smaller than the size of the minimum bounding box, making the analysis more targeted.

[0116] On the one hand, it avoids the analysis error caused by too large a local range. On the other hand, it ensures that in different overall deformation situations, it can effectively focus on the local characteristics of the cloth for analysis, providing a reliable basis for accurately judging the cloth deformation and reasonably adjusting the cutting path.

[0117] Calculate the dimensions of the local range of each point cloud according to the formula, that is, the length, width and height of the local range. Finally, with each point cloud as the center, obtain the local range of each point cloud according to the dimensions of the local range. The finally obtained local range is a cuboid range centered on each point cloud. For example, for the th point cloud, when the dimensions (length, width, height) of its local range are 5, 4, and 3 respectively, then with the th point cloud as the center, obtain a cuboid range with a length of 5, a width of 4, and a height of 3, and use this cuboid range as the local range of this point cloud.

[0118] S32: Extract the local detail features of each point cloud according to the local range of each point cloud.

[0119] First, for each point cloud, use the surface fitting technology to perform surface fitting on all the point clouds within the local range of this point cloud, and use the fitted surface as the local surface of this point cloud. Specifically, use the least squares method to perform surface fitting on all the point clouds within the local range of this point cloud, or the radial basis function can also be used to perform surface fitting on all the point clouds within the local range of this point cloud.

[0120] The surface of the arc-proof clothing fabric has a complex geometry. Using the surface fitting technology to obtain the local surface of each point cloud can effectively extract the geometric features of the fabric to be cut in the area near this point cloud. Through surface fitting, the discrete point cloud is transformed into a continuous surface model, intuitively presenting the curvature and shape changes of the fabric surface. For example, at the fabric folds, the local surface can clearly show the curvature and trend of the folds, providing an intuitive basis for analyzing the deformation in this area.

[0121] Next, obtain the normal vectors of each point cloud and calculate them. The normal vector is defined as the vector perpendicular to the tangent plane of the surface at a specific point, and this vector contains the directional characteristics of the surface at that point. The change in the direction of the normal vector can intuitively reflect the change in the normal direction of the surface of the fabric to be cut. Since the fabric to be cut is composed of fibers, by analyzing the change in the direction of the normal vector, the arrangement direction of the fibers inside the fabric to be cut can be further inferred. When the direction of the normal vectors of all the point clouds within the local range of a certain point cloud changes significantly, it is very likely that the fiber arrangement in the area corresponding to this local range of the fabric to be cut is relatively disordered, because the irregularity of the fiber arrangement will cause a greater difference in the direction of the tangent plane of the surface at different points, resulting in a significant change in the direction of the normal vector. In addition, when the direction of the normal vectors of all the point clouds within the local range of a certain point cloud changes significantly, in addition to the possibility of disordered fiber arrangement, it may also indicate that the area corresponding to this local range of the fabric to be cut has been subjected to external forces, because external forces will change the shape and internal structure of the fabric, thereby affecting the tangent plane of the surface and ultimately being reflected in the change of the normal vector. For example, when the fabric to be cut is twisted or unevenly stretched, the direction of the normal vector in the corresponding area will change significantly.

[0122] Then, for each point cloud, calculate the curvature of the local surface based on the geometric properties of its local surface. Specifically, based on the geometric properties of the surface, the curvature is approximately calculated by analyzing the normal vector and the bending characteristics of the surface. Obtain the normal vectors at each point cloud corresponding to the local surface, and determine the principal curvature direction by analyzing the bending degree of the surface in different normal vector directions. Finally, calculate the value of the principal curvature based on the bending degree of the surface in the principal curvature direction, and use this as the curvature of the local surface.

[0123] Curvature, as a quantity used to describe the bending degree of a curve or surface, has a clear physical meaning in different dimensions. In the context of a three-dimensional surface, curvature reflects the bending degree of the surface at a specific point. By calculating the curvature of the local surface of each point cloud, the deformation condition of the fabric to be cut near this point can be deeply understood. Generally speaking, areas with a larger curvature often mean that there are obvious deformations in the fabric to be cut in this area. For example, there may be folds or severe stretching. Folds will cause a complex bending shape on the surface of the fabric to be cut, resulting in an increase in the curvature of the local surface; similarly, severe stretching will change the original shape of the fabric, causing a significant change in the bending degree of the local area, which is then reflected as an increase in the curvature value. This method of judging the deformation degree of the fabric by curvature provides an important quantitative basis for accurately identifying the local deformation of the fabric.

[0124] Next, obtain the point cloud density within the local range of each point cloud. For each point cloud, calculate the average distance between the point cloud and all point clouds within its local range to reflect the point cloud density around the point. The smaller the average distance, the higher the point cloud density. To obtain a more intuitive representation of the point cloud density, take the reciprocal of the average distance as the point cloud density.

[0125] Point cloud density is an important indicator reflecting the tightness of the spatial distribution of the point cloud. A relatively large point cloud density within the local range of a certain point cloud indicates that the point cloud in this local range is relatively dense. Analyzing from the actual situation of the fabric, a dense distribution of the point cloud often implies that the fabric in this area may have been subjected to a squeezing effect. Because during the squeezing process, the local space of the fabric is compressed, and the originally relatively evenly distributed point cloud will gather together, resulting in an increase in the point cloud density. Conversely, when the point cloud density is small, it indicates that the point cloud in this area is relatively sparse. This sparse distribution usually indicates that the fabric may have undergone a stretching process in this area, because stretching will expand the local range of the fabric, and the point cloud is distributed in a larger space, thus reducing the point cloud density. Therefore, the local range where the point cloud density increases or decreases sharply is more likely to have local deformation compared to the local range where the point cloud density changes smoothly.

[0126] Finally, the roughness of the local surface of each point cloud is also an important indicator reflecting the deformation of the fabric to be cut. Even if the curvatures of the local surfaces of different point clouds are the same, the difference in the roughness of the surfaces can reveal the differences in the microscopic state of the fabric surface. When the local surface is relatively rough, it often means that there are more microscopic unevennesses on the fabric surface, and this microscopic unevenness is a specific manifestation of local deformation. It may be due to external forces, resulting in local displacement or arrangement changes of the fabric fibers, and then forming microscopic unevenness on the surface. By analyzing the roughness of the local surface of the point cloud, a more comprehensive understanding of the local deformation of the fabric surface can be obtained, providing more abundant information for accurately judging the overall deformation of the fabric.

[0127] Specifically, for each point cloud, first calculate the variance of the Euclidean distances from all point clouds within the local range of the point cloud to the local surface of the point cloud, and use this variance as the roughness of the local surface of the point cloud. The variance of the distance can effectively quantify the degree of dispersion of the distances from the point cloud to the local surface. The unevenness of the fabric surface to be cut is manifested as: there are differences in the distances between all point clouds within the local range of each point cloud and the local surface of the point cloud. The more differences there are, the greater the degree of dispersion of these distances, that is, the greater the variance of the distances, which also means that the microscopic unevenness of the fabric surface is more serious and the roughness is higher; conversely, the smaller the variance, the more concentrated the distances, the smoother the surface, and the lower the roughness.

[0128] S33: Determine the local deformation possibility of each point cloud based on the local detail features of each point cloud.

[0129] When analyzing the local surface of each point cloud, a key point is that even if the curvatures of the local surfaces of different point clouds are the same, there may still be significant differences in the roughness of the surfaces. Therefore, when comprehensively analyzing the local deformation possibility of each point cloud, it is possible to determine whether to exclude the influence of curvature differences on the local deformation possibility based on the magnitude of the curvature differences of the local surfaces of different point clouds. When the curvature differences are very small, it indicates that the bending degree of the local surface of the point cloud is closer to the surrounding average level. At this time, the influence of curvature differences on the local deformation possibility is relatively small, while the influence of other factors (such as point cloud density, normal vector direction, etc.) on the local deformation possibility is more significant. Therefore, the dimension of curvature differences can be ignored when calculating the local deformation possibility. On the contrary, when the curvature differences are large, the contribution of curvature differences to the local deformation possibility needs to be retained. However, regardless of whether the curvature differences are large or small, when calculating the local deformation possibility, the dimension of the roughness of the surface must always be retained, and through the synergistic effect of roughness on other factors, the deformation possibility is highlighted.

[0130] First, analyze the relative difference between the curvature of the local surface of each point cloud and the average curvature within the local range of the point cloud. When the relative difference is large, it indicates that the bending degree of the local surface of the point cloud is significantly different from the average level, indicating that there may be severe folds or stretching within the local range of the point cloud. Therefore, the contribution to the local deformation amount is large; on the contrary, when the relative difference is small, it means that the bending degree of the local surface of the point cloud is close to the average level, indicating that the local range of the point cloud is relatively flat. Therefore, the contribution to the local deformation amount is small.

[0131] Specifically, the calculation formula for the relative difference between the curvature of the local surface of the

[0132]

[0133] th point cloud and the average curvature within the local range of the point cloud is: In this formula, is the curvature of the local surface of the th point cloud, is the average curvature within the local range of the th point cloud, and

[0134] is the absolute value symbol. Next, according to the relative difference between the curvature of the local surface of the th point cloud and the average curvature within the local range of the point cloud, the calculation method of the local deformation possibility of the

[0135] th point cloud is divided into two types. The first type, when The relative difference between the curvature of the local surface of a point cloud and the average curvature within the local range of the point cloud is small, and the degree of bending of the local surface of the th point cloud is relatively close to the average degree of bending of the local range where it is located. At this time, the relative difference between the curvature of the local surface of the th point cloud and the average curvature within the local range of the point cloud has a relatively small impact on the possibility of local deformation. When calculating the possibility of local deformation, the influence of this part is ignored. This is because in this case, other factors such as point cloud density and normal vector direction have a more prominent impact on local deformation. For example, in a relatively flat area of the fabric, although the curvature difference is small, the change in point cloud density may reflect potential stretching or squeezing conditions. At this time, paying attention to other factors can more accurately judge the possibility of local deformation.

[0136] Therefore, the calculation formula for the possibility of local deformation of the th point cloud is:

[0137]

[0138] In this formula, is the possibility of local deformation of the th point cloud, and its numerical value reflects the possibility of deformation occurring in the local area where the point cloud is located. is the total number of point clouds within the local range of the th point cloud, is the curvature of the local surface of the th point cloud, which intuitively reflects the degree of bending of the local surface of the point cloud. For example, in the wrinkled area of the fabric, usually has a larger value, indicating that the bending here is more intense. is the average curvature within the local range of the th point cloud, and this average curvature represents the overall bending trend of the local range. is the normal vector of the th point cloud, is the normal vector of the th point cloud within the local range of the th point cloud, is the cosine value of the angle between and , and the angle is set to use The values within the interval are represented because for the cloth to be cut, the cloth surface is continuous and smoothly transitional (even in the presence of wrinkles, etc., it is continuously changing). Adjacent point clouds represent adjacent positions on the cloth surface. Due to the continuity of the cloth, the normal vector directions of adjacent point clouds do not have sudden and extreme turns. Therefore, the angle between the normal vectors usually does not exceed 180 degrees. is the point cloud density within the local range of the -th point cloud, is the average point cloud density within the local range of the -th point cloud, is the roughness of the local surface of the -th point cloud, is the preset curvature difference threshold, set to 0.3 (empirical value), is the absolute value symbol.

[0139] In this formula, the method for obtaining the average curvature is as follows: Obtain the curvatures of the local surfaces of each of the point clouds within the local range of the -th point cloud, and calculate the average of the curvatures of all the local surfaces of the point clouds as the average curvature within the local range of the -th point cloud.

[0140] In this formula, the method for obtaining the average point cloud density is as follows: Obtain the point cloud densities of the local ranges of each of the point clouds within the local range of the -th point cloud, and calculate the average of the point cloud densities of all the local ranges of the point clouds as the average point cloud density within the local range of the -th point cloud.

[0141] In this formula, calculates the average of the cosine values of the angles between the normal vector of the -th point cloud and the normal vectors of all the point clouds within its local range. Since the cosine function is monotonically decreasing in the interval, the larger this average value, the smaller the angle between the normal vector of the -th point cloud and the normal vectors of all the point clouds within its local range, indicating that the directions of the normal vectors of all the point clouds within this local range are more consistent, and the area of the cloth to be cut corresponding to this local range is probably relatively flat and the possibility of local deformation is small; conversely, when this average value is smaller, it means that the directions of the normal vectors of all the point clouds within the local range change more, suggesting that there may be disordered fiber arrangement or complex external forces acting on the area of the cloth to be cut corresponding to this local range, and the possibility of local deformation is greater. Therefore, by constructing and Negative correlation

[0142] In this formula , this part calculates the relative difference between the point cloud density in the local range of the -th point cloud and the average point cloud density in the local range. When this value is greater than 1, it indicates that the point cloud in this local range is relatively dense, and it means that the corresponding position of the cloth to be cut may be squeezed in this local range. When this value is less than 1, it indicates that the point cloud in this local range is relatively sparse, and the corresponding position of the cloth to be cut in this local range may be stretched. Through this relative difference, the influence of the change in point cloud density on the local deformation amount is reflected.

[0143] Second, when , it indicates that the relative difference between the curvature of the local surface of the -th point cloud and the average curvature in the local range of this point cloud is relatively large, and there is a significant difference between the bending degree of the local surface of the -th point cloud and the average bending degree in the local range of this point cloud. For example, at the folds of the cloth, the curvature difference is often relatively large. At this time, the relative difference between the curvature of the local surface of the -th point cloud and the average curvature in the local range of this point cloud has a relatively large influence on the possibility of local deformation. When calculating the possibility of local deformation, the influence of this part is retained.

[0144] Therefore, the calculation formula for the possibility of local deformation of the -th point cloud is:

[0145]

[0146] The meaning of each character in this formula is exactly the same as the meaning of the characters in the previous formula.

[0147] Through the collaborative analysis of multiple factors, the local deformation characteristics of the cloth under the action of different external force combinations can be accurately captured. For example, when the cloth to be cut is simultaneously subjected to extrusion and torsion, the point cloud density will increase due to extrusion, the direction of the normal vector will be disordered due to torsion, the curvature will also change, and the roughness may change due to factors such as surface friction. By comprehensively considering multiple factors related to the local deformation of the cloth, such as curvature difference, normal vector direction difference, point cloud density difference, and surface roughness, the local deformation situation of the cloth can be comprehensively described from multiple angles. Compared with the method that only considers a single factor, it can more accurately reflect the actual local deformation degree.

[0148] In addition, for the convenience of comparison, the maximum and minimum values of the local deformation possibilities of all point clouds are obtained, and the minimum-maximum normalization method is used to normalize the local deformation possibility of each point cloud, so that the numerical value of the local deformation possibility of each point cloud is within within the interval

[0149] S4: Determine whether the cloth to be cut deforms according to the local deformation possibilities of all point clouds.

[0150] First, determine whether there are suspected deformed point clouds among all point clouds:

[0151] Preset the local deformation possibility threshold to 0.6 (empirical value); if the local deformation possibility of a certain point cloud is greater than 0.6, the higher the possibility that the cloth to be cut deforms at the position corresponding to this point cloud, and this point cloud is regarded as a suspected deformed point cloud; if the local deformation possibility of a certain point cloud is less than or equal to 0.6, the lower the possibility that the cloth to be cut deforms at the position corresponding to this point cloud, and this point cloud is regarded as a normal point cloud.

[0152] Next, analyze among all point clouds. If there are no suspected deformed point clouds, it is determined that the cloth to be cut has not deformed; if there are suspected deformed point clouds, use the iterative self-organizing clustering algorithm, set an appropriate neighborhood radius to 0.05 meters (because the scanning accuracy of obtaining point clouds by laser scanning is relatively high, the point cloud distribution is relatively dense, and a smaller neighborhood radius can accurately identify adjacent data points), set the minimum number of points to 5 (because all point cloud data has been preprocessed, the data quality is good, and the accuracy of the point cloud is relatively high, and a smaller number of points can represent a valid clustering cluster), and divide all suspected deformed points into different clustering clusters through this clustering algorithm, and regard the area where each clustering cluster is located as a suspected deformed area.

[0153] Finally, preset the area ratio threshold to (empirical value). If the area ratio of all suspected deformed areas in the cloth to be cut is greater than , it is determined that the cloth to be cut has deformed, and all suspected deformed areas are determined as deformed areas; if the area ratio of all suspected deformed areas in the cloth to be cut is less than or equal to , it means that the current cloth to be cut is relatively flat as a whole and there is no obvious deformation. It is determined that the cloth to be cut has not deformed. Therefore, there is no deformed area for the cloth to be cut.

[0154] S5: Execute different cutting strategies according to different judgment results to achieve intelligent cutting of the cloth to be cut for the arc-proof clothing.

[0155] If the judgment result shows that the cloth to be cut has deformed, the system will immediately issue a notice to inform the staff that there is a deformation in the current cloth. The staff needs to re-adjust the cutting path according to the specific deformation situation of the cloth to avoid the deformed area. This is because if the deformed area is not avoided during the cutting process, it will affect the quality of the final protective clothing. For example, cutting in the deformed area may cause changes in the physical properties of the cloth, reducing its protection ability against electric arcs and high temperatures, or causing deviations in the shape of the protective clothing, affecting the comfort and safety of wearing.

[0156] If the judgment result shows that the cloth to be cut has not deformed, the pre-set cutting path will be directly executed. The pre-set cutting path is formulated based on the standard cloth and the design requirements of the protective clothing, and can ensure that the shape and size of the cut cloth precisely meet the standards for making arc-proof clothing.

[0157] Through the above series of steps, that is, first accurately judging the overall deformation, deeply analyzing the local deformation on the basis of the overall deformation analysis, and finally clustering the deformation positions according to the judgment results of the local deformation, it provides comprehensive, accurate and targeted information for the adjustment of the arc-proof clothing cloth cutting process.

[0158] Although this specification has shown and described multiple embodiments of the present invention, it is obvious to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will think of many changes, alterations and alternative ways without departing from the spirit and idea of the present invention. It should be understood that various alternative solutions to the embodiments of the present invention described herein can be adopted in the practice of the present invention.

Claims

1. An intelligent cutting method for fabrics used in arc protection clothing production, characterized in that: include: All point clouds of the fabric to be cut of the arc protection suit are obtained by laser scanning. The overall deformation of the fabric to be cut is determined according to the size difference between the minimum bounding box of all point clouds of the fabric to be cut and the minimum bounding box of all point clouds of the standard fabric. The specific method is as follows: According to the size difference between the minimum bounding box of all point clouds of the cloth to be cut and the minimum bounding box of all point clouds of the standard cloth, the deformation rate of the cloth to be cut in the length direction is calculated. , Deformation rate in width direction and the deformation rate in the height direction ; Calculate the overall deformation of the cloth to be cut: ； In the formula, is the overall deformation of the cloth to be cut, , , are the deformation weights of the cloth to be cut in the length, width and height directions respectively; The local range of each point cloud of the cloth to be cut is dynamically set by the overall deformation amount, the local surface is determined based on the local range, and the local deformation possibility of each point cloud is calculated: ； In the formula, For the The local deformation possibility of a point cloud, For the The total number of point clouds within the local range of a point cloud, For the The curvature of the local surface of the point cloud, It is The average curvature in the local range of the point cloud, For the The normal vector of the point cloud, For the In the local area of ​​the point cloud The normal vector of the point cloud, for and The cosine of the angle between For the The point cloud density of the local area of ​​the point cloud, For the The average point cloud density in the local area of ​​the point cloud, For the The roughness of the local surface of a point cloud, is the preset curvature difference threshold, is the absolute value symbol; In response to the determination result of whether the cloth to be cut generates deformation according to the local deformation possibility of all point clouds, different cutting strategies are executed to realize intelligent cutting of the cloth to be cut of the arc protection clothing.

2. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 1 is characterized in that: The method of dynamically setting the local range of each point cloud of the cloth to be cut is; Calculate the size of the local range of each point cloud; , where is the size of the local range of each point cloud, is the size of the minimum bounding box of all point clouds of the cloth to be collected, is an adjustment factor greater than 0, is the magnification factor, is the round-up symbol, is the overall deformation of the cloth to be cut, for The threshold value, is the natural exponential function; Taking each point cloud as the center, the local range of each point cloud is determined according to the size of the local range of each point cloud.

3. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 1, characterized in that: The determination result of whether the cloth to be cut is deformed according to the local deformation possibility of all point clouds includes: determining whether there is a suspected deformed point cloud in all point clouds in response to the comparison result of the local deformation possibility of each point cloud and a preset local deformation possibility threshold; if there is no suspected deformed point cloud, determining that the cloth to be cut is not deformed; if there is a suspected deformed point cloud, clustering all suspected deformed point clouds to obtain multiple clusters, and taking the area where each cluster is located as a suspected deformation area; If the area ratio of all suspected deformation areas in the cloth to be cut is greater than the preset area ratio threshold, it is determined that the cloth to be cut is deformed, and all suspected deformation areas are determined as deformation areas; if the area ratio of all suspected deformation areas in the cloth to be cut is not greater than the preset area ratio threshold, it is determined that the cloth to be cut is not deformed, and there is no deformation area in the cloth to be cut.

4. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 1 is characterized in that: The average curvature within the local range of the point cloud and the average point cloud density within the local range of the point cloud are determined as follows: Get the The local range of the point cloud The curvature of each local surface of the point cloud is calculated The mean curvature of all local surfaces of the point cloud is taken as The average curvature in the local range of a point cloud; Get the The local range of the point cloud The point cloud density of each local area of ​​the point cloud is calculated The mean of the point cloud density of all local ranges of the point cloud is taken as the The average point cloud density within the local range of a point cloud.

5. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 1, characterized in that: The method for determining the local surface based on the local range is: The surface fitting technology is used to perform surface fitting on all point clouds within the local range of each point cloud to obtain the local surface of the point cloud.

6. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 3 is characterized in that: The method for determining whether there are suspected deformed point clouds in all point clouds is: Preset local deformation possibility threshold; If the local deformation possibility of a point cloud is greater than the local deformation possibility threshold, the point cloud is regarded as a suspected deformed point cloud. If the local deformation possibility of a point cloud is not greater than the local deformation possibility threshold, the point cloud is regarded as a normal point cloud.

7. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 3 is characterized in that: The methods to implement different cropping strategies are: If the fabric to be cut is deformed, adjust the cutting path to avoid the deformed area; If the fabric to be cut does not deform, the preset cutting path is executed.

8. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 5, characterized in that: The method for determining the roughness of the local surface is: The variance of the Euclidean distances from all point clouds within the local range of each point cloud to the local surface of the point cloud is calculated, and the variance is used as the roughness of the local surface of the point cloud.

9. The intelligent cutting method for fabrics used in arc protection clothing production according to claim 2, characterized in that: The method for obtaining the deformation weights of the cloth to be cut in the length, width, and height directions is: Prepare in advance a fabric sample of the same material as the fabric to be cut, apply different tensions to the fabric sample in the length, width, and height directions, and record the deformation generated under each tension; The relationship curve between the tension and deformation of the fabric sample in each direction is obtained by using the curve fitting technology. Based on the relationship curve, the ratio of the average deformation change rate and the average tension change rate of the fabric sample in each direction is obtained as the stretch sensitivity of the fabric sample in each direction. The sum of the stretch sensitivities in each direction is taken as the total stretch sensitivity. The ratio of the stretch sensitivity of the cloth sample in the length, width and height directions to the total stretch sensitivity is used as the deformation weight of the cloth to be cut in the length, width and height directions, respectively.

Images