Intelligent processing method and system for carbon fiber material thermoplastic mold

Abstract

The present invention relates to the field of mold processing technology, and discloses a method and system for intelligent processing of carbon fiber thermoplastic molds. The method comprises: matching feature points on a multi-dimensional laser image of a product structure to obtain target feature points; constructing a three-dimensional structure diagram based on the target feature points, and generating product parameters based on the three-dimensional structure diagram; generating a processing trajectory corresponding to the product structure based on the product parameters, optimizing the processing trajectory to obtain a target processing trajectory; constructing a carbon fiber material processing file corresponding to the product structure based on the target processing trajectory, calculating the material intersection thickness based on the carbon fiber material processing file; and correcting the carbon fiber material processing file based on the material intersection thickness to obtain a tool path for processing the carbon fiber mold of the product structure. The present invention can improve the precision of intelligent mold processing.

Description

Technical Field

[0001] The present invention relates to the field of mold processing technology, and in particular to an intelligent processing method and system for a carbon fiber material thermoplastic mold. Background Art

[0002] Carbon fiber (CF) is a new type of high-strength, high-modulus fiber with a carbon content of over 95%. Carbon fiber has a series of excellent properties such as high strength, high modulus, corrosion resistance, and low thermal expansion coefficient. The application of carbon fiber materials in the new energy field is expanding rapidly. At the same time, the rise of emerging industries such as flying cars and robots has also led to an increasing demand for carbon fiber materials.

[0003] Carbon fiber thermoplastic molds play a vital role in the manufacturing process of carbon fiber composite materials. Thermoplastic molds have faster molding speeds and can achieve one-step molding of complex structural parts, thereby improving production efficiency. At the same time, they have good dimensional stability and can ensure the dimensional accuracy of the product. However, existing mold processing mainly designs the mold surface based on the digital model of the part. Then, based on experience, the entire mold is scaled to obtain a certain mold model. However, this method relies too much on manual experience and lacks scientificity and precision. Secondly, in the actual processing process, the difference in thermal expansion properties between the mold material and the part material is not fully considered, which leads to errors in the part forming process, affecting the quality and precision of the final product. Therefore, how to improve the accuracy of mold processing has become an urgent problem to be solved. Summary of the Invention

[0004] The present invention provides an intelligent processing method and system for a carbon fiber material thermoplastic mold, the main purpose of which is to solve the problem of poor mold processing precision.

[0005] To achieve the above objectives, the present invention provides an intelligent processing method for a carbon fiber material thermoplastic mold, comprising:

[0006] Acquire a multi-dimensional laser image of the product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points;

[0007] constructing a three-dimensional structure diagram of the product structure according to the target feature points, and generating product parameters corresponding to the product structure according to the three-dimensional structure diagram;

[0008] Generate a processing trajectory corresponding to the product structure according to the product parameters, optimize the processing trajectory, and obtain a target processing trajectory;

[0009] Constructing a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculating the material intersection thickness according to the carbon fiber material processing file;

[0010] The carbon fiber material processing file is corrected according to the material intersection thickness to obtain the carbon fiber material mold processing tool path of the product structure.

[0011] Optionally, performing feature point matching on the multi-dimensional laser image to obtain target feature points includes:

[0012] Performing laser region separation on the multi-dimensional laser image to obtain feature regions;

[0013] Calculate feature points based on the feature area and calculate pixel grayscale and value of the feature area;

[0014] The feature points are calculated using the following formula: in, represents feature points, Represents the pixel points in the feature area, Represents pixel points The horizontal axis, Represents pixel points The vertical coordinate of

[0015] The feature points are matched according to the pixel grayscale and value to obtain target feature points.

[0016] Optionally, constructing the three-dimensional structure diagram of the product structure according to the target feature points includes:

[0017] Calculating a disparity map according to the target feature points, and converting the disparity map into a three-dimensional coordinate map;

[0018] Calculating an adjacent space transformation matrix of the multi-dimensional laser image according to the three-dimensional coordinate graph;

[0019] The adjacent space transformation matrix of the multi-dimensional laser image is calculated using the following formula: in, represents the adjacent space transformation matrix, Represents the spatial transformation matrix of the camera coordinate system of the left camera of the next perspective relative to the world coordinate system, Represents the spatial transformation matrix of the camera coordinate system of the left camera in the previous view relative to the world coordinate system;

[0020] Point cloud splicing is performed on the three-dimensional coordinate graph according to the adjacent space transformation matrix to obtain a three-dimensional structure graph.

[0021] Optionally, generating a processing trajectory corresponding to the product structure according to the product parameters includes:

[0022] Setting processing parameters according to the product parameters, and determining the boundary contour of the product structure according to the processing parameters;

[0023] Mapping the boundary contour to two-dimensional contour points, and planning a two-dimensional machining path according to the two-dimensional contour points;

[0024] The two-dimensional processing path is mapped to the three-dimensional space corresponding to the product structure to obtain the processing trajectory corresponding to the product structure.

[0025] Optionally, optimizing the processing trajectory to obtain a target processing trajectory includes:

[0026] Binary-encode the processing steps according to the processing trajectory to obtain a process population;

[0027] Calculating the trajectory length of each particle in the process population, and performing crossover mutation on the process population according to the trajectory length to obtain a mutant population;

[0028] Performing chaotic mapping on the mutant population to obtain a mapped population, and calculating an average trajectory length and a maximum trajectory length of particles in the mapped population;

[0029] Iteratively optimizing the mapping population according to the average trajectory length and the maximum trajectory length until a difference between the average trajectory length and the maximum trajectory length is within a preset difference range, thereby obtaining an optimized population;

[0030] A target processing trajectory is determined according to the optimized population.

[0031] Optionally, constructing the carbon fiber material processing file corresponding to the product structure according to the target processing trajectory includes:

[0032] Determining a tool processing path according to the target processing trajectory;

[0033] Constructing a mold design surface corresponding to the product structure according to the three-dimensional structure diagram;

[0034] Program coding is performed according to the tool processing path and the mold design surface to obtain a fiber material processing file.

[0035] Optionally, calculating the material intersection thickness according to the carbon fiber material processing file includes:

[0036] Performing material forming simulation on the product structure to obtain a mold material profile;

[0037] Performing mesh processing on the mold material surface to obtain a mesh model;

[0038] Calculating model intersections of the carbon fiber material processing file on the grid model;

[0039] Interpolation calculation is performed on the intersection points of the model to obtain the thickness of the material intersection points.

[0040] Optionally, performing interpolation calculation on the model intersection to obtain the material intersection thickness includes:

[0041] Determining triangular elements between the model intersection and the nodes on the meshed model;

[0042] Calculating the unit thickness and triangle area of the triangular unit;

[0043] Calculate the material intersection thickness based on the unit thickness and the triangle area;

[0044] The thickness of the material intersection is calculated using the following formula: in, Indicates model intersection The corresponding material intersection thickness, 、 、 Represents the nodes and intersections in the mesh model respectively. exist 、 、 In the triangular unit, 、 、 、 Represents triangles ,triangle ,triangle and triangles The area of the triangle, 、 、 Represents nodes respectively 、 、 The corresponding element thickness.

[0045] Optionally, the carbon fiber material processing file is corrected by the thickness of the material intersection to obtain the carbon fiber material mold processing tool path of the product structure, including;

[0046] Calculating the intersection thickness difference according to the intersection thickness of the material;

[0047] Correcting the coordinates of the tool position in the carbon fiber material processing file according to the intersection thickness difference to obtain a target tool position;

[0048] A tool path for machining a carbon fiber material mold is generated according to the target tool position point.

[0049] In order to solve the above problems, the present invention also provides an intelligent processing system for carbon fiber material thermoplastic molds, the system comprising:

[0050] A feature point matching module is used to obtain a multi-dimensional laser image of the product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points;

[0051] A product parameter calculation module, configured to construct a three-dimensional structure diagram of the product structure according to the target feature points, and generate product parameters corresponding to the product structure according to the three-dimensional structure diagram;

[0052] A processing trajectory optimization module is used to generate a processing trajectory corresponding to the product structure according to the product parameters, and optimize the processing trajectory to obtain a target processing trajectory;

[0053] a material intersection thickness calculation module, configured to construct a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculate the material intersection thickness according to the carbon fiber material processing file;

[0054] The processing file correction module is used to correct the carbon fiber material processing file according to the thickness of the material intersection point to obtain the carbon fiber material mold processing tool path of the product structure.

[0055] The embodiment of the present invention uses a multi-dimensional laser image of the product structure to perform feature point matching, which can quickly identify feature points and simultaneously achieve surface reconstruction of the product structure, thereby improving the accuracy of subsequent three-dimensional structural diagram construction. The product parameters of the product structure are extracted based on the three-dimensional structural diagram, and the corresponding processing trajectory can be quickly generated based on the product parameters. The processing trajectory is optimized to obtain a target processing trajectory with higher processing efficiency. A carbon fiber material processing file is constructed based on the target processing trajectory, and the material intersection thickness is calculated based on the carbon fiber material processing file. The carbon fiber material processing file can be corrected based on the material intersection thickness, thereby effectively improving the accuracy of mold processing. Therefore, the intelligent processing method and system for carbon fiber thermoplastic molds proposed in the present invention can solve the problem of poor mold processing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic flow chart of an intelligent processing method for a carbon fiber thermoplastic mold provided by one embodiment of the present invention;

[0057] Figure 2 A schematic diagram of a process for constructing a three-dimensional structure diagram of a product structure according to an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of a process for generating a processing trajectory corresponding to a product structure according to product parameters provided by an embodiment of the present invention;

[0059] Figure 4 This is a functional module diagram of an intelligent processing system for carbon fiber thermoplastic molds provided by one embodiment of the present invention.

[0060] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0061] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0062] The embodiment of the present application provides an intelligent processing method for carbon fiber material thermoplastic molds. The execution subject of the intelligent processing method for carbon fiber material thermoplastic molds includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent processing method for carbon fiber material thermoplastic molds can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0063] Reference Figure 1 FIG. 1 is a flow chart of an intelligent processing method for a carbon fiber thermoplastic mold according to an embodiment of the present invention. In this embodiment, the intelligent processing method for a carbon fiber thermoplastic mold includes:

[0064] S1. Acquire a multi-dimensional laser image of a product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points.

[0065] In this embodiment of the present invention, a product structure requiring mold processing, such as a specific product object, is projected onto its surface using an array of lasers. A pre-set left and right camera form a binocular camera system that captures the product structure from all angles. This produces a multidimensional image containing information about the laser array. The laser array is not a single pixel in the image, but rather a diffuse laser area. This results in a multidimensional laser image of the laser area captured by the left and right cameras. This multidimensional laser image can be used to identify characteristic points on the product structure's surface, facilitating three-dimensional reconstruction of the product structure.

[0066] In an embodiment of the present invention, performing feature point matching on the multi-dimensional laser image to obtain target feature points includes:

[0067] Performing laser region separation on the multi-dimensional laser image to obtain feature regions;

[0068] Calculate feature points based on the feature area and calculate pixel grayscale and value of the feature area;

[0069] The feature points are matched according to the pixel grayscale and value to obtain target feature points.

[0070] In detail, the multi-dimensional laser image contains a laser area, and the laser area is separated from the image using mask clipping to form a series of rectangles centered on the laser to obtain the feature area. The centroid of the feature area is then calculated as the feature point to obtain the feature point corresponding to each feature area, and the sum of the pixel grayscale values of the feature area is calculated.

[0071] In the embodiment of the present invention, the feature points are calculated using the following formula: in, represents feature points, Represents the pixel points in the feature area, Represents pixel points The horizontal axis, Represents pixel points The vertical coordinate of .

[0072] In detail, the pixel values of the pixels in each feature area that belong to the laser area are set to 1, and the pixel values of other pixels are set to 0, and then the centroid of the entire feature area is constructed as the feature point. For example, this application can use green laser, and the pixel points in the feature area that belong to the green laser are set to 1.

[0073] Furthermore, matching the feature points according to the pixel grayscale and value to obtain target feature points includes:

[0074] Performing feature point search using the feature points to obtain a feature point range;

[0075] The feature point range is screened according to the pixel grayscale and value to obtain target feature points.

[0076] In an embodiment of the present invention, after grayscale processing is performed on the multi-dimensional laser image, the sum of the grayscale values of each feature area is calculated, and a feature point search is performed within a preset search range based on the horizontal coordinate of the feature point to obtain the feature point range corresponding to different views. The pixel grayscale sum value of the feature area where the feature point within the feature point range is located is calculated. The pixel grayscale sum value whose difference in the pixel grayscale sum value is within the preset threshold range corresponds to the target feature point.

[0077] For example, the search range ds, d+s can be set according to the parallax d between the left and right views and the preset spacing limit s of the array laser area to obtain the feature point range, so that the matching target feature points can be obtained by screening according to the pixel grayscale and value.

[0078] In the embodiment of the present invention, feature point matching is matching the same feature points captured by the left and right cameras. For example, feature points captured by the left camera are matched with feature points captured by the right camera to obtain target feature points.

[0079] Furthermore, before taking multi-dimensional laser images, the left and right cameras can be calibrated and epipolar corrected to eliminate the geometric error between the left and right cameras. Specifically, the translation vector of the camera coordinate system can be calculated according to the relative rotation matrix after camera calibration and the inverse Rodrigues transformation, and then the horizontal coordinates of the left and right camera coordinate systems can be made parallel to the translation vector to complete the epipolar correction.

[0080] In the embodiment of the present invention, by performing feature point matching, feature points can be quickly identified, while surface reconstruction of the product structure is achieved, thereby improving the accuracy of subsequent three-dimensional structure diagram construction.

[0081] S2. Construct a three-dimensional structure diagram of the product structure according to the target feature points, and generate product parameters corresponding to the product structure according to the three-dimensional structure diagram.

[0082] In the embodiment of the present invention, the three-dimensional structure diagram is a three-dimensional modeling of the product structure based on the target feature points, thereby reconstructing the three-dimensional information of the product structure and accurately calculating the product parameters corresponding to the product structure.

[0083] In the embodiment of the present invention, see Figure 2 As shown, the three-dimensional structure diagram of the product structure is constructed according to the target feature points, including:

[0084] S21, calculating a disparity map according to the target feature points, and converting the disparity map into a three-dimensional coordinate map;

[0085] S22, calculating an adjacent space transformation matrix of the multi-dimensional laser image according to the three-dimensional coordinate graph;

[0086] S23. Perform point cloud splicing on the three-dimensional coordinate graph according to the adjacent space transformation matrix to obtain a three-dimensional structure graph.

[0087] In this embodiment of the present invention, the horizontal displacement of the target feature point in the left and right views is calculated. That is, for a feature point in the left image, the horizontal displacement of its corresponding target feature point in the right image is the disparity. The disparity value is plotted on the image to form a disparity map. The disparity map and camera parameters are then used to convert the disparity map into a three-dimensional coordinate map using a reprojection matrix. The disparity map can be converted into the three-dimensional coordinates of each pixel using the reprojectImageTo3D function in OpenCV to obtain a three-dimensional coordinate map.

[0088] Furthermore, the coordinates of each pixel point in the three-dimensional coordinate map are used as point cloud coordinates, and the left camera can be selected as the standard reference object. In the same two adjacent perspectives, the coordinates of the same feature point in different camera coordinate systems can be obtained. For example, the coordinate of the same point in the left camera coordinate system in the previous perspective is 1, the coordinate in the left camera coordinate system in the next perspective is 2, and the coordinate in the world coordinate system is 3. Then, the adjacent space transformation matrix is constructed according to the space transformation matrix of coordinates 1 and 2 relative to the world coordinate system, and then the left camera of the previous perspective is used as the standard reference system. According to the adjacent space transformation matrix, the point cloud of the next perspective is converted to the coordinate system with the left camera of the previous perspective as the standard reference, so as to perform point cloud splicing, perform comprehensive three-dimensional modeling of the product structure, and obtain a three-dimensional structure diagram.

[0089] In detail, the point cloud coordinates in the camera coordinate system can be obtained by comparing the coordinates in the world coordinate system with the camera coordinate system.

[0090] The spatial transformation matrix of the coordinate system relative to the world coordinate system is multiplied. Specifically, the spatial transformation matrix of the camera coordinate system of the previous view and the next view left camera relative to the world coordinate system is calculated based on the same feature point and the internal and external parameters of the camera.

[0091] Specifically, the adjacent space transformation matrix of the multi-dimensional laser image is calculated using the following formula: in, represents the adjacent space transformation matrix, Represents the spatial transformation matrix of the camera coordinate system of the left camera of the next perspective relative to the world coordinate system, Represents the spatial transformation matrix of the camera coordinate system of the left camera in the previous view relative to the world coordinate system.

[0092] In an embodiment of the present invention, the point clouds in the three-dimensional coordinate diagrams of adjacent perspectives are spliced through adjacent space transformation matrices to obtain a three-dimensional structural diagram of the full perspective, so that the three-dimensional structure of the product structure can be fully displayed according to the three-dimensional architecture diagram, providing a basis for subsequent mold processing.

[0093] In the embodiment of the present invention, the product parameters are geometric features of the product structure and texture parameters of the product (such as surface material), etc. The product parameters are used to more accurately describe the product structure.

[0094] Specifically, generating product parameters corresponding to the product structure according to the three-dimensional structure diagram includes:

[0095] Extracting geometric features of the three-dimensional structure diagram, and calculating geometric parameters of the product structure based on the geometric features;

[0096] Performing finite cloud analysis on the three-dimensional structure diagram to obtain material parameters of the product structure;

[0097] The geometric parameters and the material parameters are collected to obtain product parameters of the product structure.

[0098] In an embodiment of the present invention, geometric parameters such as length, width, height, radius, and angle can be calculated using feature information such as vertex coordinates, side lengths, and surface normals of a three-dimensional structural diagram. Finite element analysis can then be used to extract the model's material parameters (such as elastic modulus and density) and geometric parameters (such as cross-sectional dimensions), allowing for further product structure analysis to yield more accurate product parameters.

[0099] S3. Generate a processing trajectory corresponding to the product structure according to the product parameters, optimize the processing trajectory, and obtain a target processing trajectory.

[0100] In the embodiment of the present invention, the processing trajectory is the route of intelligent processing of the mold, and defines the motion path of the processing tool in three-dimensional space.

[0101] In the embodiment of the present invention, see Figure 3 As shown, the step of generating a processing trajectory corresponding to the product structure according to the product parameters includes:

[0102] S31, setting processing parameters according to the product parameters, and determining the boundary contour of the product structure according to the processing parameters;

[0103] S32, mapping the boundary contour to two-dimensional contour points, and planning a two-dimensional processing path according to the two-dimensional contour points;

[0104] S33: Map the two-dimensional processing path to the three-dimensional space corresponding to the product structure to obtain a processing trajectory corresponding to the product structure.

[0105] Specifically, the geometric shape, size and corresponding carbon fiber material properties of the product structure can be determined based on the product parameters. The boundary contour of the product structure can be determined based on the processing parameters. For example, the length, width and other information in different areas can be used to construct the contour of the product structure and analyze the areas that need to be processed.

[0106] Furthermore, the 3D data points corresponding to the boundary contour are projected onto a plane to obtain 2D contour points. Based on these 2D contour points, parallel and equidistant tool paths are then planned to create a 2D machining path. A parallel and equidistant tool path refers to a process where cutting is performed along a series of mutually parallel paths, with the spacing between adjacent paths being equal. Specifically, a preset initial path is offset equidistantly along a specific direction (such as the normal direction) to generate a series of parallel and equidistant paths, which are then combined and spliced to form the 2D machining path.

[0107] In the embodiment of the present invention, the two-dimensional processing path can be mapped into the three-dimensional space where the three-dimensional structure diagram corresponding to the product structure is located, thereby obtaining the processing trajectory in the three-dimensional space.

[0108] Furthermore, according to specific processing parameters, CAM (Computer-Aided Manufacturing) software can be used to generate a tool path of parallel and equally spaced tool paths to obtain a processing trajectory, wherein the parameters of the processing tool, such as cutting speed, feed rate, cutting depth, etc., can be set in the CAM software.

[0109] In the embodiment of the present invention, the processing trajectory optimization is to optimize the processing trajectory to further improve the accuracy of mold processing.

[0110] In an embodiment of the present invention, optimizing the processing trajectory to obtain a target processing trajectory includes:

[0111] Binary-encode the processing steps according to the processing trajectory to obtain a process population;

[0112] Calculating the trajectory length of each particle in the process population, and performing crossover mutation on the process population according to the trajectory length to obtain a mutant population;

[0113] Performing chaotic mapping on the mutant population to obtain a mapped population, and calculating an average trajectory length and a maximum trajectory length of particles in the mapped population;

[0114] Iteratively optimizing the mapping population according to the average trajectory length and the maximum trajectory length until a difference between the average trajectory length and the maximum trajectory length is within a preset difference range, thereby obtaining an optimized population;

[0115] A target processing trajectory is determined according to the optimized population.

[0116] In an embodiment of the present invention, binary encoding is performed according to the processing parameters, time, processing trajectory, etc. involved in the processing trajectory to obtain the process populations corresponding to the initial multiple processing trajectories, the trajectory length of each particle processing trajectory in the process population is calculated, and the process population is cross-mutated with the minimum trajectory length as the objective function to obtain a mutant population. Then, chaotic mapping optimization is performed on the particle individuals with larger objective function values. After optimization, if the objective function value increases, the optimized value is retained; if it decreases, the value before optimization is retained to obtain a mapping population.

[0117] Furthermore, the difference between the average trajectory length and the maximum trajectory length of the particles in the mapping population is calculated to see if it meets the preset threshold. If so, the optimized population is obtained. If not, the mapping population is iteratively optimized until the difference between the average trajectory length and the maximum trajectory length is within the preset difference range. The optimized population is obtained, the trajectory length of the particles in the optimized population is calculated, and the processing trajectory corresponding to the minimum trajectory length is selected as the target processing trajectory.

[0118] In the embodiment of the present invention, by optimizing the processing trajectory, the processing route of the mold processing can be optimized, the efficiency of the mold processing can be improved, and a target processing trajectory with a shorter processing time can be obtained.

[0119] S4. Constructing a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculating the material intersection thickness according to the carbon fiber material processing file.

[0120] In an embodiment of the present invention, the carbon fiber material processing file is a coded file for mold processing according to the target processing trajectory, which includes the tool position point during mold processing, that is, the center of the ball cutter during processing, and the point used to characterize the tool characteristics of the mold processing tool. The carbon fiber material processing file can be used to generate a data program for mold processing, and then the mold processing can be performed.

[0121] In an embodiment of the present invention, constructing the carbon fiber material processing file corresponding to the product structure according to the target processing trajectory includes:

[0122] Determining a tool processing path according to the target processing trajectory;

[0123] Constructing a mold design surface corresponding to the product structure according to the three-dimensional structure diagram;

[0124] Program coding is performed according to the tool processing path and the mold design surface to obtain a fiber material processing file.

[0125] In an embodiment of the present invention, the tool processing path is the movement path of the tool in three-dimensional space during processing, including the coordinates of the starting point, end point, and intermediate point. The processing path can be obtained based on the three-dimensional coordinates corresponding to the target processing trajectory in the three-dimensional structure diagram.

[0126] Furthermore, the mold design surface is the surface within the mold that forms the product's shape. Specifically, the surface is the forming portion of the mold, typically consisting of a front mold (movable mold) and a back mold (fixed mold). When the mold is closed, the surface forms an enclosed space, the shape of which determines the final product's appearance. Specifically, CAD software can be used to construct the mold design surface corresponding to the product structure based on a 3D model of the 3D structural diagram. The CAD surface is then numerically programmed based on the set equal material thickness gap.

[0127] In the embodiment of the present invention, the program code is a CNC machining program compiled based on the tool processing path and the mold design surface, which is a specific instruction for mold processing. The CNC machining program can be compiled based on the tool processing path and the mold design surface using preset CNC programming software such as UG NX, WorkNC, etc. to obtain a carbon fiber material processing file.

[0128] In an embodiment of the present invention, the material intersection thickness is the material thickness at the intersection between the tool and the carbon fiber material during mold processing. Based on the material intersection thickness, the thickness deviation between the mold and the carbon fiber material during mold processing can be calculated, thereby improving the accuracy of mold processing.

[0129] Specifically, the calculating the material intersection thickness according to the carbon fiber material processing file includes:

[0130] Performing material forming simulation on the product structure to obtain a mold material profile;

[0131] Performing mesh processing on the mold material surface to obtain a mesh model;

[0132] Calculating model intersections of the carbon fiber material processing file on the grid model;

[0133] Interpolation calculation is performed on the intersection points of the model to obtain the thickness of the material intersection points.

[0134] In detail, material forming simulation is a CAE (Computer Aided Engineering) forming simulation of the material forming process of the mold design surface of the product structure. Specifically, the forming simulation can be performed based on the three-dimensional geometric model corresponding to the mold design surface to obtain the mold material surface with carbon fiber as the mold material. The mold material surface can be used to obtain the thickness distribution of the product structure after forming, the thickness of the carbon fiber material on different surfaces of the product structure, and the thickness distribution is used as the basis for the gap distribution between the male and female molds and the pressing surface to correct the tool point location in the carbon fiber material processing file, thereby improving the accuracy of the tool point location in the carbon fiber material processing file.

[0135] In an embodiment of the present invention, the intersection between the tool position point in the processing tool path and the grid model is determined from the carbon fiber material processing file, wherein, since the carbon fiber material processing file is obtained by CNC programming based on equal material thickness gap, the contact point between the mold processing tool and the carbon fiber material, that is, the tool contact point, can be calculated based on the tool position point. The present invention can calculate the intersection corresponding to the grid model by connecting the tool contact point and the tool position point to obtain the model intersection.

[0136] Furthermore, the interpolation calculation of the model intersection to obtain the material intersection thickness includes:

[0137] Determining triangular elements between the model intersection and the nodes on the meshed model;

[0138] Calculating the unit thickness and triangle area of the triangular unit;

[0139] The material intersection thickness is calculated based on the unit thickness and the triangle area.

[0140] Specifically, the thickness of the material intersection is calculated using the following formula: in, Indicates model intersection The corresponding material intersection thickness, 、 、 Represents the nodes and intersections in the mesh model respectively. exist 、 、 In the triangular unit, 、 、 、 Represents triangles ,triangle ,triangle and triangles The area of the triangle, 、 、 Represents nodes respectively 、 、 The corresponding element thickness.

[0141] In an embodiment of the present invention, the thickness of the material intersection at the intersection is calculated and the difference between it and the original thickness of the carbon fiber material on the mold material profile is calculated to obtain the thickness increment at the corresponding position. The moving direction of the tool position point can be determined according to the positive and negative signs, thereby optimizing the position of the tool position point and obtaining a more accurate tool path.

[0142] S5. Correct the carbon fiber material processing file according to the material intersection thickness to obtain a tool path for processing the carbon fiber material mold of the product structure.

[0143] In the embodiment of the present invention, the correction of the carbon fiber material processing file is to correct the tool position points in the tool path in the carbon fiber material processing file to obtain the corrected tool path for carbon fiber material mold processing.

[0144] In an embodiment of the present invention, the carbon fiber material processing file is corrected by the thickness of the material intersection to obtain the carbon fiber material mold processing tool path of the product structure, including;

[0145] Calculating the intersection thickness difference according to the intersection thickness of the material;

[0146] Correcting the coordinates of the tool position in the carbon fiber material processing file according to the intersection thickness difference to obtain a target tool position;

[0147] A tool path for machining a carbon fiber material mold is generated according to the target tool position point.

[0148] In an embodiment of the present invention, the difference between the material intersection thickness at the intersection and the original thickness value of the carbon fiber material on the mold material profile is calculated to obtain the intersection thickness difference. According to the intersection thickness difference, the tool position point is moved by the distance of the intersection thickness difference along the line connecting the tool position point and the tool contact point to obtain the target tool position point to correct the coordinates of the tool position point. The target tool position point is used to construct the carbon fiber material mold processing tool path, that is, the mold processing trajectory.

[0149] Among them, the corresponding tool position points in the carbon fiber material processing file can be replaced by the target tool position points to obtain the processing tool path file, and then the processing tool path file can be used to perform intelligent processing control and carry out actual mold processing.

[0150] In the embodiment of the present invention, the tool path of the mold processing can be directly corrected by machining the tool path of the carbon fiber material mold without modifying the curve of the three-dimensional model, thereby effectively improving the accuracy of the mold processing.

[0151] like Figure 4 , which is a functional module diagram of an intelligent processing system for carbon fiber thermoplastic molds provided by one embodiment of the present invention.

[0152] The intelligent processing system 400 for carbon fiber thermoplastic molds described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the intelligent processing system 400 for carbon fiber thermoplastic molds can include a feature point matching module 401, a product parameter calculation module 402, a processing trajectory optimization module 403, a material intersection thickness calculation module 404, and a processing file correction module 405. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These modules are stored in the electronic device's memory.

[0153] In this embodiment, the functions of each module / unit are as follows:

[0154] The feature point matching module 401 is used to obtain a multi-dimensional laser image of the product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points;

[0155] The product parameter calculation module 402 is used to construct a three-dimensional structure diagram of the product structure according to the target feature points, and generate product parameters corresponding to the product structure according to the three-dimensional structure diagram;

[0156] The processing trajectory optimization module 403 is used to generate a processing trajectory corresponding to the product structure according to the product parameters, and optimize the processing trajectory to obtain a target processing trajectory;

[0157] The material intersection thickness calculation module 404 is used to construct a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculate the material intersection thickness according to the carbon fiber material processing file;

[0158] The processing file correction module 405 is used to correct the carbon fiber material processing file according to the material intersection thickness to obtain a tool path for processing the carbon fiber material mold of the product structure.

[0159] In detail, each module described in the intelligent processing system 400 for carbon fiber thermoplastic molds according to the embodiment of the present invention is used in the same manner as described above. Figures 1 to 3 The intelligent processing method of carbon fiber thermoplastic mold described in the previous section is the same technical means and can produce the same technical effects, so I will not go into details here.

[0160] The present invention also provides an electronic device, which may include a processor, a memory, a communication bus and a communication interface, and may also include a computer program stored in the memory and run on the processor, such as an intelligent processing method program for carbon fiber material thermoplastic molds.

[0161] In some embodiments, the processor may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips.

[0162] The memory includes at least one type of readable storage medium, including a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory may be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device.

[0163] The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory and at least one processor.

[0164] The communication interface is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a wireless interface.

[0165] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0166] Specifically, the specific implementation method of the processor for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0167] In the several embodiments provided herein, it should be understood that the disclosed devices, systems, and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical functional division, and actual implementation may employ other division methods.

[0168] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0169] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0170] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, techniques, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results.

[0171] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems recited in a system claim may also be implemented by a single unit or system through software or hardware. Terms such as "first" and "second" are used to indicate names and do not imply any particular order.

[0172] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent processing method for carbon fiber thermoplastic molds, characterized in that: The method comprises: Acquire a multi-dimensional laser image of the product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points; Constructing a three-dimensional structure diagram of the product structure based on the target feature points, and generating product parameters corresponding to the product structure based on the three-dimensional structure diagram; wherein constructing the three-dimensional structure diagram of the product structure based on the target feature points includes: calculating a disparity map based on the target feature points, converting the disparity map into a three-dimensional coordinate map; and calculating an adjacent space transformation matrix of the multi-dimensional laser image based on the three-dimensional coordinate map; The adjacent space transformation matrix of the multi-dimensional laser image is calculated using the following formula: Among them, M 12 Represents the adjacent spatial transformation matrix, M2 represents the spatial transformation matrix of the camera coordinate system of the left camera of the next perspective relative to the world coordinate system, and M1 represents the spatial transformation matrix of the camera coordinate system of the left camera of the previous perspective relative to the world coordinate system; Performing point cloud splicing on the three-dimensional coordinate graph according to the adjacent space transformation matrix to obtain a three-dimensional structure graph; Generating a processing trajectory corresponding to the product structure according to the product parameters, and optimizing the processing trajectory to obtain a target processing trajectory; wherein, generating the processing trajectory corresponding to the product structure according to the product parameters includes: setting processing parameters according to the product parameters, determining a boundary contour of the product structure according to the processing parameters; mapping the boundary contour to two-dimensional contour points, and planning parallel and equidistant tool paths according to the two-dimensional contour points to obtain a two-dimensional processing path; mapping the two-dimensional processing path to a three-dimensional space corresponding to the product structure to obtain a processing trajectory corresponding to the product structure; Constructing a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculating the material intersection thickness according to the carbon fiber material processing file; The carbon fiber material processing file is corrected according to the material intersection thickness to obtain the carbon fiber material mold processing tool path of the product structure.

2. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 1, characterized in that: The performing feature point matching on the multi-dimensional laser image to obtain target feature points includes: Performing laser region separation on the multi-dimensional laser image to obtain feature regions; Calculate feature points based on the feature area and calculate pixel grayscale and value of the feature area; The feature points are calculated using the following formula: Where (x0, y0) represents the feature point, f(x, y) represents the pixel point in the feature area, x represents the horizontal coordinate of the pixel point f(x, y), and y represents the vertical coordinate of the pixel point f(x, y); The feature points are matched according to the pixel grayscale and value to obtain target feature points.

3. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 1, characterized in that: The step of optimizing the processing trajectory to obtain a target processing trajectory includes: Binary-encode the processing steps according to the processing trajectory to obtain a process population; Calculating the trajectory length of each particle in the process population, and performing crossover mutation on the process population according to the trajectory length to obtain a mutant population; Performing chaotic mapping on the mutant population to obtain a mapped population, and calculating an average trajectory length and a maximum trajectory length of particles in the mapped population; Iteratively optimizing the mapping population according to the average trajectory length and the maximum trajectory length until a difference between the average trajectory length and the maximum trajectory length is within a preset difference range, thereby obtaining an optimized population; A target processing trajectory is determined according to the optimized population.

4. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 1, characterized in that: The step of constructing a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory includes: Determining a tool processing path according to the target processing trajectory; Constructing a mold design surface corresponding to the product structure according to the three-dimensional structure diagram; Program coding is performed according to the tool processing path and the mold design surface to obtain a fiber material processing file.

5. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 1, characterized in that: The calculating the material intersection thickness according to the carbon fiber material processing file includes: Performing material forming simulation on the product structure to obtain a mold material profile; Performing mesh processing on the mold material surface to obtain a mesh model; Calculating model intersections of the carbon fiber material processing file on the grid model; Interpolation calculation is performed on the intersection points of the model to obtain the thickness of the material intersection points.

6. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 5, characterized in that: The interpolation calculation of the model intersection to obtain the material intersection thickness includes: Determining triangular elements between the model intersection and the nodes on the meshed model; Calculating the unit thickness and triangle area of the triangular unit; Calculate the material intersection thickness based on the unit thickness and the triangle area; The thickness of the material intersection is calculated using the following formula: Among them, t P Indicates the thickness of the material intersection corresponding to the model intersection point P. A, B, and C represent the nodes in the mesh model. The intersection point P is in the triangular unit where A, B, and C are located. S △BCP 、S △ABC 、S △ACP 、S △ABP Denote the triangular areas of triangle BCP, triangle ABC, triangle ACP, and triangle ABP, respectively. A , t B , t C Represent the element thickness corresponding to nodes A, B, and C respectively.

7. The intelligent processing method of carbon fiber material thermoplastic mold according to claim 1, characterized in that: The step of correcting the carbon fiber material processing file by using the material intersection thickness to obtain a tool path for processing the carbon fiber material mold of the product structure includes: Calculating the intersection thickness difference according to the intersection thickness of the material; Correcting the coordinates of the tool position in the carbon fiber material processing file according to the intersection thickness difference to obtain a target tool position; A tool path for machining a carbon fiber material mold is generated according to the target tool position point.

8. An intelligent processing system for carbon fiber thermoplastic molds, characterized in that: The system comprises: A feature point matching module is used to obtain a multi-dimensional laser image of the product structure, perform feature point matching on the multi-dimensional laser image, and obtain target feature points; a product parameter calculation module, configured to construct a three-dimensional structure diagram of the product structure based on the target feature points, and generate product parameters corresponding to the product structure based on the three-dimensional structure diagram; wherein constructing the three-dimensional structure diagram of the product structure based on the target feature points includes: calculating a disparity map based on the target feature points, converting the disparity map into a three-dimensional coordinate map; and calculating an adjacent space transformation matrix of the multi-dimensional laser image based on the three-dimensional coordinate map; The adjacent space transformation matrix of the multi-dimensional laser image is calculated using the following formula: Among them, M 12 Represents the adjacent spatial transformation matrix, M2 represents the spatial transformation matrix of the camera coordinate system of the left camera of the next perspective relative to the world coordinate system, and M1 represents the spatial transformation matrix of the camera coordinate system of the left camera of the previous perspective relative to the world coordinate system; Performing point cloud splicing on the three-dimensional coordinate graph according to the adjacent space transformation matrix to obtain a three-dimensional structure graph; a machining trajectory optimization module, configured to generate a machining trajectory corresponding to the product structure based on the product parameters, and optimize the machining trajectory to obtain a target machining trajectory; wherein generating the machining trajectory corresponding to the product structure based on the product parameters includes: setting machining parameters based on the product parameters, determining a boundary contour of the product structure based on the machining parameters; mapping the boundary contour to two-dimensional contour points, and planning parallel equidistant tool paths based on the two-dimensional contour points to obtain a two-dimensional machining path; and mapping the two-dimensional machining path to a three-dimensional space corresponding to the product structure to obtain a machining trajectory corresponding to the product structure; a material intersection thickness calculation module, configured to construct a carbon fiber material processing file corresponding to the product structure according to the target processing trajectory, and calculate the material intersection thickness according to the carbon fiber material processing file; The processing file correction module is used to correct the carbon fiber material processing file according to the thickness of the material intersection point to obtain the carbon fiber material mold processing tool path of the product structure.

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