Compound manufacturing contour grinding allowance detection method and system based on point cloud matching

Abstract

The application belongs to the technical field of additive manufacturing, and specifically discloses a composite manufacturing contour grinding allowance detection method and system based on point cloud matching. The method comprises the following steps: obtaining external contour data of a printed workpiece; generating a grinding path curve based on the external contour data by using a contour line method; discretizing the grinding path curve to obtain a plurality of discrete points; discretizing a digital model of the printed workpiece into point cloud data, and aligning the point cloud data with the external contour data based on a preset anchor point; sorting the external contour data and generating a triangular mesh model; obtaining the intersection point of the normal extension line of each discrete point and the corresponding triangular sub-face sheet in the triangular mesh model; and taking the Cartesian space distance value between the discrete point and the corresponding intersection point as the grinding allowance value. The application can accurately estimate the grinding allowance value required for completing the in-situ grinding task.

Description

Technical Field

[0001] This application belongs to the field of additive manufacturing technology, and more specifically, relates to a method and system for detecting grinding allowance of composite manufacturing contours based on point cloud matching. Background Technology

[0002] Laser-directed energy deposition (LDED) technology uses a layer-by-layer stacking method for additive manufacturing. During this process, the material melts, accumulates, and cools to form its shape. The surface morphology often deviates macroscopically or microscopically from the theoretical numerical model, making it difficult to meet the required machining accuracy and surface quality. Composite manufacturing technology integrates additive and subtractive manufacturing processes, eliminating machining tolerances caused by layered manufacturing and ensuring superior surface quality. In composite manufacturing, because the additive and subtractive equipment operates on the same processing platform, this architecture facilitates the unification of the coordinate system within the machining system. Based on the spatial transformation relationships between multiple coordinate systems, they are transformed to a common reference coordinate system. This allows for precise allowance removal during the subtractive process based on the measured morphology of the additively manufactured part, forming a multi-process, same-model, composite manufacturing platform integrating "additive manufacturing - visual measurement - allowance calculation - subtractive machining - result analysis." However, currently, there is no method to quickly mathematically map data from multiple machining coordinate systems based on a reference coordinate system and accurately estimate the grinding allowance required to complete in-situ grinding tasks, thus failing to digitize the entire machining data and status. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the purpose of this application is to provide a method and system for detecting grinding allowance in composite manufacturing profiles based on point cloud matching, aiming to solve the problem that it is impossible to obtain the grinding allowance required for accurate in-situ grinding in existing additive and subtractive composite manufacturing processes.

[0004] To achieve the above objectives, in a first aspect, this application provides a method for detecting grinding allowance in composite manufacturing profiles based on point cloud matching, comprising the following steps:

[0005] S1 acquires the external contour data of the printed workpiece, and generates a grinding path curve based on the external contour data using the contour line method;

[0006] S2 discretizes the grinding path curve to obtain multiple discrete points; the digital model of the printed workpiece is discretized into point cloud data.

[0007] S3 aligns the point cloud data with the external contour data based on preset anchor points; sorts the external contour data and generates a triangular mesh model;

[0008] S4 obtains the intersection point of the normal extension line of each discrete point with the corresponding triangular sub-face in the triangular mesh model; obtains the Cartesian space distance value between each discrete point and the corresponding intersection point as the grinding allowance value.

[0009] This application enables rapid mathematical mapping of point cloud data under multiple machining coordinate systems based on a reference coordinate system, and accurately estimates the grinding allowance required to complete the in-situ grinding task, thereby realizing the digitization of the entire station's machining data and status.

[0010] Furthermore, in step S1, the external contour data of the printed workpiece is scanned and measured using a line laser vision module and an external triggering method.

[0011] Furthermore, in step S1, the step of generating the grinding path curve using the contour line method includes:

[0012] S101 uses the triangulation method to discretize the standard geometric model of the printed part into a tetrahedral finite element model;

[0013] S102 calculates the height values ​​of the triangle vertices in the tetrahedral finite element model to obtain the contour line positions;

[0014] S103 connects all contour lines sequentially according to the printed path topology to obtain the grinding path curve.

[0015] Furthermore, the distance between adjacent path points in the grinding path curve is the same.

[0016] Furthermore, in step S2, the grinding path curve is discretized using an equidistant discretization method.

[0017] Furthermore, the spacing between adjacent discrete points is equal to the diameter of the laser cladding head exit. .

[0018] Furthermore, in step S3, the point cloud data and the outer contour data are first filtered until the number of points is the same, and then the filtered point cloud data and the outer contour data are aligned.

[0019] Furthermore, the coordinate system direction of the preset anchor point is consistent with the coordinate system direction of each processing robot used in the composite manufacturing process, and the coordinate system position of the preset anchor point is the same as the coordinate system position of the workpiece to be printed.

[0020] Furthermore, the method for sorting the external contour data is as follows: construct a KD-tree based on the external contour data, and recursively traverse the KD-tree to sort the external contour data.

[0021] Secondly, this application provides a system for implementing the aforementioned point cloud matching-based composite manufacturing contour grinding allowance detection method, comprising:

[0022] The grinding path curve acquisition module is used to acquire the external contour data of the printed workpiece, and generate the grinding path curve based on the external contour data using the contour line method.

[0023] The discrete processing module is used to discretize the grinding path curve to obtain multiple discrete points; it is also used to discretize the digital model of the printed workpiece into point cloud data.

[0024] The triangular mesh model generation module is used to align the point cloud data with the external contour data based on preset anchor points, sort the external contour data, and generate a triangular mesh model.

[0025] The grinding allowance acquisition module is used to acquire the intersection point of the normal extension line of the discrete point and the corresponding triangular sub-face in the triangular mesh model; it is also used to acquire the Cartesian space distance between the discrete point and the intersection point as the grinding allowance value.

[0026] Thirdly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0027] Fourthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0028] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0029] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0030] (1) The measurement method provided in this application measures the external contour data of the printed workpiece online, and aligns the point cloud data of the discretized digital model of the printed workpiece in the composite manufacturing platform with the measured external contour data, and then calculates the removal allowance of the surface contour of the part in the subtractive machining process. By realizing the rapid mathematical mapping of data under multiple machining coordinate systems based on the reference coordinate system, and accurately estimating the removal allowance required to complete the in-situ grinding task, the digitization of the whole-station machining data and status is realized.

[0031] (2) The measurement method provided in this application breaks through the limitations of traditional offline detection by introducing three-dimensional vision online measurement technology. It can acquire the three-dimensional morphology data of the workpiece surface in real time during the grinding process, and quickly calculate the deviation between the actual contour of the printed workpiece and the theoretical model by combining the reference coordinate system, dynamically optimize key parameters such as grinding path and cutting depth, and avoid over-cutting or under-cutting problems.

[0032] (3) In the measurement method provided in this application, anchor points with the same coordinate system direction as each processing robot of the composite manufacturing platform are pre-selected, and the coordinate system of the anchor point is the same as the coordinate system of the printed workpiece, so that the entire reference coordinate system has stability. This stability can avoid the error of tooling positioning by the composite manufacturing platform. Even if the workpiece undergoes micro-displacement during processing, the processing path can be quickly corrected through coordinate system mapping, thereby significantly improving the adaptability to fluctuations in the processing environment.

[0033] (4) The measurement method provided in this application constructs a digital closed loop of "measurement-analysis-processing-remeasurement" through mathematical modeling of whole-station data. The composite manufacturing platform can automatically generate process parameter combinations, greatly reducing manual intervention, and is especially suitable for processing parts with complex curved surfaces or high precision requirements. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the process for detecting grinding allowance of composite manufacturing contours based on point cloud matching provided in the embodiments of this application;

[0035] Figure 2 This is a schematic diagram of the multi-robotic arm composite processing system and the location of the anchor points provided in the embodiments of this application;

[0036] Figure 3 This is a schematic diagram of the tetrahedral finite element model and contour point positions provided in the embodiments of this application;

[0037] Figure 4 This is a schematic diagram illustrating the grinding allowance calculation principle provided in the embodiments of this application;

[0038] Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0040] In this article, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The symbol " / " in this article indicates that the related objects are in an "or" relationship; for example, A / B means A or B.

[0041] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0042] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0043] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0044] The embodiments of this application are described below with reference to the accompanying drawings.

[0045] This embodiment provides a method for detecting grinding allowance in composite manufacturing contours based on point cloud matching, such as... Figure 1 As shown, it includes the following steps:

[0046] S1 acquires the external contour data of the printed workpiece, and generates the grinding path curve based on the external contour data using the contour line method;

[0047] S2 discrete grinding path curve, obtain multiple discrete points; discretize the digital model of the printed workpiece into point cloud data;

[0048] S3 aligns point cloud data with external contour data based on preset anchor points; sorts the external contour data and generates a triangular mesh model;

[0049] S4 obtains the intersection point of the normal extension line of each discrete point with the corresponding triangular sub-face in the triangular mesh model; obtains the Cartesian space distance value between each discrete point and the corresponding intersection point, as the grinding allowance value.

[0050] Specifically, such as Figure 2As shown, before step S1, a preset anchor point (i.e., the anchor point in the figure) is selected in the coordinate system of the digital model of the printed workpiece. The coordinate system direction of the preset anchor point is consistent with the coordinate system direction of each processing robot used in the composite manufacturing process. The coordinate system position of the preset anchor point is the same as the coordinate system position of the workpiece to be printed, so as to achieve coordinate system unity.

[0051] A line laser vision system is installed at the end effector of each robotic arm. An external triggering method is used to synchronously measure the printed workpiece to obtain its external contour. In step S1, the line laser vision module is used to scan and measure the external contour data of the printed workpiece using an external triggering method. Specifically, by using preset anchor points or calibration targets, the coordinate system of the line laser vision module, the robotic arm, and the global coordinate system of the workpiece's digital model are aligned. When the scanning end of the line laser vision module reaches the target position, an external controller (such as a PLC) sends a pulse signal to trigger the line laser vision module to perform a single data acquisition. The preferred scanning speed among the scanning parameters is... 8mm / s ,in:

[0052] The method for calculating the scan length L for each scan is as follows:

[0053] (1)

[0054] In the formula, for Y Directional point distance, N For the number of collections, V For scanning speed, F For sensor scan frame rate, T It is a periodicity.

[0055] Step S1, which involves generating the grinding path curve using the contour line method, includes:

[0056] S101 uses the triangulation method to discretize the standard geometric model of the printed part into a tetrahedral finite element model.

[0057] Specifically, first, obtain a standard geometric model: ensure the geometric model of the printed part exists in a common format (such as STL, IGES, etc.). STL format is commonly used in 3D printing, representing the object's surface as a series of triangles. Then, perform necessary preprocessing on the geometric model, such as correcting topological errors (e.g., non-manifold edges, overlapping surfaces, etc.), to ensure the model's integrity and accuracy. For the surface of the 3D model, the Delaunay triangulation algorithm can be used for triangulation. Delaunay triangulation is a commonly used algorithm that can generate high-quality triangular meshes. For example, the `scipy.spatial.Delaunay` function in Python can be used to triangulate a point set.

[0058] After completing the surface triangulation, the surface mesh needs to be extended to the interior to generate a tetrahedral mesh. Specialized mesh generation tools (such as Gmsh and TetGen) can be used. These tools can generate internal tetrahedral elements from the surface mesh.

[0059] Finally, mesh optimization is performed, which involves checking the quality of the generated tetrahedral mesh, including the shape, size, and angles of the elements. Low-quality elements may affect the accuracy of the finite element analysis, so elements that do not meet the quality requirements need to be optimized and adjusted. Specifically, mesh optimization algorithms, such as node smoothing and edge flipping techniques, can be used to improve the accuracy of the finite element analysis.

[0060] Based on the material properties of the printed part, assign corresponding material properties, apply loads and boundary conditions to each tetrahedral element, generate a finite element model file, and finally save the discretized tetrahedral mesh, material properties, loads and boundary conditions in a format that can be recognized by finite element analysis software (such as ABAQUS, ANSYS).

[0061] S102 calculates the height values ​​of the triangle vertices in the tetrahedral finite element model to obtain the contour line positions (i.e., contour points).

[0062] The specific calculation method is illustrated below: Take the i vertices of the tetrahedral finite element model and determine the height of each vertex. h i With set height value h The size between them. For example... Figure 3 As shown, taking vertices 1, 2, and 3 in the diagram, if the heights corresponding to these three vertices... h 1. h 2 、h 3 are all greater than h ,or h 1. h 2 、h 3 are all less than h If the contour lines do not pass through the triangle, then the contour lines do not pass through the triangle. h 1. h 2 are both greater than h , h 3 less than h Then the contour lines start from line segment L. 13 and line segment L 23 The contour points between them pass through; if Then the contour lines start from line segment L. 12 Line segment L 23 It passes through the points of equal elevation between them.

[0063] S103 connects all contour lines sequentially according to the printed path topology to obtain the grinding path curve.

[0064] Starting from the bottom contour line, connect the contour lines of each layer upwards sequentially. For contour lines of adjacent layers, connection points can be found using interpolation or fitting methods to ensure path continuity. The connected path is then optimized to ensure smoothness and continuity. Curve fitting methods, such as Bézier curves or spline curves, can be used to smooth the path and obtain the grinding path curve. Furthermore, the distance between adjacent path points in the grinding path curve should be the same.

[0065] In step S2, the grinding path curve is discretized using an equidistant discretization method. In a preferred embodiment, the spacing between adjacent discretized points is equal to the diameter of the laser cladding head exit. It can significantly improve processing accuracy, cladding quality, material utilization and surface properties, while reducing the heat-affected zone and processing costs.

[0066] In step S3, the point cloud data and the outer contour data are first filtered until the number of points is approximately the same. Then, the filtered point cloud data and the outer contour data are aligned. The filtering methods include: using Gaussian filtering to smooth the point cloud data, which effectively reduces noise and makes the data cleaner; or using median filtering to remove outliers and maintain the overall characteristics of the data. After filtering, downsampling is performed based on the distance between the midpoints of the point cloud data to retain key points and remove redundant points. Alignment of the point cloud data with the outer contour data can be achieved using the above methods or similar methods.

[0067] In step S3, the method for sorting the external contour data is as follows: construct a KD-tree based on the external contour data, and recursively traverse the KD-tree to sort the external contour data.

[0068] A KD-tree is a variant of a binary search tree where each node represents a point in a k-dimensional space, dividing the space into two half-spaces. By recursively partitioning the space, a KD-tree can efficiently organize and store data points in high-dimensional spaces.

[0069] The construction process is as follows:

[0070] 1) Selecting the partitioning dimension: Usually, the dimensions are selected sequentially. For example, in a two-dimensional space, the partition is first divided by the x-axis, then by the y-axis, and then the process is repeated.

[0071] 2) Select the split point: Find the median of the data points on the selected dimension and use it as the current node.

[0072] 3) Space partitioning: Using the current node as the reference, the space is divided into two half-spaces. Points less than the median form the left subtree, and points greater than the median form the right subtree.

[0073] 4) Recursive construction: Repeat the above steps for the left and right subtrees respectively until there are no data points in the subtree or only one data point remains. The KD-tree construction is then complete.

[0074] The search process is as follows:

[0075] 1) Nearest Neighbor Search: Starting from the root node, based on the value of the query point in the current partition dimension, decide whether to search the left or right subtree until a leaf node is reached. Then backtrack to check if there is a closer point in other subtrees.

[0076] 2) Range search: Starting from the root node, determine if the current node is within the query range. If it is, add the node to the result set and recursively traverse the subtree.

[0077] After sorting the external contour data and generating a triangular mesh model according to the aforementioned steps, as follows: Figure 4 As shown, in step S4, the intersection point of the normal extension line of each discrete point and the corresponding triangular sub-face in the triangular mesh model is obtained. Then, the Cartesian spatial distance value between each discrete point and the corresponding intersection point is obtained as the required grinding allowance value. The calculation of the Cartesian spatial distance value is a conventional calculation method in this technical field. For example, the coordinate values ​​of the discrete point and the corresponding intersection point can be obtained, and then the Euclidean formula can be introduced to calculate it. This application will not elaborate further. Finally, the Cartesian spatial distance values ​​corresponding to all the discrete points obtained form a set of grinding allowance values. Subsequent grinding can be carried out accurately along the grinding path curve with these grinding allowance values ​​as the reference.

[0078] In another embodiment, a system for implementing the aforementioned point cloud matching-based composite manufacturing profile grinding allowance detection method is also provided, the system comprising:

[0079] The grinding path curve acquisition module is used to acquire the external contour data of the printed workpiece and generate the grinding path curve based on the external contour data using the contour line method.

[0080] The discrete processing module is used to discretize the grinding path curve and obtain multiple discrete points; it is also used to discretize the digital model of the printed workpiece into point cloud data.

[0081] The triangle mesh model generation module is used to align point cloud data with external contour data based on preset anchor points, sort the external contour data and generate a triangle mesh model.

[0082] The grinding allowance acquisition module is used to obtain the intersection point of the normal extension line of the discrete point and the corresponding triangular sub-face in the triangular mesh model; it is also used to obtain the Cartesian space distance between the discrete point and the intersection point as the grinding allowance value.

[0083] It is understood that the detailed functional implementation of each of the above units / modules can be found in the description in the aforementioned method embodiments, and will not be repeated here.

[0084] It should be understood that the above-described device is used to execute the methods in the above embodiments. The implementation principle and technical effect of the corresponding program modules in the device are similar to those described in the above methods. The working process of the device can be referred to the corresponding process in the above methods, and will not be repeated here.

[0085] Based on the methods in the above embodiments, this application provides an electronic device, which may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. The processor 410, communication interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute the methods in the above embodiments.

[0086] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0087] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0088] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0089] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0090] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0091] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0092] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0093] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for detecting grinding allowance in composite manufacturing contours based on point cloud matching, characterized in that, Includes the following steps: S1 acquires the external contour data of the printed workpiece, and based on the external contour data, generates a grinding path curve using the contour line method: S101 uses the triangulation method to discretize the standard geometric model of the printed workpiece into a tetrahedral finite element model; S102 calculates the height values ​​of the triangle vertices in the tetrahedral finite element model to obtain the contour line positions; S103 connects all contour lines sequentially according to the printed path topology to obtain the grinding path curve; S2 discretizes the grinding path curve to obtain multiple discrete points; the digital model of the printed workpiece is discretized into point cloud data. S3 aligns the point cloud data with the external contour data based on preset anchor points: first, the point cloud data and the external contour data are filtered until the number of points is the same, then the filtered point cloud data and the external contour data are aligned; and / or, the coordinate system direction of the preset anchor points is consistent with the coordinate system direction of each processing robot used in the composite manufacturing process, and the coordinate system position of the preset anchor points is the same as the coordinate system position of the workpiece to be printed; the external contour data is sorted and a triangular mesh model is generated; S4 obtains the intersection point of the normal extension line of each discrete point with the corresponding triangular sub-face in the triangular mesh model; obtains the Cartesian space distance value between each discrete point and the corresponding intersection point as the grinding allowance value.

2. The method for detecting grinding allowance of composite manufacturing contours based on point cloud matching as described in claim 1, characterized in that, In step S1, the external contour data of the printed workpiece is scanned and measured using a line laser vision module and an external triggering method.

3. The method for detecting grinding allowance of composite manufacturing contours based on point cloud matching as described in claim 1, characterized in that, The distance between adjacent path points in the grinding path curve is the same.

4. The method for detecting grinding allowance of composite manufacturing contours based on point cloud matching as described in claim 1, characterized in that, In step S2, the grinding path curve is discretized using an equidistant discretization method.

5. The method for detecting grinding allowance of composite manufacturing contours based on point cloud matching as described in claim 4, characterized in that, The spacing between adjacent discrete points is equal to the diameter of the laser cladding head exit. .

6. A system for implementing the point cloud matching-based composite manufacturing contour grinding allowance detection method as described in any one of claims 1-5, characterized in that, include: The grinding path curve acquisition module is used to acquire the external contour data of the printed workpiece, and generate the grinding path curve based on the external contour data using the contour line method. The discrete processing module is used to discretize the grinding path curve to obtain multiple discrete points; it is also used to discretize the digital model of the printed workpiece into point cloud data. The triangular mesh model generation module is used to align the point cloud data with the external contour data based on preset anchor points, sort the external contour data, and generate a triangular mesh model. The grinding allowance acquisition module is used to acquire the intersection point of the normal extension line of the discrete point and the corresponding triangular sub-face in the triangular mesh model; it is also used to acquire the Cartesian space distance between the discrete point and the intersection point as the grinding allowance value.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, the processor performs the grinding allowance detection method as described in any one of claims 1-5.

8. A computer program product, characterized in that, When the computer program product is run on the processor, the processor performs the grinding allowance detection method as described in any one of claims 1-5.

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