Size measurement method, device and equipment for shot peening forming crater and storage medium

Abstract

The invention discloses a shot peening forming crater size measurement method, device and equipment and a storage medium, and the method comprises the steps: scanning the surface of a shot peening forming part to obtain point cloud data, and obtaining a finite element mesh model based on the point cloud data; flattening the finite element mesh model to obtain a flattened finite element mesh model; acquiring all node data in the flattened finite element mesh model, and taking the node data as a flattening point cloud; and screening out crater point clouds from the flat point clouds, and measuring the crater point clouds to obtain the diameter and depth of each crater. According to the method, the point cloud data of the surface of the shot peening forming part is obtained and converted into the finite element mesh model for flattening simulation processing, and the diameter and depth of the crater are obtained based on the flattened finite element mesh model, so that the situation of crater area segmentation error caused by introduction of edge segmentation is avoided, and the crater size measurement precision is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a shot forming crater size measurement method, device, equipment and storage medium. BACKGROUND

[0002] In the shot forming process, the crater diameter and depth are important indicators affecting the performance of the parts after shot forming. For example, if the crater depth-width ratio is too large, it will cause great difficulty to the subsequent spraying process, resulting in poor surface quality and affecting the appearance of the aircraft. At the same time, the large crater diameter and depth will affect the fatigue performance of the parts. At the same time, when developing shot forming process parameters by using inherent strain method, the diameter and depth of the crater are also important reference elements for evaluating the size and size of the inherent strain.

[0003] At present, the image information of the shot forming part surface is usually collected by a 2D industrial camera, and the shot crater area is identified and segmented by using an image processing algorithm, and then the crater diameter is analyzed. However, when the size is measured by using the above method, the depth information of the crater cannot be obtained because the depth of field of the industrial camera is limited and only two-dimensional size information of the shot can be identified. In addition, when the crater area is segmented, an edge segmentation method is usually used, but due to the interference of picture definition and noise, the edge segmentation is usually inaccurate, resulting in segmentation error of the crater area. SUMMARY

[0004] The present application provides a shot forming crater size measurement method to accurately measure the size of the shot forming crater.

[0005] According to a first aspect of the present application, a shot forming crater size measurement method is provided, comprising:

[0006] scanning the surface of the shot forming part to obtain point cloud data, and obtaining a finite element grid model based on the point cloud data;

[0007] flattening the finite element grid model to obtain a flattened finite element grid model;

[0008] obtaining all node data in the flattened finite element grid model, and taking the node data as a flat point cloud;

[0009] screening crater point cloud from the flat point cloud, and measuring the diameter and depth of each crater from the crater point cloud.

[0010] Optionally, after the scanning of the surface of the shot forming part to obtain the point cloud data, the method further comprises:

[0011] de-noising the point cloud data to obtain de-noised point cloud data;

[0012] The finite element mesh model is acquired based on the point cloud data.

[0013] The finite element mesh model is acquired based on the denoised point cloud data.

[0014] The finite element mesh model is acquired based on the denoised point cloud data.

[0015] The denoised point cloud data is geometrically reconstructed by using a geometric reconstruction function to acquire a three-dimensional lithography STL geometric surface.

[0016] The node coordinates and connection relationships of the triangular facets on the STL geometric surface are extracted.

[0017] The finite element mesh model is established according to the node coordinates and the connection relationships.

[0018] The flattened finite element mesh model is acquired by flattening the finite element mesh model.

[0019] A simulation flattening boundary condition is established, wherein the boundary condition includes setting a rigid plane on a first plane of the finite element mesh model that is a crater depression and setting a specified intensity pressure load on a second plane of the finite element mesh model that is a crater protrusion.

[0020] The flattened finite element mesh model is acquired by flattening the finite element mesh model based on the boundary condition.

[0021] The flattened finite element mesh model is acquired by flattening the finite element mesh model based on the boundary condition.

[0022] The first plane of the finite element mesh model is brought into contact with the rigid plane.

[0023] The pressure load is applied to the second plane of the finite element mesh model to flatten the finite element mesh model on the rigid plane to acquire the flattened finite element mesh model, wherein the crater region remains in a depressed state.

[0024] The crater point cloud is screened from the flattened point cloud.

[0025] A geometric plane is fitted based on the flattened point cloud.

[0026] The crater point cloud and a plane point cloud are acquired by segmenting the flattened point cloud based on the geometric plane, wherein the plane point cloud is located on the geometric plane, and the crater point cloud is located outside the geometric plane.

[0027] Optionally, the diameter and depth of each shot pit are obtained by measuring the shot pit point cloud, comprising:

[0028] The shot pit point cloud is clustered by using a clustering algorithm to obtain a plurality of point cloud clusters, wherein each point cloud cluster corresponds to a shot pit;

[0029] The minimum outer frame corresponding to each point cloud cluster is obtained, and the diameter of the shot pit corresponding to the point cloud cluster is determined according to the minimum outer frame;

[0030] The maximum distance between each point cloud cluster and the geometric plane is obtained, and the depth of the shot pit corresponding to the point cloud cluster is determined according to the maximum distance.

[0031] According to another aspect of the present application, a device for measuring the size of a shot pit formed by shot peening is provided, comprising:

[0032] A finite element mesh model acquisition module is configured to scan the surface of a shot peened part to obtain point cloud data, and to obtain a finite element mesh model based on the point cloud data;

[0033] A finite element mesh model flattening module is configured to flatten the finite element mesh model to obtain a flattened finite element mesh model;

[0034] A flattened point cloud acquisition module is configured to obtain all node data in the flattened finite element mesh model, and to take the node data as a flattened point cloud;

[0035] A shot pit detection module is configured to filter shot pit point cloud from the flattened point cloud, and to measure the diameter and depth of each shot pit from the shot pit point cloud.

[0036] According to another aspect of the present application, an electronic device is provided, comprising:

[0037] at least one processor; and

[0038] a memory communicatively connected to the at least one processor; wherein

[0039] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the method according to any one of the embodiments of the present application.

[0040] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to implement the method according to any one of the embodiments of the present application when executed.

[0041] The technical scheme of the embodiment of the present application obtains point cloud data of the shot forming part surface, converts the point cloud data into a finite element grid model for flattening simulation processing, and obtains the diameter and depth of the crater based on the flattened finite element grid model, thereby avoiding the crater region segmentation error caused by edge segmentation, and improving the precision of the crater size measurement.

[0042] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0044] Figure 1 is a flowchart of a shot forming crater size measurement method according to the embodiment one of the present application;

[0045] Figure 2 is a part surface schematic diagram of shot forming according to the embodiment one of the present application;

[0046] Figure 3 is a part surface point cloud data of shot forming according to the embodiment one of the present application;

[0047] Figure 4 is an STL geometric surface according to the embodiment one of the present application;

[0048] Fig. 5(a) is a schematic diagram of a finite element grid model according to the embodiment one of the present application;

[0049] Fig. 5(b) is a schematic diagram of a flattened finite element grid model according to the embodiment one of the present application;

[0050] Figure 6 is node data of the flattened finite element grid model according to the embodiment one of the present application;

[0051] Figure 7 is a schematic diagram of a planar point cloud according to the embodiment one of the present application;

[0052] Figure 8 is a schematic diagram of a crater point cloud according to the embodiment one of the present application;

[0053] Figure 9It is a flow chart of a shot forming crater size measurement method according to the second embodiment of the present application.

[0054] Figure 10 It is a flattening simulation modeling schematic diagram according to the second embodiment of the present application.

[0055] Figure 11 It is a structural schematic diagram of a shot forming crater size measurement device according to the third embodiment of the present application.

[0056] Figure 12 It is a structural schematic diagram of an electronic device according to the fourth embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the scope of protection of the present application.

[0058] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0059] Embodiment one

[0060] Figure 1 A flow chart of a shot forming crater size measurement method is provided for the first embodiment of the present application. The present embodiment can be applicable to the case of measuring the size of a shot forming crater. The method can be executed by a shot forming crater size measurement device, which can be realized in the form of hardware and / or software. As shown in the figure, the method comprises: Figure 1

[0061] Step S101, scanning the surface of the shot forming part to obtain point cloud data, and obtaining a finite element grid model based on the point cloud data.

[0062] ​Optionally, after scanning the shot-formed part surface to obtain point cloud data, the method further comprises: performing denoising processing on the point cloud data to obtain denoised point cloud data; and obtaining a finite element mesh model based on the point cloud data, comprising: obtaining a finite element mesh model based on the denoised point cloud data.

[0063] Optionally, obtaining the finite element mesh model based on the denoised point cloud data comprises: performing geometric reconstruction on the denoised point cloud data using a geometric reconstruction function to obtain a three-dimensional lithography STL geometric surface; extracting node coordinates and connection relationships of triangular facets on the STL geometric surface; and establishing the finite element mesh model according to the node coordinates and the connection relationships.

[0064] Specifically, as shown in FIG. 1, it is a schematic diagram of a shot-formed part surface. In this embodiment, a 3D scanner is used to scan the shot-formed part surface to obtain point cloud data, as shown in FIG. 2. Figure 2 Figure 3 As shown in FIG. 2, it is point cloud data of the shot-formed part surface. In this embodiment, the obtained point cloud data is preprocessed. The preprocessing at this time can include denoising processing and curvature downsampling processing. Of course, this embodiment is only an example and does not limit the specific type of preprocessing operation. When performing denoising processing, some isolated noise points in the point cloud data are removed to improve the quality of the point cloud.

[0065] In this embodiment, after obtaining the preprocessed point cloud data, geometric reconstruction is performed to obtain a three-dimensional lithography (STereoLithography, STL) geometric surface. The STL geometric surface is mainly composed of triangular facets formed by multiple nodes, as shown in FIG. 3. Figure 4 After obtaining the STL geometric surface, the node coordinates and connection relationships of the triangular facets on the STL geometric surface are extracted, and a finite element mesh model is established according to the node coordinates and the connection relationships, as shown in FIG. 5(a), which is a schematic diagram of the finite element mesh model. Thus, the part surface is simulated in the form of the finite element mesh model, and the size of the craters is measured based on the simulation result.

[0066] Optionally, the method for performing the flattening processing on the finite element mesh model to obtain the flattened finite element mesh model comprises: establishing a simulation flattening boundary condition, wherein the boundary condition comprises setting a rigid plane on a first plane of the crater depression of the finite element mesh model and setting a specified strength pressure load on a second plane of the crater protrusion of the finite element mesh model; and performing the flattening processing on the finite element mesh model based on the boundary condition to obtain the flattened finite element mesh model.

[0067] ​​

[0068] Specifically, after obtaining the finite element grid model, since the model simulated at this time is obtained based on the STL geometric surface, the corresponding finite element grid model is also a curved surface model, and it is difficult to measure the size of the crater based on the curved surface model relative to the plane because it involves angle conversion. In the present embodiment, the obtained finite element grid model is flattened, and when flattening, a simulation flattening boundary condition is established, and the flattening of the finite element grid model is realized based on the established boundary condition. As shown in FIG. 5(b), it is a schematic diagram of the flattened finite element grid model.

[0069] In step S103, all node data in the flattened finite element grid model is obtained, and the node data is taken as a flat point cloud.

[0070] Specifically, after obtaining the flattened finite element grid model as shown in FIG. 5(b), all node data in the model is extracted, as shown in FIG. 6(a), it is the node data of the flattened finite element grid model, and the extracted all node data is taken as a flat point cloud, and subsequent size measurement of the crater is carried out based on the obtained flat point cloud. Figure 6 Specifically, after obtaining the flattened finite element grid model as shown in FIG. 5(b), all node data in the model is extracted, as shown in FIG. 6(a), it is the node data of the flattened finite element grid model, and the extracted all node data is taken as a flat point cloud, and subsequent size measurement of the crater is carried out based on the obtained flat point cloud.

[0071] In the present embodiment, after obtaining the flat point cloud, the flat point cloud is fitted to obtain a geometric plane, and the flat point cloud is divided into a plane point cloud and a crater point cloud based on the fitted geometric plane, as shown in FIG. 7(a), it is the plane point cloud, and as shown in FIG. 7(b), it is the crater point cloud. Figure 6 In the present embodiment, after obtaining the flat point cloud, the flat point cloud is fitted to obtain a geometric plane, and the flat point cloud is divided into a plane point cloud and a crater point cloud based on the fitted geometric plane, as shown in FIG. 7(a), it is the plane point cloud, and as shown in FIG. 7(b), it is the crater point cloud. Figure 3 As shown in FIG. 7(a), the node data of the flattened finite element grid model, compared with the shot forming part surface point cloud data as shown in FIG. 6(b), since the whole two pieces are pressed onto a plane through the simulation flattening operation, the calculation process of the crater measurement is simplified, and the overall efficiency of the crater measurement is improved. Of course, the present embodiment is only an example, and the specific number of flat point clouds contained in the flattened finite element grid model is not limited.

[0072] In step S104, the crater point cloud is screened out from the flat point cloud, and the diameter and depth of each crater are obtained by measuring the crater point cloud.

[0073] Optionally, the crater point cloud is screened out from the flat point cloud, including: fitting the flat point cloud to obtain a geometric plane; and dividing the flat point cloud into a crater point cloud and a plane point cloud based on the geometric plane, wherein the plane point cloud is located on the geometric plane, and the crater point cloud is located outside the geometric plane.

[0074] In the present embodiment, after obtaining the flat point cloud, the flat point cloud is fitted to obtain a geometric plane, and the flat point cloud is divided into a plane point cloud and a crater point cloud based on the fitted geometric plane, as shown in FIG. 7(a), it is the plane point cloud, and as shown in FIG. 7(b), it is the crater point cloud. Figure 7 In the present embodiment, after obtaining the flat point cloud, the flat point cloud is fitted to obtain a geometric plane, and the flat point cloud is divided into a plane point cloud and a crater point cloud based on the fitted geometric plane, as shown in FIG. 7(a), it is the plane point cloud, and as shown in FIG. 7(b), it is the crater point cloud. Figure 8The crater point cloud is shown. In the embodiment, the specific number of the planar point cloud and the crater point cloud is not limited. In the segmentation based on the geometric plane, the flat point cloud located on the geometric plane is taken as the planar point cloud, and the flat point cloud located outside the geometric plane is taken as the crater point cloud.

[0075] Optionally, the diameter and depth of each crater are obtained by measuring the crater point cloud, including: clustering the crater point cloud by using a clustering algorithm to obtain a plurality of point cloud clusters, wherein each point cloud cluster corresponds to one crater; obtaining the minimum outer frame corresponding to each point cloud cluster, and determining the diameter of the crater corresponding to the point cloud cluster according to the minimum outer frame; obtaining the maximum distance of each point cloud cluster from the geometric plane, and determining the depth of the crater corresponding to the point cloud cluster according to the maximum distance.

[0076] In one specific implementation, after obtaining the crater point cloud, the crater point cloud is clustered according to a clustering algorithm to obtain a plurality of point cloud clusters, wherein the distance between the crater point clouds located in the same point cloud cluster is within a specified range. In the embodiment, the distance between the crater point clouds contained in each point cloud cluster is not limited, so that each point cloud cluster corresponds to one crater. Among them, the crater point clouds in the same point cloud cluster are not located on the planar point cloud, and the distance from the geometric plane is different. Therefore, in the embodiment, the maximum distance of the point cloud cluster from the geometric plane is obtained, and the maximum distance is taken as the depth of the crater. For example, the point cloud cluster corresponding to the crater X contains four crater point clouds, a, b, c, and d, and the vertical distances of the four crater point clouds from the geometric plane are a=1, b=3, c=4, and d=2, respectively. It is determined that the depth of the crater X is 4. In addition, the minimum outer frame corresponding to each point cloud cluster is obtained, and the diameter of the crater corresponding to the point cloud cluster is determined according to the minimum outer frame. For example, the minimum outer frame surrounding the four crater point clouds a, b, c, and d has a side length of 8, and 8 is taken as the diameter of the crater X. Of course, the embodiment is only an example, and in actual application, each crater corresponds to a point cloud cluster containing a large number of crater point clouds. In the embodiment, the specific number of crater point clouds contained in each point cloud cluster is not limited.

[0077] Optionally, after the crater point cloud is clustered by using a clustering algorithm to obtain a plurality of point cloud clusters, it further includes: receiving a crater group measurement instruction, wherein the crater group measurement instruction includes a point cloud cluster number; determining a target point cloud cluster according to the point cloud cluster number, wherein each target point cloud cluster corresponds to one crater group; obtaining the minimum outer frame corresponding to each target point cloud cluster, and determining the diameter of the crater group corresponding to the target point cloud cluster according to the minimum outer frame; obtaining the maximum distance of each target point cloud cluster from the geometric plane, and determining the depth of the crater group corresponding to the target point cloud cluster according to the maximum distance.

[0078] It should be noted that in this embodiment, the size of the designated crater group is also measured according to the user's crater group measurement instruction, wherein the crater group is composed of a plurality of adjacent craters. When measuring the crater group, the point cloud cluster numbers contained in the instruction are obtained, for example, e, f and g, the point cloud cluster e corresponds to the crater A, the point cloud cluster B corresponds to the crater A, and the point cloud cluster g corresponds to the crater C. The point cloud clusters indicated by the point cloud cluster numbers are clustered to obtain target point cloud clusters, and the target point cloud clusters correspond to one crater group, for example, the crater group is specifically composed of craters A, B and C. In this embodiment, the specific number of craters contained in the crater group is not limited. The size measurement method of the crater group is roughly the same as the measurement method of the crater. The diameter is specifically determined by the smallest outer frame, and the depth is determined by the maximum distance between the target point cloud cluster and the geometric plane. This embodiment will not be described again.

[0079] In the embodiment of the application, the point cloud data of the shot forming part surface is obtained, and the finite element grid model is converted for flattening simulation processing. The diameter and depth of the crater are obtained based on the flattened finite element grid model, which avoids the crater area segmentation error caused by edge segmentation, thereby improving the accuracy of the crater size measurement.

[0080] Example two

[0081] Figure 9 The flowchart of the shot forming crater size measurement method provided in the embodiment two of the application is specifically described based on the above-mentioned embodiment. As shown in Figure 6 The method comprises the following steps:

[0082] Step S201, scanning the surface of the shot forming part to obtain point cloud data, and obtaining a finite element grid model based on the point cloud data.

[0083] Optionally, after scanning the surface of the shot forming part to obtain point cloud data, the method further comprises: denoising the point cloud data to obtain denoised point cloud data; and obtaining a finite element grid model based on the point cloud data, which comprises: obtaining a finite element grid model based on the denoised point cloud data.

[0084] Optionally, obtaining a finite element grid model based on the denoised point cloud data comprises: performing geometric reconstruction on the denoised point cloud data using a geometric reconstruction function to obtain a three-dimensional lithography STL geometric surface; extracting node coordinates and connection relationships of triangular facets on the STL geometric surface; and establishing a finite element grid model according to the node coordinates and the connection relationships.

[0085] Step S202, establishing a simulation flattening boundary condition.

[0086] Specifically, in order to simplify the calculation process of the measurement, the finite element grid model obtained in the embodiment is flattened, and the boundary conditions for flattening simulation are established before flattening by simulation. The boundary conditions include setting a rigid plane on the first plane of the finite element grid model of the crater depression, and setting a specified strength pressure load on the second plane of the finite element grid model of the crater protrusion. The set pressure load needs to flatten the finite element grid model of the part, but the crater area needs to remain in a depressed state, that is, the size of the load pressure can only flatten the part, but not the crater, and as long as the pressure load can achieve this effect, it is within the protection scope of the application.

[0087] Step S203, flattening the finite element grid model based on the boundary conditions to obtain a flattened finite element grid model.

[0088] Optionally, flattening the finite element grid model based on the boundary conditions to obtain a flattened finite element grid model includes: contacting the first plane of the finite element grid model with a rigid plane; and applying a pressure load on the second plane of the finite element grid model to flatten the finite element grid model on the rigid plane to obtain a flattened finite element grid model, wherein the crater area remains in a depressed state.

[0089] Specifically, as shown in Figure 10 The simulation modeling diagram for flattening is shown. In the embodiment, the first plane of the finite element grid model is contacted with a rigid plane, and a pressure load is applied on the second plane of the finite element grid model. The part of the finite grid model far from the rigid plane gradually approaches the flattening load, and finally contacts and fits with the rigid plane, that is, the finite element grid model is flattened on the rigid plane. Since the set pressure load is not enough to change the crater, the final finite element grid model of the part becomes flat, but the crater area remains in a depressed state.

[0090] Step S204, obtaining all node data in the flattened finite element grid model, and taking the node data as a flat point cloud.

[0091] Step S205, screening out crater point clouds from the flat point cloud, and measuring the diameter and depth of each crater.

[0092] Optionally, screening out the crater point cloud from the flat point cloud includes: fitting a geometric plane according to the flat point cloud; and segmenting the flat point cloud according to the geometric plane to obtain the crater point cloud and a plane point cloud, wherein the plane point cloud is located on the geometric plane, and the crater point cloud is located outside the geometric plane.

[0093] Optionally, the diameter and depth of each crater are obtained by measuring the crater point cloud, including: clustering the crater point cloud using a clustering algorithm to obtain a plurality of point cloud clusters, wherein each point cloud cluster corresponds to a crater; obtaining the minimum outer frame corresponding to each point cloud cluster, and determining the diameter of the crater corresponding to the point cloud cluster according to the minimum outer frame; obtaining the maximum distance of each point cloud cluster from the geometric plane, and determining the depth of the crater corresponding to the point cloud cluster according to the maximum distance.

[0094] Optionally, after the plurality of point cloud clusters are obtained by clustering the crater point cloud using a clustering algorithm, the method further includes: receiving a crater group measurement instruction, wherein the crater group measurement instruction includes a point cloud cluster number; determining a target point cloud cluster according to the point cloud cluster number, wherein each target point cloud cluster corresponds to a crater group; obtaining the minimum outer frame corresponding to each target point cloud cluster, and determining the diameter of the crater group corresponding to the target point cloud cluster according to the minimum outer frame; obtaining the maximum distance of each target point cloud cluster from the geometric plane, and determining the depth of the crater group corresponding to the target point cloud cluster according to the maximum distance.

[0095] In the embodiments of the present application, the point cloud data of the shot forming part surface is obtained, and is converted into a finite element grid model for flattening simulation processing, and the diameter and depth of the crater are obtained based on the flattened finite element grid model, which avoids the crater area segmentation error caused by edge segmentation, thereby improving the accuracy of the crater size measurement.

[0096] Embodiment three

[0097] Figure 11 The structure schematic diagram of the shot forming crater size measurement device provided by the embodiment three of the present application is shown in FIG. 3. Figure 11 As shown in the figure, the device includes a finite element grid model acquisition module 310, a finite element grid model flattening module 320, a flat point cloud acquisition module 330, and a crater measurement module 340.

[0098] The finite element grid model acquisition module 310 is configured to scan the surface of the shot forming part to obtain point cloud data, and obtain a finite element grid model based on the point cloud data.

[0099] The finite element grid model flattening module 320 is configured to flatten the finite element grid model to obtain a flattened finite element grid model.

[0100] The flat point cloud acquisition module 330 is configured to obtain all node data in the flattened finite element grid model, and take the node data as a flat point cloud.

[0101] The crater measurement module 340 is configured to screen crater point cloud from the flat point cloud, and measure the crater point cloud to obtain the diameter and depth of each crater.

[0102] Optionally, the device further comprises a denoising module configured to perform denoising processing on the point cloud data to obtain denoised point cloud data; and a finite element mesh model acquisition module configured to acquire the finite element mesh model based on the denoised point cloud data.

[0103] Optionally, the finite element mesh model acquisition module is configured to perform geometric reconstruction on the denoised point cloud data using a geometric reconstruction function to obtain a three-dimensional lithography STL geometric surface.

[0104] The node coordinates and connection relationship of the triangular facets on the STL geometric surface are extracted.

[0105] The finite element mesh model is established according to the node coordinates and connection relationship.

[0106] Optionally, the finite element mesh model flattening module is configured to establish a simulation flattening boundary condition, wherein the boundary condition comprises setting a rigid plane on a first plane of the finite element mesh model crater depression and setting a specified intensity pressure load on a second plane of the finite element mesh model crater protrusion.

[0107] The finite element mesh model is flattened based on the boundary condition to obtain a flattened finite element mesh model.

[0108] Optionally, the finite element mesh model flattening module is configured to contact the first plane of the finite element mesh model with the rigid plane.

[0109] The pressure load is applied to the second plane of the finite element mesh model to flatten the finite element mesh model on the rigid plane to obtain a flattened finite element mesh model, wherein the crater region remains in a depressed state.

[0110] Optionally, the crater measurement module comprises a crater point cloud screening unit configured to fit a geometric plane according to the flat point cloud.

[0111] The flat point cloud is segmented according to the geometric plane to obtain crater point cloud and plane point cloud, wherein the plane point cloud is located on the geometric plane and the crater point cloud is located outside the geometric plane.

[0112] Optionally, the crater measurement module further comprises a crater size measurement unit configured to perform clustering on the crater point cloud using a clustering algorithm to obtain a plurality of point cloud clusters, wherein each point cloud cluster corresponds to a crater.

[0113] The minimum outer frame corresponding to each point cloud cluster is obtained, and the diameter of the crater corresponding to the point cloud cluster is determined according to the minimum outer frame.

[0114] The maximum distance between each point cloud cluster and the geometric plane is obtained, and the depth of the crater corresponding to the point cloud cluster is determined according to the maximum distance.

[0115] Optionally, the device further comprises a crater cluster measurement module configured to receive a crater cluster measurement instruction, wherein the crater cluster measurement instruction comprises a point cloud cluster number.

[0116] determine a target point cloud cluster according to the point cloud cluster number, wherein each target point cloud cluster corresponds to a crater cluster respectively;

[0117] obtain a minimum outer frame corresponding to each target point cloud cluster, and determine a diameter of the crater cluster corresponding to the target point cloud cluster according to the minimum outer frame;

[0118] obtain a maximum distance between each target point cloud cluster and the geometric plane, and determine a depth of the crater cluster corresponding to the target point cloud cluster according to the maximum distance.

[0119] The size measurement device for shot forming craters provided by the embodiments of the present application can execute the size measurement method for shot forming craters provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0120] Embodiment four

[0121] Figure 12 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the applications described and / or claimed in this document.

[0122] As shown in the figure, Figure 12 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., connected to the at least one processor 11 in communication, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0123] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0124] The processor 11 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the operation indicator data simulation method.

[0125] In some embodiments, the operation indicator data simulation method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the operation indicator data simulation method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the operation indicator data simulation method by any other appropriate means, such as by means of firmware.

[0126] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0127] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package and partially on a remote machine or entirely on a remote machine or server.

[0128] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0129] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0130] The systems and techniques described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described herein, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0131] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0132] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in different orders, as long as the desired results of the technical solutions of the present disclosure can be achieved, and the present disclosure is not limited herein.

[0133] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for measuring the size of a shot peening crater, characterized in that: include: Scanning the surface of the shot-peened part to obtain point cloud data, and obtaining a finite element mesh model based on the point cloud data; Flattening the finite element mesh model to obtain a flattened finite element mesh model; Acquire all node data in the flattened finite element mesh model and use the node data as a flattened point cloud; A crater point cloud is selected from the flattened point cloud, and the crater point cloud is measured to obtain the diameter and depth of each crater.

2. The method according to claim 1, characterized in that After scanning the surface of the shot peening part to obtain point cloud data, the method further includes: Performing denoising on the point cloud data to obtain denoised point cloud data; The obtaining of a finite element mesh model based on the point cloud data comprises: The finite element mesh model is obtained based on the denoised point cloud data.

3. The method according to claim 2, characterized in that The obtaining of the finite element mesh model based on the denoised point cloud data comprises: Performing geometric reconstruction on the denoised point cloud data using a geometric reconstruction function to obtain a three-dimensional STL geometric surface; Extracting node coordinates and connection relationships of triangular facets on the STL geometric surface; The finite element mesh model is established according to the node coordinates and the connection relationship.

4. The method according to claim 1, wherein The step of flattening the finite element mesh model to obtain a flattened finite element mesh model includes: Establishing boundary conditions for simulated flattening, wherein the boundary conditions include setting a rigid plane on a first plane where the finite element mesh model crater is concave, and setting a pressure load of a specified intensity on a second plane where the finite element mesh model crater is convex; The finite element mesh model is flattened based on the boundary conditions to obtain a flattened finite element mesh model.

5. The method according to claim 4, characterized in that The step of flattening the finite element mesh model based on the boundary condition to obtain a flattened finite element mesh model includes: contacting the first plane of the finite element mesh model with the rigid plane; The pressure load is applied to the second plane of the finite element mesh model to flatten the finite element mesh model onto the rigid plane to obtain the flattened finite element mesh model, wherein the crater area still remains in a concave state.

6. The method according to claim 1, characterized in that The step of filtering out the crater point cloud from the flattened point cloud comprises: Perform fitting according to the flattened point cloud to obtain a geometric plane; The flattened point cloud is segmented according to the geometric plane to obtain the crater point cloud and the plane point cloud, wherein the plane point cloud is located on the geometric plane and the crater point cloud is located outside the geometric plane.

7. The method according to claim 6, characterized in that Measuring the crater point cloud to obtain the diameter and depth of each crater includes: Clustering the crater point cloud using a clustering algorithm to obtain multiple point cloud clusters, wherein each point cloud cluster corresponds to a crater; Obtaining a minimum outer frame corresponding to each of the point cloud clusters, and determining a diameter of the crater corresponding to the point cloud cluster according to the minimum outer frame; The maximum distance between each point cloud cluster and the geometric plane is obtained, and the depth of the crater corresponding to the point cloud cluster is determined according to the maximum distance.

8. The method according to claim 5, characterized in that After clustering the crater point cloud using a clustering algorithm to obtain a plurality of point cloud clusters, the method further includes: receiving a crater cluster measurement instruction, wherein the crater cluster measurement instruction includes a point cloud cluster number; Determining a target point cloud cluster according to the point cloud cluster number, wherein each target point cloud cluster corresponds to a crater group; Obtaining a minimum outer frame corresponding to each target point cloud cluster, and determining the diameter of the crater cluster corresponding to the target point cloud cluster according to the minimum outer frame; The maximum distance between each target point cloud cluster and the geometric plane is obtained, and the depth of the crater group corresponding to the target point cloud cluster is determined according to the maximum distance.

9. A device for measuring the size of shot peening craters, characterized in that: include: A finite element mesh model acquisition module is used to scan the surface of the shot peening part to obtain point cloud data, and obtain a finite element mesh model based on the point cloud data; A finite element mesh model flattening module, configured to flatten the finite element mesh model to obtain a flattened finite element mesh model; a flattened point cloud acquisition module, configured to acquire all node data in the flattened finite element mesh model and use the node data as a flattened point cloud; The crater measurement module is used to filter out crater point clouds from the flattened point cloud, and measure the crater point clouds to obtain the diameter and depth of each crater.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method according to any one of claims 1 to 7 when executed.

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