Real-time detection method for curved surfaces of honeycomb core material and various complex parts
Through contactless 3D scanning technology, the shape of honeycomb core materials and complex parts is captured and processed, and the problems of low measurement efficiency and accuracy in the prior art are solved, and efficient and accurate dimensional detection and processing adjustment are achieved.
Patent Information
- Application Number
- CN202411467265.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-21
- Publication Date
- 2025-01-03
AI Technical Summary
The prior art is difficult to accurately measure the curved surface of honeycomb core materials and complex parts, the efficiency and accuracy of conventional measurement methods are low, and the honeycomb core materials are prone to deformation, resulting in inaccurate measurement results.
Using contactless 3D scanning technology, the shape and size data of the target object are captured through the scanner, data processing and model generation are carried out, and converted into a digital point cloud or mesh model, texture mapping and solidification are carried out, and finally with the standard design. Comparative measurement of drawings.
Improve measurement efficiency and accuracy, avoid damage to the workpiece by contact measurement, ensure machining accuracy and reduce secondary clamping errors.
Smart Images
Figure CN119245547A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of detection, in particular to the technical field of real-time detection methods for workpieces. Background Art
[0002] Honeycomb core materials are composed of a series of thin-walled units in hexagonal (most common) or other shapes (such as square, round, etc., but the hexagonal structure has the best mechanical properties), which are connected to form a honeycomb-like structure. The thin-walled units support each other to form a stable three-dimensional structure. Due to its internal hollow structure, the density of the honeycomb core material is very low. For example, the density of aluminum honeycomb core is usually between 30-60kg / m³, which makes it very advantageous in weight-sensitive applications.
[0003] Despite its low density, honeycomb core materials have excellent performance in terms of bearing pressure, tension and shear forces. Its structure can effectively disperse external forces to each thin-walled unit. In the aerospace field, it can meet the structural strength requirements while reducing weight. The hollow structure prevents the effective transfer of heat and sound. In the construction field, honeycomb core materials can be used to manufacture insulation boards and soundproof walls. It has strong designability and can change the size, shape, wall thickness and material of the honeycomb unit according to different needs, so as to meet a variety of application scenarios from industry to civil use.
[0004] Due to the special composition structure of the honeycomb core material, the conventional measurement method cannot accurately select the measurement point when measuring, because the selected measurement point may just be located at the position of the hole of the honeycomb core material, so the measurement point cannot be selected. In addition, the honeycomb core material has good elasticity. When the measuring tool contacts the honeycomb core material, elastic deformation is very likely to occur, and it cannot be accurately measured. Conventional measurement methods need to select more measurement points to measure complex parts surfaces, and the measurement efficiency and accuracy are low. Summary of the invention
[0005] The purpose of the present invention is to solve the problems in the prior art, propose a real-time detection method for honeycomb core materials and various complex parts surfaces, and provide a non-contact 3D scanning measurement method, which scans the model of honeycomb core materials or complex parts through a scanner and then processes the model software for measurement.
[0006] To achieve the above object, the present invention proposes a real-time detection method for honeycomb core materials and various complex parts surfaces, comprising the following steps: Step S1, data acquisition, using a scanner to scan the target object, the scanner sends rays or light to the target object and records their interaction with the surface of the target object, thereby capturing the shape, size and surface details of the object; Step S2, data processing, pre-processing and processing the data collected by the scanner, and converting it into a digital point cloud or mesh model; if it is converted into a digital point cloud, jump to step S3, if it is generated into a mesh model, jump to step S4; Step S3, mesh generation, processing the point cloud data obtained in step S2, connecting each discrete point cloud data to convert it into a continuous object surface mesh model; Step S4, texture mapping, mapping the real texture of the target object onto the generated mesh model; Step S5, converting into a solid model, converting the mesh model processed in step S4 into a solid model; Step S6, measuring the converted solid model to obtain the required size, and comparing the scanned solid model with the digital model of the standard design drawing to obtain the size deviation between the workpiece and the drawing.
[0007] Preferably, the preprocessing in step S2 includes removing irrelevant data points, filtering noise and registering the point cloud.
[0008] Preferably, the step S2 further comprises data stitching, stitching together a plurality of scan data to form a complete digital model of the target object.
[0009] Preferably, the data stitching process is performed by matching shared feature points or using overlapping areas for registration.
[0010] Preferably, when registering by matching shared feature points, the scanner first uses itself to collect data on the surface of the object, and in the collected image or point cloud data, unique feature points are detected by an algorithm; Under different scanning angles, if there are common feature points, the feature points are identified. Once the feature points are identified, data fusion can be performed. During the fusion process, the relative positions of different scanning parts are adjusted according to the consistency of the shared feature points and point cloud data in the overlapping area.
[0011] Preferably, the feature points are places where the texture of the surface of the object changes, corners of geometric shapes, or places where the color changes significantly.
[0012] Preferably, when registering by identifying overlapping regions, when scanning an object, adjacent scanning regions may have overlapping portions, and the scanner compares data from different scanning positions to identify these overlapping regions; Once the overlapping areas are identified, data fusion can be performed. During the fusion process, the relative positions of different scan parts are adjusted based on the consistency of shared feature points and point cloud data in the overlapping areas.
[0013] Preferably, for scanners based on laser scanning, the spatial positions of points in the point cloud data are compared; for scanners based on structured light scanning, the image data features in the overlapping area are compared.
[0014] The beneficial effects of the real-time detection method for honeycomb core materials and various complex parts surfaces of the present invention are as follows: the present invention uses a scanner to capture the geometric shape and appearance features of the target honeycomb core material or complex parts, and converts them into a digital model, and then uses software to solidify the model of the honeycomb core material or complex parts for measurement. Thus, the size information of the target honeycomb core material or complex part is obtained, and the measurement efficiency and measurement accuracy are improved. There is no need to contact the workpiece during measurement, which solves the problem that the honeycomb core material is easily deformed when conventional contact measuring tools measure the honeycomb core material, resulting in inaccurate measurement results. Non-contact size detection can effectively protect the workpiece from being damaged during the measurement process. During the processing process, the three-dimensional real-time digital model of the processed workpiece can be scanned at any time for comparison with the digital model of the standard design drawing. Once a deviation is found, it can be adjusted in time to ensure the processing accuracy and avoid errors caused by secondary clamping.
[0015] The features and advantages of the present invention will be described in detail through embodiments in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 It is a schematic diagram of scanning a target object in step S1 of a real-time detection method for honeycomb core materials and various complex parts surfaces of the present invention.
[0017] Figure 2 is a schematic diagram of the model obtained by scanning in step S1.
[0018] Figure 3 It is a schematic diagram of the process of conversion into a solid model.
[0019] Figure 4 This is a schematic diagram of the model before removing the redundant ones.
[0020] Figure 5 This is a schematic diagram after removing redundant models.
[0021] Figure 6 This is a schematic diagram of the model smoothing process.
[0022] Figure 7 Step S6 is to import the obtained solid model and the design 3D drawing into the detection software for comparison detection. Figure 1 .
[0023] Figure 8 Step S6 is to import the obtained solid model and the design 3D drawing into the detection software for comparison detection. Figure 2 .
[0024] Fig. 9 Step S6 is to import the obtained solid model and the designed 3D drawing into the detection software at the same time for comparison and detection result diagram.
[0025] Fig.10 This is a schematic diagram of directly measuring the obtained solid model in step S6.
[0026] in: DETAILED DESCRIPTION
[0027] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below through the accompanying drawings and embodiments. However, 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 scope of the present invention. In addition, in the following description, the description of known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.
[0028] In the description of the present invention, it should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element.
[0029] In the description of the present invention, it should be noted that the terms "center", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the invention product is usually placed when in use, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third" and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. "Several" means one or more, unless otherwise clearly and specifically defined.
[0030] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. Example
[0031] The present invention provides a real-time detection method for honeycomb core materials and various complex parts surfaces, comprising the following steps: Step S1, data collection, see Figure 1 , Figure 2 , use a laser scanner to scan the target object, such as Figure 1 As shown, in this embodiment, the target object is a honeycomb core material, and the laser scanner sends rays or light lines to the target object in different ways, and records their interactions with the surface of the target object, so as to capture the shape, size and surface details of the object; the laser scanner in this embodiment uses blue light, and the blue light emission: using the high energy and short wavelength of blue light, by scanning the surface of the object, the shape and texture information of the surface of the object is converted into digital signals, and then processed and reconstructed by a computer to obtain a three-dimensional model of the object; Step S2, data processing, preprocessing and processing the data collected by the scanner to convert it into a digital point cloud or mesh model; wherein the preprocessing includes removing irrelevant data points, filtering noise and registering the point cloud to ensure accuracy and consistency; if the conversion is converted into a digital point cloud, jump to step S3, if the mesh model is generated, jump to step S4; If the scanning range in step S2 is relatively large or scanning needs to be performed from different angles, multiple scan data need to be stitched together to form a complete digital model of the honeycomb core material. The stitching process is performed by matching shared feature points or using overlapping areas for registration: Among them, when registering by matching shared feature points, the scanner first uses itself to collect data on the surface of the object, and in the collected image or point cloud data, the algorithm detects unique feature points; Under different scanning angles, if there are common feature points, the feature points are identified. Once the feature points are identified, data fusion can be performed. During the fusion process, the relative positions of different scanned parts are adjusted according to the consistency of the shared feature points and point cloud data in the overlapping area. Common algorithms are based on feature descriptors, such as SIFT (Scale Invariant Feature Transform) or SURF (Speeded Up Robust Features) algorithms. These algorithms can generate a unique descriptor for each feature point, so that under different viewing angles, even if the appearance of the feature point may change due to changes in viewing angle, it can still be matched through descriptors; in addition to feature descriptors, geometric constraints are also used to improve the accuracy of matching. Since 3D objects have certain geometric shapes, the relative positions of shared feature points in space should satisfy certain geometric relationships. For example, if the same corner point of a cuboid is scanned from two different viewing angles, the distance and angle relationship of this corner point relative to other points under the two viewing angles should be consistent. By establishing such a geometric constraint model, the matching of shared feature points can be further screened and confirmed.
[0032] When registering by identifying overlapping areas, when scanning an object, there will be overlapping parts in adjacent scanning areas. The scanner compares the data of different scanning positions to identify these overlapping areas. For handheld 3D scanners based on laser scanning, the spatial positions of points in the point cloud data are compared; for those based on structured light scanning, the image data features in the overlapping area are compared. For example, when scanning a large mechanical part, two adjacent scans may have some overlapping areas. The overlapping area can be determined by analyzing the point cloud density or image texture.
[0033] Once the overlapping area is identified, data fusion can be performed. During the fusion process, the relative positions of different scanned parts are adjusted according to the consistency of the shared feature points and point cloud data in the overlapping area. For example, if there are 5 shared feature points matched successfully in the overlapping area, the precise position relationship of these points can be used to stitch two adjacent scan data together to obtain a complete and continuous 3D model. At the same time, the data in the overlapping area will be optimized to remove duplicate data points and improve the quality of the 3D model. Step S3, mesh generation, processing the point cloud data obtained in step S2, connecting each discrete point cloud data to convert it into a continuous object surface mesh model; these meshes can be patches composed of triangles, quadrilaterals or other geometric shapes. The density and accuracy of the mesh can be adjusted as needed; When a 3D scanner scans an object, the first thing it gets is point cloud data on the object's surface. These point clouds are a series of discrete points, each with its three-dimensional coordinates, representing a sampling point on the object's surface. Mesh generation is the process of converting these discrete point cloud data into a continuous surface representation, usually a triangular mesh.
[0034] For example, when scanning a statue, the scanner obtains the coordinate information of many discrete points on the statue's surface. Mesh generation is to connect these points to construct a continuous mesh structure that approximates the shape of the statue's surface.
[0035] In the process of mesh generation, the most common method is to construct a triangular mesh. This is based on a mathematical algorithm to connect the points in the point cloud data into triangles. For example, the Delaunay triangulation algorithm is used. This algorithm reasonably selects points to construct triangles based on the spatial relationship between the points, making the shape of the triangle as regular as possible and satisfying certain geometric optimization conditions.
[0036] The vertices of each triangle are points in the point cloud, and many triangles are connected to form a mesh that can approximate the surface shape of the object. For objects with complex shapes, there will be thousands of triangles connected to each other to accurately depict the geometric shape of the object.
[0037] Data in the form of a mesh is more convenient for subsequent operations. In computer graphics, a triangular mesh is a common way to represent the shape of a three-dimensional object. After the mesh is generated, operations such as rendering, animation, and 3D printing can be performed.
[0038] For example, in the field of 3D printing, the model data recognized by 3D printers is usually in the form of meshes. After the 3D scanner converts the scanned point cloud into a mesh, it can directly transmit the data to the 3D printer for printing, thus creating a solid object similar to the scanned object. At the same time, in computer rendering scenes, the mesh model can be better combined with the lighting model, etc., to present a realistic visual effect.
[0039] Step S4, texture mapping, mapping the real texture of the target object onto the generated mesh model; this can make the model more realistic; Step S5, converting into a solid model, see Figure 3 , Figure 4 , the grid model processed in step S4 is converted into a solid model; in order to facilitate the selection of measurement points on the model, the digital model of the honeycomb core material needs to be converted into a solid model to perform various size measurements. The software used for converting to a solid model in this embodiment is the existing post-processing software for solid conversion.
[0040] To improve measurement accuracy, refer to Figure 4 , Figure 5 and Figure 6 This step also includes removing redundant models and model smoothing steps until the model has clear edges.
[0041] Step S6, measuring the converted solid model to obtain the required size, and comparing the scanned solid model with the digital model of the standard design drawing to obtain the size deviation between the workpiece and the drawing.
[0042] There are two comparison methods in this embodiment. Comparison method 1 is as follows: Figure 7 , Figure 8 , Fig. 9 As shown, the obtained solid model and the designed 3D drawing are simultaneously imported into the inspection software for comparative inspection, the two models are overlapped and compared, and the dimensional deviation between the workpiece and the drawing is analyzed based on the comparison results; Comparison method 2 Fig.10 As shown, the obtained solid model is directly measured to obtain the required size. The method of this embodiment uses a scanner to capture the geometric shape and appearance characteristics of the target honeycomb core material, and converts it into a digital model, and then uses software to solidify the model of the honeycomb core material for measurement. In this way, the size information of the target honeycomb core material or complex parts is obtained, and the measurement efficiency and measurement accuracy are improved. There is no need to contact the workpiece during measurement, which solves the problem that the honeycomb core material is easily deformed when measuring the honeycomb core material with conventional contact measuring tools, resulting in inaccurate measurement results.
[0043] The three-dimensional laser scanner used in the first embodiment emits light in the following ways: The way handheld 3D scanners emit light varies from device to device. The most common ones are as follows: Pulse emission: By emitting a single-point, high-energy and extremely short-duration laser pulse, the three-dimensional coordinates of the object's surface are determined by measuring the flight time of the light.
[0044] Phase emission: emits an uninterrupted beam of continuous laser light with an integer wavelength, and calculates and records the distance of the target object by measuring the phase difference of the reflected light.
[0045] Laser triangulation method: emit laser to the surface of the object, set a CCD camera or other photoelectric detector at the other end of the baseline to receive the signal reflected by the object, and record the angle between the incident light and the reflected light. The baseline length between the laser light source and the CCD is known. According to the geometric relationship of the triangle, the distance between the scanner and the object can be deduced using this known information.
[0046] Structured light emission: By projecting specific structured light patterns, such as gratings, stripes, etc., onto the surface of an object, and then using a camera or sensor to capture the deformation of these patterns, the three-dimensional shape of the object's surface can be calculated.
[0047] Blue light emission: Using the high energy and short wavelength of blue light, the shape and texture information of the object surface is converted into digital signals by scanning the surface of the object, and then processed and reconstructed by a computer to obtain a three-dimensional model of the object. Embodiment 1 Scanning is performed by blue light emission.
[0048] The standard parts used in this application document can all be purchased from the market, and the specific connection methods of each part adopt mature conventional means such as bolts, rivets, welding, etc. in the prior art. The electric slide rail slide, cylinder, welding machine, electric telescopic rod and internal components of the controller all adopt conventional models in the prior art, and their internal structures belong to the prior art structure. Workers can complete normal operation of them according to the existing technical manual. In addition, the circuit connection adopts the conventional connection method in the prior art, and no specific description is given here.
[0049] It should be noted that, although the above embodiments have been described in this article, the scope of patent protection of the present invention is not limited thereby. Therefore, based on the innovative concept of the present invention, changes and modifications made to the embodiments described herein, or equivalent structures or equivalent process changes made using the contents of the present specification and drawings, directly or indirectly applying the above technical solutions to other related technical fields are all included in the scope of protection of the patent of the present invention.
Claims
1. A real-time detection method for honeycomb core materials and various complex parts surfaces, characterized in that: The following steps are involved: Step S1, data acquisition, using a scanner to scan the target object, the scanner sends rays or light to the target object and records their interaction with the surface of the target object, thereby capturing the shape, size and surface details of the object; Step S2, data processing, pre-processing and processing the data collected by the scanner, and converting it into a digital point cloud or mesh model; if it is converted into a digital point cloud, jump to step S3, if it is generated into a mesh model, jump to step S4; Step S3, mesh generation, processing the point cloud data obtained in step S2, connecting each discrete point cloud data to convert it into a continuous object surface mesh model; Step S4, texture mapping, mapping the real texture of the target object onto the generated mesh model; Step S5, converting into a solid model, converting the mesh model processed in step S4 into a solid model; Step S6, measuring the converted solid model to obtain the required size, and comparing the scanned solid model with the digital model of the standard design drawing to obtain the size deviation between the workpiece and the drawing.
2. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 1, characterized in that: The preprocessing in step S2 includes removing irrelevant data points, filtering noise, and registering the point cloud.
3. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 1, characterized in that: The step S2 also includes data stitching, stitching together a plurality of scanned data to form a complete digital model of the target object.
4. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 3, characterized in that: The data stitching process is performed by matching shared feature points or using overlapping areas for registration.
5. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 4, characterized in that: When registering by matching shared feature points, the scanner first uses itself to collect data on the surface of the object, and in the collected image or point cloud data, the algorithm detects unique feature points; Under different scanning angles, if there are common feature points, the feature points are identified. Once the feature points are identified, data fusion can be performed. During the fusion process, the relative positions of different scanning parts are adjusted according to the consistency of the shared feature points and point cloud data in the overlapping area.
6. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 5, characterized in that: The feature points are places where the texture of the object surface changes, corners of geometric shapes, or places where the color changes significantly.
7. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 5, characterized in that: When registering by identifying overlapping areas, when scanning an object, adjacent scan areas will have overlapping parts, and the scanner compares the data from different scanning positions to identify these overlapping areas; Once the overlapping areas are identified, data fusion can be performed. During the fusion process, the relative positions of different scan parts are adjusted based on the consistency of shared feature points and point cloud data in the overlapping areas.
8. A real-time detection method for honeycomb core materials and various complex parts surfaces as claimed in claim 7, characterized in that: For laser scanning based scanners, the spatial positions of the points in the point cloud data are compared; for structured light scanning based scanners, the image data features in the overlapping area are compared.