Visual detection equipment for appearance of large part

Abstract

The invention discloses visual detection equipment for the appearance of a large part, which relates to the technical field of laser measurement and comprises a laser emitting and receiving module, a laser measurement control unit and a data fusion and processing module, the laser measurement control unit is used for processing and analyzing the received laser signal to obtain distance information of the surface of the part and a three-dimensional model of an actual part; the data fusion and processing module is used for performing fusion processing on the visual detection data and the laser measurement data, analyzing and processing the fused data through a specific algorithm, judging whether the whole part and each part are qualified or not, and generating a detection report; according to the invention, by introducing a laser measurement technology, precise detection and precise size measurement of small defects on the surface of a large part can be realized, and the detection precision is further improved through organic fusion with visual detection data.

Description

Technical Field

[0001] The present invention relates to the technical field of laser measurement, and particularly relates to a visual inspection device for the appearance of large parts. Background Art

[0002] With the development of modern industry, large parts are increasingly widely used in the fields of aerospace, automobile manufacturing, new energy, etc. The quality and performance requirements for large parts are also getting higher and higher. Therefore, more accurate and efficient detection methods are needed, and multi-type auxiliary detection can further improve the accuracy of detection;

[0003] Existing multi-probe detection devices often use spherical fixed brackets to install and fix multiple detection probes. When multiple detection probes are operating, due to the influence of the fixed spacing, the multiple detection probes cannot be adjusted in a narrow area, which causes inconvenience to detection. Moreover, the multiple detection probes installed on the spherical fixed brackets need to rotate the spherical fixed brackets to repeatedly detect a single area, resulting in a reduction in detection efficiency. Therefore, this application designs a visual inspection device for the appearance of large parts to solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to solve the deficiencies in the prior art and propose a visual inspection device for the appearance of large parts.

[0005] To achieve the above purpose, the present invention adopts the following technical solution: A visual inspection device for the appearance of large parts, including a bottom plate. It is characterized in that a placement box is provided on the top surface of the bottom plate. A sliding guide seat is provided at the side end of the placement box. The sliding guide seat is vertically erected on the bottom plate. A manipulator detection mechanism is slidably provided on the sliding guide seat. The manipulator detection mechanism is composed of a mechanical gripper and a detection component. One side of the mechanical gripper is slidably sleeved on the sliding guide seat. A docking seat is provided on the other side of the mechanical gripper. The detection component includes a detection main column, a plurality of movable rotating sleeves, a rotating motor, and a vision detector; the vision detector is used to collect visual detection data of the parts.

[0006] It further includes a laser measurement detection component, and the laser measurement detection component includes a laser emission and reception module, a laser measurement control unit, and a data fusion and processing module;

[0007] The laser emission and reception module is used to send laser signals and receive the laser signals reflected from the surface of the parts;

[0008] The laser measurement control unit is used to adjust the laser emission parameters according to the detection requirements; process and analyze the received laser signals to obtain the distance information of the surface of the parts and the three-dimensional model of the actual parts; wherein the laser emission parameters include the frequency, power, and emission angle of the laser emission.

[0009] The data fusion and processing module is used to fuse and process visual detection data and laser measurement data, analyze and process the fused data through specific algorithms, judge whether the overall parts and each part are qualified, and generate inspection reports.

[0010] Preferably, protective support pads are provided at the bottom ends of the support columns of the placement box, and a support frame for supporting and placing large parts is provided at the upper end of the placement box.

[0011] Preferably, the detection component is composed of a detection main column and a plurality of movable sleeves. The plurality of movable sleeves are clamped on the detection main column at equal intervals. A rotary motor is installed at equal intervals in the detection main column. A transmission disc is installed on the motor shaft of the rotary motor. The transmission disc is convexly provided with protrusions at equal intervals. A fan-shaped notch for rotating the protrusions is opened on the detection main column. The protrusions of the transmission disc are fixedly connected with the movable sleeves, and a visual detector is provided at the bottom end of the detection main column.

[0012] Preferably, a sliding detection column is slidably provided in each of the movable sleeves. A detection probe is installed at the bottom end of the sliding detection column. Two micro-motors driven sliding gears are provided at the upper end of the sliding detection column. A sliding tooth groove for cooperating with the sliding gears is opened in the movable sleeve, and a limit sliding groove for clamping the sliding detection column is opened in the movable sleeve.

[0013] Preferably, multiple groups of laser emission and reception modules are provided. Each group of laser emission and reception modules is installed at the position of the detection main column corresponding to each movable sleeve. The laser emission device emits a laser beam and irradiates it on the surface of the large part. The laser reception device receives the laser signal reflected from the surface of the part.

[0014] Preferably, the received laser signal is processed and analyzed, specifically:

[0015] Identify the inspection requirements of the parts, including the material, surface characteristics and inspection accuracy requirements of the large parts; determine the frequency, power and emission angle of the laser emission according to the inspection requirements;

[0016] Obtain the time length from the laser emission to the reception, and according to the propagation speed of the laser in the air, calculate the distance from the laser emission point to the measurement point on the surface of the part by using a preset formula and record it as the measurement distance;

[0017] Construct a three-dimensional model of the actual part by combining the triangulation principle with the emission angle and the relative position relationship of the measurement points.

[0018] Preferably, the execution steps of the data fusion and processing module are specifically:

[0019] Data alignment: Adopt a feature - point - based matching algorithm to process the laser measurement data and visual inspection data. Extract feature points from the visual images in the visual inspection data and the laser measurement data, and use the descriptors of the feature points for matching to determine their corresponding relationships, thereby achieving spatial alignment of the data;

[0020] Constructing a standard 3D model and defect judgment: According to the design drawings or standard specifications of the parts, preset the standard 3D model of the parts; where the standard 3D model defines the dimensions, shapes, and factory - range information of each part of the parts;

[0021] Compare and analyze the standard 3D model with the 3D model of the actual part. By calculating the deviation of each point between the standard 3D model and the 3D model of the actual part, determine whether there are protruding or sunken areas; identify the area and depth of the protrusion or depression in the protruding or sunken area. When the area or depth of the protruding or sunken area exceeds the preset tolerance range, mark this area as a potential defect area; perform a weighted calculation on the area and depth of the protrusion or depression in the protruding or sunken area to obtain a defect score;

[0022] Divide the parts into several regions according to the structural characteristics and functional importance of the parts for the 3D model of the actual part, and set a regional importance weight for each region;

[0023] Identify the defect scores and the total number of defect areas of the potential defect areas in each region;

[0024] Perform a weighted calculation on all potential defect areas and the total number of defect areas in the region to obtain a regional defect value;

[0025] Then perform a weighted processing on the regional defect values of all divided regions on the part and their corresponding regional importance weights to obtain the comprehensive defect score of the part;

[0026] If the comprehensive defect value is greater than its preset defect threshold, it means the part is unqualified; otherwise, it means the part is qualified;

[0027] Finally, generate an inspection report: Mark the basic information of the part, the qualification rate within the preset production cycle, the change trend of the qualification rate, the detailed information of all potential defect areas, the defect situation of each region, and the overall comprehensive defect score, etc. as the inspection report; The inspection report is presented in a combination of visual charts and text descriptions.

[0028] Preferably, the data fusion and processing module further includes a marking and display module;

[0029] A marking display module is used to, when a component is unqualified, match the defect score of each defect on the component with a preset defect marking value range group to obtain the corresponding defect marking; and visually mark and display the defect marking on a preset three-dimensional model of the component.

[0030] Compared with the prior art, a large component appearance visualization detection device provided by the present invention has the following beneficial effects:

[0031] 1. By introducing laser measurement technology, the present invention can achieve precise detection of minute defects on the surface of large components and accurate dimension measurement, and further improve the detection accuracy through the organic integration with visual detection data.

[0032] 2. By providing a manipulator detection mechanism, the flexible adjustment of the movable rotating sleeve and the sliding detection column in its detection assembly can quickly adapt to the complex structure of components and the requirements of different detection parts; at the same time, the rapid movement of the mechanical gripper makes the detection process more efficient, enabling rapid detection of large components in all directions and at multiple angles, effectively improving the detection efficiency and shortening the detection cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings described herein are used to provide a further understanding of the present invention, form a part of this application, and the schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0034] Figure 1 is an overall schematic diagram of a large component appearance visualization detection device proposed by the present invention;

[0035] Figure 2 is a three-dimensional view of a placement box proposed by the present invention;

[0036] Figure 3 is a three-dimensional view of a manipulator detection assembly proposed by the present invention;

[0037] Figure 4 is a three-dimensional view of a detection assembly proposed by the present invention;

[0038] Figure 5 is a principle block diagram of a laser measurement detection assembly proposed by the present invention.

[0039] Reference numerals in the figures: 1, bottom plate; 2, placement box; 3, sliding guide seat; 4, manipulator detection mechanism; 5, protective support pad; 6, support frame; 7, mechanical gripper; 8, docking seat; 9, detection main column; 10, rotating motor; 11, sliding detection column; 12, sliding tooth groove; 13, sliding gear; 14, limiting sliding groove. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0041] See Figures 1 - 5 , a large part appearance visualization detection device in the present invention includes a bottom plate 1. A placement box 2 is provided on the top surface of the bottom plate 1. A sliding guide seat 3 is provided at the side end of the placement box 2. The sliding guide seat 3 is vertically erected on the bottom plate 1. A manipulator detection mechanism 4 is slidably provided on the sliding guide seat 3. The manipulator detection mechanism 4 is composed of a mechanical gripper 7 and a detection component. One side of the mechanical gripper 7 is slidably sleeved on the sliding guide seat 3. A docking seat 8 is provided on the other side of the mechanical gripper 7. The detection component includes a detection main column 9, a plurality of movable rotating sleeves, a rotating motor 10, and a vision detector; the vision detector is used to collect visual detection data of the part;

[0042] It further includes a laser measurement detection component, which includes a laser emission and reception module, a laser measurement control unit, and a data fusion and processing module;

[0043] The laser emission and reception module is used to send a laser signal and receive the laser signal reflected from the surface of the part;

[0044] The laser measurement control unit is used to adjust the laser emission parameters according to the detection requirements; process and analyze the received laser signal to obtain the distance information of the part surface and the three-dimensional model of the actual part; where the laser emission parameters include the frequency, power, and emission angle of the laser emission;

[0045] The data fusion and processing module is used to fuse and process the visual detection data and the laser measurement data, analyze and process the fused data through a specific algorithm, judge whether the overall part and each part are qualified, and generate a detection report.

[0046] In this application, protective support pads 5 are provided at the bottom ends of the support columns of the placement box 2, and a support frame 6 for supporting and placing large parts is provided at the upper end of the placement box 2.

[0047] In this application, the detection component is composed of a detection main column 9 and a plurality of movable rotating sleeves. The plurality of movable rotating sleeves are equidistantly clamped on the detection main column 9. A rotating motor 10 is equidistantly installed in the detection main column 9. A transmission disk is installed on the motor shaft of the rotating motor 10. The transmission disk is convexly provided with protrusions at equal intervals. A fan-shaped notch for rotating the protrusions is opened on the detection main column 9. The protrusions of the transmission disk are fixedly connected to the movable rotating sleeves, and a vision detector is provided at the bottom end of the detection main column 9.

[0048] In this application, a sliding detection column 11 is slidably provided in each movable rotating sleeve. A detection probe is installed at the bottom end of the sliding detection column 11. Two sliding gears 13 driven by micro-motors are provided at the upper end of the sliding detection column 11. A sliding tooth groove 12 for cooperating with the sliding gear 13 is formed in the movable rotating sleeve, and a limiting sliding groove 14 for clamping the sliding detection column 11 is formed in the movable rotating sleeve.

[0049] In this application, multiple groups of laser emission and reception modules are provided. Each group of laser emission and reception modules is installed at the position of the detection main column 9 corresponding to each movable rotating sleeve. The laser emission device emits a laser beam, which irradiates on the surface of the large component. The laser reception device receives the laser signal reflected from the surface of the component; the laser emission and reception module includes a laser emission device and a laser emission device. By being arranged at different positions, it is possible to measure the surface of the component from different angles, so as to obtain more comprehensive three-dimensional information.

[0050] In this application, the received laser signal is processed and analyzed. Specifically:

[0051] Identify the detection requirements of the component, including the material, surface characteristics and detection accuracy requirements of the large component; determine the laser emission frequency f, power P and emission angle θ according to the detection requirements;

[0052] Obtain the time length from laser emission to reception and record it as t. According to the propagation speed c of the laser in the air, use the preset formula Calculate the distance from the laser emission point to the measurement point on the surface of the component and record it as the measurement distance d; repeatedly obtain the measurement distances at this position multiple times and record them as di (i = 1, 2,..., n). Preprocess the measurement distances, including data filtering and outlier rejection processing; record the preprocessed measurement distances as the preprocessed measurement distances , where i represents the number of any value in a group of different measurement distances;

[0053] Construct a three-dimensional model of the actual component through the triangulation principle in combination with the emission angle and the relative position relationship of the measurement points. Specifically:

[0054] Take the laser emission position as the origin O, the horizontal direction as the x-axis, the vertical direction as the y-axis, and the direction perpendicular to the x and y axes as the z-axis;

[0055] According to the triangulation principle in combination with the emission angle In combination with the preprocessed measurement distance , calculate the three-dimensional coordinates of each measurement point in the coordinate system ; The formula for any three-dimensional coordinate is , , ;

[0056] Combine the three-dimensional coordinates of all measurement points to form point cloud data; then obtain point cloud data at multiple angles and positions to get multiple sets of point cloud data; use the Iterative Closest Point (ICP) algorithm to register the multiple sets of point cloud data to minimize the distance between each set of point clouds; use voxel grid filtering to divide the point cloud into several voxel grids, and only retain one representative point in each voxel grid;

[0057] Convert the processed point cloud data into a continuous surface model through a surface reconstruction algorithm (such as using the moving least squares method to fit a local surface in the neighborhood of each point, and obtaining the surface model of the entire component surface by continuously moving the neighborhood); perform optimization processing on the reconstructed surface model to construct a three-dimensional model of the actual component; where the optimization processing includes smoothing processing and hole filling; when constructing the three-dimensional model of the actual component, a point cloud compression algorithm based on octree can also be used to compress the processed point cloud data to reduce the data storage volume and processing time.

[0058] In this application, the execution steps of the data fusion and processing module are specifically as follows:

[0059] Data alignment: Use a feature point-based matching algorithm (such as the SIFT algorithm) to process the laser measurement data and visual inspection data, extract feature points from the visual image in the visual inspection data and the laser measurement data, and use the descriptors of the feature points for matching to determine their corresponding relationship, thereby achieving spatial alignment of the data. This is prior art and will not be elaborated in detail in this application;

[0060] Construct a standard three-dimensional model and preliminary defect judgment:

[0061] Preset a standard three-dimensional model of the component according to the design drawing or standard specifications of the component; where the standard three-dimensional model defines the dimensions, shapes, and factory range information of each part of the component;

[0062] Compare and analyze the standard three-dimensional model with the three-dimensional model of the actual component. By calculating the deviation of each point between the standard three-dimensional model and the three-dimensional model of the actual component, determine whether there are protruding or concave areas; identify the area A and depth H of the protrusion or depression in the protruding or concave area. When the area or depth of the protruding or concave area exceeds the preset tolerance range, mark this area as a potential defect area; perform a weighted calculation on the area A and depth H of the protrusion or depression in the protruding or concave area to obtain a defect score S;

[0063] The three-dimensional model of the actual component is divided into several regions according to the structural characteristics and functional importance of the component (for example, independent regions are divided for key stress-bearing parts, connection parts, etc.), and a regional importance weight wr is set for each region, with a value range of (0, 1], where r represents the region number;

[0064] Identify the defect score Sj of the potential defect regions and the total number M of defect regions in each region;

[0065] The weighted calculation of all potential defect regions and the total number of defect regions in the region is performed to obtain the regional defect value D, and the formula is expressed as , where j represents the number of the potential defect region, M represents the total number of potential regions, wj represents the severity weight of the potential defect region j, and wm represents the defect quantity weight;

[0066] Then, the regional defect values of all divided regions on the component are weighted with their corresponding regional importance weights to obtain the comprehensive defect score of the component , and the formula is expressed as , where R represents the total number of divided regions, and Dr represents the regional defect value corresponding to region r;

[0067] If the comprehensive defect value is greater than its preset defect threshold, it indicates that the component is unqualified; otherwise, it indicates that the component is qualified;

[0068] Generate an inspection report: Mark the basic information of the component (such as component name, model, batch number, manufacturer), the qualification rate within the preset production cycle, the change trend of the qualification rate, the detailed information of all potential defect regions (including location, area, depth, defect score), the defect situation of each region (regional defect value, regional importance weight), and the overall comprehensive defect score, etc. as the inspection report; The inspection report is presented in a combination of visual charts (such as bar charts showing the comparison of regional defect values and line charts presenting the change trend of the qualification rate) and text descriptions.

[0069] In this application, the data fusion and processing module further includes a marking and display module;

[0070] A marking display module, which is used to match the defect score of each defect on a component with a preset defect marking value range group when the component is unqualified, so as to obtain the corresponding defect marking; visually mark and display the defect marking on the preset three-dimensional model of the component; it should be noted that the preset defect marking value range group includes defect marking value ranges of different levels, for example, minor defects, moderate defects, and severe defects respectively correspond to different score intervals; compare each defect score with the defect marking value range group to determine its category. For example, if a defect score falls within the severe defect value range, the corresponding severe defect marking is matched, providing a basis for subsequent visual marking.

[0071] Using three-dimensional modeling and graphics rendering technologies, at the corresponding defect positions on the three-dimensional model, different levels of defects are marked with different colors, shapes, or patterns; for example, severe defects are marked with eye-catching red triangles, moderate defects are marked with yellow circles, and minor defects are marked with blue squares, which is convenient for staff to intuitively understand the defect positions and severity levels, and quickly evaluate the quality status of the components.

[0072] Through the marking display module, when the component is unqualified, the abstract defect score can be quickly converted into an intuitive visual marking, which is convenient for operators, quality management personnel, and engineers to quickly identify key problem areas, and they can have a clear understanding of the defect situation without complex data analysis, significantly improving the decision-making efficiency and reducing misjudgments and omissions.

[0073] The working principle of a large component appearance visualization detection device provided by the present invention is as follows:

[0074] Preparation stage: Connect the device electrical pipeline on the manipulator detection mechanism 4, and connect the power supply and air pump; place the large component on the support frame 6 of the placement box 2 to complete the preparatory work before detection.

[0075] Detection stage: Start the manipulator detection mechanism 4, and the mechanical gripper 7 drives the detection component to move to a suitable position; the visual detector at the bottom of the detection column 9 starts to conduct a preliminary detection on the large component to obtain the overall appearance information; at the same time, the laser emission and reception module starts to work, emitting a laser beam to the surface of the component; the laser measurement control unit calculates the distance data on the surface of the component in real time according to the reflected laser signal and generates a three-dimensional model of the actual component; the sliding detection column 11 in the movable sleeve can adjust the extended length and angle according to the detection requirements under the cooperation of the sliding gear 13 driven by the micro-motor and the sliding tooth groove 12, further improving the detection accuracy; the rotating motor 10 drives the transmission disc to rotate, and through the cooperation of the convex block and the fan-shaped notch, the movable sleeve rotates to adjust the position of the detection probe, realizing the detection of different parts of the component, and at the same time, it can also flexibly avoid the complex structures on the component, improving the detection efficiency.

[0076] Data processing and analysis stage: The laser measurement control unit transmits the acquired laser measurement data to the data fusion and processing module for fusion with the data collected by the vision detector; this module analyzes and processes the fused data through specific algorithms to determine whether the overall part and each part are qualified and generates an inspection report.

[0077] End stage: After the inspection is completed, the manipulator inspection mechanism 4 returns to its original position, the power supply and air pump are turned off, and the entire inspection process is completed.

[0078] As mentioned above, it is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent replacements or changes, and should be covered by the protection scope of the present invention.

Claims

1. A large component appearance visualization detection device, including a bottom plate (1), characterized in that, A placement box (2) is provided on the top surface of the bottom plate (1). A sliding guide seat (3) is provided at the side end of the placement box (2). The sliding guide seat (3) is vertically erected on the bottom plate (1). A manipulator detection mechanism (4) is slidably provided on the sliding guide seat (3). The manipulator detection mechanism (4) is composed of a mechanical gripper (7) and a detection component. One side of the mechanical gripper (7) is slidably sleeved on the sliding guide seat (3). A docking seat (8) is provided on the other side of the mechanical gripper (7). The detection component includes a detection main column (9), a plurality of movable rotating sleeves, a rotating motor (10), and a vision detector; the vision detector is used to collect visual detection data of parts. It further includes a laser measurement detection component. The laser measurement detection component includes a laser emission and reception module, a laser measurement control unit, and a data fusion and processing module. The laser emission and reception module is used to send laser signals and receive the laser signals reflected from the surface of the parts. The laser measurement control unit is used to adjust the laser emission parameters according to the detection requirements; process and analyze the received laser signals to obtain the distance information of the surface of the parts and the three-dimensional model of the actual parts; where the laser emission parameters include the frequency, power, and emission angle of the laser emission. The data fusion and processing module is used to fuse and process the visual detection data and the laser measurement data, analyze and process the fused data through a specific algorithm, judge whether the whole part and each part are qualified, and generate a detection report.

2. The appearance visualization detection device for large parts according to claim 1, characterized in that, Protective support pads (5) are provided at the bottom ends of the support columns of the placement box (2). A support frame (6) for supporting and placing large parts is provided at the upper end of the placement box (2).

3. The appearance visualization detection device for large parts according to claim 1, characterized in that, The detection component is composed of a detection main column (9) and a plurality of movable rotating sleeves. The plurality of movable rotating sleeves are equidistantly clamped on the detection main column (9). A rotating motor (10) is equidistantly installed in the detection main column (9). A transmission disc is installed on the motor shaft of the rotating motor (10). The transmission disc is convexly provided with protrusions at equal intervals. A fan-shaped notch for rotating the protrusions is opened on the detection main column (9). The protrusions of the transmission disc are fixedly connected to the movable rotating sleeves. A vision detector is provided at the bottom end of the detection main column (9).

4. The appearance visualization detection device for large parts according to claim 3, characterized in that, A sliding detection column (11) is slidably provided in each of the movable rotating sleeves. A detection probe is installed at the bottom end of the sliding detection column (11). Two sliding gears (13) driven by a micro motor are provided at the upper end of the sliding detection column (11). A sliding tooth groove (12) for cooperating with the sliding gears (13) is opened in the movable rotating sleeve. A limit sliding groove (14) for clamping the sliding detection column (11) is opened in the movable rotating sleeve.

5. The appearance visualization detection device for large parts according to claim 1, characterized in that, A plurality of groups of the laser emission and reception modules are provided. Each group of the laser emission and reception modules is installed at the position of the detection main column (9) corresponding to each movable rotating sleeve. The laser emission device emits a laser beam, which irradiates on the surface of the large part. The laser reception device receives the laser signal reflected from the surface of the part.

6. The appearance visualization detection device for large parts according to claim 1, characterized in that Processing and analyzing the received laser signal specifically includes: Identify the inspection requirements for components, including the material, surface characteristics, and inspection accuracy requirements of large components; determine the laser emission frequency, power, and emission angle according to the inspection requirements; Obtain the time length from laser emission to reception, and calculate the distance from the laser emission point to the measurement point on the component surface, denoted as the measurement distance, according to the propagation speed of the laser in the air using a preset formula; Construct a three-dimensional model of the actual component by combining the triangulation principle with the emission angle and the relative position relationship of the measurement points.

7. The appearance visualization detection device for large parts according to claim 1, characterized in that, The execution steps of the data fusion and processing module are specifically as follows: Data alignment: Adopt a feature point-based matching algorithm to process the laser measurement data and visual inspection data. Extract feature points from the visual image in the visual inspection data and the laser measurement data, and use the descriptors of the feature points for matching to determine their corresponding relationship and achieve spatial alignment of the data; Construct a standard three-dimensional model and defect judgment: Preset the standard three-dimensional model of the component according to the design drawing or standard specifications of the component; the standard three-dimensional model defines the dimensions, shapes, and factory range information of each part of the component; Compare and analyze the standard three-dimensional model with the three-dimensional model of the actual component, and determine whether there are protruding or concave areas by calculating the deviation of each point between the standard three-dimensional model and the three-dimensional model of the actual component; Identify the area and depth of the protrusion or depression in the protruding or concave area. When the area or depth of the protruding or concave area exceeds the preset tolerance range, mark this area as a potential defect area; Perform weighted calculation on the area and depth of the protrusion or depression in the protruding or concave area to obtain the defect score; Divide the component into several regions according to the structural characteristics and functional importance of the component for the three-dimensional model of the actual component, and set the regional importance weight for each region; Identify the defect score and the total number of defect areas of the potential defect areas in each region; Perform weighted calculation on all potential defect areas and the total number of defect areas in the region to obtain the regional defect value; Then perform weighted processing on the regional defect values of all divided regions on the component and their corresponding regional importance weights to obtain the comprehensive defect score of the component; If the comprehensive defect value is greater than its preset defect threshold, it means the component is unqualified; otherwise, it means the component is qualified; Finally, generate an inspection report: Mark the basic information of the component, the qualification rate within the preset production cycle, the change trend of the qualification rate, the detailed information of all potential defect areas, the defect conditions of each region, and the overall comprehensive defect score, etc. as the inspection report; the inspection report is presented in a combination of visual charts and text descriptions.

8. An appearance visualization detection device for large parts according to claim 1, characterized in that, The data fusion and processing module also includes a marking and display module; The marking and display module is used to match the defect score of each defect on the component with the preset defect marking value range group when the component is unqualified to obtain the corresponding defect marking; Visually mark and display the defect marking on the preset three-dimensional model of the component.

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