Automatic structured light three-dimensional scanning detection method and system

Abstract

The invention relates to the technical field of structured light three-dimensional detection equipment, and discloses an automatic structured light three-dimensional scanning detection method, which comprises the following steps: carrying out three-dimensional scanning on a standard part for teaching, and constructing a parameter packet of the standard part; collecting three-dimensional point cloud data of the surface of the standard part, and constructing a three-dimensional model; the three-dimensional model and the parameter package are combined to construct a formula of the corresponding part type, and a formula database is formed; scanning a two-dimensional code or a bar code of a to-be-detected part to obtain information of the to-be-detected part, and matching a detection formula in the formula database; and calling the detection formula to carry out three-dimensional scanning detection on the to-be-detected part so as to determine a detection result of the to-be-detected part, and binding the detection result with the scanned two-dimensional code or bar code. According to the invention, simple change of real-time parameters in the scanning operation process is realized, the working speed of automatic operation is effectively improved, the time cost of using equipment is reduced, the use threshold of operators is reduced, and the simplicity and convenience of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of structured light three-dimensional detection devices, and particularly to an automated structured light three-dimensional scanning detection method and system. Background Art

[0002] In the field of modern industrial production, the dimensional accuracy and surface quality of components are key indicators for measuring product performance and reliability. As an efficient and non-contact detection tool, a three-dimensional contour optical scanner can accurately obtain the three-dimensional contour data of components, thereby realizing the detection of their dimensions and surface defects, and has been widely used in the manufacturing industry. To improve the detection efficiency and automation level, a technical solution that uses a robotic arm and an electromechanical control system to replace manual operation of the three-dimensional contour optical scanner for detection has emerged.

[0003] However, in the existing same control systems, there are some problems that need to be solved urgently. On the one hand, there are certain thresholds and requirements for operators. Operators need to be familiar with the principle, parameter settings, and operation methods of the three-dimensional contour optical scanner, and at the same time, they also need to master the collaborative control logic of the robotic arm and the electromechanical control system, including the motion planning of the robotic arm, the adjustment of positioning accuracy, and the calibration and debugging of the system. This not only requires operators to have a relatively high professional and technical level but also requires special training to operate proficiently, resulting in insufficient simplicity and convenience of the system, which limits its application in some scenarios with relatively low technical requirements for operators.

[0004] On the other hand, during the scanning operation process, the existing system cannot easily change real-time parameters. For example, when detecting components of different materials, shapes, or sizes, it is often necessary to adjust the scanning speed, exposure time, resolution, and other parameters of the scanner, as well as the control parameters such as the motion speed and trajectory of the robotic arm according to the actual situation. However, due to the unfriendly human-machine interface of the existing system and the complex parameter adjustment process, it is difficult for operators to quickly complete parameter changes without interrupting the operation or performing complex operations, thus affecting the continuity and flexibility of the detection process.

[0005] In addition, the existence of these problems makes it impossible to effectively improve the working rate of automated operations. Operators need to spend a lot of time and energy in the operation process to adapt to the operation requirements of the system, adjust parameters, and deal with problems such as low detection efficiency caused by inconvenient parameter adjustment, resulting in serious constraints on the automation level and efficiency of the entire detection process, and the advantages of the robotic arm and the electromechanical control system in improving production efficiency cannot be fully utilized. Summary of the Invention

[0006] The present invention provides an automated structured light three-dimensional scanning and detection method and system, which realizes the simple modification of real-time parameters during the scanning operation process, effectively improves the working rate of the automated operation, reduces the time cost of using equipment, lowers the usage threshold of operators, and enhances the simplicity and convenience of the system.

[0007] The present invention provides an automated structured light three-dimensional scanning and detection method, including:

[0008] Performing three-dimensional scanning on a standard component for teaching, and constructing a parameter package of the standard component; wherein, the parameter package includes name, drawing number, serial number, shutter, resolution, and the movement path of the scanning robot, and the rotation angle of the turntable therein;

[0009] Collecting three-dimensional point cloud data on the surface of the standard component, and constructing a three-dimensional model of the standard component according to the three-dimensional point cloud data;

[0010] Combining the three-dimensional model and the parameter package of the standard component to construct a recipe corresponding to the component type of the standard component;

[0011] Integrating the recipes corresponding to the component types of multiple standard components to form a recipe database;

[0012] Scanning the QR code or bar code of the component to be detected to obtain the information of the component to be detected, and matching the detection recipe of the component to be detected in the recipe database according to the information of the component to be detected;

[0013] Invoking the detection recipe to perform three-dimensional scanning and detection on the component to be detected to determine the detection result of the component to be detected, and binding the detection result to the scanned QR code or bar code; wherein, the detection result includes dimension data and defect data.

[0014] Further, the step of performing three-dimensional scanning on a standard component for teaching and constructing a parameter package of the standard component includes:

[0015] A six-axis collaborative robot equipped with a three-dimensional structured light scanner scans the standard component to achieve path teaching;

[0016] After scanning one surface of the standard component, manually input the angle of the absolute position of the turntable of the six-axis collaborative robot in the operating system and run;

[0017] The turntable of the six-axis collaborative robot rotates the fixture and the standard part to the second scanning surface, and performs path teaching of the six-axis robot again;

[0018] After teaching all the surfaces of the standard component, save all the paths of the six-axis robot, including the scanning paths of each surface of the six-axis robot and the rotation angles of the turntable, and assign a number to them;

[0019] Manually fill in the name, drawing number, number, shutter, and resolution information of the detected component on the operating system to construct the parameter package of the standard component.

[0020] Further, the step of collecting the three-dimensional point cloud data of the surface of the standard component and constructing the three-dimensional model of the standard component according to the three-dimensional point cloud data includes:

[0021] Use binocular cameras to scan the surface of the standard part respectively to obtain the point cloud data on each surface, and calculate the relative distance between each point and the lens according to the ToF method;

[0022] Use a preset coordinate transformation formula to transform the polar coordinates in the spatial data into global Cartesian coordinates, and perform matrix calculation to transform the point cloud data on each surface into a unified coordinate system;

[0023] Fuse the quaternion array measured by the binocular camera and the relative distance measured by the ToF method to obtain the accurate spatial data of each point;

[0024] Use a point cloud stitching algorithm to stitch the point cloud data on different surfaces of the standard part to form a complete three-dimensional model.

[0025] Further, the step of calculating the relative distance between each point and the lens according to the ToF method includes:

[0026] The laser emitter of the three-dimensional scanner emits a laser pulse to the surface of the standard component, and the laser pulse is reflected back after hitting the surface of the standard component and is received by the receiver;

[0027] Measure the time t from the emission to the return of the laser pulse, and calculate the relative distance between each point and the lens of the three-dimensional scanner. The calculation formula is:

[0028]

[0029] Among them, c represents the speed of light, set to 3×10 8 m / s; t represents the time from the emission to the return of the laser pulse; D represents the relative distance between each point and the lens.

[0030] Further, in the step of using a preset coordinate transformation formula to transform the polar coordinates in the spatial data into global Cartesian coordinates,

[0031] Single-point coordinate transformation formula:

[0032]

[0033] Among them, θ represents the horizontal angle, and φ represents the pitch angle;

[0034] Multi-sensor fusion:

[0035] P global = R quat ·P local + t

[0036] Among them, R quat represents the rotation matrix generated by the quaternion, and t represents the translation vector.

[0037] Furthermore, in the step of converting the polar coordinates in the spatial data into global Cartesian coordinates by using a preset coordinate conversion formula and performing matrix calculation to convert the point cloud data on each surface into a unified coordinate system, the matrix calculation includes:

[0038] Determine the coordinate system relationship: Determine the relationship between the coordinate system of the calibration plate and the coordinate system of the standard component. Assume that the coordinate system of the calibration plate is {C}, and the coordinate system of the standard component is {P};

[0039] Collect data: Use a binocular camera to image the calibration plate to obtain the homogeneous coordinates of the positioning punctuation marks on the calibration plate, and record the coordinates of these positioning punctuation marks in the coordinate system of the standard component at the same time;

[0040] Establish a homogeneous coordinate matrix: Form a matrix H C with the homogeneous coordinates of the positioning punctuation marks on the calibration plate, and form a matrix H P with the coordinates of the corresponding positioning punctuation marks in the coordinate system of the standard component;

[0041] Calculate the transformation matrix: Calculate the transformation matrix T from {C} to {P} by the least squares method or other optimization methods.

[0042] Furthermore, the transformation matrix T is expressed as:

[0043]

[0044] Among them, is the inverse matrix of the matrix H C , and the transformation matrix T represents the transformation relationship from the calibration plate coordinate system {C} to the standard component coordinate system {P}; the homogeneous coordinate matrix H C contains the homogeneous coordinates of the positioning punctuation marks on the calibration plate; the homogeneous coordinate matrix H P contains the coordinates of the corresponding positioning punctuation marks in the coordinate system of the standard component; the inverse matrix is used to convert the coordinates in the calibration plate coordinate system to the standard component coordinate system.

[0045] The present invention also provides an automated structured light three-dimensional scanning and detection system for implementing the automated structured light three-dimensional scanning and detection method as described above. The system includes a data acquisition module, an automated control module, an image processing and optimization module, a data compatibility output module, a quality control report generation module, a safety protection module, a user interaction module, an intelligent fixture and turntable system module, and a system integration and coordination module;

[0046] The data acquisition module is connected to the image processing and optimization module, the image processing and optimization module is connected to the data compatibility output module, the data compatibility output module is connected to the automated control module, the automated control module is connected to the user interaction module, the quality control report generation module, and the intelligent fixture and turntable system module. The intelligent fixture and turntable system module is also connected to the safety protection module and the system integration and coordination module;

[0047] The data acquisition module is used to quickly obtain three-dimensional point cloud data of the part surface through a high-precision three-dimensional scanner;

[0048] The automated control module is used to perform path teaching with a six-axis collaborative robot to realize the automated scanning and detection process;

[0049] The image processing and optimization module is used to process and optimize the three-dimensional point cloud data of the part surface;

[0050] The data compatibility output module is used to ensure that the output format is compatible with mainstream industrial software;

[0051] The quality control and report generation module is used to compare the digital model and generate a detailed detection report to quickly identify product deviations;

[0052] The safety and protection module is used to perform real-time protection with ultrasonic sensors, and a dual-power system ensures the stable operation of the equipment;

[0053] The user interaction module is used to provide a graphical interface and touch screen operation to realize path teaching and recipe management;

[0054] The intelligent fixture and turntable system module adopts a modular design, automatically adjusts the workpiece position according to a preset program, and synchronizes with the robot scanning path;

[0055] The system integration and coordination module is used to realize the coordinated work of each module through an integrated control system.

[0056] The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0057] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0058] The beneficial effects of the present invention are as follows:

[0059] The present invention performs three-dimensional scanning on standard components for teaching, constructs a parameter package of the standard components; collects three-dimensional point cloud data on the surface of the standard components and constructs a three-dimensional model; generates a formula and a formula database corresponding to the component type of the standard components; scans the two-dimensional code or bar code of the component to be detected to obtain information about the component to be detected, and matches the detection formula in the formula database; calls the detection formula to perform three-dimensional scanning detection on the component to be detected to determine the detection result of the component to be detected, and binds it to the scanned two-dimensional code or bar code. It reduces the usage threshold and usage cost of automation equipment, that is, reduces the technical requirements for equipment operators and the employment cost and time cost of enterprise employee training. By simply changing real-time parameters, it is more suitable for the usage scenario and improves the working rate of automated operations, reducing the time cost of using equipment. Description of the Drawings

[0060] Figure 1 It is a schematic flowchart of the method according to an embodiment of the present invention.

[0061] Figure 2 It is a schematic flowchart of the formula adding process in the present invention.

[0062] Figure 3 It is a schematic diagram of the detection operation execution in the present invention.

[0063] Figure 4 It is a schematic flowchart of the actual operation process in the present invention.

[0064] Figure 5 It is a schematic diagram of the device structure according to an embodiment of the present invention.

[0065] Figure 6 It is a schematic diagram of the internal structure of a computer device according to an embodiment of the present invention.

[0066] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0068] As Figures 1-3 shown, the present invention provides an automated structured light three-dimensional scanning detection method, including:

[0069] S1. Perform three-dimensional scanning on standard components for teaching, and construct a parameter package for the standard components; wherein, the parameter package includes name, drawing number, serial number, shutter speed, resolution, and the movement path of the scanning robot, as well as the rotation angle of the turntable therein.

[0070] Select the fixture for the part to be measured and install it on the assembly. The 6-axis collaborative robot is equipped with a three-dimensional structured light scanner for path teaching. After completing the scanning of one surface, manually input the absolute position angle of the turntable in the operating system and click to run. Subsequently, the turntable drives the fixture and the part to be measured to rotate to the second scanning file, and the path teaching of the robot is carried out again. After completing the teaching of all surfaces, all the paths of the robot can be saved, including the scanning paths of each surface of the robot and the rotation angle of the turntable, and a serial number is assigned. Fill in information such as the name, drawing number, serial number, shutter speed, resolution, etc. of the detected component on the operating system. The serial number in the control system corresponds to the serial number of the path of the robot for this scanned workpiece. Finally, the parameter package of the standard component is formed.

[0071] S2. Collect the three-dimensional point cloud data on the surface of the standard component, and construct a three-dimensional model of the standard component based on the three-dimensional point cloud data.

[0072] Three-dimensional scanning obtains the geometric information on the surface of an object through non-contact measurement technology, discretely samples the model into digital point cloud data, and finally reconstructs it into a continuous three-dimensional model. It includes data acquisition → coordinate alignment → point cloud processing → surface reconstruction. The specific steps are as follows:

[0073] S201. Use binocular cameras to scan the surface of the standard part respectively, obtain the point cloud data on each surface, and calculate the relative distance between each point and the lens according to the ToF method.

[0074] 1) The laser emitter of the three-dimensional scanner emits a laser pulse to the surface of the standard component. After the laser pulse hits the surface of the standard component, it is reflected back and received by the receiver.

[0075] 2) Measure the time t from the emission to the return of the laser pulse, and calculate the relative distance between each point and the lens of the three-dimensional scanner. ToF (Time of Flight method) calculates the distance by measuring the time from the emission to the return of the laser. Assume the time from the emission to the return of the laser is t, and the speed of light is c. Then the distance D can be calculated by the following formula:

[0076]

[0077] Among them, c represents the speed of light, set at 3×10 8 m / s; t represents the time from the emission to the return of the laser pulse; D represents the relative distance between each point and the lens.

[0078] S202. Convert the polar coordinates in the spatial data into global Cartesian coordinates using a preset coordinate conversion formula, and perform matrix calculation to convert the point cloud data on each surface into a unified coordinate system;

[0079] Coordinate conversion: Polar coordinates → Global Cartesian coordinates, single-point coordinate conversion formula:

[0080]

[0081] where θ represents the horizontal angle and φ represents the pitch angle;

[0082] Multi-sensor fusion:

[0083] P global = R quat · P local + t

[0084] where R quat represents the rotation matrix generated by quaternions, and t represents the translation vector.

[0085] The specific steps of matrix calculation are as follows:

[0086] 1) Determine the coordinate system relationship: Determine the relationship between the coordinate system of the calibration plate and the coordinate system of the standard component. Assume that the coordinate system of the calibration plate is {C} and the coordinate system of the standard component is {P};

[0087] 2) Collect data: Use a binocular camera to image the calibration plate, obtain the homogeneous coordinates of the positioning punctuation marks on the calibration plate, and record the coordinates of these positioning punctuation marks in the coordinate system of the standard component at the same time;

[0088] 3) Establish a homogeneous coordinate matrix: Form a matrix H C with the homogeneous coordinates of the positioning punctuation marks on the calibration plate, and form a matrix H P with the coordinates of the corresponding positioning punctuation marks in the coordinate system of the standard component;

[0089] 4) Calculate the transformation matrix: Calculate the transformation matrix T from {C} to {P} through the least squares method or other optimization methods. The transformation matrix T is expressed as:

[0090]

[0091] where is the inverse matrix of the matrix H C , and the transformation matrix T represents the transformation relationship from the calibration plate coordinate system {C} to the standard component coordinate system {P}; the homogeneous coordinate matrix H C contains the homogeneous coordinates of the positioning punctuation marks on the calibration plate; the homogeneous coordinate matrix H PInclude the coordinates of the corresponding positioning punctuation marks in the standard component coordinate system; inverse matrix For converting the coordinates in the calibration plate coordinate system to the standard component coordinate system.

[0092] S203. Fuse the quaternion array measured by the binocular camera and the relative distance measured by the ToF method to obtain the accurate spatial data of each point;

[0093] S204. Adopt a point cloud stitching algorithm to stitch the point cloud data on different surfaces of the standard part to form a complete three-dimensional model.

[0094] Specific example:

[0095] Suppose there is a tooling fixture, and it is necessary to scan and stitch its three surfaces.

[0096] 1) Data acquisition: Use the binocular camera to scan the three surfaces respectively to obtain the point cloud data on each surface. At the same time, use the ToF method to measure the relative distance between each point and the lens.

[0097] 2) Coordinate transformation: Through matrix calculation, convert the point cloud data on each surface to a unified coordinate system. Suppose the homogeneous coordinate matrix of the positioning punctuation marks on the calibration plate is H C , and the coordinate matrix of the corresponding positioning punctuation marks in the actual component coordinate system is H P , then the transformation matrix T is:

[0098]

[0099] 3) Spatial information fusion: Fuse the quaternion array measured by the binocular camera and the distance data measured by the ToF method. For example, for a point [X, Y, Z, 1], the distance measured by the ToF method is D, then the accurate spatial information of this point is:

[0100] [X', Y', Z'] = [X, Y, Z] + [0, 0, D - Z]

[0101] 4) Stitching algorithm: By identifying and matching the artificial marker points (Markers) in different scanning segments, calculate the rigid body transformation parameters (rotation matrix R and translation vector T) between coordinate systems to achieve the accurate alignment of multi-viewpoint clouds.

[0102] S3. Combine the three-dimensional model and parameter package of the standard component to construct the recipe corresponding to the component type of the standard component;

[0103] The present invention writes and optimizes the underlying script code of the human-machine interface HMI, uses the recipe function to edit and save parameters such as the name, drawing number, number, shutter, resolution, required tooling fixtures, etc. of the parts to be detected, and saves the parameters after detecting the corresponding parts by using the equipment in the early stage.

[0104] The recipe function can save and create a corresponding parameter package for the workpiece through one-time teaching, which includes the name, drawing number, number, shutter, resolution of the detected parts, as well as the movement path of the robot and the rotation angle of the turntable therein. When performing the next scanning operation, the parameter package can be directly called for scanning without secondary adjustment.

[0105] Recipe production process: The tooling fixture adapted to the part to be measured is installed on the fixture bracket; the part to be measured is installed on the fixture; start scanning, manually teach the path of the multi-axis collaborative robot on the first surface, and after completing the scanning of the first surface, manually input the angle of the absolute position of the turntable in the operating system; click to run, then the turntable drives the tooling fixture and the part to be measured to rotate to the second scanning position, that is, the second surface, and perform the path teaching of the multi-axis collaborative robot again; repeat the above path teaching steps; after completing the path teaching of multiple surfaces, save all the paths of the multi-axis collaborative robot, and the above information includes the scanning path of each surface of the multi-axis collaborative robot and the rotation angle of the turntable and assigns a unique number.

[0106] S4. Integrate the recipes corresponding to the component types of multiple standard components to form a recipe database;

[0107] S5. Scan the QR code or bar code of the part to be detected to obtain the information of the part to be detected, and match the detection recipe of the part to be detected in the recipe database according to the information of the part to be detected;

[0108] S6. Call the detection recipe to perform three-dimensional scanning detection on the part to be detected to determine the detection result of the part to be detected, and bind the detection result to the scanned QR code or bar code; wherein, the detection result includes dimension data and defect data.

[0109] Before performing the automated scanning operation by calling the recipe, automatically check the tooling fixture. If it does not meet the corresponding parameter package, remind to replace the corresponding tooling fixture. After replacing the tooling fixture, directly click start to implement the automated scanning operation; generate the tooling fixture sub-parameter packages corresponding to different tooling fixtures through path teaching; the component parameter package includes the corresponding tooling fixture sub-parameter packages.

[0110] The component parameter package contains the basic parameters of the part to be detected, the movement path of the robot and the corresponding rotation angle of the turntable. The basic parameters of the part include name, drawing number, number, shutter, resolution.

[0111] The numbers of the component parameter packages corresponding to different components to be measured are set differently. The basic parameters of the components to be detected are filled in the operating system. The basic parameters of the components include numbers, and the numbers of the corresponding component parameter packages on the operating system are the same as those on the robot control system.

[0112] As Figure 4 shown, during the detection process, the scanning parameters (such as shutter, resolution, etc.) can be changed in real time, and the automatic scanning detection process is started. Manual operation: Select the fixture and install it, the control system selects and calls the recipe, and selects the robot running program; Scanner: Recharge the task, import the fiducial points, import the cutting plane, set the scanning mode, and start the scanner; Robot / rotary table: The robot executes the scanning path, completes the single-sided scanning, waits for the rotary table to rotate to the other side, continues to execute the scanning path, and completes the scanning of all surfaces of the part; If there are missing features in the first scan, start the second scan, the robot ends the script, and the operator uses manual teaching to complete the missing features. After confirming that the features are completed, the scanning is completed. Finally, the robot returns to the origin, the scanning data is exported, and the data is saved to the detection software; Perform CX detection: Open the detection file template prepared with elevated privileges, import the saved data for batch processing, and output the detection report results to the user-specified folder. The control system completes the scanning task of the part, and the program returns to the initial position, waiting for the next task.

[0113] The fully automated structured light three-dimensional scanning and detection device for implementing the above method includes a multi-axis collaborative robot, a three-dimensional structured light scanner, an ultrasonic ranging device, a detection workbench, a turntable, a tooling fixture, a fixture bracket, and a human-machine interface; The multi-axis collaborative robot and the turntable are installed on the detection workbench; The three-dimensional structured light scanner and the ultrasonic ranging device are carried on the multi-axis collaborative robot; The turntable is provided with a fixture bracket, the fixture bracket is provided with a tooling fixture, and the component to be measured is installed on the tooling fixture. Positioning marks are provided on the above turntable, tooling fixture, and fixture bracket, and positioning marks are provided on the above component to be measured.

[0114] Through the design of the control system and the writing of the code, the present invention realizes prompting the operator to use hand-tightened quick-change screws to replace the corresponding tooling fixtures, one-key calling the scanning parameter settings, and one-key starting the automated scanning operation. For the operating system recipe switching process, when there is a saved recipe for the measured path, find the recipe in the recipe table on the operating system automation interface and click to call it. A prompt will pop up asking you to replace it with the fixture corresponding to the measured workpiece. After the recipe is successfully called, it will be automatically matched to the scanning path of the robot.

[0115] By scanning the QR code or barcode of the part, key information such as product model and batch number can be quickly obtained, and the detection formula (such as path, parameters) can be automatically matched. After scanning the code, the preset detection program (such as the robot scanning path, turntable rotation angle) is automatically started, reducing the manual operation link. Bind the scanned code to the detection results (such as dimension data, defect report) to achieve full-process quality traceability.

[0116] When using this type of equipment, the operator needs to judge the selection of tooling fixtures and the setting of scanning parameters based on personal experience, which has a direct impact on the final scanning result of the parts, and the differences in personal experience among different operators will also have a direct impact on and differences in the final scanning result. On this basis, the present invention saves the operator's optimal selection of tooling fixtures and scanning parameter settings to minimize the impact on the final scanning result and ensure that the operations of each person will not cause deviation in the final scanning result.

[0117] When using this type of equipment, the operator needs to select tooling fixtures and set scanning parameters, etc. During the scanning process, it is necessary to judge the generated point cloud model and change the real-time parameters during the process to obtain a more accurate scanning result. The present invention realizes the real-time change of scanning parameters during the process through the design and code implementation of the control system, and after a single scan is completed, a simple operation interface and a secondary scanning function are provided for the operator, enabling the operator to have more choices for the scanning result and more refined point cloud data supplementation, optimizing the accuracy of the final scanning detection result.

[0118] The present invention coordinates through an electromechanical control system composed of multiple controllers and a human-machine interface. The operator only needs to click the "Save Recipe" and "Call Parameters" buttons in the human-machine interface to set all parameters and directly start the automated operation process. The present invention first uses a composite interaction method of local work + human-machine interface + barcode scanner. Different from the existing equipment in the industry, the part of the detection parameters of the parts and the control part of the equipment electromechanical system are handed over to the human-machine interface for control operation, and the computing power redundancy of the local workstation is given to the geometric quantity detection function and the parts scanning imaging function to ensure the smooth operation of the equipment, and ensure that inexperienced operators can directly start the specific operation of the equipment through simple training. Through the supporting information collection of the barcode scanner and the integrated control software, a complete life cycle record of the parts from production to detection to final delivery is realized, meeting the requirements of ISO9001 (international quality standard).

[0119] Such as Figure 5As shown in the figure, the present invention also provides an automated structured light three-dimensional scanning and detection system for implementing the automated structured light three-dimensional scanning and detection method described above. The system includes a data acquisition module, an automated control module, an image processing and optimization module, a data compatibility output module, a quality control report generation module, a safety protection module, a user interaction module, an intelligent fixture and turntable system module, and a system integration and coordination module;

[0120] The data acquisition module is connected to the image processing and optimization module, the image processing and optimization module is connected to the data compatibility output module, the data compatibility output module is connected to the automated control module, the automated control module is connected to the user interaction module, the quality control report generation module, and the intelligent fixture and turntable system module. The intelligent fixture and turntable system module is also connected to the safety protection module and the system integration and coordination module;

[0121] 1. Data acquisition module

[0122] Quickly obtain the three-dimensional point cloud data of the part surface through a high-precision three-dimensional scanner. Using laser non-contact scanning technology, a high-precision sensor and multiple laser lines are used for scanning. Process: Start the scanner, perform omnidirectional data acquisition on the workpiece to ensure that the detection coverage is without dead ends.

[0123] 2. Automated control module

[0124] Implement the automated scanning and detection process to reduce manual intervention. Use a six-axis collaborative robot for path teaching and perform multi-device collaborative operations through an automated control system. Process: Configure the robot path and scanner parameters through a graphical interface to achieve one-key start detection.

[0125] 3. Image processing and optimization module

[0126] Process and optimize the scanned data to improve the efficiency and accuracy of data processing. Enhance the mesh optimization function, local resolution function, and real-time generation of triangular networks. Process: After scanning is completed, automatically process the data, including mesh optimization and detail retention.

[0127] 4. Data compatibility output module

[0128] Ensure that the output format is compatible with mainstream industrial software, facilitating secondary data analysis and process optimization. The output format is compatible with software such as CAD and MES. Process: Export the scanned data, supporting multiple formats for subsequent analysis and use.

[0129] 5. Quality control and report generation module

[0130] Generate a detailed inspection report to quickly identify product deviations. Compare the digital model and generate a report, supporting the export of multi-format data. Process: After the inspection is completed, the data is automatically exported to generate a 3D comparison chart and an inspection report.

[0131] 6. Safety and protection module

[0132] Ensure the safety of the equipment and operations. Use ultrasonic sensors for real-time protection, and a dual-power system to ensure the stable operation of the equipment. Process: Monitor the equipment status in real time and manual intervention can be carried out in case of emergencies.

[0133] 7. User interaction module

[0134] Provide an intuitive and efficient operation interface to lower the learning threshold. Graphical interface, touch-screen operation, supporting path teaching and recipe management. Process: The user operates through the interface, such as path teaching, recipe switching, etc.

[0135] 8. Intelligent fixture and turntable system module

[0136] Support quick changeover and adapt to small-batch, multi-variety production scenarios. Modular design, and automated rotation reduces manual adjustment time. Process: Automatically adjust the workpiece position according to the preset program, synchronized with the robot scanning path.

[0137] 9. System integration and coordination module

[0138] Unify the control of modules such as robots, scanners, and turntables, and simplify the multi-device coordination process. Multi-module collaborative management to ensure seamless task connection. Process: Through the integrated control system, realize the collaborative work of each module.

[0139] As Figure 6 shown, the present invention also provides a computer device, which can be a server, and its internal structure can be as Figure 6 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store all the data required for the process of the automated structured light three-dimensional scanning detection method. The network interface of the computer device is used to communicate with external terminals through the network. When the computer program is executed by the processor, it realizes the automated structured light three-dimensional scanning detection method.

[0140] Those skilled in the art can understand, Figure 6The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied.

[0141] An embodiment of this application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements any one of the above-mentioned automated structured light three-dimensional scanning detection methods.

[0142] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned method embodiments. Among them, any reference to a memory, storage, database, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0143] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, device, article, or method including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, device, article, or method. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, device, article, or method including that element.

[0144] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. An automated structured light three-dimensional scanning and detection method, characterized in that, Including: Performing three-dimensional scanning on standard components for teaching, and constructing a parameter package of the standard components; wherein, the parameter package includes name, drawing number, serial number, shutter, resolution, and the movement path of the scanning robot, and the rotation angle of the turntable therein; Collecting three-dimensional point cloud data on the surface of the standard components, and constructing a three-dimensional model of the standard components according to the three-dimensional point cloud data; Combining the three-dimensional model and the parameter package of the standard components to construct a recipe corresponding to the component type of the standard components; Integrating recipes corresponding to component types of multiple standard components to form a recipe database; Scanning the QR code or barcode of the component to be detected to obtain information of the component to be detected, and matching the detection recipe of the component to be detected in the recipe database according to the information of the component to be detected; Invoking the detection recipe to perform three-dimensional scanning detection on the component to be detected to determine the detection result of the component to be detected, and binding the detection result to the scanned QR code or barcode; wherein, the detection result includes dimension data and defect data.

2. The automated structured light three-dimensional scanning detection method according to claim 1, wherein The step of performing three-dimensional scanning on standard components for teaching and constructing a parameter package of the standard components includes: A six-axis collaborative robot is equipped with a three-dimensional structured light scanner to scan the standard components to achieve path teaching; After scanning one surface of the standard components, manually input the angle of the absolute position of the turntable of the six-axis collaborative robot in the operating system and run; The turntable of the six-axis collaborative robot drives the fixture and the standard part to rotate to the second scanning surface, and performs path teaching of the six-axis robot again; After completing the teaching of all surfaces of the standard components, save all paths of the six-axis robot, including the scanning path of each surface of the six-axis robot and the rotation angle of the turntable, and assign a serial number; Manually fill in the name, drawing number, serial number, shutter, and resolution information of the component to be detected on the operating system to construct a parameter package of the standard components.

3. The automated structured light three-dimensional scanning detection method according to claim 1, wherein The step of collecting three-dimensional point cloud data on the surface of the standard components and constructing a three-dimensional model of the standard components according to the three-dimensional point cloud data includes: Using binocular cameras to scan the surface of the standard part respectively to obtain point cloud data on each surface, and calculating the relative distance between each point and the lens according to the ToF method; Using a preset coordinate transformation formula to convert the polar coordinates in the spatial data into global Cartesian coordinates, and performing matrix calculation to convert the point cloud data on each surface into a unified coordinate system; Fusing the quaternion array measured by the binocular camera and the relative distance measured by the ToF method to obtain accurate spatial data of each point; Using a point cloud stitching algorithm to stitch the point cloud data on different surfaces of the standard part to form a complete three-dimensional model.

4. The automated structured light three-dimensional scanning and detection method according to claim 3, wherein The step of calculating the relative distance between each point and the lens according to the ToF method includes: The laser emitter of the three-dimensional scanner emits a laser pulse to the surface of the standard component, and the laser pulse is reflected back after hitting the surface of the standard component and is received by the receiver; Measure the time t from the emission to the return of the laser pulse, and calculate the relative distance between each point and the lens of the 3D scanner. The calculation formula is as follows: Among them, c represents the speed of light, which is set to 3×10 8 m / s; t represents the time from the emission to the return of the laser pulse; D represents the relative distance between each point and the lens.

5. The automated structured light three-dimensional scanning detection method according to claim 3, characterized in that In the step of converting the polar coordinates in the spatial data into global Cartesian coordinates by using a preset coordinate conversion formula, Single-point coordinate conversion formula: where θ represents the horizontal angle and φ represents the pitch angle; Multi-sensor fusion: P global = R quat ·P local + t Among them, R quat represents the rotation matrix generated by quaternions, and t represents the translation vector.

6. The automated structured light three-dimensional scanning and detection method according to claim 3, characterized in that In the step of converting the polar coordinates in the spatial data into global Cartesian coordinates by using a preset coordinate conversion formula, performing matrix calculation, and converting the point cloud data on each surface into a unified coordinate system, the matrix calculation includes: Determine the coordinate system relationship: Determine the relationship between the coordinate system of the calibration plate and the coordinate system of the standard component. Assume that the coordinate system of the calibration plate is {C} and the coordinate system of the standard component is {P}; Collect data: Use a binocular camera to image the calibration plate, obtain the homogeneous coordinates of the positioning punctuation marks on the calibration plate, and record the coordinates of these positioning punctuation marks in the coordinate system of the standard component at the same time; Establish a homogeneous coordinate matrix: form a matrix H with the homogeneous coordinates of the positioning punctuation marks on the calibration plate C , and form a matrix H with the coordinates of the corresponding positioning punctuation marks in the standard component coordinate system P ; Calculate the transformation matrix: Calculate the transformation matrix T from {C} to {P} by the least squares method or other optimization methods.

7. The automated structured light three-dimensional scanning detection method according to claim 6, wherein, The transformation matrix T is expressed as: Among them, is the inverse matrix of matrix H C The transformation matrix T represents the transformation relationship from the calibration plate coordinate system {C} to the standard component coordinate system {P}; the homogeneous coordinate matrix H C contains the homogeneous coordinates of the positioning punctuation marks on the calibration plate; the homogeneous coordinate matrix H P contains the coordinates of the corresponding positioning punctuation marks in the standard component coordinate system; the inverse matrix is used to convert the coordinates in the calibration plate coordinate system to the standard component coordinate system.

8. An automated structured light three-dimensional scanning and detection system, characterized in that, For implementing the automated structured light 3D scanning and detection method described in any one of claims 1 to 7, the system includes a data acquisition module, an automated control module, an image processing and optimization module, a data compatibility output module, a quality control report generation module, a safety protection module, a user interaction module, an intelligent fixture and turntable system module, and a system integration and coordination module; The data acquisition module is connected to the image processing and optimization module, the image processing and optimization module is connected to the data compatibility output module, the data compatibility output module is connected to the automated control module, the automated control module is connected to the user interaction module, the quality control report generation module, and the intelligent fixture and turntable system module. The intelligent fixture and turntable system module is also connected to the safety protection module and the system integration and coordination module; The data acquisition module is used to quickly obtain the 3D point cloud data of the part surface through a high-precision 3D scanner; The automated control module is used to perform path teaching by using a six-axis collaborative robot to realize the automated scanning and detection process; The image processing and optimization module is used to process and optimize the 3D point cloud data of the part surface; The data compatibility output module is used to ensure that the output format is compatible with mainstream industrial software; The quality control and report generation module is used to compare the digital model and generate a detailed detection report to quickly identify product deviations; The safety and protection module is used to perform real-time protection by using an ultrasonic sensor, and the dual-power system ensures the stable operation of the equipment; The user interaction module is used to provide a graphical interface and touch screen operation to realize path teaching and recipe management; The intelligent fixture and turntable system module adopts a modular design, automatically adjusts the workpiece position according to a preset program, and is synchronized with the robot scanning path; The system integration and coordination module is used to realize the collaborative work of each module through an integrated control system.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it realizes the steps of the method described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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