Digital area array 3D projection global automatic deviation detection visualization method

Abstract

The invention discloses a digital area array 3D projection global automatic deviation detection visualization method. The method comprises the steps that a mechanical arm and digital area array 3D projection positioning model is established; establishing a relative position relationship between a target station of the mechanical arm and the digital area array 3D projection positioning model and a detected object, and constructing a global measurement field; path planning is conducted on the mechanical arm according to the to-be-detected range of the detected object and the global measurement field, and a measurement target path is obtained; and acquiring a measurement model of the detected object based on the measurement target path, and performing comparative analysis on the measurement model and a theoretical model to realize 3D projection global automatic deviation visual detection. Compared with a previous detection method, the method is more autonomous, more accurate and more comprehensive, 3D projection global visualization and automatic deviation detection can be realized, the detection efficiency is improved, and the personnel detection time is shortened.

Description

Technical Field

[0001] The present invention belongs to the field of 3D projection visualization, and relates to qualitative and quantitative evaluation of pits, gaps, and step differences, and in particular to a global automatic deviation detection visualization method for digital array 3D projection. Background Art

[0002] Aircraft, car bodies, precision mechanical parts, glass, sheet metal and other measuring surfaces may have discontinuous features, such as pits or cracks, and detecting these pits or cracks requires a resolution of microns to millimeters. Digital array 3D projection is used to scan and inspect the surface of the object to be inspected, and the pits and gap steps on the surface of the object are accurately located to improve the accuracy of the measurement.

[0003] At present, 3D laser projection technology is widely used in the field of inspection as a high-precision, high-positioning quality manufacturing technology. Because the surface pits and assembly deviations of the inspected object are difficult to measure with high precision, before the application of 3D laser projection positioning technology, traditional assembly positioning technology mostly uses manual measuring tools such as vernier calipers, micrometers, dial indicators, etc. to locate and assemble the inspected object, that is, the deviation position is judged by the eyes and experience of designers and inspectors, and the accuracy often does not meet the standard. In addition, the measurement is time-consuming, and due to the limitations of the operator's proficiency, the deviation data read has large errors. Later, the method of detecting the gap was to use a handheld gap gun, but the gap gun cannot be globally positioned and it is too troublesome to manually perform large-area inspections. The inspection is prone to deviations, resulting in frequent operations and low efficiency.

[0004] Therefore, a global automatic deviation detection visualization method for digital array 3D projection is urgently needed to address the shortcomings of the existing technology. Summary of the invention

[0005] The purpose of the present invention is to propose a digital array 3D projection global automatic deviation detection visualization method to solve the problem of automatic detection and visualization of object surface information.

[0006] To achieve the above object, the present invention provides a digital array 3D projection global automatic deviation detection visualization method, comprising the following steps:

[0007] Establish a 3D projection positioning model of the robotic arm and digital array;

[0008] Establishing the relative position relationship between the target station of the manipulator and the digital array 3D projection positioning model and the detected object, and constructing a global measurement field;

[0009] Performing path planning for the robot arm according to the detection range of the detected object and the global measurement field to obtain a measurement target path;

[0010] Based on the measurement target path, a measurement model of the detected object is obtained, and compared and analyzed with the theoretical model to achieve global automatic deviation visualization detection of 3D projection.

[0011] Optionally, establish a 3D projection positioning model of the robotic arm and the digital array, including:

[0012] Calibrate the calibration plate in the world coordinate system, obtain the relative position between the digital array 3D projection and the calibration plate, and then solve the optical center of the digital array 3D projection;

[0013] A base coordinate system of the robotic arm is established, and the base coordinate system of the robotic arm is used as the working coordinate system. The end coordinate system of the robotic arm is solved through the base coordinate system, and the relative position relationship between the end coordinate system of the robotic arm and the optical center of the digital area array 3D projection is solved, and then a positioning model of the robotic arm and the digital area array 3D projection is established.

[0014] Optionally, establish the base coordinate system of the robot arm, including:

[0015] Calculate the relative posture relationship between the laser tracker and the calibration plate of the 3D projection of the calibration digital array, place the robot arm at zero position, control the angles of each joint, and measure the coordinate value of the flange fixing point at the end of the robot arm through the laser tracker target ball at every preset angle;

[0016] Keeping the target axis angle unchanged, rotate the first axis, measure the first coordinate value of the flange fixing point at the end of the robot arm, and then obtain the fitting circle;

[0017] Determine the center of the circle according to the fitted circle, and draw a straight line through the center of the circle and perpendicular to the plane where the fitted circle is located as the Z axis of the base coordinate system;

[0018] The robot arm is placed at zero position again, the target axis angle is kept unchanged, the second axis is rotated, and the second coordinate value of the flange fixing point at the end of the robot arm is measured, thereby obtaining the fitting plane;

[0019] Fitting the robotic arm base and measuring the plane where the robotic arm base is located;

[0020] According to the Z axis of the base coordinate system and the plane where the robot arm base is located, a normal line of the fitting plane is obtained, and the normal line is used as the Y axis of the base coordinate system;

[0021] The X axis of the base coordinate system is determined according to the coordinate system rule.

[0022] Optionally, the relative position relationship between the end coordinate system of the robotic arm and the optical center of the digital array 3D projection is:

[0023]

[0024] Among them, T o is the transformation matrix from the digital array 3D projection coordinate system to the robot end coordinate system, E is the 3×3 unit matrix, P0=[X o Y o Z o ] T is a 3×1 position matrix.

[0025] Optionally, establishing a relative position relationship between the target position of the robot arm and the digital array 3D projection positioning model and the detected object, and constructing a global measurement field includes:

[0026] According to the relative position relationship between the calibration plate and the laser tracker, a laser tracker target ball is placed at each reference point on the surface of the detected object to calibrate parameters of the to-be-detected range on the surface of the detected object;

[0027] Based on the detection range of the detected object, the robotic arm is placed at the optimal measurement position of the digital array 3D projection, and the robotic arm drives the digital array 3D projection to scan the detection range, and the number of positions required for the robotic arm is calculated according to the detection range, and then the target position of the robotic arm is obtained according to the optimal measurement position of the digital array 3D projection;

[0028] The target position of the robotic arm is calibrated row by row to obtain the relative position relationship between the target position of the robotic arm and the digital array 3D projection positioning model and the detected object, thereby constructing the global measurement field.

[0029] Optionally, performing path planning on the robot arm according to the scanning range of the detected object and the global measurement field to obtain a measurement target path includes:

[0030] Acquiring the relative position relationship according to the global measurement field;

[0031] Based on the relative position relationship, the robot arm is path-planned for a single station to realize automatic detection of pits, grooves, and curved surfaces, and the robot arm is moved to an initial zero position;

[0032] Based on the inspection range of the object to be inspected, the surface of the object to be inspected is scanned and inspected by driving the digital area array 3D projection through the rotation of the robot arm joints, and a global planning is performed on several of the stations with the robot arm stiffness and the optimal measurement distance of the digital area array 3D projection as the target to obtain the target path.

[0033] Optionally, path planning is performed on the robot arm at a single station to achieve automatic detection of pits, grooves, and curved surfaces, including:

[0034] When the detected object has the pit, the digital area array 3D projection is driven by the robotic arm to perform surround detection above the pit, so as to obtain the shape and depth of the pit and realize automatic detection of the pit;

[0035] When the detected object has the groove, the outer contour of the groove is scanned, then the scanning is transitioned from the outer contour to the inner side of the groove, and then the scanning returns to the starting point of the outer contour scanning to complete the automatic detection of the groove;

[0036] When the object to be detected has the curved surface, the target curve of the curved surface is extracted, and coordinate points are selected on the target curve to fit the function curve, and then the digital area array 3D projection is driven by the robotic arm to perform scanning and detection according to the function curve.

[0037] Optionally, based on the measurement target path, a measurement model of the detected object is obtained, and compared and analyzed with a theoretical model to realize 3D projection global automatic deviation detection visualization, including:

[0038] Based on the measurement target path, the robotic arm drives the digital area array 3D projection to move, and the digital area array 3D projection scans to obtain point cloud data on the surface of the detected object;

[0039] splicing the point cloud data in sequence to obtain a measurement model of the detected object;

[0040] If the theoretical model is known, the coordinate system of the theoretical model and the measurement model are aligned, and the point cloud data is processed and spliced, and then compared and analyzed with the theoretical model to obtain deviation pair data, obtain the detection result of the detected object, and use color index to realize 3D projection global automatic deviation detection visualization, wherein the point cloud data includes ordered point cloud and unordered point cloud;

[0041] If the theoretical model is unknown, the image obtained by the digital area array 3D projection scanning is subjected to noise reduction and enhancement, and the images scanned by a single station and the images scanned by several stations are spliced ​​in sequence to obtain the surface features of the detected object, and then an automated deviation detection 3D projection model is established to realize the visualization of global automatic deviation detection of 3D projection.

[0042] Optionally, processing and splicing the point cloud data includes:

[0043] Using a direct observation method, the noise points of the ordered point cloud are deleted to obtain a denoised ordered point cloud;

[0044] A double filtering method is used to perform noise reduction and smoothing on the disordered point cloud to obtain a noise-reduced disordered point cloud;

[0045] The ordered point cloud after noise reduction and the disordered point cloud after noise reduction are simplified, and the point cloud data obtained by scanning the digital area array 3D projection driven by the robot arm according to the measurement target path are sequentially spliced.

[0046] The present invention has the following beneficial effects:

[0047] Compared with the prior art, the present invention realizes the fusion of the robotic arm and the digital array 3D projection when detecting the surface integrity of an object, optimizes the steps of autonomous measurement required by personnel for detecting objects, and establishes an integrated dynamic projection model of global scanning of the object to be measured by digital array 3D projection and autonomous movement of the robotic arm; based on the coordinate transformation matrix and the relative posture solution algorithm, compared with previous detection methods, it is more autonomous, more accurate, and more comprehensive, and can realize global visualization of 3D projection, automatic deviation detection, improve detection efficiency, and reduce personnel detection time; for object surface detection, the present invention integrates the robotic arm and the digital array 3D projection system to realize global visualization of all-round digital array 3D projection, providing a reference for the construction of a digital twin dynamic evolution model. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0049] Figure 1 It is a schematic diagram of the process of the digital array 3D projection global automatic deviation detection visualization method according to an embodiment of the present invention;

[0050] Figure 2 Schematic diagram of the 3D projection calibration model of the robotic arm and digital array proposed in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0052] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0053] In view of the shortcomings of existing technologies, large-scale detection and deviation display can timely check and correct dimensional deviations, reduce quality defects, and improve product detection rate. To detect the actual situation of the surface of the object to be tested, the digital array 3D projection is combined with the robotic arm. The digital array 3D projection is driven by the movement of the robotic arm to scan and detect the object to be tested, so as to realize automatic scanning of the object to be tested, reduce detection errors, shorten detection time, and improve detection efficiency. In addition, the actual situation of the surface of the object to be tested can be monitored in real time, and the global automatic deviation detection visualization of 3D projection can be realized.

[0054] In view of the problem that digital array 3D projection cannot complete global positioning, automatic layout, and global visualization display, a detection method combining a manipulator with digital array 3D projection is proposed. First, a positioning model of the manipulator and the digital array 3D projection is established. After the positioning model is established, a laser tracker is used to determine the relative position relationship between the manipulator, the digital array 3D projection positioning model and the object to be detected, and the construction of the global measurement field is completed. The path of the manipulator is planned according to the range of the object to be detected that has been determined when the measurement field is constructed. Since the measurement model coordinate system has been obtained when the measurement field is constructed, it is aligned with the theoretical model coordinate system. As the manipulator drives the digital array 3D projection to move according to the planned measurement target path, the point cloud scanned by the digital array 3D projection is sequentially spliced ​​to form a complete measurement model of the area to be detected. The 3D deviation comparison analysis is performed with the theoretical model, and the deviation data between the two can be directly displayed. The mapping relationship between the color display of the deviation detection data and the color index is determined, and the deviation ratio of the surface of the object to be detected can be intuitively observed from the deviation comparison chart, thereby realizing global automatic deviation detection visualization.

[0055] like Figure 1 As shown, the digital array 3D projection global automatic deviation detection visualization method of the present invention comprises the following steps:

[0056] Establish a 3D projection positioning model of the robotic arm and digital array;

[0057] Establish the relative position relationship between the target position of the robot arm and the digital array 3D projection positioning model and the object to be detected, and construct a global measurement field;

[0058] The robot arm is path-planned according to the detection range of the object to be detected and the global measurement field to obtain the measurement target path;

[0059] Based on the measurement target path, the measurement model of the object to be inspected is obtained and compared with the theoretical model to achieve global automatic deviation visualization detection of 3D projection.

[0060] Furthermore, a 3D projection positioning model of the robotic arm and the digital array is established, including:

[0061] Calibrate the calibration plate in the world coordinate system, obtain the relative position between the digital array 3D projection and the calibration plate, and then solve the optical center of the digital array 3D projection;

[0062] The base coordinate system of the robot arm is established, and the base coordinate system of the robot arm is used as the working coordinate system. The end coordinate system of the robot arm is solved based on the working coordinate system, and then the relative posture relationship between the end coordinate system of the robot arm and the optical center of the digital area array 3D projection is solved, so as to establish the positioning model of the robot arm and the digital area array 3D projection.

[0063] Specifically, the 3D projection detection system plays a vital role in the global measurement field. A complete detection system can synchronize the surface state of the object being measured in real time and more intuitively display the 3D information of the surface of the object being measured. The digital array 3D projection is fixed at the end of the robotic arm. There is a calibration plate under the world coordinate system {W}. The calibration plate can be used to simultaneously solve the relative posture relationship between it and the digital array 3D projection and the laser tracker. The calibration plate is calibrated using the optical projection positioning principle of the digital array 3D projection, and the relative posture between the digital array 3D projection and the calibration plate can be obtained, and then the optical center of the digital array 3D projection, that is, the coordinate origin of the digital array 3D projection coordinate system {P}, can be solved. For the positioning of the robotic arm, a laser tracker is used to calibrate the parameters of its base coordinate system. After the base coordinate system is established, the base coordinate system of the robot is used as the working coordinate system. The end coordinate system of the robot is solved based on the working coordinate system, and then the relative position relationship between the end coordinate system of the robot and the optical center of the digital array 3D projection is solved to establish the positioning model of the robot and the digital array 3D projection, such as Figure 2 shown.

[0064] Furthermore, the base coordinate system of the robot arm is established, including:

[0065] Obtain the relative position relationship between the laser tracker and the calibration plate of the 3D projection of the calibration digital array, and place the robot arm at zero position to control the angle of each joint;

[0066] Keeping the target axis angle unchanged, rotate the first axis, measure the first coordinate value of the flange fixing point at the end of the robot arm, and then obtain the fitting circle;

[0067] Determine the center of the circle according to the fitted circle, and take the straight line passing through the center of the circle and perpendicular to the plane where the fitted circle is located as the Z axis of the base coordinate system;

[0068] Reposition the robot arm to zero position, keep the target axis angle unchanged, rotate the second axis, measure the second coordinate value of the flange fixing point at the end of the robot arm, and then obtain the fitting plane;

[0069] Fit the robot arm base and measure the plane where the robot arm base is located;

[0070] According to the Z axis of the base coordinate system and the plane where the robot base is located, the normal of the fitting plane is obtained, the normal is used as the Y axis of the base coordinate system, and the X axis of the base coordinate system is determined according to the coordinate system rule.

[0071] Specifically, for the positioning of the robot arm, a laser tracker is used to calibrate the parameters of its base coordinate system. Place the robot arm at zero position, with the angles of each joint being 0°, -90°, 0°, -90°, 0°, and 0° respectively; keep the angles of other axes unchanged, rotate axis 1, and measure the coordinate values ​​of a fixed point at the end flange of the robot arm through the laser tracker target ball at certain angles, and fit a circle C1 based on these points; determine the center of the circle based on the fitted circle, and make a straight line l1 that passes through the center of the circle and is perpendicular to the plane where the circle C1 is located as the Z axis of the base coordinate system; place the robot arm at zero position again, keep the angles of other axes unchanged, rotate axis 2, and measure the coordinate values ​​of the fixed point at the end flange of the robot arm through the laser tracker target ball at certain angles, and fit a plane M based on these points; place the laser tracker target ball on the base of the robot arm, fit the base of the robot arm on the computer software, and measure the plane B where the base is located; take the intersection of the Z axis of the base coordinate system and the plane where the base is located as the origin of the base coordinate system, make the normal of plane M through the coordinate origin as the Y axis, and finally determine the X axis according to the coordinate system law. Among them, {B} is the base coordinate of the robot arm, located on the plane of the robot arm installation base, and is the reference datum of the torsion angle coordinate system of other links of the robot arm, used to describe the position and posture of the robot arm joint in the base coordinate system. {M} is the coordinate system of the end of the robot arm, and its relative position and posture with the optical center of the digital array 3D projection fixed at the end of the robot arm is theoretically unchanged.

[0072] Furthermore, the relative position relationship between the end coordinate system of the robot arm and the optical center of the digital array 3D is:

[0073]

[0074] Among them, T o is the transformation matrix from the digital array 3D projection coordinate system to the robot end coordinate system, E is the 3×3 unit matrix, P0=[X o Y o Z o ] T is a 3×1 position matrix.

[0075] It can be seen that the change in the position of the digital array 3D projection coordinate system caused by the movement of the robotic arm can be solved in real time, so the robotic arm and the digital array 3D projection can be regarded as a relatively moving overall model, thereby establishing a positioning model between the robotic arm and the digital array 3D projection.

[0076] Furthermore, the relative position relationship between the target position of the robot arm and the digital array 3D projection positioning model and the detected object is established to construct a global measurement field, including:

[0077] Determine the relative position relationship between the calibration plate and the laser tracker for calibrating the digital array 3D projection, and place the laser tracker target ball at each reference point on the surface of the object to be detected to calibrate the parameters of the projection range on the surface of the object to be detected;

[0078] Based on the detection range of the object to be detected, a robotic arm is placed at the optimal measurement position of the digital array 3D projection. The robotic arm drives the digital array 3D projection to scan the detection range. The number of target positions required for the robotic arm is calculated according to the detection range, and then the target position of the robotic arm is planned according to the optimal measurement position of the digital array 3D projection.

[0079] The target position of the robot arm is calibrated row by row to obtain the relative position relationship between the target position of the robot arm and the digital array 3D projection positioning model and the detected object, and then the global measurement field is constructed.

[0080] Specifically, in order to realize the real-time detection of gaps and pits on the surface of the object to be detected, it is necessary to build a high-precision measurement field of the global coordinate system. Since the positioning model of the robotic arm and the digital array 3D projection has been established, it is also necessary to establish the relative relationship between the positioning model and the object to be detected. Solve the relative posture relationship between the calibration plate of the digital array 3D projection and the laser tracker, place the laser tracker target ball at each reference point on the surface of the object to be detected, calibrate the parameters of the projection area on the surface of the object to be detected, and then the laser tracker receives the laser reflected by the target ball to obtain the coordinate system {Q} of the object to be detected. Place the robotic arm with the digital array 3D projection installed at the best measurement position of the digital array 3D projection. The placement position must ensure that the robotic arm can drive the digital array 3D projection to scan all the surface information of the object to be detected at this station. The scanning task of this station can be ended only after the scanning is completed. Since the measurement area of ​​a single position of the robot arm is limited, and the robot arm driving the digital array 3D projection cannot complete the measurement of the entire detection range of the object to be detected at one position, it is necessary to divide the detection range into areas according to the stiffness of the robot arm, and the robot arm drives the digital array 3D projection to scan and detect the divided areas one by one. The target position planning of the robot arm is completed according to the optimal measurement position of the digital array 3D projection, and then all the robot arm positions required for the object to be detected are calibrated one by one through the laser tracker. In this way, the relative position relationship between the target position of the robot arm and the digital array 3D projection positioning model and the object to be detected is determined. The digital array 3D projection scans the object to be detected in full coverage, realizing real-time detection of the global coordinate system.

[0081] Furthermore, the path of the robot arm is regulated according to the scanning range of the detected object and the global measurement field to obtain the measurement target path, including:

[0082] According to the global measurement field, the relative position relationship is obtained;

[0083] Based on the relative position relationship, the robot arm performs path planning for a single station, realizes automatic detection of pits, grooves, and curved surfaces, and moves the robot arm to the initial zero position;

[0084] Based on the inspection range of the object to be inspected, the digital area array 3D projection is driven by the rotation of the robot arm joint to scan and inspect the surface of the object to be inspected, and a global planning is carried out on several positions based on the stiffness of the robot arm and the optimal measurement distance of the digital area array 3D projection to obtain the measurement target path.

[0085] Specifically, after the global measurement field is constructed, that is, after the global coordinate system is unified with high precision, the relative position relationship between the digital array 3D projection and the object to be detected can be solved in real time. In order to realize the automatic detection of the gap pits on the surface of the object to be detected by the digital array 3D projection, the trajectory of the robot arm is first planned for a single station; since the surface of the object to be detected is not all planes, and is limited by the measurement range and accuracy of the digital array 3D projection itself, it is necessary to plan the scanning path of the robot arm single station to realize the automatic detection of pits, grooves, and curved surfaces. At this time, the robot arm can be moved to the initial zero position, and the surface of the object to be detected can be scanned and detected by rotating the joints, and the scanning task of this station can be completed. Subsequently, multiple stations are globally planned: the robot arm station planning first meets the accessibility requirements of scanning all the features of the surface of the object to be detected, and the robot arm station planning is carried out with the robot arm stiffness and the optimal measurement distance of the digital array 3D projection as the target. Due to the large size of the object to be detected, and it may be limited by the complex environment of the measurement field itself, one station cannot cover the entire object to be measured. The surface of the object to be measured is divided into several areas using the range of the object to be measured scanned by the laser tracker, and the scanning is performed in blocks until the scanning of the entire object to be measured is completed. After the robot arm planning of the entire object to be measured is completed, the robot arm with the fixed digital area array 3D projection is placed in the first station, and the movement of the robot arm drives the digital area array 3D projection to complete the measurement task of the entire measurement field according to the plan.

[0086] Furthermore, the robot arm is path-planned for a single station to achieve automatic detection of pits, grooves, and curved surfaces, including:

[0087] When there is a pit on the object to be inspected, the robot arm drives the digital array 3D projection to perform surround inspection above the pit to obtain the shape and depth of the pit, thus realizing automatic detection of the pit.

[0088] When there is a groove on the object to be detected, the outer contour of the groove is scanned, and then the inner side of the groove is scanned from the outer contour, and then the scanning returns to the starting point of the outer contour scanning to complete the automatic detection of the groove.

[0089] When the object to be inspected has a curved surface, the target curve of the surface is extracted, and coordinate points are selected on the target curve to fit the function curve. The digital area array 3D projection is then driven by a robotic arm to perform scanning and inspection according to the function curve.

[0090] Specifically, for the situation that there may be pits on the measured surface, the cone surround measurement method is adopted, that is, when the pit is detected, the digital surface array 3D projection is driven by the robot arm to perform surround detection along the shape of the pit above the pit. At this time, the field of view will form a cone, and the specific shape and depth of the pit can be detected; for the situation that there may be grooves on the surface of the measured object, the method of scanning the intersection of two planes is adopted, that is, the outer contour is scanned first, and then the outer contour is transitioned to the inner side of the groove and finally returned to the starting point of the outer contour scan to complete the detection task of the groove; for the situation that there may be curved surface features on the surface of the measured object, the measurement method based on the normal direction of the curved surface is adopted, that is, a curve is extracted from the curved surface, and an appropriate number of coordinate points are selected on the curve to fit an approximate function curve by interpolation method, and the digital surface array 3D projection can be driven by the robot arm to perform scanning and detection according to the fitted curve.

[0091] Furthermore, based on the measurement target path, the measurement model of the object to be inspected is obtained and compared with the theoretical model to realize the visualization of 3D projection global automatic deviation detection, including:

[0092] Based on the measurement target path, the robot arm drives the digital array 3D projection to move, and the digital array 3D projection scans to obtain point cloud data on the surface of the object being tested;

[0093] The point cloud data are stitched together in sequence to obtain the measurement model of the detected object;

[0094] If the theoretical model is known, the coordinate systems of the theoretical model and the measurement model are aligned, and the point cloud data is processed and spliced, and then compared and analyzed with the theoretical model to obtain deviation comparison data, obtain the deviation detection result of the detected object, and use color index to realize 3D projection global automatic deviation detection visualization, where the point cloud data includes ordered point cloud and unordered point cloud;

[0095] If the theoretical model is unknown, the images obtained by digital array 3D projection scanning are subjected to noise reduction and enhancement and other processing, and the images scanned by a single station and the images scanned by several stations are stitched in turn to obtain the surface features of the object to be detected, and then an automated deviation detection 3D projection model is established to realize the visualization of global automatic deviation detection of 3D projection.

[0096] Furthermore, the point cloud data is processed and spliced, including:

[0097] The direct observation method is used to delete the noise points of the ordered point cloud to obtain the denoised ordered point cloud;

[0098] The double filtering method is used to reduce noise and smooth the disordered point cloud to obtain the disordered point cloud after noise reduction;

[0099] The ordered point cloud after denoising and the disordered point cloud after denoising are simplified, and the point cloud data obtained by scanning the digital array 3D projection along the measurement target path by the robotic arm are spliced ​​in sequence.

[0100] Specifically, when the entire measurement field is established, the laser tracker has measured the coordinate system of the area to be detected of the object to be detected. If the geometric theoretical model of the object to be detected is also known after three-dimensional modeling, the known theoretical model is aligned with the measurement model of the area to be detected of the object to be detected obtained by scanning and splicing the digital array 3D projection, so as to perform the following deviation detection. The point cloud obtained by the digital array 3D projection scanning is processed and spliced: first, the point cloud data obtained by the digital array 3D projection scanning is denoised. For the ordered point cloud: first, the direct observation method is used to import the scanned original point cloud data directly into the processing software. The noise points that can be directly distinguished by the human eye, such as some isolated points, can be manually deleted on the relevant software. For the disordered point cloud: the double filtering method is used to denoise the disordered point cloud, and the point cloud data is smoothed to indirectly eliminate or reduce the influence of noise on the accuracy of point cloud splicing. Then, the denoised point cloud data is streamlined under the premise of ensuring the surface detail features of the object to be measured, reducing the data redundancy in the point cloud data, and speeding up the point cloud splicing and three-dimensional imaging. After noise reduction and simplification, the point cloud scanned by the robot arm according to the planned path can be spliced ​​in sequence. Because the robot arm measurement target path planning has been completed, and the coordinate systems of the theoretical model and the measurement model have also been aligned, as the robot arm drives the digital array 3D projection to move, the complete measurement model of the object to be detected can be gradually obtained. The measurement model and the theoretical model are compared and analyzed for 3D deviations, and the deviation comparison data between the measurement model and the theoretical model are obtained, so as to know the detection results of pits and gaps on the surface of the object to be detected. In order to solve the problem of visual display of the detection results, the color index method is adopted. The color index is established using the RGB triple color model commonly used in computer systems. The mapping relationship between the color display of the deviation detection data and the color index is determined, and the deviation data can be directly displayed in the deviation comparison chart. For pits, the deviation data such as length, width and height are displayed, and for gap step differences, the gap and step difference deviation data are directly displayed. In addition, the deviation data information and deviation position information on the surface of the object to be detected can be intuitively observed by the color ratio distribution in the deviation comparison chart, realizing global automatic deviation detection visualization.

[0101] If there is no theoretical model, the images scanned by the digital array 3D projection are subjected to noise reduction and enhancement, and then the images scanned by a single station are spliced, and then the images scanned by each station are processed and spliced ​​in turn. Then, the curvature, morphology and other characteristics of the detected object can be obtained, thereby establishing an automated deviation detection 3D projection model and realizing the visualization of 3D projection automatic deviation detection.

[0102] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A digital array 3D projection global automatic deviation detection visualization method, characterized in that: The specific steps include: Establish a 3D projection positioning model of the robotic arm and digital array; Establishing the relative position relationship between the target station of the manipulator and the digital array 3D projection positioning model and the detected object, and constructing a global measurement field; Performing path planning for the robot arm according to the detection range of the detected object and the global measurement field to obtain a measurement target path; Based on the measurement target path, a measurement model of the detected object is obtained, and compared and analyzed with the theoretical model to achieve global automatic deviation visualization detection of 3D projection.

2. The digital array 3D projection global automatic deviation detection visualization method according to claim 1, characterized in that: Establish a 3D projection positioning model of the robotic arm and digital array, including: Calibrate the calibration plate in the world coordinate system, obtain the relative position between the digital array 3D projection and the calibration plate, and then solve the optical center of the digital array 3D projection; A base coordinate system of the robotic arm is established, and the base coordinate system of the robotic arm is used as the working coordinate system. The end coordinate system of the robotic arm is solved through the base coordinate system, and the relative position relationship between the end coordinate system of the robotic arm and the optical center of the digital area array 3D projection is solved, and then a positioning model of the robotic arm and the digital area array 3D projection is established.

3. The digital array 3D projection global automatic deviation detection visualization method according to claim 2, characterized in that: Establish the base coordinate system of the robot arm, including: Calculate the relative posture relationship between the laser tracker and the calibration plate of the 3D projection of the calibration digital array, place the robot arm at zero position, control the angles of each joint, and measure the coordinate value of the flange fixing point at the end of the robot arm through the laser tracker target ball at every preset angle; Keeping the target axis angle unchanged, rotate the first axis, measure the first coordinate value of the flange fixing point at the end of the robot arm, and then obtain the fitting circle; Determine the center of the circle according to the fitted circle, and draw a straight line through the center of the circle and perpendicular to the plane where the fitted circle is located as the Z axis of the base coordinate system; The robot arm is placed at zero position again, the target axis angle is kept unchanged, the second axis is rotated, and the second coordinate value of the flange fixing point at the end of the robot arm is measured, thereby obtaining the fitting plane; Fitting the robotic arm base and measuring the plane where the robotic arm base is located; According to the Z axis of the base coordinate system and the plane where the robot arm base is located, a normal line of the fitting plane is obtained, and the normal line is used as the Y axis of the base coordinate system; The X axis of the base coordinate system is determined according to the coordinate system rule.

4. The digital array 3D projection global automatic deviation detection visualization method according to claim 2, characterized in that: The relative position relationship between the end coordinate system of the robotic arm and the optical center of the digital array 3D projection is: Among them, T o is the transformation matrix from the digital array 3D projection coordinate system to the robot end coordinate system, E is the 3×3 unit matrix, P0=[X o Y o Z o ] T is a 3×1 position matrix.

5. The digital array 3D projection global automatic deviation detection visualization method according to claim 1, characterized in that: Establishing the relative position relationship between the target position of the manipulator and the digital array 3D projection positioning model and the detected object, and constructing the global measurement field includes: According to the relative position relationship between the calibration plate and the laser tracker, a laser tracker target ball is placed at each reference point on the surface of the detected object to calibrate parameters of the to-be-detected range on the surface of the detected object; Based on the detection range of the detected object, the robotic arm is placed at the optimal measurement position of the digital array 3D projection, and the robotic arm drives the digital array 3D projection to scan the detection range, and the number of positions required for the robotic arm is calculated according to the detection range, and then the target position of the robotic arm is obtained according to the optimal measurement position of the digital array 3D projection; The target position of the robotic arm is calibrated row by row to obtain the relative position relationship between the target position of the robotic arm and the digital array 3D projection positioning model and the detected object, thereby constructing the global measurement field.

6. The digital array 3D projection global automatic deviation detection visualization method according to claim 5, characterized in that: The path of the robot arm is planned according to the scanning range of the detected object and the global measurement field to obtain the measurement target path, including: Acquiring the relative position relationship according to the global measurement field; Based on the relative position relationship, the robot arm is path-planned for a single station to realize automatic detection of pits, grooves, and curved surfaces, and the robot arm is moved to an initial zero position; Based on the inspection range of the object to be inspected, the surface of the object to be inspected is scanned and inspected by driving the digital area array 3D projection through the rotation of the robot arm joints, and a global planning is performed on several of the stations with the robot arm stiffness and the optimal measurement distance of the digital area array 3D projection as the target to obtain the target path.

7. The digital array 3D projection global automatic deviation detection visualization method according to claim 6, characterized in that: The robot arm is subjected to path planning for a single station to realize automatic detection of pits, grooves and curved surfaces, including: When the detected object has the pit, the digital area array 3D projection is driven by the robotic arm to perform surround detection above the pit, so as to obtain the shape and depth of the pit and realize automatic detection of the pit; When the detected object has the groove, the outer contour of the groove is scanned, then the scanning is transitioned from the outer contour to the inner side of the groove, and then the scanning returns to the starting point of the outer contour scanning to complete the automatic detection of the groove; When the object to be detected has the curved surface, the target curve of the curved surface is extracted, and coordinate points are selected on the target curve to fit the function curve, and then the digital area array 3D projection is driven by the robotic arm to perform scanning and detection according to the function curve.

8. The digital array 3D projection global automatic deviation detection visualization method according to claim 1, characterized in that: Based on the measurement target path, a measurement model of the object to be detected is obtained, and compared and analyzed with the theoretical model to realize 3D projection global automatic deviation detection visualization, including: Based on the measurement target path, the robotic arm drives the digital area array 3D projection to move, and the digital area array 3D projection scans to obtain point cloud data on the surface of the detected object; splicing the point cloud data in sequence to obtain a measurement model of the detected object; If the theoretical model is known, the coordinate system of the theoretical model and the measurement model are aligned, and the point cloud data is processed and spliced, and then compared and analyzed with the theoretical model to obtain deviation pair data, obtain the detection result of the detected object, and use color index to realize 3D projection global automatic deviation detection visualization, wherein the point cloud data includes ordered point cloud and unordered point cloud; If the theoretical model is unknown, the image obtained by the digital area array 3D projection scanning is subjected to noise reduction and enhancement, and the images scanned by a single station and the images scanned by several stations are spliced ​​in sequence to obtain the surface features of the detected object, and then an automated deviation detection 3D projection model is established to realize the visualization of global automatic deviation detection of 3D projection.

9. The digital array 3D projection global automatic deviation detection visualization method according to claim 8, characterized in that: Processing and splicing the point cloud data includes: Using a direct observation method, the noise points of the ordered point cloud are deleted to obtain a denoised ordered point cloud; A double filtering method is used to perform noise reduction and smoothing on the disordered point cloud to obtain a noise-reduced disordered point cloud; The ordered point cloud after noise reduction and the disordered point cloud after noise reduction are simplified, and the point cloud data obtained by scanning the digital area array 3D projection driven by the robot arm according to the measurement target path are sequentially spliced.

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