Adaptive Calibration Method for Installation Deviation of Multi-Point Angle Deviation Detection Equipment for Aircraft Transparent Parts

Abstract

This invention provides an adaptive calibration method for installation deviation of a multi-point angular deviation detection device for aerospace transparent parts, belonging to the field of automated inspection technology. The method first acquires an array of light spot images and preprocesses them to obtain binary images corresponding to four light spots. Then, adaptive spot center positioning is performed on the binary images corresponding to the four light spots. After calculating the centers of the four light spots, calibration is performed with the corresponding four crosshair standard positions generated by the CCD array to obtain an adaptive dynamic adjustment amount. The adjustment angle is calculated based on the adjustment amount, and this adjustment angle is removed from each angular deviation detection result of the transparent part, ultimately obtaining an accurate measurement result. This method can formulate a specific adjustment scheme for the array-type angular deviation detection device for aerospace transparent parts and solve the adjustment angle in real time for device calibration.

Description

Technical Field

[0001] This invention relates to the field of automated inspection technology, and in particular to an adaptive calibration method for installation deviation of a multi-point angular deviation detection device for aerospace transparent parts. Background Technology

[0002] Transparent components in aviation are crucial for pilots to observe the external environment and determine distances. Factors affecting the optical performance of transparent components include optical angular deviation, optical distortion, transmittance, refractive index, parallax, and sharpness. Among these, the measurement of optical angular deviation is of great significance for the optical quality inspection of aviation transparent components. Therefore, an array-type angular deviation detection device for aviation transparent components (i.e., a multi-point angular deviation detection device for aviation transparent components) was developed. The main principle of this device is that four 2×2 laser beams generated by an array laser emitter are deflected after passing through the component under test and then captured by an array laser receiver, ultimately forming four high-brightness spots on its CCD array. By locating the offset of the spots before and after testing the component under test, and combining this with the corresponding installation distance, the angular deviation values ​​at the four points can be directly calculated.

[0003] To obtain accurate angular deviation values, the installation deviation of the aerospace transparent component array angular deviation detection equipment needs to be calibrated before measurement. The traditional calibration method uses a level measuring instrument to ensure that the laser emitting and receiving devices are level, but this method has low calibration accuracy, low adjustment efficiency, and difficulty in ensuring the stability of calibration results. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing an adaptive calibration method for the installation deviation of a multi-point angular deviation detection device for aviation transparent parts, thereby achieving adaptive calibration of the installation deviation of the array-type angular deviation detection device for aviation transparent parts.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an adaptive calibration method for installation deviation of a multi-point angular deviation detection device for aerospace transparent parts, comprising the following steps:

[0006] Step 1: Acquire the array spot image and preprocess it to obtain the binarized images corresponding to the four spots;

[0007] Before conducting inspection of transparent aerospace components, an image containing four bright spots is captured on the CCD array of the array laser receiver, denoted as I;

[0008] The images of the four light spot regions are uniformly divided to form four independent rectangular light spot regions of the same size, denoted as I1, I2, I3 and I4;

[0009] Mean filtering was applied to each of the four rectangular regions to remove noise that affected the localization of the light spot;

[0010] Adaptive threshold segmentation is performed on the four rectangular regions after mean filtering to obtain the corresponding binarized images;

[0011] The specific steps for adaptive threshold segmentation of the four rectangular regions after mean filtering are as follows:

[0012] The average pixel value of the spot image after mean filtering is used as the initial threshold for image segmentation;

[0013] The laser image is divided into two parts, the target area and the background, based on the initial threshold, and the range of the image area occupied by the target is calculated at the same time.

[0014] Calculate the average value of all pixels within the image region occupied by the target;

[0015] Based on the relationship between image brightness and camera exposure brightness, the average value of all pixels within the image area occupied by the target is multiplied by the scaling factor K as the threshold for final image binarization, resulting in a binarized image.

[0016] Step 2: Perform adaptive spot center localization on the binarized images corresponding to the four spots;

[0017] Step 2.1: Detect the edges of the light spots in the binarized I1, I2, I3 and I4 images;

[0018] The Sobel operator is used to calculate the gradient of the image, yielding the horizontal gradient G. x and vertical gradient G y ;

[0019] Calculate the gradient magnitude M and direction Θ of the image;

[0020] For each pixel in the image, only local maxima along the gradient direction are retained; that is, if M(x,y) is the maximum value in the neighborhood, it is retained, otherwise it is set to 0. Then, a high threshold T is set. H and low threshold T L Pixels are categorized into strong edges, weak edges, and non-edges;

[0021] Finally, it is determined whether weak edges are connected to strong edges, and only weak edges connected to strong edges are retained to obtain the final extracted image edge pixels;

[0022] Step 2.2: Perform elliptical least-squares fitting on the edge pixels of the light spots obtained from the four images I1, I2, i3, and i4 respectively to calculate the corresponding approximate elliptical regions. Intersect this region with the original denoised image without binarization to obtain an elliptical gray-level region. Then, for this gray-level region, use the weighted gray-level centroid method to locate the final light spot center. The mathematical form is as follows:

[0023]

[0024] Where (x0,y0) represents the center coordinates of the light spot, I′(x,y) represents the pixel grayscale value of the image, M is the number of horizontal pixels in the image, N is the number of vertical pixels in the image, and M*N represents the pixel size of the elliptical grayscale region.

[0025] Step 3: Establish an adaptive linear correlation calibration optimization strategy to perform adaptive calibration of installation deviation; after calculating the four spot centers, calibrate them with the corresponding four crosshair standard positions generated by the CCD array to obtain the adaptive dynamic adjustment amount; calculate the adjustment angle based on the adjustment amount, remove the adjustment angle from each transparent part corner deviation detection result, and finally obtain accurate measurement results;

[0026] The four rectangular regions I1, I2, I3 and I4 that were segmented are restored to the original complete rectangular pixel regions with four-point array light spots;

[0027] A coordinate system is established with the top left corner of the original image containing four light spots captured by the camera as the origin, the horizontal direction as the X-axis, and the vertical direction as the Y-axis. The center coordinates of the light spots in these four rectangular areas are unified into this coordinate system, denoted as (X... i ,Y i ), where i = 1, 2, 3, 4; at the same time, the standard positions of the four crosshairs are also unified into this coordinate system, denoted as (X ti ,Y ti Therefore, the four spot offsets are expressed in the following mathematical form:

[0028]

[0029] For the four light spots, the offsets are organized into the following matrix:

[0030]

[0031] A linear correlation model is established between the spot offset and the adjustment range of the array-type angular deviation detection equipment for aerospace transparent parts, which is expressed by the following linear equation:

[0032] P = A·W + B

[0033] Where P is the offset matrix of the light spot; A is the adjustment matrix, representing the influence of different adjustment directions on the position of the light spot; W is the adjustment vector, representing the amount to be adjusted; and B is a constant term, representing the initial offset of the system.

[0034] Using the least squares method to solve for W, the result is in the following form:

[0035] W = (A T A)-1 A T P

[0036] After inputting the offset matrix of the light spot, an adaptive dynamic adjustment amount is obtained; the adjustment angle is calculated based on the adjustment amount, and then the adjustment angle is removed from each transparent part angle deviation detection result to finally obtain an accurate measurement result.

[0037] The beneficial effects of adopting the above technical solution are as follows: The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts provided by this invention, based on digital image processing and combined with calibration optimization strategies, establishes an adaptive linear correlation calibration strategy. This strategy can formulate specific adjustment schemes for the array-type angular deviation detection equipment for aerospace transparent parts, and solve the adjustment angle in real time to calibrate the equipment. This method has the advantages of adaptive adjustment, high computational efficiency, high calibration accuracy, and high degree of automation, significantly improving the calibration technology level of installation deviation. Attached Figure Description

[0038] Figure 1 A flowchart of the installation deviation adaptive calibration method for a multi-point angular deviation detection device for aerospace transparent parts provided in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the light spot shift provided in an embodiment of the present invention. Detailed Implementation

[0040] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0041] In this embodiment, the adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aviation transparent parts is as follows: Figure 1 As shown, it includes the following steps:

[0042] Step 1: Acquire array spot images and preprocess them to obtain binarized images corresponding to the four spots. Before conducting the inspection of aerospace transparent parts, first capture an image containing four bright spots on the CCD array of the array laser receiver, denoted as I. Then, uniformly segment the image of the area where the four spots are located to form four independent rectangular regions of the same size, denoted as I1, I2, I3, and I4. Subsequently, mean filtering is applied to these four rectangular regions to remove noise that affects spot positioning. Adaptive threshold segmentation is then applied to the four rectangular regions after mean filtering to obtain the corresponding binarized images.

[0043] This embodiment takes the light spot image I1 as an example to perform adaptive threshold segmentation. The specific steps are as follows: the average pixel value of the light spot image I1 after mean filtering is... The mathematical expression for the initial threshold used for image segmentation is as follows:

[0044]

[0045] Where I1(i,j) is the grayscale pixel value of (i,j) in image I1;

[0046] Next, based on the initial threshold The laser image is divided into two parts: the target region and the background. The area occupied by the target in the image is calculated. Then, the average value of all pixels within the target's area is calculated. Its mathematical form is as follows:

[0047]

[0048] Based on the relationship between image brightness and camera exposure brightness, using average values... Multiply by the scaling factor K as the final binarization threshold As shown in equation (3), the image is binarized and segmented;

[0049]

[0050] The remaining spot images I2, I3, and I4 are also segmented using the same adaptive thresholding method to obtain the corresponding binarized images;

[0051] The implementation conditions for step 1 are as follows: 1) Ensure that the array laser emitting device and the receiving device in the array-type angular deviation detection equipment for aviation transparent parts are roughly on the same horizontal line; 2) After the initial adjustment, the detection equipment should be fixed and vibration should be avoided; 3) Confirm that the array laser receiving end can accurately focus the light spot onto the CCD array; 4) Ensure that the lighting conditions are stable and the laser intensity remains unchanged during the image capture process.

[0052] Step 2: Perform adaptive spot center localization on the binarized images corresponding to the four spots;

[0053] Step 2.1: Detect the edges of the light spots in the binarized I1, I2, I3 and I4 images;

[0054] This embodiment uses the binarized image I1 as an example to briefly describe the edge detection process. The specific steps are as follows: First, the Sobel operator is used to calculate the gradient of the I1 image to obtain the horizontal gradient G. x and vertical gradient G y The mathematical form is as follows:

[0055]

[0056] Among them, S x and S yThese represent the horizontal and vertical filters of the Sobel operator, respectively.

[0057] Next, the gradient magnitude M and direction Θ of the binarized image I1 are calculated, mathematically as follows:

[0058]

[0059] Θ(x,y)=arctan(G y / / G x (6)

[0060] Next, for each pixel I1(x,y), only the local maxima along the gradient direction are retained; that is, if M(x,y) is the maximum value in the neighborhood, it is retained, otherwise it is set to 0. Then, a high threshold T is set. H and low threshold T L Pixels are divided into strong edges, weak edges, and non-edges, mathematically as follows:

[0061]

[0062] Here, se(x,y) represents edge pixels. When se(x,y) = 1, it is a strong edge; when se(x,y) = 0, it is a non-edge; and when se(x,y) = weak, it is a weak edge.

[0063] Finally, we check whether weak edges are connected to strong edges. Only if they are connected can weak edges be preserved. The mathematical form is as follows:

[0064]

[0065] Where E(x,y) represents the final extracted edge pixels;

[0066] Images I2, I3, and I4 are processed using the same edge detection process to obtain the corresponding light spot image edges.

[0067] Step 2.2: Perform elliptical least-squares fitting on the edge pixels of the light spots obtained from the four images I1, I2, I3, and I4 respectively to calculate the corresponding approximate elliptical regions. Intersect this region with the original denoised image without binarization to obtain an elliptical gray-level region. Then, for this gray-level region, use the weighted gray-level centroid method to locate the final light spot center. The mathematical form is as follows:

[0068]

[0069] Where (x0, y0) represents the coordinates of the light spot center, I ′(x,y) represents the pixel grayscale value of the image, M is the number of horizontal pixels in the image; N is the number of vertical pixels in the image, and M*N represents the pixel size of the elliptical grayscale region;

[0070] Through the above edge detection, ellipse fitting and weighted gray centroid extraction, the spot centers of I1, I2, I3 and I4 are obtained respectively;

[0071] The implementation conditions for step 2 are as follows: ensure that the implementation conditions of step 1 remain unchanged, and adjust the image exposure to avoid the edges of the light spots being too blurry.

[0072] Step 3: Establish an adaptive linear correlation calibration optimization strategy to perform adaptive calibration of installation deviation; after calculating the four spot centers, calibrate them with the corresponding four crosshair standard positions generated by the CCD array to obtain the adaptive dynamic adjustment amount; calculate the adjustment angle based on the adjustment amount, remove the adjustment angle from each transparent part corner deviation detection result, and finally obtain accurate measurement results;

[0073] First, the four segmented rectangular regions I1, I2, I3, and I4 are restored to their original complete rectangular pixel regions with four-point arrayed light spots. Second, a coordinate system is established with the top-left corner of the original image containing the four-point light spots captured by the camera as the origin, the horizontal direction as the X-axis, and the vertical direction as the Y-axis. The center coordinates of the light spots in these four rectangular regions are then unified into this coordinate system, denoted as (X... i ,Y i ), where i = 1, 2, 3, 4, such as Figure 2 As shown; at the same time, the standard positions of the four crosshairs are also unified into this coordinate system, denoted as (X... ti ,Y ti ), where i = 1, 2, 3, 4; Figure 2 In the diagram, 6 represents the received incident laser beam; 7 represents the light spot formed on the CCD array; 8 represents the CCD array; 9 represents the position of the reference crosshair; (X1, Y1) are the coordinates of the center of the upper left light spot; (X t1 ,Y t1 (X1, Y2) represents the coordinates of the upper left reference position; (X2, Y2) represents the coordinates of the upper right spot center; (X... t2 ,Y t2 (X3, Y4) represents the coordinates of the upper right corner reference position; (X3, Y4) represents the coordinates of the lower left corner light spot center; (X... t3 ,Y t3 (X4, Y4) represents the coordinates of the lower left reference position; (X4, Y4) represents the coordinates of the lower right spot center; (X... t4 ,Y t4ΔX1 is the coordinate of the lower right corner reference position; ΔX2 is the deviation of the upper left corner spot center from the reference position; ΔX3 is the deviation of the lower left corner spot center from the reference position; ΔX4 is the deviation of the lower right corner spot center from the reference position.

[0074] Therefore, the offsets of the four light spots are expressed in the following mathematical form:

[0075]

[0076] For the four light spots, the offsets are organized into the following matrix:

[0077]

[0078] A linear correlation model is established between the spot offset and the adjustment range of the array-type angular deviation detection equipment for aerospace transparent parts, which is expressed by the following linear equation:

[0079] P = A·W + B (12)

[0080] Where P is the offset matrix of the light spot; A is the adjustment matrix, representing the influence of different adjustment directions on the position of the light spot; W is the adjustment vector, representing the amount to be adjusted; and B is a constant term, representing the initial offset of the system.

[0081] The adjustment of this aerospace transparent component array-type angular deviation detection device only involves compensation for horizontal and vertical offsets. Therefore, the adjustment matrix A is given as follows based on the standard position of the light spot:

[0082]

[0083] Using the least squares method to solve for W, the result is in the following form:

[0084] W = (A T A) -1 A T P (14)

[0085] After inputting the offset matrix of the light spot, an adaptive dynamic adjustment amount is obtained; the adjustment angle is calculated based on the adjustment amount, and then the adjustment angle is removed from each transparent part angle deviation detection result to finally obtain an accurate measurement result.

[0086] In this embodiment, the angular deviation value of a single 1° standard optical wedge is detected using the method of the present invention, thereby verifying the accuracy of the calibration method of the present invention. The angular deviation value represented by standard optics, resulting from incident light at any angle, is a fixed value and can be used as a detection standard. The specific implementation process is as follows: First, an uncalibrated angular deviation detection device is used to detect the standard optical wedge to obtain the corresponding angular deviation value; then, the angular deviation detection device is calibrated, and the same optical wedge is detected again to obtain the calibrated angular deviation value. By comparing the two angular deviation values ​​before and after calibration, the accuracy of the calibration can be demonstrated based on their magnitude.

[0087] The detection and calibration process consists of three parts: angular deviation detection of the standard optical wedge using uncalibrated equipment, equipment calibration, and angular deviation detection of the standard optical wedge using calibrated equipment.

[0088] Step S1: Angular deviation detection of the standard optical wedge using uncalibrated equipment. First, construct an array-type angular deviation detection device for the aerospace transparent component. The specific steps are as follows: Adjust the array laser emitter, the transparent component support, and the array laser receiver so that their centers are approximately on the same horizontal line. Next, adjust the horizontal distance between the array laser emitter and the transparent component to 1.25m, and the horizontal distance between the transparent component and the array laser receiver to 1.15m. The array laser receiver consists of a polarizer, a focusing lens, and a CCD array; therefore, a 0.95° polarizer, a 1.5mm focusing lens, and a Work Power WP-UT880 / M CCD array are selected.

[0089] Next, the uncalibrated device was used to detect the angular deviation of the standard optical wedge. First, the array laser emitter was turned on to generate a 2×2 uniform laser with an intensity of 3mW. Then, the laser was received by the array laser receiver, forming four bright spots on the CCD array. The image of the spot before deviation was recorded, and the center coordinates of the four spots were extracted. Next, the 1° standard optical wedge was fixed on a transparent bracket, ensuring that the array laser beam passed through the wedge, and the center coordinates of the spot after deviation were recorded again. Based on the principle of angular deviation calculation, combined with the center coordinates of the four spots before and after deviation and the focal length of the focusing lens of the array laser receiver, the angular deviation values ​​of the current four regions can be calculated. The results are as follows: 1° optical wedge: top left: 1.1201°; top right: 1.1129°; bottom left: 1.0976°; bottom right: 1.0892°

[0090] The top left corner represents the angular deviation value calculated by shifting the light spot before and after the top left corner, and the same applies to the top right, bottom left, and bottom right corners.

[0091] Step S2: Calibration of Angular Deviation Detection Equipment. The equipment is calibrated, and the calibration algorithm flow is as follows: Figure 1As shown. First, without inserting the optical wedge, based on the detection equipment built in step S1, the array laser emitting device is turned on, causing it to form four bright spots on the CCD array of the receiving device, and the current spot image is acquired. Second, the image is segmented into I1, I2, I3, and I4 according to the area where the spot is located, and image processing is performed on the segmented areas to remove noise. Then, adaptive threshold segmentation is performed based on the image grayscale. Combining edge detection, elliptical region extraction, and weighted grayscale centroid methods, the center of the spot is located, and four coordinates are extracted. Finally, the image areas are merged, and the coordinates are unified. A calibration optimization strategy is established, inputting the standard position of the crosshair and the center coordinates of the spot, and outputting the calibration matrix W = [0.036, 0.027], where 0.036 indicates that the device needs to be adjusted by 0.036 pixels in the horizontal direction; 0.027 indicates that the device needs to be adjusted by 0.027 pixels in the vertical direction, and the corresponding adjustment angle is calculated from the geometric output matrix.

[0092] Step S3: Use the calibrated equipment to detect the angular deviation of the standard optical wedge. First, place the 1° standard optical wedge into the detection equipment, ensuring that the array laser beam passes through the wedge, and then record the coordinates of the center of the offset spot. Based on the principle of angular deviation calculation, combined with the coordinates of the four center points after offset and the coordinates of the four points before offset in step S2, as well as the focal length of the focusing lens of the array laser receiving device, the angular deviation values ​​of the current four area positions can be calculated. Next, according to the adjustment angle in step S2, the angular deviation value is calibrated, and the following results are obtained: 1° optical wedge: top left: 1.0191°; top right: 1.0203°; bottom left: 1.0054°; bottom right: 1.0032°

[0093] Step S4: Numerical Analysis. The standard deviation of the angle deviation calculated in Step S1 is 0.1057; the standard deviation of the angle deviation calculated in Step S3 is 0.0143. By comparing the standard deviation of the angle deviation with the angle deviation value of the corresponding point, it can be seen that the detection accuracy after calibration using the method of this invention is higher, and its performance is outstanding under the same detection algorithm.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. An adaptive calibration method for installation deviation of a multi-point angular deviation detection device for aerospace transparent parts, characterized in that: Includes the following steps: Step 1: Before conducting the inspection of the transparent aerospace parts, capture the array spot image on the CCD array of the array laser receiver and preprocess it to obtain the binarized image corresponding to the four spots. Step 2: Perform adaptive spot center localization on the binarized images corresponding to the four spots; Step 3: Establish an adaptive linear correlation calibration optimization strategy to perform adaptive calibration of installation deviations; After calculating the four spot centers, they are calibrated with the corresponding four crosshair standard positions generated by the CCD array to obtain the adaptive dynamic adjustment amount. The adjustment angle is calculated based on the adjustment amount, and this adjustment angle is removed from each transparent part angle deviation detection result to obtain an accurate measurement result.

2. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 1, characterized in that: Step 1 includes: Before conducting inspection of transparent aerospace components, an image containing four bright spots is captured on the CCD array of the array laser receiver, denoted as I; The images of the four light spot regions are uniformly divided to form four independent rectangular light spot regions of the same size, denoted as I1, I2, I3 and I4; Mean filtering was applied to each of the four rectangular regions to remove noise that affected the localization of the light spot; Adaptive thresholding is applied to the four rectangular regions after mean filtering to obtain the corresponding binarized images.

3. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 2, characterized in that: The method for adaptive threshold segmentation of the four rectangular regions after mean filtering is as follows: The average pixel value of the spot image after mean filtering is used as the initial threshold for image segmentation; The laser image is divided into two parts, the target area and the background, based on the initial threshold, and the range of the image area occupied by the target is calculated at the same time. Calculate the average value of all pixels within the image region occupied by the target; Based on the relationship between image brightness and camera exposure brightness, the average value of all pixels within the image area occupied by the target is multiplied by a scaling factor K as the threshold for final image binarization, resulting in a binarized image.

4. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 2, characterized in that: Step 2.1: Detect the edges of the light spots in the binarized I1, I2, I3 and I4 images; Step 2.2: Perform elliptical least squares fitting on the edge pixels of the light spots obtained from the four images I1, I2, I3 and I4 respectively to calculate the corresponding approximate elliptical regions. Intersect this region with the original denoised image without binarization to obtain an elliptical gray-level region. Then, for the gray-level region, use the weighted gray-level centroid method to locate the final light spot center.

5. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 4, characterized in that: Step 2.1 includes: The Sobel operator is used to calculate the gradient of the image, yielding the horizontal gradient G. x and vertical gradient G y ; Calculate the gradient magnitude M and direction Θ of the image; For each pixel in the image, only local maxima along the gradient direction are retained; that is, if M(x,y) is the maximum value in the neighborhood, it is retained, otherwise it is set to 0. Then, a high threshold T is set. H and low threshold T L Pixels are categorized into strong edges, weak edges, and non-edges; Finally, it checks whether weak edges are connected to strong edges, and only retains weak edges that are connected to strong edges to obtain the final extracted image edge pixels.

6. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 5, characterized in that: The center of the light spot mentioned in step 2.2 is shown by the following formula: Where (x0,y0) represents the center coordinates of the light spot, I′(x,y) represents the pixel grayscale value of the image, M is the number of horizontal pixels in the image, N is the number of vertical pixels in the image, and M*N represents the pixel size of the elliptical grayscale region.

7. The adaptive calibration method for installation deviation of the multi-point angular deviation detection equipment for aerospace transparent parts according to claim 6, characterized in that: Step 3 includes: The four rectangular regions I1, I2, I3 and I4 that were segmented are restored to the original complete rectangular pixel regions with four-point array light spots; A coordinate system is established with the top left corner of the original image containing four light spots captured by the camera as the origin, the horizontal direction as the X-axis, and the vertical direction as the Y-axis. The center coordinates of the light spots in these four rectangular areas are unified into this coordinate system, denoted as (X... i ,Y i ), where i = 1, 2, 3, 4; at the same time, the standard positions of the four crosshairs are also unified into this coordinate system, denoted as (X ti ,Y ti Therefore, the four spot offsets are expressed in the following mathematical form: For the four light spots, the offsets are organized into the following matrix: A linear correlation model is established between the spot offset and the adjustment range of the array-type angular deviation detection equipment for aerospace transparent parts, which is expressed by the following linear equation: P = A·W + B Where P is the offset matrix of the light spot; A is the adjustment matrix, representing the influence of different adjustment directions on the position of the light spot; W is the adjustment vector, representing the amount to be adjusted; and B is a constant term, representing the initial offset of the system. Using the least squares method to solve for W, the result is in the following form: W=(A T A) -1 A T P After inputting the offset matrix of the light spot, an adaptive dynamic adjustment amount is obtained; the adjustment angle is calculated based on the adjustment amount, and then the adjustment angle is removed from each transparent part angle deviation detection result to finally obtain an accurate measurement result.

Images