Self-adaptive calibration method for installation deviation of multi-point angular deviation detection equipment for aviation transparent part

Abstract

The invention provides a self-adaptive calibration method for installation deviation of multi-point angular deviation detection equipment for aviation transparent parts, and relates to the technical field of automatic detection. The method comprises the following steps: firstly, acquiring an array light spot image, and preprocessing the array light spot image to obtain binary images corresponding to four light spots; self-adaptive light spot center positioning is carried out on the binarized images corresponding to the four light spots; after the four light spot centers are obtained through calculation, calibration is carried out on the four light spot centers and four corresponding cross curve standard positions generated by the CCD area array, and self-adaptive dynamic adjustment amount is obtained; and calculating an adjustment angle according to the adjustment amount, and removing the adjustment angle in each transparent part angle deviation detection result to finally obtain an accurate measurement result. According to the method, a specific adjustment scheme of the aviation transparent part array type angular deviation detection equipment can be formulated, and the adjustment angle can be solved in real time, so that the equipment can be calibrated.

Description

Technical Field

[0001] The invention relates to the field of automated detection technology, and in particular to an installation deviation adaptive calibration method for multi-point angular deviation detection equipment of an aviation transparent part. Background Art

[0002] Aviation transparent parts are important components for pilots to observe the external environment and determine the distance. Factors that affect the optical performance of transparent parts include: optical angular deviation, optical distortion, transmittance, refractive index, parallax and clarity. Among them, the measurement of optical angular deviation is of great significance to the optical quality inspection of aviation transparent parts. For this purpose, an array angular deviation detection device for aviation transparent parts (also known as multi-point angular deviation detection device for aviation transparent parts) is established. The main principle of this detection device is that 4 2×2 laser beams generated by an array laser emitting device are deflected after passing through the tested part, and then captured by the array laser receiving device, and finally four bright spots are formed on its CCD array. By locating the offset of the light spot of the tested part before and after the detection, and combining the corresponding installation distance, the angular deviation values ​​of the four points can be directly calculated.

[0003] In order to obtain accurate angular deviation values, the installation deviation in the aviation transparent component array angular deviation detection equipment needs to be calibrated before measurement. The traditional calibration method is to use a level gauge to ensure that the laser transmitter and receiver remain level, but this method has low calibration accuracy, low adjustment efficiency, and it is difficult to ensure the stability of the calibration results. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an adaptive calibration method for installation deviation of multi-point angular deviation detection equipment for aviation transparent parts in view of the deficiencies of the above-mentioned prior art, so as to realize adaptive calibration of installation deviation of array angular deviation detection equipment for aviation transparent parts.

[0005] In order to solve the above 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 aviation transparent parts, comprising the following steps:

[0006] Step 1: Obtain the array spot image and perform preprocessing to obtain the binary image corresponding to the four spots;

[0007] Before the inspection of aviation transparent parts is carried out, an image containing four bright spots on the CCD array of the array laser receiving device is captured, which is denoted as I;

[0008] The images of the areas where the four light spots are located are evenly divided to form four independent light spot rectangular areas of the same size, which are recorded as I1, I2, I3 and I4;

[0009] The four rectangular areas are respectively subjected to mean filtering to remove the noise that affects the light spot positioning;

[0010] Perform adaptive threshold segmentation on the four rectangular areas after mean filtering to obtain the corresponding binary images;

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

[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, according to the initial threshold, and the range of the image area occupied by the target is calculated;

[0014] Calculate the average value of all pixels in the image area occupied by the target;

[0015] According to the relationship between image brightness and camera exposure brightness, the average value of all pixels in the image area occupied by the target multiplied by the proportional coefficient K is used as the threshold for the final image binarization to obtain a binary image;

[0016] Step 2: Adaptively locate the center of the light spot according to the binary images corresponding to the four light spots;

[0017] Step 2.1: Detect the edge of the light spot on the binarized images I1, I2, I3 and I4;

[0018] Use the Sobel operator to calculate the gradient of the image and get the horizontal gradient G x and the vertical gradient G y ;

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

[0020] For each pixel in the image, only the local maximum in the gradient direction is 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 , classify pixels into strong edge, weak edge and non-edge;

[0021] Finally, detect whether the weak edge is connected to the strong edge, and only retain the weak edge connected to the strong edge to obtain the final extracted image edge pixels;

[0022] Step 2.2: Perform elliptical least squares fitting on the spot edge pixels obtained from the four images I1, I2, i3 and i4, calculate the corresponding approximate elliptical area, and use this area to intersect with the original denoised image that has not been binarized to obtain an elliptical grayscale area. Then, for its grayscale area, use the weighted grayscale centroid method to locate the final spot center. The mathematical form is as follows:

[0023]

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

[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 with the corresponding four cross-line standard positions generated by the CCD array to obtain an adaptive dynamic adjustment amount; calculate the adjustment angle according to the adjustment amount, remove the adjustment angle in each transparent part angle deviation detection result, and finally obtain an accurate measurement result;

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

[0027] The upper left corner of the original image containing four light spots collected by the camera is taken as the origin, the horizontal direction is the X axis, and the vertical direction is the Y axis to establish a coordinate system, and the center coordinates of the light spots in the four rectangular areas are unified into the coordinate system, recorded as (X i ,Y i ), where i = 1, 2, 3, 4; at the same time, the four cross-line standard positions are also unified into this coordinate system, denoted as (X ti ,Y ti ), where; therefore, the four spot offsets are expressed by the following mathematical form:

[0028]

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

[0030]

[0031] A linear correlation model between the light spot offset and the adjustment amount of the aviation transparent component array angular deviation detection equipment is established, which is expressed by a linear equation:

[0032] P=A·W+B

[0033] Among them, P is the offset matrix of the light spot; A is the adjustment matrix, which represents the influence of different adjustment directions on the position of the light spot; W is the adjustment vector, which represents the amount to be adjusted; B is the constant term, which represents the initial offset of the system;

[0034] Using the least squares method to solve W, the result is as follows:

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

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

[0037] The beneficial effect of adopting the above technical solution is that the method for adaptively calibrating the installation deviation of the multi-point angular deviation detection equipment for aviation transparent parts provided by the present invention is based on digital image processing and combined with the calibration optimization strategy to establish an adaptive linear correlation calibration strategy. This strategy can formulate a specific adjustment plan for the aviation transparent parts array angular deviation detection equipment, 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, and significantly improves the technical level of calibration of installation deviation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of a method for adaptively calibrating installation deviations of a multi-point angular deviation detection device for aviation transparent parts provided in an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of light spot offset provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0041] In this embodiment, the aviation transparent part multi-point angular deviation detection device installation deviation adaptive calibration method, such as Figure 1 As shown, the following steps are included:

[0042] Step 1: Acquire the array spot image and perform preprocessing to obtain the binary images corresponding to the four spots. Before carrying out the aviation transparent parts inspection, first capture the image containing four highlighted spots on the CCD array of the array laser receiving device, which is recorded as I. Then, evenly segment the image according to the area where the four spots are located to form four independent rectangular areas of the same size, which are recorded as I1, I2, I3 and I4. Subsequently, perform mean filtering on these four rectangular areas respectively to remove the noise that affects the positioning of the spots. Perform adaptive threshold segmentation on the four rectangular areas after mean filtering to obtain the corresponding binary images.

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

[0044]

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

[0046] Next, according to the initial threshold The laser image is divided into two parts: the target area and the background. The range of the image area occupied by the target is calculated at the same time. Then, the average value of all pixels in the image area occupied by the target is calculated. Its mathematical form is as follows:

[0047]

[0048] According to the relationship between image brightness and camera exposure brightness, the average Multiply by the scale factor K as the final binarization threshold As shown in formula (3), the image is binarized and segmented;

[0049]

[0050] The other spot images I2, I3, and I4 are segmented by the above-mentioned adaptive threshold in the same way to obtain the corresponding binary images;

[0051] The implementation conditions of step 1 are as follows: 1) Ensure that the array laser emitting device and receiving device in the aviation transparent parts array angular deviation detection equipment are approximately located on the same horizontal line; 2) After the initial adjustment, the detection equipment should be fixed and avoid vibration; 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 during the image capture process and the laser intensity remains unchanged.

[0052] Step 2: Adaptively locate the center of the light spot according to the binary images corresponding to the four light spots;

[0053] Step 2.1: Detect the edge of the light spot on the binarized images I1, I2, I3 and I4;

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

[0055]

[0056] Among them, S x and S yRespectively represent the horizontal and vertical filters of the Sobel operator;

[0057] Secondly, calculate the gradient magnitude M and direction Θ of the binarized image I1. The mathematical form is as follows:

[0058]

[0059] Θ(x,y)=arctan(G y / / G x ) (6)

[0060] Next, for each pixel I1(x, y), only the local maximum in the gradient direction is 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 edge, weak edge and non-edge. The mathematical form is as follows:

[0061]

[0062] Wherein, 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; when se(x,y)=weak, it is a weak edge;

[0063] Finally, check whether the weak edge is connected to the strong edge. Only when it is connected can the weak edge be preserved. The mathematical form is as follows:

[0064]

[0065] Among them, E(x,y) represents the edge pixels finally extracted;

[0066] The above edge detection process is also repeated for images I2, I3 and I4 to obtain the corresponding light spot image edges respectively;

[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, calculate the corresponding approximate elliptical area, and use this area to intersect with the original denoised image that has not been binarized to obtain an elliptical grayscale area. Then, for its grayscale area, use the weighted grayscale centroid method to locate the final light spot center. The mathematical form is as follows:

[0068]

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

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

[0071] The implementation conditions of step 2 are as follows: ensure that the implementation conditions of step 1 remain unchanged, and adjust the image exposure to avoid excessive blurring of the edge of the light spot.

[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 with the corresponding four cross-line standard positions generated by the CCD array to obtain an adaptive dynamic adjustment amount; calculate the adjustment angle according to the adjustment amount, remove the adjustment angle in each transparent part angle deviation detection result, and finally obtain an accurate measurement result;

[0073] First, the four rectangular areas I1, I2, I3 and I4 after segmentation are restored to the initial complete rectangular pixel area with four-point array light spots; secondly, a coordinate system is established with the upper left corner of the original image containing four-point light spots collected by the camera as the origin, the horizontal direction as the X axis, and the vertical direction as the Y axis, and the center coordinates of the light spots of the four rectangular areas are unified into the coordinate system, recorded as (X i ,Y i ), where i = 1, 2, 3, 4, such as Figure 2 At the same time, the four cross-line standard positions are also unified into this coordinate system, denoted as (X ti ,Y ti ), where i = 1, 2, 3, 4; Figure 2 In the figure, 6 represents the incident laser light received; 7 represents the light spot formed on the CCD array; 8 represents the array CCD; 9 represents the reference crosshair position; (X1, Y1) is the coordinate of the center of the light spot in the upper left corner; (X t1 ,Y t1 ) is the coordinate of the upper left corner reference position; (X2, Y2) is the coordinate of the center of the upper right corner spot; (X t2 ,Y t2 ) is the coordinate of the upper right corner reference position; (X3, Y4) is the coordinate of the center of the lower left corner spot; (X t3 ,Y t3 ) is the coordinate of the reference position of the lower left corner; (X4, Y4) is the coordinate of the center of the light spot in the lower right corner; (X t4 ,Y t4) is the coordinate of the lower right corner reference position; ΔX1 is the deviation between the upper left corner light spot center and the reference position; ΔX2 is the deviation between the upper right corner light spot center and the reference position; ΔX3 is the deviation between the lower left corner light spot center and the reference position; ΔX4 is the deviation between the lower right corner light spot center and the reference position.

[0074] Therefore, the four spot offsets are expressed by the following mathematical form:

[0075]

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

[0077]

[0078] A linear correlation model between the light spot offset and the adjustment amount of the aviation transparent component array angular deviation detection equipment is established, which is expressed by a linear equation:

[0079] P=A·W+B (12)

[0080] Among them, P is the offset matrix of the light spot; A is the adjustment matrix, which represents the influence of different adjustment directions on the position of the light spot; W is the adjustment vector, which represents the amount to be adjusted; B is the constant term, which represents the initial offset of the system;

[0081] The adjustment of the aviation transparent component array angular deviation detection device only involves the compensation offset in the horizontal and vertical directions, so the adjustment matrix A is given as follows according to the standard position of the light spot:

[0082]

[0083] Using the least squares method to solve W, the result is as follows:

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

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

[0086] In this embodiment, the method of the present invention is used to detect the angular deviation value of a single 1° standard optical wedge, thereby verifying the accuracy of the calibration method of the present invention. The angular deviation value generated by incidence from any angle represented by standard optics is a fixed value and can be used as a detection standard. The specific idea of ​​the implementation process is: first, an uncorrected 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 then the same optical wedge is detected again to obtain the corrected angular deviation value. By comparing the two angular deviation values ​​before and after correction, the accuracy of the correction can be explained based on their precision.

[0087] The detection and correction process consists of three parts: using an uncalibrated device to detect the angular deviation of a standard optical wedge, calibrating the device, and using the calibrated device to detect the angular deviation of a standard optical wedge.

[0088] Step S1: Use an uncalibrated device to detect the angular deviation of the standard optical wedge. First, build an array angular deviation detection device for aviation transparent parts. The specific steps are as follows: adjust the array laser emitting device, the transparent part bracket and the array laser receiving device so that their centers are roughly on the same horizontal line. Secondly, adjust the horizontal distance between the array laser emitting device and the transparent part to 1.25m, and adjust the horizontal distance between the transparent part and the array laser receiving device to 1.15m. The array laser receiving device consists of a polarizer, a focusing lens and an array CCD, so a 0.95° polarizer, a 1.5mm focusing lens and a Work Power WP-UT880 / M array CCD are selected respectively.

[0089] Next, use the uncalibrated device to detect the angular deviation of the standard optical wedge. First, turn on the array laser emitting device to generate a 2×2 uniform laser with an intensity of 3mw. Then, the laser is received by the array laser receiving device, forming four bright spots on the CCD array, recording the current unshifted spot image, and extracting the center coordinates of the four spots. Next, fix the 1° standard optical wedge on a transparent bracket to ensure that the array laser light passes through the optical wedge, and record the center coordinates of the offset spot again. According to the principle of angular deviation calculation, combined with the center coordinates of the four points corresponding to the offset before and after the offset and the focal length of the focusing mirror of the array laser receiving device, the angular deviation values ​​of the current four regional positions can be calculated, and the results are as follows: 1° optical wedge: upper left: 1.1201°; upper right: 1.1129°; lower left: 1.0976°; lower right: 1.0892°

[0090] The upper left represents the angular deviation value calculated by offsetting the front and rear light spots at the upper left corner, and the same is true for the upper right, lower left, and lower right.

[0091] Step S2: Calibrate the angular deviation detection device. The device is calibrated, and the calibration algorithm flow is as follows: Figure 1As shown. First, without inserting the optical wedge, according to the detection equipment built in step S1, turn on the array laser emitting device to form four bright spots on the area array CCD of the receiving device, and collect the current spot image. Secondly, the image is divided into I1, I2, I3 and I4 according to the area where the spot is located, and the segmented area is processed to remove noise. Then, adaptive threshold segmentation is performed according to the image grayscale. Combining the three methods of edge detection, elliptical area extraction and weighted grayscale centroid, the center of the spot is located, and four coordinates are extracted. Finally, the image area is merged to unify the coordinates. Establish a calibration optimization strategy, input the standard position of the crosshairs and the center coordinates of the spot, and output the calibration matrix W = [0.036, 0.027], where 0.036 means that the device needs to be adjusted by 0.036 pixels in the horizontal direction; 0.027 means that the device needs to be adjusted by 0.027 pixels in the vertical direction, and the corresponding adjustment angle is calculated by the geometric output matrix.

[0092] Step S3: Use the calibrated equipment to detect the angular deviation of the standard optical wedge. First, place a 1° standard optical wedge into the detection equipment to ensure that the array laser light passes through the optical wedge, and then record the center coordinates of the light spot after the offset. According to the principle of angular deviation calculation, combined with the center coordinates of the four points after the offset and the four-point coordinates before the offset in step S2, as well as the focal length of the focusing mirror of the array laser receiving device, the angular deviation values ​​of the current four regional positions can be calculated. Then, according to the adjustment angle in step S2, the angular deviation value is calibrated to obtain the following results: 1° optical wedge: upper left: 1.0191°; upper right: 1.0203°; lower left: 1.0054°; lower right: 1.0032°

[0093] Step S4: numerical analysis. The standard deviation of the angular deviation calculated in step S1 is 0.1057; the standard deviation of the angular deviation calculated in step S3 is 0.0143. By comparing the standard deviation of the angular deviation with the angular deviation value of the corresponding point, it can be seen that the detection accuracy after calibration using the method of the present invention is higher and the 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, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements 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. A method for adaptively calibrating installation deviation of multi-point angular deviation detection equipment for aviation transparent parts, characterized in that: The following steps are involved: Step 1: Before carrying out aviation transparent parts inspection, capture the array spot image on the CCD array of the array laser receiving device and perform preprocessing to obtain the binary image corresponding to the four spots; Step 2: Adaptively locate the center of the light spot according to the binary images corresponding to the four light spots; Step 3: Establish an adaptive linear correlation calibration optimization strategy to perform adaptive calibration of installation deviation; After the four spot centers are calculated, they are calibrated with the corresponding four cross-line standard positions generated by the CCD array to obtain the adaptive dynamic adjustment amount; The adjustment angle is calculated according to the adjustment amount, and the adjustment angle is removed from each transparent component angle deviation detection result to finally obtain an accurate measurement result.

2. The method for self-adaptive calibration of installation deviation of multi-point angular deviation detection equipment for aviation transparent parts according to claim 1 is characterized by: The step 1 comprises: Before the inspection of aviation transparent parts is carried out, an image containing four bright spots on the CCD array of the array laser receiving device is captured, which is denoted as I; The images of the areas where the four light spots are located are evenly divided to form four independent light spot rectangular areas of the same size, which are recorded as I1, I2, I3 and I4; The four rectangular areas are respectively subjected to mean filtering to remove the noise that affects the light spot positioning; The four rectangular areas after mean filtering are segmented by adaptive threshold to obtain the corresponding binary images.

3. The method for adaptively calibrating installation deviation of multi-point angular deviation detection equipment for aviation transparent parts according to claim 2, characterized in that: The method for performing adaptive threshold segmentation on the four rectangular areas after mean filtering is: 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, according to the initial threshold, and the range of the image area occupied by the target is calculated; Calculate the average value of all pixels in the image area occupied by the target; According to the relationship between image brightness and camera exposure brightness, the average value of all pixels in the image area occupied by the target multiplied by the proportional coefficient K is used as the threshold for the final image binarization to obtain a binary image.

4. The method for self-adaptive calibration of installation deviation of multi-point angular deviation detection equipment for aviation transparent parts according to claim 2, characterized in that: Step 2.1: Detect the edge of the light spot on the binarized images I1, I2, I3 and I4; 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, calculate the corresponding approximate elliptical area, and use this area to intersect with the original denoised image that has not been binarized to obtain an elliptical grayscale area. Then, for the grayscale area, use the weighted grayscale centroid method to locate the final center of the light spot.

5. The method for self-adaptive calibration of installation deviation of multi-point angular deviation detection equipment for aviation transparent parts according to claim 4, characterized in that: The step 2.1 comprises: Use the Sobel operator to calculate the gradient of the image and get the horizontal gradient G x and the vertical gradient G y ; Calculate the gradient magnitude M and direction Θ of the image; For each pixel in the image, only the local maximum in the gradient direction is 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 classified into strong edge, weak edge and non-edge; Finally, it is detected whether the weak edge is connected to the strong edge, and only the weak edge connected to the strong edge is retained to obtain the final extracted image edge pixels.

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

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

Images