A method for detecting surface defects of lens

Abstract

The present invention discloses a method for detecting surface defects of a lens, which relates to the technical field of lens detection and solves the problem that some relatively hidden scratches and some relatively fine air bubbles cannot be identified, resulting in incomplete detection of surface defects. The present invention determines the associated reflection angle by preferentially adopting the reflection method of the irradiated line through the relevant processing for the abnormal area, and determines whether the angle comparison is consistent based on the specific comparison between the incident angle and the reflection angle. When the reflection test is normal, the refraction analysis is performed to determine whether the refraction angle generated in each area is consistent, so as to evaluate whether there are relevant cracks and defects such as air bubbles inside the lens. The evaluation and processing method is more comprehensive and accurate, and can achieve better evaluation and processing detection effect.

Description

Technical Field

[0001] The present invention relates to the technical field of lens detection, and in particular to a method for detecting surface defects of a lens. Background Art

[0002] Lenses are transparent materials with one or more curved surfaces made of optical materials such as glass or resin. After polishing, they are often assembled with glasses frames to form glasses. They are used to correct the user's vision and obtain a clear field of vision.

[0003] The application with publication number CN115144401A discloses a lens surface defect detection method using optical imaging. The detection scheme is designed from the perspective of optical-mechanical-electrical-computer integration, and the ability of optical parallel computing is fully utilized to achieve detection in much less than 1 second. The design of the invention scheme is derived and analyzed from the level of mathematical physics theory, which also makes the method itself theoretically self-consistent. The present invention includes the following steps: (1) constructing an incoherent light illumination and imaging system; (2) optical operations in the imaging optical path; (3) imaging and image calculation. In order to realize lens defect detection, the present invention uses optical imaging and the real-time characteristics of optical path calculation to perform complex calculations simultaneously during the imaging process, and then combines simple post-processing operations to obtain defect detection results. The present invention only needs to place the lens to be tested at the glass lens to be tested in the optical path to obtain the corresponding defect detection results in real time.

[0004] The relevant detection process for surface defects of optical lenses is generally based on high-definition visual equipment to detect relevant defects on the surface of optical lenses. However, the original detection method can only identify some relatively obvious defects. It can identify more obvious scratches, but some more hidden scratches and some relatively subtle air bubbles cannot be identified, resulting in incomplete detection of surface defects and an incomplete detection process. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a method for detecting surface defects of a lens, which solves the problem that some relatively hidden scratches and some relatively fine air bubbles cannot be identified, resulting in incomplete detection of surface defects.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for detecting surface defects of a lens comprises the following steps:

[0007] S1) Use the designated machine vision equipment to obtain the high-definition image of the surface of the lens, and after micro-processing the high-definition image of the surface, determine the image to be processed, and then combine the relevant lens standard model to compare the image to be processed with the lens standard model to determine the abnormal area. The specific method is as follows:

[0008] S11, based on the acquired surface high-definition image, determine the edge profile of the corresponding lens based on the surface high-definition image, and then scale down the edge profile based on the specific radiation range, the scale-down ratio is Y1, where Y1 is a preset value, and calibrate the high-definition image contained in the scaled edge profile as the image to be processed;

[0009] S12, performing an overlap comparison between the image to be processed and the corresponding lens standard model, wherein the lens standard model is a standard model of the lens of the corresponding model, and the standard model is also a model of the same size after the outline is proportionally reduced and segmented, based on the feature points inside the corresponding edge outlines of the image to be processed and the lens standard model, the image to be processed and the related areas at the same position inside the lens standard model are compared to identify whether the regional images of the related areas between the two are consistent, if they are consistent, the image to be processed is calibrated as the standard image, if there are inconsistent related areas, the corresponding related areas are calibrated as abnormal areas;

[0010] S2) Based on the determined abnormal area, the overall contour of the corresponding abnormal area is identified, and then based on the contour points of the overall contour, a set of feature processing lines is locked, and the feature processing lines are horizontally mapped on the surface of the abnormal area to determine the undetermined feature lines. The specific method is as follows:

[0011] S21, based on the outer edge contour of the corresponding abnormal area, determine the overall contour of the abnormal area, determine contour points on the overall contour in sequence, identify two groups of contour points with the farthest distance between two groups of straight lines from a plurality of contour points, and mark the straight line between the two groups of contour points as a feature processing line;

[0012] S22, based on the determined feature processing line, using a vertical and horizontal mapping method, mapping the feature processing line to the surface of the abnormal region, confirming the undetermined feature line after the feature processing line is mapped on the surface of the abnormal region, and marking the undetermined feature line on the surface of the abnormal region;

[0013] S3), based on the undetermined feature line determined in the surface of the abnormal area, based on the specific relevant features of the undetermined feature line, the curvature feature of the undetermined feature line at the same position is locked from the standard lens model, and based on the corresponding curvature feature, the undetermined feature line is divided into multiple micro-arc segments, and the specific sub-steps are:

[0014] S31, based on the specific position feature of the abnormal area in the original image to be processed, determining the relevant area on the surface of the standard lens model with the same position feature;

[0015] S32, based on the specific position features of the undetermined characteristic line determined inside the abnormal area, determine the related arc with the same position features in the related area, and use the related arc as the calibration arc of the undetermined characteristic line;

[0016] S33, identifying the relevant arcs existing in the calibration arc, calibrating some arc segments belonging to the same arc value as a single group of arc segments, and determining the arc and arc length of the single group of arc segments, and synchronously dividing the undetermined characteristic line into multiple micro arc segments based on the division determination method of the single group of arc segments, and the micro arc segments correspond to the single group of arc segments one by one:

[0017] Arc H based on a single set of arc segments i And the arc length L i , where i represents a different single group of arc segments, using R i =L i ÷H i Determine the radius value R associated with this arc segment i , the distance length R is generated at the two endpoints of this single set of arc segments i The two groups of related line segments are rotated in a related manner so that the other end points of the two groups of related line segments coincide with each other, the coincidence point is locked, and the coincidence point is marked as the center of the circle of this single group of arc segments;

[0018] S4), based on the micro-arc segments divided by the undetermined characteristic line, a reflection test is performed on each micro-arc segment, based on the single group of arc segments corresponding to the micro-arc segment and based on the relevant characteristics of the single group of arc segments, a reflection base surface is determined, based on the determined reflection base surface, a reflection angle is determined, and then based on the numerical difference between the incident angle and the reflection angle, whether there is diffuse reflection at this point is evaluated, and signal calibration is performed. The specific sub-steps are:

[0019] S41, starting from one end of the undetermined feature line and ending at the other end, a reflection test is performed on each group of points inside the undetermined feature line, and a group of irradiation lines are determined by using externally associated optical equipment, and the reflection lines are determined after the irradiation lines are irradiated to the relevant points;

[0020] S42, determine the micro-arc segment to which the relevant point belongs, determine the same point in the standard single group of arc segments, and based on the center of the single group of arc segments, construct the radius between the center and the same point, and then construct a group of base surfaces perpendicular to the radius and intersecting the same point, determine the angle J1 between the irradiation line and the base surface, and then determine the angle J2 between the reflection line and the base surface. If J1=J2, it means that the detection of this point is correct. If J1≠J2, it means that the detection of this point is wrong, indicating that there is diffuse reflection at this point, and then directly generate a lens surface scratch signal for relevant display;

[0021] S5), when the reflection test of the undetermined characteristic line is completed and there is no diffuse reflection, a refraction test is performed on several points inside the undetermined characteristic line to identify whether the difference between the incident angle and the refraction angle of the relevant light is consistent, and based on the identification result, it is determined whether there is an air bubble inside the abnormal area; the specific sub-steps are:

[0022] S51, starting from one end of the undetermined characteristic line and ending at the other end, a refraction test is performed on each group of points inside the undetermined characteristic line, and a group of irradiation lines are determined by using external related optical equipment, and the wavelength of the reference rays is adjusted until the irradiation lines can pass through the lens, and the refraction lines are determined after the irradiation lines irradiate the related points;

[0023] S52, determine the micro-arc segment to which the relevant points belong, and use the same method as step S42 to determine the base surface associated with the relevant points inside the corresponding micro-arc segment, determine the irradiation line and the generated refraction line, extend the irradiation line forward, determine a set of extended virtual lines, and determine the angle J between the refraction line and the extended virtual line. k , where k represents different relevant points within the undetermined feature line;

[0024] S53. After the refraction test of the undetermined characteristic line is completed, confirm the generated angles J k Are they all consistent? If they are consistent, a normal test signal is generated. If they are not consistent, an air bubble signal is generated, which means that there are air bubbles inside the abnormal area of ​​the lens, causing the density of the related area to change, thereby causing the angle of the refraction line to change abnormally.

[0025] The present invention provides a method for detecting surface defects of a lens. Compared with the prior art, the method has the following beneficial effects:

[0026] The present invention performs relevant confirmation of the abnormal area existing on the lens surface based on the relevant standard model, and after the abnormal area is confirmed, the longest characteristic line inside the abnormal area is identified based on the overall edge contour of the abnormal area, and then the characteristic line is mapped into the abnormal area, and a number of groups of related arcs associated with the characteristic line are determined based on the relevant model, and the related center of the circle is confirmed. This processing method can ensure that the detection result of the subsequent surface defect detection is the most accurate, and the best defect detection processing effect is achieved;

[0027] Subsequently, for the relevant processing of such abnormal areas, the irradiation line is preferentially reflected to determine the associated reflection angle, based on the specific comparison of the incident angle and the reflection angle, to determine whether the angle comparison is consistent. When the reflection test is normal, refraction analysis is performed to determine whether the refraction angle generated in each area is consistent, so as to assess whether there are relevant cracks and air bubbles and other defects inside the lens. The assessment and processing method is more comprehensive and accurate, and can achieve better assessment and processing detection effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the process of the present invention;

[0029] Figure 2It is a schematic diagram of the related processing of a single group of arc segments of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Example 1

[0032] See also Figure 1 The present application provides a method for detecting surface defects of a lens, comprising the following steps:

[0033] S1), using a designated machine vision device to acquire a high-definition image of the surface of the lens. This machine vision device is a high-definition camera acquisition device and a high-precision instrument. The device is selected in advance by relevant personnel, and the surface high-definition image is micro-processed to determine the image to be processed, and then combined with the relevant lens standard model, the image to be processed is compared with the lens standard model to determine the abnormal area. Specifically, the abnormal area is determined based on the comparison between the image to be processed and the relevant lens standard model, and the surface high-definition image and the lens standard model are relatedly divided, and based on the specific division results, the relevant area that can be compared is determined, and then based on the specific comparison results of the relevant area, the abnormal area is determined, wherein the specific method of determining the abnormal area is:

[0034] S11, based on the acquired surface high-definition image, the edge contour of the corresponding lens is determined based on the surface high-definition image, and then proportionally reduced based on the specific radiation range of the edge contour, the reduction ratio is Y1, where Y1 is a preset value, and the high-definition image contained in the reduced edge contour is calibrated as the image to be processed. First, it is not the image that is reduced, but the contour of the lens is reduced, that is, the outer edge of the lens is removed, and its specific value is determined by the operator based on experience. The reduction ratio is the ratio of the overall proportion after reduction to the original overall proportion, generally 95%, which is convenient for removing the associated area between the lens and the frame. Such areas do not need to undergo relevant analysis processes. Because the method of determining the edge contour of the lens based on the high-definition image of the lens is relatively common, it will not be described in detail here. Generally, the gradient of the image can be calculated using the Sobel operator, thereby highlighting the edge in the image; by applying the Sobel operator in the horizontal and vertical directions and superimposing the results of these two directions, more obvious edge information can be obtained; this method is suitable for capturing linear edges in images and is very useful for preliminarily determining the contour of the lens;

[0035] S12, overlay and compare the image to be processed and the corresponding lens standard model, wherein the lens standard model is a standard model of the lens of the corresponding model, and this standard model is also a model of the same size after the outline is proportionally reduced, and the edge area of ​​the original model is removed, which is prepared in advance by the relevant operator, based on the feature points inside the corresponding edge outlines of the image to be processed and the lens standard model, compare the image to be processed and the related areas at the same position inside the lens standard model, and identify whether the regional images of the related areas between the two are consistent. If they are consistent, the image to be processed is calibrated as the standard image. If there are inconsistent related areas, the corresponding related areas are calibrated as abnormal areas;

[0036] Specifically, after the correlation comparison between the image and the model, the corresponding relevant area at the same position can be determined. When the relevant area at the same position is compared, it can be determined whether the relevant area in the image to be processed is consistent with the relevant area corresponding to the lens standard model. If the comparison results are consistent when the two are compared, it means that there is no error. If the comparison results are inconsistent when the two are compared, it means that it is an abnormal area. If such abnormal area has related defects or related air bubbles, subsequent correlation analysis is required to determine whether the corresponding abnormal area is a defect or a corresponding air bubble.

[0037] S2), based on the determined abnormal area, identify the overall contour of the corresponding abnormal area, and then lock a set of feature processing lines based on the contour points of the overall contour, and horizontally map the feature processing lines on the surface of the abnormal area to determine the pending feature lines. Specifically, the pending feature line is the central axis of the overall contour, and there are several edge points on the outer edge of the overall contour. There are length segments between the edge points. When the length segment of the relevant edge point reaches the maximum, then the longest segment of this type belongs to the feature processing line. The specific method of determining the pending feature line is:

[0038] S21, based on the outer edge contour of the corresponding abnormal area, determine the overall contour of the abnormal area, determine the contour points on the overall contour in sequence, identify two groups of contour points with the farthest distance between two groups of straight lines from a number of contour points, and calibrate the straight line between the two groups of contour points as a feature processing line, whose contour is a corresponding line segment, and whose line segment is composed of a number of points, then there are related straight lines between adjacent points, and the straight line distances between each adjacent point are different, and determine a set of maximum distances from the straight line distances between the several adjacent points, so as to lock the longest straight line and calibrate it as a feature processing line;

[0039] S22, because the corresponding lens surface is a curvature area, the determined feature processing line is a straight line, and it is necessary to map the feature processing line to its abnormal area. Based on the determined feature processing line, the feature processing line is mapped to the surface of the abnormal area by vertical and horizontal mapping. The undetermined feature line after the feature processing line is mapped is confirmed on the surface of the abnormal area, and the undetermined feature line is calibrated on the surface of the abnormal area. Specifically, the feature processing line is a straight line between corresponding contour points, and such a straight line is definitely not located on the surface of the abnormal area. Then the subsequent detection process is for the surface of the abnormal area, so it is necessary to determine the relevant undetermined feature line on the surface of the abnormal area, and calibrate the undetermined feature line on the surface of the abnormal area;

[0040] S3), based on the undetermined feature line determined on the surface of the abnormal area, based on the specific relevant features of the undetermined feature line, the curvature feature of the undetermined feature line at the same position is locked from the standard lens model, and the undetermined feature line is divided into multiple micro-arc segments based on the corresponding curvature feature. Specifically, the undetermined feature line is located on the surface of the abnormal area, and the lens surface has a relevant curvature, then such feature line also belongs to a curvature line, but because it is unclear whether the undetermined feature line is a single group of curvature lines or composed of multiple groups of curvature lines, it is necessary to analyze and confirm the multiple groups of curvature lines, so as to divide the undetermined feature line into multiple micro-arc segments, wherein the specific sub-steps of division are:

[0041] S31, based on the specific position feature of the abnormal area in the original image to be processed, determining the relevant area on the surface of the standard lens model with the same position feature;

[0042] S32, based on the specific position features of the undetermined feature line determined inside the abnormal area, determine the related arc with the same position features in the related area, and use the related arc as the calibration arc of the undetermined feature line. Since the image to be compared and the model are restored in a 1:1 ratio during comparison, the same arc area can be determined according to the corresponding comparison process;

[0043] S33, identifying the relevant arcs existing in the calibration arc, calibrating some arc segments belonging to the same arc value as a single group of arc segments, and determining the arc and arc length of the single group of arc segments, and synchronously dividing the undetermined characteristic line into multiple micro arc segments based on the division determination method of the single group of arc segments, and the micro arc segments correspond to the single group of arc segments one by one:

[0044] Combination Figure 2 , based on the arc length H of a single set of arc segments i And the arc length L i , where i represents a different single group of arc segments, using R i =L i ÷H i Determine the radius value R associated with this arc segment i(Radian = arc length ÷ radius), the distance length R is generated at the two endpoints of this single set of arc segments i The related line segments of the two groups of related line segments are rotated in a related manner so that the other end points of the two groups of related line segments coincide with each other, and the coincidence point is locked. The coincidence point is marked as the center of the circle of this single group of arc segments. This arc segment exists, and the radius value is also confirmed. The line segments related to the radius value are determined at the two end points, and then the line segments are overlapped. The coincidence point of the two radius corresponding end points is the center of the circle of this arc segment. Subsequently, the reflection angle can be confirmed based on this center to identify whether the reflection angles are consistent.

[0045] S4), based on the micro-arc segments divided by the undetermined characteristic line, a reflection test is performed on each micro-arc segment, based on the single group of arc segments corresponding to the micro-arc segment and based on the relevant characteristics of the single group of arc segments, a reflection base surface is determined, based on the determined reflection base surface, a reflection angle is determined, and then based on the numerical difference between the incident angle and the reflection angle, whether there is diffuse reflection at this point is evaluated, and signal calibration is performed, wherein the specific sub-steps of the evaluation are:

[0046] S41, starting from one end of the undetermined feature line and ending at the other end, a reflection test is performed on each group of points inside the undetermined feature line, and a group of irradiation lines are determined by using externally associated optical equipment, and the reflection lines are determined after the irradiation lines are irradiated to the relevant points;

[0047] S42, Combination Figure 2 , determine the micro-arc segment to which the relevant points belong, determine the same points in the standard single group of arc segments, and based on the center of the single group of arc segments, construct the radius between the center of the circle and the same point, and then construct a set of base surfaces perpendicular to this radius and intersecting the same point, determine the angle J1 between the irradiation line and the base surface, and then determine the angle J2 between its reflection line and the base surface. If J1=J2, it means that the detection of this point is correct. If J1≠J2, it means that the detection of this point is incorrect, indicating that there is diffuse reflection at this point. Then directly generate the scratch signal on the surface of the lens for relevant display. The so-called diffuse reflection is different from the mirror reflection. , mirror reflection is smooth reflection, and its reflection angle can be determined based on the reference plane, but the mirror area related to diffuse reflection is a rough area. Only when there is a rough area will the light reflection be irregular, which means that there are scratches in the corresponding lens area, resulting in unevenness in such areas, which leads to diffuse reflection during reflection. Similarly, when confirming the angles of J1 and J2, the confirmed angles are in opposite directions, because the two are in a reflection state. If J1 determines the angle with the base surface downward, then J2 also determines the angle with the base surface downward.

[0048] S5), when the reflection test of the undetermined characteristic line is completed and there is no diffuse reflection, a refraction test is performed on several points inside the undetermined characteristic line to identify whether the difference between the incident angle and the refraction angle of the relevant light is consistent. Based on the identification result, it is determined whether there are air bubbles inside the abnormal area (if there are air bubbles, there will be relevant changes in density. If the density is different, the refraction angle of the same group of light will be different). The specific sub-steps of identification are:

[0049] S51, starting from one end of the undetermined characteristic line and ending at the other end, a refraction test is performed on each group of points inside the undetermined characteristic line, and a group of irradiation lines are determined by using external related optical equipment, and the wavelength of the reference rays is adjusted until the irradiation lines can pass through the lens, and the refraction lines are determined after the irradiation lines irradiate the related points;

[0050] S52, determine the micro-arc segment to which the relevant points belong, and use the same method as step S42 to determine the base surface associated with the relevant points inside the corresponding micro-arc segment, determine the irradiation line and the generated refraction line, extend the irradiation line forward, determine a set of extended virtual lines, and determine the angle J between the refraction line and the extended virtual line. k , where k represents different relevant points within the undetermined feature line;

[0051] S53. After the refraction test of the undetermined characteristic line is completed, confirm the generated angles J k Are they consistent? If they are consistent, a normal test signal is generated, which may be caused by dirt on the back of the lens, resulting in misjudgment of the abnormal area. If they are not consistent, an air bubble signal is generated, which means that there are air bubbles inside the abnormal area of ​​the lens, causing changes in the density of the related area, thereby causing abnormal changes in the angle of the refraction line;

[0052] Specifically, when air bubbles appear inside the lens, the corresponding density of the relevant area will change accordingly. In the area where the air bubbles appear, the volume of material used during generation remains unchanged. Because of the existence of air bubbles, the volume of material will be squeezed at the periphery, which will cause the density of the corresponding surrounding area to change accordingly. When performing refraction analysis on areas with inconsistent density, if the density of each area is consistent, the resulting refraction angle will not change accordingly. If the density of each area is not consistent, the corresponding refraction angle will be inconsistent, resulting in correlated changes in the refraction angle.

[0053] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0054] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for detecting surface defects of a lens, characterized in that: The following steps are involved: S1) Use the designated machine vision equipment to obtain the high-definition image of the surface of the lens, and after micro-processing the high-definition image of the surface, determine the image to be processed, and then combine the relevant lens standard model to compare the image to be processed with the lens standard model to determine the abnormal area. The specific method is as follows: S11, based on the acquired surface high-definition image, determine the edge profile of the corresponding lens based on the surface high-definition image, and then scale down the edge profile based on the specific radiation range, the scale-down ratio is Y1, where Y1 is a preset value, and calibrate the high-definition image contained in the scaled edge profile as the image to be processed; S12, performing an overlap comparison between the image to be processed and the corresponding lens standard model, wherein the lens standard model is a standard model of the lens of the corresponding model, and the standard model is also a model of the same size after the outline is proportionally reduced and segmented, based on the feature points inside the corresponding edge outlines of the image to be processed and the lens standard model, the image to be processed and the related areas at the same position inside the lens standard model are compared to identify whether the regional images of the related areas between the two are consistent, if they are consistent, the image to be processed is calibrated as the standard image, if there are inconsistent related areas, the corresponding related areas are calibrated as abnormal areas; S2) Based on the determined abnormal area, the overall contour of the corresponding abnormal area is identified, and then based on the contour points of the overall contour, a set of feature processing lines is locked, and the feature processing lines are horizontally mapped on the surface of the abnormal area to determine the undetermined feature lines. The specific method is as follows: S21, based on the outer edge contour of the corresponding abnormal area, determine the overall contour of the abnormal area, determine contour points on the overall contour in sequence, identify two groups of contour points with the farthest distance between two groups of straight lines from a plurality of contour points, and mark the straight line between the two groups of contour points as a feature processing line; S22, based on the determined feature processing line, using a vertical and horizontal mapping method, mapping the feature processing line to the surface of the abnormal region, confirming the undetermined feature line after the feature processing line is mapped on the surface of the abnormal region, and marking the undetermined feature line on the surface of the abnormal region; S3), based on the undetermined feature line determined in the surface of the abnormal area, based on the specific relevant features of the undetermined feature line, the curvature feature of the undetermined feature line at the same position is locked from the standard lens model, and based on the corresponding curvature feature, the undetermined feature line is divided into multiple micro-arc segments, and the specific sub-steps are: S31, based on the specific position feature of the abnormal area in the original image to be processed, determining the relevant area on the surface of the standard lens model with the same position feature; S32, based on the specific position features of the undetermined characteristic line determined inside the abnormal area, determine the related arc with the same position features in the related area, and use the related arc as the calibration arc of the undetermined characteristic line; S33, identifying the relevant arcs existing in the calibration arc, calibrating some arc segments belonging to the same arc value as a single group of arc segments, and determining the arc and arc length of the single group of arc segments, and synchronously dividing the undetermined characteristic line into multiple micro arc segments based on the division determination method of the single group of arc segments, and the micro arc segments correspond to the single group of arc segments one by one: Arc H based on a single set of arc segments i And the arc length L i , where i represents a different single group of arc segments, using R i =L i ÷H i Determine the radius value R associated with this arc segment i , the distance length R is generated at the two endpoints of this single set of arc segments i The two groups of related line segments are rotated in a related manner so that the other end points of the two groups of related line segments coincide with each other, the coincidence point is locked, and the coincidence point is marked as the center of the circle of this single group of arc segments; S4), based on the micro-arc segments divided by the undetermined characteristic line, a reflection test is performed on each micro-arc segment, based on the single group of arc segments corresponding to the micro-arc segment and based on the relevant characteristics of the single group of arc segments, a reflection base surface is determined, based on the determined reflection base surface, a reflection angle is determined, and then based on the numerical difference between the incident angle and the reflection angle, whether there is diffuse reflection at this point is evaluated, and signal calibration is performed. The specific sub-steps are: S41, starting from one end of the undetermined feature line and ending at the other end, a reflection test is performed on each group of points inside the undetermined feature line, and a group of irradiation lines are determined by using externally associated optical equipment, and the reflection lines are determined after the irradiation lines are irradiated to the relevant points; S42, determine the micro-arc segment to which the relevant point belongs, determine the same point in the standard single group of arc segments, and based on the center of the single group of arc segments, construct the radius between the center and the same point, and then construct a group of base surfaces perpendicular to the radius and intersecting the same point, determine the angle J1 between the irradiation line and the base surface, and then determine the angle J2 between the reflection line and the base surface. If J1=J2, it means that the detection of this point is correct. If J1≠J2, it means that the detection of this point is wrong, indicating that there is diffuse reflection at this point, and then directly generate a lens surface scratch signal for relevant display; S5), when the reflection test of the undetermined characteristic line is completed and there is no diffuse reflection, a refraction test is performed on several points inside the undetermined characteristic line to identify whether the difference between the incident angle and the refraction angle of the relevant light is consistent, and based on the identification result, it is determined whether there is an air bubble inside the abnormal area; the specific sub-steps are: S51, starting from one end of the undetermined characteristic line and ending at the other end, a refraction test is performed on each group of points inside the undetermined characteristic line, and a group of irradiation lines are determined by using external related optical equipment, and the wavelength of the reference rays is adjusted until the irradiation lines can pass through the lens, and the refraction lines are determined after the irradiation lines irradiate the related points; S52, determine the micro-arc segment to which the relevant points belong, and use the same method as step S42 to determine the base surface associated with the relevant points inside the corresponding micro-arc segment, determine the irradiation line and the generated refraction line, extend the irradiation line forward, determine a set of extended virtual lines, and determine the angle J between the refraction line and the extended virtual line. k , where k represents different relevant points within the undetermined feature line; S53. After the refraction test of the undetermined characteristic line is completed, confirm the generated angles J k Are they all consistent? If they are consistent, a normal test signal is generated. If they are not consistent, an air bubble signal is generated, which means that there are air bubbles inside the abnormal area of ​​the lens, causing the density of the related area to change, thereby causing the angle of the refraction line to change abnormally.

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