CN119756800A - Intelligent detection system adapted to optical lens - Google Patents
Intelligent detection system adapted to optical lens Download PDFInfo
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Abstract
本发明涉及光学镜头检测技术领域，尤其涉及适配于光学镜头的智能检测系统，包括光学镜头智检中心、光学数据库、初步外观测评分析单元、光检干扰量化分析单元、递进式透光测检单元、成像层次性测评单元以及测评反馈单元；本发明初步的从目标光学镜头的缺陷提取和外观图像两个点进行分析，以便初步的了解目标光学镜头是否存在缺陷和外观是否正常，以便提高目标光学镜头的检测效率，而通过信息反馈的方式进一步对目标光学镜头的检测干扰因素进行分析，以提高后续目标光学镜头检测结果的准确性，通过递进式的方式从光通量和成像图像两个角度对目标光学镜头性能进行检测，以提高目标光学镜头检测全面性。
The present invention relates to the field of optical lens detection technology, and in particular to an intelligent detection system adapted for optical lenses, comprising an optical lens intelligent detection center, an optical database, a preliminary external observation evaluation and analysis unit, an optical detection interference quantitative analysis unit, a progressive light transmission detection unit, an imaging hierarchical evaluation unit, and an evaluation feedback unit; the present invention preliminarily analyzes two points of defect extraction and appearance image of a target optical lens, so as to preliminarily understand whether the target optical lens has defects and whether the appearance is normal, so as to improve the detection efficiency of the target optical lens, and further analyzes the detection interference factors of the target optical lens by means of information feedback, so as to improve the accuracy of subsequent target optical lens detection results, and detects the performance of the target optical lens from two angles of luminous flux and imaging image in a progressive manner, so as to improve the comprehensiveness of the target optical lens detection.
Description
Technical Field
The invention relates to the technical field of optical lens detection, in particular to an intelligent detection system suitable for an optical lens.
Background
For devices such as video cameras, still cameras, and terminals with photographing functions, the mirror quality of their optical lenses has a significant effect on the quality of the imaged image. Therefore, in order to ensure the quality of the image photographed by the apparatus, the optical lens needs to be subjected to defect detection before being assembled to the apparatus, however, except that surface defects visible to the naked eye such as mirror abrasion, mirror contamination, etc. can be manually completed, the optical defects related to the optical lens are difficult to accurately identify by means of manual discrimination;
However, in the prior art, defect detection is performed in a single image comparison mode, so that the detection structure deviation is large, the data is not comprehensive enough, and detection cannot be performed from two angles of the light transmittance of the optical lens and the definition of an imaging image, so that the detection reliability of the optical lens is low and the detection is not comprehensive, and meanwhile, monitoring feedback adjustment cannot be performed on detection interference factors, so that the detection structure error is large, and the detection efficiency of the optical lens is reduced;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an intelligent detection system suitable for an optical lens, which is used for solving the technical defects, preliminarily analyzing two points of defect extraction and appearance images of the target optical lens so as to preliminarily know whether the target optical lens has defects and whether the appearance is normal or not, so as to improve the detection efficiency of the target optical lens, detecting the performance of the target optical lens from two angles of luminous flux and imaging images in a progressive manner so as to improve the detection comprehensiveness of the target optical lens, namely, carrying out regional luminous flux regulation evaluation analysis on the actual light transmittance, comparing and analyzing the luminous flux angle, intuitively knowing the light transmittance performance detection result of the target optical lens, carrying out information hierarchical processing feedback evaluation analysis on imaging background information, managing imaging characteristic image detection interference factors, and being beneficial to feeding back the detection result of the target optical lens from the side of imaging definition angle.
The intelligent detection system adapted to the optical lens comprises an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation analysis unit, a light detection interference quantitative analysis unit, a progressive light transmission detection unit, an imaging layering evaluation unit and an evaluation feedback unit;
the optical lens intelligent detection center is used for calling the appearance characteristic image of the target optical lens from the optical database and sending the appearance characteristic image to the preliminary appearance evaluation analysis unit;
the preliminary appearance evaluation analysis unit is used for carrying out defect feature extraction and appearance defect comparison analysis on the received appearance feature image, and carrying out discrimination processing on the obtained preliminary appearance deviation value to obtain a feedback instruction or a defect signal;
The light detection interference quantitative analysis unit is used for responding to the feedback instruction, collecting detection interference information of the target optical lens, carrying out evaluation interference level processing feedback analysis on the detection interference information, and carrying out discrimination processing on the obtained evaluation interference coefficient to obtain a normal signal or an interference signal;
The progressive light transmission testing unit is used for responding to the normal signal, collecting the actual light transmittance of the target optical lens, carrying out regional light transmission regulation and control testing analysis on the actual light transmittance, and carrying out discrimination processing on the obtained light transmission defect testing coefficient to obtain a qualified signal or an unqualified signal;
the imaging hierarchical evaluation unit is used for responding to the normal signal, collecting imaging background information of the target optical lens, carrying out information hierarchical processing feedback evaluation analysis on the imaging background information, and carrying out discriminant analysis on the obtained clear evaluation offset coefficient to obtain a clear signal or a fuzzy signal.
Preferably, the defect feature extraction and appearance defect control analysis process is as follows:
the method comprises the steps of collecting a detection period of a target optical lens, setting the detection period as a time threshold, obtaining an appearance characteristic image of the target optical lens in the time threshold, dividing the appearance characteristic image into m sub-area blocks, wherein m is a natural number larger than zero, carrying out defect information extraction on each sub-area block of the appearance characteristic image, wherein the defect information comprises bubbles and cracks, obtaining defect information of each sub-area block, carrying out discrimination processing on the defect information, generating progressive signals if the defect information does not exist, and generating display alarm signals if the defect information exists.
Preferably, when the progressive signal is generated, an appearance characteristic image of the normal optical lens is obtained, the appearance characteristic image of the normal optical lens is set as a standard appearance characteristic image, a difference value between the appearance characteristic image and the standard appearance characteristic image is obtained, the difference value between the appearance characteristic image and the standard appearance characteristic image is set as a preliminary appearance deviation value, and the preliminary appearance deviation value is subjected to discrimination processing to obtain a feedback instruction or a defect signal.
Preferably, the evaluation interference level processing feedback analysis process is as follows:
The method comprises the steps of obtaining detection interference information of a target optical lens in a time threshold, wherein the detection interference information comprises a clamping interference value and a light-passing interference value, comparing the clamping interference value and the light-passing interference value with a preset clamping interference value threshold and a preset light-passing interference value threshold, analyzing, setting the number of the clamping interference value and the light-passing interference value which is larger than or equal to the preset clamping interference value threshold and the preset light-passing interference value threshold as an evaluation interference coefficient, and judging the evaluation interference coefficient to obtain a normal signal or an interference signal.
Preferably, the clamping interference value represents an acute angle value formed by the inclination of the bottom surface of the target optical lens after the clamping is completed and the horizontal workbench, and the light flux interference value represents the number of the corresponding numerical values of the illumination information of the light detection assembly of the target optical lens exceeding the preset threshold, wherein the illumination information comprises the light source flickering frequency and the light source flickering times.
Preferably, the analysis process of the regional light flux control evaluation treatment is as follows:
dividing a target optical lens into i sub-area blocks, wherein i is a natural number larger than zero, acquiring the center point of each sub-area, detecting the light transmittance of the center point of each sub-area by controlling a light detection assembly, acquiring the standard light transmittance of the center point of each sub-area block of a normal optical lens, further acquiring the illumination luminous flux corresponding to the standard light transmittance of the center point of each sub-area block, and setting the illumination luminous flux as the standard illumination luminous flux;
The method comprises the steps of detecting light transmittance of center points of all sub-area blocks of a target optical lens through controlling a light detection assembly, obtaining actual light transmittance of the center points of all sub-area blocks, comparing and analyzing the actual light transmittance with standard light transmittance, adjusting illumination luminous flux of the light detection assembly if the actual light transmittance is not equal to the standard light transmittance, further obtaining actual illumination luminous flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance, setting a difference value between the actual illumination luminous flux and the standard illumination luminous flux as a light transmittance deviation coefficient, and processing the light transmittance deviation coefficient to obtain a standard signal or a deviation signal.
Preferably, the number of the sub-area blocks corresponding to the generated deviation signal is obtained, the number of the sub-area blocks corresponding to the generated deviation signal is set as a light transmission defect evaluation coefficient, and the light transmission defect evaluation coefficient is judged:
and if the light transmission defect evaluation coefficient is not equal to zero, generating a disqualification signal, and judging whether the signal is qualified or not.
Preferably, the information hierarchical processing feedback evaluation analysis process is as follows:
Based on an optical imaging principle, imaging background information of a target optical lens in a time threshold is obtained, the imaging background information comprises environment dust concentration and the number of interference light sources, the interference light sources represent light sources of a light detection assembly, the number corresponding to the imaging background information exceeding a preset threshold is obtained, the number corresponding to the imaging background information exceeding the preset threshold is set as an imaging interference coefficient, and the imaging interference coefficient is judged and processed to obtain an effective signal or an ineffective signal.
Preferably, when generating effective signals, acquiring imaging characteristic images of a target optical lens in a time threshold, carrying out g sub-region blocks on the imaging characteristic images, wherein g is a natural number larger than zero, acquiring RGB values of each pixel grid in each sub-region block of the imaging characteristic images, further acquiring the maximum value and the minimum value in the RGB values of the pixel grids in each sub-region block, and setting the maximum value and the minimum value as Smax and Smin respectively;
Meanwhile, constructing RGB value intervals A [ Smin, smax ] in each sub-area block according to Smax and Smin of each sub-area block to obtain RGB value intervals B [ ZSMin, ZSMax ] of each sub-area block of a normal optical lens, comparing and analyzing the intervals A [ Smin, smax ] and B [ ZSMin, ZSMax ] to obtain values obtained by subtracting ZSmax of the interval B from Smax of each sub-area block interval A and ZSmin of subtracting the interval B from Smin of the interval A, setting the values as peak section deviation values and valley Duan Pian difference values respectively, and carrying out discriminant analysis on the peak section deviation values and the valley section deviation values to obtain a normal area and an abnormal area;
the number of the abnormal areas is obtained, the number of the abnormal areas is set to be a clear evaluation offset coefficient, and the clear evaluation offset coefficient is subjected to discriminant analysis to obtain a clear signal or a fuzzy signal.
The beneficial effects of the invention are as follows:
(1) The invention primarily analyzes two points of defect extraction and appearance images of the target optical lens so as to primarily know whether the target optical lens has defects and has normal appearance or not so as to improve the detection efficiency of the target optical lens, and further analyzes the detection interference factors of the target optical lens in an information feedback mode, namely carries out evaluation interference level processing feedback analysis on the detection interference information so as to adjust the detection interference factors of the target optical lens according to display characters so as to improve the accuracy of the detection results of the subsequent target optical lens;
(2) According to the invention, the performance of the target optical lens is detected from two angles of luminous flux and imaging images in a progressive manner, so that the detection comprehensiveness of the target optical lens is improved, namely, the actual light transmittance is subjected to regional light transmittance regulation and control evaluation analysis, so that the light transmittance performance detection result of the target optical lens is compared and analyzed from the luminous flux angle, the imaging background information is subjected to information hierarchical processing feedback evaluation analysis, the imaging characteristic image detection interference factor is managed on one hand, and the detection result of the target optical lens is fed back from the imaging definition angle side face on the other hand.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a flow chart of the system of the present invention;
Fig. 2 is a partial analysis reference diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
Referring to fig. 1 to 2, the intelligent detection system adapted to an optical lens of the present invention includes an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation analysis unit, a light detection interference quantitative analysis unit, a progressive light transmission evaluation unit, an imaging layering evaluation unit and an evaluation feedback unit, wherein the optical database is in unidirectional communication with the optical lens intelligent detection center, the optical lens intelligent detection center is in unidirectional communication with the preliminary appearance evaluation analysis unit, the preliminary appearance evaluation analysis unit is in unidirectional communication with the light detection interference quantitative analysis unit and the evaluation feedback unit, the light detection interference quantitative analysis unit is in unidirectional communication with the progressive light transmission evaluation unit, the imaging layering evaluation unit and the evaluation feedback unit, and the progressive light transmission evaluation unit and the imaging layering evaluation unit are in unidirectional communication with the evaluation feedback unit;
the optical lens intelligent detection center is used for calling the appearance characteristic image of the target optical lens from the optical database and sending the appearance characteristic image to the preliminary appearance evaluation analysis unit;
the preliminary appearance evaluation analysis unit is used for carrying out defect feature extraction and appearance defect comparison analysis on the received appearance feature image so as to preliminarily know whether the target optical lens has defects and whether the appearance is normal or not, so that the detection efficiency of the target optical lens is improved, and the specific defect feature extraction and appearance defect comparison analysis process is as follows:
Acquiring a detection period of a target optical lens, setting the detection period as a time threshold, acquiring an appearance characteristic image of the target optical lens within the time threshold, dividing the appearance characteristic image into m sub-area blocks, wherein m is a natural number larger than zero, carrying out defect information extraction on each sub-area block of the appearance characteristic image, wherein the defect information comprises bubbles, cracks and the like, acquiring the defect information of each sub-area block, carrying out discrimination processing on the defect information, generating progressive signals if the defect information does not exist, generating display alarm signals if the defect information exists, sending the display alarm signals to an evaluation feedback unit, and immediately making preset early warning characters corresponding to the display alarm signals after the evaluation feedback unit receives the display alarm signals so as to primarily know whether the target optical lens has defects or not, so that the detection efficiency of the target optical lens is improved;
When a progressive signal is generated, an appearance characteristic image of a normal optical lens is obtained, the appearance characteristic image of the normal optical lens is set as a standard appearance characteristic image, a difference value between the appearance characteristic image and the standard appearance characteristic image is obtained, the difference value between the appearance characteristic image and the standard appearance characteristic image is set as a preliminary appearance deviation value, and the preliminary appearance deviation value is judged:
if the preliminary appearance deviation value is smaller than a preset preliminary appearance deviation value threshold value, generating a feedback instruction;
If the preliminary appearance deviation value is greater than or equal to a preset preliminary appearance deviation value threshold value, generating a defect signal, sending a feedback instruction or the defect signal to an evaluation feedback unit, and immediately displaying preset early warning characters corresponding to the feedback instruction or the defect signal after the evaluation feedback unit receives the feedback instruction or the defect signal, so that the appearance detection result of the target optical lens can be intuitively known;
When a feedback instruction is generated, the light detection interference quantitative analysis unit is used for responding to the feedback instruction, collecting detection interference information of the target optical lens, and performing evaluation interference level processing feedback analysis on the detection interference information so as to adjust detection interference factors of the target optical lens according to display characters, so that accuracy of detection results of the subsequent target optical lens is improved, and the specific evaluation interference level processing feedback analysis process is as follows:
The method comprises the steps of obtaining detection interference information of a target optical lens in a time threshold, wherein the detection interference information comprises a clamping interference value and a light-passing interference value, comparing the clamping interference value and the light-passing interference value with a preset clamping interference value threshold and a preset light-passing interference value threshold, analyzing, setting the number of the clamping interference value and the light-passing interference value which is larger than or equal to the preset clamping interference value threshold and the preset light-passing interference value threshold as an evaluation interference coefficient, and judging the evaluation interference coefficient:
If the evaluation interference coefficient=0, generating a normal signal;
If the evaluation interference coefficient=1 or if the evaluation interference coefficient=2, generating an interference signal, and transmitting a normal signal or the interference signal to an evaluation feedback unit, wherein the evaluation feedback unit immediately displays preset early warning characters corresponding to the normal signal or the interference signal after receiving the normal signal or the interference signal so as to adjust the detection interference factors of the target optical lens according to the displayed characters, thereby improving the accuracy of the detection result of the subsequent target optical lens;
in the embodiment of the invention, the clamping interference value represents an acute angle value formed by the inclination of the bottom surface of the clamped target optical lens and the horizontal workbench, and the larger the clamping interference value is, the larger the interference of the clamping of the target optical lens to the subsequent detection is, and the larger the reliability abnormal risk of the detection result is;
In the embodiment of the invention, the light flux interference value represents the number of the corresponding values of the illumination information of the light detection assembly of the target optical lens exceeding the preset threshold value, the illumination information comprises the light source flicker frequency, the light source flicker frequency and the like, and it is to be noted that the light flux interference value is an influence parameter reflecting the interference of the light source on the detection of the target optical lens, and the larger the value of the light flux interference value is, the larger the detection error risk of the target optical lens is;
In the embodiment of the invention, the light detection component represents a light detection light source.
Embodiment two:
When a normal signal is generated, the progressive light transmittance detection unit is used for responding to the normal signal, collecting the actual light transmittance of the target optical lens, and carrying out regional light transmittance regulation and control evaluation analysis on the actual light transmittance so as to compare and analyze from the light flux angle, intuitively know the light transmittance performance detection result of the target optical lens, and further help to deeply detect the light transmittance performance of the target optical lens, wherein the specific regional light transmittance regulation and control evaluation analysis process is as follows:
In the embodiment of the invention, the light transmittance of the target optical lens is detected by controlling the light detection assembly;
dividing a target optical lens into i sub-area blocks, wherein i is a natural number larger than zero, acquiring the center point of each sub-area, detecting the light transmittance of the center point of each sub-area by controlling a light detection assembly, acquiring the standard light transmittance of the center point of each sub-area block of a normal optical lens, further acquiring the illumination luminous flux corresponding to the standard light transmittance of the center point of each sub-area block, and setting the illumination luminous flux as the standard illumination luminous flux;
The method comprises the steps of detecting light transmittance of center points of all sub-area blocks of a target optical lens by controlling a light detection assembly, obtaining actual light transmittance of the center points of all sub-area blocks, comparing the actual light transmittance with standard light transmittance, adjusting illumination light flux of the light detection assembly if the actual light transmittance is not equal to the standard light transmittance, further obtaining actual illumination light flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance, setting a difference value between the actual illumination light flux and the standard illumination light flux as a light transmittance deviation coefficient, and processing the light transmittance deviation coefficient:
if the light transmission deviation coefficient belongs to the preset light transmission deviation coefficient range, generating a standard signal;
If the light transmission deviation coefficient does not belong to the preset light transmission deviation coefficient range, a deviation signal is generated;
The number of the sub-area blocks corresponding to the generated deviation signals is obtained, the number of the sub-area blocks corresponding to the generated deviation signals is set as a light transmission defect evaluation coefficient, and the light transmission defect evaluation coefficient is judged and processed:
if the light transmission defect evaluation coefficient is equal to zero, generating a qualified signal;
If the light transmission defect evaluation coefficient is not equal to zero, generating an unqualified signal, and sending the qualified signal or the unqualified signal to an evaluation feedback unit, wherein the evaluation feedback unit immediately displays preset early warning characters corresponding to the qualified signal or the unqualified signal after receiving the qualified signal or the unqualified signal so as to intuitively know the light transmission performance detection result of the target optical lens;
When a normal signal is generated, the imaging hierarchical evaluation unit is used for responding to the normal signal, collecting imaging background information of the target optical lens, and carrying out information hierarchical processing feedback evaluation analysis on the imaging background information, wherein the imaging hierarchical processing feedback evaluation analysis is used for managing imaging characteristic image detection interference factors on one hand and helping to feed back detection results of the target optical lens from the imaging definition angle side face on the other hand, and the specific information hierarchical processing feedback evaluation analysis process is as follows:
Based on an optical imaging principle, imaging background information of a target optical lens in a time threshold is obtained, the imaging background information comprises environment dust concentration, the number of interference light sources and the like, the interference light sources represent light sources of the light detection assembly, the number corresponding to the imaging background information, corresponding to the number exceeding a preset threshold, is obtained, the number corresponding to the imaging background information, corresponding to the number exceeding the preset threshold, is set as an imaging interference coefficient, and the imaging interference coefficient is judged and processed:
If the imaging interference coefficient is equal to zero, generating an effective signal;
if the imaging interference coefficient is not equal to zero, generating an invalid signal, sending the invalid signal to an evaluation feedback unit, and immediately displaying preset early warning characters corresponding to the invalid signal after the evaluation feedback unit receives the invalid signal, so as to manage imaging characteristic image detection interference factors in time and improve the detection precision of subsequent imaging characteristic images;
When a valid signal is generated:
Acquiring imaging characteristic images of a target optical lens in a time threshold, carrying out g sub-area blocks on the imaging characteristic images, wherein g is a natural number larger than zero, acquiring RGB values of each pixel grid in each sub-area block of the imaging characteristic images, further acquiring maximum values and minimum values of the RGB values of the pixel grids in each sub-area block, and setting the maximum values and the minimum values of the RGB values of the pixel grids in each sub-area block as Smax and Smin respectively;
Meanwhile, constructing RGB value intervals A [ Smin, smax ] in each sub-area block according to Smax and Smin of each sub-area block, obtaining RGB value intervals B [ ZSMin, ZSMax ] of each sub-area block of a normal optical lens, comparing and analyzing the intervals A [ Smin, smax ] and B [ ZSMin, ZSMax ], obtaining a value obtained by subtracting ZSmax of the interval B from Smax of each sub-area block interval A and a value obtained by subtracting ZSmin of the interval B from Smin of the interval A, setting the values as peak section deviation values and valley Duan Pian difference values respectively, and carrying out discriminant analysis on the peak section deviation values and the valley section deviation values:
if the peak section deviation value belongs to a preset peak section deviation value range and the valley Duan Piancha value belongs to a preset valley section deviation value range, judging that the corresponding sub-area block is a normal area;
If the peak section deviation value does not belong to the preset peak section deviation value range or the valley section deviation value belongs to the preset valley section deviation value range, judging that the corresponding sub-region block is an abnormal region;
the number of the abnormal areas is obtained, the number of the abnormal areas is set as a clear evaluation offset coefficient, and discrimination analysis is carried out on the clear evaluation offset coefficient:
if the clear evaluation offset coefficient is equal to zero, a clear signal is generated;
If the clear evaluation offset coefficient is not equal to zero, generating a fuzzy signal, sending the clear signal or the fuzzy signal to an evaluation feedback unit, and immediately displaying preset early warning characters corresponding to the clear signal or the fuzzy signal after the evaluation feedback unit receives the clear signal or the fuzzy signal, so as to feed back a detection result of the target optical lens from the imaging definition angle side of the target optical lens, and detecting through the light transmittance and the imaging two angles of the target optical lens at the same time, so that the detection comprehensiveness of the target optical lens is improved;
In summary, the method and the device primarily analyze two points of the defect extraction and the appearance image of the target optical lens so as to primarily know whether the defect and the appearance of the target optical lens are normal or not, so as to improve the detection efficiency of the target optical lens, and further analyze the detection interference factor of the target optical lens in an information feedback mode, namely perform evaluation interference level processing feedback analysis on the detection interference information, so as to adjust the detection interference factor of the target optical lens according to the display text, and improve the accuracy of the detection result of the subsequent target optical lens;
The performance of the target optical lens is detected from two angles of luminous flux and imaging images in a progressive mode, so that the detection comprehensiveness of the target optical lens is improved, namely, regional light flux regulation and control evaluation analysis is conducted on actual light transmittance, so that the light transmittance performance detection result of the target optical lens is compared and analyzed from the luminous flux angle, the information hierarchical processing feedback evaluation analysis is conducted on imaging background information, the imaging characteristic image detection interference factors are managed on one hand, and the detection result of the target optical lens is fed back from the imaging definition angle side face on the other hand.
The size of the threshold is set for convenience of comparison, and depends on the number of sample data and the number of cardinalities set for each group of sample data by a person skilled in the art, so long as the proportional relationship between the parameter and the quantized value is not affected.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (9)
1. The intelligent detection system is suitable for the optical lens and is characterized by comprising an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation analysis unit, a light detection interference quantitative analysis unit, a progressive light transmission detection unit, an imaging layering evaluation unit and an evaluation feedback unit;
the optical lens intelligent detection center is used for calling the appearance characteristic image of the target optical lens from the optical database and sending the appearance characteristic image to the preliminary appearance evaluation analysis unit;
the preliminary appearance evaluation analysis unit is used for carrying out defect feature extraction and appearance defect comparison analysis on the received appearance feature image, and carrying out discrimination processing on the obtained preliminary appearance deviation value to obtain a feedback instruction or a defect signal;
The light detection interference quantitative analysis unit is used for responding to the feedback instruction, collecting detection interference information of the target optical lens, carrying out evaluation interference level processing feedback analysis on the detection interference information, and carrying out discrimination processing on the obtained evaluation interference coefficient to obtain a normal signal or an interference signal;
The progressive light transmission testing unit is used for responding to the normal signal, collecting the actual light transmittance of the target optical lens, carrying out regional light transmission regulation and control testing analysis on the actual light transmittance, and carrying out discrimination processing on the obtained light transmission defect testing coefficient to obtain a qualified signal or an unqualified signal;
the imaging hierarchical evaluation unit is used for responding to the normal signal, collecting imaging background information of the target optical lens, carrying out information hierarchical processing feedback evaluation analysis on the imaging background information, and carrying out discriminant analysis on the obtained clear evaluation offset coefficient to obtain a clear signal or a fuzzy signal.
2. The intelligent inspection system for an optical lens of claim 1, wherein the defect feature extraction and appearance defect contrast analysis process is as follows:
the method comprises the steps of collecting a detection period of a target optical lens, setting the detection period as a time threshold, obtaining an appearance characteristic image of the target optical lens in the time threshold, dividing the appearance characteristic image into m sub-area blocks, wherein m is a natural number larger than zero, carrying out defect information extraction on each sub-area block of the appearance characteristic image, wherein the defect information comprises bubbles and cracks, obtaining defect information of each sub-area block, carrying out discrimination processing on the defect information, generating progressive signals if the defect information does not exist, and generating display alarm signals if the defect information exists.
3. The intelligent detection system for an optical lens according to claim 2, wherein when generating a progressive signal, an appearance characteristic image of a normal optical lens is obtained, the appearance characteristic image of the normal optical lens is set as a standard appearance characteristic image, a difference value between the appearance characteristic image and the standard appearance characteristic image is obtained, the difference value between the appearance characteristic image and the standard appearance characteristic image is set as a preliminary appearance deviation value, and the preliminary appearance deviation value is subjected to discrimination processing to obtain a feedback instruction or a defect signal.
4. The intelligent detection system adapted to an optical lens according to claim 1, wherein the evaluation interference level processing feedback analysis process is as follows:
The method comprises the steps of obtaining detection interference information of a target optical lens in a time threshold, wherein the detection interference information comprises a clamping interference value and a light-passing interference value, comparing the clamping interference value and the light-passing interference value with a preset clamping interference value threshold and a preset light-passing interference value threshold, analyzing, setting the number of the clamping interference value and the light-passing interference value which is larger than or equal to the preset clamping interference value threshold and the preset light-passing interference value threshold as an evaluation interference coefficient, and judging the evaluation interference coefficient to obtain a normal signal or an interference signal.
5. The intelligent detection system adapted to the optical lens according to claim 3, wherein the clamping interference value indicates an acute angle value formed by inclination of the bottom surface of the target optical lens after clamping and the horizontal workbench, the light flux interference value indicates the number of corresponding values of illumination information of a light detection assembly of the target optical lens exceeding a preset threshold, and the illumination information includes a light source flicker frequency and a light source flicker frequency.
6. The intelligent detection system adapted to an optical lens according to claim 1, wherein the analysis process of the regional light flux control evaluation process is as follows:
dividing a target optical lens into i sub-area blocks, wherein i is a natural number larger than zero, acquiring the center point of each sub-area, detecting the light transmittance of the center point of each sub-area by controlling a light detection assembly, acquiring the standard light transmittance of the center point of each sub-area block of a normal optical lens, further acquiring the illumination luminous flux corresponding to the standard light transmittance of the center point of each sub-area block, and setting the illumination luminous flux as the standard illumination luminous flux;
The method comprises the steps of detecting light transmittance of center points of all sub-area blocks of a target optical lens through controlling a light detection assembly, obtaining actual light transmittance of the center points of all sub-area blocks, comparing and analyzing the actual light transmittance with standard light transmittance, adjusting illumination luminous flux of the light detection assembly if the actual light transmittance is not equal to the standard light transmittance, further obtaining actual illumination luminous flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance, setting a difference value between the actual illumination luminous flux and the standard illumination luminous flux as a light transmittance deviation coefficient, and processing the light transmittance deviation coefficient to obtain a standard signal or a deviation signal.
7. The intelligent detection system according to claim 6, wherein the number of sub-area blocks corresponding to the generated deviation signal is obtained, the number of sub-area blocks corresponding to the generated deviation signal is set as a light transmission defect evaluation coefficient, and the light transmission defect evaluation coefficient is subjected to a discrimination process:
and if the light transmission defect evaluation coefficient is not equal to zero, generating a disqualification signal, and judging whether the signal is qualified or not.
8. The intelligent detection system adapted to an optical lens according to claim 1, wherein the information hierarchy process feedback evaluation analysis process is as follows:
Based on an optical imaging principle, imaging background information of a target optical lens in a time threshold is obtained, the imaging background information comprises environment dust concentration and the number of interference light sources, the interference light sources represent light sources of a light detection assembly, the number corresponding to the imaging background information exceeding a preset threshold is obtained, the number corresponding to the imaging background information exceeding the preset threshold is set as an imaging interference coefficient, and the imaging interference coefficient is judged and processed to obtain an effective signal or an ineffective signal.
9. The intelligent detection system adapted to an optical lens according to claim 8, wherein when generating an effective signal, acquiring an imaging feature image of a target optical lens within a time threshold, performing g sub-region blocks on the imaging feature image, wherein g is a natural number greater than zero, acquiring RGB values of each pixel grid in each sub-region block of the imaging feature image, further acquiring a maximum value and a minimum value in the RGB values of the pixel grids in each sub-region block, and setting the maximum value and the minimum value as Smax and Smin respectively;
Meanwhile, constructing RGB value intervals A [ Smin, smax ] in each sub-area block according to Smax and Smin of each sub-area block to obtain RGB value intervals B [ ZSMin, ZSMax ] of each sub-area block of a normal optical lens, comparing and analyzing the intervals A [ Smin, smax ] and B [ ZSMin, ZSMax ] to obtain values obtained by subtracting ZSmax of the interval B from Smax of each sub-area block interval A and ZSmin of subtracting the interval B from Smin of the interval A, setting the values as peak section deviation values and valley Duan Pian difference values respectively, and carrying out discriminant analysis on the peak section deviation values and the valley section deviation values to obtain a normal area and an abnormal area;
the number of the abnormal areas is obtained, the number of the abnormal areas is set to be a clear evaluation offset coefficient, and the clear evaluation offset coefficient is subjected to discriminant analysis to obtain a clear signal or a fuzzy signal.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119972541A (en) * | 2025-04-14 | 2025-05-13 | 福建优恩立光电科技有限公司 | Industrial inspection system based on SWIR 6mm lens based on neural network |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1248092A2 (en) * | 2001-03-09 | 2002-10-09 | Novartis AG | Lens inspection |
| CN117232792A (en) * | 2023-11-14 | 2023-12-15 | 南京木木西里科技有限公司 | Microscope defect detection system based on image information |
| CN117686514A (en) * | 2023-12-06 | 2024-03-12 | 江西超联光电科技有限公司 | Zxfoom precision and precision zxfoom precision and precision Defect detection method of |
| CN117929393A (en) * | 2024-03-21 | 2024-04-26 | 广东金鼎光学技术股份有限公司 | Lens defect detection method, system, processor and storage medium |
| CN119125167A (en) * | 2024-11-04 | 2024-12-13 | 常州市常英机械有限公司 | A photovoltaic aluminum frame surface defect detection system |
-
2024
- 2024-12-26 CN CN202411940095.5A patent/CN119756800B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1248092A2 (en) * | 2001-03-09 | 2002-10-09 | Novartis AG | Lens inspection |
| CN117232792A (en) * | 2023-11-14 | 2023-12-15 | 南京木木西里科技有限公司 | Microscope defect detection system based on image information |
| CN117686514A (en) * | 2023-12-06 | 2024-03-12 | 江西超联光电科技有限公司 | Zxfoom precision and precision zxfoom precision and precision Defect detection method of |
| CN117929393A (en) * | 2024-03-21 | 2024-04-26 | 广东金鼎光学技术股份有限公司 | Lens defect detection method, system, processor and storage medium |
| CN119125167A (en) * | 2024-11-04 | 2024-12-13 | 常州市常英机械有限公司 | A photovoltaic aluminum frame surface defect detection system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119972541A (en) * | 2025-04-14 | 2025-05-13 | 福建优恩立光电科技有限公司 | Industrial inspection system based on SWIR 6mm lens based on neural network |
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