Intelligent Detection System Adapted to Optical Lenses

Abstract

The present invention relates to the technical field of optical lens detection, and particularly to an intelligent detection system adapted to an optical lens, including an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation and analysis unit, a light detection interference quantification and analysis unit, a progressive light transmission detection unit, an imaging hierarchy evaluation unit, and an evaluation feedback unit; The present invention initially analyzes from two points, namely, defect extraction and appearance image of the target optical lens, in order to initially understand whether there are defects in the target optical lens and whether the appearance is normal, so as to improve the detection efficiency of the target optical lens. And by means of information feedback, the detection interference factors of the target optical lens are further analyzed to improve the accuracy of the subsequent detection results of the target optical lens. The performance of the target optical lens is detected from two angles of luminous flux and imaging image in a progressive manner to improve the comprehensiveness of the detection of the target optical lens.

Description

Technical Field

[0001] The present invention relates to the technical field of optical lens detection, and particularly to an intelligent detection system adapted to an optical lens. Background Art

[0002] For devices such as cameras, cameras, and terminals with a shooting function, the mirror surface quality of their optical lenses has a significant impact on the image quality obtained by imaging. Therefore, in order to ensure the image quality captured by the device, before the optical lens is assembled into the device, defect detection needs to be carried out. However, except for surface defects visible to the naked eye such as mirror surface wear and mirror surface contamination, which can be completed manually, it is difficult to accurately identify the optical defects involving the optical lens through manual screening;

[0003] However, in the prior art, defect detection is carried out by means of single image comparison, resulting in large deviations in the detection results, incomplete data, and the inability to detect from the two angles of the light transmittance and the clarity of the imaging image. Furthermore, it leads to low credibility and incomplete detection of the optical lens, and at the same time, it is unable to monitor and feedback-adjust the detection interference factors, thereby resulting in large errors in the detection results and reducing the detection efficiency of the optical lens;

[0004] In view of the above technical defects, a solution is proposed herein. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent detection system adapted to an optical lens to solve the above-mentioned technical defects. The present invention initially analyzes from two points: defect extraction and appearance image of the target optical lens, so as to preliminarily understand whether there are defects in the target optical lens and whether the appearance is normal, so as to improve the detection efficiency of the target optical lens. The performance of the target optical lens is detected from two angles of light flux and imaging image in a progressive manner to improve the comprehensiveness of the target optical lens detection, that is, the regional light flux regulation evaluation and analysis of the actual light transmittance are carried out to conduct comparison and analysis from the angle of light flux, and the detection result of the light transmittance performance of the target optical lens can be intuitively understood. The imaging background information is processed and feedback evaluated hierarchically. On the one hand, the detection interference factors of the imaging feature image are managed, and on the other hand, it helps to feedback the detection result of the target optical lens from the side of the imaging clarity angle.

[0006] The purpose of the present invention can be achieved by the following technical solutions: an intelligent detection system adapted to an optical lens, including an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation and analysis unit, a light detection interference quantification analysis unit, a progressive light transmittance detection unit, an imaging hierarchical evaluation unit, and an evaluation feedback unit;

[0007] The optical lens intelligent inspection center is used to retrieve the appearance feature image of the target optical lens from the optical database and send the appearance feature image to the preliminary appearance evaluation and analysis unit;

[0008] The preliminary appearance evaluation and analysis unit is used to extract defect features and conduct appearance defect comparison analysis on the received appearance feature image, judge and process the obtained preliminary appearance deviation value, and obtain a feedback instruction or a defect signal;

[0009] The optical inspection interference quantification analysis unit is used to respond to the feedback instruction, collect the detection interference information of the target optical lens at the same time, conduct evaluation interference magnitude processing feedback analysis on the detection interference information, judge and process the obtained evaluation interference coefficient, and obtain a normal signal or an interference signal;

[0010] The progressive light transmission detection unit is used to respond to the normal signal, collect the actual light transmittance of the target optical lens at the same time, conduct regional light flux regulation evaluation processing analysis on the actual light transmittance, judge and process the obtained light transmission defect evaluation coefficient, and obtain a qualified signal or an unqualified signal;

[0011] The imaging hierarchy evaluation unit is used to respond to the normal signal, collect the imaging background information of the target optical lens at the same time, conduct information hierarchy processing feedback evaluation analysis on the imaging background information, judge and analyze the obtained clear evaluation deviation coefficient, and obtain a clear signal or a fuzzy signal.

[0012] Preferably, the defect feature extraction and appearance defect comparison analysis process is as follows:

[0013] Collect the detection period of the target optical lens and set it as the time threshold. Obtain the appearance feature image of the target optical lens within the time threshold, divide the appearance feature image into m sub-region blocks, where m is a natural number greater than zero. Extract defect information from each sub-region block of the appearance feature image. The defect information includes bubbles and cracks. Obtain the defect information of each sub-region block and conduct judgment processing on the defect information. If there is no defect information, generate a progressive signal. If there is defect information, generate a display warning signal.

[0014] Preferably, when generating a progressive signal, obtain the appearance feature image of a normal optical lens, set the appearance feature image of the normal optical lens as the standard appearance feature image, obtain the difference value between the appearance feature image and the standard appearance feature image, and set the difference value between the appearance feature image and the standard appearance feature image as the preliminary appearance deviation value, and conduct judgment processing on the preliminary appearance deviation value to obtain a feedback instruction or a defect signal.

[0015] Preferably, the evaluation interference magnitude processing feedback analysis process is as follows:

[0016] Obtain the detection interference information of the target optical lens within the time threshold. The detection interference information includes the clamping interference value and the light passing interference value. Compare and analyze the clamping interference value and the light passing interference value with the preset clamping interference value threshold and the preset light passing interference value threshold. Set the number of the clamping interference value and the light passing interference value that is greater than or equal to the preset clamping interference value threshold and the preset light passing interference value threshold as the evaluation interference coefficient, and perform discrimination processing on the evaluation interference coefficient to obtain a normal signal or an interference signal.

[0017] Preferably, the clamping interference value represents the acute angle value formed by the inclination of the bottom surface of the target optical lens after clamping with the horizontal workbench; the light passing interference value represents the number of corresponding values of the illumination information of the light detection component of the target optical lens exceeding the preset threshold. The illumination information includes the light source flashing frequency and the light source flashing times.

[0018] Preferably, the area-type light passing regulation evaluation and processing analysis process is as follows:

[0019] Divide the target optical lens into i sub-region blocks, where i is a natural number greater than zero. Obtain the center points of each sub-region. Detect the light transmittance of the center points of each sub-region by controlling the light detection component. Obtain the standard light transmittance of the center points of each sub-region block of the normal optical lens, and then obtain the corresponding illumination light flux of the standard light transmittance of the center points of each sub-region block, and set it as the standard illumination light flux;

[0020] Detect the light transmittance of the center points of each sub-region block of the target optical lens by controlling the light detection component. Obtain the actual light transmittance of the center points of each sub-region block. Compare and analyze the actual light transmittance with the standard light transmittance. If the actual light transmittance is not equal to the standard light transmittance, adjust the illumination light flux of the light detection component, and then obtain the actual illumination light flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance. Set the difference between the actual illumination light flux and the standard illumination light flux as the light transmittance deviation coefficient, and perform processing on the light transmittance deviation coefficient to obtain a standard signal or a deviation signal.

[0021] Preferably, obtain the number of sub-region blocks corresponding to the generated deviation signal, and set the number of sub-region blocks corresponding to the generated deviation signal as the light transmittance defect evaluation coefficient, and perform discrimination processing on the light transmittance defect evaluation coefficient:

[0022] If the light transmittance defect evaluation coefficient is equal to zero, generate a qualified signal; if the light transmittance defect evaluation coefficient is not equal to zero, generate an unqualified signal, and output the qualified signal or the unqualified signal.

[0023] Preferably, the information hierarchical processing feedback evaluation analysis process is as follows:

[0024] Based on the principle of optical imaging, the imaging background information of the target optical lens within the time threshold is obtained. The imaging background information includes the ambient dust concentration and the number of interfering light sources. The interfering light sources refer to the light sources excluding the optical detection components. The number corresponding to the imaging background information whose value exceeds the preset threshold is obtained, and the number corresponding to the imaging background information whose value exceeds the preset threshold is set as the imaging interference coefficient, and the imaging interference coefficient is discriminated to obtain a valid signal or an invalid signal.

[0025] Preferably, when a valid signal is generated: the imaging feature image of the target optical lens within the time threshold is obtained, the imaging feature image is divided into g sub-region blocks, where g is a natural number greater than zero. The RGB values of each pixel grid in each sub-region block of the imaging feature image are obtained, and then the maximum value and the minimum value among the RGB values of the pixel grids in each sub-region block are obtained, and they are respectively set as Smax and Smin;

[0026] At the same time, according to Smax and Smin of each sub-region block, the RGB value interval A[Smin, Smax] of each sub-region block is constructed, and the RGB value interval B[ZSmin, ZSmax] of each sub-region block of the normal optical lens is obtained. The interval A[Smin, Smax] and the interval B[ZSmin, ZSmax] are compared and analyzed. The value obtained by subtracting ZSmax of interval B from Smax of interval A of each sub-region block and the value obtained by subtracting ZSmin of interval B from Smin of interval A of each sub-region block are obtained, and they are respectively set as the peak segment deviation value and the valley segment deviation value, and the peak segment deviation value and the valley segment deviation value are discriminated and analyzed to obtain the normal region and the abnormal region;

[0027] The number of abnormal regions is obtained, and the number of abnormal regions is set as the clarity evaluation offset coefficient, and the clarity evaluation offset coefficient is discriminated and analyzed to obtain a clear signal or a fuzzy signal.

[0028] The beneficial effects of the present invention are as follows:

[0029] (1) The present invention initially analyzes from two points: the defect extraction of the target optical lens and the appearance image, so as to initially understand whether there are defects in the target optical lens and whether the appearance is normal, so as to improve the detection efficiency of the target optical lens. And through the way of information feedback, the detection interference factors of the target optical lens are further analyzed, that is, the evaluation interference magnitude processing feedback analysis is carried out on the detection interference information, so as to adjust the detection interference factors of the target optical lens according to the displayed text, so as to improve the accuracy of the subsequent detection results of the target optical lens;

[0030] (2) The present invention detects the performance of the target optical lens from two perspectives of luminous flux and imaging image in a progressive manner to improve the comprehensiveness of the detection of the target optical lens, that is, to perform area-based luminous flux regulation evaluation and analysis on the actual transmittance, so as to conduct comparison and analysis from the perspective of luminous flux, and intuitively understand the detection results of the transmittance performance of the target optical lens. Perform information-level processing feedback evaluation and analysis on the imaging background information. On the one hand, manage the interference factors in the detection of the imaging feature image, and on the other hand, help to indirectly feedback the detection results of the target optical lens from the perspective of imaging clarity. Brief Description of the Drawings

[0031] The present invention will be further described below with reference to the accompanying drawings;

[0032] Figure 1 is the system flow block diagram of the present invention;

[0033] Figure 2 is the local analysis reference diagram of the present invention. Detailed Embodiments

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment 1:

[0036] Please refer to Figures 1 to 2 As shown, the present invention is an intelligent detection system adapted to an optical lens, including an optical lens intelligent detection center, an optical database, a preliminary appearance evaluation and analysis unit, a light detection interference quantification analysis unit, a progressive light transmittance detection unit, an imaging hierarchy evaluation unit, and an evaluation feedback unit. The optical database is in one-way communication connection with the optical lens intelligent detection center, the optical lens intelligent detection center is in one-way communication connection with the preliminary appearance evaluation and analysis unit, the preliminary appearance evaluation and analysis unit is in one-way communication connection with both the light detection interference quantification analysis unit and the evaluation feedback unit, the light detection interference quantification analysis unit is in one-way communication connection with the progressive light transmittance detection unit, the imaging hierarchy evaluation unit, and the evaluation feedback unit, and both the progressive light transmittance detection unit and the imaging hierarchy evaluation unit are in one-way communication connection with the evaluation feedback unit;

[0037] The optical lens intelligent detection center is used to retrieve the appearance feature image of the target optical lens from the optical database and send the appearance feature image to the preliminary appearance evaluation and analysis unit;

[0038] The preliminary appearance evaluation and analysis unit is used to extract defect features and conduct appearance defect comparison analysis on the received appearance feature images, so as to preliminarily understand whether there are defects in the target optical lens and whether the appearance is normal, in order to improve the detection efficiency of the target optical lens. The specific process of defect feature extraction and appearance defect comparison analysis is as follows:

[0039] Collect the detection period of the target optical lens and set it as the time threshold. Obtain the appearance feature image of the target optical lens within the time threshold. Divide the appearance feature image into m sub-region blocks, where m is a natural number greater than zero. Extract defect information from each sub-region block of the appearance feature image. The defect information includes bubbles, cracks, etc. Obtain the defect information of each sub-region block and conduct discrimination processing on the defect information. If there is no defect information, generate a progressive signal. If there is defect information, generate a display warning signal and send the display warning signal to the evaluation feedback unit. After receiving the display warning signal, the evaluation feedback unit immediately generates the preset warning text corresponding to the display warning signal, so as to preliminarily understand whether there are defects in the target optical lens and improve the detection efficiency of the target optical lens;

[0040] When a progressive signal is generated, obtain the appearance feature image of a normal optical lens, set the appearance feature image of the normal optical lens as the standard appearance feature image, obtain the difference value between the appearance feature image and the standard appearance feature image, and set the difference value between the appearance feature image and the standard appearance feature image as the preliminary appearance deviation value, and conduct discrimination processing on the preliminary appearance deviation value:

[0041] If the preliminary appearance deviation value is less than the preset preliminary appearance deviation value threshold, generate a feedback instruction;

[0042] If the preliminary appearance deviation value is greater than or equal to the preset preliminary appearance deviation value threshold, generate a defect signal. Send the feedback instruction or the defect signal to the evaluation feedback unit. After receiving the feedback instruction or the defect signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the feedback instruction or the defect signal, so as to intuitively understand the appearance detection result of the target optical lens;

[0043] When a feedback instruction is generated, the optical inspection interference quantization analysis unit is used to respond to the feedback instruction. At the same time, collect the detection interference information of the target optical lens, conduct evaluation interference level processing and feedback analysis on the detection interference information, so as to adjust the detection interference factors of the target optical lens according to the displayed text to improve the accuracy of the subsequent detection result of the target optical lens. The specific process of evaluation interference level processing and feedback analysis is as follows:

[0044] Obtain the detection interference information of the target optical lens within the time threshold. The detection interference information includes the clamping interference value and the light passage interference value. Compare and analyze the clamping interference value and the light passage interference value with the preset clamping interference value threshold and the preset light passage interference value threshold. Set the number of the clamping interference value and the light passage interference value that is greater than or equal to the preset clamping interference value threshold and the preset light passage interference value threshold as the evaluation interference coefficient, and perform discrimination processing on the evaluation interference coefficient:

[0045] If the evaluation interference coefficient = 0, generate a normal signal;

[0046] If the evaluation interference coefficient = 1 or if the evaluation interference coefficient = 2, generate an interference signal, and send the normal signal or the interference signal to the evaluation feedback unit. After receiving the normal signal or the interference signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the normal signal or the interference signal, so as to adjust the detection interference factors of the target optical lens according to the displayed text, and improve the accuracy of the subsequent detection results of the target optical lens;

[0047] In the embodiment of the present invention, the clamping interference value represents the acute angle value formed by the bottom surface of the target optical lens after clamping and the horizontal workbench being inclined. It should be noted that the larger the value of the clamping interference value, the greater the interference of the clamping of the target optical lens on the subsequent detection, and the greater the risk of abnormal credibility of the detection result;

[0048] In the embodiment of the present invention, the light passage interference value represents the number of corresponding values of the illumination information of the light detection component of the target optical lens exceeding the preset threshold. The illumination information includes the light source flicker frequency, the light source flicker times, etc. It should be noted that the light passage interference value is an influence parameter reflecting the interference of the light source on the detection of the target optical lens. The larger the value of the light passage interference value, the greater the risk of detection error of the target optical lens;

[0049] In the embodiment of the present invention, the light detection component represents the light detection light source.

[0050] Embodiment Two:

[0051] When a normal signal is generated, the progressive light transmission detection unit is used to respond to the normal signal, and at the same time collect the actual light transmittance of the target optical lens, and perform regional light passage regulation evaluation processing and analysis on the actual light transmittance, so as to perform comparison and analysis from the perspective of light flux, and intuitively understand the detection result of the light transmittance performance of the target optical lens, and further help to deeply detect the light transmittance performance of the target optical lens. The specific process of the regional light passage regulation evaluation processing and analysis is as follows:

[0052] In the embodiment of the present invention, the light transmittance of the target optical lens is detected by controlling the light detection component;

[0053] Divide the target optical lens into i sub-region blocks, where i is a natural number greater than zero. Obtain the center points of each sub-region. By controlling the optical inspection component, perform light transmittance detection on the center points of each sub-region, obtain the standard light transmittance of the center points of each sub-region block of the normal optical lens, and then obtain the illumination light flux corresponding to the standard light transmittance of the center points of each sub-region block, and set it as the standard illumination light flux;

[0054] By controlling the optical inspection component, perform light transmittance detection on the center points of each sub-region block of the target optical lens, obtain the actual light transmittance of the center points of each sub-region block, compare and analyze the actual light transmittance with the standard light transmittance. If the actual light transmittance is not equal to the standard light transmittance, adjust the illumination light flux of the optical inspection component, and then obtain the actual illumination light flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance. Set the difference between the actual illumination light flux and the standard illumination light flux as the light transmittance deviation coefficient, and process the light transmittance deviation coefficient:

[0055] If the light transmittance deviation coefficient belongs to the preset light transmittance deviation coefficient range, generate a standard signal;

[0056] If the light transmittance deviation coefficient does not belong to the preset light transmittance deviation coefficient range, generate a deviation signal;

[0057] Obtain the number of sub-region blocks corresponding to the generated deviation signal, and set the number of sub-region blocks corresponding to the generated deviation signal as the light transmittance defect evaluation coefficient, and perform discriminant processing on the light transmittance defect evaluation coefficient:

[0058] If the light transmittance defect evaluation coefficient is equal to zero, generate a qualified signal;

[0059] If the light transmittance defect evaluation coefficient is not equal to zero, generate an unqualified signal, and send the qualified signal or unqualified signal to the evaluation feedback unit. After receiving the qualified signal or unqualified signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the qualified signal or unqualified signal, so as to intuitively understand the light transmittance performance detection result of the target optical lens;

[0060] When a normal signal is generated, the imaging hierarchy evaluation unit is used to respond to the normal signal, and at the same time collect the imaging background information of the target optical lens, perform information hierarchical processing feedback evaluation analysis on the imaging background information. On the one hand, manage the interference factors for the imaging feature image detection, and on the other hand, help to feedback the detection result of the target optical lens from the perspective of imaging clarity. The specific information hierarchical processing feedback evaluation analysis process is as follows:

[0061] Based on the principle of optical imaging, the imaging background information of the target optical lens within the time threshold is obtained. The imaging background information includes the environmental dust concentration, the number of interfering light sources, etc. The interfering light source refers to the light source excluding the optical detection component. The number corresponding to the imaging background information whose value exceeds the preset threshold is obtained, and the number corresponding to the imaging background information whose value exceeds the preset threshold is set as the imaging interference coefficient, and the imaging interference coefficient is discriminated:

[0062] If the imaging interference coefficient is equal to zero, an effective signal is generated;

[0063] If the imaging interference coefficient is not equal to zero, an invalid signal is generated. The invalid signal is sent to the evaluation feedback unit. After receiving the invalid signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the invalid signal, so as to manage the interference factors of the imaging feature image detection in a timely manner and improve the subsequent imaging feature image detection accuracy;

[0064] When an effective signal is generated:

[0065] The imaging feature image of the target optical lens within the time threshold is obtained. The imaging feature image is divided into g sub-region blocks, where g is a natural number greater than zero. The RGB values of each pixel grid in each sub-region block of the imaging feature image are obtained. Furthermore, the maximum value and the minimum value among the RGB values of the pixel grids in each sub-region block are obtained, and the maximum value and the minimum value among the RGB values of the pixel grids in each sub-region block are respectively set as Smax and Smin;

[0066] At the same time, based on Smax and Smin of each sub-region block, the RGB value interval A[Smin, Smax] of each sub-region block is constructed. The RGB value interval B[ZSmin, ZSmax] of each sub-region block of the normal optical lens is obtained. The interval A[Smin, Smax] and the interval B[ZSmin, ZSmax] are compared and analyzed. The value obtained by subtracting ZSmax of interval B from Smax of interval A of each sub-region block and the value obtained by subtracting ZSmin of interval B from Smin of interval A of each sub-region block are obtained, and they are respectively set as the peak segment deviation value and the valley segment deviation value, and the peak segment deviation value and the valley segment deviation value are discriminated and analyzed:

[0067] If the peak segment deviation value belongs to the preset peak segment deviation value range and the valley segment deviation value belongs to the preset valley segment deviation value range, the corresponding sub-region block is judged as a normal region;

[0068] If the peak segment deviation value does not belong to the preset peak segment deviation value range, or the valley segment deviation value belongs to the preset valley segment deviation value range, the corresponding sub-region block is judged as an abnormal region;

[0069] Obtain the number of abnormal areas, set the number of abnormal areas as the clear evaluation offset coefficient, and conduct discriminant analysis on the clear evaluation offset coefficient:

[0070] If the clear evaluation offset coefficient is equal to zero, generate a clear signal;

[0071] If the clear evaluation offset coefficient is not equal to zero, generate a fuzzy signal, and send the clear signal or the fuzzy signal to the evaluation feedback unit. After receiving the clear signal or the fuzzy signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the clear signal or the fuzzy signal, so as to indirectly feedback the detection result of the target optical lens from the perspective of the imaging clarity of the target optical lens. At the same time, the target optical lens is detected from the two angles of light transmittance and imaging to improve the comprehensiveness of the target optical lens detection;

[0072] In summary, the present invention initially analyzes from two points: the defect extraction and the appearance image of the target optical lens, so as to initially understand whether there are defects in the target optical lens and whether the appearance is normal, so as to improve the detection efficiency of the target optical lens. And through the way of information feedback, further analyze the detection interference factors of the target optical lens, that is, conduct evaluation interference magnitude processing feedback analysis on the detection interference information, so as to adjust the detection interference factors of the target optical lens according to the displayed text to improve the accuracy of the subsequent detection result of the target optical lens;

[0073] Detect the performance of the target optical lens from two angles of luminous flux and imaging image in a progressive manner to improve the comprehensiveness of the target optical lens detection, that is, conduct regional luminous flux regulation evaluation processing analysis on the actual light transmittance, so as to conduct comparison analysis from the perspective of luminous flux, and intuitively understand the detection result of the light transmittance performance of the target optical lens. Conduct information hierarchical processing feedback evaluation analysis on the imaging background information. On the one hand, manage the detection interference factors of the imaging feature image, and on the other hand, help to indirectly feedback the detection result of the target optical lens from the perspective of imaging clarity.

[0074] The setting of the threshold value is for the convenience of comparison. Regarding the size of the threshold value, it depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0075] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent replacements or changes, and should be covered by the protection scope of the present invention.

Claims

1. An intelligent detection system adapted to an optical lens, characterized in that, It includes an intelligent optical lens inspection center, an optical database, a preliminary appearance evaluation and analysis unit, a light inspection interference quantification analysis unit, a progressive light transmission inspection unit, an imaging hierarchy evaluation unit, and an evaluation feedback unit; The preliminary appearance evaluation and analysis unit is unidirectionally communicatively connected to both the light inspection interference quantification analysis unit and the evaluation feedback unit. The light inspection interference quantification analysis unit is unidirectionally communicatively connected to the progressive light transmission inspection unit, the imaging hierarchy evaluation unit, and the evaluation feedback unit. Both the progressive light transmission inspection unit and the imaging hierarchy evaluation unit are unidirectionally communicatively connected to the evaluation feedback unit; The intelligent optical lens inspection center is used to retrieve the appearance feature image of the target optical lens from the optical database and send the appearance feature image to the preliminary appearance evaluation and analysis unit; The preliminary appearance evaluation and analysis unit is used to extract defect features and conduct appearance defect comparison analysis on the received appearance feature image, discriminate and process the obtained preliminary appearance deviation value to obtain a feedback instruction or a defect signal; The light inspection interference quantification analysis unit is used to respond to the feedback instruction, simultaneously collect the detection interference information of the target optical lens, conduct evaluation interference magnitude processing and feedback analysis on the detection interference information, discriminate and process the obtained evaluation interference coefficient to obtain a normal signal or an interference signal; The progressive light transmission inspection unit is used to respond to the normal signal, simultaneously collect the actual light transmittance of the target optical lens, conduct regional light flux regulation evaluation processing and analysis on the actual light transmittance, discriminate and process the obtained light transmission defect evaluation coefficient to obtain a qualified signal or an unqualified signal; The imaging hierarchy evaluation unit is used to respond to the normal signal, simultaneously collect the imaging background information of the target optical lens, conduct information hierarchy processing and feedback evaluation analysis on the imaging background information, discriminate and analyze the obtained clear evaluation deviation coefficient to obtain a clear signal or a fuzzy signal; After receiving the feedback instruction or the defect signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the feedback instruction or the defect signal; After receiving the normal signal or the interference signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the normal signal or the interference signal; After receiving the qualified signal or the unqualified signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the qualified signal or the unqualified signal; After receiving the clear signal or the fuzzy signal, the evaluation feedback unit immediately displays the preset warning text corresponding to the clear signal or the fuzzy signal.

2. The intelligent detection system adapted to an optical lens according to claim 1, wherein The process of defect feature extraction and appearance defect comparison analysis is as follows: Collect the detection time period of the target optical lens and set it as the time threshold. Obtain the appearance feature image of the target optical lens within the time threshold. Divide the appearance feature image into m sub-region blocks, where m is a natural number greater than zero. Extract defect information from each sub-region block of the appearance feature image. The defect information includes bubbles and cracks. Obtain the defect information of each sub-region block and conduct discrimination processing on the defect information. If there is no defect information, generate a progressive signal. If there is defect information, generate a display warning signal.

3. The intelligent detection system adapted to an optical lens according to claim 2, characterized in that, When generating a progressive signal, an appearance feature image of a normal optical lens is obtained, the appearance feature image of the normal optical lens is set as the standard appearance feature image, a difference value between the appearance feature image and the standard appearance feature image is obtained, and the difference value between the appearance feature image and the standard appearance feature image is set as the preliminary appearance deviation value, and the preliminary appearance deviation value is subjected to a discrimination process to obtain a feedback instruction or a defect signal.

4. The intelligent detection system adapted to an optical lens according to claim 1, characterized in that The process of evaluating interference level processing feedback analysis is as follows: Detection interference information of the target optical lens within a time threshold is obtained. The detection interference information includes a clamping interference value and a light passing interference value. The clamping interference value and the light passing interference value are compared and analyzed with a preset clamping interference value threshold and a preset light passing interference value threshold. The number of the clamping interference value and the light passing interference value that is greater than or equal to the preset clamping interference value threshold and the preset light passing interference value threshold is set as the evaluation interference coefficient, and the evaluation interference coefficient is subjected to a discrimination process to obtain a normal signal or an interference signal.

5. The intelligent detection system adapted to an optical lens according to claim 4, wherein, The clamping interference value represents an acute angle value formed by the bottom surface of the target optical lens after clamping and the horizontal workbench being inclined; the light passing interference value represents the number of times that the corresponding value of the illumination information of the light detection component of the target optical lens exceeds a preset threshold. The illumination information includes the light source flashing frequency and the light source flashing times.

6. The intelligent detection system adapted to an optical lens according to claim 1, wherein, The process of area-type light passing regulation evaluation processing analysis is as follows: The target optical lens is divided into i sub-region blocks, where i is a natural number greater than zero. The center points of each sub-region are obtained. By controlling the light detection component, the light transmittance of the center points of each sub-region is detected. The standard light transmittance of the center points of each sub-region block of the normal optical lens is obtained, and then the standard illumination light flux corresponding to the standard light transmittance of the center points of each sub-region block is obtained and set as the standard illumination light flux; By controlling the light detection component, the light transmittance of the center points of each sub-region block of the target optical lens is detected. The actual light transmittance of the center points of each sub-region block is obtained. The actual light transmittance is compared and analyzed with the standard light transmittance. If the actual light transmittance is not equal to the standard light transmittance, the illumination light flux of the light detection component is adjusted, and then the actual illumination light flux corresponding to the moment when the actual light transmittance is equal to the standard light transmittance is obtained. The difference between the actual illumination light flux and the standard illumination light flux is set as the light transmittance deviation coefficient, and the light transmittance deviation coefficient is processed to obtain a standard signal or a deviation signal.

7. The intelligent detection system adapted to an optical lens according to claim 6, characterized in that, The number of sub-region blocks corresponding to the generated deviation signal is obtained, and the number of sub-region blocks corresponding to the generated deviation signal is set as the light transmittance defect evaluation coefficient, and the light transmittance defect evaluation coefficient is subjected to a discrimination process: If the light transmittance defect evaluation coefficient is equal to zero, a qualified signal is generated; If the light transmittance defect evaluation coefficient is not equal to zero, an unqualified signal is generated, and the qualified signal or the unqualified signal is sent to the evaluation feedback unit.

8. The intelligent detection system adapted to an optical lens according to claim 1, characterized in that, The process of information hierarchical processing feedback evaluation analysis is as follows: Based on the principle of optical imaging, the imaging background information of the target optical lens within the time threshold is obtained. The imaging background information includes the ambient dust concentration and the number of interfering light sources. The interfering light sources refer to the light sources excluding the light detection components. The number corresponding to the imaging background information value exceeding the preset threshold is obtained, and the number corresponding to the imaging background information value exceeding the preset threshold is set as the imaging interference coefficient. Then, the imaging interference coefficient is discriminated to obtain a valid signal or an invalid signal.

9. The intelligent detection system adapted to an optical lens according to claim 8, wherein When a valid signal is generated: The imaging feature image of the target optical lens within the time threshold is obtained. The imaging feature image is divided into g sub-region blocks, where g is a natural number greater than zero. The RGB values of each pixel grid in each sub-region block of the imaging feature image are obtained. Furthermore, the maximum value and the minimum value among the RGB values of the pixel grids in each sub-region block are obtained and are respectively set as Smax and Smin. At the same time, the RGB value interval A[Smin, Smax] of each sub-region block is constructed based on Smax and Smin of each sub-region block. The RGB value interval B[ZSmin, ZSmax] of each sub-region block of the normal optical lens is obtained. The interval A[Smin, Smax] and the interval B[ZSmin, ZSmax] are compared and analyzed. The value obtained by subtracting ZSmax of interval B from Smax of interval A and the value obtained by subtracting ZSmin of interval B from Smin of interval A in each sub-region block are obtained and are respectively set as the peak segment deviation value and the valley segment deviation value. Then, the peak segment deviation value and the valley segment deviation value are discriminated and analyzed to obtain the normal region and the abnormal region. The number of abnormal regions is obtained, and the number of abnormal regions is set as the clarity evaluation offset coefficient. Then, the clarity evaluation offset coefficient is discriminated and analyzed to obtain a clear signal or a fuzzy signal.

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