AOI (automatic optical inspection) appearance detection method, system, medium and equipment for vehicle-mounted LCD (liquid crystal display) screen

Abstract

The invention relates to the technical field of LCD (Liquid Crystal Display) screen detection, in particular to an AOI (Automatic Optic Inspection) appearance detection method and system for a vehicle-mounted LCD screen, a medium and equipment. A2, detecting the front and back surfaces of the electrode; a3, appearance detection results are combined and processed; step A4, LCD screen lightening electric detection is carried out; and A5, processing an LCD screen electric quantity lighting detection result. The method is ingenious in design, defects are intelligently screened out by analyzing poor surface appearance defects of products and poor electrode ITO circuit damage, the defects are classified according to the A bin, the B bin and the C bin, and misjudgment and missed judgment of personnel are reduced; the manpower demand is greatly reduced, and the detection efficiency and accuracy are improved; comprehensive detection of the vehicle-mounted LCD screen can be completed in a short time, various appearance defects can be accurately recognized, and missing detection and misjudgment caused by visual fatigue, subjective judgment and other factors in manual detection are effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of LCD screen detection, and in particular to an AOI appearance detection method, system, medium, and device for in-vehicle LCD screens. Background Art

[0002] With the development of automotive intelligence, the usage of in-vehicle LCD screens has increased. The appearance and lighting detection quality thereof affect the user experience and driving safety. As a non-contact high-precision detection means, the importance of AOI detection technology has become increasingly prominent. It can effectively detect appearance defects such as scratches, cracks, bubbles, and dirt. The integration of the AOI detection system with automated production equipment, MES (Manufacturing Execution System) systems, etc. has been improved, realizing functions such as automatic material handling, detection, data transmission and analysis, and alarm prompts, improving production efficiency and quality control levels. With the development of automotive electronics and intelligence, the usage of in-vehicle LCD screens has increased, and the requirements for their quality and reliability have been improved, driving the growth of the market demand for AOI detection technology.

[0003] The existing AOI detection of in-vehicle LCD screens has the following defects:

[0004] 1. Slow detection speed: Traditional detection methods require manual spot visual inspection under a microscope for the appearance defects of the electrode ITO (Indium Tin Oxide) and the product surface, which is time-consuming and laborious, with a slow detection speed and is prone to missed inspections, unable to meet the requirements of the production line.

[0005] 2. Poor reliability: Since human eye visual inspection can only detect and judge the defects visible to the naked eye, it is difficult to accurately distinguish the categories of appearance defects and there is a risk of misjudgment.

[0006] 3. Lack of comprehensive judgment of multiple factors: Traditional detection methods are mainly based on lighting signal detection and personnel appearance detection judgment, that is, products with normal lighting and normal personnel appearance are considered good products. For invisible defects such as ITO line defects, cracks, and dirt in appearance detection, it will lead to poor product quality in the later stage. Summary of the Invention

[0007] The present invention provides an AOI appearance detection method, system, medium, and device for in-vehicle LCD screens in view of the problems of the prior art.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions:

[0009] The present invention provides an AOI appearance detection method for in-vehicle LCD screens, which includes the following steps:

[0010] Step A1, Surface Appearance Detection: The appearance loading robot places the in-vehicle LCD screen to be tested on the appearance platform, drives the appearance platform to move into the imaging field of view of the appearance detection camera. After the machine tool PLC receives the imaging instruction, it performs image acquisition. After the acquisition is completed, according to the preset appearance data processing method, the final result is output to the appearance detection UI host;

[0011] Step A2, Electrode Front and Back Detection: After the surface appearance detection is completed, the initial electrode front and back synchronous detection is carried out. The machine tool PLC receives the imaging instruction to perform image acquisition. After the initial acquisition is completed, according to the preset data processing method, the final result is output to the appearance detection UI host; When it is necessary to detect the in-vehicle LCD screen with double electrodes, the machine tool PLC sends a signal to control the appearance platform to move into place for the second electrode front and back synchronous detection. According to the preset appearance data processing method, the final result is output to the appearance detection UI host;

[0012] Step A3, Merging and Processing of Appearance Detection Results: After both the surface external detection and the electrode front and back detection are completed, finally, the appearance detection UI host gives the final "union" result as OK or NG; If the result is OK, the machine tool PLC sends a signal to Step A4 for lighting and electrical testing; If the result is NG, the machine tool PLC sends a signal to the unloading and placing in Warehouse C for processing;

[0013] Step A4, Lighting and Electrical Testing of LCD Screen: The electrical testing loading robot places the in-vehicle LCD screen that needs to be lit and electrically tested on the electrical testing station, turns on the light through the power-on and the electrical testing AOI software to control the lighting program, flips during the lighting process, and the electrical testing imaging camera collects and gathers the images of each frame during the flipping process. According to the preset electrical testing data processing method, the final result is output to the lighting and electrical testing UI host;

[0014] Step A5, Processing of the Results of the LCD Screen Lighting and Electrical Testing: The results of the lighting and electrical testing at each work station are transmitted to the lighting and electrical testing UI host for data induction and summary. Finally, the lighting and electrical testing UI host gives the data consistent with the work station results; If the result is an OK product, the machine tool PLC sends a signal to the unloading mechanism to place the OK product in Warehouse A; If the result is an NG product, the machine tool PLC sends a signal to the unloading mechanism to place the NG product in Warehouse B.

[0015] Among them, the appearance data processing method includes the following steps:

[0016] Step S1, Modeling of Machine Type Appearance AOI Inspection: According to the name, resolution, and size parameters of the LCD screen machine type, set the corresponding machine type model;

[0017] Step S2, According to the established corresponding machine type model, refer to the MSA sample and the detection requirements for appearance defects in the SOP of the corresponding process for parameter setting;

[0018] Step S3, Appearance MSA Training and Trial Run Evaluation: According to the defect categories of the selected appearance MSA samples, corresponding defect pictures are collected by running the film for each parameter table corresponding to each defect. Parameter details are set for defects outside the specifications, and the corresponding parameters for defects within the specifications are set to the default OK.

[0019] Step S4, Output Appearance AOI Detection Defect Types and Results: The appearance detection types include: a - Appearance Surface Inspection, b - Front Electrode Inspection, and c - Back Electrode Inspection. The final output result is: Output Result Z = a ∪ b ∪ c.

[0020] Among them, the method for processing electrical measurement data includes the following steps:

[0021] Step S5, If the appearance detection UI host gives the final "union" result as OK, the output result is given to the lighting electrical measurement process to establish an electrical measurement model for the model.

[0022] Step S6, According to the established electrical measurement model for the model, parameter settings are made with reference to the detection requirements for lighting electrical measurement defects in the lighting electrical measurement MSA sample and the SOP of the corresponding process.

[0023] Step S7, According to the defect categories of the selected electrical measurement MSA samples, corresponding defect pictures are collected by running the film for each parameter table corresponding to each defect. Parameter details are set for defects outside the specifications, and the corresponding parameters for defects within the specifications are set to the default OK.

[0024] Step S8, Output Electrical Measurement AOI Detection Defect Types and Results: The lighting electrical measurement types include: Station A1 / A2 on Side A, Station B1 / B2 on Side B. Their results are output separately and do not affect each other; Output Result Z = A1, A2, B1, B2.

[0025] The present invention also provides a system for an AOI appearance detection method, which includes an appearance loading robot, an appearance platform, an electrical measurement loading robot, a machine tool PLC, a transfer mechanism, an appearance detection camera, an appearance detection UI host, an electrical measurement picture-taking camera, and a lighting electrical measurement UI host. The transfer mechanism includes a platform running X-axis and a platform running Q-axis. The appearance platform is installed on the platform running Q-axis. The platform running Q-axis is used to drive the appearance platform to rotate, and the platform running X-axis is used to drive the platform running Q-axis to reciprocate along the X-axis; the appearance loading robot is used to place the to-be-tested vehicle-mounted LCD screen on the appearance platform. The transfer mechanism is used to transfer the appearance platform to the station of the appearance detection camera for appearance detection and send the detection result to the appearance detection UI host. If the detection result is OK, the vehicle-mounted LCD screen is transferred to the station of the electrical measurement picture-taking camera by the electrical measurement loading robot for lighting, and the final result is output to the lighting electrical measurement UI host.

[0026] Among them, the appearance platform includes a base and six vacuum areas arranged on the vacuum base. The six vacuum areas include a first vacuum area, a second vacuum area, a third vacuum area, a fourth vacuum area, a fifth vacuum area, and a sixth vacuum area. The first vacuum area and the fourth vacuum area are respectively located at the upper corner and the lower corner on one side of the upper end face of the vacuum base, the third vacuum area and the sixth vacuum area are respectively located at the upper corner and the lower corner on the other side of the upper end face of the vacuum base, and the second vacuum area and the fifth vacuum area are respectively located on the upper side and the lower side of the middle part of the upper end face of the vacuum base.

[0027] The present invention also provides a computer storage medium storing computer instructions which, when called, are used to execute the AOI appearance detection method for an in-vehicle LCD screen described above.

[0028] The present invention also provides an electronic device. Among them, the electronic device includes: a processor; and a memory arranged to store computer-executable instructions which, when executed, cause the processor to execute the AOI appearance detection method for an in-vehicle LCD screen described above.

[0029] Advantages of the present invention:

[0030] The present invention is ingeniously designed. By analyzing the surface appearance defects and the damage of the electrode ITO circuit of the product, the defects are intelligently screened out and classified into three bins A, B, and C, reducing the misjudgment and missed judgment of personnel. The appearance detection of this application uses a camera to collect high-definition original defect pictures to detect the binding defects that are difficult to distinguish visually, greatly reducing the manpower requirement and improving the detection efficiency and accuracy. It can complete the comprehensive detection of the in-vehicle LCD screen in a short time, can accurately identify various appearance defects such as scratches, cracks, bubbles, missing corners, dirt, etc., and can detect defects as small as the micron level, effectively avoiding the missed detection and misjudgment caused by factors such as visual fatigue and subjective judgment in manual detection. Description of the Drawings

[0031] Figure 1 It is a schematic structural diagram of the in-vehicle LCD screen of the present invention.

[0032] Figure 2 It is a flowchart of the AOI appearance detection method for an in-vehicle LCD screen of the present invention.

[0033] Figure 3 It is a flowchart of the appearance data processing method and the electrical measurement data processing method of the present invention.

[0034] Figure 4Schematic diagram of the structure of the appearance platform, transfer mechanism and appearance detection camera of the present invention.

[0035] Figure 5 Schematic diagram of the structure of the appearance platform of the present invention.

[0036] In Figures 1 to 5 The reference numerals in

[0037] 1. Platform operation X-axis; 2. Platform operation Q-axis; 3. Appearance detection camera; 4. Base; 5. First vacuum area; 6. Second vacuum area; 7. Third vacuum area; 8. Fourth vacuum area; 9. Fifth vacuum area; 10. Sixth vacuum area. Detailed implementation mode

[0038] For the convenience of understanding by those skilled in the art, the present invention will be further described below in conjunction with embodiments and drawings. The content mentioned in the implementation mode does not limit the present invention. The present invention will be described in detail below with reference to the drawings.

[0039] Embodiment 1

[0040] Embodiment 1 of the present application provides an AOI appearance detection method for an in-vehicle LCD screen, as Figure 2 shown, which includes the following steps:

[0041] Step A1, surface appearance detection: The appearance loading robot places the in-vehicle LCD screen to be tested on the appearance platform, drives the appearance platform to move into the image acquisition field of view of the appearance detection camera. After the machine tool PLC receives the image acquisition instruction, it performs image acquisition. After the acquisition is completed, according to the preset appearance data processing method, the final result is output to the appearance detection UI host;

[0042] Step A2, electrode front and back detection: After the surface appearance detection is completed, the initial electrode front and back synchronous detection is carried out. The machine tool PLC receives the image acquisition instruction to perform image acquisition. After the initial acquisition is completed, according to the preset data processing method, the final result is output to the appearance detection UI host; When it is necessary to detect the in-vehicle LCD screen with double electrodes, the machine tool PLC sends a signal to control the appearance platform to move into place to perform the second electrode front and back synchronous detection. According to the preset appearance data processing method, the final result is output to the appearance detection UI host;

[0043] Step A3, appearance detection result merging and processing: After both the surface external detection and the electrode front and back detection are completed, finally the appearance detection UI host gives the final "union" result as OK or NG; If the result is OK, the machine tool PLC sends a signal to step A4 for lighting and electrical testing; If the result is NG, the machine tool PLC sends a signal to the blanking and placing in bin C for processing;

[0044] Step A4, LCD screen lighting and electrical measurement detection: The robotic arm for electrical measurement loading places the in-vehicle LCD screen to be lit and electrically measured on the electrical measurement station. The lighting process is controlled by the energization and the electrical measurement AOI software to turn on the light. During the lighting process, the screen is flipped. The electrical measurement image capture camera then captures and collects the graphics of each frame during the flipping process. According to the preset electrical measurement data processing method, the final result is output to the lighting and electrical measurement UI host;

[0045] Step A5, Processing the results of the LCD screen power-on lighting detection: The results of the lighting and electrical measurement at each work station are transmitted to the lighting and electrical measurement UI host for data induction and summary. Finally, the lighting and electrical measurement UI host gives data consistent with the station results. If the result is an OK product, the machine tool PLC sends a signal to the unloading mechanism to place the OK product in bin A. If the result is an NG product, the machine tool PLC sends a signal to the unloading mechanism to place the NG product in bin B.

[0046] Specifically, the present invention is ingeniously designed. By analyzing the surface appearance defects and the damage of the electrode ITO circuit of the product, the defects are intelligently screened out and classified into three bins, namely A, B, and C, reducing misjudgment and missed judgment by personnel. In this application, the appearance detection uses a camera to collect high-definition original defect images, detects binding defects that are difficult to distinguish visually, greatly reduces the manpower requirement, and improves the detection efficiency and accuracy. It can complete a comprehensive detection of the in-vehicle LCD screen in a short time, can accurately identify various appearance defects, such as scratches, cracks, bubbles, missing corners, dirt, etc., and can detect defects as small as the micron level, effectively avoiding missed detection and misjudgment caused by factors such as visual fatigue and subjective judgment in manual detection.

[0047] In the embodiment of the present application, as Figure 3 shown, the appearance data processing method includes the following steps:

[0048] Step S1, Modeling for the AOI inspection of the model appearance: According to the name, resolution, and size parameters of the LCD screen model, set the corresponding model;

[0049] Step S2, According to the established corresponding model, refer to the MSA template and the detection requirements for appearance defects in the SOP of the corresponding process to set parameters, as shown in the following table:

[0050]

[0051]

[0052] Step S3, Appearance MSA Training and Trial Run Evaluation: Based on the defect categories of the selected appearance MSA templates, corresponding defect images are collected by running the wafers for each parameter table corresponding to a defect. Parameter details are set for defects outside the specifications, and the corresponding parameters for defects within the specifications are set to the default OK; avoid over-inspection of parameters, which may affect the efficiency of manual re-judgment operations. The reference of defect categories is as follows:

[0053] Sample Number Defect Name Defect Size (Gray Value) Judgment Result First Time Second Time 1 Long Edge Chipping L > 1mm NG 2 Long Edge Angular Chipping D > 0.2mm NG 3 Short Edge Angular Chipping D > 0.2mm NG 4 Short Edge Chipping L > 1mm NG 5 ITO Scratch L > 0.2mm NG 6 Contamination D > 2mm NG 7 Dimple D > 0.15mm NG 8 Bump D > 0.15mm NG 9 Liquid Crystal Leakage D > 0.05mm NG 10 Electrode Oxidation D > 1mm NG

[0054] Step S4, Output Appearance AOI Detection Defect Types and Results: The appearance detection types include: a - Appearance Surface Inspection, b - Front Electrode Inspection, and c - Back Electrode Inspection. The final output result is: Output Result Z = a ∪ b ∪ c.

[0055] In the embodiment of this application, as Figure 3 shown, the electrical measurement data processing method includes the following steps:

[0056] Step S5, When the result value obtained from Step S4 is 1 (i.e., the result is OK), the output result is given to the lighting electrical measurement process. If the appearance detection UI host gives the final "union" result as OK, the output result is given to the lighting electrical measurement process to establish an electrical measurement model for the machine type;

[0057] Step S6, According to the established electrical measurement model for the machine type, refer to the detection requirements for lighting electrical measurement defects in the lighting electrical measurement MSA template and the SOP of the corresponding process to set parameters as follows:

[0058]

[0059] Step S7, Based on the defect categories of the selected electrical measurement MSA templates, corresponding defect images are collected by running the wafers for each parameter table corresponding to a defect. Parameter details are set for defects outside the specifications, and the corresponding parameters for defects within the specifications are set to the default OK; avoid over-inspection of parameters, which may affect the efficiency of manual re-judgment operations. The reference of defect categories is as follows:

[0060] Sample Number Defect Name Defect Size (Gray Value) Judgment Result First Time Second Time 1 Bright Spot L > G84 NG 2 Dark Spot D > 0.10mm NG 3 Cell Foreign Object D > 0.08mm NG 4 G Line Break Not Allowed NG 5 S Line Break Not Allowed NG 6 X Line Not Allowed NG 7 Y Line Not Allowed NG 8 White Spot D > 0.10mm NG 9 Black Spot D > 0.10mm NG 10 TPC Grid Not Allowed NG

[0061] Step S8, Output Electrical Measurement AOI Detection Defect Types and Results: The lighting electrical measurement types include: Station A1 / A2 on Side A, Station B1 / B2 on Side B. Their results are output separately without affecting each other; Output Result Z = A1, A2, B1, B2.

[0062] The beneficial effects of the present invention are: Compared with the existing technologies, the present invention proposes a method for appearance AOI detection of in-vehicle LCD screens. Based on the principle of high-definition original image acquisition by cameras and intelligent defect calculation, a new intelligent method for identifying appearance defects is proposed.

[0063] High detection accuracy: It can accurately identify various appearance defects, such as scratches, cracks, bubbles, missing corners, dirt, etc. It can detect defects as small as the micron level, effectively avoiding missed detections and misjudgments caused by factors such as visual fatigue and subjective judgment in manual inspection.

[0064] Fast detection speed: It can complete a comprehensive inspection of in-vehicle LCD screens in a short time. For example, for Tongguang semi-automatic medium-sized in-vehicle backlight automatic vision inspection machine, the test time is about 10 - 15s, which greatly improves production efficiency and meets the needs of large-scale production.

[0065] Strong stability: Once the detection parameters and standards are set, the AOI detection system can stably and continuously detect according to the standards without being interfered by external factors, ensuring that the detection quality of each in-vehicle LCD screen is consistent. It is difficult for manual inspection to maintain a stable detection level for a long time. It detects completely according to the preset standards and procedures, avoiding the differences caused by factors such as personal experience and subjective awareness in manual inspection, and the detection results are more objective and fair, providing a reliable basis for product quality evaluation.

[0066] Data statistics and analysis function: It can record and statistically analyze the detection data in detail, such as defect type, quantity, location, etc., and generate reports. By analyzing these data, it can help enterprises find out the problems and causes of defects in the production process, so as to optimize the production process and improve product quality.

[0067] Cost reduction: Although the procurement and maintenance of equipment require certain costs, in the long run, AOI detection technology can greatly reduce the workload and cost of manual inspection, and at the same time reduce the outflow of defective products caused by misjudgments in manual inspection, reducing after-sales costs and losses to the enterprise's reputation.

[0068] Embodiment 2

[0069] The second embodiment of this application provides a system for an AOI appearance detection method, which includes an appearance loading robot, an appearance platform, an electrical measurement loading robot, a machine tool PLC, a transfer mechanism, an appearance detection camera 3, an appearance detection UI host, an electrical measurement image acquisition camera, and a lighting electrical measurement UI host. The transfer mechanism includes a platform running X-axis 1 and a platform running Q-axis 2, as Figure 4As shown in the figure, the appearance platform is installed on the platform running Q-axis 2, and the platform running Q-axis 2 is used to drive the appearance platform to rotate. The platform running X-axis 1 is used to drive the platform running Q-axis 2 to reciprocate along the X-axis; the appearance loading robot is used to place the vehicle-mounted LCD screen to be tested on the appearance platform, and the transfer mechanism is used to transfer the appearance platform to the station of the appearance detection camera 3 for appearance detection and send the detection result to the appearance detection UI host. If the detection result is OK, the vehicle-mounted LCD screen is transferred to the station of the electrical measurement imaging camera by the electrical measurement loading robot for lighting, and the final result is output to the lighting electrical measurement UI host.

[0070] In the embodiment of the present application, as Figure 5 shown, the appearance platform includes a base 4 and six vacuum areas arranged on the vacuum base 4. The six vacuum areas include a first vacuum area 5, a second vacuum area 6, a third vacuum area 7, a fourth vacuum area 8, a fifth vacuum area 9, and a sixth vacuum area 10. The first vacuum area 5 and the fourth vacuum area 8 are respectively located at the upper left corner and the lower left corner on one side of the upper end surface of the vacuum base 4, and the third vacuum area 7 and the sixth vacuum area 10 are respectively located at the upper right corner and the lower right corner on the other side of the upper end surface of the vacuum base 4. The second vacuum area 6 and the fifth vacuum area 9 are respectively located at the upper side and the lower side in the middle of the upper end surface of the vacuum base 4; among them, a plurality of vacuum suction holes are provided in each vacuum area for adsorbing the vehicle-mounted LCD screen. Specifically, through the novel design of the appearance detection platform, it is designed into 6 independent vacuum areas, which can meet the electrode design of the vehicle-mounted LCD screen in the four directions of up, down, left, and right, and at the same time meet the A / B dual-channel operation process of the equipment, and be compatible with single / double electrodes of the vehicle-mounted LCD screen, enhancing the technical versatility.

[0071] Embodiment III

[0072] The embodiment III of the present application provides a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute the AOI appearance detection method of a vehicle-mounted LCD screen when the computer instructions are called.

[0073] Embodiment IV

[0074] The embodiment IV of the present application provides an electronic device, wherein the electronic device includes: a processor; and a memory arranged to store computer-executable instructions, and the executable instructions, when executed, cause the processor to execute the AOI appearance detection method of a vehicle-mounted LCD screen.

[0075] The above description is only a preferred embodiment of the present invention and does not impose any formal restrictions on the present invention. Although the present invention is disclosed above in a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art, without departing from the scope of the technical solution of the present invention, when making some changes or modifications using the above-disclosed technical content to equivalent embodiments of equivalent changes, as long as they do not depart from the content of the technical solution of the present invention, any simple modifications, equivalent changes and modifications made to the above embodiments according to the technical means of the present invention all fall within the scope of the technical solution of the present invention.

Claims

1. An AOI appearance detection method for in-vehicle LCD screens, characterized in that, Including the following steps: Step A1, Surface Appearance Detection: The appearance loading robot places the in-vehicle LCD screen to be tested on the appearance platform, drives the appearance platform to move into the image acquisition field of view of the appearance detection camera. After the machine tool PLC receives the image acquisition instruction, it performs image acquisition. After the acquisition is completed, according to the preset appearance data processing method, the final result is output to the appearance detection UI host; Step A2, Electrode Front and Back Detection: After the surface appearance detection is completed, the initial electrode front and back synchronous detection is carried out. The machine tool PLC receives the image acquisition instruction to perform image acquisition. After the initial acquisition is completed, according to the preset data processing method, the final result is output to the appearance detection UI host; When it is necessary to detect the in-vehicle LCD screen with double electrodes, the machine tool PLC sends a signal to control the appearance platform to move into place to perform the second electrode front and back synchronous detection. According to the preset appearance data processing method, the final result is output to the appearance detection UI host; Step A3, Merging and Processing of Appearance Detection Results: After both the surface external detection and the electrode front and back detection are completed, finally the appearance detection UI host gives the final "union" result as OK or NG; If the result is OK, the machine tool PLC sends a signal to Step A4 for lighting and electrical testing; If the result is NG, the machine tool PLC sends a signal to the unloading and placing in Warehouse C for processing; Step A4, Lighting and Electrical Testing of LCD Screen: The electrical testing loading robot places the in-vehicle LCD screen that needs to be lit and electrically tested on the electrical testing station, lights it through the power-on and the electrical testing AOI software controls the lighting program, and flips it during the lighting process. The electrical testing image acquisition camera collects the images of each frame during the flipping process. According to the preset electrical testing data processing method, the final result is output to the lighting and electrical testing UI host; Step A5, Processing of the Results of the LCD Screen Power Lighting Detection: The results of the lighting and electrical testing at each work station are transmitted to the lighting and electrical testing UI host for data induction and summary. Finally, the lighting and electrical testing UI host gives the data consistent with the work station results; If the result is an OK product, the machine tool PLC sends a signal to the unloading mechanism to place the OK product in Warehouse A; If the result is an NG product, the machine tool PLC sends a signal to the unloading mechanism to place the NG product in Warehouse B.

2. The AOI appearance detection method for an in-vehicle LCD screen according to claim 1, wherein, The appearance data processing method includes the following steps: Step S1, Machine Model Appearance AOI Inspection Modeling: According to the name, resolution and size parameters of the LCD screen model, set the corresponding machine model; Step S2, According to the established corresponding machine model, refer to the MSA sample and the appearance defect detection requirements in the SOP of the corresponding process for parameter setting; Step S3, Appearance MSA Training and Trial Run Evaluation: According to the defect categories of the selected appearance MSA samples, run the film for each defect corresponding parameter table to collect the corresponding defect pictures, set the parameter details for the defects outside the specifications, and set the corresponding parameters for the defects within the specifications to the default OK; Step S4, Output Appearance AOI Detection Defect Types and Results: The appearance detection types include: a - Appearance Surface Inspection, b - Front Electrode Inspection, and c - Back Electrode Inspection. The final output result is: Output Result Z = a ∪ b ∪ c.

3. The AOI appearance detection method for an in-vehicle LCD screen according to claim 1, characterized in that The described electrical measurement data processing method includes the following steps: Step S5: If the appearance detection UI host gives the final "union" result as OK, output the result to the lighting electrical measurement process and establish an electrical measurement model for the model type. Step S6: According to the established electrical measurement model for the model type, refer to the lighting electrical measurement MSA template and the detection requirements for lighting electrical measurement defects in the SOP of the corresponding process to set parameters. Step S7: Based on the defect categories of the selected electrical measurement MSA template, run the wafer to collect corresponding defect pictures for each parameter table corresponding to each defect, set the parameter details for defects outside the specifications, and set the corresponding parameters for defects within the specifications as the default OK. Step S8: Output the defect types and results of the electrical measurement AOI detection: The lighting electrical measurement types include: Station A1 / A2 on side A, Station B1 / B2 on side B, and their results are output separately without affecting each other. The output result Z = A1, A2, B1, B2.

4. A system for the AOI appearance detection method of the in-vehicle LCD screen according to claims 1-3, characterized in that: It includes an appearance loading robot, an appearance platform, an electrical measurement loading robot, a machine tool PLC, a transfer mechanism, an appearance detection camera, an appearance detection UI host, an electrical measurement image acquisition camera, and a lighting electrical measurement UI host. The transfer mechanism includes a platform running X-axis and a platform running Q-axis. The appearance platform is installed on the platform running Q-axis. The platform running Q-axis is used to drive the appearance platform to rotate, and the platform running X-axis is used to drive the platform running Q-axis to reciprocate along the X-axis. The appearance loading robot is used to place the on-vehicle LCD screen to be measured on the appearance platform. The transfer mechanism is used to transfer the appearance platform to the station of the appearance detection camera for appearance detection and send the detection result to the appearance detection UI host. If the detection result is OK, the on-vehicle LCD screen is transferred to the station of the electrical measurement image acquisition camera by the electrical measurement loading robot for lighting, and the final result is output to the lighting electrical measurement UI host.

5. A system for the AOI appearance detection method according to claim 4, characterized in that: The appearance platform includes a base and six vacuum areas arranged on the vacuum base. The six vacuum areas include a first vacuum area, a second vacuum area, a third vacuum area, a fourth vacuum area, a fifth vacuum area, and a sixth vacuum area. The first vacuum area and the fourth vacuum area are respectively located at the upper corner and the lower corner on one side of the upper end surface of the vacuum base. The third vacuum area and the sixth vacuum area are respectively located at the upper corner and the lower corner on the other side of the upper end surface of the vacuum base. The second vacuum area and the fifth vacuum area are respectively located on the upper side and the lower side in the middle of the upper end surface of the vacuum base.

6. A computer storage medium stores computer instructions, which are used to execute an AOI appearance detection method for an on-vehicle LCD screen as described in any one of claims 1-3 when the computer instructions are called.

7. An electronic device, wherein, The electronic device includes: a processor; and a memory arranged to store computer-executable instructions, and the executable instructions, when executed, cause the processor to execute an AOI appearance detection method for an on-vehicle LCD screen as described in any one of claims 1-3.

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