Detection device, surface defect detection method, device, equipment and storage medium

Abstract

The application discloses a kind of detection device, surface defect detection method, device, equipment and storage medium, it is related to automobile technical field, it aims at solving when artificial detection product surface defect, the accuracy of identifying defect is lower, and then the grade of product cannot be accurately determined, lead to the processing effect of subsequent product is poor.The device comprises: fixed platform, for placing the object to be detected;Multiple vision sensors, multiple vision sensors are used to shoot the image data of different parts of the surface of the object to be detected;Controller, connected with multiple vision sensors, for obtaining the image data of different parts of the surface of the object to be detected;Based on the image data of different parts of the surface of the object to be detected, obtain the defect identification result of different parts of the surface of the image to be detected;Based on the defect identification result of different parts of the surface of the image to be detected, output the defect grade of the object to be detected.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a detection device, surface defect detection method, apparatus, equipment, and storage medium. Background Technology

[0002] In the processing of products made of different materials (such as semiconductor crystals), each step in the manufacturing process introduces defects to the product's surface. Different surface defects result in different product grades, and different grades require different subsequent processing techniques. Therefore, accurately detecting surface defects and determining the product grade is crucial for improving the quality of downstream processes and reducing their processing costs. Currently, surface defect detection relies on manual identification under strong light conditions to determine the product grade.

[0003] However, when manually inspecting product surfaces for defects, the accuracy of visual defect identification is low, and different people may identify different defects, making it impossible to accurately determine the product's grade and resulting in poor subsequent processing. This leads to low accuracy in defect detection. Summary of the Invention

[0004] The purpose of this invention is to provide a detection device, surface defect detection method, apparatus, equipment, and storage medium, which aims to solve the problem that when manually inspecting product surfaces, the accuracy of defect identification is low, which makes it impossible to accurately determine the product grade and leads to poor subsequent processing results.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, a detection device is provided, comprising: a fixed stage for placing an object to be detected; multiple vision sensors for capturing image data of different parts of the surface of the object to be detected; a controller connected to the multiple vision sensors for acquiring image data of different parts of the surface of the object to be detected; obtaining defect identification results of different parts of the surface of the object to be detected based on the image data of different parts of the surface of the object to be detected; and outputting the defect level of the object to be detected based on the defect identification results of different parts of the surface of the object to be detected.

[0007] In some embodiments, the fixed platform includes: a platform, an air connector, and a vacuum source; an air channel is provided on the platform; the air channel is connected to the vacuum source through the air connector; the vacuum source generates negative pressure, which is transmitted to the air channel through the air connector, so that the platform adsorbs the object to be tested.

[0008] In some embodiments, the fixed stage further includes a rotary motor disposed below the stage surface, the rotary motor rotating to drive the stage surface and the object to be tested on the stage surface to rotate.

[0009] In some embodiments, the plurality of vision sensors include at least: a first vision sensor, a second vision sensor, and a third vision sensor; the detection end of the first vision sensor is opposite to a first part of the object to be detected, so that the first vision sensor acquires image data of the first part; the first part includes the upper surface and top edge of the object to be detected; the detection end of the second vision sensor is opposite to a second part of the object to be detected, so that the second vision sensor acquires image data of the second part; the second part includes the lower surface and bottom edge of the object to be detected; the detection end of the third vision sensor is opposite to the second part of the object to be detected, so that the third vision sensor acquires image data of a third part; the third part includes the side surface of the object to be detected.

[0010] In some embodiments, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0011] In some embodiments, the detection device further includes: a plurality of light sources; the plurality of light sources are used to illuminate the object to be detected.

[0012] In some embodiments, the plurality of light sources include at least: a first light source and a second light source; the light outlet of the first light source is opposite to a first part of the object to be tested, so that the first light source illuminates the first part; the first part includes the upper surface and top edge of the object to be tested; the light outlet of the second light source is opposite to a second part of the object to be tested, so that the second light source illuminates the second part; the second part includes the lower surface and bottom edge of the object to be tested.

[0013] In some embodiments, the defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

[0014] Secondly, a surface defect detection method is provided, the method comprising: acquiring image data of different parts of the surface of the object to be detected during the rotation of the object to be detected; obtaining defect identification results of different parts of the surface of the object to be detected based on the image data of different parts of the surface of the object to be detected; and outputting the defect level of the object to be detected based on the defect identification results of different parts of the surface of the object to be detected.

[0015] In some embodiments, different parts of the surface of the object to be tested include: a first part, a second part, and a third part; the first part includes the upper surface and top edge of the object to be tested; the second part includes the lower surface and bottom edge of the object to be tested; and the third part includes the side surface of the object to be tested.

[0016] In some embodiments, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0017] In some embodiments, the defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

[0018] In some embodiments, based on image data of different parts of the surface of the object to be detected, defect identification results of different parts of the surface of the image to be detected are obtained, including: based on the detection algorithms corresponding to the image data of different parts, the image data of different parts are analyzed and processed to obtain defect identification results of different parts.

[0019] Thirdly, a surface defect detection device is provided, comprising: a transmission module and a processing module; the transmission module is used to acquire image data of different parts of the surface of the object to be detected during the rotation of the object to be detected; the processing module is used to obtain defect identification results of different parts of the surface of the object to be detected based on the image data of different parts of the surface of the object to be detected; the processing module is also used to output the defect level of the object to be detected based on the defect identification results of different parts of the surface of the object to be detected.

[0020] In some embodiments, different parts of the surface of the object to be tested include: a first part, a second part, and a third part; the first part includes the upper surface and top edge of the object to be tested; the second part includes the lower surface and bottom edge of the object to be tested; and the third part includes the side surface of the object to be tested.

[0021] In some embodiments, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0022] In some embodiments, the defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

[0023] In some embodiments, the processing module is further configured to analyze and process the image data of different parts based on the detection algorithms corresponding to the image data of different parts, and obtain the defect identification results of different parts.

[0024] Fourthly, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the methods of the second aspect described above and any possible implementation thereof.

[0025] Fifthly, a computer-readable storage medium is provided, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the methods of the second aspect and any possible implementation thereof.

[0026] In a sixth aspect, a computer program product is provided, comprising computer instructions that, when executed on an electronic device, cause the electronic device to perform the method described in the second aspect and any possible implementation thereof.

[0027] This application provides a detection device in which multiple vision sensors can capture image data of different parts of the surface of an object to be inspected, placed on a fixed platform. Furthermore, the controller of the detection device can obtain defect identification results for different parts based on the image data, and output the defect level of the object to be inspected based on the defect identification results for different parts.

[0028] In other words, defects typically vary across different parts of the surface of an object to be inspected. Therefore, by using a vision sensor matched to the specific area, more accurate defect identification results can be obtained. The defect identification results for different areas reflect the degree of defect at those areas; the greater the defect degree, the higher the defect grade. This facilitates subsequent processing of the object based on the defect grade, improving the effectiveness of subsequent processing. This solves the technical problem of low accuracy in defect identification during manual inspection of product surfaces, which leads to an inability to accurately determine the product grade and consequently, poor subsequent processing results, thus improving the accuracy of defect detection. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 A schematic diagram of the structure of a detection device provided in one embodiment of this application;

[0031] Figure 2 A schematic diagram of the structure of a fixed platform provided in one embodiment of this application;

[0032] Figure 3 A schematic diagram of the structure of an object to be detected is provided for one embodiment of this application;

[0033] Figure 4 A schematic diagram of the structure of a surface defect detection system provided in one embodiment of this application;

[0034] Figure 5 A flowchart illustrating a surface defect detection method provided in one embodiment of this application. Figure 1 ;

[0035] Figure 6 A flowchart illustrating a surface defect detection method provided in one embodiment of this application. Figure 2 ;

[0036] Figure 7 A software architecture diagram of a surface defect detection method provided for one embodiment of this application;

[0037] Figure 8 A block diagram of a surface defect detection device provided in one embodiment of this application;

[0038] Figure 9 A block diagram of an electronic device provided for one embodiment of this application. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" and "second" may explicitly or implicitly include one or more of that feature.

[0041] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a communication between the internal components of two elements. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0042] In embodiments of the invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0043] In embodiments of the present invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in embodiments of the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0044] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0045] In the product processing process, defects are inevitable at every step. If defective products flow into the next step, it will cause a waste of production resources and costs. Therefore, timely detection of defective products is extremely important for reducing product processing costs.

[0046] Ingots are the most upstream product in semiconductor crystal processing and one of the most crucial technological steps. Different surface defects lead to different ingot grades, and the subsequent processing techniques for ingots of different grades vary significantly. Therefore, timely detection of ingot defects and accurate determination of ingot grade are essential for improving the quality and reducing the processing costs of downstream processes. In current ingot processing, defects are mainly detected manually under strong light conditions using the naked eye. This method is not only inefficient but also inconsistent.

[0047] To address the aforementioned issues, this application provides a surface defect detection method. This method uses multiple vision sensors installed at different locations to acquire images of different parts of the ingot surface, comprehensively obtaining visual information from various areas. Based on the fusion and comprehensive analysis of multiple defect detection algorithms corresponding to the multiple vision sensors, different types of surface defects on the ingot surface are detected. This enables the detection of different types of defects on different parts of the ingot surface, achieving ingot grade classification under multi-part, multi-defect conditions. Furthermore, during the image acquisition process, a specific method is used to stably fix the ingot, preventing positional movement during image acquisition. This avoids the risk of ingot damage due to falling and improves data acquisition stability. Moreover, the method can acquire not only two-dimensional images of the ingot surface but also three-dimensional images, thereby improving the accuracy of defect detection.

[0048] In other words, this application can stably and accurately collect surface information from different parts and dimensions of the ingot surface, and combine multiple detection algorithms for comprehensive detection and analysis, thereby accurately detecting different types of defects in different parts of the ingot surface, and accurately determining the production grade of the ingot based on the type of surface defects, providing an important basis for improving the quality of downstream processes and reducing the processing costs of downstream processes.

[0049] Figure 1 This is a schematic diagram of a detection device provided for one embodiment of this application. Figure 1 As shown, the detection device 10 includes: a fixed stage 11, a vision sensor 12, a vision sensor 13, a vision sensor 14, a controller 15, an object to be detected 16, a light source 17, and a light source 18.

[0050] This application provides a detection device 10, which includes: a fixed stage 11 for placing an object 16 to be detected; multiple vision sensors for capturing image data of different parts of the surface of the object 16; and a controller 15 connected to the multiple vision sensors (i.e., ...). Figure 1 The system connects vision sensors 12, 13, and 14 to acquire image data of different parts of the surface of the object 16 to be inspected. Based on the image data of different parts of the surface of the object 16 to be inspected, defect identification results of different parts of the surface of the object 16 to be inspected are obtained. Based on the defect identification results of different parts of the surface of the object 16 to be inspected, the defect level of the object to be inspected is output.

[0051] Optionally, the object to be detected 16 can be a columnar semiconductor crystal product, such as polycrystalline silicon, monocrystalline silicon, silicon carbide, etc. Image data can include two-dimensional image data and three-dimensional image data. The image data can be image data processed by image processing operations, which can include operations such as clipping and merging.

[0052] Defect identification results may include at least one of the following: the number of defects, the size of the defects, the type of the defects, and the location of the defects. The size of the defects may be the average diameter of the defects. The type of defects may be a protrusion, a depression, a crack, or a bright spot, etc.

[0053] The controller 15 can obtain the score of a certain part of a certain object based on the score of each defect identification result and the weight of each defect identification result. Furthermore, the scores of each part of different parts are added together to obtain the total score of the object to be inspected, and the defect level of the object to be inspected is obtained based on the total score of the object to be inspected.

[0054] For example, suppose there are multiple vision sensors, namely, three vision sensors. Figure 1 The system includes vision sensors 12, 13, and 14. Vision sensor 12 acquires image data of a first portion of the surface of the object 16 to be inspected. Vision sensor 13 acquires image data of a second portion of the surface of the object 16 to be inspected. Vision sensor 14 acquires image data of a third portion of the surface of the object 16 to be inspected.

[0055] So, assuming the number of defects is 0-5, the score is 3; the number of defects is 6-10, the score is 5; and the number of defects is more than 10, the score is 10. Assuming the average diameter of the defects is 0-0.5 micrometers, the score is 3; the average diameter of the defects is 0.6-1 micrometer, the score is 5; and the average diameter of the defects is more than 1 micrometer, the score is 10. A bright spot type of defect scores 3; a protrusion or depression type scores 5; and a crack type scores 10. A defect located in the central region scores 10; and a defect located in the edge region scores 5.

[0056] So, assuming the first part has 3 defects, an average defect diameter of 1.7 micrometers, a defect type of crack, and is located in the central region of the first part, then the score for the first part is 3 + 5 + 10 + 10 = 28 points. Similarly, if the score for the second part is 20 points and the score for the third part is 25 points, then the total score for the object under inspection is 28 + 20 + 25 = 75 points.

[0057] Let's assume that when the score of the object to be inspected is 0-40, the defect level is Level 1; when the score is 41-80, the defect level is Level 2; and when the score is 81-120, the defect level is Level 3. Therefore, the defect level of this object to be inspected is Level 2.

[0058] It should be noted that the determination of the defect level of the object to be inspected is usually closely related to parameters such as the number of defects, the size of defects, the type of defects, and the location of defects. Therefore, by comprehensively analyzing parameters such as the number of defects, the size of defects, the type of defects, and the location of defects, a reasonable determination of the level of the object to be inspected can be formed.

[0059] The grade of the object to be tested can provide an important basis for improving the quality of downstream processes and reducing their processing costs. When the grade of the object to be tested is high (e.g., grade 1), the quality of the downstream processes needs to be high, and the processing costs will also be higher. When the grade of the object to be tested is low (e.g., grade 3), the quality of the downstream processes can be lower, and the processing costs will also be lower.

[0060] As one possible implementation method, Figure 2 This is a schematic diagram of a fixed platform provided for one embodiment of this application. Figure 2 As shown, the fixed platform 11 includes: a platform 111, an air connector 112, and a vacuum source 113; an air channel 1111 is provided on the platform 111; the air channel 1111 is connected to the vacuum source 113 through the air connector 112; the vacuum source 113 generates negative pressure, which is transmitted to the air channel 1111 through the air connector 112, so that the platform 111 adsorbs the object to be tested 16.

[0061] This application uses a fixed stage to adsorb the object to be detected, which can fix the ingot and avoid the ingot from moving or falling during the process of the vision sensor acquiring the image of the object to be detected, which would lead to inaccurate image acquisition or damage caused by the ingot falling, thus improving the stability of data acquisition.

[0062] As one possible implementation, such as Figure 2 As shown, the fixed stage 11 also includes a rotary motor 114, which is located below the stage 111. The rotary motor 114 rotates to drive the stage 111 and the object to be tested 16 on the stage 111 to rotate.

[0063] This application utilizes a rotary motor to rotate the object to be inspected at a certain speed, thereby ensuring that the vision sensor system can acquire image data from different positions on the surface of the object to be inspected, that is, acquire complete image data of the surface of the object to be inspected, thereby improving the accuracy of subsequent detection of defects in the object to be inspected.

[0064] As one possible implementation, such as Figure 1 As shown, the multiple vision sensors include at least: a first vision sensor (i.e., vision sensor 12), a second vision sensor (i.e., vision sensor 13), and a third vision sensor (i.e., vision sensor 14).

[0065] Figure 3 This is a schematic diagram of the structure of an object to be detected, provided as an embodiment of this application. Figure 3 As shown, the object to be inspected 16 includes a first part, a second part, and a third part. The first part includes the upper surface 161 and the top edge 162 of the object to be inspected 16. The second part includes the lower surface 163 and the bottom edge 164 of the object to be inspected 16. The third part includes the side surface 165 of the object to be inspected 16.

[0066] The detection end of the first visual sensor is positioned opposite a first portion of the object to be detected 16, enabling the first visual sensor to acquire image data of the first portion. The detection end of the second visual sensor is positioned opposite a second portion of the object to be detected, enabling the second visual sensor to acquire image data of the second portion. The detection end of the third visual sensor is positioned opposite the second portion of the object to be detected, enabling the third visual sensor to acquire image data of a third portion. The third portion includes the side surface of the object to be detected.

[0067] Optionally, the first vision sensor can be an industrial camera, the second vision sensor can be an industrial camera, and the parameters of the first vision sensor and the second vision sensor are different. The third vision sensor can be a line scan camera.

[0068] It should be noted that since different parts of the object to be detected have different reflective properties, smoothness, and other characteristics, the visual sensors used to collect data from different parts are also different. Using a visual sensor that matches the characteristics of a particular part to collect image data from that part can improve the accuracy of the collected image data.

[0069] This application can acquire images of different parts of the surface of the object to be inspected through multiple vision sensors, and can comprehensively obtain visual information of different parts, thereby improving the accuracy of subsequent detection of defects in the object to be inspected and determining the grade of the object to be inspected.

[0070] As one possible implementation, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0071] Optionally, the first and second vision sensors can be used to acquire two-dimensional image data. The third vision sensor can be used to acquire both two-dimensional and three-dimensional image data.

[0072] The two-dimensional image data for the first and second parts can be image data containing two-dimensional information such as color and brightness. The two-dimensional image data for the third part can be a grayscale image containing two-dimensional information such as brightness, and the three-dimensional image data can be a depth image containing three-dimensional information such as depth and point clouds. The image data for the third part can be obtained by image fusion of the grayscale image and the depth image of the third part.

[0073] This application can utilize the characteristics of the side surface of the object under inspection to acquire two-dimensional and three-dimensional image data of the side surface of the object under inspection, and obtain fused image data, thereby better presenting the surface defect characteristics of the object under inspection. Furthermore, acquiring two-dimensional and three-dimensional image data of the ingot surface through a vision sensor can improve the accuracy of defect detection.

[0074] As one possible implementation, the detection device 10 also includes: multiple light sources; the multiple light sources are used to illuminate the object to be detected.

[0075] like Figure 1 As shown, multiple light sources can be two light sources, namely... Figure 1 Light source 17 and light source 18 in the image.

[0076] Alternatively, multiple light sources can be adjusted to suitable lighting conditions individually.

[0077] The light source in this application can provide illumination conditions, thereby improving the accuracy of image data acquired by the vision sensor.

[0078] As one possible implementation, such as Figure 1 As shown, the multiple light sources include at least a first light source (i.e., light source 17) and a second light source (i.e., light source 18). The light outlet of the first light source is opposite to a first part of the object to be tested, so that the first light source illuminates the first part. The first part includes the upper surface and top edge of the object to be tested. The light outlet of the second light source is opposite to a second part of the object to be tested, so that the second light source illuminates the second part. The second part includes the lower surface and bottom edge of the object to be tested.

[0079] It should be noted that industrial cameras used to acquire image data of the first and second locations require a light source to accurately acquire the image data of those locations. However, line scan cameras used to acquire the third location can accurately acquire image data of that location without requiring a light source.

[0080] This application can use appropriate light sources to illuminate the image based on the characteristics of the vision sensor, thereby improving the accuracy of the image data acquired by the vision sensor.

[0081] Figure 4 A schematic diagram of the structure of a surface defect detection system provided in one embodiment of this application; as shown Figure 4 As shown, the surface defect detection system 20 (i.e., the controller) includes: a target object fixing module 21, a motor control module 22, a vision sensor control module 23, a light source control module 24, a defect detection module 25, an image fusion module 26, and a defect analysis module 27.

[0082] The vision sensor control module 23 includes a first vision sensor control module 231, a second vision sensor control module 232, and a third vision sensor control module 233. The light source control module 24 includes a first light source control module 241 and a second light source control module 242. The defect detection module 25 includes a first defect detection module 251, a second defect detection module 252, and a third defect detection module 253.

[0083] The object-to-be-detected fixing module 21 is used to control the fixing stage to adsorb the object to be detected; the motor control module 22 is used to control the rotation of the rotary motor; the first vision sensor control module 231 is used to control the first vision sensor to capture image data of the first part of the object to be detected; the second vision sensor control module 232 is used to control the second vision sensor to capture image data of the second part of the object to be detected; and the third vision sensor control module 233 is used to control the third vision sensor to capture image data of the third part of the object to be detected.

[0084] The first light source control module 241 is used to control the first light source; the second light source control module 242 is used to control the second light source; the first defect detection module 251 is used to detect the image data of the first part captured by the first vision sensor based on the first detection algorithm corresponding to the first vision sensor, and obtain the defect identification result of the first part; the second defect detection module 252 is used to detect the image data of the second part captured by the second vision sensor based on the second detection algorithm corresponding to the second vision sensor, and obtain the defect identification result of the second part; the third defect detection module 253 is used to detect the image data of the third part captured by the second vision sensor based on the third detection algorithm corresponding to the third vision sensor, and obtain the defect identification result of the third part.

[0085] The image fusion module 26 is used to fuse the two-dimensional image data and three-dimensional image data of the third part to obtain the fused image data; the defect analysis module 27 is used to comprehensively analyze the defect identification results of the first part, the second part and the third part, and output the level of the object to be detected.

[0086] Figure 5 A schematic flowchart of a surface defect detection method provided in one embodiment of this application, applied to a controller, such as... Figure 5 As shown, the surface defect detection method includes the following steps:

[0087] S301. During the rotation of the object to be detected, acquire image data of different parts of the surface of the object to be detected.

[0088] Optionally, the controller's object-to-be-obtained (OTB) fixing module can control the fixing stage to adsorb the OTB, while the controller's light source control module can control the light source to turn on and illuminate the OTB. The controller's motor control module can control the rotary motor to start rotating, thereby rotating the OTB. During the rotation of the OTB, the controller's vision sensor control module can control multiple vision sensors to capture image data of different parts of the OTB's surface. Furthermore, the controller's defect detection module can acquire image data of different parts of the OTB's surface.

[0089] For example, the image data of different parts of the surface of the object to be detected can be image data collected during the process of the object rotating one, two, or three times.

[0090] S302. Based on image data of different parts of the surface of the object to be inspected, obtain the defect identification results of different parts of the surface of the image to be inspected.

[0091] Optionally, the defect identification results may include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

[0092] The controller's defect detection module can perform image processing operations on image data from different parts to obtain image data after image processing.

[0093] Based on image data from different parts after image processing, the controller's defect detection module can obtain defect identification results for different parts of the surface of the image to be detected through detection algorithms.

[0094] In one possible implementation, Figure 6 A schematic flowchart of a surface defect detection method provided for one embodiment of this application is shown below. Figure 6 As shown, step S302 specifically includes the following steps:

[0095] S401. Based on the detection algorithms corresponding to the image data of different parts, the image data of different parts are analyzed and processed to obtain the defect identification results of different parts.

[0096] Optionally, based on the detection algorithms corresponding to the image data of different parts, the defect analysis module of the controller can analyze and process the image data of different parts to obtain the defect identification results of different parts.

[0097] For example, suppose the multiple vision sensors include a first vision sensor, a second vision sensor, and a third vision sensor. Then, the detection algorithm corresponding to the first vision sensor can be a first detection algorithm, the detection algorithm corresponding to the second vision sensor can be a second detection algorithm, and the detection algorithm corresponding to the third vision sensor can be a third detection algorithm.

[0098] It should be noted that the image data for different parts are obtained by different vision sensors. The image data obtained by different vision sensors need to be analyzed and processed by the corresponding detection algorithms of the vision sensors in order to improve the accuracy of defect identification.

[0099] This application can detect defects in different images based on images acquired by multiple vision sensors, and obtain defect identification results for different parts, thereby improving the accuracy of defect identification.

[0100] S303. Based on the defect identification results of different parts of the surface of the image to be detected, output the defect level of the object to be detected.

[0101] Optionally, based on the defect identification results of different parts of the surface of the image to be detected, the defect analysis module of the controller can output the defect level of the object to be detected.

[0102] In one possible implementation, the different parts of the surface of the object to be detected include: a first part, a second part, and a third part; the first part includes the upper surface and top edge of the object to be detected; the second part includes the lower surface and bottom edge of the object to be detected; and the third part includes the side surface of the object to be detected.

[0103] Optionally, the controller's object-to-be-detected fixing module can control the fixing stage to adsorb the object to be detected. Simultaneously, the controller's first light source control module can control the first light source to turn on, illuminating the first part. The controller's second light source control module can control the second light source to turn on, illuminating the second part.

[0104] Furthermore, the controller's motor control module can control the rotary motor to start rotating, thereby rotating the object to be detected. Simultaneously, the controller's first vision sensor control module can control the first vision sensor to capture image data of a first part of the object to be detected. The controller's second vision sensor control module can control the second vision sensor to capture image data of a second part of the object to be detected. The controller's third vision sensor control module can control the third vision sensor to capture image data of a third part of the object to be detected.

[0105] Furthermore, the controller's first defect detection module can detect the image data of a first part captured by the first vision sensor based on the first detection algorithm corresponding to the first vision sensor, and obtain the defect identification result of the first part. The controller's second defect detection module can detect the image data of a second part captured by the second vision sensor based on the second detection algorithm corresponding to the second vision sensor, and obtain the defect identification result of the second part. The controller's third defect detection module can detect the image data of a third part captured by the second vision sensor based on the third detection algorithm corresponding to the third vision sensor, and obtain the defect identification result of the third part.

[0106] In one possible implementation, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0107] Optionally, for the image data of the third part, the image fusion module of the controller can fuse the two-dimensional image data and the three-dimensional image data of the third part to obtain the fused image data, and obtain the defect identification result of the third part based on the fused image data.

[0108] It should be noted that in the process of acquiring surface images of the object to be inspected based on multiple vision sensors, and in the process of detecting surface defects by multiple detection algorithms, in order to ensure that each step can be carried out synchronously, a multi-threaded parallel approach needs to be adopted in the software architecture.

[0109] In one possible embodiment, Figure 7 A software architecture diagram of a surface defect detection method provided for one embodiment of this application is shown below. Figure 7 As shown, the software architecture diagram includes: 1 main thread and 3 sub-threads (i.e., sub-thread 1, sub-thread 2 and sub-thread 3).

[0110] The main thread initializes the hardware and software, and starts sub-threads 1, 2, and 3. Further, in the main thread, the object-to-be-detected fixing module controls the fixing platform to attract the object to be detected. Simultaneously, in sub-thread 1, the first light source control module activates the first light source, and in sub-thread 2, the second light source control module activates the second light source. Further, in the main thread, the motor control module controls the rotary motor to start rotating. Simultaneously, in sub-thread 1, the first vision sensor control module controls the first vision sensor to periodically capture image data of the first part; in sub-thread 2, the second vision sensor control module controls the second vision sensor to periodically capture image data of the second part; and in sub-thread 3, the third vision sensor control module controls the third vision sensor to periodically capture two-dimensional and three-dimensional image data of the third part.

[0111] Furthermore, when the rotary motor completes a full rotation, in the main thread, the motor control module controls the rotary motor to stop rotating. At the same time, in sub-thread 1, the first vision sensor control module controls the first vision sensor to stop capturing image data of the first part. In sub-thread 2, the second vision sensor control module controls the second vision sensor to stop capturing image data of the second part. And in sub-thread 3, the third vision sensor control module controls the third vision sensor to stop capturing two-dimensional and three-dimensional image data of the third part.

[0112] Furthermore, in sub-thread 1, the first light source is turned off by the first light source control module, and simultaneously, in sub-thread 2, the second light source is turned off by the second light source control module. Also, in sub-thread 3, the image fusion module fuses the two-dimensional and three-dimensional image data of the third part to obtain the fused image data. Further, in sub-thread 1, the first detection algorithm of the first defect detection module detects the image data of the first part to obtain the defect identification result of the first part; simultaneously, in sub-thread 2, the second detection algorithm of the second defect detection module detects the image data of the second part to obtain the defect identification result of the second part; and in sub-thread 3, the third detection algorithm of the third defect detection module detects the fused image data to obtain the defect identification result of the third part. Finally, in the main thread, the defect analysis module comprehensively analyzes the defect identification results of the first, second, and third parts and outputs the level of the object to be detected.

[0113] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the surface defect detection device or electronic device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] This application embodiment can, according to the above method, exemplarily divide a surface defect detection device or electronic device into functional modules. For example, the surface defect detection device or electronic device may include functional modules corresponding to each functional division, or two or more functions may be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0115] Figure 8 A block diagram of a surface defect detection device provided in one embodiment of this application. (Refer to...) Figure 8 The surface defect detection device 110 includes a transmission module 1101 and a processing module 1102.

[0116] The transmission module 1101 is used to acquire image data of different parts of the surface of the object to be inspected during the rotation of the object to be inspected; the processing module 1102 is used to obtain defect identification results of different parts of the surface of the object to be inspected based on the image data of different parts of the surface of the object to be inspected; the processing module 1102 is also used to output the defect level of the object to be inspected based on the defect identification results of different parts of the surface of the object to be inspected.

[0117] In some embodiments, different parts of the surface of the object to be tested include: a first part, a second part, and a third part; the first part includes the upper surface and top edge of the object to be tested; the second part includes the lower surface and bottom edge of the object to be tested; and the third part includes the side surface of the object to be tested.

[0118] In some embodiments, the image data of the first and second parts are two-dimensional image data; the image data of the third part is a combination of two-dimensional and three-dimensional image data.

[0119] In some embodiments, the defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

[0120] In some embodiments, the processing module 1102 is further configured to analyze and process the image data of different parts based on the detection algorithms corresponding to the image data of different parts, and obtain the defect identification results of different parts.

[0121] Figure 9 This is a block diagram of an electronic device provided as an embodiment of this application. Figure 9 As shown, the electronic device 130 includes, but is not limited to, a processor 1301 and a memory 1302.

[0122] The memory 1302 described above is used to store the executable instructions of the processor 1301. It is understood that the processor 1301 is configured to execute instructions to implement the surface defect detection method in the above embodiments.

[0123] It should be noted that those skilled in the art will understand that Figure 9 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 9 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0124] Processor 1301 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 1302, and by calling data stored in memory 1302, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Processor 1301 may include one or more processing modules. Optionally, processor 1301 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 1301.

[0125] The memory 1302 can be used to store software programs and various data. The memory 1302 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and application programs required by at least one functional module (such as an acquisition unit, a determination module, a processing unit, etc.). Furthermore, the memory 1302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0126] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 1302 including instructions, which can be executed by a processor 1301 of an electronic device 130 to implement the surface defect detection method in the above embodiments.

[0127] In actual implementation, Figure 8 The functions of the transmission module 1101 and the processing module 1102 can both be provided by Figure 9 The processor 1301 calls the computer program stored in the memory 1302 to implement the function. The specific execution process can be found in the description of the surface defect detection method section of the previous embodiment, and will not be repeated here.

[0128] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device.

[0129] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by the processor 1301 of an electronic device to complete the surface defect detection method described above.

[0130] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of the electronic device, they implement the various processes of the above-described surface defect detection method embodiments and achieve the same technical effect as the above-described surface defect detection method. To avoid repetition, they will not be described again here.

[0131] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0132] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0133] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the classified units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, essentially, or the part that contributes to related technologies, or the entirety or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute the entirety or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0136] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A detection device, characterized in that, The detection device includes: A fixed platform is used to place the object to be inspected. Multiple vision sensors are used to capture image data of different parts of the surface of the object to be detected. The controller is connected to the plurality of vision sensors to acquire image data of different parts of the surface of the object to be inspected; based on the image data of different parts of the surface of the object to be inspected, it obtains the defect identification results of different parts of the surface of the image to be inspected; based on the defect identification results of different parts of the surface of the image to be inspected, it outputs the defect level of the object to be inspected. The plurality of vision sensors include at least: a first vision sensor, a second vision sensor, and a third vision sensor; The detection end of the first visual sensor is opposite to a first part of the object to be detected, so that the first visual sensor can acquire image data of the first part; the first part includes the upper surface and top edge of the object to be detected; The detection end of the second visual sensor is opposite to the second part of the object to be detected, so that the second visual sensor can acquire image data of the second part; the second part includes the lower surface and bottom edge of the object to be detected; The detection end of the third visual sensor is opposite to the second part of the object to be detected, so that the third visual sensor can acquire image data of the third part; the third part includes the side of the object to be detected; The image data of the first and second parts are two-dimensional image data; the image data of the third part is both two-dimensional and three-dimensional image data.

2. The detection device according to claim 1, characterized in that, The fixed platform includes: a platform, an air connector, and a vacuum source; an air channel is provided on the platform; the air channel is connected to the vacuum source through the air connector; the vacuum source generates negative pressure, which is transmitted to the air channel through the air connector, so that the platform adsorbs the object to be tested.

3. The detection device according to claim 2, characterized in that, The fixed platform also includes: A rotary motor is disposed below the table surface, and the rotation of the rotary motor causes the table surface and the object to be tested on the table surface to rotate.

4. The detection device according to claim 1, characterized in that, The detection device further includes: multiple light sources; the multiple light sources are used to illuminate the object to be detected.

5. The detection device according to claim 4, characterized in that, The plurality of light sources includes at least: a first light source and a second light source; the light outlet of the first light source is opposite to a first part of the object to be tested, so that the first light source illuminates the first part; the first part includes the upper surface and top edge of the object to be tested; the light outlet of the second light source is opposite to a second part of the object to be tested, so that the second light source illuminates the second part; the second part includes the lower surface and bottom edge of the object to be tested.

6. The detection device according to claim 1, characterized in that, The defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

7. A method for detecting surface defects, characterized in that, The method, applied to the detection apparatus of any one of claims 1-6, comprises: During the rotation of the object to be detected, image data of different parts of the surface of the object to be detected are acquired; Based on image data from different parts of the surface of the object to be detected, defect identification results are obtained for different parts of the surface of the image to be detected. Based on the defect identification results of different parts of the surface of the image to be detected, the defect level of the object to be detected is output.

8. The method according to claim 7, characterized in that, The different parts of the surface of the object to be tested include: a first part, a second part, and a third part; the first part includes the upper surface and top edge of the object to be tested; the second part includes the lower surface and bottom edge of the object to be tested; and the third part includes the side surface of the object to be tested.

9. The method according to claim 8, characterized in that, The image data of the first and second parts are two-dimensional image data; the image data of the third part is both two-dimensional and three-dimensional image data.

10. The method according to claim 7, characterized in that, The defect identification results include at least one of the following: the number of defects, the size of the defects, the type of defects, and the location of the defects.

11. The method according to claim 7, characterized in that, The method of obtaining defect identification results for different parts of the surface of the object to be detected based on image data from different parts of the surface includes: Based on the detection algorithms corresponding to the image data of the different parts, the image data of the different parts are analyzed and processed to obtain the defect identification results of the different parts.

12. A surface defect detection device, characterized in that, The device includes a transmission module and a processing module; the transmission module includes multiple visual sensors. The transmission module is used to acquire image data of different parts of the surface of the object to be detected during the rotation of the object to be detected. The processing module is used to obtain defect identification results for different parts of the surface of the image to be detected based on image data of different parts of the surface of the object to be detected; The processing module is also used to output the defect level of the object to be detected based on the defect identification results of different parts of the surface of the image to be detected; The plurality of vision sensors include at least: a first vision sensor, a second vision sensor, and a third vision sensor; The detection end of the first visual sensor is opposite to a first part of the object to be detected, so that the first visual sensor can acquire image data of the first part; the first part includes the upper surface and top edge of the object to be detected; The detection end of the second visual sensor is opposite to the second part of the object to be detected, so that the second visual sensor can acquire image data of the second part; the second part includes the lower surface and bottom edge of the object to be detected; The detection end of the third visual sensor is opposite to the second part of the object to be detected, so that the third visual sensor can acquire image data of the third part; the third part includes the side of the object to be detected.

13. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in any one of claims 7 to 11.

14. A computer-readable storage medium, characterized in that, When the computer-executable instructions stored in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is capable of performing the method as described in any one of claims 7 to 11.

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