Industrial product internal defect detection method, device, equipment, medium and product

Abstract

The application discloses an industrial product internal defect detection method, device, equipment, medium and product, and relates to the field of defect detection. The method comprises the following steps: acquiring three-dimensional optical scanning data of a target material product to be detected and first transmission image data of the product to be detected in a first transmission direction; determining first thickness data of the product to be detected in the first transmission direction according to the three-dimensional optical scanning data of the product to be detected and the first transmission direction; determining second thickness data of the product to be detected in the first transmission direction according to the first transmission image data and a target mapping relationship, wherein the target mapping relationship is used to indicate the mapping relationship between the thickness of an object of the target material and the proportion of the absorbed ray energy; and determining an internal defect detection result of the product to be detected according to the first thickness data and the second thickness data. The application can accurately detect the internal defects of the industrial product, reduce radiation pollution, and improve the defect detection efficiency.

Description

Technical Field

[0001] This application relates to the field of defect detection, and in particular to a method, apparatus, equipment, medium, and product for detecting internal defects in industrial products. Background Technology

[0002] Computed tomography (CT) technology is increasingly being used to detect internal defects in industrial products. By performing CT scans from multiple directions, the three-dimensional structure of the industrial product is reconstructed based on the obtained transmission image data to determine whether internal defects exist.

[0003] However, CT reconstruction requires dozens or even hundreds of high-resolution transmission images to achieve high-resolution reconstruction of the three-dimensional structure of industrial products. This results in high costs and long time consumption of tens of minutes or even longer, leading to low efficiency. At the same time, taking a large number of transmission images also greatly increases the possibility of radiation contamination. Ultimately, this makes it difficult to use CT technology for high-throughput online or line-side inspection of industrial products. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for detecting internal defects in industrial products, which can accurately detect internal defects in industrial products while reducing radiation pollution and improving defect detection efficiency.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for detecting internal defects in industrial products, including: The process involves acquiring three-dimensional optical scanning data of the product under test, and first transmission image data of the product under test in a first transmission direction; determining first thickness data of the product under test in the first transmission direction based on the three-dimensional optical scanning data and the first transmission direction; determining second thickness data of the product under test in the first transmission direction based on the first transmission image data and a target mapping relationship, where the target mapping relationship indicates the mapping relationship between the thickness of the object of the target material and the proportion of radiation energy absorbed; and determining the internal defect detection result of the product under test based on the first and second thickness data, where the internal defect detection result indicates whether the product under test has internal defects. The determination of the target mapping relationship includes: Acquire three-dimensional optical scanning data of a sample product of the target material, and second transmission image data of the sample product in the second transmission direction. The sample product is a product without internal defects. Based on the three-dimensional optical scanning data and the second transmission direction of the sample product, determine the first sample thickness data of the sample product in the second transmission direction. Based on the first sample thickness data and the second transmission image data, determine the target mapping relationship.

[0006] Optionally, methods for detecting internal defects in industrial products also include: Acquire third transmission image data of the product to be tested in the third transmission direction, which is different from the first transmission direction; determine the third thickness data of the product to be tested in the third transmission direction based on the three-dimensional optical scanning data of the product to be tested and the third transmission direction; determine the fourth thickness data of the product to be tested in the third transmission direction based on the third transmission image data and the target mapping relationship. Based on the first thickness data and the second thickness data, the internal defect detection results of the product to be inspected are determined, including: Based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data, the internal defect detection results of the product under test are determined. The internal defect detection results are also used to indicate the location of the internal defects present in the product under test.

[0007] Optionally, based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data, the internal defect detection results of the product to be inspected are determined, including: Based on the first thickness data and the second thickness data, the first internal defect data of the product under test in the first transmission direction is determined; based on the third thickness data and the fourth thickness data, the second internal defect data of the product under test in the third transmission direction is determined; based on the first internal defect data and the second internal defect data, the internal defect detection result of the product under test is determined.

[0008] Optionally, the sample product has the same shape and structure as the product to be tested.

[0009] Optionally, when the shape and structure of the sample contain internal holes, the method for detecting internal defects in industrial products also includes: Acquire fourth transmission image data of the sample product in the fourth transmission direction, which is different from the second transmission direction; determine the second sample thickness data of the sample product in the fourth transmission direction based on the three-dimensional optical scanning data of the sample product and the fourth transmission direction; determine the location of the internal holes of the sample product based on the first sample thickness data and the second sample thickness data. Based on the first internal defect data and the second internal defect data, determine the internal defect detection results of the product to be tested, including: Based on the location of the internal holes in the sample product, the first internal defect data, and the second internal defect data, the internal defect detection results of the product to be tested are determined.

[0010] Optionally, if the first thickness data is consistent with the second thickness data, it is determined that the product under test has no internal defects; otherwise, it is determined that the product under test has internal defects.

[0011] Secondly, this application provides an industrial product internal defect detection device, comprising: Base, transmission bracket, transmission component, optical bracket, optical scanning sensor, moving mechanism, clamping mechanism, processing unit; The base has an opening at the top, and a slide rail support plate is provided at the front of the interior of the base. The transmission bracket is vertically installed in the base, and the lower end of the transmission bracket is fixedly connected to the base. The transmission component is installed on the front side of the transmission bracket. The transmission component includes a transmitter head and a receiver head, and the positions of the transmitter head and the receiver head correspond to each other. The optical bracket is vertically installed in the base, and the lower end of the optical bracket is fixedly connected to the base. The optical scanning sensor is installed on the front side of the optical bracket. The moving mechanism includes a slide rail and a slider. The front end of the slide rail is mounted on the slide rail support plate, the rear end of the slide rail is mounted on the optical bracket, and the slider is mounted on the slide rail and moves back and forth along the slide rail. The clamping mechanism is mounted on the slider and is used to clamp the product to be tested; The processing unit is electrically connected to the transmission component and the optical scanning sensor, and the processing unit is used to perform the steps of the industrial product internal defect detection method described in the first aspect above.

[0012] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the industrial product internal defect detection method of any of the first aspects above.

[0013] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the industrial product internal defect detection method of any one of the first aspects described above.

[0014] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the industrial product internal defect detection method according to any one of the first aspects above.

[0015] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method for detecting internal defects in industrial products. It involves acquiring three-dimensional optical scanning data of the product under test, and first transmission image data of the product under test in a first transmission direction. Based on the three-dimensional optical scanning data of the product under test, reflecting its actual outer contour, and the first transmission direction, a first thickness data reflecting the theoretical thickness of the product under test in the first transmission direction can be determined. Based on the first transmission image data reflecting the proportion of radiation energy absorbed when the product under test is transmitted, and a target mapping relationship indicating the mapping relationship between the thickness of the target material and the proportion of radiation energy absorbed, a second thickness data reflecting the actual thickness of the product under test in the first transmission direction can be determined. Based on the first thickness data reflecting the theoretical thickness and the second thickness data reflecting the actual thickness, it is possible to accurately determine whether the product under test has internal defects, thus obtaining the internal defect detection result of the product under test.

[0016] Meanwhile, for the product to be inspected, only one transmission scan and one optical scan are needed to obtain the results of its internal defect detection. This reduces the number of scans required for inspection, reduces radiation pollution, and improves defect detection efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in 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.

[0018] Figure 1 An application environment diagram for the industrial product internal defect detection method provided in the embodiments of this application; Figure 2 A schematic flowchart illustrating the method for detecting internal defects in industrial products provided in this application embodiment; Figure 3 A schematic diagram of the overall structure of the industrial product internal defect detection device provided in the embodiments of this application; Figure 4 A schematic diagram of the structure of the industrial product internal defect detection device provided in this application embodiment after removing the base; Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached drawings: 310-base; 320-slide rail support plate; 330-transmission bracket; 340-transmission component; 341-transmitter head; 342-receiver head; 350-optical bracket; 360-optical scanning sensor; 370-moving mechanism; 371-slide rail; 372-slider; 380-clamping mechanism; 390-product to be tested. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] The method for detecting internal defects in industrial products provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on another server. Terminal 102 can send the acquired three-dimensional optical scan data of the product to be inspected, as well as the first transmission image data in the first transmission direction, to server 104. After receiving the data from terminal 102, server 104 determines the first thickness data of the product to be inspected in the first transmission direction based on the three-dimensional optical scan data and the first transmission direction; determines the second thickness data of the product to be inspected in the first transmission direction based on the first transmission image data and the target mapping relationship; and determines the internal defect detection result of the product to be inspected based on the first thickness data and the second thickness data. Server 104 can feed back the obtained internal defect detection result of the product to be inspected to terminal 102. In addition, in some embodiments, the method for detecting internal defects in industrial products can also be implemented by either server 104 or terminal 102. For example, terminal 102 can directly perform internal defect detection processing on the data of the product to be tested, or server 104 can obtain the data of the product to be tested from the data storage system and perform internal defect detection processing on the data of the product to be tested.

[0023] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers, or it can be a cloud server.

[0024] In one exemplary embodiment, such as Figure 2 As shown, a method for detecting internal defects in industrial products is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the following steps are taken: S201 to S204.

[0025] S201. Obtain the three-dimensional optical scanning data of the product to be tested of the target material, and the first transmission image data of the product to be tested in the first transmission direction.

[0026] For example, the target material can be a light metal or non-metallic material such as aluminum, magnesium, aluminum alloy, or magnesium alloy, but cannot be a heavy metal with a high atomic number and high density (such as lead, tungsten, steel, iron, etc.).

[0027] For example, an optical scanning sensor can be used to scan the product under inspection from multiple angles to obtain three-dimensional optical scanning data of the product. It is understood that the three-dimensional optical scanning data can only show the outer contour data of the product and cannot provide data on its internal structure.

[0028] For example, a CT transducer can be used to perform a transmissive scan of the product to be inspected in a first transmissive direction to obtain first transmissive image data.

[0029] It can be understood that transmission image data can be a grayscale image of the proportion of X-ray energy absorbed when the product being scanned is projected in a certain transmission direction (within a certain range, the grayscale value is linearly related to the density and thickness of the transmitted material); the lower the grayscale value of any projection position of the product to be tested in the grayscale image (i.e., the pixel in the grayscale image, the actual size of the pixel is determined by the resolution of the CT transducer), the greater the thickness of the actual position of the product to be tested in the first transmission direction.

[0030] S202. Based on the three-dimensional optical scanning data of the product to be tested and the first transmission direction, determine the first thickness data of the product to be tested in the first transmission direction.

[0031] For example, the outer contour data (i.e., the three-dimensional coordinate data of the surface of the product to be inspected) of the product to be inspected can be obtained based on the three-dimensional optical scanning data of the product to be inspected. Then, for any position a of the product to be inspected under the projection of the first transmission direction, the straight-line distance between the ray at the projection position a and the exit point in the first transmission direction (i.e., the distance the ray travels in the product to be inspected when it passes through the product to be inspected at the projection position a) can be calculated. By traversing all projection positions of the product to be inspected under the projection of the first transmission direction, the first thickness data can be finally obtained.

[0032] It can be understood that the first thickness data indicates the thickness value corresponding to any position of the product to be tested under the first transmission direction.

[0033] S203. Based on the first transmission image data and the target mapping relationship, determine the second thickness data of the product to be inspected in the first transmission direction.

[0034] The target mapping relationship is used to indicate the mapping relationship between the thickness of the target material and the proportion of radiation energy absorbed. The determination of the target mapping relationship includes: acquiring three-dimensional optical scanning data of a sample product of the target material, and second transmission image data of the sample product in the second transmission direction, wherein the sample product is a product without internal defects; determining the first sample thickness data of the sample product in the second transmission direction based on the three-dimensional optical scanning data and the second transmission direction; and determining the target mapping relationship based on the first sample thickness data and the second transmission image data.

[0035] For example, sample products can be verified in various ways (such as CT reconstruction mentioned in the background art) to ensure that they are products without internal defects.

[0036] It should be noted that the specific implementation methods for obtaining the three-dimensional optical scanning data, the second transmission image data, and determining the first sample thickness data of the sample product are similar to the aforementioned specific implementation methods for obtaining the three-dimensional optical scanning data, the first transmission image data, and determining the first thickness data of the product to be tested, and will not be repeated here.

[0037] For example, the sample product and the product to be tested may have different or the same shape and structure, and there is no limitation thereto.

[0038] For example, when the sample product has the same shape and structure as the product to be tested, systematic errors such as ray scattering, secondary radiation, and path superposition caused by structural differences can be eliminated, the linear fit between gray value and material thickness is the highest, and the measurement error of defect size is reduced. It should be noted that the second transmission direction may be the same as or different from the first transmission direction, and there is no restriction on this.

[0039] It is understandable that when the sample product is a product without internal defects, the second transmission image data can reflect the true thickness corresponding to any projection position of the sample product under the second transmission direction; thus, the correspondence between the object thickness and grayscale value under the target material can be established, and the target mapping relationship can be obtained.

[0040] For example, the target mapping relationship can include the object thickness corresponding to the grayscale value under the target material. For instance, the target mapping relationship can include "under the target material, the object thickness corresponding to grayscale value 10 is 20cm, and the object thickness corresponding to grayscale value 20 is 15cm".

[0041] It can be understood that the first transmission image data is a grayscale image of the proportion of X-ray energy absorbed under the projection of the product to be inspected in the first transmission direction.

[0042] For example, continuing with the aforementioned target mapping relationship, when the gray value corresponding to the projection position a of the first transmission image in the first transmission direction is 30, it can be determined that the thickness corresponding to the projection position a of the product to be tested in the first transmission direction is 10cm.

[0043] It should be noted that the target mapping relationship can also be determined in the following ways: Acquire the fifth transmission image data of the product under test in the fifth transmission direction, as well as the three-dimensional optical scan data of the product under test; At the same location, the ratio of the gray value of the product to be tested at that location (obtained from the fifth transmission image data) to the thickness data of the product to be tested at that location (i.e., the thickness of the three-dimensional optical scan image of the product to be tested at that location in the fifth transmission direction) is calculated to obtain the mapping coefficient of the product to be tested at that location. By performing the previous step on multiple locations of the product to be tested, multiple mapping coefficients corresponding to the product to be tested can be obtained. Statistical analysis is performed on the mapping coefficients corresponding to multiple locations with the same grayscale value to determine the target mapping relationship; or, statistical analysis is performed on the mapping coefficients corresponding to multiple locations with the same thickness to determine the target mapping relationship.

[0044] For example, if the grayscale value of position c1 of the product M1 under the projection in the fifth transmission direction is 10, and the thickness of the product M1 at position c1 in the fifth transmission direction is 20cm, then the mapping coefficient corresponding to position c1 is 10 / 20=0.5; the grayscale value corresponding to position c2 is also 10, and the corresponding thickness is 25, then the mapping coefficient corresponding to c2 is 10 / 25=0.4; the grayscale value corresponding to position c3 is also 10, and the corresponding thickness is 20cm, then the mapping coefficient corresponding to c3 is also 10 / 20=0.5. Since the gray values ​​corresponding to the three positions c1, c2, and c3 are the same, the corresponding mapping coefficient 0.5 appears most frequently. Therefore, the target mapping relationship can include "under the target material, the object thickness corresponding to gray value 10 is 20cm".

[0045] S204. Based on the first thickness data and the second thickness data, determine the internal defect detection results of the product to be inspected.

[0046] Among them, the internal defect detection results are used to indicate whether the product under test has internal defects.

[0047] For example, if the first thickness data is consistent with the second thickness data, it is determined that the product under test has no internal defects; otherwise, it is determined that the product under test has internal defects.

[0048] For example, for the projected position 'a' of the product under the first transmission direction, the thickness value A corresponding to the projected position 'a' in the first thickness data and the thickness value B corresponding to the second thickness data can be determined. When the thickness value A is equal to the thickness value B, it indicates that there is no internal defect at the projected position 'a' in the first transmission direction. When the thickness value A is not equal to the thickness value B, it indicates that there is an internal defect at the projected position 'a' in the first transmission direction. It can be understood that the difference between the thickness value A and the thickness value B is the size of the internal defect at the projected position 'a' of the product under the test in the first transmission direction.

[0049] It should be noted that the product under test is determined to be free of internal defects only when no internal defects are found at any projected position of the product under test; otherwise, the product under test is determined to have internal defects.

[0050] In some possible implementations, a difference threshold can be set. When the difference between the thickness corresponding to all projected positions in the first thickness data and the thickness corresponding to the thickness in the second thickness data is less than the difference threshold, it is determined that the product under test does not have internal defects; otherwise, it is determined that the product under test has internal defects. This can reduce detection errors caused by measurement errors.

[0051] This embodiment of the disclosure acquires three-dimensional optical scanning data of the product to be tested, and first transmission image data of the product to be tested in a first transmission direction. Based on the three-dimensional optical scanning data of the product to be tested, which reflects the actual outer contour of the product to be tested, and the first transmission direction, a first thickness data of the product to be tested, reflecting the theoretical thickness, can be determined in the first transmission direction. Based on the first transmission image data, which reflects the proportion of radiation energy absorbed when the product to be tested is transmitted, and a target mapping relationship indicating the mapping relationship between the thickness of the object of the target material and the proportion of radiation energy absorbed, a second thickness data of the product to be tested, reflecting the actual thickness, can be determined in the first transmission direction. Based on the first thickness data reflecting the theoretical thickness and the second thickness data reflecting the actual thickness, it can be accurately determined whether the product to be tested has internal defects, and the internal defect detection result of the product to be tested can be obtained.

[0052] Meanwhile, for the product to be tested, only one transmission scan and one optical scan are needed to obtain the internal defect detection results, which reduces the number of scans, reduces radiation pollution, and improves detection efficiency.

[0053] In some possible embodiments, in order to determine the specific location of internal defects in a product, the industrial product internal defect detection method may further include: Acquire third transmission image data of the product to be tested in the third transmission direction, which is different from the first transmission direction; determine the third thickness data of the product to be tested in the third transmission direction based on the three-dimensional optical scanning data of the product to be tested and the third transmission direction; determine the fourth thickness data of the product to be tested in the third transmission direction based on the third transmission image data and the target mapping relationship. Based on the first thickness data and the second thickness data, the internal defect detection results of the product to be inspected are determined, including: Based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data, the internal defect detection results of the product under test are determined. The internal defect detection results are also used to indicate the location of the internal defects present in the product under test.

[0054] It should be noted that the specific implementation methods for acquiring the third transmission image data of the product to be tested, as well as determining the third thickness data and the fourth thickness data, are similar to the specific implementation methods for acquiring the first transmission image data of the product to be tested, as well as determining the first thickness data and the second thickness data, as described above, and will not be repeated here.

[0055] Specifically, based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data, the internal defect detection results of the product to be inspected are determined, including: Based on the first thickness data and the second thickness data, the first internal defect data of the product under test in the first transmission direction is determined; based on the third thickness data and the fourth thickness data, the second internal defect data of the product under test in the third transmission direction is determined; based on the first internal defect data and the second internal defect data, the internal defect detection result of the product under test is determined.

[0056] For example, for any projection position a of the product to be inspected in the first transmission direction, the thickness value A corresponding to the projection position a in the first thickness data and the thickness value B corresponding to the second thickness data can be determined. The difference between the thickness value A and the thickness value B is calculated to obtain the first internal defect data of the projection position a in the first transmission direction. All projection positions of the product to be inspected in the first transmission direction are traversed to obtain the first internal defect data of the product to be inspected in the first transmission direction. For any projection position b of the product to be inspected in the third transmission direction, and the thickness value C corresponding to the projection position b in the third thickness data and the thickness value D corresponding to the second thickness data; calculate the difference between the thickness value C and the thickness value D to obtain the second internal defect data of the projection position b in the second transmission direction; traverse all projection positions of the product to be inspected in the third transmission direction to obtain the second internal defect data of the product to be inspected in the third transmission direction.

[0057] For example, based on the first internal defect data, the second internal defect data, and the spatial coordinate data of the product to be inspected, the spatial coordinate data corresponding to the first internal defect data, and the spatial coordinate data corresponding to the second internal defect data, the specific spatial coordinates of the location of the internal defect in the product to be inspected can be determined according to the geometric principle of binocular perspective projection.

[0058] This embodiment obtains the third thickness data and the fourth thickness data of the product under test in a third transmission direction different from the first transmission direction. This allows the determination of the location of the internal defect of the product under test in the third transmission direction. By combining the location of the internal defect of the product under test in the third transmission direction determined by the first thickness data and the second thickness data of the product under test in the first transmission direction, the specific spatial location of the internal defect of the product under test can be accurately determined.

[0059] In some possible embodiments, when the sample product has the same shape and structure as the product to be tested, and the design of the sample product's shape and structure contains internal holes, in order to accurately determine the location of internal defects in the product to be tested, the industrial product internal defect detection method further includes: Acquire fourth transmission image data of the sample product in the fourth transmission direction, which is different from the second transmission direction; determine the second sample thickness data of the sample product in the fourth transmission direction based on the three-dimensional optical scanning data of the sample product and the fourth transmission direction; determine the location of the internal holes of the sample product based on the first sample thickness data and the second sample thickness data. Based on the first internal defect data and the second internal defect data, determine the internal defect detection results of the product to be tested, including: Based on the location of the internal holes in the sample product, the first internal defect data, and the second internal defect data, the internal defect detection results of the product to be tested are determined.

[0060] It should be noted that the specific implementation methods for obtaining the fourth transmission image data of the sample product, determining the second sample thickness data, and determining the location of the internal holes in the sample product are similar to the specific implementation methods for obtaining the second transmission image data, determining the first sample thickness data, and determining the location of the internal defects in the product to be tested, and will not be repeated here.

[0061] For example, after obtaining the first internal defect data and the second internal defect data, the location of the internal void (understandably, the internal void includes internal holes and internal defects) of the product to be inspected can be determined based on the first internal defect data and the second internal defect data. Since the sample product has the same shape and structure as the product to be tested, the designed internal holes can be directly removed from the internal gaps of the product to be tested based on the location of the internal holes in the sample product, thus obtaining the internal defects and their locations in the product to be tested.

[0062] This application also provides an application scenario in which the above-described method for detecting internal defects in industrial products is applied. Specifically, the method for detecting internal defects in industrial products provided in this embodiment can be applied in an industrial product manufacturing scenario. Raw materials are processed and treated through an industrial production line to obtain an industrial product to be inspected; defect detection is performed on the industrial product to be inspected; after the industrial product to be inspected passes the defect detection, it enters the downstream packaging and shipping stages. The method for detecting internal defects in industrial products provided in this embodiment belongs to the internal defect detection stage in the defect detection stage of the industrial product to be inspected.

[0063] Based on the same inventive concept, this application also provides an industrial product internal defect detection device for implementing the above-described industrial product internal defect detection method. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the industrial product internal defect detection device provided below can be found in the limitations of the industrial product internal defect detection method described above, and will not be repeated here.

[0064] In one exemplary embodiment, such as Figure 3 , Figure 4 As shown, an industrial product internal defect detection device is provided, comprising: Base 310, transmission bracket 330, transmission component 340, optical bracket 350, optical scanning sensor 360, moving mechanism 370, clamping mechanism 380, processing unit; The upper part of the base 310 is open, and the front end of the interior of the base 310 is provided with a slide rail 371 and a support plate 320. The transmission bracket 330 is vertically installed in the base 310, and the lower end of the transmission bracket 330 is fixedly connected to the base 310. The transmission component 340 is installed on the front side of the transmission bracket 330. The transmission component 340 includes a transmitter head 341 and a receiver head 342, and the positions of the transmitter head 341 and the receiver head 342 are corresponding. The optical bracket 350 is vertically mounted in the base 310, and the lower end of the optical bracket 350 is fixedly connected to the base 310. The optical scanning sensor 360 is mounted on the front side of the optical bracket 350. The moving mechanism 370 includes a slide rail 371 and a slider 372. The front end of the slide rail 371 is mounted on the slide rail 371 support plate 320, and the rear end of the slide rail 371 is mounted on the optical bracket 350. The slider 372 is mounted on the slide rail 371 and moves back and forth along the slide rail 371. The clamping mechanism 380 is mounted on the slider 372 and is used to clamp the product 390 to be tested; The processing unit is electrically connected to the transmission component 340 and the optical scanning sensor 360, and is used to perform the steps of the above-described method for detecting internal defects in industrial products.

[0065] For example, the slider 372 can be moved to the front end of the track first, and the product to be inspected 390 can be clamped by the clamping mechanism 380; then the slider 372 can be moved to the rear end, so that the product to be inspected 390 is close to the transmission bracket 330 and is in the transmission scanning area of ​​the transmission component 340, and the transmission component 340 can be used to acquire the transmission data of the product to be inspected 390 in at least one transmission direction; then the slider 372 can be moved to the rear end, so that the product to be inspected 390 is close to the optical bracket 350 and is in the optical scanning area of ​​the transmission component 340, and the optical scanning sensor 360 can be used to acquire the three-dimensional optical scanning data of the product to be inspected 390; the processing unit determines the internal defect detection result of the product to be inspected 390 based on the transmission data and three-dimensional optical scanning data of the product to be inspected, combined with the target mapping relationship.

[0066] For example, in order to acquire transmission data in multiple transmission directions, the transmission component 340 may include multiple sets of corresponding transmitter heads 341 and receiver heads 342.

[0067] It is understood that the processing unit can be as described above. Figure 1 The terminal 102 or server 104 in the text will not be described in detail here.

[0068] The specific implementation methods and beneficial effects of this device embodiment can be found in the foregoing method embodiments, and will not be repeated here.

[0069] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When the computer program is executed by the processor, it implements the aforementioned method for detecting internal defects in industrial products.

[0070] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0071] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0072] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0073] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0074] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0075] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0076] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0077] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0078] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting internal defects in industrial products, characterized in that, The method for detecting internal defects in industrial products includes: Acquire three-dimensional optical scanning data of the product to be tested of the target material, and first transmission image data of the product to be tested in the first transmission direction; Based on the three-dimensional optical scanning data of the product to be tested and the first transmission direction, the first thickness data of the product to be tested in the first transmission direction is determined; Based on the first transmission image data and the target mapping relationship, the second thickness data of the product to be tested in the first transmission direction is determined. The target mapping relationship is used to indicate the mapping relationship between the thickness of the target material and the proportion of radiation energy absorbed. Based on the first thickness data and the second thickness data, the internal defect detection result of the product to be tested is determined, and the internal defect detection result is used to indicate whether the product to be tested has internal defects. The determination of the target mapping relationship includes: Acquire three-dimensional optical scanning data of the sample product of the target material, and second transmission image data of the sample product in the second transmission direction, wherein the sample product is a product without internal defects; Based on the three-dimensional optical scanning data of the sample product and the second transmission direction, the first sample thickness data of the sample product in the second transmission direction is determined; The target mapping relationship is determined based on the first sample thickness data and the second transmission image data.

2. The method for detecting internal defects in industrial products according to claim 1, characterized in that, The method for detecting internal defects in industrial products also includes: Acquire third transmission image data of the product to be tested in a third transmission direction, wherein the third transmission direction is different from the first transmission direction; Based on the three-dimensional optical scanning data of the product to be tested and the third transmission direction, the third thickness data of the product to be tested in the third transmission direction is determined; Based on the third transmission image data and the target mapping relationship, the fourth thickness data of the product to be tested in the third transmission direction is determined; The step of determining the internal defect detection result of the product to be inspected based on the first thickness data and the second thickness data includes: Based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data, the internal defect detection result of the product to be tested is determined, and the internal defect detection result is also used to indicate the location of the internal defects existing in the product to be tested.

3. The method for detecting internal defects in industrial products according to claim 2, characterized in that, The step of determining the internal defect detection result of the product to be inspected based on the first thickness data, the second thickness data, the third thickness data, and the fourth thickness data includes: Based on the first thickness data and the second thickness data, the first internal defect data of the product to be tested in the first transmission direction is determined; Based on the third thickness data and the fourth thickness data, the second internal defect data of the product to be tested in the third transmission direction is determined; Based on the first internal defect data and the second internal defect data, the internal defect detection result of the product to be tested is determined.

4. The method for detecting internal defects in industrial products according to claim 3, characterized in that, The sample product has the same shape and structure as the product to be tested.

5. The method for detecting internal defects in industrial products according to claim 4, characterized in that, When the shape and structure of the sample contain internal holes, the method for detecting internal defects in industrial products further includes: Acquire fourth transmission image data of the sample product in a fourth transmission direction, wherein the fourth transmission direction is different from the second transmission direction; Based on the three-dimensional optical scanning data of the sample product and the fourth transmission direction, the second sample thickness data of the sample product in the fourth transmission direction is determined; Based on the first sample thickness data and the second sample thickness data, the location of the internal holes in the sample product is determined; The step of determining the internal defect detection result of the product to be tested based on the first internal defect data and the second internal defect data includes: Based on the location of the internal holes in the sample product, the first internal defect data, and the second internal defect data, the internal defect detection result of the product to be tested is determined.

6. The method for detecting internal defects in industrial products according to claim 1, characterized in that, If the first thickness data is consistent with the second thickness data, it is determined that the product under test has no internal defects; otherwise, it is determined that the product under test has internal defects.

7. An industrial product internal defect detection device, characterized in that, The industrial product internal defect detection device includes: Base (310), transmission bracket (330), transmission assembly (340), optical bracket (350), optical scanning sensor (360), moving mechanism (370), clamping mechanism (380), processing unit; The base (310) has an opening at the top, and a slide rail (371) support plate (320) is provided at the front end of the base (310). The transmission bracket (330) is vertically disposed in the base (310), and the lower end of the transmission bracket (330) is fixedly connected to the base (310). The transmission assembly (340) is disposed on the front side of the transmission bracket (330). The transmission assembly (340) includes a transmitter (341) and a receiver (342), and the positions of the transmitter (341) and the receiver (342) are corresponding. The optical bracket (350) is vertically arranged in the base (310), the lower end of the optical bracket (350) is fixedly connected to the base (310), and the optical scanning sensor (360) is arranged on the front side of the optical bracket (350). The moving mechanism (370) includes a slide rail (371) and a slider (372). The front end of the slide rail (371) is disposed on the slide rail (371) support plate (320), the rear end of the slide rail (371) is disposed on the optical bracket (350), and the slider (372) is disposed on the slide rail (371) and moves back and forth along the slide rail (371). The clamping mechanism (380) is disposed on the slider (372) and is used to clamp the product to be tested (390). The processing unit is electrically connected to the transmission component (340) and the optical scanning sensor (360), and the processing unit is used to perform the steps of the industrial product internal defect detection method according to any one of claims 1-6.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method for detecting internal defects in an industrial product according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method for detecting internal defects in industrial products as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method for detecting internal defects in industrial products as described in any one of claims 1-6.

Images