Solder ball quality evaluation method and electronic equipment

Abstract

The embodiment of the invention relates to the technical field of industrial detection, in particular to a solder ball quality evaluation method and electronic equipment, and the method comprises the steps: processing a sectional image of a BGA solder ball, calculating the contour area of the solder ball and the area of a solder material, and calculating the size of the solder ball according to the contour area of the solder ball. The volume of the welding material is calculated according to the area of the welding material of the welding ball, and the void volume ratio of the welding ball is calculated according to the volume of the welding ball and the volume of the welding material, so that the void volume ratio of the welding ball is calculated efficiently and accurately without depending on methods such as a deep learning model and adaptive threshold segmentation, and the accuracy of void volume ratio detection of the welding ball is improved. The method is high in stability and reliability, is high in universality, accurately obtains the quality evaluation result of the solder ball according to the void volume ratio, and improves the accuracy of the quality evaluation of the solder ball.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of industrial detection, and in particular, to a solder ball quality evaluation method and electronic equipment. BACKGROUND

[0002] With the rapid development of electronic technology, miniaturization of packaging and high-density assembly of new devices, the quality requirements of assembly are also increasing. Compared with traditional packaging forms, the main feature of BGA packaging technology is that all solder joints are arranged in an array form under the chip. BGA packaging can reduce the size of the device and greatly increase the number of pins that can be placed. Therefore, it is very difficult to detect the quality of BGA solder joints. In the complex background, there are still problems such as low precision and long time consumption in solder ball segmentation and extraction. When the density of components on the printed circuit board is increasing, the traditional deep learning model and adaptive threshold segmentation method have a calculation speed bottleneck problem, which is poor in real-time performance and difficult to meet the real-time requirements of online detection. In addition, there is a general problem. When facing new scenes, the model performance may decrease or even fail, which has low reliability. It is difficult to efficiently and accurately detect the hollow volume inside the solder ball and judge the quality of the solder ball. SUMMARY

[0003] Therefore, an embodiment of the present application aims to provide a solder ball quality evaluation method and electronic equipment to solve the technical problem of low accuracy in BGA solder ball hollow volume detection in the related art.

[0004] To solve the above technical problems, an embodiment of the present application provides the following technical solutions. In a first aspect, an embodiment of the present application provides a solder ball quality evaluation method, which comprises: obtaining solder ball image data, the solder ball image data comprising a plurality of continuous solder ball tomographic images; performing binarization processing on the solder ball tomographic images to obtain a binarized image corresponding to the solder ball tomographic images; based on the binarized image, calculating a contour area of the solder ball and a solder material area in the binarized image; based on the contour area of the solder ball, calculating a solder ball volume; based on the solder material area of the solder ball, calculating a solder material volume; based on the solder ball volume and the solder material volume, obtaining a hollow volume rate of the solder ball; based on the hollow volume rate of the solder ball, obtaining a quality evaluation result of the solder ball.

[0005] In some embodiments, based on the binarized image, the contour area of the solder ball in the binarized image is calculated, comprising: extracting a solder ball contour from the binarized image, the solder ball contour comprising a plurality of contour points; Based on the coordinates of the contour points, the contour area of the solder ball is calculated.

[0006] In some embodiments, based on the binary image, the solder material area of the solder ball in the binary image is calculated, including: Based on the binary image, a mask image corresponding to the binary image is obtained. Based on the binary image and the mask image, a target image is obtained, the target image being in the form of a binary image. The area of a target region in the target image is calculated, the area of the target region being the solder material area of the solder ball, the target region being a region occupied by pixels having a first value.

[0007] In some embodiments, based on the binary image, a mask image corresponding to the binary image is obtained, including: The first pixels outside the solder ball contour in the binary image are converted into second pixels, and the second pixels inside the solder ball contour in the binary image are converted into first pixels, to obtain a mask image corresponding to the binary image, the first pixels being pixels having a first value, and the second pixels being pixels having a second value.

[0008] In some embodiments, based on the binary image and the mask image, a target image is obtained, including: The binary image and the mask image corresponding to the binary image are subjected to a logical AND operation to obtain the target image.

[0009] In some embodiments, based on the contour area of the solder ball, the volume of the solder ball is calculated, including: The contour areas of the solder balls in all the binary images are added to obtain the volume of the solder ball.

[0010] In some embodiments, based on the solder material area of the solder ball, the volume of the solder material is calculated, including: The solder material areas of the solder balls in all the binary images are added to obtain the volume of the solder material.

[0011] In some embodiments, based on the volume of the solder ball and the volume of the solder material, the hollow volume rate of the solder ball is obtained, including: The volume of the solder ball is subtracted from the volume of the solder material to obtain a hollow volume. The hollow volume is divided by the volume of the solder ball to obtain a hollow volume rate.

[0012] In some embodiments, based on the hollow volume rate of the solder ball, a quality evaluation result of the solder ball is obtained, including: In response to the hollow volume rate being greater than or equal to a volume rate threshold, a first evaluation result is determined as the quality evaluation result of the solder ball, the first evaluation result indicating that the solder ball is an unqualified solder ball. In response to the cavity volume ratio being less than the volume ratio threshold, the second evaluation result is determined as the quality evaluation result of the solder ball, and the second evaluation result indicates that the solder ball is a qualified solder ball.

[0013] In a second aspect, an electronic device is provided, and the electronic device comprises: a processor and a memory connected to the processor in communication; The memory stores computer program instructions executable by the processor, and the computer program instructions, when executed by the processor, cause the electronic device to perform any one of the solder ball quality evaluation methods of the first aspect.

[0014] The embodiments of the present application have the following beneficial effects: Unlike the related art, the solder ball quality evaluation method provided by the embodiments of the present application comprises: obtaining solder ball image data, the solder ball image data comprising a plurality of continuous solder ball tomographic images, performing binaryzation processing on the solder ball tomographic images to obtain binaryzation images corresponding to the solder ball tomographic images, calculating the contour area and the solder material area of the solder ball in the binaryzation images based on the binaryzation images, calculating the volume of the solder ball based on the contour area of the solder ball, calculating the volume of the solder material based on the solder material area of the solder ball, obtaining the cavity volume ratio of the solder ball based on the volume of the solder ball and the volume of the solder material, and obtaining the quality evaluation result of the solder ball based on the cavity volume ratio of the solder ball.

[0015] The embodiments of the present application calculate the contour area and the solder material area of the solder ball by processing the tomographic images of the BGA solder ball, thereby calculating the volume of the solder ball based on the contour area of the solder ball, calculating the volume of the solder material based on the solder material area of the solder ball, calculating the cavity volume ratio of the solder ball based on the volume of the solder ball and the volume of the solder material, and not relying on deep learning models and adaptive threshold segmentation methods. In this way, the cavity volume ratio of the solder ball can be efficiently and accurately calculated, the accuracy of the cavity volume ratio detection of the solder ball is improved, the stability and reliability are high, the generality is strong, and finally the quality evaluation result of the solder ball is accurately obtained based on the cavity volume ratio, and the accuracy of the quality evaluation of the solder ball is improved. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the drawings needed to be used in the related art or the embodiments. Obviously, the drawings described below only show some of the embodiments of the present application, and should not be regarded as a limitation to the protection scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0017] Figure 1 is an application scenario diagram of the solder ball quality evaluation method provided by some embodiments of the present application; Figure 2is a structural schematic diagram of an electronic device provided by some embodiments of the present application; Figure 3 is a flowchart of a solder ball quality evaluation method provided by some embodiments of the present application; Figure 4 is a schematic diagram of a solder ball tomographic image in some embodiments of the present application; Figure 5 is Figure 4 is a schematic diagram of a binarized image obtained after binarization processing of the solder ball tomographic image shown in the embodiment; Figure 6 is Figure 5 is a schematic diagram of a first binarized image in the binarized images shown in the embodiment Figure 1 ; Figure 7 is Figure 5 is a schematic diagram of a first binarized image in the binarized images shown in the embodiment Figure 2 ; Figure 8 is Figure 6 is a schematic diagram of a mask image obtained after mask processing of the first binarized image shown in the embodiment; Figure 9 is Figure 6 is a schematic diagram of a target image obtained after fusion of the first binarized image shown in the embodiment and Figure 8 the mask image shown in the embodiment. DETAILED DESCRIPTION

[0018] In order to make the objects and advantages of the embodiments of the present application more easily understood, the technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. The following detailed description of the embodiments of the present application in the accompanying drawings is not intended to limit the scope of the present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of the present application.

[0019] It should be noted that the various technical features described in the following embodiments of the present application can be combined with each other without conflict, and are within the protection scope of the present application. In addition, although the functional modules are divided in the device or structure schematic diagram, and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a manner different from the module division in the device or the order in the flowchart. In addition, the "first", "second", "third" and other similar expressions used herein do not limit the data and execution order, but are only for the purpose of facilitating the description and distinguishing the same items or similar items with basically the same function and effect, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of technical features.

[0020] Unless otherwise defined, the technical terms and scientific terms used in the specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs. The terms used in the specification are only for the purpose of describing the specific embodiments and are not used to limit the present application. It should be understood that the term "and / or" used in the specification includes any and all combinations of one or more listed items.

[0021] With the rapid development of electronic technology, the miniaturization of packaging and the high density of assembly as well as the continuous emergence of new devices, the quality requirements of assembly are also increasing. Compared with the traditional packaging form, the main feature of BGA packaging technology is that all the solder joints are arranged in an array form under the chip. BGA packaging can reduce the size of the device and greatly increase the number of pins that can be placed, so it is very difficult to detect the quality of the solder joints of BGA. The extraction of solder balls under complex background still has problems such as low precision and long time-consuming.

[0022] When the density of components on a printed circuit board is increasing, in the related art, a deep learning model and an adaptive threshold segmentation method are used to extract the solder ball region, and the inventors find that this approach not only has a calculation speed bottleneck, poor real-time performance, and difficulty in meeting the real-time requirements of online detection, but also has a generalization problem. In the face of new scenarios, the model performance has the risk of decline or even failure, and the reliability is low, and it is difficult to efficiently and accurately detect and calculate the hollow volume inside the solder ball and judge the quality of the solder ball.

[0023] Therefore, the embodiment of the present application provides a solder ball quality evaluation method, by processing the tomographic image of the BGA solder ball, the contour area and the solder material area of the solder ball are calculated, so as to calculate the volume of the solder ball according to the contour area of the solder ball, and calculate the volume of the solder material according to the solder material area of the solder ball, and calculate the hollow volume rate of the solder ball according to the volume of the solder ball and the volume of the solder material, which does not rely on the deep learning model and the adaptive threshold segmentation method, so as to efficiently and accurately calculate the hollow volume rate of the solder ball, improve the accuracy of the hollow volume rate detection of the solder ball, and the stability and the reliability are high, and the universality is strong, and finally the quality evaluation result of the solder ball is accurately obtained according to the hollow volume rate of the solder ball, and the accuracy of the solder ball quality evaluation is improved.

[0024] Please refer to Figure 1 , Figure 1 The application scenario schematic diagram of the solder ball quality evaluation method provided by some embodiments of the present application is schematically shown.

[0025] As Figure 1 shown, the application scenario includes an electronic device 100 and a detection imaging device 200, and the electronic device 100 is in communication connection with the detection imaging device 200 through a network, wherein the instances of the network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network and a combination thereof, for example, an Ethernet.

[0026] The printed circuit board has a plurality of BGA (Ball Grid Array, ball grid array) solder balls, the detection imaging device 200 is used for detecting and imaging the printed circuit board, obtaining a plurality of solder ball tomographic images corresponding to each BGA solder ball, and then taking the plurality of solder ball tomographic images of each BGA solder ball as solder ball image data, and sending the solder ball image data to the electronic device 100 through the network, so that the electronic device 100 obtains the solder ball image data.

[0027] For example, after obtaining the solder ball image data, the electronic device 100 performs binaryzation processing on each solder ball tomographic image in the solder ball image data to obtain a corresponding binaryzation image. The contour area and the solder material area of the BGA solder ball in the binaryzation image are calculated according to the binaryzation image, wherein the contour area is the area of the BGA solder ball, and the solder material area is the area of the metal material used when soldering electronic components, and the metal material includes tin, lead, aluminum and other metal compounds.

[0028] In some embodiments, the volume of the BGA solder ball is calculated according to the contour area of the BGA solder ball in all the binarized images, the volume of the solder material is calculated according to the solder material area of the BGA solder ball in all the binarized images, and the hollow volume rate of the BGA solder ball is calculated according to the volume of the BGA solder ball and the volume of the solder material. Finally, the quality evaluation result of the BGA solder ball is obtained according to the hollow volume rate of the BGA solder ball, for example, when the hollow volume rate of the BGA solder ball is greater than or equal to a preset hollow volume rate threshold, the quality evaluation result of the BGA solder ball is determined to be unqualified, and when the hollow volume rate of the BGA solder ball is less than the preset hollow volume rate threshold, the quality evaluation result of the BGA solder ball is determined to be qualified.

[0029] It should be understood that Figure 1 The application scenario shown is only illustrative of one case of BGA solder ball quality evaluation, and the application scenario in which the electronic device 100 is a notebook computer does not cause any limitation on any condition such as the structure, type and number of the electronic device 100 and the detection imaging device 200 in other application scenarios or embodiments. For example, in some other application scenarios or embodiments, the electronic device 100 can also be a tablet computer, a desktop computer or other suitable types of devices or apparatuses, or the electronic device 100 can also be an FPGA chip, a single-chip microcomputer, a microcontroller or other any suitable component, and an engineer can configure these components in the detection imaging device 200 for use in cooperation with the detection imaging device 200 to complete the evaluation of the quality of the BGA solder ball.

[0030] To facilitate understanding of the solder ball quality evaluation method provided by the embodiments of the present application, the electronic device provided by the embodiments of the present application is first described in detail.

[0031] Please refer to Figure 2 , Figure 2 The structural schematic diagram of the electronic device provided by some embodiments of the present application is shown.

[0032] As Figure 2 shown, the electronic device 100 includes at least one processor 110 and a memory 120 connected in communication, Figure 2 For example, one processor 110 is connected to the bus system 130. Among them, various components in the electronic device 100 are coupled together through the bus system 130, and the bus system 130 is used to realize the connection and communication between various components. It is easy to understand that the bus system 130 can include not only a data bus, but also a power bus, a control bus and a state signal bus, etc. However, in order to clearly illustrate and concisely, all kinds of buses are marked as the bus system 130 in the Figure 2 It can be understood that Figure 2The structure shown in the embodiments is only illustrative, and does not cause any limitation to the structure of the electronic device. For example, the electronic device can further include more or less components than the structure shown, or have a different configuration from the structure shown. Figure 2 Figure 2

[0033] Specifically, the processor 110 is configured to provide operation and control capabilities to support the electronic device 100 to perform corresponding business logic and functions, for example, to support the electronic device 100 to perform any one of the solder ball quality evaluation methods provided by the embodiments of the present application, or to perform the steps in any one of the possible implementation manners of any one of the solder ball quality evaluation methods provided by the embodiments of the present application. It can be understood that the processor 110 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0034] ​​The memory 120, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, instructions and modules, such as programs, instructions and modules corresponding to the solder ball quality evaluation method in the embodiments of the present application. In some embodiments, the memory 120 can include a program storage area and a data storage area, the program storage area can store an operating system and application programs required by at least one function, and the data storage area can store data created according to the use of the processor 110, etc. The processor 110 executes various functional applications and data processing of the electronic device 100 by running the non-transitory software programs, instructions and modules stored in the memory 120, thereby implementing any one of the solder ball quality evaluation methods provided by the embodiments of the present application, or executing the steps in any one of the possible implementation manners of any one of the solder ball quality evaluation methods provided by the embodiments of the present application. In some embodiments, the memory 120 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device or other non-transitory solid-state storage device. In some embodiments, the memory 120 can also include a memory remotely arranged with respect to the processor 110, which can be connected to the processor 110 through a communication network. It should be understood that examples of the above-mentioned communication network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and combinations thereof.

[0035] According to the above, it can be understood that the implementation execution subject of any one of the solder ball quality evaluation methods provided by the embodiments of the present application can be any suitable type of electronic device with certain computing and control capabilities, which can be implemented and executed by the above-mentioned electronic device 100. In some possible implementation manners, the solder ball quality evaluation method provided by the embodiments of the present application can be implemented by executing computer program instructions stored in the memory by the processor.

[0036] The solder ball quality evaluation method provided by the embodiments of the present application will be described in detail below in combination with an exemplary application and implementation of the electronic device provided by the embodiments of the present application.

[0037] Please refer to Figure 3 , Figure 3 The flowchart schematically showing the solder ball quality evaluation method provided by some embodiments of the present application is shown.

[0038] As can be understood by those skilled in the art, the solder ball quality evaluation method provided by the embodiments of the present application can be applied to the above-mentioned electronic device (such as the electronic device 100). Specifically, the execution subject of the solder ball quality evaluation method is one or at least two processors of the electronic device.

[0039] As Figure 3 shown, the solder ball quality evaluation method includes but is not limited to the following steps S31-S37: S31: Acquire solder ball image data, which includes multiple consecutive solder ball tomographic images.

[0040] For example, after the inspection imaging device performs inspection imaging on the solder balls, it obtains multiple consecutive tomographic images of each solder ball. In this embodiment of the invention, the multiple consecutive tomographic images of the solder balls corresponding to each solder ball are obtained from the inspection imaging device via a network, thus acquiring solder ball image data. Alternatively, the inspection imaging device packages the multiple consecutive tomographic images of the solder balls corresponding to each solder ball into solder ball image data and sends the solder ball image data to an electronic device. In this way, this embodiment of the invention obtains solder ball image data.

[0041] For example, please see Figure 4 , Figure 4 The illustration shows a schematic diagram of a tomographic image of a solder ball in solder ball image data provided in some embodiments of the present invention. Figure 4 In the solder ball tomographic image, the XY direction represents the transverse fault direction, and the YZ and XZ directions represent the longitudinal fault directions. It can be understood that by continuously segmenting and extracting solder ball tomographic images along the transverse fault direction, multiple consecutive solder ball tomographic images can be obtained. Similarly, by continuously segmenting and extracting solder ball tomographic images along the longitudinal fault direction, multiple consecutive solder ball tomographic images can be obtained.

[0042] S32: Perform binarization processing on the solder ball tomographic image to obtain the corresponding binarized image.

[0043] For example, a pixel segmentation threshold is set based on the grayscale value of the welding material used in the welding. Each weld ball tomographic image is then binarized according to the pixel segmentation threshold to distinguish between the weld ball region and the void region, resulting in a binarized image corresponding to each weld ball tomographic image. It should be understood that any other suitable method or approach can be used to binarize the weld ball tomographic images to obtain the corresponding binarized images; this embodiment of the invention does not impose any limitations on this.

[0044] For example, please see Figure 5 , Figure 5 Schematic illustration Figure 4 A schematic diagram of the binarized image obtained after binarizing the tomographic image of the solder ball shown in the embodiment. Figure 5 The binarized image shown includes a first binarized image and a second binarized image. The first binarized image is the binarized image obtained after binarizing the weld ball fracture image in the transverse direction, and the second binarized image is the binarized image obtained after binarizing the weld ball fracture image in the longitudinal direction.

[0045] S33: Based on the binarized image, calculate the outline area of ​​the solder ball and the area of ​​the solder material in the binarized image.

[0046] It is understood that when calculating the outline area of ​​the solder ball and the area of ​​the solder material, the embodiments of the present invention select the first binarized image for calculation. Of course, in other embodiments, the second binarized image can also be selected to calculate the outline area of ​​the solder ball and the area of ​​the solder material. The embodiments of the present invention do not limit this in any way.

[0047] Among them, the outline area is used to characterize the overall cross-sectional shape of the solder ball, and the solder area is used to characterize the area of ​​the actual solder portion in the cross-section.

[0048] For example, please refer to Figure 6 , Figure 6 In the first binarized image shown (i.e., the binarized image obtained after binarizing the cross-sectional image of the solder ball in the transverse direction), pixels with a value of 255 (i.e., white) represent the solder ball region (including the solder area) or other pixels, while pixels with a value of 0 (i.e., black) represent the background region or void region. During the solder ball contour analysis and screening process, the BGA solder ball contour region is selected based on prior information about the BGA solder balls (e.g., area, aspect ratio, roundness, etc.). It can be understood that the area refers to the area of ​​the circle within the BGA pad frame, the aspect ratio is set to 80%-100%, and the roundness is set to greater than or equal to 80%.

[0049] Of course, any other suitable method can be used to filter the solder ball outline region, such as performing connected component analysis on the first binarized image to find the largest connected region as the main body of the solder ball, thus obtaining the solder ball outline region.

[0050] After identifying the solder ball outline region, the total number of pixels in the outline region is multiplied by the area of ​​each individual pixel to obtain the area of ​​the solder ball outline region. This area is the outline area of ​​the solder ball. Pixels with a value of 1 in the outline region are then selected as candidate pixels. The first number of candidate pixels is counted, and this first number is multiplied by the area of ​​each individual pixel to obtain the area of ​​the solder material region. This area is the solder material area of ​​the solder ball.

[0051] S34: Calculate the volume of the solder ball based on its outline area.

[0052] It is understandable that multiple solder ball tomographic images are obtained by continuously segmenting and cutting along the transverse direction. Therefore, each first binarized image includes the outline area of ​​the solder ball at the transverse section. The outline areas of the solder balls corresponding to all the first binarized images are summed to obtain the volume of the solder ball.

[0053] For example, the volume of the solder ball is obtained by integrating or summing the contour areas of multiple consecutive first binarized images along the transverse direction.

[0054] In some embodiments, the solder ball volume is calculated based on the profile area of the solder ball, specifically including but not limited to the following steps S341: S341: Adding the profile area of the solder ball in all the binary images to obtain the solder ball volume.

[0055] In this embodiment, the profile area of the solder ball in each first binary image is added to obtain the solder ball volume.

[0056] S35: Calculating the solder material volume based on the solder material area of the solder ball.

[0057] It can be understood that the plurality of solder ball tomographic images are continuously segmented and cut along the transverse tomographic direction, and thus each first binary image includes the solder material area of the solder ball at the transverse tomographic section. The solder material area of the solder ball corresponding to all the first binary images is added to obtain the solder material volume.

[0058] For example, the solder material area of the solder ball in the plurality of continuous first binary images along the transverse tomographic direction is integrated or added to obtain the solder material volume.

[0059] In some embodiments, the solder material volume is calculated based on the solder material area of the solder ball, specifically including but not limited to the following steps S351: S351: Adding the solder material area of the solder ball in all the binary images to obtain the solder material volume.

[0060] In this embodiment, the solder material area of the solder ball in each first binary image is added to obtain the solder material volume.

[0061] S36: Obtaining the hollow volume rate of the solder ball based on the solder ball volume and the solder material volume.

[0062] In the embodiment of the present application, the hollow volume rate is used to reflect the proportion of the internal hollow volume of the solder ball to the entire solder ball volume.

[0063] For example, in some embodiments, the hollow volume rate of the solder ball is obtained based on the solder ball volume and the solder material volume, specifically including but not limited to the following steps S361-S362: S361: Subtracting the solder material volume from the solder ball volume to obtain the hollow volume.

[0064] S362: Dividing the hollow volume by the solder ball volume to obtain the hollow volume rate.

[0065] In the embodiment of the present application, the following formula is used: to calculate the hollow volume rate of the solder ball. Wherein, is the hollow volume rate of the solder ball, is the solder ball volume, is the solder material volume, The hollow volume rate of the solder ball is calculated by substituting the solder ball volume and the solder material volume into the formula.

[0066] S37: A quality evaluation result of the solder ball is obtained based on the hollow volume rate of the solder ball.

[0067] It can be understood that the larger the hollow volume rate is, the worse the quality of the solder ball is, and the smaller the hollow volume rate is, the better the quality of the solder ball is. In the embodiment of the present application, the final quality evaluation result is determined according to a preset hollow rate threshold or a quality grade rule.

[0068] For example, a quality grade rule reference table is obtained, the quality grade rule reference table is used to represent the corresponding relationship between the hollow volume rate and the quality grade, the quality grade corresponding to the calculated hollow volume rate is found in the quality grade rule reference table according to the calculated hollow volume rate, and the quality grade corresponding to the hollow volume rate is taken as the quality evaluation result of the solder ball, or the quality evaluation result of the solder ball is generated according to the quality grade corresponding to the hollow volume rate.

[0069] For example, the quality grade rule reference table is shown in Table 1 as follows: Table 1:

[0070] According to Table 1, when the hollow volume rate is 8.6%, the quality grade corresponding to the hollow volume rate is A, and then the quality grade A is taken as the quality evaluation result of the solder ball, or the quality evaluation result of the solder ball is generated according to the quality grade A. It can be easily understood that Table 1 only schematically shows the corresponding relationship between the hollow volume rate of the solder ball and the quality grade, and does not cause any limitation on any case of other embodiments.

[0071] The solder ball quality evaluation method provided by the embodiment of the present application calculates the contour area of the solder ball and the solder material area by processing the tomographic image of the BGA solder ball, calculates the volume of the solder ball according to the contour area of the solder ball, calculates the volume of the solder material according to the solder material area of the solder ball, calculates the hollow volume rate of the solder ball according to the volume of the solder ball and the volume of the solder material, and does not depend on the deep learning model and the adaptive threshold segmentation method. In this way, the hollow volume rate of the solder ball is efficiently and accurately calculated, the accuracy of the hollow volume rate detection of the solder ball is improved, the stability and the reliability are high, the universality is strong, the quality evaluation result of the solder ball is accurately obtained according to the hollow volume rate, and the accuracy of the quality evaluation of the solder ball is improved.

[0072] For example, in some embodiments, the contour area of the solder ball in the binary image is calculated based on the binary image, specifically including but not limited to the following steps S331-S332: S331: The solder ball contour is extracted from the binary image.

[0073] S332: Calculate the solder ball contour area based on the coordinates of the contour points.

[0074] For example, for each first binary image, the solder ball contour is extracted from the first binary image, and the solder ball contour includes a plurality of contour points. For example, the contour formed by the red pixel points in the first binary image shown in Figure 7 , Figure 7 The contour formed by the red pixel points in the first binary image shown in

[0075] For example, the contour area of the solder ball is calculated according to the first formula, and the first formula is as follows:

[0076] In the first formula, is the number of contour points in the solder ball contour, , , , is the coordinate of the contour point. The coordinates of each contour point in the solder ball contour are obtained, and the coordinates of each contour point are substituted into the first formula to calculate the contour area of the solder ball. For example, according to the first formula, the contour area of the solder ball is calculated to be 1430 pixels. Figure 7

[0077] For example, in some embodiments, based on the binary image, the solder material area of the solder ball in the binary image is calculated, specifically including but not limited to the following steps S333-S335: S333: Based on the binary image, obtain the mask image corresponding to the binary image.

[0078] The mask image is a binary image that only includes the solder ball region and the non-solder ball region. In the embodiments of the present application, the non-target pixels outside the solder ball region and the non-target pixels inside the solder ball region in the first binary image are both masked to obtain the mask image corresponding to the first binary image. For example, referring to Figure 6 and Figure 8 , the non-target pixels outside the solder ball region and the non-target pixels inside the solder ball region in the first binary image shown in Figure 6 are both masked to obtain the mask image corresponding to the first binary image shown in Figure 8 .

[0079] In some embodiments, based on the binary image, the mask image corresponding to the binary image is obtained, specifically including but not limited to the following steps S3331: ​S3331: converting the first pixels outside the solder ball contour in the binarized image into second pixels, and converting the second pixels inside the solder ball contour in the binarized image into first pixels, to obtain a mask image corresponding to the binarized image.

[0080] In the embodiment, the first value is 255, and the second value is 0. Specifically, the first pixels (i.e., non-target pixels / white pixels) outside the solder ball contour in the first binarized image are converted into second pixels (i.e., black pixels), and the second pixels (i.e., non-target pixels / black pixels) inside the solder ball contour in the binarized image are converted into first pixels (i.e., white pixels), to obtain a mask image corresponding to the first binarized image.

[0081] S334: obtaining a target image based on the binarized image and the mask image.

[0082] In the embodiment, the target image is in the form of a binary image. Specifically, the pixels at corresponding positions in the first binarized image and the mask image are fused to obtain the target image. When the pixels at a candidate position in the first binarized image and the mask image are both black, the pixel at the candidate position in the target image is black. When the pixels at the candidate position in the first binarized image and the mask image are both white, the pixel at the candidate position in the target image is white. When the pixel at the candidate position in the first binarized image is white and the pixel at the candidate position in the mask image is black, the pixel at the candidate position in the target image is black. The candidate position is any position in the first binarized image or the mask image.

[0083] For example, as shown in FIG. 6, the first binarized image and the mask image are fused to obtain the target image. Figure 6 Figure 8 Figure 9 Figure 9 As shown in FIG. 6, the non-target pixels outside the solder ball region in the first binarized image have been filtered out and will not affect the calculation of the hollow volume. Figure 6

[0084] In some embodiments, the target image is obtained based on the binarized image and the mask image, specifically including but not limited to the following step S3341: S3341: performing a logical AND operation on the binarized image and the mask image corresponding to the binarized image to obtain the target image.

[0085] ​​​​For example, a logical AND operation is performed between the first binarized image and the corresponding mask image. This logical AND operation involves performing a bitwise AND operation on the pixel values ​​of corresponding positions in the first binarized image and the mask image. Specifically, when the pixel value of the corresponding position in both the first binarized image and the mask image is 255, the pixel value at that position is assigned a value of 255, making that pixel white. When the pixel value of the corresponding position in both the first binarized image and the mask image is 0, the pixel value at that position is assigned a value of 0, making that pixel black. When the pixel value of the corresponding position in the first binarized image is 255 and the pixel value of the corresponding position in the mask image is 0, the pixel value at that position is assigned a value of 0, making that pixel black, ultimately resulting in the target image.

[0086] S335: Calculate the area of ​​the target region in the target image.

[0087] In this embodiment, the area of ​​the target region is the area of ​​the solder ball, and the target region is the area occupied by pixels with a pixel value of the first value. Pixels with a pixel value of the first value are white pixels.

[0088] For example, after obtaining the target image, the area occupied by white pixels in the target image (i.e., the target area) is calculated, that is, the number of white pixels is counted, and the number of white pixels is used as the area of ​​the target area, thereby obtaining the solder area of ​​the solder ball.

[0089] For example, please see Figure 9 , Figure 9 The number of white pixels in the target image shown is the area of ​​the target region (i.e., the solder area of ​​the solder ball). The area of ​​the target region is the solder area of ​​the solder ball in the first binarized image, and the solder area of ​​the solder ball is 1370 pixels.

[0090] In some embodiments, the quality assessment result of the solder ball is obtained based on the void volume ratio of the solder ball, specifically including but not limited to the following steps S371-S372: S371: If the void volume ratio is greater than or equal to the volume ratio threshold, the first evaluation result is determined to be the quality evaluation result of the solder ball.

[0091] S372: If the void volume ratio is less than the volume ratio threshold, the second evaluation result is determined as the quality evaluation result of the solder ball.

[0092] In this embodiment, the engineers set the volume rate threshold value in advance according to engineering experience. After calculating the hollow volume rate of the solder ball, the embodiment compares the hollow volume rate with the volume rate threshold value. When the hollow volume rate is greater than or equal to the volume rate threshold value, it indicates that the hollow volume of the solder ball exceeds the threshold value, and the first evaluation result is determined as the quality evaluation result of the solder ball, which indicates that the solder ball is an unqualified solder ball. When the hollow volume rate is less than the volume rate threshold value, it indicates that the hollow volume of the solder ball does not exceed the threshold value, and the second evaluation result is determined as the quality evaluation result of the solder ball, which indicates that the solder ball is an unqualified solder ball.

[0093] In summary, the solder ball quality evaluation method provided by the embodiment can efficiently and accurately calculate the hollow volume rate of the solder ball by processing the tomographic image of the BGA solder ball, calculating the contour area and solder material area of the solder ball, calculating the solder ball volume according to the contour area of the solder ball, calculating the solder material volume according to the solder material area of the solder ball, and calculating the hollow volume rate of the solder ball according to the solder ball volume and the solder material volume. The method does not rely on deep learning models and adaptive threshold segmentation methods, and thus can efficiently and accurately calculate the hollow volume rate of the solder ball, improve the accuracy of the hollow volume rate detection of the solder ball, and has high stability, reliability and universality. Finally, the quality evaluation result of the solder ball is accurately obtained according to the hollow volume rate, and the accuracy of the solder ball quality evaluation is improved.

[0094] The embodiment provides a computer readable storage medium, and the computer readable storage medium stores computer program instructions executable by a processor. When the computer program instructions are executed by the processor, the computer executes any one of the solder ball quality evaluation methods provided by the embodiment, or executes the steps in any one of the possible implementation manners of the solder ball quality evaluation methods provided by the embodiment.

[0095] In some embodiments, the storage medium can be a flash memory, a hard disk, an optical disk, a register, a magnetic surface memory, a removable disk, a CD-ROM, a random access memory (RAM), a read-only memory (ROM), an electrically programmable ROM, and an electrically erasable programmable ROM, or any other form of storage medium known in the art, or various devices including one or any combination of the above storage mediums.

[0096] In some embodiments, the computer program instructions can be in the form of programs, software, software modules, scripts or codes, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and can be deployed in any form, including being deployed as independent programs or being deployed as modules, components, subroutines or other units suitable for use in a computing environment.

[0097] As an example, computer program instructions can be, but are not necessarily, resident in a file system, and can be stored in one or more files on a file system, in a machine readable storage medium, in one or more computer program products, in one or more physical computer storage devices, such as a hard disk, floppy disk, CD-ROM, or DVD, in one or more memories, such as a ROM, RAM, or flash memory, in one or more physically distinct computer program products, such as one or more physical computer storage devices, or in one or more files in a file system. As another example, computer program instructions can be stored in a transitory computer-readable medium, such as a communication network or a wireless communication channel.

[0098] As an example, computer program instructions can be deployed to be executed by one or more computing devices, such as those included in a smart terminal or a server, or by multiple computing devices located at one site or distributed across multiple sites and interconnected by a communication network. It will be readily understood that the individual steps of the methods described in the embodiments of the present application can be implemented directly using electronic hardware, or using computer program instructions executable by a processor, or using a combination of the two.

[0099] Those skilled in the art can understand that the embodiments provided by the present application are only illustrative, and the writing order of the individual steps in the methods of the embodiments does not mean a strict execution order and does not constitute any limitation on the implementation process, and the order can be adjusted, combined, and deleted according to actual needs. The modules or sub-modules, units or sub-units, etc. in the devices or systems of the embodiments can be combined, divided, and deleted according to actual needs. For example, the division of the unit is only a logical functional division, and there can be another division manner in actual implementation. For another example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0100] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Those skilled in the art can understand that all or part of the processes in the above-described embodiments can be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium, and when the computer program is executed, the processes of the embodiments of the above-described methods can be included.

[0101] It should be noted that the above examples are intended to illustrate the technical concept and characteristics of the present application, and the purpose is to enable those skilled in the art to understand the content of the present application and to implement it accordingly, and cannot be used to limit the scope of protection of the present application. Those skilled in the art can understand that all or part of the processes of the above examples can be modified according to the technical solutions described in the embodiments of the present application, or some technical features can be replaced equivalently. It can be understood that these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be regarded as equivalent changes and modifications based on the embodiments of the present application, and should belong to the scope covered by the claims of the present application.

Claims

1. A method of solder ball quality assessment, characterized by, The method comprises: obtaining solder ball image data, the solder ball image data comprising a plurality of continuous solder ball tomographic images; performing binaryzation processing on the solder ball tomographic images to obtain binaryzation images corresponding to the solder ball tomographic images; based on the binaryzation images, calculating the contour area and the solder material area of the solder ball in the binaryzation images; based on the contour area of the solder ball, calculating the volume of the solder ball; based on the solder material area of the solder ball, calculating the volume of the solder material; based on the volume of the solder ball and the volume of the solder material, obtaining the hollow volume rate of the solder ball; based on the hollow volume rate of the solder ball, obtaining the quality evaluation result of the solder ball.

2. The method of claim 1, wherein, The method comprises: extracting the solder ball contour from the binaryzation image, the solder ball contour comprising a plurality of contour points; based on the coordinates of the contour points, calculating the contour area of the solder ball.

3. The method of claim 1, wherein, The method comprises: based on the binaryzation image, obtaining a mask image corresponding to the binaryzation image; based on the binaryzation image and the mask image, obtaining a target image in the form of a binary image; calculating the area of a target region in the target image, the area of the target region being the solder material area of the solder ball, the target region being a region occupied by pixels with a first value.

4. The method of claim 3, wherein, The method comprises: converting first pixels outside the solder ball contour in the binaryzation image into second pixels, and converting second pixels inside the solder ball contour in the binaryzation image into first pixels, to obtain a mask image corresponding to the binaryzation image, the first pixels being pixels with a first value, and the second pixels being pixels with a second value.

5. The method of claim 3, wherein, The method comprises: performing a logical AND operation on the binaryzation image and the mask image corresponding to the binaryzation image to obtain the target image.

6. The method of claim 1, wherein, The method comprises: adding the contour areas of the solder ball in all the binaryzation images to obtain the volume of the solder ball.

7. The method of claim 1, wherein, The method comprises: adding the solder material areas of the solder ball in all the binaryzation images to obtain the volume of the solder material.

8. The method according to any one of claims 1 to 7, characterized in that, The method comprises: subtracting the volume of the solder material from the volume of the solder ball to obtain the hollow volume; dividing the hollow volume by the volume of the solder ball to obtain the hollow volume rate.

9. The method according to any one of claims 1-7, characterized in that, The method comprises: in response to the hollow volume rate being greater than or equal to a volume rate threshold, determining a first evaluation result as the quality evaluation result of the solder ball, the first evaluation result indicating that the solder ball is an unqualified solder ball; in response to the hollow volume rate being less than the volume rate threshold, determining a second evaluation result as the quality evaluation result of the solder ball, the second evaluation result indicating that the solder ball is a qualified solder ball.

10. An electronic device, comprising: The method comprises: a processor and a memory connected to the processor in communication; the memory stores computer program instructions executable by the processor, which, when executed by the processor, causes the electronic device to perform the solder ball quality evaluation method according to any one of claims 1-9.

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