Welding Quality Detection Method and Welding Quality Detection Equipment

Abstract

The present application discloses a welding quality detection method and a welding quality detection device. The welding quality detection method includes: obtaining a detection image; using a processing device to calculate a staining area percentage of an area stained with staining ink in a welding area in the detection image with respect to the area of the welding area, and determining whether the staining area percentage is greater than a predetermined staining percentage; if it is determined that the staining area percentage is not greater than the predetermined staining percentage, it is determined that the welding quality at the position to be detected is good, and detection result information is generated; if it is determined that the staining area percentage is greater than the predetermined staining percentage, it is determined that the welding quality at the position to be detected is poor, and detection result information is generated.

Description

Technical Field

[0001] The present application relates to a welding quality detection method and a welding quality detection device, and particularly to a welding quality detection method and a welding quality detection device for detecting the welding quality of a substrate welded by surface mount technology (SMT). Background Art

[0002] The Red Dye Penetration Test is one of the common methods used to detect the welding quality of a circuit board. The general process of this method is as follows: First, the circuit board to be detected is immersed in red ink. Then, after the circuit board is taken out and dried, the electrical components (such as IC chips, etc.) on the circuit board are removed. Subsequently, the circuit board is manually placed under a microscope with an appropriate magnification, and the condition of the welding area on the circuit board is observed by the naked eye, and the welding quality of the welding area is judged based on personal experience.

[0003] In the above detection process, the observation is mainly carried out by the naked eye of a human, and the judgment of the welding quality is subjectively made by relevant personnel. Therefore, problems such as incorrect judgment often occur, and the method of observing manually requires a large amount of time and cost. In addition, when observing and judging with the naked eye of a human, there may also be a problem that different people have completely different judgments on the welding quality of the same circuit board. Summary of the Invention

[0004] The present application discloses a welding quality detection method and a welding quality detection device, mainly for improving problems such as time-consuming, laborious, and poor detection quality in the conventional method of observing the welding quality of relevant welding positions on a substrate by the naked eye of a human.

[0005] One embodiment of the present application discloses a welding quality detection method for detecting the welding quality of a to-be-detected position of a to-be-detected component. The to-be-detected component is formed by a process of soaking a dye ink, drying, and removing an electronic component included in an electronic component. The electronic component includes a substrate and an electronic component. The substrate is provided with at least one solder pad, and the solder pad is connected to the electronic component through a welding structure. The position of the substrate for setting the solder pad is defined as the to-be-detected position. The welding quality detection method includes: an image acquisition step: acquiring a detection image, where the detection image includes at least one welding area, and the welding area corresponds to the image of the to-be-detected position; a percentage calculation and quality determination step: using a processing device to calculate the area percentage of the area stained by the dye ink in the welding area accounting for the area of the welding area, and using the processing device to determine whether the staining area percentage is greater than a predetermined staining percentage; if the processing device determines that the staining area percentage is not greater than the predetermined staining percentage, the processing device will determine that the welding quality of the to-be-detected position is good and generate a corresponding detection result information; if the processing device determines that the staining area percentage is greater than the predetermined staining percentage, the processing device will determine that the welding quality of the to-be-detected position is poor and generate a corresponding detection result information.

[0006] Optionally, between the image acquisition step and the percentage calculation and quality determination step, there is also an image processing step: using the processing device to adjust at least one of the R value, G value, and B value of at least a part of the pixels in the detection image, or adjust at least one of the H value, S value, and V value of at least a part of the pixels in the detection image, according to at least one of the color of the dye ink, the color of the welding structure, and the color of the solder mask layer of the substrate.

[0007] Optionally, in the image acquisition step, first control an auxiliary light source to project an auxiliary light beam onto the to-be-detected position of the substrate, then control an image capture device to capture the image of the to-be-detected position of the substrate to generate a detection image, and then control the image capture device to transmit the detection image to the processing device; wherein, the color of the auxiliary light beam is the same type of color as the color of the dye ink, or the color of the auxiliary light beam is determined according to the dye ink and the subtractive color mixing method, so that the pixels stained by the dye ink in the detection image appear as gray or black.

[0008] Optionally, between the image acquisition step and the percentage calculation and quality determination step, the following is also included: a welding structure judgment step: using a processing device to determine whether there is an image of a welding structure in the welding area, and the image of the welding structure corresponds to the image of the welding structure on the substrate; if the processing device determines that there is no image of the welding structure in the welding area, the processing device will determine that there is a gap between the pad and the substrate, and the welding quality of the position to be detected is poor, and corresponding detection result information will be generated, and the processing device will no longer execute the percentage calculation and quality determination steps; if the processing device determines that there is an image of the welding structure in the welding area, the percentage calculation and quality determination steps will be continued.

[0009] Optionally, in the percentage calculation and quality determination step, if the processing device determines that the stained area percentage is greater than a predetermined staining percentage, the following steps will be executed: a brightness judgment step: using the processing device to calculate the average brightness of all pixels in the welding area and determine whether the average brightness is lower than a predetermined brightness; if the processing device determines that the average brightness is lower than the predetermined brightness, the processing device will determine that there is a gap at the position where the pad is connected to the welding structure, and the welding quality of the position to be detected is poor, and corresponding detection result information will be generated; wherein, the predetermined staining percentage is not less than 1%.

[0010] Optionally, in the brightness judgment step, if the processing device determines that the average brightness is not lower than the predetermined brightness, the following steps will be executed: a boundary arc shape judgment step: using the processing device to determine whether there is a high-brightness area in the welding area, and at least one section of the boundary of the high-brightness area is arc-shaped; wherein, the average brightness of all pixels included in the high-brightness area is greater than the average brightness of the remaining area of the welding area; if the processing device determines that there is a high-brightness area in the welding area and at least one section of the boundary of the high-brightness area is arc-shaped, the processing device will determine that there is a soldering problem of pillow effect between the pad and the connected welding structure, and the welding quality of the position to be detected is poor, and corresponding detection result information will be generated; if the processing device determines that there is a high-brightness area in the welding area, but there is no arc-shaped section in the boundary of the high-brightness area, the processing device will determine that there is a soldering problem of open circuit between the pad and the connected welding structure, and the welding quality of the position to be detected is poor, and corresponding detection result information will be generated.

[0011] Optionally, in the boundary arc shape judgment step, when the processing device determines that the percentage of the total number of pixels with brightness higher than the average brightness in the welding area in the total number of all pixels in the welding area exceeds 10%, the processing device will determine that the welding area contains a high-brightness area.

[0012] Optionally, in the percentage calculation and quality determination steps, if the processing device determines that the percentage of the stained area is not greater than a predetermined staining percentage, the following steps are performed: a brightness calculation step: using the processing device to calculate the brightness of each pixel in the welding area; a defect determination step: using the processing device to compare the brightness of each pixel to determine whether there is a defect area in the welding area; wherein, the average brightness of all pixels in the defect area is lower than a predetermined brightness; if the processing device determines that there is at least one defect area in the welding area, the processing device will determine that there are bubbles or voids in the welding area, and the welding quality of the position to be detected is poor, and corresponding detection result information is generated; if the processing device determines that there is no defect area in the welding area, the processing device will determine that the welding quality of the position to be detected is good, and corresponding detection result information is generated; wherein, the predetermined staining percentage is between 0% and 25%.

[0013] Optionally, the substrate is provided with a plurality of pads, and each pad is connected to a welding structure, and at least one electronic component is connected to the plurality of pads through the plurality of welding structures. The position where the substrate is used to set each pad is defined as a position to be detected; the welding quality detection method is used to detect the welding quality of the component to be tested. In the image acquisition step, it is detected that the image contains a plurality of welding areas, and each welding area corresponds to the image of one of the positions to be detected; between the image acquisition step and the percentage calculation and quality determination steps, the following steps are further included: a detection quantity calculation step: calculating the total number of welding areas included in the detection image; after the detection quantity calculation step, the percentage calculation and quality determination steps are repeatedly executed a predetermined number of times, the predetermined number of times is equal to the total number of welding areas, and in each percentage calculation and quality determination step, the processing device calculates the percentage of the stained area of different welding areas; after the percentage calculation and quality determination steps are executed the predetermined number of times, the following steps are performed: a total percentage calculation and quality determination step: using the processing device to calculate the percentage of the number of stained welding areas greater than the predetermined staining percentage in the total number of welding areas, and determining whether the percentage of the number of stained areas is greater than a predetermined percentage of the number of areas; if the processing device determines that the percentage of the number of stained areas is greater than the predetermined percentage of the number of areas, the processing device will determine that the welding quality of the component to be tested is poor, and correspondingly generate a detection result information of the component to be tested; if the processing device determines that the percentage of the number of stained areas is not greater than the predetermined percentage of the number of areas, the processing device will determine that the welding quality of the component to be tested is good, and correspondingly generate a detection result information of the component to be tested.

[0014] Optionally, the following steps are further included between the image acquisition step and the percentage calculation and quality determination step: A numbering step: The processing device can sequentially assign a number to a plurality of welding areas according to a first direction and a second direction in sequence; the first direction is different from the second direction; the processing device assigns different numbers to each welding area; wherein, after the numbering step, the processing device sequentially performs the percentage calculation and quality determination step on the plurality of welding areas according to the plurality of numbers, and the processing device will generate detection result information corresponding to each welding area, and each detection result information includes the corresponding number.

[0015] Optionally, in the numbering step, the processing device first rotates the detection image by a predetermined angle, and then sequentially assigns numbers to a plurality of welding areas according to the first direction and the second direction in sequence.

[0016] One embodiment of the present application discloses a welding quality detection device, which includes: a stage, a processing device, an image capturing device, and an output device. The stage is used to carry a substrate. The image capturing device and the output device are respectively electrically connected to the processing device. The processing device can execute a welding quality detection method. The welding quality detection method is used to detect the welding quality of a to-be-detected position of a to-be-detected component. The to-be-detected component is formed by an electronic component through a process of soaking in a staining ink, drying, and removing an electronic element included in the electronic component. The electronic component includes a substrate and an electronic element. The substrate is provided with at least one pad, and the pad is connected to the electronic element through a welding structure. The position of the substrate for setting the pad is defined as the to-be-detected position. The welding quality detection method includes: An image acquisition step: controlling the image capturing device to capture an image of the to-be-detected position of the to-be-detected component disposed on the stage to obtain a detection image. The detection image includes at least one welding area, and the welding area corresponds to the image of the to-be-detected position; A percentage calculation and quality determination step: calculating the area percentage of the area stained by the staining ink in the welding area to the area of the welding area; A percentage calculation and quality determination step: determining whether the staining area percentage is greater than a predetermined staining percentage; if the staining area percentage is not greater than the predetermined staining percentage, it is determined that the welding quality of the to-be-detected position is good, and a corresponding detection result information is generated and transmitted to the output device; if the staining area percentage is greater than the predetermined staining percentage, it is determined that the welding quality of the to-be-detected position is poor, and a corresponding detection result information is generated and transmitted to the output device.

[0017] Optionally, between the image acquisition step and the percentage calculation and quality determination step, the method further includes: a welding structure judgment step: determining whether there is an image of a welding structure in the welding area, where the image of the welding structure corresponds to the image of the welding structure on the substrate; if it is determined that there is no image of the welding structure in the welding area, it is determined that there is a gap between the pad and the substrate, and the welding quality at the position to be detected is poor, and corresponding detection result information is generated, and the percentage calculation and quality determination steps are no longer executed; if it is determined that there is an image of the welding structure in the welding area, the percentage calculation and quality determination steps are continued.

[0018] Optionally, in the percentage calculation and quality determination step, if it is determined that the percentage of the stained area is greater than a predetermined staining percentage, a brightness judgment step is executed: calculating an average brightness of all pixels in the welding area, and determining whether the average brightness is lower than a predetermined brightness; if it is determined that the average brightness is lower than the predetermined brightness, it is determined that there is a gap at the position where the pad is connected to the welding structure, and the welding quality at the position to be detected is poor, and corresponding detection result information is generated; wherein, the predetermined staining percentage is not less than 1%.

[0019] Optionally, in the brightness judgment step, if it is determined that the average brightness is not lower than the predetermined brightness, the following steps are executed: a boundary arc shape judgment step: determining whether there is a high-brightness area in the welding area, and at least one section of the boundary of the high-brightness area is arc-shaped; wherein, the average brightness of all pixels included in the high-brightness area is greater than the average brightness of the remaining area of the welding area; if it is determined that there is a high-brightness area in the welding area and at least one section of the boundary of the high-brightness area is arc-shaped, it is determined that there is a soldering problem of pillow effect between the pad and the connected welding structure, and the welding quality at the position to be detected is poor, and corresponding detection result information is generated; if it is determined that there is a high-brightness area in the welding area and no section of the boundary of the high-brightness area is arc-shaped, it is determined that there is a soldering problem of open circuit between the pad and the connected welding structure, and the welding quality at the position to be detected is poor, and corresponding detection result information is generated.

[0020] Optionally, in the boundary arc shape judgment step, when it is determined that the percentage of the total number of pixels with brightness higher than the average brightness in the welding area in the total number of all pixels in the welding area exceeds 10%, it is determined that the welding area contains a high-brightness area.

[0021] Optionally, in the percentage calculation and quality determination steps, if it is determined that the percentage of the stained area is not greater than a predetermined staining percentage, the following steps are performed: a brightness calculation step: calculating the brightness of each pixel in the welding area; a defect determination step: comparing the brightness of each pixel to determine whether there is a defect area in the welding area; wherein, the average brightness of all pixels in the defect area is lower than a predetermined brightness; if it is determined that there is at least one defect area in the welding area, it is determined that there are bubbles or voids in the welding area, and the welding quality of the position to be detected is poor, and corresponding detection result information is generated; if it is determined that there is no defect area in the welding area, it is determined that the welding quality of the position to be detected is good, and corresponding detection result information is generated; wherein, the predetermined staining percentage is between 0% and 25%.

[0022] Optionally, the substrate is provided with a plurality of pads, and each pad is connected to a welding structure, and at least one electronic component is connected to the plurality of pads through the plurality of welding structures. The position where the substrate is used to set each pad is defined as a position to be detected; the welding quality detection method is used to detect the welding quality of the component to be tested. In the image acquisition step, it is detected whether the image contains a plurality of welding areas, and each welding area corresponds to the image of one of the positions to be detected; between the image acquisition step and the percentage calculation and quality determination steps, the following steps are further included: a detection quantity calculation step: calculating the total number of welding areas included in the detection image; after the detection quantity calculation step, the percentage calculation and quality determination steps are repeatedly executed a predetermined number of times, the predetermined number of times is equal to the total number of welding areas, and in each percentage calculation and quality determination step, the percentage of the stained area of different welding areas is calculated; after the percentage calculation and quality determination steps are executed a predetermined number of times, the following steps are performed: a total number percentage calculation and quality determination step: calculating the percentage of the number of stained welding areas greater than the predetermined staining percentage in the total number of welding areas, and determining whether the percentage of the number of stained areas is greater than a predetermined percentage of the number; if it is determined that the percentage of the number of stained areas is greater than the predetermined percentage of the number, it is determined that the welding quality of the component to be tested is poor, and a detection result information of the component to be tested is correspondingly generated; if it is determined that the percentage of the number of stained areas is not greater than the predetermined percentage of the number, it is determined that the welding quality of the component to be tested is good, and a detection result information of the component to be tested is correspondingly generated.

[0023] Optionally, the following steps are further included between the image acquisition step and the percentage calculation and quality determination step: A numbering step: rotating the detected image by a predetermined angle, or adjusting the position of at least one welding area in the detected image in the detected image, so as to sequentially assign a number to a plurality of welding areas according to a first direction and a second direction in sequence; the first direction is different from the second direction; wherein, each welding area is assigned a different number; wherein, after the numbering step, the percentage calculation and quality determination step are performed on the plurality of welding areas according to the plurality of numbers in sequence, and detection result information corresponding to each welding area is generated, and each detection result information includes the corresponding number.

[0024] Optionally, in the numbering step, the processing device first rotates the detected image by a predetermined angle, and then sequentially assigns numbers to the plurality of welding areas according to the first direction and the second direction in sequence.

[0025] In summary, the welding quality detection method and the welding quality detection device of the present application can quickly and correctly judge the welding quality of the to-be-detected position of the substrate, and during the determination process, there is no subjective judgment of relevant personnel. Therefore, the problem that different people observe the same substrate but make completely different judgments in the prior art will not occur.

[0026] For a further understanding of the features and technical content of the present application, please refer to the following detailed description and drawings of the present application. However, these descriptions and drawings are only used to illustrate the present application and do not impose any limitation on the protection scope of the present application. Description of the Drawings

[0027] Figure 1 It is a block diagram of the welding quality detection device of the present application.

[0028] Figure 2 It is a flowchart of the first embodiment of the welding quality detection method of the present application.

[0029] Figure 3 And Figure 4 They are schematic diagrams showing the detection images determined to have good and poor welding quality respectively through the first embodiment of the welding quality detection method of the present application presented on the display device.

[0030] Figure 5 It is a flowchart of the second embodiment of the welding quality detection method of the present application.

[0031] Figure 6 It is a flowchart of the third embodiment of the welding quality detection method of the present application.

[0032] Figure 7 And Figure 8Schematic flowcharts of the fourth embodiment of the welding quality inspection method of the present application, and schematic diagrams showing inspection images for determining that there is no welding structure in the welding area presented on a display device using this embodiment.

[0033] Figure 9 Schematic flowchart of the fifth embodiment of the welding quality inspection method of the present application.

[0034] Figure 10 And Figure 11 Schematic diagrams showing inspection images for determining that pillow effect and open circuit soldering problems occur in solder pads at positions to be inspected and their connected welding structures through the fifth embodiment of the welding quality inspection method of the present application.

[0035] Figure 12 And Figure 13 Schematic flowcharts of the sixth embodiment of the welding quality inspection method of the present application, and schematic diagrams showing inspection images for determining that there are bubbles or voids in the welding area presented on a display device using this embodiment.

[0036] Figure 14 Schematic flowchart of the seventh embodiment of the welding quality inspection method of the present application.

[0037] Figure 15 Schematic flowchart of the eighth embodiment of the welding quality inspection method of the present application.

[0038] Figure 16 Schematic diagram of the numbering steps of the eighth embodiment of the welding quality inspection method of the present application. Detailed implementation manners

[0039] In the following description, if specific figures are pointed out or as shown in specific figures, it is only to emphasize that in the subsequent description, most of the related content mentioned appears in that specific figure, but it does not limit that only that specific figure can be referred to in the subsequent description.

[0040] Please refer to Figures 1 to 4, the welding quality detection device 100 of the present application is used to detect the welding quality of at least one position to be detected of a component to be detected, and the welding quality detection method of the present application is used to detect the welding quality of at least one position to be detected of a component to be detected. In practical applications, the welding quality detection method of the present application can be executed by the welding quality detection device 100 of the present application, but is not limited thereto. The component to be detected is formed by an electronic component successively through a process of soaking in a staining ink, drying, and removing at least one electronic component included in the electronic component. The electronic component includes a substrate and the electronic component. The substrate is provided with at least one solder pad (commonly known as PAD). The solder pad is connected to the electronic component through a welding structure. The position on the substrate for setting the solder pad is defined as the position to be detected.

[0041] In practical applications, the staining ink can be, for example, red ink, but is not limited thereto. The color of the staining ink can be determined, for example, according to the surface color of the circuit board. Regarding the soaking time of the substrate in the staining ink, the drying time after soaking, etc., they can all be determined according to the actual material of the substrate, the type of staining ink, the type of electronic component, etc., and are not limited herein. The substrate can be various circuit boards; the solder pad can be connected to a trace on the substrate, or the solder pad can be not connected to a trace on the substrate; the welding structure can be composed of, for example, solder balls, solder paste, etc., but is not limited thereto; the electronic component can be any electronic part. For example, the electronic component can be an IC chip.

[0042] The welding quality detection device 100 of the present application includes a stage (not shown in the figure), a processing device 1, and an image capturing device 2. The stage is used to carry the component to be detected. The processing device 1 is electrically connected to the image capturing device 2. The processing device 1 can control the image capturing device 2 to capture an image of the position to be detected of the component to be detected. The processing device 1 can execute the welding quality detection method of the present application to judge the welding quality of at least one position to be detected included in the component to be detected set on the stage. The stage can be any mechanism that can be used to carry and fix the substrate; the processing device 1 refers to any computer, cloud server, etc. that can perform image recognition and image calculation.

[0043] The welding quality detection method of the present application includes:

[0044] An image acquisition step S11: Acquire a detection image 21. The detection image 21 includes at least one welding area 21A, and the welding area 21A corresponds to the image of the position to be detected.

[0045] A percentage calculation and quality determination step S12: Use the processing device 1 to calculate the area percentage of the area stained by the staining ink in the welding area 21A with respect to the area of the welding area 21A, and use the processing device 1 to determine whether the staining area percentage is greater than a predetermined staining percentage;

[0046] If the processing device determines that the staining area percentage is not greater than (less than or equal to) the predetermined staining percentage, the processing device will determine that the welding quality at the position to be detected is good (as Figure 3 shown), and generate a corresponding detection result information 11;

[0047] If the processing device determines that the staining area percentage is greater than the predetermined staining percentage, the processing device will determine that the welding quality at the position to be detected is poor (as Figure 4 shown), and generate the corresponding detection result information 11.

[0048] In practical applications, in the image acquisition step S11, it can be to use the image capture device 2 to capture an image of a single position to be detected of the component to be measured to directly form the detection image 21, or, it can be to first use the image capture device 2 to capture a captured image including multiple positions to be detected on the component to be measured, and then, according to the requirements, segment an image including a single position to be detected from the captured image to be used as the detection image 21.

[0049] In the percentage calculation and quality determination step S12, the processing device 1 can, for example, calculate the RGB values (or HSV values) of each pixel in the welding area 21A, and compare them with the RGB values (or HSV values) of each pixel in the welding area 21A stored in advance corresponding to the staining ink to determine which pixels belong to the stained pixels. Finally, by calculating the number of stained pixels and the total number of pixels included in the welding area 21A, the staining area percentage is calculated. For example, if the staining ink is red, the processing device 1 can determine whether the R value, G value, and B value of each pixel in the welding area 21A respectively fall within a predetermined range (for example, the R value is greater than 200, the G value is less than 130, and the B value is less than 130); if the processing device 1 determines that the R value, G value, and B value of the current pixel respectively fall within the predetermined range, the processing device 1 can determine that the current pixel has been stained red; of course, the processing device 1 can also convert the RGB value of each pixel into an HSV value and then compare it with the HSV value of the corresponding staining ink stored in advance to determine whether the pixels in the welding area 21A have been stained. In practical applications, the imaging device 2 can be used to capture the staining ink in an environment with the same light source to generate a captured image, and then the processing device can analyze the captured image to obtain the predetermined range.

[0050] In one specific application, in order to improve the speed at which the processing device 1 executes the percentage calculation and quality determination step S12, in the image acquisition step S11, the image capture device 2 can also be provided with a filter, so that the image capture device 2 can only receive light beams corresponding to the color of the dye ink. In one preferred embodiment, the welding quality detection device 100 can also include a display device 3 and at least one input device 4, and the processing device 1 is electrically connected to the display device 3 and the input device 4. The processing device 1 can control the display device 3 to display the detection image 21, and after the percentage calculation and quality determination step S12, the processing device 1 can control the display device 3 to display the detection result information 11, and the detection result information 11 can include the detection image 21 and a calculation result data 111. In this way, the user can simultaneously see the detection image 21 and the calculation result data 111 through the detection result information 11 displayed on the display device 3 to know what percentage of the area in the current detection image 21 has been dyed. Among them, the calculation result data 111 is generated after the processing device 1 executes the percentage calculation and quality determination step S12. In addition, the user can, according to actual needs, operate the input device 4 to determine the predetermined dyeing percentage. The input device 4 can include, for example, a mouse, a keyboard, a touch screen, etc. In one specific embodiment, the predetermined dyeing percentage can be 0-25%; in the embodiment where the predetermined dyeing percentage is 0%, in the percentage calculation and quality determination step S12, as long as the welding area 21A is dyed, the processing device 1 will determine that the welding quality is poor.

[0051] As Figure 3 shown, if the processing device 1 determines that the welding quality of the position to be detected is good, for example, the user can view the detection image 21 (the shaded part in the figure represents the dyed area) and the text such as "predetermined dyeing percentage: 0.5%" (i.e., the calculation result data 111) in the detection result information 11 displayed on the display device 3, and the user can judge whether the processing device 1 makes a mistake in the determination by viewing the detection image 21 and the calculation result data 111.

[0052] As Figure 4 shown, if the processing device 1 determines that the welding quality of the position to be detected is poor, for example, the user can view the detection image 21 (the shaded part in the figure represents the dyed area) and the text such as "predetermined dyeing percentage: 68%" (i.e., the calculation result data 111) in the detection result information 11 displayed on the display device 3, and the user can further judge the cause of the poor welding quality of the current position to be detected by viewing the detection image 21. Of course, the user can also judge whether the processing device 1 makes a mistake in the determination by viewing the detection image 21 and the calculation result data 111.

[0053] In practical applications, the processing device 1 can receive a change information 41 generated by the input device 4 and change the RGB value (or HSV value) of the dyeing ink in the percentage calculation and quality determination step S12; that is to say, the user can, according to the color of the dyeing ink currently in use, operate the input device 4 to change the RGB value (i.e., the RGB value of the dyeing ink) used by the processing device 1 in the percentage calculation and quality determination step S12 to compare whether each pixel in the welding area 21A is dyed.

[0054] In a specific implementation, after the processing device 1 executes the percentage calculation and quality determination step S12, the processing device 1 can transmit the detection result information 11 and the detection image 21 to the display device 3 or an external electronic device (such as a remote server, a smart phone, a tablet computer, etc.), and the user can then understand whether the welding quality of the current position to be detected is good by viewing the detection result information 11 and the detection image 21 displayed on the display device 3.

[0055] The above-mentioned welding quality detection method and welding quality detection device of the present application are more efficient and have stable quality determination compared with the conventional method of using the naked eye in combination with devices such as microscopes to observe and judge whether the welding quality is good. More specifically, the conventional process for detecting the welding quality of the position to be detected is that relevant personnel set the component to be tested under an electron microscope (or a microscope with an appropriate magnification), and then relevant personnel subjectively judge whether there is dyeing ink in the welding area by visual observation, and finally subjectively determine the welding quality of the position to be detected; this method is not only time-consuming and laborious, but also highly dependent on the experience of relevant personnel. Even different personnel observing the same position to be detected may obtain completely different judgment results. Therefore, the conventional detection method has an unstable quality determination situation.

[0056] Please refer to Figure 1 and Figure 5, the biggest difference between this embodiment and the aforementioned first embodiment lies in that: between the image acquisition step S11 and the percentage calculation and quality determination step S12, there is also an image processing step SX: the processing device 1 adjusts at least one of the R value, G value, and B value of at least a part of the pixels in the detection image 21, or adjusts at least one of the H value, S value, and V value of at least a part of the pixels in the detection image 21, based on at least one of the color of the staining ink, the color of the welding structure, and the color of the solder mask of the substrate. Thereby, when the processing device 1 executes the percentage calculation and quality determination step S12, it can better judge the pixels that have been stained, so as to more accurately calculate the staining area percentage and more accurately determine the welding quality of the position to be detected.

[0057] For example, the processing device 1 can first use the R value, G value, and B value (or H value, S value, and V value) of the solder mask as a reference to judge the pixels with substantially the same R value, G value, and B value (or H value, S value, and V value), and then adjust the RGB values (or HSV values) of these pixels towards the hue of black.

[0058] For example, assuming the staining ink is red, the processing device 1 can first use the actual R value, G value, and B value (or H value, S value, and V value) of the staining ink as a reference to judge the pixels with substantially the same R value, G value, and B value (or H value, S value, and V value), and then adjust the RGB values of these pixels to (255, 0, 0). That is to say, the processing device 1 first judges which pixels have been stained, and then the processing device 1 directly adjusts the RGB values of these pixels to pure red.

[0059] For example, assuming the staining ink is red, in the image processing step SX, the processing device 1 can first judge whether the R value, G value, and B value of each pixel meet the relational expression of R > 200, G < 130, and B < 130. If the processing device 1 judges that the RGB value of the pixel meets the above relational expression, the processing device 1 can modify the R value of the pixel to 255 and adjust the G value and B value of the pixel to one-fourth of the original value.

[0060] In different applications, in the image processing step SX, the processing device 1 can also read each pixel one by one and compare the RGB value (or HSV value) of each pixel with that of adjacent pixels. If the RGB value of the current pixel differs significantly from that of adjacent pixels, the processing device 1 can directly modify the current pixel to black or white. Thus, each pixel included in the detected image obtained through the image processing step SX appears either black or white. In the percentage calculation and quality determination step S12, the processing device can simply calculate the percentage of the stained area by calculating the number of white (or black) pixels.

[0061] Please also refer to Figure 1 and Figure 6 , the welding quality detection method of this embodiment sequentially includes an image acquisition step S21 and a percentage calculation and quality determination step S22. The percentage calculation and quality determination step S22 is the same as the percentage calculation and quality determination step S12 of the first embodiment and will not be elaborated here.

[0062] In the image acquisition step S21, first, at least one auxiliary light source is controlled to project an auxiliary light beam onto at least one position to be detected on the substrate. Then, the image capture device 2 is controlled to capture an image of at least one position to be detected on the substrate to generate a detected image 21. Subsequently, the image capture device 2 is controlled to transfer the detected image 21 to the processing device 1. The auxiliary light beam is mainly used to enhance the edges of defects (such as bubbles, holes, stained areas) existing on the pads at the positions to be detected. Thereby, the stained areas or defect areas in the detected image 21 can be more clearly displayed, and the processing device 1 can better identify whether specific defects (such as bubbles, holes, etc.) appear in the welding area in the detected image 21. In one specific embodiment, the auxiliary light source can be a ring light.

[0063] In one embodiment, the image capture device 2 can be arranged directly above the substrate, while the auxiliary light source is not arranged directly above the substrate, and the auxiliary light beam emitted by the auxiliary light source is projected onto each position to be detected on the substrate in a lateral direction. Thus, the presentation effect of various boundaries in the detected image 21 can be enhanced, such as the boundary between the welding area and the solder mask, the boundary of bubbles (or holes, etc.) within the welding area, etc. The auxiliary light source referred to in this embodiment can be white light, but is not limited thereto.

[0064] In one embodiment, the color of the auxiliary light beam emitted by the auxiliary light source may be a similar color to the color of the dye ink. For example, if the color of the dye ink is red, the auxiliary light source may emit a light beam with a wavelength between 620 and 750 nm. In this way, the red color of the dyed area in the welding area of the detected image can be made more obvious.

[0065] In another embodiment, the color of the auxiliary light beam emitted by the auxiliary light source may be determined based on the dye ink and the subtractive mixing method, so that the pixels dyed with the dye ink in the detected image appear as gray or black. For example, if the dye ink is red, two auxiliary light sources may be made to emit light beams close to yellow (570 - 590 nm) and close to cyan (476 - 495 nm) respectively and project them onto the substrate simultaneously. In this way, the pixels dyed with the dye ink in the detected image will appear in a form close to black or gray.

[0066] In one different embodiment, a fluorescent agent may also be added to the dye ink, and the component to be tested and the image capturing device may be arranged in a dark room, and the auxiliary light source may emit ultraviolet light and project it onto the component to be tested. In this way, in the captured image, the undyed area will generally appear black, while the dyed area will appear fluorescent. Thereby, in subsequent steps, the processing device can more quickly determine which areas in the detected image have been dyed.

[0067] In one embodiment, the welding quality detection device 100 may include at least two auxiliary light sources, and the two auxiliary light sources can emit light beams with different wavelengths respectively. In the image acquisition step S21, the processing device 1 may first control one of the auxiliary light sources to project a first auxiliary light beam onto the position to be detected, and control the image capturing device 2 to capture the image of the position to be detected to form a first image. Then, the processing device 1 may control the other auxiliary light source to project a second auxiliary light beam with a different wavelength onto the same position to be detected, and then control the image capturing device 2 to capture the image of the position to be detected to form a second image. Finally, the processing device 1 may integrate the first image and the second image into the detected image. Thereby, the object to be analyzed in the welding area (such as the dyed area, the welding structure, the solder mask layer, etc.) can be presented more clearly. Of course, the processing device 1 may also perform the foregoing image processing steps SX on the first image and the second image first, and then integrate the first image and the second image into the detected image.

[0068] As mentioned above, for example, if the solder mask is green and the dyeing ink is red, the processing device 1 can first control one of the auxiliary light sources to project a green light beam with a wavelength of 495 to 570 nm to the position to be detected, and then control the image capture device 2 to capture the image of the position to be detected to generate a first image. In this way, the green color of the solder mask will be more obvious in the first image; then, the processing device 1 controls another auxiliary light source to project a red light beam with a wavelength of 620 to 750 nm to the same position to be detected, and controls the image capture device 2 to capture the image of the position to be detected to generate a second image. In this way, the dyed area will be more obvious in the second image; finally, the processing device 1 can integrate the first image and the second image into the detection image, thereby making the boundary of the welding area clearer and the dyed area more clearly presented.

[0069] It should be noted that the welding quality inspection device 100 of the present application may also include at least one auxiliary light source to implement the welding quality inspection method of this embodiment. Furthermore, in practical applications, the welding quality inspection method of this embodiment may be combined with the welding quality inspection method of the second embodiment to form another embodiment.

[0070] Please also refer to Figure 1 、 Figure 7 and Figure 8 The biggest difference between this embodiment and the first embodiment is that the following is further included between the image acquisition step S11 and the percentage calculation and quality determination step S12:

[0071] A welding structure determination step SW: using the processing device 1 to determine whether a welding structure image exists in the welding area 21A of the detection image 21, wherein the welding structure image corresponds to an image of the welding structure on the substrate;

[0072] like Figure 8As shown, if the processing device 1 determines that there is no welding structure image in the welding area 21A, the processing device 1 will determine that there is a gap between the pad and the substrate, and the welding quality at the position to be detected is poor, and corresponding detection result information 11 will be generated. Then, the processing device 1 will no longer execute the percentage calculation and quality determination step S12. In practical applications, when the processing device 1 determines that there is a gap between the pad and the substrate, the processing device 1 can further determine that the substrate quality of the component to be detected is poor. For example, relevant personnel can view the detection result information 11 on the display and thus know that there may be a problem with the quality of the substrate of the component to be detected. In this way, relevant personnel can check in the direction of possible problems with the substrate (such as foreign objects in the board, poor lamination process, insufficient glue in the board, uneven resin flow in the board, uneven copper foil lamination in the board, poor surface treatment of glass fiber, etc.). On the contrary, if the processing device 1 determines that there is a welding structure image in the welding area 21A, the percentage calculation and quality determination step S12 will be continued.

[0073] In one specific embodiment, in the welding structure judgment step SW, the processing device 1 can be used to determine whether the welding area 21A matches a pre-stored image; if the processing device 1 determines that the welding area 21A matches the pre-stored image, the processing device 1 will determine that there is no welding structure at the position to be detected; if the processing device determines that the welding area 21A does not match the pre-stored image, the processing device will determine that there is a welding structure at the position to be detected. That is to say, the processing device 1 can pre-store an image of the welding area 21A without a welding structure (i.e., the pre-stored image), and in the welding structure judgment step SW, the processing device 1 can use various image comparison methods to determine whether the detection image 21 is the same as the pre-stored image.

[0074] It should be noted that in practical applications, the processing device can also pre-store an image of an incomplete welding structure in the welding area 21A (i.e., the pre-stored image). When the processing device determines that the detection image 21 matches the pre-stored image, it determines that there is no welding structure at the position to be detected. That is to say, the processing device can determine that there is no welding structure in the welding area 21A when there is only half or less than half of an incomplete welding structure on the substrate.

[0075] In another specific embodiment, in the welding structure determination step SW, the processing device 1 may calculate an average brightness of all pixels in the welding area 21A and determine whether the average brightness is lower than a default welding structure brightness; if the processing device 1 determines that the average brightness is lower than the default welding structure brightness, the processing device 1 will determine that there is no welding structure at the position to be detected; if the processing device 1 determines that the average brightness is higher than the default welding structure brightness, the processing device 1 will determine that there is a welding structure at the position to be detected. Specifically, when there is no welding structure at the position to be detected on the substrate and it appears black or dark, this method can be used to quickly determine whether there is a welding structure in the welding area 21A of the detection image 21.

[0076] It should be noted that the processing device 1 can use various methods to determine whether there is a welding structure in the welding area 21A of the detection image 21, not limited to the above two methods. For example, in another embodiment, the processing device 1 can also use a related machine learning model to determine whether there is a welding structure in the detection image 21; since the shape, material, size, etc. of the welding structure may vary according to the requirements of different manufacturers, and the welding structure may be connected to a single trace, two traces, or more traces, the machine learning module can better and more quickly judge the detection image 21.

[0077] Please refer to Figure 1 、 Figures 9 to 11 As shown in, the welding quality detection method of this embodiment sequentially includes an image acquisition step S31, a percentage calculation and quality determination step S32, a brightness judgment step S33, and a boundary arc shape judgment step S34. The image acquisition step S31 and the percentage calculation and quality determination step S32 are the same as the image acquisition step S11 and the percentage calculation and quality determination step S12 of the first embodiment respectively, and will not be elaborated here.

[0078] In the percentage calculation and quality determination step S32, if the processing device 1 determines that the staining area percentage is greater than the predetermined staining percentage (for example, the staining area percentage is greater than or equal to 1%), the following steps are executed:

[0079] A brightness judgment step S33: The processing device 1 calculates an average brightness of all pixels in the welding area 21A and determines whether the average brightness is lower than a predetermined brightness;

[0080] If the processing device 1 determines that the average brightness is lower than the predetermined brightness, the processing device 1 will determine that there is a gap at the position where the pad is connected to the welding structure, and the welding quality of the position to be detected is poor (the processing device 1 can also further determine that the substrate quality of the component to be tested is poor), and generate corresponding detection result information. Among them, the predetermined brightness refers to the brightness pre-stored in the processing device 1, and this pre-stored brightness can be input by relevant personnel, for example.

[0081] Specifically, if there is a gap at the position where the pad is connected to the welding structure, after the electronic component is removed, a rough pad and interface intermetallic compound (IMC) will remain at the position to be detected, and in the detection image 21, relevant personnel will observe that the image of the welding area 21A presents a rough surface with low brightness.

[0082] As described above, that is to say, if the processing device 1 determines that the proportion of the stained area in the welding area 21A in the detection image 21 exceeds the predetermined staining percentage, there is a welding structure in the welding area 21A, and the average brightness of the welding area 21A is lower than the predetermined brightness, then relevant personnel will be able to know from the detection result information 11 generated by the processing device 1 that the welding quality of this component to be tested is poor, and the reason for the poor welding quality may be that there is a gap at the position where the pad is connected to the welding structure. Thus, relevant personnel can accordingly prioritize checking for problems such as whether there are poor substrate quality or design issues (such as overly dense internal circuit distribution in some areas of the substrate), inconsistent or uneven solder ball sizes, too little solder paste, and poor SMT process control (such as uneven heating temperature, too fast heating and cooling rates) during the manufacturing process of the electronic component.

[0083] If in the brightness determination step S33, the processing device 1 determines that the average brightness of the welding area 21A is higher than the predetermined brightness, then the boundary arc determination step S34 is executed: using the processing device 1 to determine whether there is a high-brightness area in the welding area 21A and at least one section of the boundary of the high-brightness area is arc-shaped; wherein, the average brightness of the high-brightness area is greater than the average brightness of the remaining areas of the welding area 21A.

[0084] As Figure 10As shown, if the processing device 1 determines that there is a high-brightness area A within the welding area 21A and at least one section A1 of the boundary of the high-brightness area is arc-shaped, the processing device 1 will determine that there is a soldering problem of head-in-pillow (HIP) in the solder pad at the position to be detected and the welding structure it is connected to, and generate corresponding detection result information. That is to say, relevant personnel can understand through viewing the detection result information that there may be a soldering problem of head-in-pillow in the solder pad at the position to be detected and the welding structure it is connected to. Thus, relevant personnel can accordingly prioritize the investigation into whether there are problems such as substrate bending, insufficient welding structure quantity, and substrate deformation due to high temperature during the reflow process in the manufacturing process of the electronic component.

[0085] As Figure 11 shown, if the processing device 1 determines that there is a high-brightness area within the welding area 21A, but none of the sections of the boundary of the high-brightness area are arc-shaped, the processing device 1 determines that there is a soldering problem of non-wet-open (NWO) in the position to be detected and the welding structure it is connected to, and generates corresponding detection result information. That is to say, relevant personnel can understand through viewing the detection result information that there may be a soldering problem of non-wet-open in the solder pad at the position to be detected and the welding structure it is connected to. Thus, relevant personnel can accordingly prioritize the investigation into whether there are problems such as substrate deformation, solder pad oxidation, poor SMT process control, and solder mask printing offset in the manufacturing process of the electronic component.

[0086] It should be noted that the processing device 1 can determine that none of the sections of the boundary of the high-brightness area are arc-shaped when the length of the boundary of the high-brightness area does not exceed one-third (but not limited to this) of the boundary of the high-brightness area. That is, when the processing device 1 determines that none of the sections of the boundary of the high-brightness area are arc-shaped as mentioned here, it does not mean that the boundary of the high-brightness section is completely without arc-shaped sections.

[0087] It is worth mentioning that in one specific application, in the boundary arc-shaped judgment step S34, the processing device 1 can determine that the welding area 21A contains a high-brightness area when the percentage of the total number of pixels with brightness higher than the average brightness in the welding area 21A among all the pixels in the welding area 21A exceeds 10%. Of course, the processing device 1 can also use other methods to determine whether the welding area 21A contains a high-brightness area.

[0088] Please also refer to Figure 1 、 Figure 12 and Figure 13, the biggest difference between this embodiment and the foregoing first embodiment is that after the percentage calculation and quality determination step S12, if the processing device 1 determines that the percentage of the stained area is not greater than (i.e., less than or equal to) a predetermined staining percentage (e.g., 0% - 5%), the following steps are executed:

[0089] A brightness calculation step S13: Use the processing device 1 to calculate the brightness of each pixel in the welding area 21A;

[0090] A defect determination step S14: Use the processing device to compare the brightness of each pixel to determine whether there is a defect area B in the welding area 21A; wherein, the average brightness of all pixels in the defect area B is lower than a predetermined brightness;

[0091] If the processing device 1 determines that there is at least one defect area B in the welding area 21A (as Figure 13 shown), the processing device 1 will determine that there are bubbles or voids in the welding area 21A and generate corresponding detection result information 11;

[0092] If the processing device 1 determines that there is no defect area B in the welding area 21A, the processing device will determine that the welding quality of the position to be detected is good and generate corresponding detection result information 11.

[0093] In the defect determination step S14, the processing device 1 may also first determine the total area of these pixels after determining that the average brightness of multiple pixels is lower than the predetermined brightness, and determine that there is a defect area B in the welding area 21A only when the total area is greater than a predetermined area; or, the processing device 1 may also first determine the ratio of the total area of these pixels to the welding area 21A after determining that the average brightness of multiple pixels is lower than the predetermined brightness, and determine that there is a defect area B in the welding area 21A only when the total area accounts for more than a predetermined ratio of the welding area 21A. For example, the processing device 1 may determine that there is a defect area B in the welding area 21A when it determines that the area of the defect area B accounts for more than 6.25% of the area of the welding area 21A. In different embodiments, the processing device 1 may also determine that there is a defect area B in the welding area 21A only when it determines that the diameter of the defect area B is greater than 25% of the diameter of the welding area 21A.

[0094] Please refer to Figure 1 and Figure 14 , the welding quality detection method of the present application can also be used to detect the welding quality of the component to be detected. Specifically, the substrate may be provided with a plurality of pads, and each pad is connected to a welding structure, and at least one electronic component is connected to the plurality of pads through a plurality of welding structures. The position of the substrate for setting each pad is defined as a position to be detected.

[0095] The welding quality detection method of this embodiment includes: an image acquisition step S41, a detection quantity calculation step S42, a percentage calculation and quality determination step S43, and a total percentage calculation and quality determination step S44. In the image acquisition step S41, it is detected whether the detection image 21 contains a plurality of welding areas, and each welding area corresponds to the image of one of the positions to be detected. The percentage calculation and quality determination step S43 of this embodiment is the same as the percentage calculation and quality determination step S12 of the foregoing first embodiment, and will not be described in detail below.

[0096] The detection quantity calculation step S42: calculates the total number of welding areas included in the detection image 21. After the detection quantity calculation step S42, the percentage calculation and quality determination step S43 will be repeatedly executed a predetermined number of times. The predetermined number of times is equal to the total number of welding areas, and in each percentage calculation and quality determination step S43, the processing device calculates the staining area percentage of different welding areas and generates a detection result information 11 corresponding to each welding area.

[0097] That is to say, assuming that there are 6 welding areas in the detection image 21, the processing device 1 will repeatedly execute the percentage calculation and quality determination step S43 a total of 6 times, and each time the percentage calculation and quality determination step S43 is executed, the welding quality of a different one of the 6 welding areas is judged, and the corresponding detection result information 11 is generated accordingly. It should be particularly noted that in the embodiment where the processing device is a multi-core processor, the processing device 1 can execute the percentage calculation and quality determination step S43 corresponding to different welding areas in a multithreading manner. When the percentage calculation and quality determination step S43 is executed the predetermined number of times, the processing device 1 will execute the total percentage calculation and quality determination step S44: use the processing device 1 to calculate the staining quantity percentage of the total number of welding areas with a staining percentage greater than the predetermined staining percentage, and judge whether the staining quantity percentage is greater than a predetermined quantity percentage;

[0098] If the processing device 1 determines that the staining quantity percentage is greater than the predetermined quantity percentage, the processing device 1 will determine that the welding quality of the component to be tested is poor and correspondingly generate a component to be tested detection result information;

[0099] If the processing device 1 determines that the staining quantity percentage is not greater than the predetermined quantity percentage, the processing device will determine that the welding quality of the component to be tested is good and correspondingly generate a component to be tested detection result information.

[0100] In one specific embodiment, the predetermined percentage may be 0%. That is to say, as long as the processing device 1 determines that the welding quality at the welding detection position of any one welding area is poor, the processing device 1 will directly determine that the welding quality of the welding assembly is poor.

[0101] In different embodiments, assume that there are 6 welding areas in the detection image 21, the predetermined percentage is 25%, and after the processing device 1 repeats the percentage calculation and quality determination step S43 six times and determines that the welding quality at the welding detection positions of 3 welding areas is poor, the processing device 1 will determine that the welding quality of the welding assembly is poor; on the contrary, if after the processing device 1 repeats the percentage calculation and quality determination step S43 six times and determines that only 1 welding area has poor welding quality at the welding detection position, the processing device 1 will determine that the welding quality of the welding assembly is good.

[0102] It is worth mentioning that in practical applications, in the detection quantity calculation step S42, the processing device 1 can, for example, determine the total number of welding areas included in the detection image by means of image recognition (such as in cooperation with a machine learning model), comparison with the pre-stored images of the welding areas, etc. However, how the processing device 1 calculates the total number of welding areas included in the detection image is not limited herein.

[0103] For example, assume that the color of the solder mask on the substrate is dark green, the colors of each pad and welding structure are close to gold and silver respectively, and the shape of the pad is close to circular. Then the processing device 1 can first perform binarization processing on the detection image 21, so that the detection image is converted from color to black and white. In the detection image 21 after binarization processing, the area corresponding to the solder mask will appear black, and the areas corresponding to the pads or welding structures will appear white. Then, the processing device 1 can determine whether each white area is close to circular and calculate the size (such as area, diameter, etc.) of each white area, so as to determine whether each white area corresponds to one of the welding areas. Of course, in a better embodiment, the processing device 1 can also directly use a relevant machine learning model to judge and calculate the number of welding areas in the color detection image 21.

[0104] Please refer to Figure 1 and Figure 15 , the biggest difference between this embodiment and the foregoing seventh embodiment is that the following steps are further included between the image acquisition step S41 and the percentage calculation and quality determination step S43:

[0105] A numbering step SZ: The processing device 1 sequentially assigns a number to a plurality of welding areas according to a first direction and a second direction in sequence; wherein, the first direction is different from the second direction; wherein, the processing device assigns a different number N to each welding area;

[0106] After the numbering step SZ, the processing device 1 can, for example, perform a percentage calculation and quality determination step S43 on the plurality of welding areas according to a plurality of numbers, and the processing device 1 will generate detection result information 11 corresponding to each welding area, and each detection result information 11 includes the corresponding number N. It should be particularly noted that in an embodiment where the processing device is a multi-core processor, the processing device 1 can perform the percentage calculation and quality determination step S43 on a plurality of welding areas with different numbers in a multithreading manner.

[0107] In one preferred embodiment, in the numbering step SZ, the processing device 1 can first rotate the detection image by a predetermined angle, and then assign numbers to each welding area. In this way, the numbers sequentially assigned by the processing device 1 will enable the user to intuitively know the position of the welding area corresponding to the number in the currently viewed detection result information 11.

[0108] For example, as Figure 16 shown, the processing device 1 can first rotate the detection image 21 counterclockwise by 10 degrees (i.e., the predetermined angle), and then, from the top to the bottom and from the right to the left of the detection image 21 (i.e., corresponding to the first direction and the second direction), sequentially assign labels (the numbers 1 to 22 marked in the figure) to each welding area. Through the design of the numbering step SZ, relevant personnel can intuitively and quickly know the number of each welding area by viewing the detection result information 11.

[0109] It should be noted that the various numbers N shown in Figure 16 are only used to assist in explaining how the processing device 1 numbers the plurality of welding areas 21A. In actual applications, during the process of the processing device 1 performing relevant image processing and judgment on the detection image 21, the processing device 1 will not form the numbers shown in the figure in each welding area 21A of the detection image 21; of course, when the processing device 1 controls the display device 3 to display the detection image 21, in order to enable relevant personnel to more clearly know which welding area 21A each detection result information 11 corresponds to, the corresponding number N can be displayed around each welding area 21A in the detection image 21 presented on the display device 3.

[0110] Regarding how the processing device 1 numbers multiple welding areas in a first direction and then in a second direction, the method is not limited to the above, but the numbers finally assigned by the processing device 1 to the multiple welding areas can basically enable the user to intuitively know which welding area the number corresponds to.

[0111] It should be noted that each embodiment can be combined with each other into a new embodiment according to actual needs, and the content cited in each embodiment is not limited to not being combined with other embodiments.

[0112] In summary, the welding quality detection method and welding quality detection equipment of the present application can quickly and correctly judge the welding quality of the position to be detected on the substrate or the welding quality of the component to be tested. Moreover, during the determination process, there is no manual determination process. Therefore, each determination is carried out according to the same standard, and problems such as different people observing the same substrate and making completely different determinations in the prior art will not occur.

Claims

1. A welding quality detection method, characterized in that, The described welding quality inspection method is used to inspect the welding quality of a to-be-inspected position of a to-be-inspected component. The to-be-inspected component is formed by a procedure of immersing an electronic component in a dyeing ink, drying, and removing an electronic element included in the electronic component. The electronic component includes a substrate and the electronic element. The substrate is provided with at least one pad, and the pad is connected to the electronic element through a welding structure. The position on the substrate for setting the pad is defined as the to-be-inspected position. The welding quality inspection method includes: An image acquisition step: acquiring a detection image, where the detection image includes at least one welding area, and the welding area corresponds to the image of the to-be-inspected position; A percentage calculation and quality determination step: using a processing device to calculate the area percentage of the area dyed by the dyeing ink in the welding area accounting for the area of the welding area, and using the processing device to determine whether the dyed area percentage is greater than a predetermined dyeing percentage; If the processing device determines that the dyed area percentage is not greater than the predetermined dyeing percentage, the processing device will determine that the welding quality of the to-be-inspected position is good and generate a corresponding detection result information; If the processing device determines that the dyed area percentage is greater than the predetermined dyeing percentage, the processing device will determine that the welding quality of the to-be-inspected position is poor and generate the corresponding detection result information; Wherein, between the image acquisition step and the percentage calculation and quality determination step, there is also included: A welding structure judgment step: using the processing device to judge whether there is a welding structure image in the welding area, and the welding structure image corresponds to the image of the welding structure on the substrate; If the processing device determines that there is no welding structure image in the welding area, the processing device will determine that there is a gap between the pad and the substrate, and the welding quality of the to-be-inspected position is poor, and generate the corresponding detection result information, and the processing device will no longer execute the percentage calculation and quality determination step; If the processing device determines that there is a welding structure image in the welding area, then the percentage calculation and quality determination step will be continued to be executed.

2. The welding quality detection method according to claim 1, characterized in that Between the image acquisition step and the percentage calculation and quality determination step, there is also included an image processing step: using the processing device to adjust at least one of the R value, G value, and B value of at least a part of the pixels in the detection image, or adjust at least one of the H value, S value, and V value of at least a part of the pixels in the detection image, according to at least one of the color of the dyeing ink, the color of the welding structure, and the color of the solder mask layer of the substrate.

3. The welding quality detection method according to claim 1, characterized in that In the image acquisition step, first control an auxiliary light source to project an auxiliary light beam onto the position to be detected on the substrate, and then control an image capture device to capture an image of the position to be detected on the substrate to generate the detection image, and then control the image capture device to transmit the detection image to the processing device; wherein, the color of the auxiliary light beam is the same as the color of the dyeing ink, or the color of the auxiliary light beam is determined according to the dyeing ink and the subtractive color mixing method, so that the pixels dyed by the dyeing ink in the detection image appear as gray or black.

4. The welding quality detection method according to claim 1, characterized in that, In the percentage calculation and quality determination step, if the processing device determines that the dyeing area percentage is greater than the predetermined dyeing percentage, then execute a brightness judgment step: use the processing device to calculate an average brightness of all pixels in the welding area, and determine whether the average brightness is lower than a predetermined brightness; if the processing device determines that the average brightness is lower than the predetermined brightness, then the processing device will determine that there is a gap at the position where the pad is connected to the welding structure, and the welding quality of the position to be detected is poor, and generate the corresponding detection result information; wherein, the predetermined dyeing percentage is not less than 1%.

5. The welding quality detection method according to claim 4, characterized in that, In the brightness judgment step, if the processing device determines that the average brightness is not lower than the predetermined brightness, then execute the following steps: A boundary arc-shaped judgment step: use the processing device to determine whether there is a high-brightness area in the welding area, and at least one section of the boundary of the high-brightness area is arc-shaped; wherein, the average brightness of all pixels included in the high-brightness area is greater than the average brightness of the remaining area of the welding area. If the processing device determines that there is the high-brightness area in the welding area, and at least one section of the boundary of the high-brightness area is arc-shaped, then the processing device will determine that there is a soldering problem of pillow effect between the pad and the welding structure connected thereto, and the welding quality of the position to be detected is poor, and generate the corresponding detection result information. If the processing device determines that there is the high-brightness area in the welding area, but there is no arc-shaped section at the boundary of the high-brightness area, then the processing device will determine that there is a soldering problem of open circuit between the pad and the welding structure connected thereto, and the welding quality of the position to be detected is poor, and generate the corresponding detection result information.

6. The welding quality detection method according to claim 5, characterized in that, In the boundary arc-shaped judgment step, when the percentage of the total number of pixels with brightness higher than the average brightness in the welding area determined by the processing device in the total number of all pixels in the welding area exceeds 10%, the processing device will determine that the high-brightness area is included in the welding area.

7. The welding quality detection method according to claim 1, characterized in that, In the percentage calculation and quality determination step, if the processing device determines that the dyeing area percentage is not greater than the predetermined dyeing percentage, then execute the following steps: A brightness calculation step: use the processing device to calculate the brightness of each pixel in the welding area. A defect determination step: using the processing device to compare the brightness of each pixel to determine whether there is a defect area in the welding area; wherein, the average brightness of all pixels in the defect area is lower than a predetermined brightness; If the processing device determines that there is at least one such defect area in the welding area, the processing device will determine that there are bubbles or voids in the welding area, and the welding quality of the position to be detected is poor, and corresponding detection result information will be generated; If the processing device determines that there is no such defect area in the welding area, the processing device will determine that the welding quality of the position to be detected is good, and corresponding detection result information will be generated; wherein, the predetermined staining percentage is between 0% and 25%.

8. The welding quality detection method according to claim 1, wherein The substrate is provided with a plurality of the pads, and each of the pads is connected to a welding structure, and at least one electronic component is connected to the plurality of pads through the plurality of welding structures. The position where the substrate is used to set each of the pads is defined as a position to be detected; the welding quality detection method is used to detect the welding quality of the component to be tested. In the image acquisition step, the detection image contains a plurality of the welding areas, and each of the welding areas corresponds to an image of one of the positions to be detected; between the image acquisition step and the percentage calculation and quality determination step, the following steps are further included: A detection quantity calculation step: calculating the total number of welding areas included in the detection image; After the detection quantity calculation step, the percentage calculation and quality determination step will be repeatedly executed a predetermined number of times. The predetermined number of times is equal to the total number of welding areas, and in each percentage calculation and quality determination step, the processing device calculates the staining area percentage of different welding areas; After the percentage calculation and quality determination step is executed the predetermined number of times, the following steps are executed: A total percentage calculation and quality determination step: using the processing device to calculate the staining quantity percentage of the total number of welding areas with a staining percentage greater than the predetermined staining percentage in the total number of welding areas, and determining whether the staining quantity percentage is greater than a predetermined quantity percentage; If the processing device determines that the staining quantity percentage is greater than the predetermined quantity percentage, the processing device will determine that the welding quality of the component to be tested is poor, and correspondingly generate a component to be tested detection result information; if the processing device determines that the staining quantity percentage is not greater than the predetermined quantity percentage, the processing device will determine that the welding quality of the component to be tested is good, and correspondingly generate a component to be tested detection result information.

9. The welding quality detection method according to claim 8, characterized in that, Between the image acquisition step and the percentage calculation and quality determination step, the following steps are further included: A numbering step: The processing device can sequentially assign a number to a plurality of the welding areas according to a first direction and a second direction in sequence; the first direction is different from the second direction; the processing device assigns different numbers to each of the welding areas; Wherein, after the numbering step, the processing device sequentially performs the percentage calculation and quality determination steps on the plurality of welding areas according to the plurality of numbers, and the processing device will generate the detection result information corresponding to each of the welding areas, and each of the detection result information contains the corresponding number.

10. The welding quality inspection method according to claim 9, wherein In the numbering step, the processing device first rotates the detection image by a predetermined angle, and then sequentially assigns the numbers to the plurality of welding areas according to the first direction and the second direction in sequence.

11. A welding quality inspection device, characterized in that, The welding quality detection device includes: a stage, a processing device, an image capturing device and an output device. The stage is used to carry a substrate. The image capturing device and the output device are electrically connected to the processing device respectively. The processing device can execute a welding quality detection method. The welding quality detection method is used to detect the welding quality of a to-be-detected position of a to-be-detected component. The to-be-detected component is formed by a program of soaking an electronic component in a staining ink, drying and removing an electronic element included in the electronic component. The electronic component includes a substrate and the electronic element. The substrate is provided with at least one pad, and the pad is connected to the electronic element through a welding structure. The position of the substrate for setting the pad is defined as the to-be-detected position. The welding quality detection method includes: An image acquisition step: Controlling the image capturing device to capture an image of the to-be-detected position of the to-be-detected component arranged on the stage to obtain a detection image, where the detection image includes at least one welding area, and the welding area corresponds to the image of the to-be-detected position; A percentage calculation and quality determination step: Calculating the area percentage of the area stained by the staining ink in the welding area to the area of the welding area; A percentage calculation and quality determination step: Judging whether the staining area percentage is greater than a predetermined staining percentage; If the staining area percentage is not greater than the predetermined staining percentage, it is determined that the welding quality of the to-be-detected position is good, and a corresponding detection result information is generated and transmitted to the output device; If the staining area percentage is greater than the predetermined staining percentage, it is determined that the welding quality of the to-be-detected position is poor, and the corresponding detection result information is generated and transmitted to the output device; Wherein, between the image acquisition step and the percentage calculation and quality determination step, there is also included: A welding structure judgment step: Judging whether there is an image of a welding structure in the welding area, and the image of the welding structure corresponds to the image of the welding structure on the substrate; If it is determined that the image of the welding structure does not exist in the welding area, it is determined that there is a gap between the pad and the substrate, the welding quality of the position to be detected is poor, and the corresponding detection result information is generated, and the percentage calculation and quality determination steps are not executed any more; If it is determined that the image of the welding structure exists in the welding area, the percentage calculation and quality determination steps are continuously executed.

12. The welding quality detection device according to claim 11, characterized in that, In the percentage calculation and quality determination steps, if it is determined that the stained area percentage is greater than the predetermined stained percentage, a brightness judgment step is executed: calculate an average brightness of all pixels in the welding area, and determine whether the average brightness is lower than a predetermined brightness; if it is determined that the average brightness is lower than the predetermined brightness, it is determined that there is a gap at the position where the pad is connected to the welding structure, the welding quality of the position to be detected is poor, and the corresponding detection result information is generated; wherein, the predetermined stained percentage is not less than 1%.

13. The welding quality detection device according to claim 12, characterized in that, In the brightness judgment step, if it is determined that the average brightness is not lower than the predetermined brightness, the following steps are executed: A boundary arc-shaped judgment step: determine whether there is a high-brightness area in the welding area, and at least one section of the boundary of the high-brightness area is arc-shaped; wherein, the average brightness of all pixels included in the high-brightness area is greater than the average brightness of the remaining area of the welding area; If it is determined that there is the high-brightness area in the welding area and at least one section of the boundary of the high-brightness area is arc-shaped, it is determined that there is a soldering problem of pillow effect in the pad and the welding structure connected thereto, the welding quality of the position to be detected is poor, and the corresponding detection result information is generated; If it is determined that there is the high-brightness area in the welding area and no section of the boundary of the high-brightness area is arc-shaped, it is determined that there is a soldering problem of open circuit in the pad and the welding structure connected thereto, the welding quality of the position to be detected is poor, and the corresponding detection result information is generated.

14. The welding quality detection device according to claim 13, wherein, In the boundary arc-shaped judgment step, when it is determined that the percentage of the total number of pixels with a brightness higher than the average brightness in the welding area in the total number of all pixels in the welding area exceeds 10%, it is determined that the high-brightness area is included in the welding area.

15. The welding quality detection device according to claim 11, characterized in that, In the percentage calculation and quality determination steps, if it is determined that the stained area percentage is not greater than the predetermined stained percentage, the following steps are executed: A brightness calculation step: calculate the brightness of each pixel in the welding area; A defect judgment step: compare the brightness of each pixel to determine whether there is a defect area in the welding area; wherein, the average brightness of all pixels in the defect area is lower than a predetermined brightness; If it is determined that there is at least one defect area in the welding area, it is determined that there are bubbles or voids in the welding area, the welding quality of the position to be detected is poor, and the corresponding detection result information is generated; If it is determined that there is no such defect area within the welding area, it is determined that the welding quality of the position to be detected is good, and the corresponding detection result information is generated; wherein, the predetermined staining percentage is between 0% and 25%.

16. The welding quality detection device according to claim 11, characterized in that The substrate is provided with a plurality of the pads, and each of the pads is connected to one of the welding structures, and at least one electronic component is connected to the plurality of pads through the plurality of welding structures. The position where the substrate is used to set each of the pads is defined as a position to be detected; the welding quality detection method is used to detect the welding quality of the component to be tested. In the image acquisition step, the detection image includes a plurality of the welding areas, and each of the welding areas corresponds to the image of one of the positions to be detected; between the image acquisition step and the percentage calculation and quality determination step, the following steps are further included: A detection quantity calculation step: calculating a total number of welding areas included in the detection image; After the detection quantity calculation step, the percentage calculation and quality determination step is repeatedly executed a predetermined number of times. The predetermined number of times is equal to the total number of welding areas, and in each percentage calculation and quality determination step, the staining area percentage of different welding areas is calculated; After the percentage calculation and quality determination step is executed the predetermined number of times, the following steps are executed: A total number percentage calculation and quality determination step: calculating a staining quantity percentage of the total number of welding areas in which the staining area percentage is greater than the predetermined staining percentage, and determining whether the staining quantity percentage is greater than a predetermined quantity percentage; If it is determined that the staining quantity percentage is greater than the predetermined quantity percentage, it is determined that the welding quality of the component to be tested is poor, and a detection result information of the component to be tested is correspondingly generated; If it is determined that the staining quantity percentage is not greater than the predetermined quantity percentage, it is determined that the welding quality of the component to be tested is good, and a detection result information of the component to be tested is correspondingly generated.

17. The welding quality detection device according to claim 16, characterized in that, Between the image acquisition step and the percentage calculation and quality determination step, the following steps are further included: A numbering step: rotating the detection image by a predetermined angle, or adjusting the position of at least one of the welding areas in the detection image, so as to sequentially assign a number to the plurality of welding areas according to a first direction and a second direction in sequence; the first direction is different from the second direction; wherein, each of the welding areas is assigned a different number; Wherein, after the numbering step, the percentage calculation and quality determination step is performed on the plurality of welding areas according to the plurality of numbers in sequence, and the detection result information corresponding to each of the welding areas is generated, and each of the detection result information includes the corresponding number.

18. The welding quality detection device according to claim 17, wherein, In the numbering step, the processing device first rotates the detection image by a predetermined angle, and then sequentially assigns the numbers to the plurality of welding areas according to the first direction and the second direction in sequence.

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