Component Bottom Pin Welding Detection System and Method

Abstract

The present invention relates to the field of welding detection, and particularly to a welding detection system and method for the bottom pins of components. It includes: acquiring and preprocessing the welding point image, further performing edge detection to obtain an edge response map; extracting feature points based on the edge response map, performing shape matching on the extracted feature points to obtain a shape matching degree; detecting the electrical performance of the welding point to obtain the resistance value of the welding point; calculating an electrical performance evaluation index of the welding point based on the resistance value of the welding point; calculating a welding quality score for the bottom pins of the component based on the shape matching degree and the electrical performance evaluation index of the welding point; setting an evaluation threshold to judge the welding quality. It solves the technical problems that when facing complex welding point images, it is easily affected by noise and illumination changes; the traditional feature point extraction and matching methods have poor effects when dealing with various shape and scale changes; and only through appearance detection and shape matching, the internal electrical performance of the welding point cannot be comprehensively evaluated.

Description

Technical Field

[0001] The present invention relates to the field of welding detection, and particularly to a welding detection system and method for the bottom pins of components. Background Art

[0002] In the process of electronic product manufacturing, the welding quality of components directly affects the performance and reliability of the product. Poor welding may lead to unstable electrical connections or insufficient durability between the pins and the printed circuit board, thus affecting the reliability and lifespan of the product. Traditional welding detection methods have certain limitations. For example, visual inspection is affected by the operator's experience and visual fatigue, and it is difficult to achieve automation and high efficiency. Although X-ray and ultrasonic inspections can detect hidden defects, the equipment is expensive and the operation is complex, which is not suitable for the real-time detection requirements in large-scale production.

[0003] With the progress of electronic manufacturing processes and the development of automation technologies, automated welding detection systems have gradually become a new trend in welding quality control. The welding detection system for the bottom pins of components can effectively detect and control welding quality, improve production efficiency and the consistency of product quality, while reducing labor costs and product return rates, and further promoting the development of the electronic manufacturing industry.

[0004] However, the existing welding detection systems for the bottom pins of components have the following technical problems: when facing complex welding point images, they are easily affected by noise and light changes, resulting in inaccurate edge detection and unable to accurately capture the edge details of welding points; the shapes of welding points are complex and variable, and traditional feature point extraction and matching methods have poor effects when dealing with various shapes and scale changes; and only through appearance detection and shape matching, the internal electrical performance of welding points cannot be comprehensively evaluated, and there are easily welding points that are physically qualified but do not meet the electrical performance standards. Summary of the Invention

[0005] The present invention provides a welding detection system and method for the bottom pins of components to solve the technical problems that when facing complex welding point images, it is easily affected by noise and light changes, resulting in inaccurate edge detection and unable to accurately capture the edge details of welding points; the shapes of welding points are complex and variable, and traditional feature point extraction and matching methods have poor effects when dealing with various shapes and scale changes; and only through appearance detection and shape matching, the internal electrical performance of welding points cannot be comprehensively evaluated, and there are easily welding points that are physically qualified but do not meet the electrical performance standards.

[0006] The welding detection system and method for the bottom pins of components of the present invention specifically include the following technical solutions:

[0007] A welding detection method for the bottom pins of components includes the following steps:

[0008] S1: Obtain and preprocess the image of the welding point to get the preprocessed image of the welding point; Use the adaptive directional gradient enhanced edge detection algorithm to perform edge detection on the preprocessed image of the welding point, obtain the edge response value at each pixel position, and form an edge response map;

[0009] S2: Based on the edge response map, extract feature points through curvature analysis, use the adaptive multi-scale shape matching algorithm to perform shape matching on the extracted feature points, and calculate the shape matching degree;

[0010] S3: According to the shape matching degree, detect the electrical performance of the welding point to obtain the resistance value of the welding point; Based on the resistance value of the welding point, use the welding point resistance evaluation algorithm to calculate the electrical performance evaluation index of the welding point;

[0011] S4: Based on the shape matching degree and the electrical performance evaluation index of the welding point, use the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the component, calculate the welding quality score of the bottom pins of the component; Set an evaluation threshold, and judge the welding quality according to the evaluation threshold.

[0012] Preferably, the S1 specifically includes:

[0013] In the implementation process of the adaptive directional gradient enhanced edge detection algorithm, calculate the gradient of each pixel in the horizontal and vertical directions, adaptively adjust the gradient value according to the local mean and local standard deviation of the pixel, and select the maximum value of each pixel in all directions as the edge response value of the pixel position.

[0014] Preferably, the S2 specifically includes:

[0015] The adaptive multi-scale shape matching algorithm calculates the distance matching degree by performing an exponential transformation on the difference between the distance of each feature point from the reference feature point and the mean distance; calculates the direction matching degree by performing a sine transformation on the direction difference; and performs a weighted sum of the matching degrees at each scale to obtain the shape matching degree.

[0016] Preferably, the S3 specifically includes:

[0017] In the implementation process of the welding point resistance evaluation algorithm, measure the resistance value at different positions and different time points, calculate the mean and standard deviation of the resistance, and use the mean and standard deviation of the resistance to calculate the deviation coefficient; calculate the resistance gradient to obtain the change rate of the resistance value; calculate the electrical performance evaluation index of the welding point based on the deviation coefficient and the resistance gradient.

[0018] Preferably, the S4 specifically includes:

[0019] The welding quality scoring algorithm calculates the welding quality score of the bottom pins of components by performing exponential transformation on the shape matching degree and the evaluation index of the electrical performance of welding points, and introducing a balance factor.

[0020] Preferably, the S4 specifically includes:

[0021] By taking the logarithm of the ratio of the shape matching degree and the evaluation index of the electrical performance of the welding point, then taking the absolute value, and processing through an exponential function, the balance factor value is obtained.

[0022] Preferably, the S4 specifically includes:

[0023] Judge the welding quality according to the evaluation threshold. When the welding quality score of the bottom pins of the component is greater than or equal to the evaluation threshold, it is qualified; when the welding quality score of the bottom pins of the component is less than the evaluation threshold, it is unqualified.

[0024] The welding detection system for the bottom pins of components includes the following:

[0025] Welding point image acquisition module: Acquire the welding point image and output the welding point image to the image preprocessing module;

[0026] Image preprocessing module: Perform image preprocessing on the welding point image to obtain the preprocessed welding point image, and output the preprocessed welding point image to the edge detection module;

[0027] Edge detection module: Use the adaptive directional gradient enhanced edge detection algorithm to perform edge detection on the preprocessed welding point image, obtain the edge response value at each pixel position, form an edge response map, and output the edge response map to the feature point extraction module;

[0028] Feature point extraction module: Based on the edge response map, extract feature points through curvature analysis, and output the feature points to the shape matching module;

[0029] Shape matching module: Use the adaptive multi-scale shape matching algorithm to perform shape matching on the feature points, calculate the shape matching degree, and output the shape matching degree to the electrical performance detection module and the welding quality evaluation module;

[0030] Electrical performance detection module: According to the shape matching degree, detect the internal electrical performance of the welding point through electrical testing means to obtain the resistance value of the welding point, and output the resistance value of the welding point to the welding point electrical performance evaluation module;

[0031] Welding point electrical performance evaluation module: Based on the resistance value of the welding point, use the welding point resistance evaluation algorithm to calculate the welding point electrical performance evaluation index, and output the welding point electrical performance evaluation index to the welding quality evaluation module;

[0032] Welding Quality Assessment Module: Based on the shape matching degree and the electrical performance evaluation index of the welding points, use the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the components, calculate the welding quality score of the bottom pins of the components, set the evaluation threshold, and judge the welding quality according to the evaluation threshold.

[0033] The beneficial effects of the technical solution of the present invention are:

[0034] 1. The adaptive directional gradient enhancement edge detection algorithm is adopted. By calculating the gradients of each pixel in different directions and adaptively adjusting the gradient values according to the local mean and local standard deviation, the edges of the welding points are accurately captured. The formed edge response map can accurately identify the edges of the welding points, improve the accuracy of welding point edge detection, and ensure the smooth progress of the welding quality control of the bottom pins of the components.

[0035] 2. Based on the edge response map, feature points are extracted through curvature analysis to ensure the accuracy of feature point extraction of the welding points. The adaptive multi-scale shape matching algorithm obtains the shape matching degree through the comprehensive calculation of the distance matching degree and the direction matching degree, and evaluates the overall shape matching situation of the welding points. The calculation process of the shape matching degree considers the matching situations at different scales, and through weighted summation, improves the accuracy and robustness of the shape matching of the welding points, providing a reliable basis for welding quality assessment.

[0036] 3. Based on the shape matching degree, the internal electrical performance of the welding points is detected by electrical testing means, especially the resistance value of the welding points with low shape matching degree is detected. The welding point resistance evaluation algorithm evaluates the consistency and stability of the resistance value of the welding points by calculating the mean, standard deviation and resistance gradient of the resistance, and obtains the electrical performance evaluation index of the welding points, comprehensively reflecting the internal electrical performance of the welding points.

[0037] 4. Based on the shape matching degree and the electrical performance evaluation index of the welding points, use the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the components. The welding quality scoring algorithm comprehensively considers the shape matching degree and the electrical performance evaluation index of the welding points through exponential transformation and balance factor, reduces the difference between the two, and ensures the balance and stability of the welding quality score.

[0038] 5. By setting the evaluation threshold to judge the welding quality, it provides reliable technical support and improves the accuracy, comprehensiveness and reliability of welding detection. Description of the Drawings

[0039] Figure 1 is the structure diagram of the welding detection system for the bottom pins of the components described in the present invention;

[0040] Figure 2 is the flowchart of the welding detection method for the bottom pins of the components described in the present invention. Detailed implementation manners

[0041] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts belong to the scope of protection of the present invention.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0043] The following specifically describes the specific solutions of the component bottom pin soldering detection system and method provided by the present invention in conjunction with the accompanying drawings.

[0044] Referring to the attached Figure 1 , which shows the structure diagram of the component bottom pin soldering detection system provided by an embodiment of the present invention. The system includes the following parts:

[0045] Soldering point image acquisition module, image preprocessing module, edge detection module, feature point extraction module, shape matching module, electrical performance detection module, soldering point electrical performance evaluation module, soldering quality evaluation module;

[0046] Soldering point image acquisition module: Use an industrial camera to capture the soldering point image and output the soldering point image to the image preprocessing module;

[0047] Image preprocessing module: Receive the soldering point image from the soldering point image acquisition module, perform image preprocessing on the soldering point image, such as denoising, enhancement, and grayscale processing, to obtain the preprocessed soldering point image, and output the preprocessed soldering point image to the edge detection module;

[0048] Edge detection module: Receive the preprocessed soldering point image from the image preprocessing module, use the adaptive directional gradient enhanced edge detection algorithm to perform edge detection on the preprocessed soldering point image, obtain the edge response value at each pixel position, form an edge response map, and output the edge response map to the feature point extraction module;

[0049] Feature point extraction module: Receive the edge response map from the edge detection module, extract feature points through curvature analysis, and output the feature points to the shape matching module;

[0050] Shape matching module: Receives the feature points from the feature point extraction module, uses the adaptive multi-scale shape matching algorithm to perform shape matching on the extracted feature points, calculates the shape matching degree, and outputs the shape matching degree to the electrical performance detection module and the welding quality evaluation module;

[0051] Electrical performance detection module: Receives the shape matching degree from the shape matching module, and based on the shape matching degree, detects the internal electrical performance of the welding point through electrical testing means to obtain the resistance value of the welding point, and outputs the resistance value of the welding point to the welding point electrical performance evaluation module;

[0052] Welding point electrical performance evaluation module: Receives the resistance value of the welding point from the electrical performance detection module, uses the welding point resistance evaluation algorithm to calculate the welding point electrical performance evaluation index, and outputs the welding point electrical performance evaluation index to the welding quality evaluation module;

[0053] Welding quality evaluation module: Based on the shape matching degree of the shape matching module and the welding point electrical performance evaluation index of the welding point electrical performance evaluation module, uses the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the component, calculates the welding quality score of the bottom pins of the component, sets the evaluation threshold, and judges the welding quality according to the evaluation threshold.

[0054] Refer to Appendix Figure 2 , which shows the flowchart of the method for detecting the welding of the bottom pins of the component provided by an embodiment of the present invention. The method includes the following steps:

[0055] S1. Obtain and preprocess the welding point image to obtain the preprocessed welding point image; Use the adaptive directional gradient enhanced edge detection algorithm to perform edge detection on the preprocessed welding point image to obtain the edge response value at each pixel position, and form an edge response map;

[0056] Use an industrial camera to capture the welding point image, and perform image preprocessing on the welding point image, such as denoising, enhancement, and grayscale processing, to improve the quality of the welding point image, eliminate noise, and enhance the contrast of the welding point image, ensuring that the welding point image is clear, and obtain the preprocessed welding point image; The image preprocessing methods such as denoising, enhancement, and grayscale processing are well-known technical means to those skilled in the art and will not be elaborated here;

[0057] Use the adaptive directional gradient enhanced edge detection algorithm to perform edge detection on the preprocessed welding point image to obtain the edge response value at each pixel position, and form an edge response map;

[0058] The adaptive directional gradient enhanced edge detection algorithm calculates the gradients of each pixel in the horizontal and vertical directions, representing the rate of change of image brightness. The horizontal gradient reflects the rate of change in the horizontal direction, and the vertical gradient reflects the rate of change in the vertical direction. To further improve the detection accuracy, gradients in different directions are calculated to ensure that edges in any direction can be accurately captured. At the same time, to enhance the saliency of the edges, the gradient values are adaptively adjusted according to the local mean and local standard deviation of the pixels. Finally, the maximum value of each pixel in all directions is selected as the edge response value of the pixel.

[0059] The calculation formula for the edge response value is:

[0060] ,

[0061] where, represents the edge response value at the pixel position ; represents the maximum operation for all direction angles to ensure the selection of the edge response value in the best direction; represents the direction angle; represents the directional gradient enhancement part, calculating the gradient intensity in the direction of angle ; represents the preprocessed welding point image in the direction, that is, the rate of change of pixel values in the horizontal direction; represents the preprocessed welding point image in the direction, that is, the rate of change of pixel values in the vertical direction; represents the cosine value of the direction angle , used to adjust the horizontal gradient component; represents the sine value of the direction angle , used to adjust the vertical gradient component; represents the adaptive enhancement part, performing gradient enhancement based on the deviation degree of pixel values relative to the local mean; represents the enhancement coefficient, used to adjust the intensity of adaptive enhancement; represents the preprocessed welding point image at the pixel position ; represents the local mean of the preprocessed welding point image near the pixel position , which can be specifically set according to the specific implementation scenario and is not limited here; represents the preprocessed welding point image at the pixel position The local standard deviation in the vicinity can be specifically set according to the specific implementation scenario and will not be limited here;

[0062] By using the adaptive directional gradient enhancement edge detection algorithm, the edge response value at each pixel position is obtained, thereby forming an edge response map to accurately identify the edge of the welding point and ensure the smooth progress of the welding quality control of the bottom pins of the components.

[0063] S2. Based on the edge response map, extract feature points through curvature analysis, use the adaptive multi-scale shape matching algorithm to perform shape matching on the extracted feature points, and calculate the shape matching degree;

[0064] Based on the edge response map, extract feature points through curvature analysis. The curvature analysis first calculates the curvature at each pixel position, and then compares the curvature at each pixel position with the set curvature threshold. If it is higher than the curvature threshold, it is used as a feature point; the curvature threshold can be specifically set according to the specific implementation scenario and will not be limited here; the curvature analysis is a well-known technical means for those skilled in the art and will not be elaborated here;

[0065] Use the adaptive multi-scale shape matching algorithm to perform shape matching on the extracted feature points and calculate the shape matching degree;

[0066] The adaptive multi-scale shape matching algorithm calculates the distance matching degree by performing an exponential transformation on the difference between the distance of each feature point from the reference feature point and the mean distance, calculates the direction matching degree by performing a sine transformation on the direction difference, comprehensively considers the matching situations at different scales, and performs a weighted sum on the matching degrees at each scale to obtain the final shape matching degree;

[0067] The specific calculation formula for the shape matching degree is:

[0068] ,

[0069] Among them, represents the shape matching degree and is used to evaluate the overall shape matching situation of the welding point; represents the summation of the shape matching degrees at different scales; represents the number of scales; represents the weight of the scale, reflecting the importance of different scales; represents the number of feature points; represents the distance matching degree; represents the exponential function, enabling the distance matching degree to decay exponentially; represents the The minimum Euclidean distance between a feature point and a reference feature point, obtained by calculating the Euclidean distance between the feature point and the reference feature point, is a well-known technical means to those skilled in the art and will not be elaborated here; represents the mean of the distances; represents the standard deviation of the distances; represents the direction matching degree; represents the sine function, which is used to convert the direction difference into the direction matching degree; represents pi, which converts the direction angle into radians and is used for sine function calculation; represents the direction of the th feature point; represents the reference feature point direction; represents magnifying the difference between the direction of the th feature point and the reference feature point direction to the range of [0, ; represents converting the direction difference into a matching degree value between [0, 1] through the square of the sine function, where the matching degree is 1 when the difference is 0 and the matching degree is 0 when the difference is

[0070] By performing multi-scale analysis on the shape of the welding point, the shape matching degree of the welding point is evaluated, thereby providing a reliable basis for the evaluation of the welding quality and improving the accuracy and robustness of the welding quality evaluation.

[0071] S3. According to the shape matching degree, detect the electrical performance of the welding point to obtain the resistance value of the welding point; based on the resistance value of the welding point, use the welding point resistance evaluation algorithm to calculate the electrical performance evaluation index of the welding point;

[0072] The shape matching degree evaluates the appearance consistency of the welding point and discovers possible physical defects of the welding point, but fails to comprehensively reflect the internal electrical performance of the welding point. It is necessary to further detect the internal electrical performance of the welding point through electrical testing means. For welding points with low shape matching degree, the resistance value of the welding point can be focused on for detection to further verify whether there are problems with the electrical connection quality;

[0073] The electrical testing means is to measure the resistance value of the welding point at different positions and different time points by applying known voltage and current;

[0074] According to the shape matching degree, detect the internal electrical performance of the welding point through electrical testing means to obtain the resistance value of the welding point, and based on the resistance value of the welding point, use the welding point resistance evaluation algorithm to calculate the electrical performance evaluation index of the welding point;

[0075] The welding point resistance evaluation algorithm measures the resistance values at different positions and time points, calculates the mean and standard deviation of the resistance, uses the mean and standard deviation of the resistance to calculate the deviation coefficient, and through the deviation coefficient, the dispersion degree of the resistance measurement values can be understood. By calculating the gradient of the resistance value, the change rate of the resistance value is determined, reflecting the stability and uniformity of the welding point resistance value;

[0076] The specific calculation formula for the evaluation index of the electrical performance of the welding point is as follows:

[0077] ,

[0078] wherein, represents the evaluation index of the electrical performance of the welding point; represents the resistance; represents the corrected deviation coefficient value, which is used to evaluate the consistency of the resistance measurement values; represents the deviation coefficient, , represents the standard deviation of the resistance measurement values, represents the mean of the resistance measurement values; represents the influence of the resistance gradient; represents the exponential function, through which the influence of the resistance gradient decays exponentially; represents the resistance gradient, , represents the gradient of the resistance in space, represents the gradient of the resistance in time.

[0079] S4. Based on the shape matching degree and the evaluation index of the electrical performance of the welding point, use the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the component, and calculate the welding quality score of the bottom pins of the component; set the evaluation threshold, and judge the welding quality according to the evaluation threshold;

[0080] Based on the shape matching degree and the evaluation index of the electrical performance of the welding point, use the welding quality scoring algorithm to evaluate the welding quality of the bottom pins of the component, and calculate the welding quality score of the bottom pins of the component; the welding quality scoring algorithm calculates the welding quality score of the bottom pins of the component by performing exponential transformation on the shape matching degree and the evaluation index of the electrical performance of the welding point and introducing a balance factor, improving the accuracy and robustness of the welding quality evaluation;

[0081] The balance factor is obtained by taking the logarithm of the ratio of the shape matching degree and the evaluation index of the electrical performance of the welding point, then taking the absolute value, and performing processing through the exponential function to obtain the balance factor value;

[0082] The specific calculation formula for the welding quality score of the bottom pins of the component is as follows:

[0083] ,

[0084] Among them, represents the welding quality score of the bottom pins of the component, which is used to evaluate the overall quality of the welding points; represents the shape matching degree, which is used to evaluate the overall shape matching of the welding points; represents the evaluation index of the electrical performance of the welding points; and respectively represent the exponential parameters used to adjust the importance of the shape matching degree and the evaluation index of the electrical performance of the welding points; represents the balance factor, which is achieved through exponential and logarithmic operations, and is used to reduce the influence of the difference between the shape matching degree and the evaluation index of the electrical performance of the welding points, ensuring the balance and stability of the welding quality score of the bottom pins of the component; represents a positive number, which is used to avoid the situation where the denominator is zero during logarithmic operations;

[0085] The welding quality scoring algorithm can achieve a comprehensive, accurate and stable evaluation of the quality of the welding points at the bottom pins of the component;

[0086] Set the evaluation threshold, which can be specifically set according to the specific implementation scenario and is not limited here; use the evaluation threshold to judge the welding quality. If the welding quality score of the bottom pins of the component is greater than or equal to the evaluation threshold, it is qualified; if the welding quality score of the bottom pins of the component is less than the evaluation threshold, it is unqualified. The specific formula is as follows:

[0087] ,

[0088] Among them, represents the welding quality score of the bottom pins of the component; represents the evaluation threshold;

[0089] Through the accurate welding quality score of the bottom pins of the component and the setting of the evaluation threshold, it provides reliable technical support for the optimization of the welding process, improves the accuracy, comprehensiveness and reliability of the welding detection of the bottom pins of the component, and provides strong technical support for industrial welding quality control.

[0090] In summary, the welding detection system and method for the bottom pins of the component are completed.

[0091] The order of the invention embodiments is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0093] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for detecting soldering of pins at the bottom of components, characterized in that: The following steps are involved: S1: acquiring and preprocessing the welding point image to obtain the preprocessed welding point image; using an adaptive directional gradient enhancement edge detection algorithm to perform edge detection on the preprocessed welding point image, the algorithm calculates the gradient of each pixel in the horizontal and vertical directions, adaptively adjusts the gradient value according to the local mean and local standard deviation of the pixel, selects the maximum value of each pixel in all directions as the edge response value of the pixel position, and forms an edge response map; S2: Based on the edge response map, feature points are extracted through curvature analysis. The adaptive multi-scale shape matching algorithm is used to perform exponential transformation on the difference between the distance and the mean distance between each feature point and the reference feature point to calculate the distance matching degree. The direction matching degree is calculated by performing sine transformation on the direction difference. The shape matching degree is obtained by weighted summing the matching degrees at each scale. S3: According to the shape matching degree, the electrical performance of the welding point is tested to obtain the resistance value of the welding point; based on the resistance value of the welding point, the welding point resistance evaluation algorithm is used to measure the resistance value at different positions and different time points to calculate the mean and standard deviation of the resistance, and the deviation coefficient is calculated using the mean and standard deviation of the resistance; the resistance gradient is calculated to obtain the rate of change of the resistance value; Calculate the electrical performance evaluation index of the solder joint based on the deviation coefficient and resistance gradient; S4: Based on the shape matching and solder joint electrical performance evaluation indicators, the soldering quality of the bottom pins of the components is evaluated using the soldering quality scoring algorithm to calculate the soldering quality score of the bottom pins of the components; An evaluation threshold is set and welding quality is judged according to the evaluation threshold.

2. The method for detecting soldering of bottom pins of components according to claim 1, characterized in that: The S4 specifically includes: The welding quality scoring algorithm calculates the welding quality score of the bottom pin of the component by performing exponential transformation on the shape matching degree and the electrical performance evaluation index of the welding point and introducing a balance factor.

3. The method for detecting soldering of bottom pins of components according to claim 2, characterized in that: The S4 specifically includes: The balance factor value is obtained by taking the logarithm of the ratio of the shape matching degree and the electrical performance evaluation index of the welding point, then taking the absolute value, and processing it through an exponential function.

4. The method for detecting soldering of bottom pins of components according to claim 2, characterized in that: The S4 specifically includes: The welding quality is judged according to the evaluation threshold. When the welding quality score of the bottom pin of the component is greater than or equal to the evaluation threshold, it is qualified; when the welding quality score of the bottom pin of the component is less than the evaluation threshold, it is unqualified.

5. A component bottom pin welding detection system, applied to the component bottom pin welding detection method according to claim 1, characterized in that it includes the following contents: Welding point image acquisition module: acquires welding point images and outputs the welding point images to the image preprocessing module; Image preprocessing module: performs image preprocessing on the welding point image to obtain a preprocessed welding point image, and outputs the preprocessed welding point image to the edge detection module; Edge detection module: Use the adaptive directional gradient enhancement edge detection algorithm to perform edge detection on the preprocessed welding point image, obtain the edge response value of each pixel position, form an edge response map, and output the edge response map to the feature point extraction module; Feature point extraction module: Based on the edge response map, feature points are extracted through curvature analysis and output to the shape matching module; Shape matching module: Uses adaptive multi-scale shape matching algorithm to perform shape matching on feature points, calculates shape matching degree, and outputs the shape matching degree to the electrical performance detection module and welding quality assessment module; Electrical performance detection module: According to the shape matching degree, the internal electrical performance of the welding point is detected by electrical testing means to obtain the resistance value of the welding point, and the resistance value of the welding point is output to the welding point electrical performance evaluation module; Welding point electrical performance evaluation module: Based on the resistance value of the welding point, the welding point electrical performance evaluation index is calculated using the welding point resistance evaluation algorithm, and the welding point electrical performance evaluation index is output to the welding quality evaluation module; Welding quality assessment module: Based on the shape matching and welding point electrical performance evaluation indicators, the welding quality of the bottom pins of the components is evaluated using the welding quality scoring algorithm, the welding quality score of the bottom pins of the components is calculated, the evaluation threshold is set, and the welding quality is judged according to the evaluation threshold.

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