Component bottom pin welding detection system and method

Abstract

The present invention relates to the field of welding detection, and in particular to a system and method for detecting welding of the bottom pins of components. The system comprises: acquiring and preprocessing welding point images, further performing edge detection, and obtaining edge response maps; extracting feature points based on the edge response maps, performing shape matching on the extracted feature points, and obtaining shape matching degrees; detecting the electrical performance of welding points, and obtaining resistance values ​​of welding points; calculating welding point electrical performance evaluation indicators based on the resistance values ​​of welding points; calculating the welding quality score of the bottom pins of components based on the shape matching degrees and welding point electrical performance evaluation indicators; and setting evaluation thresholds to judge welding quality. The system solves the technical problems that welding point images are easily affected by noise and changes in illumination when faced with complex welding point images; the traditional feature point extraction and matching methods are not effective in dealing with a variety of shape and scale changes; and the internal electrical performance of welding points cannot be fully evaluated only through appearance detection and shape matching.

Description

Technical Field

[0001] The present invention relates to the field of welding detection, and in particular to a system and method for detecting welding of pins at the bottom of a component. Background Art

[0002] In the manufacturing process of electronic products, the welding quality of components directly affects the performance and reliability of the products. Poor welding may lead to unstable electrical connection or insufficient durability between the pins and the printed circuit board, thus affecting the reliability and life of the product. Traditional welding inspection 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 inspection can detect hidden defects, the equipment is expensive and the operation is complicated, which is not suitable for real-time inspection needs in large-scale production.

[0003] With the advancement of electronic manufacturing technology and the development of automation technology, automated welding inspection systems have gradually become a new trend in welding quality control. The component bottom pin welding inspection system can effectively detect and control welding quality, improve production efficiency and product quality consistency, while reducing labor costs and product return rates, further promoting the development of the electronic manufacturing industry.

[0004] However, the existing component bottom pin welding detection system has the following technical problems: when faced with complex welding point images, it is easily affected by noise and lighting changes, resulting in inaccurate edge detection and failure to accurately capture the edge details of the welding points; the shapes of welding points are complex and changeable, and traditional feature point extraction and matching methods are not effective when dealing with a variety of shape and scale changes; and only through appearance inspection and shape matching, it is impossible to fully evaluate the internal electrical performance of welding points, and it is easy to have welding points that are physically qualified but do not meet the electrical performance standards. Summary of the invention

[0005] The present invention provides a component bottom pin welding detection system and method to solve the problem that when facing complex welding point images, they are easily affected by noise and light changes, resulting in inaccurate edge detection and inability to accurately capture the edge details of the welding points; the shapes of the welding points are complex and changeable, and traditional feature point extraction and matching methods are not effective when dealing with various shape and scale changes; only through appearance detection and shape matching, it is impossible to fully evaluate the internal electrical performance of the welding points, and there is a technical problem that there are physically qualified welding points but the electrical performance does not meet the standards.

[0006] The component bottom pin welding detection system and method of the present invention specifically include the following technical solutions: The method for detecting the soldering of the pins at the bottom of the component comprises the following steps: S1: Acquire and preprocess the welding point image to obtain a preprocessed welding point image; use an adaptive directional gradient enhancement edge detection algorithm to perform edge detection on the preprocessed welding point image to obtain an edge response value at each pixel position to form an edge response map; S2: Based on the edge response map, feature points are extracted through curvature analysis, and the shape matching of the extracted feature points is performed using an adaptive multi-scale shape matching algorithm to calculate the shape matching degree; 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 calculate the electrical performance evaluation index of the welding point; S4: Based on the shape matching degree and the electrical performance evaluation index of the soldering point, the soldering quality of the bottom pins of the components is evaluated using the soldering quality scoring algorithm, and the soldering quality score of the bottom pins of the components is calculated; an evaluation threshold is set, and the soldering quality is judged according to the evaluation threshold.

[0007] Preferably, the S1 specifically includes: In the implementation process of the adaptive directional gradient enhancement edge detection algorithm, the gradient of each pixel in the horizontal and vertical directions is calculated, the gradient value is adaptively adjusted according to the local mean and local standard deviation of the pixel, and the maximum value of each pixel in all directions is selected as the edge response value of the pixel position.

[0008] Preferably, the S2 specifically includes: The adaptive multi-scale shape matching algorithm calculates the distance matching degree by exponentially transforming the difference between the distance and the mean distance of each feature point and the reference feature point; calculates the direction matching degree by performing a sine transform on the direction difference; and obtains the shape matching degree by weighted summation of the matching degrees at each scale.

[0009] Preferably, the S3 specifically includes: In the process of implementing the welding point resistance evaluation algorithm, the resistance value is measured at different positions and different time points, the mean and standard deviation of the resistance are calculated, and the deviation coefficient is calculated using the mean and standard deviation of the resistance; the rate of change of the resistance value is obtained by calculating the resistance gradient; and the electrical performance evaluation index of the welding point is calculated based on the deviation coefficient and the resistance gradient.

[0010] Preferably, 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.

[0011] Preferably, 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.

[0012] Preferably, 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.

[0013] The component bottom pin welding detection system includes the following: 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.

[0014] The beneficial effects of the technical solution of the present invention are: 1. Adopting adaptive directional gradient enhanced edge detection algorithm, by calculating the gradient of each pixel in different directions and adaptively adjusting the gradient value according to the local mean and local standard deviation, the edge of the welding point is accurately captured. The formed edge response map can accurately identify the edge of the welding point, improve the accuracy of welding point edge detection, and ensure the smooth quality control of the welding of the bottom pins of components.

[0015] 2. Based on the edge response map, feature points are extracted through curvature analysis to ensure the accuracy of feature point extraction of welding points. The adaptive multi-scale shape matching algorithm obtains shape matching through comprehensive calculation of distance matching and direction matching, and evaluates the overall shape matching of welding points. The calculation process of shape matching takes into account the matching of different scales. Through weighted summation, the accuracy and robustness of shape matching of welding points are improved, providing a reliable basis for welding quality evaluation.

[0016] 3. Based on the shape matching, the internal electrical performance of the welding point is tested by electrical testing means, especially focusing on the resistance value of the welding point with low shape matching. The welding point resistance evaluation algorithm is used to calculate the mean, standard deviation and resistance gradient of the resistance, and the consistency and stability of the resistance value of the welding point are evaluated. The electrical performance evaluation index of the welding point is obtained, which fully reflects the internal electrical performance of the welding point.

[0017] 4. 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 a soldering quality scoring algorithm. The soldering quality scoring algorithm comprehensively considers the shape matching and solder joint electrical performance evaluation indicators through exponential transformation and balance factors, reduces the difference between the two, and ensures the balance and stability of the soldering quality score.

[0018] 5. By setting the evaluation threshold, the welding quality is judged, which provides reliable technical support and improves the accuracy, comprehensiveness and reliability of welding detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a structural diagram of the component bottom pin welding detection system of the present invention; Figure 2 This is a flow chart of the method for detecting soldering of bottom pins of components described in the present invention. DETAILED DESCRIPTION

[0020] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0022] The specific scheme of the component bottom pin welding detection system and method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0023] See attached Figure 1 , which shows a structural diagram of a component bottom pin welding detection system provided by an embodiment of the present invention, the system includes the following parts: Welding point image acquisition module, image preprocessing module, edge detection module, feature point extraction module, shape matching module, electrical performance detection module, welding point electrical performance evaluation module, welding quality evaluation module; Welding point image acquisition module: Use an industrial camera to capture welding point images and output the welding point images to the image preprocessing module; Image preprocessing module: receiving the welding point image from the welding point image acquisition module, performing image preprocessing on the welding point image, such as denoising, enhancement and grayscale processing, to obtain the preprocessed welding point image, and outputting the preprocessed welding point image to the edge detection module; Edge detection module: receiving the preprocessed welding point image from the image preprocessing module, performing edge detection on the preprocessed welding point image using an adaptive directional gradient enhancement edge detection algorithm, obtaining an edge response value at each pixel position, forming an edge response map, and outputting the edge response map to the feature point extraction module; Feature point extraction module: receives the edge response map from the edge detection module, extracts feature points through curvature analysis, and outputs the feature points to the shape matching module; Shape matching module: receives feature points from the feature point extraction module, uses an 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 assessment module; Electrical performance detection module: receives the shape matching degree from the shape matching module, detects the internal electrical performance of the welding point through electrical testing means according to the shape matching degree, obtains the resistance value of the welding point, and outputs the resistance value of the welding point to the welding point electrical performance evaluation module; Welding point electrical performance evaluation module: receives the resistance value of the welding point from the electrical performance detection module, calculates the welding point electrical performance evaluation index using the welding point resistance evaluation algorithm, and outputs the welding point electrical performance evaluation index to the welding quality evaluation module; Welding quality assessment module: Based on the shape matching degree of the shape matching module and the welding point electrical performance assessment index of the welding point electrical performance assessment module, the welding quality of the bottom pins of the components is assessed using the welding quality scoring algorithm, the welding quality score of the bottom pins of the components is calculated, the assessment threshold is set, and the welding quality is judged according to the assessment threshold.

[0024] Refer to the attached Figure 2 , which shows a flow chart of a method for detecting soldering of bottom pins of components provided by an embodiment of the present invention, the method comprising the following steps: S1, acquiring and preprocessing the welding point image to obtain a preprocessed welding point image; using an adaptive directional gradient enhancement edge detection algorithm to perform edge detection on the preprocessed welding point image to obtain an edge response value at each pixel position to form an edge response map; An industrial camera is used to capture a welding point image, and image preprocessing is performed on the welding point image, such as denoising, enhancing, and graying, to improve the quality of the welding point image, eliminate noise, and enhance the contrast of the welding point image, to ensure that the welding point image is clear, and to obtain a preprocessed welding point image; the image preprocessing, such as denoising, enhancing, and graying, is a technical means well known to those skilled in the art, and will not be described in detail herein; The preprocessed welding point image is subjected to edge detection using an adaptive directional gradient enhancement edge detection algorithm to obtain an edge response value at each pixel position and form an edge response map; The adaptive directional gradient enhancement edge detection algorithm expresses the rate of change of image brightness by calculating the gradient of each pixel in the horizontal and vertical directions. 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. In order to further improve the detection accuracy, the gradients in different directions are calculated to ensure that the edges in any direction can be accurately captured. At the same time, in order to enhance the significance of the edge, the gradient value is adaptively adjusted according to the local mean and local standard deviation of the pixel. Finally, the maximum value of each pixel in all directions is selected as the edge response value of the pixel. The calculation formula of edge response value is: , in, Indicates the pixel position The edge response value at ; Represents angles in all directions Perform a maximum value operation to ensure that the edge response value in the best direction is selected; Indicates the direction angle; Represents the directional gradient enhancement part, calculated at an angle of The gradient strength in the direction of Represents the pre-processed welding point image exist Directional gradient, that is, the rate of change of pixel value in the horizontal direction; Represents the pre-processed welding point image exist Directional gradient, that is, the rate of change of pixel value in the vertical direction; Indicates direction angle The cosine value of is used to adjust the horizontal gradient component; Indicates direction angle The sine value of is used to adjust the vertical gradient component; Represents the adaptive enhancement part, which performs gradient enhancement based on the degree of deviation of pixel values ​​relative to the local mean; Represents the enhancement coefficient, which is used to adjust the strength of adaptive enhancement; Represents the pre-processed welding point image At pixel position The pixel value at ; Represents the pre-processed welding point image At pixel position The local mean value nearby can be set according to the specific implementation scenario and is not limited here; Represents the pre-processed welding point image At pixel position The local standard deviation of the vicinity can be set according to the specific implementation scenario and is not limited here; By using an adaptive directional gradient enhancement edge detection algorithm to obtain the edge response value of each pixel position, an edge response map is formed to accurately identify the edges of the soldering points and ensure smooth quality control of the soldering of the bottom pins of components.

[0025] S2. Based on the edge response map, feature points are extracted through curvature analysis, and the shape matching is performed on the extracted feature points using an adaptive multi-scale shape matching algorithm to calculate the shape matching degree; Based on the edge response map, feature points are extracted by curvature analysis. The curvature analysis first calculates the curvature of each pixel position, and then compares the curvature of each pixel position with a set curvature threshold. If the curvature is higher than the curvature threshold, it is used as a feature point. The curvature threshold can be set according to the specific implementation scenario and is not limited here. The curvature analysis is a technical means well known to those skilled in the art and will not be described in detail here. Use an adaptive multi-scale shape matching algorithm to perform shape matching on the extracted feature points and calculate the shape matching degree; The adaptive multi-scale shape matching algorithm performs exponential transformation on the difference between the distance and the mean distance of each feature point and the reference feature point to calculate the distance matching degree, performs sine transformation on the direction difference to calculate the direction matching degree, comprehensively considers the matching conditions at different scales, and performs weighted summation on the matching degrees at each scale to obtain the final shape matching degree; The specific calculation formula of shape matching is: , in, Indicates the shape matching degree, which is used to evaluate the overall shape matching of the welding point; It represents the sum of shape matching degrees at different scales; Indicates the number of scales; Indicates the weight of the scale, reflecting the importance of different scales; Indicates the number of feature points; Indicates the distance matching degree; represents an exponential function, which makes the distance matching degree decay exponentially; Indicates The minimum Euclidean distance between a feature point and a reference feature point is obtained by calculating the Euclidean distance between the feature point and the reference feature point, which is a technical means well known to those skilled in the art and will not be described in detail here; represents the mean of the distance; represents the standard deviation of the distance; Indicates the degree of direction matching; represents the sine function, which is used to convert the direction difference into the direction matching degree; Represents pi, converts the direction angle into radians for sine function calculation; Indicates The direction of the feature points; Indicates the direction of the reference feature point; Indicates that the The difference between the direction of the feature point and the direction of the reference feature point is enlarged to [0, ]scope; It means that the direction difference is converted into a matching degree value between [0,1] by the square of the sine function, where the matching degree is 1 when the difference is 0 and the matching degree is When the matching degree is 0; Through multi-scale analysis of the shape of the welding points, the shape matching of the welding points is evaluated, thus providing a reliable basis for the evaluation of welding quality and improving the accuracy and robustness of welding quality evaluation.

[0026] 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 calculate the electrical performance evaluation index of the welding point; The shape matching evaluates the appearance consistency of the solder joint and finds possible physical defects in the solder joint, but it fails to fully reflect the internal electrical performance of the solder joint. It is necessary to further test the internal electrical performance of the solder joint through electrical testing methods. For solder joints with low shape matching, the resistance value of the solder joint can be tested to further verify whether there is a problem with the quality of the electrical connection. 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; According to the shape matching degree, the internal electrical performance of the welding point is tested by electrical testing means 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 calculate the electrical performance evaluation index of the welding point; The welding point resistance evaluation algorithm measures the resistance value at different positions and different time points, calculates the mean value and standard deviation of the resistance, and uses the mean value and standard deviation of the resistance to calculate the deviation coefficient. The degree of dispersion of the resistance measurement value can be understood through the deviation coefficient. The gradient of the resistance value is calculated to determine the rate of change of the resistance value, which reflects the stability and uniformity of the resistance value of the welding point. The specific calculation formula for the electrical performance evaluation index of the welding point is: , in, Indicates the electrical performance evaluation index of the welding point; Represents resistance; Indicates the corrected coefficient of deviation value, which is used to evaluate the consistency of resistance measurement values; represents the coefficient of variation, , represents the standard deviation of the resistance measurements, Indicates the mean value of resistance measurements; represents the effect of resistance gradient; represents an exponential function, through which the influence of the resistance gradient decays exponentially; represents the resistance gradient, , represents the gradient of resistance in space, Represents the gradient of resistance over time.

[0027] S4. Based on the shape matching degree and the electrical performance evaluation index of the welding point, the welding quality of the bottom pin of the component is evaluated using the welding quality scoring algorithm, and the welding quality score of the bottom pin of the component is calculated; the evaluation threshold is set, and the welding quality is judged according to the evaluation threshold; Based on the shape matching degree and the electrical performance evaluation index of the soldering point, the soldering quality of the bottom pin of the component is evaluated by using the soldering quality scoring algorithm, and the soldering quality score of the bottom pin of the component is calculated; the soldering quality scoring algorithm performs exponential transformation on the shape matching degree and the electrical performance evaluation index of the soldering point, and introduces a balance factor to calculate the soldering quality score of the bottom pin of the component, thereby improving the accuracy and robustness of the soldering quality evaluation; The balance factor 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 to obtain the balance factor value; The specific calculation formula for the soldering quality score of the bottom pins of components is: , in, Indicates the soldering quality score of the bottom pins of components, which is used to evaluate the overall quality of soldering points; Indicates the shape matching degree, which is used to evaluate the overall shape matching of the welding point; Indicates the electrical performance evaluation index of the welding point; and represent the index parameters used to adjust the importance of the shape matching and electrical performance evaluation indicators of the solder joint, respectively; It represents the balance factor, which is realized through exponential and logarithmic operations, and is used to reduce the influence of the difference between the shape matching degree and the electrical performance evaluation index of the solder joint, so as to ensure the balance and stability of the soldering quality score of the bottom pin of the component; Represents a positive number, used to avoid the situation where the denominator is zero during logarithmic operations; The soldering quality scoring algorithm can achieve a comprehensive, accurate and stable assessment of the soldering quality of the bottom pins of components; The evaluation threshold can be set according to the specific implementation scenario and is not limited here. The evaluation threshold is used to judge the welding quality. If the welding quality score of the bottom pin of the component is greater than or equal to the evaluation threshold, it is qualified; if the welding quality score of the bottom pin of the component is less than the evaluation threshold, it is unqualified. The specific formula is as follows: , in, Indicates the soldering quality score of the bottom pins of components; represents the evaluation threshold; Through accurate scoring of component bottom pin welding quality and setting of evaluation thresholds, reliable technical support is provided for the optimization of welding processes, the accuracy, comprehensiveness and reliability of component bottom pin welding detection are improved, and strong technical support is provided for industrial welding quality control.

[0028] In summary, the component bottom pin welding detection system and method are completed.

[0029] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages 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.

[0030] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0031] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should 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: Acquire and preprocess the welding point image to obtain a preprocessed welding point image; use an adaptive directional gradient enhancement edge detection algorithm to perform edge detection on the preprocessed welding point image to obtain an edge response value at each pixel position to form an edge response map; S2: Based on the edge response map, feature points are extracted through curvature analysis, and the shape matching of the extracted feature points is performed using an adaptive multi-scale shape matching algorithm to calculate the shape matching degree; 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 calculate the electrical performance evaluation index of the welding point; 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 S1 specifically includes: In the implementation process of the adaptive directional gradient enhancement edge detection algorithm, the gradient of each pixel in the horizontal and vertical directions is calculated, the gradient value is adaptively adjusted according to the local mean and local standard deviation of the pixel, and the maximum value of each pixel in all directions is selected as the edge response value of the pixel position.

3. The method for detecting soldering of bottom pins of components according to claim 1, characterized in that: The S2 specifically includes: The adaptive multi-scale shape matching algorithm calculates the distance matching degree by exponentially transforming the difference between the distance and the mean distance of each feature point and the reference feature point; calculates the direction matching degree by performing a sine transform on the direction difference; and obtains the shape matching degree by weighted summation of the matching degrees at each scale.

4. The method for detecting soldering of bottom pins of components according to claim 1, characterized in that: The S3 specifically includes: In the process of implementing the welding point resistance evaluation algorithm, the resistance value is measured at different positions and different time points, the mean and standard deviation of the resistance are calculated, and the deviation coefficient is calculated using the mean and standard deviation of the resistance; the rate of change of the resistance value is obtained by calculating the resistance gradient; and the electrical performance evaluation index of the welding point is calculated based on the deviation coefficient and the resistance gradient.

5. 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.

6. The method for detecting soldering of bottom pins of components according to claim 5, 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.

7. The method for detecting soldering of bottom pins of components according to claim 5, 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.

8. Component bottom pin welding detection system, characterized in that: Includes the following: 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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