An optimized method for improving the welding strength of capacitor leads

Abstract

The present application provides an optimization method for improving the welding strength of capacitor guide pins, which relates to the technical field of capacitors and includes: measuring the target guide pin attributes of the capacitor guide pins; after locally calling the target object attributes of the welding object, performing solder control analysis according to the target object attributes and the target guide pin attributes to obtain solder correlation information; performing initial setting of welding parameters according to the target guide pin attributes and the target object attributes to obtain initial welding parameters; initializing the welding strength optimization space based on the initial welding parameters and the welding feed speed range; performing small-batch verification and optimization of welding control in the welding strength optimization space, and outputting target welding control parameters; and performing the welding operation of the capacitor guide pins on the welding object according to the target welding control parameters. Through the present application, the technical problems of unstable welding quality and low production efficiency in the prior art can be solved, and the technical effects of improving the stability of welding quality and optimizing production efficiency can be achieved.

Description

Technical Field

[0001] This application relates to the technical field of capacitors, and in particular to an optimization method for improving the welding strength of capacitor leads. Background Art

[0002] In modern electronic manufacturing, the welding quality of capacitor leads directly affects the performance and reliability of capacitors. Especially in demanding application scenarios such as high frequency and high voltage, the precision and strength of welding become particularly important.

[0003] Currently, in the process of adjusting the parameters of lead welding in the prior art, it usually relies on manual setting of control indicators, such as welding time, temperature, pressure and other welding control parameters. Although these parameters can affect the welding quality to a certain extent, due to the differences in welding objects and the uncertainty and complexity of welding conditions, a large number of trial-and-error experiments are often required to gradually adjust the control parameters. However, this way that relies on manual experience and trial-and-error is not only inefficient, but also may lead to an increase in production costs and unnecessary waste of resources. In addition, the prior art does not fully consider the relationship between the lead properties and the welding strength requirements during the welding process, and is even less able to systematically optimize these welding control parameters through an accurate mathematical model. Therefore, the prior art lacks a precise and efficient welding control optimization method, and cannot ensure the high efficiency and consistency of the production process while meeting the welding strength requirements.

[0004] In summary, there are technical problems in the prior art that due to the adjustment of welding control parameters relying on manual experience and not fully considering the relationship between the lead properties and the welding strength requirements, the welding quality is unstable and the production efficiency is low, further affecting the reliability and consistency of lead welding. Summary of the Invention

[0005] The purpose of this application is to provide an optimization method for improving the welding strength of capacitor leads, so as to solve the technical problems in the prior art that due to the adjustment of welding control parameters relying on manual experience and not fully considering the relationship between the lead properties and the welding strength requirements, the welding quality is unstable and the production efficiency is low, further affecting the reliability and consistency of lead welding.

[0006] In view of the above problems, the present application provides an optimization method for improving the welding strength of capacitor leads, including: determining the target lead attributes of the capacitor leads, where the target lead attributes include target material characteristics and target geometric characteristics; locally calling the target object attributes of the welding object, and then performing solder control analysis based on the target object attributes and the target lead attributes to obtain solder-related information, where the solder-related information includes the welding feed speed range and the target solder type; performing initial setting of welding parameters based on the target lead attributes and the target object attributes to obtain initial welding parameters; initializing the welding strength optimization space based on the initial welding parameters and the welding feed speed range; performing small-batch verification optimization of welding control in the welding strength optimization space to output target welding control parameters; and performing the welding operation of the capacitor leads on the welding object according to the target welding control parameters.

[0007] The technical solution provided in the present application has at least the following technical effects or advantages: By determining the target lead attributes of the capacitor leads, where the target lead attributes include target material characteristics and target geometric characteristics; locally calling the target object attributes of the welding object, and then performing solder control analysis based on the target object attributes and the target lead attributes to obtain solder-related information, where the solder-related information includes the welding feed speed range and the target solder type; performing initial setting of welding parameters based on the target lead attributes and the target object attributes to obtain initial welding parameters; initializing the welding strength optimization space based on the initial welding parameters and the welding feed speed range; performing small-batch verification optimization of welding control in the welding strength optimization space to output target welding control parameters; and performing the welding operation of the capacitor leads on the welding object according to the target welding control parameters. That is to say, by achieving the technical goal of automated and precise welding control, the technical effects of improving the stability of welding quality and optimizing production efficiency are achieved.

[0008] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. Description of the Drawings

[0009] To more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on the provided drawings.

[0010] Figure 1 It is a schematic flow chart of an optimization method for improving the welding strength of capacitor leads in the present application;

[0011] Figure 2 It is a schematic flow chart of performing the welding operation of the capacitor leads in an optimization method for improving the welding strength of capacitor leads in the present application. Detailed implementation manners

[0012] By providing an optimization method for improving the welding strength of capacitor leads, the present application solves the technical problems in the prior art that due to the adjustment of welding control parameters relying on manual experience and not fully considering the relationship between the lead attributes and the welding strength requirements, the welding quality is unstable and the production efficiency is low, further affecting the reliability and consistency of lead welding. The technical goal of realizing automatic and precise welding control is achieved, and the technical effect of improving the stability of welding quality and optimizing the production efficiency is achieved.

[0013] Next, the technical solutions in the present application will be clearly and completely described with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described here. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the convenience of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0014] Please refer to the atta Figure 1 chments. The present application provides an optimization method for improving the welding strength of capacitor leads, which specifically includes the following steps:

[0015] S100: Measure the target lead attributes of the capacitor leads, where the target lead attributes include target material characteristics and target geometric characteristics.

[0016] Specifically, the capacitor lead is the lead for which the welding strength needs to be optimized. By measuring the target lead properties of the capacitor lead. The target lead properties include target material characteristics and target geometric characteristics. The target material characteristics refer to the material properties of the capacitor lead, such as electrical conductivity, high-temperature resistance, or corrosion resistance, which directly affect heat conduction and welding strength during welding. For example, if the lead is made of copper, it may conduct heat more easily during welding, thus affecting the welding temperature and the quality of the solder joint. Among them, for the target material characteristics, experimental methods can be used to measure the physical and chemical properties of the lead. For example, a tensile test can be used to measure the tensile strength of the lead material, or thermal analysis (such as thermogravimetric analysis) can be used to determine its stability at high temperatures and evaluate its heat conduction performance; for electrical conductivity, the four-probe method is usually used to measure the resistivity. These methods can quantify the material characteristics of the lead, such as conductivity, melting point, and high-temperature resistance. The target geometric characteristics refer to the shape, size, and surface state of the lead, such as the diameter, length, and surface finish of the lead, which affect the contact area and heat concentration during welding. By considering these two properties comprehensively, the optimization method can more accurately adjust the welding parameters to achieve the ideal welding strength. Among them, an optical microscope or a scanning electron microscope (SEM) can be used to observe the surface roughness or morphology of the lead. In addition, a laser rangefinder or a three-dimensional laser scanner can be used to measure the precise size and geometric shape of the lead, including the length, diameter, and its changing shape parameters.

[0017] S200: After locally calling the target object properties of the welding object, solder control analysis is performed based on the target object properties and the target lead properties to obtain solder-related information, where the solder-related information includes the welding feed speed range and the target solder type.

[0018] Furthermore, step S200 of the present application further includes:

[0019] S210: Solder feed control analysis is performed based on the solder joint size parameters and the target geometric characteristics to obtain the welding feed speed range; S220: Solder compatibility analysis is performed based on the pad material properties and the target material characteristics to obtain the target solder type; S230: The welding feed speed range and the target solder type are associated and stored to obtain the solder-related information.

[0020] Specifically, the welding object refers to the object for welding the leads of a capacitor to an external circuit (such as a circuit board or other electrical connection components). After invoking the target object attributes of the welding object locally, the solder joint size parameter refers to the size of the welding area in the target object attributes, such as the diameter and depth of the solder joint. The target geometric characteristics refer to the characteristics of the lead, such as its shape, size, and surface condition. Based on the solder joint size parameter and the target geometric characteristics, solder feeding control analysis is carried out to determine the feeding speed during the welding process to ensure that the solder can fill the solder joint appropriately, thereby achieving the best welding effect and obtaining the welding feeding speed range. The welding feeding speed range refers to the range of solder supply. For example, if the set solder supply speed range is twenty millimeters per second, it can avoid solder overflow caused by excessive solder or loose solder joints caused by insufficient solder.

[0021] Next, the pad material attributes refer to the properties of the pad material during the welding process, such as its thermal conductivity, corrosion resistance, etc. These characteristics will affect the flow and adhesion effect of the solder during the welding process. The target material characteristics refer to the physical and chemical characteristics of the lead material, which determine the selected solder to ensure the welding quality. For example, if the lead is made of copper, a solder containing silver may be selected because silver has good electrical conductivity and welding strength. Based on these material attributes, solder compatibility analysis can be carried out to obtain the target solder type and determine the most suitable solder type, thereby avoiding loose welding or solder joint defects caused by incompatible solder.

[0022] Finally, the association storage of the welding feeding speed range and the target solder type is for subsequent use. During different welding processes, the most suitable solder type and feeding speed can be automatically selected according to different welding requirements, effectively improving the automation and intelligence of the welding process.

[0023] Furthermore, step S220 of the present application further includes:

[0024] S221: Obtain the target material properties and the target heat resistance range from the extraction of the target material characteristics; S222: Traverse the solder adaptation information library using the pad material properties and the target material properties respectively to obtain the first adapted solder set and the second adapted solder set; S223: Solve the intersection of the first adapted solder set and the second adapted solder set to obtain the compatible adapted solder set, where multiple compatible adapted solders in the compatible adapted solder set have multiple sample material melting point range identifiers; S224: Solve the intersection of the target heat resistance range and the pad heat resistance range to obtain the compatible heat resistance range, and then traverse the multiple sample material melting point ranges using the compatible heat resistance range to screen and obtain M compatible adapted solders from the compatible adapted solder set; S225: Apply the M compatible adapted solders to conduct a small batch test of lead welding to obtain M solder spreading percentages and M intermetallic compound percentages; S226: Preset the spreading influence weight and the intermetallic compound influence weight, and evaluate the M solder spreading percentages and M intermetallic compound percentages using the spreading influence weight and the intermetallic compound influence weight to obtain M compatible adaptation coefficients; S227: Extract the target solder type from the M compatible adapted solders by serializing the M compatible adaptation coefficients, where the target solder type has an atmosphere sensitivity identifier.

[0025] Specifically, the target material properties and the target heat resistance range are obtained from the extraction of the target material characteristics. The target material properties refer to property information such as conductivity and corrosion resistance. At the same time, the temperature range that the material can withstand, that is, the target heat resistance range, also needs to be determined. For example, the heat resistance range of a copper lead may be from 400 degrees Celsius to 500 degrees Celsius, which is used to select a suitable solder subsequently.

[0026] Then, access each piece of information in the solder adaptation information library in sequence, and respectively use the pad material properties and the target material properties to retrieve in the solder adaptation information library to obtain the first adapted solder set and the second adapted solder set. Among them, the first adapted solder set is the solder screened according to the properties of the pad material, and the second adapted solder set is the solder screened according to the target material properties.

[0027] Next, solve the intersection of the first adapted solder set and the second adapted solder set to find all the solders that meet the requirements in both adapted solder sets, and obtain the compatible adapted solder set. The solders in the compatible adapted solder set not only meet the requirements of the pad but also can be compatible with the material properties of the target lead. The solders in the compatible adapted solder set have multiple sample material melting point range identifiers, and the sample material melting point range identifier refers to the melting point range of each solder. For example, the solder may have a melting point range of 200 degrees Celsius to 300 degrees Celsius.

[0028] Then, find the intersection of the target heat resistance range and the pad heat resistance range to obtain the intersection part and get the compatible heat resistance range. Access each melting point in the melting point ranges of multiple sample materials in sequence, and retrieve the compatible heat resistance range, so as to screen out the solders within the compatible heat resistance range from the compatible solder set. Furthermore, these solders can withstand high working temperatures without performance degradation, and obtain M kinds of compatible solders. Here, M is an integer greater than 0.

[0029] Next, conduct a small batch test of lead pin soldering using the M kinds of screened compatible solders to obtain the solder spread percentage and the intermetallic compound percentage. The small batch test is to test different solders under actual soldering conditions to evaluate their performance. Through the test, the spread percentage of each solder (the degree of distribution of the solder during the soldering process, that is, the spreading ability of the solder in the contact area) and the intermetallic compound percentage (the proportion of the compound formed by the reaction of the solder and the lead pin metal during the soldering process) can be obtained, which helps to select the best solder.

[0030] Then, preset the spread influence weight and the intermetallic compound influence weight. The spread influence weight and the intermetallic compound influence weight are used to measure the spreading degree of the solder and the influence of forming intermetallic compounds during the soldering process. Use the spread influence weight and the intermetallic compound influence weight to evaluate the M solder spread percentages and the M intermetallic compound percentages. For example, a solder with good spreading may have a higher weight, while too many intermetallic compounds may cause unstable solder joints, so a weighted evaluation is performed on them to obtain M compatible adaptation coefficients.

[0031] Finally, by serializing the M compatible adaptation coefficients, serialization means sorting according to the compatible adaptation coefficients of each solder to find the most suitable solder type. Extract the target solder type from the M kinds of compatible solders. The target solder type has an atmosphere sensitivity identifier, indicating its sensitivity to the ambient atmosphere (such as oxygen, humidity, etc.), which may affect the stability and final quality during the soldering process.

[0032] S300: Initialize and set the soldering parameters according to the target lead pin attributes and the target object attributes to obtain the initial soldering parameters.

[0033] Furthermore, step S300 of the present application further includes:

[0034] S310: Obtain the target thermal conductivity from the extraction of the target material properties; S320: Use the target thermal conductivity, solder joint size parameters, and target solder type as search conditions for local search to obtain multiple historical welding times; S330: Conduct a discrete analysis of the multiple historical welding times and output a welding time interval; S340: Interactively obtain the solder heat resistance range of the target solder type, and obtain the welding temperature interval by solving the intersection of the solder heat resistance range and the compatible heat resistance range; S350: Obtain the guide pin pressure tolerance interval by analyzing the target geometric characteristics; S360: Interactively obtain the equipment capacity interval of the welding equipment, and obtain the welding pressure interval by solving the intersection of the guide pin pressure tolerance interval and the equipment capacity interval; S370: Obtain the welding atmosphere type and atmosphere flow rate interval from the atmosphere sensitivity identifier; S380: Integrate the welding time interval, welding temperature interval, welding pressure interval, welding atmosphere type, and atmosphere flow rate interval, and output the initial welding parameters.

[0035] Specifically, obtain the target thermal conductivity, that is, the thermal conductivity, from the physical properties in the target material properties. Thermal conductivity is an index to measure the heat conduction ability of materials. The higher the thermal conductivity, the stronger the heat transfer ability of the material. For example, the thermal conductivity of copper is higher than that of aluminum. Therefore, understanding the thermal conductivity of the target guide pin material helps to control the heat distribution during welding and avoid damage to the guide pin caused by excessive temperature.

[0036] Next, use factors such as the target thermal conductivity, the size of the solder joint (such as the diameter and depth of the solder joint), and the selected solder type as search conditions to search for and compare historical welding records, and obtain multiple completed welding times from them. These historical data can be used to infer and optimize the possible time range during the welding process. For example, for materials with larger solder joints and higher thermal conductivity, historical records show that the welding time may be between five seconds and ten seconds.

[0037] Next, conduct a discrete analysis of the historical welding times. Discrete analysis means analyzing these historical welding time data to find the distribution law of the data, and then obtaining a reasonable time interval and outputting the welding time interval. For example, the welding time is concentrated between eight seconds and twelve seconds, which helps to determine the time range of the welding process and avoid the influence of too long or too short welding time on the welding quality.

[0038] Then, interactively obtain the solder heat resistance range of the target solder type. The solder heat resistance range refers to the highest and lowest temperature ranges that the solder can withstand during the welding process. The compatible heat resistance range is the temperature interval that matches the heat resistance characteristics of the guide pin and the solder pad. By solving the intersection of the solder heat resistance range and the compatible heat resistance range, the most suitable welding temperature interval is obtained to ensure that the temperature during the welding process does not exceed the tolerance range of the material, thereby ensuring the welding quality and the stability of the guide pin.

[0039] According to the shape and size of the guide pin, calculate the pressure range it can withstand during the welding process to obtain the pressure tolerance range of the guide pin. Geometric characteristics include the diameter, length, surface roughness, etc. of the guide pin, and these factors will affect the pressure tolerance ability of the guide pin. For example, a slender guide pin may have a smaller pressure range it can withstand, while a short and thick guide pin can withstand a larger pressure.

[0040] Next, interactively obtain the equipment capacity range of the welding equipment. The capacity range of the welding equipment refers to the maximum and minimum pressure ranges that the welding equipment can provide. By performing an intersection analysis on the pressure tolerance range of the guide pin and the pressure capacity range of the welding equipment, the appropriate welding pressure range can be determined.

[0041] Then, obtain the welding atmosphere type and the atmosphere flow rate range from the atmosphere-sensitive identifier. The atmosphere-sensitive identifier refers to the sensitivity of the selected solder to changes in the atmosphere during the welding process. The atmosphere type refers to the type of ambient gas used during the welding process, such as nitrogen, argon, etc., and the atmosphere flow rate range is the range of the gas flow velocity during the welding process, which will affect the diffusion of the solder and the cleanliness of the metal surface.

[0042] Finally, integrate the welding time range, welding temperature range, welding pressure range, welding atmosphere type, and atmosphere flow rate range, and output the initial welding parameters. These parameters are the basic basis for performing welding operations.

[0043] S400: Initialize the welding strength optimization space based on the initial welding parameters and the welding feed rate range.

[0044] Specifically, initialize the welding strength optimization space based on the initial welding parameters and the welding feed rate range. The initial welding parameters serve as the basic reference points for the welding process, ensuring that the welding operation can be carried out under appropriate conditions. Next, the welding feed rate range refers to the range of the solder application speed during the welding process. The feed rate of the solder has an important impact on the welding quality. An overly fast feed rate may result in incomplete welding, while an overly slow rate may affect production efficiency. By combining the initial welding parameters and the welding feed rate range, the welding strength optimization space can be initialized to search for the optimal welding strength within different ranges. During the welding process, by continuously adjusting and optimizing the parameters, the parameter combination that can best ensure the welding strength can be found, thereby ensuring the welding quality and stability and avoiding the welding strength not meeting the requirements due to improper parameter settings.

[0045] S500: Conduct small-batch verification and optimization of welding control in the welding strength optimization space, and output the target welding control parameters.

[0046] Furthermore, step S500 of the present application further includes:

[0047] S510: Construct the optimization space for welding strength based on the welding time interval, welding temperature interval, welding pressure interval, gas flow rate interval, and welding feed rate interval; S520: After positioning H initial welding particle points in the optimization space for welding strength, extract the H sample welding control parameters of the H initial welding particle points for small-batch welding tests to obtain an H-set of initial strength indicators, where the initial strength indicator set includes initial drawing strength, initial shear strength, initial peel strength, initial thermal cycle strength, and initial fatigue strength; S530: Conduct a welding fitness evaluation based on the H-set of initial strength indicators and output H initial welding fitness values; S540: Analyze the optimization trend of the H initial welding particle points according to the H initial welding fitness values to obtain a welding parameter adjustment direction vector; S550: Serialize the H initial welding fitness values and locate the optimized starting particle point among the H initial welding particle points according to the fitness extreme value; S560: Pre-define the adjustment step size for welding indicators; S570: Use the welding parameter adjustment direction vector as the constraint for the particle movement direction and the adjustment step size for welding indicators as the constraint for the particle movement distance, and conduct small-batch verification and optimization for welding control in the optimization space for welding strength until the welding fitness fluctuates stably, and output the target welding control parameters.

[0048] Specifically, an optimization space for welding strength is constructed based on the welding time interval, welding temperature interval, welding pressure interval, gas flow rate interval, and welding feed rate interval. The interval of each parameter represents the possible variation range of the parameter during the actual welding process. By combining the intervals, an optimization space for welding strength is constructed, and various parameters are adjusted therein to achieve the best welding strength.

[0049] Then, after positioning H initial welding particle points in the optimization space for welding strength, extract the welding control parameters of these particle points and conduct small-batch welding tests. The initial welding particle points represent possible combinations of welding parameters and are multiple points randomly selected from the constructed optimization space for welding strength. Each point represents a set of specific welding parameters, such as specific time, temperature, pressure, etc. After conducting small-batch welding tests at the positions of these initial particle points, the H-set of initial strength indicators obtained, including initial drawing strength, shear strength, peel strength, thermal cycle strength, and fatigue strength, helps evaluate the strength characteristics of the welding points.

[0050] Next, conduct a welding fitness evaluation based on the initial strength indicator set. The welding fitness evaluation is a quantitative score for the welding quality. By analyzing the initial strength indicators (such as drawing strength, shear strength, etc.), it is judged whether the welding points meet the quality requirements, and H initial welding fitness values are output. The particle points with high fitness correspond to the parameter combinations that can achieve the expected welding strength.

[0051] Then, based on the initial welding fitness, an optimization trend analysis is performed on the initial welding particle points. The optimization trend analysis refers to determining which direction of adjustment may bring better welding strength by analyzing the fitness of each particle point, and then obtaining the welding parameter adjustment direction vector. For example, if the welding strength of some particle points is good, it may mean that their setting of certain parameters is better than that of other points, thus determining the adjustment direction.

[0052] Next, serialize the initial welding fitness, arrange all the fitness values in descending order, and select the best particle point as the starting point for optimization, which serves as the basis for the next step of optimization to ensure that the finally selected welding parameters can meet the highest strength requirements.

[0053] Then, pre-define the adjustment step size of the welding index, which represents the change amount when adjusting the welding parameters each time during the welding process. For example, the welding time may increase by one second each time, and the welding temperature may increase by 50 degrees Celsius. The smaller the step size is set, the higher the precision of the optimization process, but more iterations may be required.

[0054] Next, by simulating the movement of particles in the welding strength optimization space, use the direction vector and step size to control the movement of particles, and gradually approach the optimal welding parameters. Take the welding parameter adjustment direction vector as the constraint for the particle movement direction, and take the welding index adjustment step size as the constraint for the particle movement distance, and conduct a small-batch verification optimization for welding control until the welding fitness fluctuates stably. The small-batch verification is to verify the welding effect through multiple small-scale tests until the fitness is stable, indicating that the optimal welding parameters have been found. Finally, output the target welding control parameters, which represent the optimized welding settings and can provide the best welding strength to meet the production requirements.

[0055] S600: According to the target welding control parameters, perform the welding operation of the capacitor lead on the welding object.

[0056] Furthermore, as Figure 2 shown, step S600 of this application further includes:

[0057] S610: Extract the target solder joint distribution from the target object attributes, where the target object attributes include pad material attributes, pad heat resistance range, solder joint size parameters, and the target solder joint distribution; S620: Locate K target solder joints on the welding object according to the target solder joint distribution; S630: Perform welding interference analysis on the K target solder joints using the target welding control parameters, and output the target welding optimization sequence; S640: According to the target welding optimization sequence and the target welding control parameters, perform the batch welding of the capacitor lead on the welding object.

[0058] Specifically, the target solder joint distribution is extracted from the target object attributes, and the distribution positions of the solder joints are determined by analyzing various characteristics of the target object. The target object attributes include pad material attributes, pad heat resistance range, solder joint size parameters, and target solder joint distribution, etc. Among them, the pad material attributes refer to the type of material used for the pad, such as copper or aluminum, which determines the thermal conductivity and adhesion of the material during the welding process. The pad heat resistance range defines the highest and lowest temperatures that the pad can withstand, directly affecting the temperature control requirements during welding. The solder joint size parameters refer to the size of the solder joint, which is usually related to the welding area and welding strength. The target solder joint distribution refers to the position distribution of the solder joints on the pad. Optimizing the distribution of the solder joints can improve the uniformity and strength of welding.

[0059] Next, K target solder joints are located on the welding object according to the target solder joint distribution, and K positions are determined on the welding object as the targets for actual welding. The positions of the target solder joints are determined according to the predetermined design and distribution rules. K target solder joints, such as 5 out of 10 solder joints, or a part selected from the overall solder joints according to the welding requirements.

[0060] Then, the target welding control parameters are used to perform welding interference analysis on the K target solder joints, and the target welding optimization sequence is output. Welding interference analysis refers to evaluating the possible interference of one solder joint on other solder joints during the welding process. For example, the heat conduction at too close distances may affect the welding cooling process of the solder joints that have been welded. The target welding control parameters refer to the specific operating parameters including welding temperature, pressure, time, etc. By analyzing these parameters, the interference relationship between different solder joints can be determined. For example, the high temperature of a certain solder joint may affect the welding quality of adjacent solder joints. Therefore, the welding optimization sequence is to adjust the welding sequence according to these interference relationships, first welding some solder joints that are not easily interfered, and then welding other solder joints to ensure the quality of each solder joint.

[0061] Next, according to the target welding optimization sequence and the target welding control parameters, batch welding of the capacitor leads is performed on the welding object. Batch welding refers to performing large-scale welding operations on the welding object according to the optimized welding sequence and control parameters. Furthermore, through the pre-set welding parameters and welding sequence, each capacitor lead in the batch production can ensure compliance with the quality standards, avoiding welding failures caused by interference or improper operation.

[0062] Furthermore, step S630 of this application further includes:

[0063] S631: Use the target welding control parameters to evaluate the thermal interference of the K target solder joints, obtaining K target thermal interference ranges; S632: Take the intersection of the thermal interference ranges as the classification condition, and divide the K target solder joints into N groups of target solder joints according to the K target thermal interference ranges; S633: Perform welding displacement analysis on the N groups of target solder joints according to the solder joint positions of the K target solder joints, and output N minimum welding displacement paths; S634: Concatenate the N minimum welding displacement paths to obtain the target welding optimization path; S635: Serialize the K target solder joints according to the target welding optimization path, and output the target welding optimization sequence.

[0064] Specifically, use target welding control parameters such as temperature, time, and pressure to evaluate the thermal interference of the K target solder joints, and analyze the thermal interference received by each solder joint during the welding process. Thermal interference refers to the situation where other solder joints are affected due to temperature changes during the welding process. The thermal interference range of each solder joint represents the range of temperature fluctuations that the area around the solder joint may receive during the welding process. Through evaluation, areas that may have an adverse impact on adjacent solder joints during the welding process can be identified in advance, thus avoiding welding failures caused by thermal interference.

[0065] Next, take the intersection of the thermal interference ranges as the classification condition. Intersection means comparing the thermal interference ranges of multiple solder joints to find solder joints with similar thermal interference effects and dividing them into one group. For example, some solder joints are subject to larger temperature fluctuations, while others are relatively smaller, so their thermal interference ranges are similar, and such solder joints will be grouped together. Divide the K target solder joints into N groups of target solder joints according to the K target thermal interference ranges. The spatial distance between each group of solder joints can ensure that there is no thermal interference characteristic between the solder joints, so that subsequent analysis can be carried out more targeted.

[0066] Then, perform welding displacement analysis on the N groups of target solder joints according to the solder joint positions of the K target solder joints. Welding displacement analysis refers to analyzing the position changes of each solder joint during the welding process, especially the displacement caused by thermal interference. Displacement usually occurs during the welding process due to the expansion or contraction of materials caused by temperature changes, which may cause the solder joints to shift, and output N minimum welding displacement paths. By analyzing the displacement of each group of solder joints, the minimum displacement path of each group of solder joints can be calculated, and the optimal welding path can be determined, reducing errors caused by position changes.

[0067] Next, concatenate the N minimum welding displacement paths to obtain the target welding optimization path. Concatenation means connecting the minimum welding displacement paths of different solder joint groups to form the optimal welding sequence and path, ensuring that each solder joint is welded in the predetermined order and minimizing the impact caused by position changes, thereby improving the welding efficiency and quality.

[0068] Finally, serialize K target solder joints according to the optimized path of the target welding, and output the optimized order of the target welding. Serialization means arranging the solder joints in the order of the optimized path to guide the actual welding operation. By serialization, the execution order of welding is determined, thus avoiding welding quality problems caused by unreasonable paths during the welding process and ensuring that each solder joint is welded in the correct order.

[0069] Furthermore, step S640 of this application further includes:

[0070] S641: Invoke the welding wire according to the target solder type, and install the target welding wire on the automatic wire feeding device of the welding equipment; S642: Extract the target wire feeding speed from the target welding control parameters; S643: During the process of controlling the automatic wire feeding device with the target wire feeding speed, use the optimized order of the target welding as the displacement constraint of the welding equipment, and use the target welding control parameters as the welding constraint of the welding equipment, and perform batch welding of the capacitor leads on the welding object.

[0071] Specifically, invoke the welding wire according to the target solder type to determine the type of welding wire to be used. The welding wire is the material used to fill the welding joint during the welding process, and its type is usually closely related to the solder used. Then, install the target welding wire on the automatic wire feeding device of the welding equipment. The automatic wire feeding device is a component of the welding equipment used to automatically supply the welding wire, and its function is to ensure a stable supply of the welding wire to the welding area during the welding process. Through this operation, the supply of the welding wire during the welding process is automated, reducing manual intervention and improving efficiency and consistency.

[0072] Next, extract the target wire feeding speed from the target welding control parameters. The welding control parameters include welding current, welding voltage, welding speed, etc., and the wire feeding speed is a key parameter for the feeding speed of the welding wire during the welding process. By controlling the parameters, the most suitable wire feeding speed can be determined to ensure the stability and welding quality of the welding process. The wire feeding speed needs to be optimized according to the welding conditions to avoid the influence of too fast or too slow wire feeding speed on the welding quality.

[0073] Then, during the process of controlling the automatic wire feeding device with the target wire feeding speed, the target welding optimization sequence is used as the displacement constraint of the welding equipment. The displacement constraint means that during the welding process, the movement path of the welding equipment needs to be executed according to the optimization sequence to ensure that the welding is carried out along the predetermined route and avoid welding errors caused by unreasonable paths. In addition, the target welding control parameters are used as the welding constraints of the welding equipment, and the movement and welding operations of the welding equipment need to follow these preset control parameters, such as welding current, welding temperature, etc., to ensure the accuracy and stability of the welding process. Under these conditions, the welding equipment can complete the batch welding of capacitor guide pins according to the specified sequence and control parameters.

[0074] In summary, the optimization method for improving the welding strength of capacitor guide pins provided by the present application has the following technical effects: by measuring the target guide pin attributes of the capacitor guide pins, where the target guide pin attributes include target material characteristics and target geometric characteristics; after locally calling the target object attributes of the welding object, solder control analysis is performed according to the target object attributes and target guide pin attributes to obtain solder correlation information, where the solder correlation information includes the welding feed speed range and the target solder type; initial welding parameter setting is performed according to the target guide pin attributes and target object attributes to obtain the initial welding parameters; the welding strength optimization space is initialized based on the initial welding parameters and the welding feed speed range; welding control small batch verification optimization is performed in the welding strength optimization space to output the target welding control parameters; according to the target welding control parameters, the welding operation of the capacitor guide pins is performed on the welding object, that is, by achieving the technical goal of automated and precise welding control, the technical effects of improving the stability of welding quality and optimizing production efficiency are achieved.

[0075] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0076] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application also intends to include these changes and variations.

Claims

1. An optimized method for improving the welding strength of capacitor guide pins, characterized in that, Including: Measuring the target pin attributes of the capacitor pins, where the target pin attributes include target material characteristics and target geometric characteristics; After locally invoking the target object attributes of the welding object, performing solder control analysis based on the target object attributes and the target pin attributes to obtain solder-related information, where the solder-related information includes a welding feed speed range and a target solder type; Performing initialization setting of welding parameters according to the target pin attributes and the target object attributes to obtain initial welding parameters; Initializing the welding strength optimization space based on the initial welding parameters and the welding feed speed range; Performing small-batch verification optimization of welding control in the welding strength optimization space and outputting target welding control parameters; Performing the welding operation of the capacitor pins on the welding object according to the target welding control parameters; Performing the welding operation of the capacitor pins on the welding object according to the target welding control parameters, including: Extracting the target solder joint distribution from the target object attributes, where the target object attributes include pad material attributes, pad heat resistance range, solder joint size parameters, and the target solder joint distribution; Locating K target solder joints on the welding object according to the target solder joint distribution; Performing welding interference analysis on the K target solder joints using the target welding control parameters and outputting a target welding optimization sequence; Performing batch welding of the capacitor pins on the welding object according to the target welding optimization sequence and the target welding control parameters; Performing batch welding of the capacitor pins on the welding object according to the target welding optimization sequence and the target welding control parameters, including: Invoking the welding wire according to the target solder type and installing the target welding wire on the automatic wire feeding device of the welding equipment; Extracting the target wire feeding speed from the target welding control parameters; During the process of controlling the automatic wire feeding device using the target wire feeding speed, using the target welding optimization sequence as the displacement constraint of the welding equipment and the target welding control parameters as the welding constraint of the welding equipment to perform batch welding of the capacitor pins on the welding object.

2. The optimized method for improving the welding strength of capacitor guide pins according to claim 1, characterized in that, Performing welding interference analysis on the K target solder joints using the target welding control parameters and outputting a target welding optimization sequence, including: Performing thermal interference evaluation on the K target solder joints using the target welding control parameters to obtain K target thermal interference ranges; Taking the intersection of the thermal interference ranges as the classification condition and dividing the K target solder joints into N groups of target solder joints according to the K target thermal interference ranges; Performing welding displacement analysis on the N groups of target solder joints according to the K solder joint positions of the K target solder joints and outputting N minimum welding displacement paths; Splicing the N minimum welding displacement paths to obtain a target welding optimization path; Serializing the K target solder joints according to the target welding optimization path and outputting the target welding optimization sequence.

3. The optimized method for improving the welding strength of capacitor guide pins according to claim 1, characterized in that Performing solder control analysis according to the target object attributes and the target pin attributes to obtain solder-related information, where the solder-related information includes a welding feed speed range and a target solder type, including: Perform solder feeding control analysis based on the solder joint size parameters and target geometric characteristics to obtain the welding feeding speed range; Perform solder compatibility analysis based on the pad material properties and target material characteristics to obtain the target solder type; Associate and store the welding feeding speed range and the target solder type to obtain the solder association information.

4. The optimized method for improving the welding strength of capacitor guide pins according to claim 3, characterized in that Perform solder compatibility analysis based on the pad material properties and target material characteristics to obtain the target solder type, including: Extract the target material properties and target heat resistance range from the target material characteristics; Use the pad material properties and target material properties to traverse the solder adaptation information library respectively to obtain the first set of adapted solders and the second set of adapted solders; Solve the intersection of the first set of adapted solders and the second set of adapted solders to obtain the compatible adapted solder set, where multiple compatible adapted solders in the compatible adapted solder set have multiple sample material melting point range identifiers; Solve the intersection of the target heat resistance range and the pad heat resistance range to obtain the compatible heat resistance range, and then use the compatible heat resistance range to traverse the multiple sample material melting point ranges to screen and obtain M compatible adapted solders from the compatible adapted solder set; Apply the M compatible adapted solders to conduct a small batch test of lead pin welding to obtain M solder spreading percentages and M intermetallic compound percentages; Preset the spreading influence weight and the intermetallic compound influence weight, and use the spreading influence weight and the intermetallic compound influence weight to evaluate the M solder spreading percentages and M intermetallic compound percentages to obtain M compatible adaptation coefficients; Extract the target solder type from the M compatible adapted solders by serializing the M compatible adaptation coefficients, where the target solder type has an atmosphere sensitivity identifier.

5. The optimization method for improving the welding strength of capacitor guide pins as described in claim 4, characterized in that, Perform initialization setting of welding parameters according to the target lead pin attributes and target object attributes to obtain the initial welding parameters, including: Extract the target thermal conductivity from the target material characteristics; Use the target thermal conductivity, solder joint size parameters and target solder type as search conditions for local search to obtain multiple historical welding times; Perform discrete analysis on the multiple historical welding times and output the welding time range; Interactively obtain the solder heat resistance range of the target solder type, and obtain the welding temperature range by solving the intersection of the solder heat resistance range and the compatible heat resistance range; Obtain the lead pin pressure tolerance range by analyzing the target geometric characteristics; Interactively obtain the equipment capacity range of the welding equipment, and obtain the welding pressure range by solving the intersection of the lead pin pressure tolerance range and the equipment capacity range; Extract the welding atmosphere type and atmosphere flow rate range from the atmosphere sensitivity identifier; Integrate the welding time range, welding temperature range, welding pressure range, welding atmosphere type and atmosphere flow rate range, and output the initial welding parameters.

6. An optimization method for improving the welding strength of capacitor leads as described in claim 5, characterized in that, Conduct small batch verification and optimization of welding control in the welding strength optimization space, and output the target welding control parameters, including: Construct the welding strength optimization space based on the welding time range, welding temperature range, welding pressure range, atmosphere flow rate range and welding feeding speed range; After locating H initial welding particle points in the welding strength optimization space, extract the H sample welding control parameters of the H initial welding particle points for small-batch welding tests to obtain H initial strength index sets, where the initial strength index sets include initial drawing strength, initial shear strength, initial peeling strength, initial thermal cycle strength, and initial fatigue strength; Conduct welding fitness evaluation based on the H initial strength index sets and output H initial welding fitness values; Conduct an optimization trend analysis on the H initial welding particle points according to the H initial welding fitness values to obtain a welding parameter adjustment direction vector; Serialize the H initial welding fitness values and locate the optimized starting particle point among the H initial welding particle points according to the fitness extreme value; Pre-define the welding index adjustment step size; Use the welding parameter adjustment direction vector as the particle movement direction constraint and the welding index adjustment step size as the particle movement distance constraint to conduct small-batch verification optimization of welding control in the welding strength optimization space until the welding fitness fluctuates stably, and output the target welding control parameters.

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