Optimization method for improving welding strength of capacitor guide pin

Abstract

The invention provides an optimization method for improving the welding strength of a capacitor guide pin, and relates to the technical field of capacitors, and the optimization method comprises the steps: measuring the target guide pin attribute of the capacitor guide pin; after the target object attribute of the welding object is called locally, welding flux control analysis is conducted according to the target object attribute and the target guide pin attribute, and welding flux associated information is obtained; welding parameter initialization setting is conducted according to the target guide pin attribute and the target object attribute, and initial welding parameters are obtained; a welding strength optimization space is initialized based on the initial welding parameters and the welding feeding speed interval; welding control small-batch verification optimization is conducted in the welding strength optimization space, and target welding control parameters are output; and according to the target welding control parameters, welding operation of the capacitor guide pin is executed on the welding object. 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 welding quality stability and optimizing the production efficiency are achieved.

Description

Technical Field

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

[0002] In the modern electronic manufacturing industry, the welding quality of capacitor guide pins directly affects the performance and reliability of the capacitor, especially in demanding application scenarios such as high frequency and high voltage, the accuracy and strength of welding become particularly important.

[0003] At present, the prior art usually relies on manually set control indicators, such as welding time, temperature, pressure and other welding control parameters, in the parameter adjustment process of guide pin welding. Although these parameters can affect the welding quality to a certain extent, due to the different welding objects, the uncertainty and complexity of welding conditions, it is often necessary to rely on a large number of trial and error experiments to gradually adjust the control parameters. However, this method of relying on manual experience and trial and error is not only inefficient, but may also lead to increased production costs and unnecessary waste of resources. In addition, the prior art does not fully consider the relationship between the guide pin properties and the welding strength requirements during the welding process, and is not able to systematically optimize these welding control parameters through precise mathematical models. Therefore, the prior art lacks an accurate and efficient welding control optimization method, and cannot ensure the efficiency and consistency of the production process while meeting the welding strength requirements.

[0004] In summary, there are technical problems in the prior art due to the fact that the adjustment of welding control parameters relies on manual experience and does not fully consider the relationship between the guide pin properties and the welding strength requirements, resulting in unstable welding quality and low production efficiency, which further affects the reliability and consistency of guide pin welding. Summary of the invention

[0005] The purpose of this application is to provide an optimization method for improving the welding strength of capacitor guide pins, so as to solve the technical problem in the prior art that the welding control parameter adjustment relies on manual experience and does not fully consider the relationship between the guide pin properties and the welding strength requirements, resulting in unstable welding quality and low production efficiency, which further affects the reliability and consistency of guide pin welding.

[0006] In view of the above problems, the present application provides an optimization method for improving the welding strength of capacitor guide pins, comprising: determining the target guide pin attributes of the capacitor guide pin, wherein the target guide pin attributes include target material properties and target geometric properties; 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-related information, wherein the solder-related information includes a welding feed speed range and a target solder type; performing welding parameter initialization settings according to the target guide pin attributes and the target object attributes to obtain initial welding parameters; initializing a welding strength optimization space based on the initial welding parameters and the welding feed speed range; performing welding control small batch verification optimization in the welding strength optimization space to output target welding control parameters; and performing a welding operation of the capacitor guide pin 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 guide needle attributes of the capacitor guide needle, wherein the target guide needle attributes include target material properties and target geometric properties; after locally calling the target object attributes of the welding object, solder control analysis is performed according to the target object attributes and the target guide needle attributes to obtain solder association information, wherein the solder association information includes a welding feed speed range and a target solder type; welding parameters are initialized and set according to the target guide needle attributes and the target object attributes to obtain initial welding parameters; 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, and target welding control parameters are output; according to the target welding control parameters, the welding operation of the capacitor guide needle is performed on the welding object, that is, by realizing the technical goal of automated and precise welding control, the technical effect of improving welding quality stability and optimizing production efficiency is achieved.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0010] Figure 1 A schematic flow chart of an optimization method for improving the welding strength of capacitor guide pins in this application; Figure 2 A schematic diagram of a flow chart of a welding operation of a capacitor guide pin in an optimization method for improving the welding strength of a capacitor guide pin of the present application. DETAILED DESCRIPTION

[0011] This application provides an optimization method for improving the welding strength of capacitor guide pins, which solves the technical problem in the prior art that the welding control parameter adjustment relies on manual experience and does not fully consider the relationship between the guide pin properties and the welding strength requirements, resulting in unstable welding quality and low production efficiency, which further affects the reliability and consistency of guide pin welding. The technical goal of achieving automated and precise welding control is achieved, and the technical effect of improving welding quality stability and optimizing production efficiency is achieved.

[0012] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0013] Please see attached Figure 1 The present application provides an optimization method for improving the welding strength of capacitor guide pins, which specifically includes the following steps: S100: Determine target guide needle properties of a capacitor guide needle, wherein the target guide needle properties include target material properties and target geometric properties.

[0014] Specifically, the capacitor pin is the pin for which welding strength optimization is to be performed. The target pin properties of the capacitor pin are determined. The target pin properties include target material properties and target geometric properties. The target material properties refer to the material properties of the capacitor pin, such as electrical conductivity, high temperature resistance or corrosion resistance, which are used to directly affect the heat conduction and welding strength during welding. For example, if the pin is made of copper, it may be easier to conduct heat during welding, thereby affecting the welding temperature and solder joint quality. Among them, for the target material properties, the physical and chemical properties of the pin can be measured by experimental methods. For example, the tensile strength of the pin material can be measured by a tensile test, or its stability at high temperature can be determined by thermal analysis (such as thermogravimetric analysis) to evaluate its thermal conductivity; for electrical conductivity, the four-probe method is usually used to measure resistivity. These methods can quantify the material properties of the pin, such as electrical conductivity, melting point and high temperature resistance. The target geometric properties refer to the shape, size and surface state of the pin, such as the diameter, length and surface finish of the pin, which are used to affect the contact area and heat concentration during welding. By considering these two properties, the optimization method can more accurately adjust the welding parameters to achieve the desired welding strength. Among them, the surface roughness or morphology of the guide pin can be observed using an optical microscope or a scanning electron microscope (SEM). In addition, a laser rangefinder or a 3D laser scanner can be used to measure the precise size and geometry of the guide pin, including length, diameter, and its varying shape parameters.

[0015] S200: After locally calling the target object attributes of the welding object, solder control analysis is performed according to the target object attributes and the target guide needle attributes to obtain solder associated information, wherein the solder associated information includes a welding feed speed range and a target solder type.

[0016] Furthermore, step S200 of the present application also includes: S210: Perform solder feed control analysis based on the solder spot size parameters and target geometric characteristics to obtain a solder feed speed range; S220: Perform solder compatibility analysis based on the pad material properties and target material characteristics to obtain a target solder type; S230: Associate and store the solder feed speed range and target solder type to obtain the solder association information.

[0017] Specifically, the welding object refers to the welding object that welds the guide pin of the capacitor to the external circuit (such as a circuit board or other electrical connection parts). After calling the target object properties of the welding object locally, the solder joint size parameter refers to the size of the welding area in the target object properties, such as the diameter and depth of the solder joint. The target geometric properties refer to the shape, size and surface state of the guide pin. According to the solder joint size parameters and target geometric properties, the solder feeding control analysis is performed to determine the feeding speed during the welding process to ensure that the solder can fill the solder joint in an appropriate amount, 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, the solder supply speed range is set to twenty millimeters per second, thereby avoiding excessive solder causing solder joint overflow, or too little solder causing the solder joint to be weak.

[0018] Next, the pad material properties refer to the properties of the pad material during the soldering process, such as its thermal conductivity, corrosion resistance, etc. These properties will affect the flow and adhesion of the solder during the soldering process. The target material properties refer to the physical and chemical properties of the guide pin material, which determine the selected solder to ensure the soldering quality. For example, if the guide pin is made of copper, a solder containing silver may be selected because silver has better conductivity and welding strength. Based on these material properties, a solder compatibility analysis can be performed to obtain the target solder type and determine the most suitable solder type, thereby avoiding weak soldering or solder joint defects caused by incompatible solder.

[0019] Finally, the welding feed speed range and the target solder type are associated and stored for subsequent use. In different welding processes, the most suitable solder type and feed speed can be automatically selected according to different welding requirements, effectively improving the automation and intelligence of the welding process.

[0020] Furthermore, step S220 of the present application also includes: S221: extracting target material properties and target heat resistance range from the target material characteristics; S222: using the pad material properties and target material properties to traverse the solder adaptation information library respectively to obtain a first adaptation solder set and a second adaptation solder set; S223: performing intersection solving on the first adaptation solder set and the second adaptation solder set to obtain a compatible adaptation solder set, wherein a plurality of compatible adaptation solders in the compatible adaptation solder set have a plurality of sample material melting point range identifiers; S224: performing intersection solving on the target heat resistance range and the pad heat resistance range to obtain a compatible heat resistance range, and using the compatible heat resistance range to traverse the plurality of sample material melting point ranges; S225: Apply the M compatible adaptive solders to conduct small batch test of guide pin welding to obtain M solder spreading percentages and M intermetallic compound percentages; S226: Preset spreading influence weights and intermetallic compound influence weights, and use the spreading influence weights and intermetallic compound influence weights to evaluate the M solder spreading percentages and M intermetallic compound percentages to obtain M compatible adaptation coefficients; S227: Extract the target solder type from the M compatible adaptive solders by serializing the M compatible adaptation coefficients, wherein the target solder type has an atmosphere sensitive identification.

[0021] Specifically, the target material properties and target heat resistance range are obtained from the target material characteristics extraction. 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, must also be determined. For example, the heat resistance range of a copper guide pin may be 400 degrees Celsius to 500 degrees Celsius, which is used to select the appropriate solder later.

[0022] Then, each information in the solder adaptation information library is accessed in turn, and the pad material attribute and the target material attribute are used to search in the solder adaptation information library to obtain the first adaptation solder set and the second adaptation solder set. The first adaptation solder set is the solder selected according to the pad material attribute, and the second adaptation solder set is the solder selected according to the target material attribute.

[0023] Next, the intersection of the first and second compatible solder sets is solved, and all solders that meet the requirements are found from the two compatible solder sets to obtain a compatible compatible solder set. The solders in the compatible compatible solder set not only meet the requirements of the pad, but are also compatible with the material properties of the target guide pin. The solders in the compatible compatible 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, such as the solder may have a melting point range of 200 degrees Celsius to 300 degrees Celsius.

[0024] Then, the target heat resistance range and the pad heat resistance range are solved for intersection, and the intersection is found to obtain the compatible heat resistance range. Each melting point in the melting point range of multiple sample materials is accessed in turn, and the compatible heat resistance range is retrieved, so as to screen out solders within the compatible heat resistance range from the compatible and adapted solder set, so that these solders can withstand higher operating temperatures without performance degradation, and M types of compatible and adapted solders are obtained. Where M is an integer greater than 0.

[0025] Next, the selected M compatible solders are used for small batch testing of guide pin welding to obtain the solder spreading percentage and intermetallic compound percentage. Small batch testing is to test different solders under actual welding conditions in order to evaluate their performance. Through the test, the spreading percentage (the degree of distribution of the solder during the welding 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 guide pin metal during the welding process) of each solder can be obtained, which helps to select the best solder.

[0026] Then, the spreading influence weight and intermetallic compound influence weight are preset, which are used to measure the spreading degree of solder and the influence of the formation of intermetallic compounds during the welding process. The spreading influence weight and intermetallic compound influence weight are used to evaluate M solder spreading percentages and M intermetallic compound percentages. For example, solder with good spreading may have a higher weight, while too much intermetallic compound may cause unstable solder joints, so they are weighted and evaluated to obtain M compatible adaptation coefficients.

[0027] Finally, by serializing the M compatible adaptation coefficients, serialization means sorting each solder according to its compatible adaptation coefficient to find the most suitable solder type. The target solder type is extracted from the M compatible and adapted solders. The target solder type has an atmosphere sensitive mark, indicating the sensitivity to the ambient atmosphere (such as oxygen, humidity, etc.), which may affect the stability and final quality of the welding process.

[0028] S300: Initialize and set welding parameters according to the target guide needle attributes and the target object attributes to obtain initial welding parameters.

[0029] Furthermore, step S300 of the present application also includes: S310: extract and obtain the target thermal conductivity from the target material characteristics; S320: perform local search using the target thermal conductivity, solder joint size parameters and target solder type as search conditions to obtain multiple historical welding times; S330: perform discrete analysis on the multiple historical welding times and output welding time intervals; S340: interactively obtain the solder heat resistance range of the target solder type, and obtain the welding temperature range by performing intersection solution on the solder heat resistance range and the compatible heat resistance range; S350: obtain the guide needle pressure tolerance range by analyzing the target geometric characteristics; S360: interactively obtain the equipment capability range of the welding equipment, and obtain the welding pressure range by performing intersection solution on the guide needle pressure tolerance range and the equipment capability range; S370: extract and obtain the welding atmosphere type and atmosphere flow rate range from the atmosphere sensitive identifier; S380: 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.

[0030] Specifically, the target thermal conductivity, i.e., thermal conductivity, is extracted from the physical properties of the target material properties. Thermal conductivity is an indicator of the thermal conductivity of a material. The higher the thermal conductivity, the stronger the material's ability to transfer heat. For example, copper has a higher thermal conductivity than aluminum. Therefore, understanding the thermal conductivity of the target guide pin material helps control the distribution of heat during welding and avoid damage to the guide pin caused by excessively high temperatures.

[0031] Next, by using 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, the historical welding records are searched and compared to obtain multiple completed welding times. These historical data can be used to infer and optimize the possible time range during the welding process. For example, for larger solder joints and materials with higher thermal conductivity, historical records show that the welding time may be between five and ten seconds.

[0032] Next, the historical welding time is discretely analyzed. Discrete analysis refers to analyzing the historical welding time data, finding the distribution pattern of the data, and then deriving 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 too long or too short welding time affecting the welding quality.

[0033] Then, the solder heat resistance range of the target solder type is obtained interactively. The solder heat resistance range refers to the highest and lowest temperature range that the solder can withstand during the welding process. The compatible heat resistance range is the temperature range that matches the heat resistance characteristics of the guide pin and the pad. By solving the intersection of the solder heat resistance range and the compatible heat resistance range, the most suitable welding temperature range 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.

[0034] According to the shape and size of the guide pin, the pressure range it can withstand during welding is calculated to obtain the guide pin pressure tolerance range. Geometric characteristics include the diameter, length, surface roughness, etc. of the guide pin, which will affect the pressure tolerance of the guide pin. For example, a thin and long guide pin may withstand a smaller pressure range, while a thick and short guide pin can withstand a larger pressure.

[0035] Next, the equipment capability range of the welding equipment is interactively obtained. The capability range of the welding equipment refers to the maximum and minimum pressure range that the welding equipment can provide. By performing an intersection analysis on the pressure tolerance range of the guide pin and the pressure capability range of the welding equipment, a suitable welding pressure range can be determined.

[0036] Then, the welding atmosphere type and atmosphere flow rate range are extracted from the atmosphere sensitive identifier. The atmosphere sensitive identifier refers to the sensitivity of the selected solder to atmosphere changes during the welding process. The atmosphere type refers to the type of ambient gas used in the welding process, such as nitrogen, argon, etc. The atmosphere flow rate range is the speed range of the gas flow during the welding process, which will affect the diffusion of the solder and the cleanliness of the metal surface.

[0037] Finally, the welding time interval, welding temperature interval, welding pressure interval, welding atmosphere type and atmosphere flow rate interval are integrated to output the initial welding parameters, which are the basic basis for welding operations.

[0038] S400: Initializing a welding strength optimization space based on the initial welding parameters and welding feed speed interval.

[0039] Specifically, the welding strength optimization space is initialized based on the initial welding parameters and the welding feed speed interval. The initial welding parameters serve as the basic reference point of the welding process, ensuring that the welding operation can be carried out under appropriate conditions. Next, the welding feed speed interval refers to the speed range of applying solder during the welding process. The solder feed speed has an important influence on the welding quality. Too fast a feed speed may lead to incomplete welding, while too slow a feed speed may affect production efficiency. By combining the initial welding parameters and the welding feed speed interval, the welding strength optimization space can be initialized to search for the best welding strength within different ranges. During the welding process, by continuously adjusting and optimizing the parameters, the parameter combination that can best guarantee the welding strength is found, thereby ensuring the welding quality and stability, and avoiding the welding strength that does not meet the requirements due to improper parameter settings.

[0040] S500: Perform small batch verification and optimization of welding control in the welding strength optimization space, and output target welding control parameters.

[0041] Furthermore, step S500 of the present application also includes: S510: construct the welding strength optimization space based on the welding time interval, welding temperature interval, welding pressure interval, atmosphere flow rate interval and welding feed rate interval; S520: after locating H initial welding particle points in the welding strength optimization space, extract H sample welding control parameters of the H initial welding particle points to perform small batch welding tests, and obtain H initial strength index sets, wherein the initial strength index set includes initial pull-out strength, initial shear strength, initial peel strength, initial thermal cycle strength and initial fatigue strength; S530: perform welding fitness evaluation based on the H initial strength index sets, and output H initial welding Fitness; S540: Analyze the optimization trend of the H initial welding particle points according to the H initial welding fitnesses to obtain the welding parameter adjustment direction vector; S550: Serialize the H initial welding fitnesses, and locate the optimization starting point particle point among the H initial welding particle points according to the fitness extreme value; S560: Predefine the welding index adjustment step; S570: Use the welding parameter adjustment direction vector as a particle movement direction constraint, use the welding index adjustment step as a particle movement distance constraint, and perform small batch verification and optimization of welding control in the welding strength optimization space until the welding fitness fluctuates stably, and output the target welding control parameters.

[0042] Specifically, the welding strength optimization space is constructed based on the welding time interval, welding temperature interval, welding pressure interval, atmosphere flow rate interval and welding feed rate interval. The interval of each parameter represents the possible range of variation of the parameter in the actual welding process. By combining the intervals, the welding strength optimization space is constructed, in which various parameters are adjusted to achieve the best welding strength.

[0043] Then, after locating H initial welding particle points in the welding strength optimization space, the welding control parameters of these particle points are extracted and small-batch welding tests are performed. The initial welding particle points represent possible welding parameter combinations and are multiple points randomly selected from the constructed welding strength optimization space. Each point represents a set of specific welding parameters, such as a specific time, temperature, pressure, etc. After small-batch welding tests are performed at these initial particle point locations, H initial strength index sets are obtained, including initial pull-out strength, shear strength, peel strength, thermal cycle strength, and fatigue strength, which help evaluate the strength characteristics of the weld.

[0044] Next, the welding fitness evaluation is performed based on the initial strength index set. The welding fitness evaluation is a quantitative score of the welding quality. By analyzing the initial strength indicators (such as pull-out strength, shear strength, etc.), it is judged whether the welding point meets the quality requirements and H initial welding fitness is output. The particle points with high fitness correspond to the parameter combination that can achieve the expected welding strength.

[0045] Then, the optimization trend analysis of the initial welding particle points is performed according to the initial welding fitness. The optimization trend analysis refers to analyzing the fitness of each particle point to determine which direction of adjustment may bring better welding strength, and then obtain the welding parameter adjustment direction vector. For example, if the welding strength of some particle points is better, it may mean that they are better than other points in the setting of certain parameters, thus determining the adjustment direction.

[0046] Next, the initial welding fitness is serialized, and all fitness values ​​are arranged in order from high to low. The best particle point is selected as the starting point of optimization, which serves as the basis for the next step of optimization to ensure that the final selected welding parameters can meet the highest strength requirements.

[0047] Then, the welding index adjustment step is predefined, which indicates the amount of change each time the welding parameters are adjusted during the welding process. For example, the welding time may be increased by one second each time, and the welding temperature may be increased by 50 degrees Celsius. The smaller the step size is set, the higher the accuracy of the optimization process, but more iterations may be required.

[0048] Next, by simulating the movement of particles in the welding strength optimization space, the direction vector and step size are used to control the movement of particles, gradually approaching the optimal welding parameters. The welding parameter adjustment direction vector is used as the particle movement direction constraint, and the welding index adjustment step size is used as the particle movement distance constraint. Small batch verification and optimization of welding control are carried out until the welding fitness fluctuates stably. Small batch verification verifies the welding effect through multiple small-scale tests until the fitness is stable, indicating that the optimal welding parameters have been found. Finally, the target welding control parameters are output, which represent the optimized welding settings, which can provide the best welding strength and meet production requirements.

[0049] S600: Performing a welding operation of the capacitor guide pin on the welding object according to the target welding control parameter.

[0050] Further, if Figure 2 As shown, step S600 of the present application also includes: S610: extracting a target solder point distribution from the target object attributes, wherein the target object attributes include pad material attributes, pad heat resistance range, solder point size parameters and the target solder point distribution; S620: locating K target solder points on the welding object according to the target solder point distribution; S630: performing welding interference analysis on the K target solder points using the target welding control parameters, and outputting a target welding optimization sequence; S640: performing batch welding of the capacitor guide pins on the welding object according to the target welding optimization sequence and the target welding control parameters.

[0051] Specifically, the target solder joint distribution is extracted from the target object attributes, and the distribution position of the solder joints is 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, among which the pad material attribute refers 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 maximum and minimum temperatures that the pad can withstand, which directly affects the temperature control requirements during welding. The solder joint size parameter refers 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 solder joints can improve the uniformity and strength of welding.

[0052] Next, K target welds are located on the welding object according to the distribution of the target welds, and K positions are determined on the welding object as the targets of the actual welding. The positions of the target welds are determined according to the predetermined design and distribution rules, and the K target welds are, for example, 5 of the 10 welds, or a portion selected from the overall welds according to the welding requirements.

[0053] 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 the evaluation of the possible interference that one solder joint may cause to other solder joints during the welding process. For example, heat conduction at a too close distance may affect the welding cooling process of the solder joints that have been welded. The target welding control parameters refer to 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 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 weld some solder joints that are not easily interfered with, and then weld other solder joints to ensure the quality of each solder joint.

[0054] Next, batch welding of capacitor guide pins is performed on the welding object according to the target welding optimization sequence and target welding control parameters. Batch welding refers to large-scale welding operations on the welding object according to the optimized welding sequence and control parameters. Then, through the pre-set welding parameters and welding sequence, each capacitor guide pin in batch production can be ensured to meet the quality standards and avoid welding failures caused by interference or improper operation.

[0055] Furthermore, step S630 of the present application also includes: S631: Use the target welding control parameters to perform thermal interference evaluation on the K target welds to obtain K target thermal interference ranges; S632: Use the intersection of thermal interference ranges as a classification condition, and divide the K target welds into N groups of target welds according to the K target thermal interference ranges; S633: Perform welding displacement analysis on the N groups of target welds according to the K weld point positions of the K target welds, and output N minimum welding displacement paths; S634: Splice the N minimum welding displacement paths to obtain a target welding optimization path; S635: Serialize the K target welds according to the target welding optimization path, and output the target welding optimization sequence.

[0056] Specifically, the target welding control parameters such as temperature, time and pressure are used to evaluate the thermal interference of K target solder joints, and the thermal interference of each solder joint during the welding process is analyzed. Thermal interference refers to the situation where the temperature change during the welding process affects other solder joints. The thermal interference range of each solder joint indicates the range of temperature fluctuations that the area around the solder joint may be subject to during the welding process. Through the evaluation, areas that may have adverse effects on adjacent solder joints during the welding process can be identified in advance, thereby avoiding welding failures caused by thermal interference.

[0057] Next, the crossover of thermal interference ranges is used as a classification condition. Crossover refers to comparing the thermal interference ranges of multiple solder joints, finding solder joints with similar thermal interference effects, and grouping them together. For example, some solder joints are subject to large temperature fluctuations, while others are relatively small, so their thermal interference ranges are similar and such solder joints will be grouped together. K target solder joints are divided into N groups of target solder joints based on 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 more targeted.

[0058] Then, the welding displacement analysis is performed on the N groups of target welding points according to the welding point positions of the K target welding points. The welding displacement analysis refers to the analysis of the position changes of each welding point during the welding process, especially the displacement caused by thermal interference. Displacement usually occurs during the welding process due to material expansion or contraction caused by temperature changes, which may cause the welding point to shift, and output N minimum welding displacement paths. By analyzing the displacement of each group of welding points, the minimum displacement path of each group of welding points can be calculated, and the optimal welding path can be determined to reduce the error caused by position changes.

[0059] Next, splice N minimum welding displacement paths to obtain the target welding optimization path. Splicing means connecting the minimum welding displacement paths of different welding point groups to form the optimal welding sequence and path, ensuring that each welding point is welded in the predetermined order and minimizing the impact of position changes, thereby improving welding efficiency and quality.

[0060] Finally, K target welds are serialized according to the target welding optimization path, and the target welding optimization sequence is output. Serialization refers to arranging the welds in the order of the optimized path to guide the actual welding operation. Through serialization, the execution order of welding is determined, thereby avoiding welding quality problems caused by unreasonable paths during the welding process and ensuring that each weld is welded in the correct order.

[0061] Furthermore, step S640 of the present application also includes: S641: Call the welding wire according to the target solder type, and install the target welding wire in the automatic wire feeding device of the welding equipment; S642: Extract the target wire feeding speed from the target welding control parameters; S643: In the process of controlling the automatic wire feeding device with the target wire feeding speed, use the target welding optimization sequence as the displacement constraint of the welding equipment, use the target welding control parameters as the welding constraints of the welding equipment, and perform batch welding of the capacitor guide pins on the welding object.

[0062] Specifically, the welding wire is called 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 weld joint during the welding process, and its type is usually closely related to the solder used. Then, the target welding wire is installed on the automatic wire feeder of the welding equipment. The automatic wire feeder is a component in the welding equipment used to automatically supply welding wire. Its function is to ensure that the welding wire is stably supplied to the welding area during the welding process. Through this operation, the supply of welding wire in the welding process is automated, reducing manual intervention and improving efficiency and consistency.

[0063] Next, the target wire feeding speed is extracted from the target welding control parameters. Welding control parameters include welding current, welding voltage, welding speed, etc., and wire feeding speed is the key parameter for the wire feeding speed during welding. By controlling the parameters, the most suitable wire feeding speed can be determined to ensure the stability of the welding process and the welding quality. The wire feeding speed needs to be optimized according to the welding conditions to avoid too fast or too slow wire feeding speed affecting the welding quality.

[0064] Then, in 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 moving path of the welding equipment needs to be executed in the optimized sequence to ensure that the welding is carried out according to 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. The movement and welding operation 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 in accordance with the prescribed sequence and control parameters.

[0065] 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 determining the target guide pin attributes of the capacitor guide pin, wherein the target guide pin attributes include target material properties and target geometric properties; after locally calling the target object attributes of the welding object, solder control analysis is performed according to the target object attributes and the target guide pin attributes to obtain solder association information, wherein the solder association information includes a welding feed speed range and a target solder type; welding parameters are initialized and set according to the target guide pin attributes and the target object attributes to obtain initial welding parameters; 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, and target welding control parameters are output; according to the target welding control parameters, the welding operation of the capacitor guide pin is performed on the welding object, that is, by realizing the technical goal of automated and precise welding control, the technical effect of improving welding quality stability and optimizing production efficiency is achieved.

[0066] 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 may 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 the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0067] 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 belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. An optimization method for improving the welding strength of capacitor guide pins, characterized in that: include: Determining target guide needle properties of the capacitor guide needle, wherein the target guide needle properties include target material properties and target geometric properties; After the target object attribute of the welding object is locally called, solder control analysis is performed according to the target object attribute and the target guide pin attribute to obtain solder associated information, wherein the solder associated information includes a welding feed speed interval and a target solder type; Initialize and set welding parameters according to the target guide needle attributes and the target object attributes to obtain initial welding parameters; Initializing the welding strength optimization space based on the initial welding parameters and welding feed speed interval; Perform small batch verification and optimization of welding control in the welding strength optimization space, and output target welding control parameters; A welding operation of the capacitor guide pin is performed on the welding object according to the target welding control parameter.

2. An optimization method for improving the welding strength of capacitor guide pins according to claim 1, characterized in that: According to the target welding control parameter, performing a welding operation of the capacitor guide pin on the welding object includes: Extracting a target solder point distribution from the target object attributes, wherein the target object attributes include pad material attributes, pad heat resistance range, solder point size parameters, and the target solder point distribution; Positioning K target welding spots on the welding object according to the target welding spot distribution; Using the target welding control parameters to perform welding interference analysis on the K target welding points, and outputting a target welding optimization sequence; The batch welding of the capacitor guide pins is performed on the welding object according to the target welding optimization sequence and the target welding control parameters.

3. An optimization method for improving the welding strength of capacitor guide pins according to claim 2, characterized in that: According to the target welding optimization sequence and the target welding control parameters, batch welding of the capacitor guide pins is performed on the welding object, including: Calling welding wire according to the target welding material type, and installing the target welding wire on an automatic wire feeding device of a welding device; extracting a target wire feeding speed from the target welding control parameters; In the process of controlling the automatic wire feeding device by using the target wire feeding speed, the target welding optimization sequence is used as the displacement constraint of the welding equipment, the target welding control parameter is used as the welding constraint of the welding equipment, and batch welding of the capacitor guide pins is performed on the welding object.

4. The optimization method for improving the welding strength of capacitor guide pins according to claim 2, characterized in that: The target welding control parameters are used to perform welding interference analysis on the K target welding points, and a target welding optimization sequence is output, including: Using the target welding control parameters to perform thermal interference evaluation on the K target welding points to obtain K target thermal interference ranges; Taking the intersection of thermal interference ranges as a classification condition, dividing the K target solder joints into N groups of target solder joints according to the K target thermal interference ranges; Perform welding displacement analysis on the N groups of target welding points according to the K welding point positions of the K target welding points, and output N minimum welding displacement paths; Connect the N minimum welding displacement paths to obtain a target welding optimization path; The K target welding points are serialized according to the target welding optimization path, and the target welding optimization sequence is output.

5. The optimization method for improving the welding strength of capacitor guide pins according to claim 3, characterized in that: Solder control analysis is performed according to the target object attributes and the target guide pin attributes to obtain solder associated information, wherein the solder associated information includes a welding feed speed interval and a target solder type, including: Perform solder feed control analysis according to the solder spot size parameters and target geometric characteristics to obtain a solder feed speed range; Perform solder compatibility analysis based on the pad material properties and target material characteristics to obtain a target solder type; The welding feed speed interval and the target solder type are stored in association to obtain the solder association information.

6. An optimization method for improving the welding strength of capacitor guide pins according to claim 5, characterized in that: Solder compatibility analysis is performed based on the pad material properties and target material characteristics to obtain a target solder type, including: Extracting target material properties and target heat resistance range from the target material characteristics; Using the pad material attribute and the target material attribute to traverse the solder matching information library respectively, to obtain a first matching solder set and a second matching solder set; Solving the intersection of the first compatible solder set and the second compatible solder set to obtain a compatible compatible solder set, wherein a plurality of compatible compatible solders in the compatible compatible solder set have a plurality of sample material melting point range identifiers; After solving the intersection of the target heat resistance range and the pad heat resistance range to obtain a compatible heat resistance range, the compatible heat resistance range is used to traverse the melting point ranges of the multiple sample materials to screen and obtain M compatible compatible solders from the compatible compatible solder set; Applying the M compatible solders to conduct a small batch test of guide pin welding to obtain M solder spreading percentages and M intermetallic compound percentages; Preset a spreading influence weight and an intermetallic compound influence weight, and use the spreading influence weight and the intermetallic compound influence weight to evaluate the M solder spreading percentages and the M intermetallic compound percentages to obtain M compatible adaptation coefficients; The target solder type is extracted from the M compatible adapting solders by serializing the M compatible adapting coefficients, wherein the target solder type has an atmosphere sensitive identification.

7. An optimization method for improving the welding strength of capacitor guide pins according to claim 6, characterized in that: Initializing and setting welding parameters according to the target guide needle attributes and the target object attributes to obtain initial welding parameters includes: Extracting a target thermal conductivity from the target material properties; Performing a local search using the target thermal conductivity, solder joint size parameters, and target solder type as search conditions to obtain a plurality of historical soldering times; Performing discrete analysis on the multiple historical welding times and outputting welding time intervals; Interactively obtaining the solder heat resistance range of the target solder type, and obtaining the welding temperature range by solving the intersection of the solder heat resistance range and the compatible heat resistance range; By analyzing the target geometric characteristics, a guide needle pressure tolerance range is obtained; Interactively obtaining the equipment capability interval of the welding equipment, and obtaining the welding pressure interval by solving the intersection of the guide needle pressure tolerance interval and the equipment capability interval; Extract and obtain welding atmosphere type and atmosphere flow rate range from the atmosphere sensitive marker; The welding time interval, welding temperature interval, welding pressure interval, welding atmosphere type and atmosphere flow rate interval are integrated to output the initial welding parameters.

8. An optimization method for improving the welding strength of capacitor guide pins according to claim 7, characterized in that: A small batch verification optimization of welding control is performed in the welding strength optimization space, and target welding control parameters are output, including: Constructing the welding strength optimization space based on the welding time interval, welding temperature interval, welding pressure interval, atmosphere flow rate interval and welding feed rate interval; After locating H initial welding particle points in the welding strength optimization space, extracting H sample welding control parameters of the H initial welding particle points to perform small batch welding tests to obtain H initial strength index sets, wherein the initial strength index sets include initial pull-out strength, initial shear strength, initial peel strength, initial thermal cycle strength and initial fatigue strength; Perform welding fitness evaluation based on the H initial strength index sets, and output H initial welding fitnesses; Performing optimization trend analysis on the H initial welding particle points according to the H initial welding fitnesses to obtain a welding parameter adjustment direction vector; The H initial welding fitnesses are serialized, and starting point particle points are positioned and optimized at the H initial welding particle points according to fitness extreme values; Predefine welding index adjustment step length; The welding parameter adjustment direction vector is used as a particle movement direction constraint, and the welding index adjustment step size is used as a particle movement distance constraint. Small batch verification and optimization of welding control are performed in the welding strength optimization space until the welding fitness fluctuates stably, and the target welding control parameters are output.

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