Spot welding method and system for producing indicating fuses

Abstract

The present invention relates to the field of resistance welding technology and proposes a spot welding method and system for indicative fuse production, comprising: obtaining a weld spot image during a fuse test weld; performing edge detection on the weld spot image to analyze the roundness and smoothness of the weld spot's outer contour, as well as the gradient distribution analysis within the weld spot, to determine the weld spot's outer contour quality and surface defectivity during the test weld; determining the weld spot's outer contour quality and surface defectivity during the test weld and adjusting welding parameters accordingly; constructing a welding quality regression model through multiple test welds and adjusting welding parameters; continuously adjusting welding parameters during the test welds using the welding quality regression model, and performing subsequent spot welding for fuse production. The present invention aims to optimize the process of adjusting welding machine parameters during multiple test welds to improve spot welding performance.

Description

Technical Field

[0001] The present invention relates to the technical field of resistance welding, and in particular to a spot welding method and system for producing indicating fuses. Background Art

[0002] With the increasing complexity and sophistication of modern electrical equipment, the importance of fuses as circuit protection components has become increasingly prominent. Indicating fuses, due to their ability to visually display the blown state, have attracted widespread application and attention. However, during the production of indicating fuses, the quality of the spot welding process directly affects the stability and reliability of their performance. Traditional spot welding methods often face problems such as inaccurate parameter control and poor welding consistency when welding indicating fuses. Improper parameter settings, such as excessively high or low current, time, or pressure, can lead to defects such as insufficient weld strength, uneven welding, weld spatter, and weld cracks, which in turn affect the electrical and mechanical properties of the fuse. Furthermore, problems such as overheating of the material and excessive cooling during welding can also lead to reduced fuse performance and even serious problems such as burn-through and excessive weld residue.

[0003] Before formal production begins, it is necessary to select multiple fuse materials as test welding samples and judge the spot welding effect and quality by observing the appearance of the solder joints, so as to fine-tune the currently set welding machine parameters. However, the conventional manual adjustment of the welding machine parameters by observing the appearance of the solder joints and repeating this process until the expected effect is achieved is too subjective, and the change in the appearance of the solder joints after each adjustment cannot be measured by a fixed standard. Therefore, it is necessary to establish a relevant model for the solder joint appearance and perform fitting regression analysis until the regression converges to judge the expected effect or the best effect. Summary of the Invention

[0004] The present invention provides a spot welding method and system for the production of indicating fuses to solve the problem that the spot welding improvement effect is inaccurate due to manual adjustment of the welding machine during multiple trial welding. The technical solutions adopted are as follows:

[0005] The present invention provides a spot welding method for producing an indicating fuse, the method comprising the following steps:

[0006] Test welding of fuse to obtain solder joint images;

[0007] The weld spot image is inspected by edge detection to analyze the roundness and smoothness of the weld spot outer contour, as well as the gradient distribution inside the weld spot, to determine the weld spot outer contour quality and weld spot surface defect degree of the test weld.

[0008] Determine the outer contour quality and surface defect degree of the weld spot during the test welding process, and adjust the welding parameters accordingly; build a welding quality regression model through multiple test welding and adjustment of welding parameters;

[0009] The welding parameters are continuously adjusted for the trial welding through the welding quality regression model.

[0010] Optionally, the weld spot image is subjected to edge detection to perform roundness and smoothness analysis of the weld spot outer contour, as well as gradient distribution analysis inside the weld spot, to determine the weld spot outer contour quality and weld spot surface defectivity of the test weld, including the following specific methods:

[0011] The outer contour edge and several internal edge pixel points are obtained by edge detection on the welding point image;

[0012] Analyze the roundness and corner point distribution of the outer contour edge to determine the outer contour quality of the weld;

[0013] The gradient comparison and edge length analysis on different edges of internal edge pixels are performed to determine the surface defect degree of the solder joint.

[0014] Optionally, the outer contour edge and several inner edge pixel points are obtained by:

[0015] Obtain several edge pixel points from the welding point image through edge detection;

[0016] Connect adjacent edge pixels to obtain several edges;

[0017] The length of each edge is obtained, and the edge with the longest length among all closed edges is used as the outer contour edge of the weld image; and several edge pixels inside the outer contour edge are used as the inner edge pixels of the weld image.

[0018] Optionally, the analysis of the roundness and corner point distribution of the outer contour edge to determine the outer contour quality of the weld spot includes the following specific methods:

[0019] Get the roundness of the outer contour edge;

[0020] The outer contour edge is detected by corner point detection to obtain several corner points; the ratio of the number of corner points to the number of pixels on the outer contour edge is obtained, and the difference obtained by subtracting the ratio from 1 is used as the contour smoothness of the outer contour edge;

[0021] The average of the roundness of the outer contour edge and the contour smoothness is taken as the outer contour quality of the weld joint of the test welding.

[0022] Optionally, the obtaining of the roundness of the outer contour edge includes the following specific methods:

[0023] The area of ​​the area enclosed by the outer contour edge is obtained, and the roundness of the outer contour edge is calculated as follows:

[0024]

[0025] in, Indicates the roundness of the outer contour edge, Indicates the length of the outer contour edge, Indicates the area of ​​the region enclosed by the outer contour edge.

[0026] Optionally, the gradient comparison and edge length analysis on different edges of the internal edge pixels to determine the surface defectivity of the solder joint may include the following specific methods:

[0027] Obtain several edges formed by internal edge pixels and record them as internal edges of the welding point;

[0028] Obtain the length of the internal edge of each solder joint and the gradient mean of all internal edge pixels on any solder joint internal edge as the overall gradient of the internal edge of the solder joint;

[0029] The surface defect degree of the solder joint is determined by the overall gradient and length of the internal edge of the solder joint.

[0030] Optionally, the method of determining the surface defect degree of the weld spot by the overall gradient and length of the inner edge of the weld spot includes the following specific methods:

[0031]

[0032] in, Indicates the surface defect of the solder joint. Indicates the number of internal edges of the solder joint, Indicates the The length of the inner edge of the strip weld, Indicates the The overall gradient of the inner edge of the strip weld, represents the overall gradient mean of the internal edges of all solder joints, represents the weight normalization function.

[0033] Optionally, the welding quality regression model is constructed by multiple welding trials and adjusting welding parameters, including the following specific methods:

[0034] After obtaining the adjusted welding parameters, re-test welding the fuse, obtain a weld spot image of the new test welding, obtain the weld spot outer contour quality and weld spot surface defect degree of the test welding, and adjust the welding parameters to obtain the second adjusted welding parameters;

[0035] Similarly, several test welds are carried out to obtain the outer contour quality and surface defect degree of the welds, and various welding parameters of each test weld are recorded, including welding current, welding time, electrode pressure, preheating temperature and cooling rate;

[0036] Obtaining the standard deviation of the welding parameters corresponding to any welding parameter under multiple welding trials, weight normalizing the standard deviations of all welding parameters, and using the obtained results as the regression weight of each welding parameter;

[0037] Multiple welding parameters of any welding trial are input into the model. The preset weight of each welding parameter in the model is its corresponding regression weight. At the same time, the weld contour quality and weld surface defect degree of the welding trial are input into the model. The output feature is the adjustment action of each welding parameter, including the parameter value and adjustment direction of each adjustment. The model is trained to construct a welding quality regression model.

[0038] Optionally, the welding parameters of the test welding are continuously adjusted by a welding quality regression model, including the following specific methods:

[0039] After the welding quality regression model outputs the adjustment action, a trial welding is performed according to the adjusted welding parameters, and the outer contour quality and surface defect degree of the weld point of the current trial welding are obtained;

[0040] Based on the welding quality regression model, combined with the welding parameters of the current test welding, the outer contour quality of the weld spot, and the surface defect degree of the weld spot, the adjustment action is continuously output. The welding parameters are adjusted in this way until the outer contour quality and surface defect degree of the weld spot in the first test welding meet the standards. The corresponding welding parameters are used as the welding parameters for spot welding in the fuse production process.

[0041] The present invention also proposes a spot welding system for producing indicating fuses, which includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0042] The beneficial effects of the present invention are as follows: the present invention quantifies the welding quality of the test welding and constructs a welding quality regression model in combination with the electric welding parameters to output the adjustment action of the electric welding parameters; wherein the edge detection is performed on the weld spot image of the test welding, the appearance quality of the weld spot is analyzed by using a machine vision method, the outer contour quality of the weld spot is determined by analyzing whether the outer contour of the weld spot is circular and smooth, and the gradient difference and distribution inside the weld spot are analyzed to quantify whether there are defects such as cracks, thereby reflecting the surface quality of the weld spot; by judging the outer contour quality of the weld spot and the surface defect degree of the weld spot under multiple test welding, the electric welding parameters are adjusted and a welding quality regression model is constructed based on this, the welding quality regression model can output the adjusted electric welding parameters, and through continuous test welding, provide a basis for subsequent spot welding quality to meet the standard; thereby, the spot welding quality is rapidly improved while continuously meeting the standard, and finally adjusted to the appropriate electric welding parameters to ensure the spot welding effect of the indicative fuse production. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 A schematic flow chart of a spot welding method for producing an indicating fuse provided by one embodiment of the present invention;

[0045] Figure 2 is the solder joint image;

[0046] Figure 3 is the outer contour edge image;

[0047] Figure 4 is the inner contour edge image. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0049] See also Figure 1 , which shows a flow chart of a spot welding method for producing an indicating fuse provided by one embodiment of the present invention, the method comprising the following steps:

[0050] Step S001: test welding a fuse to obtain a welding point image.

[0051] The purpose of this embodiment is to quantify the welding quality of the weld spot during the trial welding process through machine vision, and to build a model to quantify the adjustment action of the welding parameters by adjusting the welding parameters corresponding to the trial welding, so as to improve the accuracy of the spot welding quality adjustment during the trial welding. First, it is necessary to prepare the welding machine and perform welding while collecting weld spot images.

[0052] Specifically, the material and fusing capacity of the indicative fuse to be welded are determined. In this embodiment, the expected specifications are a current of 300A and a fusing time of 2.5 to 3 seconds. Initial welding parameters are set based on the expected specifications of the indicative fuse, including welding current, welding time, electrode pressure, preheating temperature, and postheating time. The various welding parameters are not specifically limited in this embodiment and are set based on experience during the initial trial welding. It should be noted that since the welding parameters are subsequently adjusted to improve the spot welding quality, the welding parameters can be set based on experience during the initial trial welding.

[0053] Furthermore, the welding position of the fuse and the terminal is determined, and at the same time, the welding point is ensured to be within the specified tolerance range. The welding position is pointed at by an industrial camera, and a small industrial camera is fixed on the welding machine to collect images of the welding point; Figure 2 As shown, after the industrial camera is installed, it is necessary to ensure that the welding point is located in the center of the lens. Figure 2 The center circle is assumed to be the solder joint area. While ensuring the integrity of the solder joint area, the zoom factor is used to keep a certain distance from the edge. In this embodiment, the distance is set to 10% of the short side length of the image.

[0054] Furthermore, one end of the fuse is aligned with the terminal and placed between the welding heads of the electric welder; the electric welder is started, and when the welding head reaches the welding temperature, pressure is applied to make the fuse and the terminal contact until the welding is completed; the set welding time and electrode pressure are maintained to ensure a strong connection between the fuse and the terminal; after the welding is completed, an industrial camera is used to capture an image of the solder joint, and the image of the solder joint of the test welding is obtained through grayscale processing.

[0055] Step S002: Perform edge detection on the solder joint image to analyze the roundness and smoothness of the solder joint outer contour, as well as the gradient distribution analysis inside the solder joint, to determine the quality of the solder joint outer contour and the surface defect degree of the solder joint.

[0056] It should be noted that an ideal solder joint should be circular or oval with smooth edges, without obvious sharp corners or notches. At the same time, the solder joint surface should be smooth and the color should be evenly distributed. On the contrary, if the solder joint surface is rough and cracks or irregular shapes appear, it is usually caused by unstable parameters during the spot welding process and excessively high temperatures. In this case, it is necessary to perform an outer contour quality analysis on the roundness and smoothness of the outer contour of the solder joint in the solder joint image, and at the same time, analyze the gradient changes and distribution inside the solder joint in the solder joint image to quantify whether the solder joint surface is smooth by smoothing the internal gradient.

[0057] Preferably, in one embodiment of the present invention, the step includes:

[0058] The outer contour edge and several internal edge pixel points are obtained by edge detection on the welding point image;

[0059] Analyze the roundness and corner point distribution of the outer contour edge to determine the outer contour quality of the weld;

[0060] The gradient comparison and edge length analysis on different edges of internal edge pixels are performed to determine the surface defect degree of the solder joint.

[0061] Preferably, in one embodiment of the present invention, edge detection is performed on the weld spot image to obtain the outer contour edge and a plurality of internal edge pixel points, including the following specific methods:

[0062] The weld spot image is detected using the Canny edge detection algorithm to obtain a number of edge pixel points; Canny edge detection is a well-known technology and will not be described in detail in this embodiment; adjacent edge pixel points are connected (eight-neighborhood adjacent), that is, connected edge pixel points are connected to obtain a number of curves, each curve is an edge, and thus a number of edges are obtained.

[0063] Furthermore, the length of each edge is obtained, and the edge with the largest length among all closed edges is used as the outer contour edge of the weld image; and several edge pixels inside the outer contour edge are used as the inner edge pixels of the weld image.

[0064] Preferably, in one embodiment of the present invention, the roundness and corner point distribution of the outer contour edge are analyzed to determine the outer contour quality of the weld, including the following specific methods:

[0065] The area of ​​the outer contour edge is obtained by the Shoelace formula (Gaussian area formula), and the roundness of the outer contour edge is calculated as follows:

[0066]

[0067] in, Indicates the roundness of the outer contour edge, Indicates the length of the outer contour edge, Indicates the area of ​​the region enclosed by the outer contour edge.

[0068] It should be noted that the closer the roundness is to 1, the closer the outer contour edge is to a circle. Without considering whether the outer contour of the solder joint is smooth, the overall shape of the outer contour of the solder joint is more standard.

[0069] Furthermore, a corner point detection algorithm is used to obtain several corner points of the outer contour edge. The corner point detection algorithm is a well-known technology and will not be described in detail in this embodiment. The ratio of the number of corner points to the number of pixel points on the outer contour edge is obtained, and the difference obtained by subtracting the ratio from 1 is used as the contour smoothness of the outer contour edge.

[0070] It should be noted that the fewer the number of corner points on the outer contour edge, the smoother the outer contour edge, the fewer sharp corners and notches on the outer contour of the weld point, the less rough it is, and the higher the quality of the outer contour of the corresponding weld point.

[0071] Furthermore, the average of the roundness of the outer contour edge and the contour smoothness is used as the outer contour quality of the weld joint of the test welding.

[0072] Preferably, in one embodiment of the present invention, gradient comparison and edge length analysis are performed on different edges of internal edge pixels to determine the surface defectivity of the weld spot, including the following specific methods:

[0073] Obtain several edges formed by internal edge pixels and record them as internal edges of the weld spot. Obtain the length of each internal edge of the weld spot and the gradient mean of all internal edge pixels on any internal edge of the weld spot as the overall gradient of the internal edge of the weld spot. The surface defect degree of the weld spot is calculated as follows:

[0074]

[0075] in, Indicates the surface defect of the solder joint. Indicates the number of internal edges of the solder joint, Indicates the The length of the inner edge of the strip weld, Indicates the The overall gradient of the inner edge of the strip weld, represents the overall gradient mean of the internal edges of all solder joints, Represents the weight normalization function, and the normalized object is the length of the internal edges of all welds.

[0076] It should be noted that, under normal circumstances, during the spot welding process, heat is transferred through the welding area, resulting in a temperature difference between the welding spot and the surrounding base material, and this temperature difference causes the generation of thermal stress. The uneven distribution of thermal stress will cause local stress concentration, which may exceed the yield limit of the material, thereby causing cracks. The cracks appear in the image as a tortuous shape and grayscale variation characteristics. In this case, the edge detection algorithm can be used to extract the gradient of the corresponding edge in the image, and the deviation of the edge pixel point on the edge and the overall gradient of the edge can be further calculated by the gradient to reflect the edge. The degree of tortuosity of the corresponding edge, and the crack usually has a certain length, and the longer the length, the more severe the crack. Therefore, in this application, when the overall gradient of the internal edge of the weld in the image deviates, and the greater the deviation, the more it conforms to the morphological characteristics of the crack, and when the length of the crack is longer, the worse the surface quality of the weld, that is, the greater the defectivity, that is, for the internal edge of the weld, the greater the deviation of its overall gradient, and the longer the length, the more likely it is to be an obvious crack or defect, then there are more obvious cracks and other defects inside the weld, the rougher the weld surface, the greater the surface defectivity of the weld, and the worse the surface quality of the weld.

[0077] At this point, the image of the test weld is edge detected, and the appearance quality of the weld is analyzed using machine vision methods. The quality of the weld contour is determined by analyzing whether the outer contour of the weld is circular and smooth. The gradient difference and distribution inside the weld are analyzed to quantify whether there are defects such as cracks, thereby reflecting the surface quality of the weld.

[0078] Step S003: Determine the outer contour quality and surface defect degree of the weld spot during the trial welding, and adjust the welding parameters accordingly; and construct a welding quality regression model by performing multiple trial welding and adjusting the welding parameters.

[0079] It should be noted that if the shape of the weld is irregular, that is, it does not fit the circle or ellipse, or there are sharp corners or spatter on the edge contour of the weld, it is usually due to the welding current being too high, causing the weld to overheat, or the electrode pressure being too low, resulting in poor contact of the weld. In this case, it is necessary to reduce the welding current and increase the electrode pressure. When the surface defects of the weld are large, reflecting the poor surface quality of the weld, it is usually due to the welding current being too high, or the welding time being too long, causing the weld to overheat, resulting in crack defects or surface roughness.

[0080] Preferably, in one embodiment of the present invention, the outer contour quality and surface defect degree of the weld spot of the test weld are judged to adjust the welding parameters, and the specific method includes:

[0081] A contour threshold is preset. In this embodiment, the contour threshold is described as 0.8. If the outer contour quality of the weld point during the test welding is less than the contour threshold, the welding parameters need to be adjusted as follows:

[0082] 1. Welding current:

[0083] 1) Adjustment direction: decrease;

[0084] 2) Adjustment range: Reduce the current value by 5-10% and observe the change in solder joint quality. In this embodiment, the adjustment range is 5% of the current value.

[0085] 2. Welding time:

[0086] 1) Adjustment direction: shorten;

[0087] 2) Adjustment range: The adjustment is reduced by 0.1-0.2 seconds, depending on the actual welding time; in this embodiment, the adjustment range is 0.1 seconds.

[0088] 3. Electrode pressure:

[0089] 1) Adjustment direction: increase;

[0090] 2) Adjustment range: Increase the pressure by 5-10% to ensure good contact between the electrode and the welding point. In this embodiment, the adjustment range is 5% of the pressure value.

[0091] After adjusting the welding parameters based on the weld profile quality, a defect threshold is preset. In this embodiment, the defect threshold is described as 0.2. If the surface defect degree of the weld during the test welding is greater than the defect threshold, further adjustments need to be made based on the already adjusted welding parameters, as follows:

[0092] 1. Welding current:

[0093] 1) Adjustment direction: decrease;

[0094] 2) Adjustment range: Reduce the current value by 5-10% to avoid overheating of the solder joint. In this embodiment, the adjustment range is 5% of the current value.

[0095] 2. Welding time:

[0096] 1) Adjustment direction: shorten;

[0097] 2) Adjustment range: Adjust to reduce 0.1-0.2 seconds to reduce heat input; in this embodiment, the adjustment range is 0.1 seconds.

[0098] 3. Preheating temperature and post-heating time:

[0099] 1) Adjustment direction: increase preheating temperature and postheating time.

[0100] 2) Adjustment range: increase the preheating temperature by 10-20°C and the post-heating time by 0.5-1 minute; in this embodiment, the adjustment range is to increase the preheating temperature by 10°C and the post-heating time by 1 minute.

[0101] Based on the initial welding trial, the adjusted welding parameters are obtained as the first adjusted welding parameters.

[0102] Preferably, in one embodiment of the present invention, a welding quality regression model is constructed by multiple welding trials and adjusting welding parameters, including the following specific methods:

[0103] After obtaining the welding parameters adjusted for the first time, a test weld is performed on the fuse again, and an image of the weld spot of the new test weld is obtained. The outer contour quality and the surface defect degree of the weld spot of the test weld are obtained according to the above method, and the welding parameters are adjusted to obtain the second adjusted welding parameters. Similarly, several test welds are performed and the outer contour quality and surface defect degree of the weld spot of the test weld are obtained. At the same time, various welding parameters of each test weld are recorded, including welding current, welding time, electrode pressure, preheating temperature, and cooling rate (obtained through post-heating time). In this embodiment, a total of five test welds are performed to construct a welding quality regression model.

[0104] Furthermore, the standard deviation of the welding parameters corresponding to any welding parameter in multiple welding trials is obtained, the standard deviation of all welding parameters is weighted normalized, and the result is used as the regression weight of each welding parameter; this embodiment adopts the Lasoo regression model, and the multiple welding parameters of any welding trial are input into the model, and the preset weight of each welding parameter in the model is its corresponding regression weight, and the weld outer contour quality and weld surface defect degree of the welding trial are input into the model at the same time; the output feature is the adjustment action of each welding parameter, including the parameter value and adjustment direction (for example, increase or decrease) of each adjustment; the model is used for training, and the welding parameters of each welding trial and the corresponding weld outer contour quality and weld surface defect degree of the welding trial are input into the regression model, and the adjustment action for the welding parameters of the next welding trial is output, and finally the construction of the welding quality regression model is completed.

[0105] At this point, by judging the quality of the weld spot outer contour and the surface defect degree of the weld spot through multiple trial welding, adjusting the welding parameters and constructing a welding quality regression model based on this. The welding quality regression model can then output the adjusted welding parameters and, through continuous trial welding, provide a basis for the subsequent spot welding quality to meet the standards.

[0106] Step S004: continuously adjust the welding parameters of the test welding through the welding quality regression model, and perform spot welding for subsequent fuse production.

[0107] After the welding quality regression model outputs an adjustment action, a trial welding is performed based on the adjusted welding parameters, and the weld outer contour quality and weld surface defect degree of the current trial welding are obtained; based on the welding quality regression model, combined with the welding parameters, weld outer contour quality and weld surface defect degree of the current trial welding, the adjustment action continues to be output, and the welding parameters are continuously adjusted in this way until the weld outer contour quality and weld surface defect degree of a trial welding meet the standards, that is, the weld outer contour quality is greater than or equal to the contour threshold and the weld surface defect degree is less than or equal to the defect threshold. The corresponding welding parameters are then used as the welding parameters for spot welding in the fuse production process, and spot welding is performed for subsequent fuse production.

[0108] At this point, by quantifying the welding quality of the test welding and building a welding quality regression model based on the welding parameters, the adjustment actions of the welding parameters are output, so that the spot welding quality can be rapidly improved while continuously meeting the standards. Finally, the appropriate welding parameters are adjusted to ensure the spot welding effect of the indicative fuse production.

[0109] In a specific embodiment of the present invention, a spot welding method for producing indicative fuses is provided, wherein edge detection is performed on a solder joint image by the method in step S002, and an outer contour edge and an inner contour edge in the solder joint image are obtained, such as Figure 2 Shown is an image of a solder joint. Figure 3 is the image corresponding to the outer contour edge, Figure 4 For an inner contour edge image, in the process of steps S001 to S004 in the spot welding method for producing an indicative fuse, the calculation results of the data corresponding to the gradient value, inner edge length, roundness, smoothness, and defectivity in the weld spot image are obtained, as shown in Table 1:

[0110] Table 1: Calculation results of the gradient value, internal edge length, roundness, smoothness, and defectivity in the solder joint image.

[0111]

[0112] Another embodiment of the present invention provides a spot welding system for producing indicative fuses, the system comprising a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, steps S001 to S004 of the above method are implemented.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. Spot welding method for the production of indicating fuses, characterized in that The method comprises the following steps: Test welding of fuse to obtain solder joint images; The weld spot image is inspected by edge detection to analyze the roundness and smoothness of the weld spot outer contour, as well as the gradient distribution inside the weld spot, to determine the weld spot outer contour quality and weld spot surface defect degree of the test weld. Determine the outer contour quality and surface defect degree of the weld spot during the test welding process, and adjust the welding parameters accordingly; build a welding quality regression model through multiple test welding and adjustment of welding parameters; The welding parameters are continuously adjusted for the test welding through the welding quality regression model; The test welding continuously adjusts the welding parameters through the welding quality regression model, including: After the welding quality regression model outputs the adjustment action, a trial welding is performed according to the adjusted welding parameters, and the outer contour quality and surface defect degree of the weld point of the current trial welding are obtained; Based on the welding quality regression model, combined with the welding parameters of the current test welding, the outer contour quality of the weld spot, and the surface defect degree of the weld spot, the adjustment action is continuously output. The welding parameters are adjusted in this way until the outer contour quality and surface defect degree of the weld spot in the first test welding meet the standards. The corresponding welding parameters are used as the welding parameters for spot welding in the fuse production process.

2. The spot welding method for producing an indicating fuse according to claim 1, characterized in that: The weld spot image is subjected to edge detection, and the roundness and smoothness analysis of the weld spot outer contour and the gradient distribution analysis inside the weld spot are performed to determine the weld spot outer contour quality and the weld spot surface defect degree of the test weld. The specific methods include: The outer contour edge and several internal edge pixel points are obtained by edge detection on the welding point image; Analyze the roundness and corner point distribution of the outer contour edge to determine the outer contour quality of the weld; The gradient comparison and edge length analysis on different edges of internal edge pixels are performed to determine the surface defect degree of the solder joint.

3. The spot welding method for producing an indicating fuse according to claim 2, characterized in that: The specific method for obtaining the outer contour edge and several internal edge pixel points is as follows: Obtain several edge pixel points from the welding point image through edge detection; Connect adjacent edge pixels to obtain several edges; The length of each edge is obtained, and the edge with the longest length among all closed edges is used as the outer contour edge of the weld image; and several edge pixels inside the outer contour edge are used as the inner edge pixels of the weld image.

4. The spot welding method for producing an indicating fuse according to claim 2, characterized in that: The analysis of the roundness and corner point distribution of the outer contour edge to determine the outer contour quality of the solder joint includes the following specific methods: Get the roundness of the outer contour edge; The outer contour edge is detected by corner point detection to obtain several corner points; the ratio of the number of corner points to the number of pixels on the outer contour edge is obtained, and the difference obtained by subtracting the ratio from 1 is used as the contour smoothness of the outer contour edge; The average of the roundness of the outer contour edge and the contour smoothness is taken as the outer contour quality of the weld joint of the test welding.

5. The spot welding method for producing an indicating fuse according to claim 4, characterized in that: The specific method for obtaining the roundness of the outer contour edge includes: The area of ​​the area enclosed by the outer contour edge is obtained, and the roundness of the outer contour edge is calculated as follows: ； in, Indicates the roundness of the outer contour edge, Indicates the length of the outer contour edge, Indicates the area of ​​the region enclosed by the outer contour edge.

6. The spot welding method for producing an indicating fuse according to claim 2, characterized in that: The specific method of performing gradient comparison and edge length analysis on different edges of internal edge pixels to determine the surface defect degree of the solder joint includes: Obtain several edges formed by internal edge pixels and record them as internal edges of the welding point; Obtain the length of the internal edge of each solder joint and the gradient mean of all internal edge pixels on any solder joint internal edge as the overall gradient of the internal edge of the solder joint; The surface defect degree of the solder joint is determined by the overall gradient and length of the internal edge of the solder joint.

7. The spot welding method for producing an indicating fuse according to claim 6, characterized in that: The specific method for determining the surface defect degree of the solder joint by the overall gradient and length of the internal edge of the solder joint is as follows: ； in, Indicates the surface defect of the solder joint. Indicates the number of internal edges of the solder joint, Indicates the The length of the inner edge of the strip weld, Indicates the The overall gradient of the inner edge of the strip weld, represents the overall gradient mean of the internal edges of all solder joints, represents the weight normalization function.

8. The spot welding method for producing an indicating fuse according to claim 2, characterized in that: The welding quality regression model is constructed by multiple welding trials and adjusting welding parameters, and the specific method includes: After obtaining the adjusted welding parameters, re-test welding the fuse, obtain a weld spot image of the new test welding, obtain the weld spot outer contour quality and weld spot surface defect degree of the test welding, and adjust the welding parameters to obtain the second adjusted welding parameters; Similarly, several test welds are carried out to obtain the outer contour quality and surface defect degree of the welds, and various welding parameters of each test weld are recorded, including welding current, welding time, electrode pressure, preheating temperature and cooling rate; Obtaining the standard deviation of the welding parameters corresponding to any welding parameter under multiple welding trials, weight normalizing the standard deviations of all welding parameters, and using the obtained results as the regression weight of each welding parameter; Input multiple welding parameters of any test welding into the model. The preset weight of each welding parameter in the model is its corresponding regression weight. At the same time, input the weld point outer contour quality and weld point surface defect degree of the test welding into the model. The output features are the adjustment actions of each welding parameter, including the parameter value and adjustment direction of each adjustment; the model is trained to construct a welding quality regression model.

9. A spot welding system for the production of indicating fuses, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that When the processor executes the computer program, the steps of the spot welding method for producing an indicating fuse according to any one of claims 1 to 8 are implemented.

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