Aluminum electrolytic capacitor shell gap welding device

Abstract

The invention discloses an aluminum electrolytic capacitor shell gap welding device, and relates to the technical field of welding, the aluminum electrolytic capacitor shell gap welding device comprises a work box and a controller, a support is arranged on the work box, an electric push rod is arranged below the support, and a plasma welding machine is installed at the movable end of the electric push rod; an adjusting assembly used for adjusting the plasma welding machine is arranged on the support. Rectangular openings are symmetrically formed in the top surface of the working box, and are provided with fixing pieces for fixing a shell of the aluminum electrolytic capacitor; the controller is electrically connected with the electric push rod, the adjusting assembly, the plasma welding machine and the fixing piece and used for controlling cooperative work of all the components. The welding quality is improved and the defective rate is reduced through cooperative work of the fixing piece, the adjusting assembly and various algorithms built in the controller; the welding efficiency is improved, and large-scale production is met; and the adaptability is enhanced, and intelligent welding is achieved.

Description

Technical Field

[0001] The present invention relates to the field of welding technology, and particularly to a gap welding device for the housing of an aluminum electrolytic capacitor. Background Art

[0002] In the field of electronic device manufacturing, aluminum electrolytic capacitors are widely used, and their performance directly affects the overall quality and stability of electronic devices. The housing of an aluminum electrolytic capacitor, as a key component, plays a protective role for the internal components, and its welding quality is crucial; poor welding quality may lead to loose sealing of the housing, exposing the internal components to the external environment, thereby affecting the electrical performance, service life of the capacitor, and even causing potential safety hazards;

[0003] Traditional welding methods for the housing of aluminum electrolytic capacitors have many drawbacks. Manual welding operations require extremely high technical levels of workers. The welding quality depends to a large extent on the experience and operation proficiency of workers. There are differences in the operation methods, welding speeds, and welding parameter settings of different workers, making it difficult to ensure the consistency of welding quality. Problems such as insecure welding, uneven weld seams, and false welding are likely to occur, resulting in a high defective rate of products; moreover, manual welding has low efficiency, is difficult to meet the needs of large-scale production, and increases production costs. Summary of the Invention

[0004] The present invention proposes a gap welding device for the housing of an aluminum electrolytic capacitor to solve the problems in the background art.

[0005] To achieve the above object, the present invention adopts the following technical solutions: A gap welding device for the housing of an aluminum electrolytic capacitor, including a working box and a controller. A bracket is provided on the working box. An electric push rod is provided below the bracket. The movable end of the electric push rod is installed with a plasma welding machine. An adjustment assembly for adjusting the plasma welding machine is provided on the bracket; Rectangular openings are symmetrically opened on the top surface of the working box, and fixing members for fixing the housing of the aluminum electrolytic capacitor are provided in the rectangular openings; The controller is electrically connected to the electric push rod, the adjustment assembly, the plasma welding machine, and the fixing member respectively, and is used to control the coordinated operation of each component.

[0006] Preferably, the fixing member includes a movable rod, a fixing plate, and a driving member. The movable rod is slidably arranged in the rectangular opening, connected to the fixing plate at the top, and connected to the driving member at the bottom; The driving member includes a connecting shaft, a micro motor, and a gear. The connecting shaft is rotatably arranged on the inner top surface of the working box, connected to the output shaft of the micro motor at the bottom, and provided with a gear on the outer wall; A strip-shaped toothed plate is provided on the side surface of the movable rod, and the strip-shaped toothed plate meshes with the gear in an interleaved manner; The control module controls the rotation direction and speed of the micro-motor. Through the meshing transmission between the gear and the strip tooth plate, it drives the relative movement of the movable rod and the fixed plate to realize the clamping and fixing of the aluminum electrolytic capacitor shell. During the transmission process, the rotation angle θ of the gear and the moving distance L of the fixed plate satisfy the formula: L = (θ × m × z) / (π), where m is the module of the gear and z is the number of teeth of the gear.

[0007] Preferably, the adjusting assembly includes longitudinal sliding rails symmetrically arranged on the inner top surface of the bracket, a second threaded slider slidably arranged on the longitudinal sliding rails, and a second lead screw rotatably arranged on the bracket. One end of the second lead screw is provided with a driving motor, and the other end is threadedly connected to the second threaded slider; The adjusting assembly further includes a transverse sliding rail, a first threaded slider, and a first lead screw. The transverse sliding rail is symmetrically arranged on the bottom surface of the second threaded slider. The first threaded slider is slidably arranged on the transverse sliding rail. The first lead screw is rotatably arranged between the support plates at both ends of the transverse sliding rail, threadedly connected to the first threaded slider, and one end is connected to the output shaft of the transmission motor; The control module controls the rotation direction and speed of the transmission motor. Through the threaded transmission between the first lead screw and the first threaded slider, it drives the first threaded slider to move horizontally on the transverse sliding rail, thereby adjusting the horizontal position of the plasma welding machine. During the horizontal position adjustment process, the number of rotation turns n' of the transmission motor and the moving distance S' of the first threaded slider satisfy the formula: S' = n' × P', where P' is the pitch of the first lead screw.

[0008] Preferably, a welding parameter adjustment algorithm is preset in the control module. The welding parameter adjustment algorithm is used to calculate the welding parameters of the plasma welding machine according to the analysis of the material characteristic vector, geometric parameters, and environmental parameters of the electrolytic capacitor shell.

[0009] Preferably, the welding parameter adjustment algorithm specifically adopts a non-linear programming algorithm optimized based on the genetic algorithm. The specific steps are as follows: Obtain the material characteristic vector, geometric parameters, and environmental parameters of the aluminum electrolytic capacitor shell, and also set the standard welding parameters of the plasma welding machine according to the welding task; among them, the material characteristic vector includes aluminum purity p, impurity content w, and heat treatment state H, the geometric parameters include thickness d, weld curvature radius r, and gap width h, the environmental parameters include environmental temperature Te and environmental humidity RH, and the welding parameters include welding current I, arc voltage U, welding speed v, and ion gas flow rate Q; Take the material characteristic vector, geometric parameters, and environmental parameters as input parameters; take the welding parameters as output parameters; Read the historical welding information, including the input parameters and output parameters during the historical welding process; Randomly generate a set number of individuals from historical welding information as the initial population; each individual corresponds to a set of welding parameters (I, U, v, Q). Calculate the fitness of each individual, specifically including calculating the welding quality cost, welding efficiency cost, and welding energy consumption cost; perform a weighted sum of the welding quality score, welding efficiency score, and welding energy consumption score to construct the objective function F(I, U, v, Q). Use the roulette wheel selection method to select individuals with fitness above the preset fitness threshold to enter the next generation. Perform a crossover operation on the selected individuals to generate new individuals. Then perform a mutation operation on the newly generated individuals. When the maximum number of iterations is reached or the fitness value converges, stop the iteration; after optimization by the genetic algorithm, obtain the welding parameters I, U, v, Q that minimize the objective function F(I, U, v, Q) as the optimal welding parameters.

[0010] Preferably, the controller includes a welding quality monitoring module and a data storage module. The welding quality monitoring module takes the start time of the plasma welding machine as the first time and the end time of welding as the second time; if there is no end time of welding, then take the current time as the second time; take the time region between the first time and the second time as the welding monitoring time zone; monitor the welding quality within the welding monitoring time zone to obtain the quality monitoring result; where the quality monitoring result includes the state parameter difference, state statistical index corresponding to the welding monitoring time zone and environmental state parameters, and the target difference, quality statistical index, quality evaluation value, and quality value corresponding to the quality factors. The data storage module is used to store the quality evaluation result and record the stored quality evaluation result as historical welding information.

[0011] Preferably, to monitor the welding quality within the welding monitoring time zone to obtain the quality monitoring result, the specific steps are as follows: Obtain the environmental state parameters during the welding process, including environmental noise, output current, and voltage of the plasma welding machine; set the normal noise value, output current target value, and output voltage target value according to the welding task. Subtract the set value from the state parameter to obtain the state parameter difference, and calculate the state statistical index of the state parameter difference within the welding monitoring time zone; where the state statistical index includes the average value, maximum value, minimum value, and standard deviation value. Perform a weighted calculation on all the state statistical indexes corresponding to the state parameters within the welding monitoring time zone to obtain the monitoring influence value corresponding to the state parameters. Simultaneously obtain the welding quality factors during the welding process, including penetration depth, weld width, and porosity; set the target penetration depth, target weld width, and standard porosity according to the welding task; Calculate the target difference corresponding to the quality factor by taking the difference between the welding quality factor and its set value; Calculate the quality statistical indicators of the target differences corresponding to the quality factors within the welding monitoring time zone; the quality statistical indicators include the average value, maximum value, minimum value, and standard deviation value; perform weighted calculation on all the quality statistical indicators corresponding to the quality factors within the welding monitoring time zone to obtain the quality evaluation value corresponding to the quality factor; Perform weighted calculation on the monitoring influence values of all state parameters and the quality evaluation values corresponding to all quality factors to obtain the quality value of this welding; Record the state parameter differences, state statistical indicators corresponding to the welding monitoring time zone and environmental state parameters, and the target differences, quality statistical indicators, quality evaluation values, and quality values corresponding to the quality factors as the quality evaluation results.

[0012] Preferably, the controller further includes a welding trajectory planning module; the welding trajectory planning module acquires the three-dimensional model of the aluminum electrolytic capacitor housing based on a three-dimensional vision sensor, and plans the optimal welding trajectory according to the weld positions required by the housing.

[0013] Preferably, the welding trajectory planning adopts a path planning method optimized based on the genetic algorithm, and the specific steps are as follows: Obtain the welding task, identify the weld positions on the aluminum electrolytic capacitor housing that need to be welded in the welding task, divide the weld positions into N discrete welding points, and form a welding trajectory from the discrete welding points, denoted as ; construct the objective function , and the calculation formula of the objective function is: , where is the distance between adjacent welding points, i represents the number of the welding point, is the welding time of each welding point; iteratively optimize the permutation order P through the genetic algorithm, and take the welding trajectory with the shortest welding path and the least welding time as the optimal welding trajectory.

[0014] Preferably, calculate the fitness of each individual, specifically including calculating the welding quality cost, welding efficiency cost, and welding energy consumption cost; perform weighted summation on the welding quality score, welding efficiency score, and welding energy consumption score to construct the objective function, specifically as follows: Obtain the welding quality factors of each welding process, including penetration depth D, weld width W, and porosity P; set the target penetration depth Dta and target weld width Wta in its welding factors according to the welding task, and calculate the welding quality score , and the formula is , where \(k_1\), \(k_2\), and \(k_3\) respectively represent the weight coefficients related to the penetration depth, bead width, and porosity, and \(k_1 + k_2 + k_3 = 1\); Obtain the welding speed \(v\) during each welding process, and calculate the welding efficiency score according to the welding speed. The formula is ; Obtain the welding current \(I\) and arc voltage \(U\) during each welding process, and calculate the welding energy consumption score based on these. The formula is ; Perform a weighted sum according to the welding quality score, welding efficiency score, and welding energy consumption score to construct an objective function , where , are respectively the weight coefficients corresponding to the welding quality score, welding efficiency score, and welding energy consumption score.

[0015] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows: 1. The present invention stably clamps the aluminum electrolytic capacitor housing through a fixing member to prevent the housing from moving during welding, and combines an adjustment component to accurately position the welding head of the plasma welding machine, ensuring precise welding of the weld. At the same time, the welding parameter adjustment algorithm calculates the optimal welding parameters based on the housing material, geometry, and environmental parameters, effectively improving the welding quality, reducing problems such as insecure welding and uneven welds, and lowering the defective rate of products.

[0016] 2. The present invention coordinates the work of each component through a controller, reduces the manual operation link, the welding trajectory planning module plans the optimal welding path, reducing the welding time; the genetic algorithm optimizes the welding parameters, enabling the welding process to proceed efficiently. Compared with traditional manual welding, the welding efficiency is greatly improved, meeting the requirements of large-scale production and reducing production costs.

[0017] 3. The present invention monitors the welding quality in real time through a welding quality monitoring module, the data storage module accumulates historical data to optimize the welding parameters, and the welding parameter adjustment algorithm can automatically adjust the welding parameters according to different housing parameters, enhancing the adaptability of the device to different production requirements and realizing intelligent welding production.

[0018] In summary, the present invention coordinates the work of a fixing member, an adjustment component, and various algorithms built into the controller, improving the welding quality and reducing the defective rate; increasing the welding efficiency and meeting the requirements of large-scale production; and also enhancing the adaptability and realizing intelligent welding, with significant advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 shows a schematic structural diagram from the front view according to an embodiment of the present invention; Figure 2 shows a schematic structural diagram from the rear view according to an embodiment of the present invention; Figure 3Shows a schematic cross-sectional structure view from the front view according to an embodiment of the present invention; Figure 4 Shows a schematic structure view of a driving member according to an embodiment of the present invention; Figure 5 Shows a schematic structure view of an adjusting assembly according to an embodiment of the present invention.

[0020] Legend description: 1. Working box; 2. Bracket; 3. Transverse slideway; 4. Rectangular opening; 5. Electric push rod; 6. Plasma welding machine; 7. Fixed plate; 8. Driving motor; 9. Second threaded slider; 10. Connecting shaft; 11. Strip-shaped toothed plate; 12. Micro motor; 13. Gear; 14. Second lead screw; 15. Longitudinal slideway; 16. First threaded slider; 17. First lead screw; 18. Driving motor; 19. Movable rod. Specific embodiments

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Please refer to Figures 1 - 5 , the present invention provides an aluminum electrolytic capacitor housing gap welding device, including a working box 1 and a controller. A bracket 2 is provided on the working box 1, an electric push rod 5 is provided below the bracket 2, and a plasma welding machine 6 is installed at the movable end of the electric push rod 5. An adjusting assembly for adjusting the plasma welding machine 6 is provided on the bracket 2; symmetric rectangular openings 4 are provided on the top surface of the working box 1, and fixing members for fixing the aluminum electrolytic capacitor housing are provided in the rectangular openings 4; The controller is electrically connected to the electric push rod 5, the adjusting assembly, the plasma welding machine 6 and the fixing member respectively, and is used to control the coordinated work of each component.

[0023] In the present invention, the fixing member includes a movable rod 19, a fixed plate 7 and a driving member. The movable rod 19 is slidably arranged in the rectangular opening 4, connected to the fixed plate 7 at the top and connected to the driving member at the bottom; the driving member includes a connecting shaft 10, a micro motor 12 and a gear 13. The connecting shaft 10 is rotatably arranged on the inner top surface of the working box 1, connected to the output shaft of the micro motor 12 at the bottom, and a gear 13 is provided on the outer wall; a strip-shaped toothed plate 11 is provided on the side surface of the movable rod 19, and the strip-shaped toothed plate 11 is meshed with the gear 13 in an alternating manner.

[0024] The control module controls the rotation direction and speed of the micro-motor 12. Through the meshing transmission between the gear 13 and the strip-shaped toothed plate 11, it drives the relative movement of the movable rod 19 and the fixed plate 7, realizing the clamping and fixing of the aluminum electrolytic capacitor shell. During the transmission process, the rotation angle θ of the gear 13 and the moving distance L of the fixed plate 7 satisfy the formula: L=(θ×m×z) / (2π), where m is the module of the gear and z is the number of teeth of the gear.

[0025] In the present invention, the adjustment assembly includes longitudinal slides 15 symmetrically arranged on the inner top surface of the bracket 2, a threaded slider two 9 slidably arranged on the longitudinal slides 15, and a lead screw two 14 rotatably arranged on the bracket 2. One end of the lead screw two 14 is provided with a drive motor 8, and the other end is threadedly connected to the threaded slider two 9. The adjustment assembly further includes a transverse slide 3, a threaded slider one 16, and a lead screw one 17. The transverse slide 3 is symmetrically arranged on the bottom surface of the threaded slider two 9. The threaded slider one 16 is slidably arranged on the transverse slide 3. The lead screw one 17 is rotatably arranged between the support plates at both ends of the transverse slide 3, threadedly connected to the threaded slider one 16, and one end is connected to the output shaft of the drive motor 18. The control module controls the rotation direction and speed of the drive motor 18. Through the threaded transmission between the lead screw one 17 and the threaded slider one 16, it drives the threaded slider one 16 to move horizontally on the transverse slide 3, thereby adjusting the horizontal position of the plasma welding machine 6. During the horizontal position adjustment process, the number of turns n' of the drive motor 18 and the moving distance S' of the threaded slider one 16 satisfy the formula: S'=n'×P', where P' is the pitch of the lead screw one 17.

[0026] In the present invention, a welding parameter adjustment algorithm is preset in the control module. The welding parameter adjustment algorithm is used to calculate the welding parameters of the plasma welding machine 6 according to the analysis of the material characteristic vector, geometric parameters, and environmental parameters of the electrolytic capacitor shell.

[0027] In the present invention, the welding parameter adjustment algorithm specifically adopts a non-linear programming algorithm optimized based on the genetic algorithm. The specific steps are as follows: Obtain the material characteristic vector, geometric parameters, and environmental parameters of the aluminum electrolytic capacitor shell, and also set the standard welding parameters of the plasma welding machine 6 according to the welding task. Among them, the material characteristic vector includes aluminum purity p, impurity content w, and heat treatment state H. The geometric parameters include thickness d, weld curvature radius r, and gap width h. The environmental parameters include environmental temperature Te and environmental humidity RH. The welding parameters include welding current I, arc voltage U, welding speed v, and ion gas flow rate Q. Use the material characteristic vector, geometric parameters, and environmental parameters as input parameters; use the welding parameters as output parameters. Read the historical welding information, including the input parameters and output parameters during the historical welding process. Randomly generate a set number of individuals from historical welding information as the initial population; each individual corresponds to a set of welding parameters (I, U, v, Q). Calculate the fitness of each individual, specifically including calculating the welding quality cost, welding efficiency cost, and welding energy consumption cost; perform a weighted sum of the welding quality score, welding efficiency score, and welding energy consumption score to construct the objective function F(I, U, v, Q). Use the roulette wheel selection method to select individuals with fitness above a preset fitness threshold to enter the next generation; the basic principle of the roulette wheel selection method is that the probability of each individual being selected is proportional to its fitness. Perform a crossover operation on the selected individuals to generate new individuals; the crossover operation can use methods such as single-point crossover and multi-point crossover to produce new combinations of welding parameters. Then perform a mutation operation on the newly generated individuals. The mutation operation can randomly change one or some welding parameters of an individual within a certain range to increase the diversity of the population. When the maximum number of iterations is reached or the fitness value converges, stop the iteration; after optimization by the genetic algorithm, obtain the welding parameters I, U, v, Q that minimize the objective function F(I, U, v, Q) as the optimal welding parameters.

[0028] In the present invention, the controller includes a welding quality monitoring module and a data storage module. The welding quality monitoring module takes the start time of the plasma welding machine 6 as the first time and the end time of welding as the second time; if there is no end time of welding, then take the current time as the second time; take the time region between the first time and the second time as the welding monitoring time zone; monitor the welding quality within the welding monitoring time zone to obtain a quality monitoring result; where the quality monitoring result includes the state parameter difference, state statistical index corresponding to the welding monitoring time zone and environmental state parameters, and the target difference, quality statistical index, quality evaluation value, and quality value corresponding to the quality factors. The data storage module is used to store the quality evaluation result and record the stored quality evaluation result as historical welding information.

[0029] In the present invention, to monitor the welding quality within the welding monitoring time zone to obtain a quality monitoring result, the specific steps are as follows: Obtain the environmental state parameters during the welding process, including environmental noise, output current, and voltage of the plasma welding machine 6; set the noise normal value, output current target value, and output voltage target value according to the welding task. Subtract the set value from the state parameter to obtain the state parameter difference, and calculate the state statistical index of the state parameter difference within the welding monitoring time zone; where the state statistical index includes the average value, maximum value, minimum value, and standard deviation value. Perform weighted calculation on all state statistical indicators corresponding to the state parameters within the welding monitoring time zone to obtain the monitoring influence value corresponding to the state parameters; Meanwhile, obtain the welding quality factors during the welding process, including penetration depth, weld width, and porosity; set the target penetration depth, target weld width, and standard porosity according to the welding task; Take the difference between the welding quality factors and their set values to obtain the target difference corresponding to the quality factors; Calculate the quality statistical indicators of the target differences corresponding to the quality factors within the welding monitoring time zone; the quality statistical indicators include average value, maximum value, minimum value, and standard deviation; perform weighted calculation on all quality statistical indicators corresponding to the quality factors within the welding monitoring time zone to obtain the quality evaluation value corresponding to the quality factors; Perform weighting on the monitoring influence values of all state parameters and the quality evaluation values corresponding to all quality factors to obtain the quality value of this welding; Record the state parameter differences, state statistical indicators corresponding to the welding monitoring time zone and environmental state parameters, the target differences, quality statistical indicators, quality evaluation values, and quality values corresponding to the quality factors as the quality evaluation results.

[0030] In the present invention, the controller further includes a welding trajectory planning module; the welding trajectory planning module acquires the three-dimensional model of the aluminum electrolytic capacitor housing based on a three-dimensional vision sensor, and plans the optimal welding trajectory according to the weld positions required by the housing.

[0031] In the present invention, the welding trajectory planning adopts a path planning method optimized based on the genetic algorithm, and the specific steps are as follows: Obtain the welding task, identify the weld positions on the aluminum electrolytic capacitor housing that need to be welded in the welding task, divide the weld positions into N discrete welding points, and form a welding trajectory from the discrete welding points, denoted as ; construct the objective function , and the calculation formula of the objective function is: , where is the distance between adjacent welding points, i represents the number of the welding point, is the welding time of each welding point; iteratively optimize the permutation order P through the genetic algorithm, and take the welding trajectory with the shortest welding path and the least welding time as the optimal welding trajectory.

[0032] In the present invention, calculate the fitness of each individual, specifically including calculating the welding quality cost, welding efficiency cost, and welding energy consumption cost, as follows: Obtain the welding quality factors of each welding process, including penetration depth D, weld width W, and porosity P; set the target penetration depth Dta and target weld width Wta in its welding factors according to the welding task, and calculate the welding quality score , and the formula is , where k1, k2, and k3 respectively represent the weight coefficients related to the penetration depth, weld width, and porosity, and k1 + k2 + k3 = 1. This formula weighs the square of the relative deviation between the penetration depth, weld width, and the target value, combines with the porosity, and comprehensively measures the deviation degree of the welding quality. The smaller the deviation, the lower the welding quality score, indicating better welding quality; Obtain the welding speed v during each welding process, and calculate the welding efficiency score according to the welding speed. The formula , indicating that the faster the welding speed, the lower the welding efficiency score. The more welding tasks are completed within the same time, the higher the efficiency; Obtain the welding current I and arc voltage U during each welding process, and calculate the welding energy consumption score accordingly. The formula is , indicating that the product of the current and voltage during the welding process represents the power consumption. The larger the product, the higher the energy consumption score, meaning the greater the welding energy consumption; Perform weighted summation based on the welding quality score, welding efficiency score, and welding energy consumption score to construct the objective function , where 、 are the weight coefficients corresponding to the welding quality score, welding efficiency score, and welding energy consumption score respectively; the weight coefficients are adjusted according to the actual production requirements and the emphasis on welding quality, efficiency, and energy consumption. For example, in the case of extremely high requirements for welding quality, the value of can be appropriately increased.

[0033] The working principle of a kind of gap welding device for the shell of aluminum electrolytic capacitors provided by the present invention is as follows: First, place the shell of the aluminum electrolytic capacitor on the top surface of the working box 1, and start the micro motor 12. The output shaft of the micro motor 12 rotates to drive the connecting shaft 10 to rotate, and then drives the gear 13 arranged on the outer wall of the connecting shaft 10 to rotate. Since the side surface of the movable rod 19 is provided with a strip-shaped tooth plate 11, and the strip-shaped tooth plate 11 meshes with the gear 13 in an interleaved manner, when the gear 13 rotates, it will drive the strip-shaped tooth plate 11 to move relatively, further drive the movable rod 19 and the fixed plate 7 connected to the top of the movable rod 19 to move relatively, so as to clamp the shell of the aluminum electrolytic capacitor.

[0034] Next, the controller controls the drive motor 8 and the transmission motor 18 according to a preset algorithm. The output shaft of the drive motor 8 rotates to drive the second lead screw 14 to rotate. The second lead screw 14 is threadedly connected to the second threaded slider 9, and the second threaded slider 9 is slidably arranged on the longitudinal slideway 15 symmetric to the inner top surface of the bracket 2. Therefore, the rotation of the second lead screw 14 will drive the second threaded slider 9 to move back and forth. At the same time, the output shaft of the transmission motor 18 rotates to drive the first lead screw 17 to rotate. The first lead screw 17 is threadedly connected to the first threaded slider 16 slidably arranged on the transverse slideway 3. The transverse slideway 3 is symmetrically arranged on the bottom surface of the second threaded slider 9, thereby driving the first threaded slider 16 to move horizontally. Finally, the position of the electric push rod 5 installed on the bottom surface of the first threaded slider 16 and the plasma welding machine 6 connected to the movable end of the electric push rod 5 is adjusted so that its welding head is aligned with the weld seam.

[0035] Then, the controller controls the plasma welding machine 6 to perform welding according to the optimal welding parameters calculated by the welding parameter adjustment algorithm. The welding parameter adjustment algorithm will obtain the material characteristic vectors of the aluminum electrolytic capacitor housing, including aluminum purity p, impurity content w, and heat treatment state H, geometric parameters including thickness d, weld curvature radius r, gap width h, and environmental parameters including environmental temperature Te, environmental humidity RH. Through a series of calculations, the optimal welding parameters such as welding current I, arc voltage U, welding speed v, and ion gas flow rate Q are obtained, and then the plasma welding machine 6 is controlled to perform welding operations with these parameters.

[0036] During the welding process, the welding quality monitoring module monitors the welding quality in real time. This module obtains the environmental state parameters during the welding process, such as environmental noise, output current and voltage of the plasma welding machine 6, and at the same time obtains the welding quality factors, including penetration depth, weld width, and porosity. According to the welding task, the normal noise value, output current target value, output voltage target value, target penetration depth, target weld width, and standard porosity are set. By calculating the state parameter differences, state statistical indicators, target differences corresponding to the quality factors, quality statistical indicators, etc., the quality evaluation value and the quality value are finally obtained. The data storage module records the relevant data, and records the state parameter differences, state statistical indicators corresponding to the welding monitoring time zone and environmental state parameters, target differences corresponding to the quality factors, quality statistical indicators, quality evaluation value and quality value as the quality evaluation result and stores it.

[0037] After welding, if necessary, the welding parameters can be optimized using the stored historical welding information to obtain better results during the next welding. For example, when encountering a welding task for an aluminum electrolytic capacitor housing with similar material characteristic vectors, geometric parameters, and environmental parameters subsequently, the corresponding welding parameters and quality evaluation results in the historical welding information can be referred to, and the current welding parameter adjustment algorithm can be fine-tuned, such as adjusting the coefficients in the calculation formulas of each parameter, so as to improve the quality and efficiency of subsequent welding.

[0038] The foregoing description of the embodiments enables those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily 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 invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An aluminum electrolytic capacitor housing gap welding device, comprising a working box (1) and a controller, characterized in that, A support (2) is provided on the working box (1). An electric push rod (5) is provided below the support (2). A plasma welding machine (6) is installed at the movable end of the electric push rod (5). An adjusting assembly for adjusting the plasma welding machine (6) is provided on the support (2). Rectangular openings (4) are symmetrically formed on the top surface of the working box (1). Fixing members for fixing the aluminum electrolytic capacitor housing are provided in the rectangular openings (4). The controller is electrically connected to the electric push rod (5), the adjusting assembly, the plasma welding machine (6) and the fixing member respectively, and is used for controlling the coordinated operation of each component.

2. The aluminum electrolytic capacitor housing gap welding device according to claim 1, characterized in that, The fixing member includes a movable rod (19), a fixing plate (7) and a driving member. The movable rod (19) is slidably arranged in the rectangular opening (4), connected to the fixing plate (7) at the top and connected to the driving member at the bottom. The driving member includes a connecting shaft (10), a micro motor (12) and a gear (13). The connecting shaft (10) is rotatably arranged on the inner top surface of the working box (1), connected to the output shaft of the micro motor (12) at the bottom, and provided with a gear (13) on the outer wall. A strip-shaped toothed plate (11) is provided on the side surface of the movable rod (19), and the strip-shaped toothed plate (11) meshes with the gear (13) in a staggered manner. The control module controls the rotation direction and speed of the micro motor (12). Through the meshing transmission between the gear (13) and the strip-shaped toothed plate (11), the movable rod (19) and the fixing plate (7) are driven to move relatively, so as to clamp and fix the aluminum electrolytic capacitor housing. During the transmission process, the rotation angle θ of the gear (13) and the moving distance L of the fixing plate (7) satisfy the formula: L=(θ×m×z) / (2π), where m is the module of the gear and z is the number of teeth of the gear.

3. The gap welding device for the aluminum electrolytic capacitor housing according to claim 1, characterized in that, The adjusting assembly includes longitudinal sliding ways (15) symmetrically arranged on the inner top surface of the support (2), a threaded slider two (9) slidably arranged on the longitudinal sliding ways (15), and a lead screw two (14) rotatably arranged on the support (2). One end of the lead screw two (14) is provided with a driving motor (8), and the other end is threadedly connected to the threaded slider two (9). The adjusting assembly further includes a transverse sliding way (3), a threaded slider one (16) and a lead screw one (17). The transverse sliding ways (3) are symmetrically arranged on the bottom surface of the threaded slider two (9). The threaded slider one (16) is slidably arranged on the transverse sliding way (3). The lead screw one (17) is rotatably arranged between the support plates at both ends of the transverse sliding way (3), threadedly connected to the threaded slider one (16), and one end is connected to the output shaft of the transmission motor (18). The control module controls the rotation direction and speed of the transmission motor (18). Through the threaded transmission between the lead screw one (17) and the threaded slider one (16), the threaded slider one (16) is driven to move horizontally on the transverse sliding way (3), so as to adjust the horizontal position of the plasma welding machine (6). During the horizontal position adjustment process, the number of rotation turns n' of the transmission motor (18) and the moving distance S' of the threaded slider one (16) satisfy the formula: S'=n'×P', where P' is the pitch of the lead screw one (17).

4. The gap welding device for the aluminum electrolytic capacitor housing according to claim 1, characterized in that, A welding parameter adjustment algorithm is preset in the control module. The welding parameter adjustment algorithm is used to calculate the welding parameters of the plasma welding machine (6) according to the analysis of the material characteristic vector, geometric parameters, and environmental parameters of the electrolytic capacitor housing.

5. The aluminum electrolytic capacitor housing gap welding device according to claim 4, characterized in that, The welding parameter adjustment algorithm specifically adopts a nonlinear programming algorithm optimized based on the genetic algorithm. The specific steps are as follows: Obtain the material characteristic vector, geometric parameters, and environmental parameters of the aluminum electrolytic capacitor housing, and also set the standard welding parameters of the plasma welding machine (6) according to the welding task. Among them, the material characteristic vector includes aluminum purity p, impurity content w, and heat treatment state H, the geometric parameters include thickness d, weld curvature radius r, and gap width h, the environmental parameters include environmental temperature Te and environmental humidity RH, and the welding parameters include welding current I, arc voltage U, welding speed v, and ion gas flow rate Q. Use the material characteristic vector, geometric parameters, and environmental parameters as input parameters; use the welding parameters as output parameters. Read historical welding information, including input parameters and output parameters during the historical welding process. Randomly generate a set number of individuals from the historical welding information as the initial population; each individual corresponds to a set of welding parameters (I, U, v, Q). Calculate the fitness of each individual, specifically including calculating the welding quality cost, welding efficiency cost, and welding energy consumption cost; perform a weighted sum of the welding quality score, welding efficiency score, and welding energy consumption score to construct the objective function F(I, U, v, Q). Adopt the roulette wheel selection method to select individuals with fitness above the preset fitness threshold to enter the next generation. Perform a crossover operation on the selected individuals to generate new individuals. Then perform a mutation operation on the newly generated individuals. When the maximum number of iterations is reached or the fitness value converges, stop the iteration; after optimization by the genetic algorithm, obtain the welding parameters I, U, v, Q that minimize the objective function F(I, U, v, Q) as the optimal welding parameters.

6. The aluminum electrolytic capacitor housing gap welding device according to claim 1, wherein, The controller includes a welding quality monitoring module and a data storage module. The welding quality monitoring module takes the start time of the plasma welding machine (6) as the first moment and the end time of welding as the second moment; if there is no end time of welding, then take the current time as the second moment; take the time region between the first moment and the second moment as the welding monitoring time zone; monitor the welding quality within the welding monitoring time zone to obtain the quality monitoring result. Among them, the quality monitoring result includes the state parameter difference, state statistical index corresponding to the welding monitoring time zone and environmental state parameters, and the target difference, quality statistical index, quality evaluation value, and quality value corresponding to the quality factors. The data storage module is used to store the quality evaluation result and record the stored quality evaluation result as historical welding information.

7. The aluminum electrolytic capacitor housing gap welding device according to claim 6, characterized in that, Monitor the welding quality within the welding monitoring time zone to obtain the quality monitoring result. The specific steps are as follows: Obtain the environmental state parameters during the welding process, including environmental noise, output current, and voltage of the plasma welding machine (6); set the noise normal value, output current target value, and output voltage target value according to the welding task. Subtract the set value from the status parameter to obtain the status parameter difference, and calculate the status statistical indicators of the status parameter difference within the welding monitoring time zone; where the status statistical indicators include the average value, the maximum value, the minimum value, and the standard deviation value. Perform weighted calculation on all the status statistical indicators corresponding to the status parameters within the welding monitoring time zone to obtain the monitoring influence value corresponding to the status parameters. At the same time, obtain the welding quality factors during the welding process, including the penetration depth, the weld width, and the porosity; set the target penetration depth, the target weld width, and the standard porosity according to the welding task. Subtract the set value from the welding quality factor to obtain the target difference corresponding to the quality factor. Calculate the quality statistical indicators of the target difference corresponding to the quality factor within the welding monitoring time zone; the quality statistical indicators include the average value, the maximum value, the minimum value, and the standard deviation value. Perform weighted calculation on all the quality statistical indicators corresponding to the quality factors within the welding monitoring time zone to obtain the quality evaluation value corresponding to the quality factors. Perform weighting on the monitoring influence values of all the status parameters and the quality evaluation values corresponding to all the quality factors to obtain the quality value of this welding. Record the status parameter difference, the status statistical indicators corresponding to the welding monitoring time zone and the environmental status parameters, the target difference corresponding to the quality factor, the quality statistical indicators, the quality evaluation value, and the quality value as the quality evaluation result.

8. The gap welding device for the aluminum electrolytic capacitor housing according to claim 1, characterized in that, The controller further includes a welding trajectory planning module; the welding trajectory planning module plans the optimal welding trajectory based on obtaining the three-dimensional model of the aluminum electrolytic capacitor housing and according to the weld position required by the housing.

9. The aluminum electrolytic capacitor housing gap welding device according to claim 8, wherein, The welding trajectory planning adopts a path planning method optimized based on the genetic algorithm, and the specific steps are as follows: Obtain a welding task, identify the weld positions on the aluminum electrolytic capacitor housing in the welding task, divide the weld positions into N discrete welding points, and form a welding trajectory from the discrete welding points, denoted as ; construct an objective function , and the calculation formula of the objective function is: , where is the distance between adjacent welding points, i represents the number of the welding point, is the welding time of each welding point; iteratively optimize the permutation order P through the genetic algorithm, and take the welding trajectory with the shortest welding path and the least welding time as the optimal welding trajectory.

10. The aluminum electrolytic capacitor housing gap welding device according to claim 5, characterized in that, Calculate the fitness of each individual, specifically including calculating the welding quality cost, the welding efficiency cost, and the welding energy consumption cost; perform weighted summation on the welding quality score, the welding efficiency score, and the welding energy consumption score to construct an objective function, specifically as follows: Obtain the welding quality factors for each welding process, including the penetration depth D, the weld width W, and the porosity P; set the target penetration depth Dta and the target weld width Wta in its welding factors according to the welding task, and calculate the welding quality score , and the formula is , where k1, k2, and k3 respectively represent the weight coefficients related to the penetration depth, the weld width, and the porosity, and k1 + k2 + k3 = 1; Obtain the welding speed v during each welding process, and calculate the welding efficiency score according to the welding speed. The formula ; Obtain the welding current I and arc voltage U during each welding process, and calculate the welding energy consumption score according to the following formula ; Construct an objective function by performing a weighted sum based on the welding quality score, welding efficiency score, and welding energy consumption score , where , are the weight coefficients corresponding to the welding quality score, welding efficiency score, and welding energy consumption score, respectively.

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