Welding rod diameter and coating thickness matching method and system based on genetic algorithm

Abstract

The invention provides a welding rod diameter and coating thickness matching method and system based on a genetic algorithm, and the method comprises the steps: converting a matching target and constraint into a quantifiable mathematical model, and enabling the mathematical model to serve as a target function and a constraint function of the genetic algorithm; generating a group of random welding rod diameter and coating thickness combinations as an initial population; performing fitness evaluation on the target function to measure the advantages and disadvantages of the combination of the diameter of each welding rod and the thickness of the coating; excellent individuals are selected from the current population according to the fitness evaluation result to enter the next generation; combining the genes of the excellent individuals through crossover operation to generate new individuals; fitness evaluation, selection and crossover operation are repeated; and selecting the combination of the diameter of the welding rod with the highest fitness and the thickness of the coating as an optimal solution. The system comprises a population generation module, an interlace operation module and an iteration termination module. Effective technical support is provided for intelligent design of the welding process.

Description

Technical Field

[0001] The present invention relates to the technical field of electrode manufacturing, and particularly relates to a method and system for matching the electrode diameter and the coating thickness based on a genetic algorithm. Background Art

[0002] Welding materials are consumables in the national economy and are widely used in various industries such as infrastructure construction, energy transportation, equipment manufacturing, petrochemical industry, and iron and steel. In terms of market capacity, affected by the rapid development of downstream industries such as construction shipbuilding, petrochemical, container, and automobile industries, the market capacity of the welding material industry is extremely large, and its growth rate is also relatively fast. The average annual growth rate in the next five years will remain above 10%. Moreover, with the optimization of the industrial structure of the welding material industry and continuous technological progress, the proportion of high-grade welding material products in the entire industry is gradually increasing, and the market capacity of the entire industry will grow at a faster rate. Therefore, the development strategy of China's welding material products in the future is gradually shifting, and high-efficiency and high-quality products with a higher degree of automation are gradually replacing manual products. Manual electrodes are gradually developing towards high strength, high toughness, low hydrogen, and environmental protection. The electrode coating refers to the coating layer applied on the surface of the welding core. After the electrode coating decomposes and melts during the welding process, it forms gas and slag, which play roles in mechanical protection, metallurgical treatment, and improving process performance. The electrode coating plays an extremely important role in the welding process and is an important factor determining the weld quality. However, when the electrode coating is too thick, a large amount of smoke and slag will be generated during welding, the deposition efficiency is low, and the welding cost of users is increased. Using electrodes with a thin coating is more suitable for vertical welding operations in all-position welding, can also increase the deposition efficiency by more than 30%, generate less smoke during welding, cause less environmental pollution to the workplace, and is beneficial to the health of welding workers. It can also reduce production costs. Thin-coated electrodes are widely used in high-end welding material markets in Europe, America, etc. Therefore, the development of thin-coated electrodes has good prospects in the high-end foreign market. However, traditional methods usually rely on empirical formulas or repeated tests to obtain the matching results of the electrode diameter and the coating thickness, lacking systematicness and scientificity.

[0003] For example, in the prior art, application number: CN202310574235.0 discloses a coating extrusion and shaping device during the processing of welding electrodes, including two sets of conveying mechanisms distributed left and right. The conveying mechanisms are in a vertical conveying state and consist of two upper and lower conveying shafts. Conveying wheels are provided on both the front and rear sides of the conveying shafts. A conveying chain is driven on the two conveying wheels on the same side of the two conveying shafts, and multiple support rods are provided on the outer wall of the conveying chain. Although the coating is extruded and shaped by adopting an all-round extrusion method, the comprehensiveness and uniformity of the force on the coating can be effectively improved, the movement of the coating due to uneven force can be avoided, it is convenient to keep the thickness and density of the coating uniform, and at the same time, the phenomenon of cracking and falling off due to uneven force on the coating can be avoided, and the tightness of the welding electrode coating forming can be improved, thereby improving the processing quality of the welding electrode. However, the matching of the welding electrode diameter and the coating thickness is not achieved, mainly relying on the experience of technicians, resulting in a lack of unified standards in the matching process and affecting the product quality to a certain extent.

[0004] Currently, the prior art has the problem that it relies on empirical formulas or repeated tests to obtain the matching result of the welding electrode diameter and the coating thickness, lacking systematicness and scientificity. Therefore, the present invention provides a method and system for matching the welding electrode diameter and the coating thickness based on a genetic algorithm. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a method for matching the welding electrode diameter and the coating thickness based on a genetic algorithm, including the following steps:

[0006] Determine the matching target and constraint conditions of the welding electrode diameter and the coating thickness, and transform the matching target and constraints into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generate a set of random combinations of the welding electrode diameter and the coating thickness as the initial population;

[0007] Conduct a fitness evaluation on the objective function to measure the quality of each combination of the welding electrode diameter and the coating thickness; the fitness evaluation includes factors such as welding quality, process efficiency, and cost; select excellent individuals from the current population to enter the next generation according to the fitness evaluation results; combine the gene combinations of the excellent individuals through crossover operations to generate new individuals;

[0008] Repeat the fitness evaluation, selection, and crossover operations until the termination condition is met; finally, select the combination of the welding electrode diameter and the coating thickness with the highest fitness as the optimal solution.

[0009] Optionally, the process of generating a set of random combinations of the welding electrode diameter and the coating thickness as the initial population includes the following steps:

[0010] Determine the population size, that is, the number of individuals to be generated;

[0011] For each individual, randomly generate the base angle, random weight coefficient, and random phase parameter of the electrode diameter and coating thickness;

[0012] Calculate the electrode diameter and coating thickness to generate the combination of electrode diameter and coating thickness of the individual; use the generated individuals as the initial population.

[0013] Optionally, the process of combining the gene combinations of excellent individuals through crossover operations includes the following steps:

[0014] Select the combination of electrode diameter and coating thickness with high fitness from the current population as the parental individuals; disassemble and recombine the parameter information of the electrode diameter and coating thickness of the selected parental individuals to form new individuals;

[0015] During the crossover process, combine the electrode diameter parameter of one parental individual with the coating thickness parameter of another parental individual to form a new combination;

[0016] The set of new individuals generated through crossover operations will be candidates for the next generation population and continue with fitness evaluation and optimization.

[0017] Optionally, the process of obtaining the fitness evaluation results includes the following steps:

[0018] Collect real-time data, including multi-dimensional indicators such as welding quality, process efficiency, and cost; perform standardization processing on the collected multi-dimensional indicators;

[0019] Assign different weight coefficients to the welding quality, process efficiency, and cost indicators, and through weighted comprehensive calculation, fuse multiple indicators into a single fitness value; substitute the standardized multi-dimensional indicator values into the weighted comprehensive formula to calculate the fitness value of each combination of electrode diameter and coating thickness;

[0020] Sort all individuals according to the fitness value, and the individuals with higher fitness values are considered more excellent; after sorting, select the individuals with high fitness values as parental individuals to enter the next generation for crossover operations.

[0021] Optionally, the process of combining the electrode diameter parameter of one parental individual with the coating thickness parameter of another parental individual includes the following steps:

[0022] Select two relatively adaptable parental individuals from the current population, each individual having a combination parameter of electrode diameter and coating thickness; through disassembly, separate the electrode diameter parameter and coating thickness parameter from the parental individuals;

[0023] The electrode diameter parameter of the first selected parental individual will be extracted and used as the reference diameter of the new individual; at the same time, the coating thickness parameter of the second parental individual will be used as the key parameter of the coating thickness;

[0024] Fuse the electrode diameter parameter and the coating thickness parameter, and re - perform functional matching between the fused electrode diameter and the coating thickness.

[0025] Optionally, the process of fusing the electrode diameter parameter and the coating thickness parameter includes the following steps:

[0026] Separate the electrode diameter parameter and the coating thickness parameter from two selected parent individuals, preliminarily evaluate the reference diameter and the key coating thickness, and determine the physical properties and functional boundaries.

[0027] Through the dynamic evaluation of the reference diameter and combined with the parameter characteristics of the coating thickness, adjust the value range of the diameter.

[0028] The matching between the reference diameter and the coating thickness is based on the non - linear mapping of the physical properties of the welding material. By re - defining the proportional relationship between the reference diameter and the coating thickness, ensure the structural strength of the electrode, the coating coverage effect, the arc stability and the heat conduction efficiency of the electrode.

[0029] Optionally, the process of determining the physical properties and functional boundaries includes the following steps:

[0030] Separate the electrode diameter parameter and the coating thickness parameter from the selected basic data source as the initial reference values of the reference diameter and the key coating thickness; quantitatively analyze the geometric characteristics and mass distribution of the reference diameter to determine the functional boundaries during the welding process.

[0031] Systematically analyze the functional characteristics of the key coating thickness. The functional boundaries cover the protection effect on the welding area, and also include the regulation effect on the arc stability and the heat conduction efficiency; through the thermodynamic response analysis of the coating thickness during the welding process, determine the functional boundaries in the high - temperature welding environment.

[0032] Combine the principle of material structure - function coupling to analyze the synergistic relationship between the reference diameter and the key coating thickness; by introducing the interface mechanics theory, analyze the interface action mechanism between the reference diameter and the coating thickness to determine the proportional range under welding conditions; through the combination of heat conduction laws and fluid flow characteristics, analyze the heat transfer efficiency of the electrode during the welding process.

[0033] Optionally, the process of re - defining the proportional relationship between the reference diameter and the coating thickness includes the following steps:

[0034] Combine the physical properties of the coating thickness to dynamically adjust the value range of the reference diameter; analyze the interaction relationship between the coating thickness and the reference diameter to determine the proportional range under the working conditions.

[0035] Based on the physical properties of the welding consumables, perform a non-linear mapping analysis on the reference diameter and the coating thickness; when adjusting the reference diameter, synchronously consider the influence of the coating thickness on its covering effect; by introducing the basic principles of thermodynamics and fluid mechanics, analyze the heat conduction efficiency of the electrode during the welding process;

[0036] Obtain the proportional relationship to ensure the comprehensive optimization of the electrode in terms of structural strength, coating covering effect, arc stability, and heat conduction efficiency.

[0037] Optionally, the process of confirming the termination condition includes the following steps:

[0038] Statistically analyze the fitness value of each individual in the current population during a certain iteration, compare it with the fitness value in the previous iteration close to a certain iteration, and calculate its absolute difference; divide the sum of the fitness change differences of all individuals by the population size, and then divide by the maximum fitness value in the current population to obtain the normalized average fitness change rate; if the average fitness change rate is less than or equal to the preset convergence threshold, it is considered that the fitness has tended to be stable and the convergence state has been reached;

[0039] For each dimension of the optimization problem, calculate the deviation between the values of all individuals in the population in this dimension and the average value, sum the squares of the deviations of each dimension, and then divide by the population size to obtain the variance of the dimension; sum and take the square root of the variances of all dimensions to obtain the diversity index of the population. If the diversity index is less than the preset diversity threshold, it is considered that the population diversity is insufficient and the iteration needs to be terminated in advance;

[0040] Convert the fitness convergence determination, population diversity determination, and maximum iteration number determination into logical expressions respectively, and combine them through the logical OR operator; if any logical expression returns True, set the termination flag, indicating that the termination condition is met and the iteration should be stopped.

[0041] A matching system for electrode diameter and coating thickness based on the genetic algorithm provided by the present invention includes:

[0042] A population generation module, responsible for determining the matching objectives and constraints of the electrode diameter and coating thickness, converting the matching objectives and constraints into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generating a set of random combinations of electrode diameter and coating thickness as the initial population;

[0043] A crossover operation module, responsible for performing fitness evaluation on the objective function to measure the quality of each combination of electrode diameter and coating thickness; the fitness evaluation includes factors such as welding quality, process efficiency, and cost; select excellent individuals from the current population to enter the next generation according to the fitness evaluation results; combine the genes of the excellent individuals through crossover operations to generate new individuals;

[0044] The iterative termination module is responsible for repeatedly performing fitness evaluation, selection, and crossover operations until the termination condition is met; finally, the combination of the electrode diameter and the coating thickness with the highest fitness is selected as the optimal solution.

[0045] In the initialization stage of the present invention, the matching objectives of the electrode diameter and the coating thickness (such as welding quality, process efficiency, cost, etc.) are transformed into a mathematical model, making the problem quantifiable and optimizable. The constraint conditions ensure that the generated solutions meet the actual process or engineering requirements; provide a clear optimization direction for the genetic algorithm, avoiding the generation of invalid solutions; ensure the scientific nature and engineering practicability of the algorithm. A group of combinations of electrode diameter and coating thickness is randomly generated as the initial solution set of the genetic algorithm; introducing diversity to avoid the algorithm prematurely falling into a local optimal solution; improving the global search ability of the algorithm to ensure the possibility of finding a better solution. Fitness evaluation and selection quantify and evaluate the advantages and disadvantages of each combination through a mathematical model, comprehensively considering key indicators such as welding quality, process efficiency, and cost; assign a clear fitness value to each solution for easy selection and elimination; ensure that the optimization result meets the multi-objective requirements and improves the feasibility of practical engineering applications; select excellent individuals from the current population according to the fitness value as the parents of the next generation population, retain high-quality solutions, improve the convergence efficiency of the algorithm, accelerate the algorithm's approach to the optimal solution, and improve the optimization efficiency; combine the genes of two parent individuals to generate new offspring individuals, combining the advantages of the parents, introducing the possibility of new solutions, enhancing the diversity of the population, avoiding population degradation, and improving the global search ability of the algorithm. Iterative optimization and termination gradually optimize the population through the cyclic iteration of fitness evaluation, selection, crossover, and mutation. The population gradually approaches the optimal solution, and the fitness value continuously increases, ensuring that the algorithm finds a solution close to the global optimum through multiple rounds of optimization; when the termination condition is met (such as reaching the iteration number or the fitness value is stable), select the individual with the highest fitness in the current population as the optimal solution, the algorithm stops running, and outputs the optimal matching scheme of the electrode diameter and the coating thickness; provide a scientific and efficient design scheme for the welding process, improve the welding quality, reduce costs, and optimize the production process.

[0046] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written specification and the drawings.

[0047] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0048] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0049] Figure 1 It is the flowchart of the method for matching the electrode diameter and the coating thickness based on the genetic algorithm in Embodiment 1 of the present invention;

[0050] Figure 2 It is the process diagram of generating a group of random combinations of electrode diameter and coating thickness as the initial population in Embodiment 2 of the present invention;

[0051] Figure 3 It is the process diagram of combining the genes of excellent individuals through crossover operation in Embodiment 3 of the present invention;

[0052] Figure 4 It is the process diagram of obtaining the evaluation result of fitness in Embodiment 4 of the present invention;

[0053] Figure 5 It is the process diagram of combining the electrode diameter parameter of one parent individual with the coating thickness parameter of another parent individual in Embodiment 5 of the present invention;

[0054] Figure 6 It is the process diagram of fusing the electrode diameter parameter and the coating thickness parameter in Embodiment 6 of the present invention;

[0055] Figure 7 It is the process diagram of determining the physical characteristics and functional boundaries in Embodiment 7 of the present invention;

[0056] Figure 8 It is the process diagram of redefining the ratio relationship between the reference diameter and the coating thickness in Embodiment 8 of the present invention;

[0057] Figure 9 It is the process diagram of confirming the termination condition in Embodiment 9 of the present invention;

[0058] Figure 10 It is the block diagram of the system for matching the electrode diameter and the coating thickness based on the genetic algorithm in Embodiment 10 of the present invention. Specific implementation manners

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not used to limit the present invention.

[0060] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0061] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0062] Embodiment 1: As Figure 1 shown, an embodiment of the present invention provides a method for matching the diameter of an electrode and the thickness of the coating based on a genetic algorithm, which includes the following steps:

[0063] S100: Determine the matching objectives and constraints of the electrode diameter and the coating thickness, convert the matching objectives and constraints into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generate a set of random combinations of electrode diameter and coating thickness as the initial population;

[0064] S200: Conduct a fitness evaluation on the objective function to measure the quality of each combination of electrode diameter and coating thickness; the fitness evaluation includes factors such as welding quality, process efficiency, and cost; select excellent individuals from the current population to enter the next generation according to the fitness evaluation results; combine the genes of the excellent individuals through crossover operations to generate new individuals;

[0065] S300: Repeat the fitness evaluation, selection, and crossover operations until the termination condition is met; finally, select the combination of electrode diameter and coating thickness with the highest fitness as the optimal solution.

[0066] Among them, the purpose of the objective function F(D,T) is to maximize the welding quality and process efficiency while minimizing the cost. It can be defined in the following form:

[0067] F(D,T) = α1·Q(D,T) + α2·E(D,T) - α3·C(D,T)

[0068]

[0069]

[0070] Wherein, D represents the diameter of the welding electrode (mm); T represents the thickness of the coating (mm); Q(D, T) represents the welding quality evaluation function, which is related to the diameter of the welding electrode and the thickness of the coating; E(D, T) represents the process efficiency evaluation function, which is related to the diameter of the welding electrode and the thickness of the coating; C(D, T) represents the cost evaluation function, which is related to the diameter of the welding electrode and the thickness of the coating; α1, α2, α3 are weight coefficients used to balance the importance of welding quality, process efficiency, and cost; D opt represents the theoretically optimal diameter of the welding electrode; T opt represents the theoretically optimal thickness of the coating; σ D and σ T are the standard deviations of the diameter of the welding electrode and the thickness of the coating respectively, used to control the degree of deviation from the optimal value; D max represents the maximum allowable value of the diameter of the welding electrode; β1, β2, β3 are adjustment parameters related to process efficiency, used to fit the relationship between the actual production efficiency and the diameter of the welding electrode and the thickness of the coating; D min represents the minimum allowable value of the diameter of the welding electrode; γ1, γ2, γ3 are weight coefficients related to cost, used to measure the influence of different factors on cost;

[0071] The constraint conditions are used to limit the value ranges of the diameter of the welding electrode and the thickness of the coating to ensure that they meet the actual welding requirements. The constraint conditions are expressed as the following inequalities:

[0072]

[0073] Wherein, D min and D max are the minimum and maximum allowable values of the diameter of the welding electrode respectively; T min and T max are the minimum and maximum allowable values of the thickness of the coating respectively; K represents the minimum ratio of the diameter of the welding electrode to the thickness of the coating, used to ensure the mechanical strength and process stability of the welding electrode. Through the above objective function and constraint conditions, the matching problem of the diameter of the welding electrode and the thickness of the coating can be transformed into a complex but quantifiable mathematical model, which will be used as the core basis of the genetic algorithm to optimize the combined design of the diameter of the welding electrode and the thickness of the coating.

[0074] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the matching objectives and constraints between the electrode diameter and the coating thickness are first determined, and the matching objectives and constraints are transformed into a quantifiable mathematical model, which serves as the objective function and constraint function of the genetic algorithm. A group of random combinations of electrode diameter and coating thickness is generated as the initial population. Secondly, the fitness of the objective function is evaluated to measure the quality of each combination of electrode diameter and coating thickness. The fitness evaluation includes factors such as welding quality, process efficiency, and cost. Excellent individuals are selected from the current population according to the fitness evaluation results to enter the next generation. Through crossover operations, the genes of excellent individuals are combined to generate new individuals. Finally, the fitness evaluation, selection, and crossover operations are repeated until the termination condition is met. Ultimately, the combination of electrode diameter and coating thickness with the highest fitness is selected as the optimal solution. In the initialization stage of step S100 of the above solution, the matching objectives of the electrode diameter and the coating thickness (such as welding quality, process efficiency, cost, etc.) are transformed into a mathematical model, making the problem quantifiable and optimizable. The constraint conditions ensure that the generated solutions meet the actual process or engineering requirements, provide a clear optimization direction for the genetic algorithm, avoid the generation of invalid solutions, and ensure the scientific nature and engineering practicability of the algorithm. A group of combinations of electrode diameter and coating thickness is randomly generated as the initial solution set of the genetic algorithm, introducing diversity, avoiding the algorithm from prematurely falling into a local optimal solution, improving the global search ability of the algorithm, and ensuring the possibility of finding a better solution. In step S200 of fitness evaluation and selection, the quality of each combination is quantitatively evaluated through a mathematical model, comprehensively considering key indicators such as welding quality, process efficiency, and cost. A clear fitness value is assigned to each solution for easy selection and elimination, ensuring that the optimization result meets the multi-objective requirements and improves the feasibility of practical engineering applications. Excellent individuals are selected from the current population according to the fitness value as the parents of the next generation population, retaining high-quality solutions, improving the convergence efficiency of the algorithm, accelerating the algorithm's approach to the optimal solution, and enhancing the optimization efficiency. The genes of two parent individuals are combined to generate new offspring individuals, combining the advantages of the parents, introducing the possibility of new solutions, enhancing the diversity of the population, avoiding population degradation, and improving the global search ability of the algorithm. In step S300 of iterative optimization and termination, through the cyclic iteration of fitness evaluation, selection, crossover, and mutation, the population is gradually optimized, the population gradually approaches the optimal solution, and the fitness value continuously increases, ensuring that the algorithm finds a solution close to the global optimum through multiple rounds of optimization. When the termination condition is met (such as reaching the iteration number or the fitness value is stable), the individual with the highest fitness in the current population is selected as the optimal solution, the algorithm stops running, and the optimal matching scheme of electrode diameter and coating thickness is output, providing a scientific and efficient design scheme for the welding process, improving welding quality, reducing costs, and optimizing the production process.

[0075] In summary, through the above steps, the method for matching the electrode diameter and the coating thickness based on the genetic algorithm in this embodiment fully utilizes the global optimization ability of the genetic algorithm. At the same time, combined with the actual engineering objectives and constraints, it ensures that the optimization results not only meet the multi-objective requirements but also have practical engineering application value. This method provides effective technical support for the intelligent design of welding processes.

[0076] Embodiment 2: As Figure 2 shown, on the basis of Embodiment 1, the process of generating a group of random combinations of electrode diameters and coating thicknesses as the initial population provided by the embodiment of the present invention includes the following steps:

[0077] S101: Determine the population size, that is, the number of individuals to be generated;

[0078] S102: For each individual, randomly generate the base angle, random weight coefficient, and random phase parameter of the electrode diameter and the coating thickness;

[0079] S103: Calculate the electrode diameter and the coating thickness, and generate the combination of the electrode diameter and the coating thickness of the individual; use the generated individuals as the initial population.

[0080] Among them, in order to generate each individual (i.e., a combination of an electrode diameter and a coating thickness) in the initial population, the following formula is used:

[0081]

[0082] In the formula, D i represents the electrode diameter (mm) of the i-th individual; T i represents the coating thickness (mm) of the i-th individual; D min and D max represent the minimum and maximum allowable values of the electrode diameter respectively; T min and T max represent the minimum and maximum allowable values of the coating thickness respectively; θ D,i and θ T,i are the base angles of the electrode diameter and the coating thickness of the i-th individual respectively, and the value range is [0, 2π], which is used to control the distribution characteristics of the generated values; ψ D,i and ψ T,i are the random weight coefficients of the i-th individual, and the value range is [0, 1], which is used to adjust the random fluctuation intensity; ξ D,i and ξ T,i are the random phase parameters of the i-th individual, and the value range is [0, 1], which is used to introduce non-linear changes.

[0083] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the population size is first determined, that is, the number of individuals to be generated. Secondly, for each individual, the base angles of the electrode diameter and the coating thickness, random weight coefficients, and random phase parameters are randomly generated. Finally, the electrode diameter and the coating thickness are calculated to generate the combination of the electrode diameter and the coating thickness of the individual; the generated individuals are used as the initial population. Step S101 of the above solution determines the population size and the number of individuals in the initial population, providing a quantitative basis for the generation of individuals. The population size directly affects the search space and efficiency of the algorithm; Significance: By setting a reasonable population size, it is ensured that the algorithm can explore a sufficient solution space with limited computing resources, avoiding premature convergence or falling into local optimal solutions. Step S102 randomly generates the base angles of the electrode diameter and the coating thickness, random weight coefficients, and random phase parameters, using randomness to generate the base angles, weight coefficients, and phase parameters of the electrode diameter and the coating thickness, ensuring the diversity of the initial population. The parameters are used for subsequent calculation of the electrode diameter and the coating thickness to generate individual characteristics. Significance: By introducing randomness, the diversity of the initial population is expanded, providing a broader search range for the optimization algorithm and improving the global search ability. Step S103 calculates the electrode diameter and the coating thickness, generates the combination of the electrode diameter and the coating thickness of the individual; the generated individuals are used as the initial population. Based on the randomly generated base angles, weight coefficients, and phase parameters, the specific values of the electrode diameter and the coating thickness are calculated to form a complete combination of individual characteristics and finally constitute the initial population. Significance: The randomly generated parameters are transformed into specific combinations of the electrode diameter and the coating thickness to complete the construction of the initial population, providing basic data for the iterative search of the optimization algorithm.

[0084] In summary, the initial population generated by the above steps in this embodiment has diversity and randomness, can provide sufficient search space for the optimization algorithm, avoid the algorithm falling into local optimal solutions, and improve the optimization efficiency and the reliability of the results at the same time.

[0085] Embodiment 3: As Figure 3 shown, on the basis of Embodiment 1, the process of combining the genes of excellent individuals through crossover operation provided by the embodiment of the present invention includes the following steps:

[0086] S201: Select the combination of the electrode diameter and the coating thickness with high fitness from the current population as the parent individuals; the parent individuals represent the current most excellent combination parameters of the electrode diameter and the coating thickness; disassemble and recombine the parameter information of the electrode diameter and the coating thickness of the selected parent individuals to form new individuals;

[0087] S202: During the crossover process, combine the electrode diameter parameter of one parent individual with the coating thickness parameter of another parent individual to form a new combination;

[0088] S203: The new individual set generated through the crossover operation will be used as candidates for the next generation population and continue with fitness evaluation and optimization.

[0089] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, first, the combination of electrode diameter and coating thickness with high fitness is selected from the current population as the parent individuals; the parent individuals represent the current best combination parameters of electrode diameter and coating thickness; the parameter information of the electrode diameter and coating thickness of the selected parent individuals is disassembled and recombined to form new individuals; secondly, during the crossover process, the electrode diameter parameter of one parent individual is combined with the coating thickness parameter of another parent individual to form a new combination; finally, the new individual set generated through the crossover operation will be used as candidates for the next generation population and continue with fitness evaluation and optimization. In step S201 of the above solution, selecting parent individuals with high fitness and disassembling and recombining their parameter information can, while retaining excellent genes, generate new individuals through recombination; it can effectively avoid local optimal solutions and ensure population diversity at the same time, providing a better genetic basis for subsequent crossover operations. In step S202, combining the electrode diameter and coating thickness parameters of different parent individuals realizes gene crossover and innovation. This combination method can break through the limitations of a single parent individual, generate new individuals with the advantages of both sides, significantly improve the exploration efficiency of the search space, and accelerate the optimization process. The new individual set generated in step S203, as candidates for the next generation population, not only continues excellent genes but also introduces new gene combinations; through fitness evaluation and optimization, better solutions can be gradually screened out, continuously improving the overall performance of the population; ensuring the continuity of evolution and the gradual realization of the optimization goal.

[0090] In summary, the crossover operation process of this embodiment effectively improves the global search ability and optimization efficiency of the algorithm through gene recombination and optimization, helps to approach the optimal solution faster, and realizes the best combination of electrode diameter and coating thickness parameters.

[0091] Example 4: As Figure 4 shown, based on Example 3, the process for obtaining the evaluation result of fitness provided by the embodiment of the present invention includes the following steps:

[0092] S2011: Collect real-time data, including multi-dimensional indicators such as welding quality (such as weld strength, solder joint uniformity), process efficiency (such as welding speed, equipment utilization rate), and cost (such as material consumption, energy cost); perform standardization processing on the collected multi-dimensional indicators;

[0093] Among them, the welding quality may be expressed as a percentage of strength, the process efficiency is quantified in time units, and the cost may be measured in currency units;

[0094] S2012: Assign different weight coefficients to indicators such as welding quality, process efficiency, and cost. Through weighted comprehensive calculation, fuse multiple indicators into a single fitness value; substitute the standardized multi-dimensional indicator values into the weighted comprehensive formula to calculate the fitness value of each combination of electrode diameter and coating thickness.

[0095] S2013: Sort all individuals according to the fitness value. The individuals with higher fitness values are considered to be more excellent; after sorting, select the individuals with high fitness values as parental individuals to enter the next generation and perform crossover operations.

[0096] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, real-time data is first collected, including multi-dimensional indicators such as welding quality (such as weld strength, solder joint uniformity), process efficiency (such as welding speed, equipment utilization rate), and cost (such as material consumption, energy cost); perform standardized processing on the collected multi-dimensional indicators; among them, welding quality may be expressed as a percentage of strength, process efficiency is quantified in time units, and cost may be measured in currency units; secondly, assign different weight coefficients to indicators such as welding quality, process efficiency, and cost. Through weighted comprehensive calculation, fuse multiple indicators into a single fitness value; substitute the standardized multi-dimensional indicator values into the weighted comprehensive formula to calculate the fitness value of each combination of electrode diameter and coating thickness; finally, sort all individuals according to the fitness value. The individuals with higher fitness values are considered to be more excellent; after sorting, select the individuals with high fitness values as parental individuals to enter the next generation and perform crossover operations. In step S2011 of the above solution, data collection and standardized processing ensure the comprehensiveness and real-time nature of the evaluation data by collecting multi-dimensional indicators such as welding quality, process efficiency, and cost. Standardized processing eliminates the differences in units and magnitudes between different indicators, making the calculation comparable. Significance: Provide a data basis with consistency and operability for weighted comprehensive calculation, and ensure the scientificity and accuracy of the evaluation process. In step S2012 of weighted comprehensive calculation, according to actual needs, assign weight coefficients to indicators such as welding quality, process efficiency, and cost, and fuse multiple indicators into a single fitness value through a weighted formula; it can quantify the comprehensive performance of the combination of electrode diameter and coating thickness. Significance: Realize the comprehensive evaluation of multi-dimensional indicators, avoid the limitations of single indicators, and provide a quantitative basis for selecting the optimal combination. In step S2013 of fitness sorting and selection, sort all individuals according to the fitness value, screen out the individuals with high fitness values as parents, and enter the crossover and mutation operations of the next generation, optimizing the evolutionary direction of the population. Significance: Through the natural selection mechanism of survival of the fittest, improve the fitness of the population, ensure the global search ability and convergence efficiency of the algorithm, and lay a foundation for finally finding the optimal solution.

[0097] In summary, this embodiment constitutes the core logic of fitness evaluation, providing a scientific and systematic technical path for optimizing the combination of electrode diameter and coating thickness.

[0098] Example 5: As Figure 5 shown, based on Example 3, the process of combining the electrode diameter parameter of one parental individual with the coating thickness parameter of another parental individual provided by the embodiment of the present invention includes the following steps:

[0099] S2021: Select two relatively more adaptable parental individuals from the current population, each individual having a combination parameter of electrode diameter and coating thickness; through disassembly, separate the electrode diameter parameter and the coating thickness parameter from the parental individuals;

[0100] S2022: The electrode diameter parameter of the first selected parental individual will be extracted and used as the reference diameter of the new individual; at the same time, the coating thickness parameter of the second parental individual will be used as the key parameter of the coating thickness;

[0101] S2023: Combine the electrode diameter parameter and the coating thickness parameter, and re-perform functional matching between the combined electrode diameter and the coating thickness.

[0102] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, first, two parent individuals with relatively strong adaptability are respectively selected from the current population, and each individual has a combined parameter of electrode diameter and coating thickness; through disassembly, the electrode diameter parameter and the coating thickness parameter are separated from the parent individuals; secondly, the electrode diameter parameter of the first selected parent individual will be extracted and used as the reference diameter of the new individual; at the same time, the coating thickness parameter of the second parent individual is used as the key parameter for the coating thickness; finally, the electrode diameter parameter and the coating thickness parameter are fused, and a new functional match is made between the fused electrode diameter and the coating thickness. In step S2021 of the above solution, disassembly and separation are carried out. Two parent individuals with strong adaptability are selected from the current population, and their electrode diameter parameters and coating thickness parameters are disassembled respectively, and these parameters are regarded as independent functional modules; the disassembly process ensures the independence and combinability of the parameters, laying a foundation for realizing flexible parameter recombination. Significance: Through disassembly, the fixed mode of traditional parameter combination is broken, enabling the free recombination of electrode diameter and coating thickness. The modular disassembly method provides technical feasibility for parameter fusion and is a key prerequisite for realizing innovative combinations. In step S2022, parameter extraction and benchmarking are carried out. The electrode diameter parameter of the first parent individual is extracted as the reference diameter of the new individual, and at the same time, the coating thickness parameter of the second parent individual is extracted as the key parameter; it is ensured that the core parameters of the new combination come from different parent individuals, thus realizing the diverse input of parameters at the structural level. Significance: By extracting specific parameters from different parent individuals, the new combination achieves complementary advantages in the dimensions of electrode diameter and coating thickness; based on the parameter selection of different parents, the limitations of a single parent can be effectively avoided, and the optimization potential of different individuals in different dimensions can be fully exerted. In step S2023, parameter fusion and functional matching are carried out. The electrode diameter parameter and the coating thickness parameter are fused, and by rematching their functional relationships, the coordination between the two is ensured; for example, a larger electrode diameter may require a thicker coating to obtain sufficient protection effect, while a smaller diameter may require a thinner coating to achieve more flexible welding performance. Significance: Functional matching realizes the collaborative optimization between the electrode diameter and the coating thickness, enabling the new combination to better adapt to the complex requirements of the welding process in practical applications; the matching not only improves the performance of the new combination but also provides a technical basis for subsequent adaptability evaluation and optimization.

[0103] In summary, the disassembly and separation in this embodiment enable the independent extraction and recombination of the electrode diameter and coating thickness parameters, breaking through the limitations of traditional combinations; extracting advantageous parameters from different parent individuals realizes multi-dimensional performance optimization; through fusion and matching, the efficiency and stability of the new combination in practical applications are ensured. This not only improves the flexibility and innovation of the electrode parameter combination but also provides a new technical path for the further optimization of the welding process; by combining the advantageous parameters of different parent generations, the performance bottleneck in traditional electrode design can be effectively solved, promoting the continuous development of welding technology.

[0104] Embodiment 6: As Figure 6 shown, on the basis of Embodiment 5, the process of fusing the electrode diameter parameter and the coating thickness parameter provided by the embodiment of the present invention includes the following steps:

[0105] S20231: Separate the electrode diameter parameter and the coating thickness parameter from the two selected parent individuals, and conduct a preliminary evaluation of the reference diameter (the first parent individual) and the key coating thickness (the second parent individual) to determine the physical characteristics and functional boundaries; the reference diameter serves as the structural core and affects the mechanical strength and welding current-carrying capacity of the electrode; the coating thickness determines the protection performance, arc stability, and heat conduction efficiency of the electrode;

[0106] S20232: Adjust the value range of the diameter through the dynamic evaluation of the reference diameter in combination with the parameter characteristics of the coating thickness;

[0107] S20233: The matching of the reference diameter and the coating thickness is based on the non-linear mapping of the physical characteristics of the welding material. By redefining the proportional relationship between the reference diameter and the coating thickness, the structural strength, coating coverage effect, arc stability, and heat conduction efficiency of the electrode are ensured.

[0108] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the electrode diameter parameter and the coating thickness parameter are first separated from two selected parent individuals, and the reference diameter (the first parent individual) and the key coating thickness (the second parent individual) are preliminarily evaluated to determine the physical characteristics and functional boundaries; the reference diameter serves as the structural core and affects the mechanical strength and welding current carrying capacity of the electrode; the coating thickness determines the protection performance, arc stability, and heat conduction efficiency of the electrode; secondly, through the dynamic evaluation of the reference diameter and in combination with the parameter characteristics of the coating thickness, the value range of the diameter is adjusted; finally, the matching of the reference diameter and the coating thickness is based on the non - linear mapping of the physical characteristics of the welding consumables. By re - defining the proportional relationship between the reference diameter and the coating thickness, the structural strength, coating coverage effect, arc stability, and heat conduction efficiency of the electrode are ensured. Step S20231 of the above solution can determine the physical characteristics and functional boundaries of the reference diameter and the key coating thickness by separating the electrode diameter and coating thickness parameters from two parent individuals and conducting a preliminary evaluation on them; the reference diameter, as the structural core, directly affects the mechanical strength and welding current carrying capacity of the electrode, ensuring the structural stability and current adaptability of the electrode during use; the coating thickness determines the protection performance, arc stability, and heat conduction efficiency of the electrode, ensuring that the electrode can effectively protect the weld, maintain a stable arc, and efficiently conduct heat during the welding process. Step S20232 adjusts the value range of the diameter through the dynamic evaluation of the reference diameter and in combination with the parameter characteristics of the coating thickness to ensure the adaptability and optimization of the electrode diameter under different working conditions. Step S20233, the matching of the reference diameter and the coating thickness is based on the non - linear mapping of the physical characteristics of the welding consumables. By re - defining the proportional relationship between the two, the structural strength, coating coverage effect, arc stability, and heat conduction efficiency of the electrode are ensured; realizing the comprehensive optimization of the structural strength, protection performance, arc stability, and heat conduction efficiency of the electrode, and improving the welding quality and efficiency.

[0109] In summary, in this embodiment, by separating, evaluating, and matching the electrode diameter and coating thickness parameters, the comprehensive optimization of the structural strength, protection performance, arc stability, and heat conduction efficiency of the electrode is achieved, thereby improving the welding quality and efficiency of the electrode.

[0110] Example 7: As Figure 7 shown, on the basis of Example 6, the process for determining the physical characteristics and functional boundaries provided by the embodiment of the present invention includes the following steps:

[0111] S20231: Extract the electrode diameter parameter and the coating thickness parameter from the selected basic data source respectively as the initial reference values of the reference diameter and the key coating thickness; conduct a quantitative analysis on the geometric characteristics and mass distribution of the reference diameter to determine the functional boundaries during the welding process;

[0112] S20232: Systematically analyze the functional characteristics of the key coating thickness. The functional boundary covers the protection effect on the welding area and also includes the regulation of arc stability and heat conduction efficiency; determine the functional boundary under high-temperature welding conditions through the thermodynamic response analysis of the coating thickness during the welding process.

[0113] S20233: Analyze the synergistic relationship between the reference diameter and the key coating thickness in combination with the principle of material structure-function coupling; analyze the interfacial action mechanism between the reference diameter and the coating thickness by introducing the interfacial mechanics theory to determine the proportional range under welding conditions; analyze the heat transfer efficiency of the electrode during the welding process by combining the heat conduction law and the fluid flow characteristics.

[0114] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the electrode diameter parameter and the coating thickness parameter are first extracted from the selected basic data source as the initial reference values of the reference diameter and the key coating thickness; the geometric characteristics and mass distribution of the reference diameter are quantitatively analyzed to determine the functional boundary during the welding process; secondly, the functional characteristics of the key coating thickness are systematically analyzed, and the functional boundary covers the protection effect on the welding area, and also includes the regulation effect on the arc stability and heat conduction efficiency; through the thermodynamic response analysis of the coating thickness during the welding process, the functional boundary under the high-temperature welding environment is determined; finally, in combination with the principle of material structure and function coupling, the synergistic relationship between the reference diameter and the key coating thickness is analyzed; by introducing the interface mechanics theory, the interface action mechanism between the reference diameter and the coating thickness is analyzed to determine the proportional range under the welding conditions; through the combination of the heat conduction law and the fluid flow characteristics, the heat transfer efficiency of the electrode during the welding process is analyzed. In step S20231 of the above solution, the functional boundary of the reference diameter is determined. By quantitatively analyzing the geometric characteristics and mass distribution of the reference diameter of the electrode, the functional boundary during the welding process is clarified; the value of the reference diameter is directly related to the mechanical strength and current-carrying capacity of the electrode, ensuring that the electrode can stably withstand the welding current during the welding process and avoiding uneven current distribution or insufficient mechanical strength caused by too large or too small a diameter. Significance: By determining the functional boundary of the reference diameter, it provides core parameter support for the structural design of the electrode, ensures that the mechanical properties of the electrode meet the requirements under the welding conditions, and at the same time provides a reliable basis for parameter optimization. In step S20232, the functional boundary of the key coating thickness is determined. By systematically analyzing the functional characteristics of the key coating thickness, the functional boundary during the welding process is clarified; the value of the coating thickness directly affects the protection performance, arc stability and heat conduction efficiency of the electrode; through the thermodynamic response analysis of the coating thickness during the welding process, the functional boundary under the high-temperature welding environment is determined to ensure that the coating can effectively isolate external impurities and maintain arc stability. Significance: By determining the functional boundary of the coating thickness, it provides technical guarantee for the protection performance and welding stability of the electrode, avoids welding defects caused by insufficient or excessive coating thickness, and at the same time lays a foundation for subsequent parameter matching. In step S20233, the synergistic relationship between the reference diameter and the coating thickness is analyzed. In combination with the principle of material structure and function coupling, the synergistic relationship between the reference diameter and the key coating thickness is analyzed. By introducing the interface mechanics theory, the interface action mechanism between the two is clarified, and the proportional range under the welding conditions is determined; at the same time, in combination with the heat conduction law and the fluid flow characteristics, the heat transfer efficiency of the electrode during the welding process is optimized.Significance: By analyzing the synergistic relationship between the reference diameter and the coating thickness, multi-dimensional optimization of the electrode performance is achieved, ensuring a comprehensive balance in aspects such as structural strength, protection effect, arc stability, and heat conduction efficiency of the electrode; breaking through the limitations of traditional single-parameter optimization and providing a new technical path for the welding process.

[0115] In summary, through the implementation of the above steps in this embodiment, the physical characteristics and functional boundaries of the reference diameter and the key coating thickness of the electrode are determined, providing a systematic theoretical basis and technical support for their integration in the welding process. It not only optimizes the performance design of the electrode but also breaks through the limitations of traditional welding parameter optimization methods, providing important technical support for the innovation of the welding process.

[0116] Example 8: As Figure 8 shown, on the basis of Example 6, the process of redefining the ratio relationship between the reference diameter and the coating thickness provided by the embodiment of the present invention includes the following steps:

[0117] S202331: Dynamically adjust the value range of the reference diameter in combination with the physical characteristics of the coating thickness; analyze the interaction relationship between the coating thickness and the reference diameter to determine the ratio range under the working conditions;

[0118] S202332: Conduct a non-linear mapping analysis of the reference diameter and the coating thickness based on the physical characteristics of the welding consumables; synchronously consider the influence of the coating thickness on its covering effect when adjusting the reference diameter; analyze the heat conduction efficiency of the electrode during the welding process by introducing the basic principles of thermodynamics and fluid mechanics;

[0119] S202333: Obtain the ratio relationship to ensure comprehensive optimization of the electrode in terms of structural strength, coating covering effect, arc stability, and heat conduction efficiency.

[0120] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, first, in combination with the physical characteristics of the coating thickness, the value range of the reference diameter is dynamically adjusted; the interaction relationship between the coating thickness and the reference diameter is analyzed to determine the proportional range under the working conditions; second, based on the physical characteristics of the welding consumables, a non-linear mapping analysis is performed on the reference diameter and the coating thickness; the adjustment of the reference diameter synchronously considers the influence of the coating thickness on its covering effect; by introducing the basic principles of thermodynamics and fluid mechanics, the heat conduction efficiency of the electrode during the welding process is analyzed; finally, a proportional relationship is obtained to ensure the comprehensive optimization of the electrode in terms of structural strength, coating covering effect, arc stability, and heat conduction efficiency. In step S202331 of the above solution, the dynamic adjustment of the reference diameter and the determination of the proportional range, in combination with the physical characteristics of the coating thickness, the value range of the reference diameter is dynamically adjusted; by analyzing the interaction relationship between the coating thickness and the reference diameter, and comprehensively considering the mechanical strength of the welding consumables, arc stability, and coating covering uniformity, the proportional range between the two under specific working conditions is determined. Significance: By dynamically adjusting the value range of the reference diameter, problems such as uneven current distribution caused by too large a diameter or insufficient mechanical strength caused by too small a diameter in electrode design are avoided; at the same time, the determination of the proportional range provides an accurate theoretical basis for welding parameter optimization, ensuring the performance stability of the electrode under specific working conditions. In step S202332, non-linear mapping analysis and heat conduction efficiency optimization, based on the physical characteristics of the welding consumables, a non-linear mapping analysis is performed on the reference diameter and the coating thickness to clarify the synergistic relationship between the two; by introducing the basic principles of thermodynamics and fluid mechanics, the heat transfer efficiency of the electrode during the welding process is analyzed, and the heat conduction path is optimized to avoid welding defects caused by heat accumulation. Significance: The non-linear mapping analysis breaks through the limitations of traditional linear relationships and realizes multi-dimensional optimization of the electrode performance; by optimizing the heat conduction efficiency, it ensures that heat can be efficiently transferred to the weld area during the welding process, while avoiding local overheating or structural deformation of the electrode, providing technical support for the precise control of the welding process. In step S202333, the determination of the proportional relationship and the comprehensive optimization of performance, through the above steps, a proportional relationship is obtained to ensure the comprehensive optimization of the electrode in terms of structural strength, coating covering effect, arc stability, and heat conduction efficiency; the structural strength meets the mechanical performance requirements under the welding conditions, the coating covering effect ensures the protection performance of the welding area, the arc stability improves the welding quality, and the heat conduction efficiency optimizes the heat management. Significance: The determination of the proportional relationship provides a comprehensive performance optimization goal for electrode design, achieving the comprehensive balance of structural strength, protection performance, arc stability, and heat conduction efficiency; it breaks through the limitations of single-objective design in traditional parameter optimization and provides an efficient and reliable technical solution for the welding process.

[0121] In summary, in this embodiment, by redefining the proportional relationship between the reference diameter and the coating thickness, the systematic optimization of the performance of the welding electrode is achieved. It not only improves the mechanical properties and process stability of the welding electrode under welding conditions, but also provides important technical support for the innovation of the welding process; ensuring the comprehensive optimization of the welding electrode in terms of structural strength, coating coverage effect, arc stability and heat conduction efficiency.

[0122] Example 9: As Figure 9 shown, on the basis of Example 1, the confirmation process of the termination condition provided by the embodiment of the present invention includes the following steps:

[0123] S301: Statistically analyze the fitness value of each individual in the current population in a certain iteration, and compare it with the fitness value in the previous iteration close to the certain iteration, and calculate its absolute difference; divide the sum of the fitness change differences of all individuals by the population size, and then divide by the maximum fitness value in the current population to obtain the normalized average fitness change rate; if the average fitness change rate is less than or equal to the preset convergence threshold, it is considered that the fitness has tended to be stable and the convergence state has been reached;

[0124] S302: For each dimension of the optimization problem, calculate the deviation between the value of all individuals in the population in this dimension and the average value, sum the squares of the deviations of each dimension, and then divide by the population size to obtain the variance of the dimension; sum and take the square root of the variances of all dimensions to obtain the population diversity index. If the diversity index is less than the preset diversity threshold, it is considered that the population diversity is insufficient and the iteration needs to be terminated in advance;

[0125] S303: Convert the fitness convergence determination, population diversity determination and maximum iteration number determination into logical expressions respectively, and combine them through the logical "OR" operator; if any logical expression returns "True", set the termination flag, indicating that the termination condition is met and the iteration should be stopped.

[0126] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, first, the fitness value of each individual in the current population in a certain iteration is statistically calculated and compared with the fitness value in the previous iteration close to the certain iteration, and its absolute difference is calculated; the sum of the fitness change differences of all individuals is divided by the population size and then divided by the maximum fitness value in the current population to obtain the normalized average fitness change rate; if the average fitness change rate is less than or equal to the preset convergence threshold, it is considered that the fitness has tended to be stable and the convergence state has been reached; secondly, for each dimension of the optimization problem (electrode diameter, coating thickness), the deviation between the value taken by all individuals in the population in this dimension and the average value is calculated, the squares of the deviations of each dimension are summed and then divided by the population size to obtain the variance of the dimension; the variances of all dimensions are summed and square-rooted to obtain the diversity index of the population. If the diversity index is less than the preset diversity threshold, it is considered that the population diversity is insufficient and the iteration needs to be terminated in advance; finally, the fitness convergence determination, population diversity determination, and maximum iteration number determination are respectively converted into logical expressions and combined through the logical "OR" operator; if any logical expression returns "True", the termination flag is set, indicating that the termination condition is met and the iteration should be stopped. Step S301 of the above solution evaluates whether the algorithm is close to convergence by monitoring the change of the fitness of individuals in the population; specifically, by comparing the fitness values of the current iteration and the previous iteration, the average value of the fitness change is calculated and normalized; normalization is to make the result unaffected by the population size and the range of fitness values and make it comparable; if the normalized average fitness change rate is lower than the preset threshold, it indicates that the population fitness is stable and the algorithm converges; a quantitative convergence criterion is provided to ensure that the algorithm can stop in time when finding an approximate optimal solution and avoid resource waste. Step S302 measures the diversity of the population. By calculating the variance in each dimension, the distribution of the population in each dimension can be understood; the square root of the sum of the variances of all dimensions is obtained, and the diversity index reflects the overall diversity level of the population; if the diversity index is lower than the preset threshold, it is considered that the population diversity is insufficient and the iteration needs to be terminated in advance; it can prevent the algorithm from prematurely falling into a local optimal solution and ensure that the algorithm can explore different regions of the solution space, thereby increasing the possibility of finding the global optimal solution. Step S303 integrates the three termination conditions of fitness convergence, population diversity, and maximum iteration number, and decides whether to terminate the iteration through the logical "OR" operator; as long as any termination condition is met, the algorithm will stop iterating; a comprehensive termination mechanism is provided to ensure that the algorithm can find a satisfactory solution while avoiding unnecessary computational overhead and preventing the algorithm from falling into an infinite loop.

[0127] In summary, this embodiment constitutes a multi-dimensional termination condition judgment mechanism, aiming to balance the convergence speed of the algorithm and the quality of the solution, ensuring that the algorithm can find a satisfactory solution within a reasonable time and maintain sufficient exploration ability to avoid falling into local optima.

[0128] Embodiment 10: As Figure 10 shown, based on Embodiments 1 - 9, the electrode diameter and coating thickness matching system provided by the embodiment of the present invention includes:

[0129] A population generation module, responsible for determining the matching objectives and constraints of the electrode diameter and coating thickness, converting the matching objectives and constraints into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generating a set of random combinations of electrode diameter and coating thickness as the initial population;

[0130] A crossover operation module, responsible for performing fitness evaluation on the objective function to measure the quality of each combination of electrode diameter and coating thickness; the fitness evaluation includes factors such as welding quality, process efficiency, and cost; selecting excellent individuals from the current population to enter the next generation according to the fitness evaluation results; combining the genes of the excellent individuals through crossover operations to generate new individuals;

[0131] An iterative termination module, responsible for repeating the fitness evaluation, selection, and crossover operations until the termination conditions are met; finally, selecting the combination of electrode diameter and coating thickness with the highest fitness as the optimal solution.

[0132] The working principle and beneficial effects of the above technical solution are as follows: The population generation module in this embodiment determines the matching target and constraint conditions for the electrode diameter and the coating thickness, converts the matching target and constraints into a quantifiable mathematical model, and uses it as the objective function and constraint function of the genetic algorithm; generates a set of random combinations of electrode diameters and coating thicknesses as the initial population; the crossover operation module performs fitness evaluation on the objective function to measure the quality of each combination of electrode diameter and coating thickness; the fitness evaluation includes factors such as welding quality, process efficiency, and cost; selects excellent individuals from the current population to enter the next generation according to the fitness evaluation results; combines the genes of the excellent individuals through crossover operations to generate new individuals; the iteration termination module repeats the fitness evaluation, selection, and crossover operations until the termination conditions are met; finally, selects the combination of electrode diameter and coating thickness with the highest fitness as the optimal solution. The population generation module of the above solution provides an initial solution for the genetic algorithm and lays a foundation for subsequent fitness evaluation, selection, and crossover operations; reasonably defining the objective function and constraint function can guide the genetic algorithm to search in the optimized direction, improving the effectiveness and accuracy of the algorithm. The crossover operation module continuously optimizes the population through fitness evaluation and genetic operations, screening out better combinations of electrode diameter and coating thickness; during the iteration process, it can gradually approach the global optimal solution, improving the matching accuracy and efficiency. The iteration termination module controls the iteration process of the algorithm to avoid resource waste caused by infinite iteration. At the same time, when the termination conditions are met, selects the combination of electrode diameter and coating thickness with the highest fitness as the optimal solution to provide guidance for actual welding production.

[0133] In summary, each module of the electrode diameter and coating thickness matching system based on the genetic algorithm in this embodiment cooperates with each other. By reasonably defining the objective function and constraint conditions, continuously optimizing the population, and controlling the iteration process, etc., it can finally automatically find the optimal combination of electrode diameter and coating thickness, improve welding quality, process efficiency, and cost-effectiveness, and has high engineering application value.

[0134] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the equivalent technology of the present invention, the present invention also intends to include these changes and modifications.

Claims

1. A method for matching electrode diameter and coating thickness based on genetic algorithm, characterized in that: The following steps are involved: Determine the matching target and constraint conditions of electrode diameter and coating thickness, and transform the matching target and constraint into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generate a set of random combinations of electrode diameter and coating thickness as the initial population; The fitness evaluation of the objective function is used to measure the advantages and disadvantages of each combination of electrode diameter and coating thickness; the fitness evaluation includes welding quality, process efficiency and cost factors; according to the fitness evaluation results, excellent individuals are selected from the current population to enter the next generation; the genes of excellent individuals are combined through crossover operation to generate new individuals; Repeat the fitness evaluation, selection and crossover operations until the termination condition is met; finally, the electrode diameter and coating thickness combination with the highest fitness is selected as the optimal solution.

2. The method for matching electrode diameter and coating thickness based on genetic algorithm according to claim 1, characterized in that: The process of generating a set of random electrode diameter and coating thickness combinations as the initial population includes the following steps: Determine the population size, that is, the number of individuals that need to be generated; For each individual, the base angle, random weight coefficient and random phase parameters of the electrode diameter and coating thickness are randomly generated; Calculate the electrode diameter and coating thickness, generate individual electrode diameter and coating thickness combinations; use the generated individuals as the initial population.

3. The method for matching electrode diameter and coating thickness based on genetic algorithm according to claim 1, characterized in that: The process of combining the genes of excellent individuals through crossover operation includes the following steps: Select a combination of electrode diameter and coating thickness with high fitness from the current population as a parent individual; disassemble and reassemble the parameter information of the electrode diameter and coating thickness of the selected parent individual to form a new individual; In the crossover process, the electrode diameter parameter of one parent individual is combined with the coating thickness parameter of another parent individual to form a new combination; The new set of individuals generated by the crossover operation will serve as candidates for the next generation population and continue to be evaluated and optimized for fitness.

4. The method for matching electrode diameter and coating thickness based on genetic algorithm as claimed in claim 3, characterized in that: The process of obtaining the fitness evaluation results includes the following steps: Collect real-time data, including welding quality, process efficiency and cost multi-dimensional indicators; standardize the collected multi-dimensional indicators; Different weight coefficients are assigned to welding quality, process efficiency and cost indicators, and multiple indicators are integrated into a single fitness value through weighted comprehensive calculation; the standardized multi-dimensional indicator values ​​are substituted into the weighted comprehensive formula to calculate the fitness value of each combination of electrode diameter and coating thickness; All individuals are sorted according to their fitness values. Individuals with higher fitness values ​​are considered to be better. After sorting, individuals with higher fitness values ​​are selected as parents to enter the next generation for crossover operation.

5. The method for matching electrode diameter and coating thickness based on genetic algorithm as claimed in claim 3, characterized in that: The process of combining the electrode diameter parameters of one parent individual with the coating thickness parameters of another parent individual consists of the following steps: Select two parent individuals with stronger adaptability from the current population, each of which has a welding rod diameter and coating thickness combination parameter; separate the welding rod diameter parameter and the coating thickness parameter from the parent individuals by disassembly; The electrode diameter parameter of the first parent individual selected will be extracted and used as the reference diameter of the new individual; at the same time, the coating thickness parameter of the second parent individual will be used as the key parameter of the coating thickness; The welding rod diameter parameter and the coating thickness parameter are merged, and the functional matching between the merged welding rod diameter and the coating thickness is re-performed.

6. The method for matching electrode diameter and coating thickness based on genetic algorithm as claimed in claim 5, characterized in that: The process of combining the electrode diameter parameter and the coating thickness parameter includes the following steps: The electrode diameter parameters and coating thickness parameters were separated from the two selected parent individuals, and the reference diameter and critical coating thickness were preliminarily evaluated to determine the physical properties and functional boundaries; Through dynamic evaluation of the reference diameter and combined with the parameter characteristics of the coating thickness, the diameter value range is adjusted; The matching of the reference diameter and the coating thickness is based on the nonlinear mapping of the physical properties of the welding material. By redefining the proportional relationship between the reference diameter and the coating thickness, the structural strength of the welding rod, the coating coverage effect, the arc stability and the thermal conduction efficiency of the welding rod are ensured.

7. The method for matching electrode diameter and coating thickness based on genetic algorithm as claimed in claim 6, characterized in that: The process of determining physical characteristics and functional boundaries includes the following steps: Extract the electrode diameter parameters and coating thickness parameters from the selected basic data source as the initial reference values ​​of the reference diameter and the key coating thickness; quantitatively analyze the geometric characteristics and mass distribution of the reference diameter to determine the functional boundary in the welding process; Systematic analysis of the functional characteristics of key coating thicknesses. The functional boundaries include the protection effect on the welding area, as well as the regulation of arc stability and heat conduction efficiency. The functional boundaries in high-temperature welding environments are determined by analyzing the thermodynamic response of coating thickness during welding. Combining the principle of material structure and function coupling, the synergistic relationship between the reference diameter and the key coating thickness is analyzed; By introducing the interface mechanics theory, the interface action mechanism between the reference diameter and the coating thickness is analyzed, and the proportional range under welding conditions is determined; by combining the heat conduction law with the fluid flow characteristics, the heat transfer efficiency of the electrode during the welding process is analyzed.

8. The method for matching electrode diameter and coating thickness based on genetic algorithm as claimed in claim 6, characterized in that: The process of redefining the proportional relationship between the reference diameter and the coating thickness includes the following steps: Combined with the physical characteristics of the coating thickness, the value range of the reference diameter is dynamically adjusted; the interaction between the coating thickness and the reference diameter is analyzed to determine the proportional range under working conditions; Based on the physical properties of welding materials, nonlinear mapping analysis is performed on the reference diameter and coating thickness. The adjustment of the reference diameter simultaneously considers the influence of coating thickness on its coverage effect. By introducing the basic principles of thermodynamics and fluid mechanics, the heat conduction efficiency of the welding rod during welding is analyzed; The proportional relationship is obtained to ensure that the welding rod achieves comprehensive optimization in terms of structural strength, coating coverage, arc stability and heat conduction efficiency.

9. The method for matching electrode diameter and coating thickness based on genetic algorithm according to claim 1, characterized in that: The confirmation process of the termination condition includes the following steps: Count the fitness value of each individual in the current population in a certain iteration, compare it with the fitness value in the previous iteration close to a certain iteration, and calculate the absolute difference; The sum of the fitness change differences of all individuals is divided by the population size, and then divided by the maximum fitness value in the current population to obtain the normalized average fitness change rate; if the average fitness change rate is less than or equal to the preset convergence threshold, it is considered that the fitness has stabilized and reached a convergence state; For each dimension of the optimization problem, calculate the deviation between the values ​​of all individuals in the population on that dimension and the average value, square the deviation of each dimension, sum it up, and divide it by the population size to get the variance of the dimension; sum the variances of all dimensions and take the square root to get the diversity index of the population. If the diversity index is less than the preset diversity threshold, it is considered that the population diversity is insufficient and the iteration needs to be terminated early. The fitness convergence judgment, population diversity judgment and maximum iteration number judgment are converted into logical expressions respectively and combined by logical or operator; if any logical expression returns True, the termination flag is set, indicating that the termination condition is met and the iteration should be stopped.

10. A welding rod diameter and coating thickness matching system based on genetic algorithm, characterized in that: Include: The population generation module is responsible for determining the matching target and constraint conditions of electrode diameter and coating thickness, converting the matching target and constraint into a quantifiable mathematical model as the objective function and constraint function of the genetic algorithm; generating a set of random combinations of electrode diameter and coating thickness as the initial population; The crossover operation module is responsible for evaluating the fitness of the objective function, which is used to measure the advantages and disadvantages of each combination of electrode diameter and coating thickness. The fitness evaluation includes welding quality, process efficiency and cost factors. According to the fitness evaluation results, excellent individuals are selected from the current population to enter the next generation. The genes of excellent individuals are combined through crossover operation to generate new individuals. The iterative termination module is responsible for repeating fitness evaluation, selection and crossover operations until the termination condition is met; finally, the electrode diameter and coating thickness combination with the highest fitness is selected as the optimal solution.

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