Chain link forming method and platform in saw chain production

Abstract

The invention provides a chain link forming method and platform in saw chain production, and relates to the technical field of chain link stamping machining.The chain link forming method comprises the steps that matching selection is conducted in a stamping die type selection library based on expected fit tolerance, and multiple sets of adaptive stamping dies are determined and comprise connecting pin stamping dies and connecting hole stamping dies; the maximum matching precision serves as an optimization target, optimization is conducted on the stamping machining parameters of the multiple sets of matched stamping dies, the stamping machining combination with the maximum fitness is output and set as the optimal machining combination, and the optimal machining combination comprises the optimal stamping die set and the optimal stamping parameters; and through the optimal stamping die set, stamping machining is conducted according to the optimal stamping parameters. By means of the chain link stamping machining method, the technical problem that according to a traditional chain link stamping machining method, the matching precision between a connecting pin and a connecting hole is unstable, and then the use performance of a chain link is affected can be solved, the precision tolerance can be effectively controlled, the matching precision of the connecting pin and the connecting hole is improved, and the stability and durability of a saw chain in the use process are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of chain link stamping processing, and in particular to a chain link forming method and platform in saw chain production. Background Art

[0002] Chain saw is a common garden tool. One of its core components is the chain. The chain is composed of multiple links, and each link is connected by a connecting pin and a connecting hole. The matching accuracy of the connecting pin and the connecting hole directly affects the assembly accuracy, working stability and service life of the chain. Therefore, ensuring the matching accuracy between the connecting pin and the connecting hole in the chain link is one of the key technologies in chain manufacturing.

[0003] At present, in the traditional chain link stamping process, the processing of connecting pins and connecting holes usually relies on standardized molds and set stamping processing parameters. However, due to the complexity of the stamping process, mold wear, changes in usage scenarios and other reasons, the traditional method has the problem of unstable matching accuracy between the connecting pins and connecting holes. Summary of the invention

[0004] The purpose of this application is to provide a chain link forming method and platform in saw chain production, so as to solve the technical problem that the matching accuracy between the connecting pin and the connecting hole is unstable in the traditional chain link stamping processing method, thereby affecting the performance of the chain link.

[0005] In view of the above problems, the present application provides a chain link forming method and platform in saw chain production.

[0006] In the first aspect, the present application provides a chain link forming method in saw chain production, which is implemented by a chain link forming platform in saw chain production, including: obtaining the chain saw product attributes and usage scenarios of the target saw chain, and performing quantitative analysis on the connection requirements of the connecting pins and connecting holes of the target chain links according to the chain saw product attributes and usage scenarios, and determining the expected fitting tolerance; matching and selecting in a stamping die selection library based on the expected fitting tolerance, and determining multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die; taking maximizing the fitting accuracy as the optimization goal, optimizing the stamping processing parameters of the multiple groups of matching stamping dies respectively, and outputting the stamping processing combination with the greatest fitness as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die group and optimal stamping parameters; through the optimal stamping die group, performing stamping processing of the connecting pins and connecting holes of the target chain links according to the optimal stamping parameters.

[0007] In the second aspect, the present application also provides a chain link forming platform in saw chain production, which is used to execute a chain link forming method in saw chain production as described in the first aspect, including: a demand quantification analysis module, which is used to obtain the chain saw product attributes and usage scenarios of the target saw chain, and perform a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain links according to the chain saw product attributes and usage scenarios, and determine the expected fitting tolerance; an adaptive stamping die determination module, which is used to match and select in the stamping die selection library based on the expected fitting tolerance, and determine multiple groups of adaptive stamping dies, wherein each group of adaptive stamping dies includes a connecting pin stamping die and a connecting hole stamping die; a stamping processing combination optimization module, which is used to optimize the stamping processing parameters of the multiple groups of adaptive stamping dies respectively with maximizing the fitting accuracy as the optimization goal, and output the stamping processing combination with the largest fitness as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die group and an optimal stamping parameter; a chain link stamping processing module, which is used to perform stamping processing of the connecting pins and connecting holes of the target chain link according to the optimal stamping parameters through the optimal stamping die group.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: By acquiring the chain saw product attributes and usage scenarios of the target saw chain, a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain link is performed according to the chain saw product attributes and usage scenarios to determine the expected matching tolerance; matching and selection are performed in the stamping die selection library based on the expected matching tolerance to determine multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die; with maximizing the matching accuracy as the optimization goal, the stamping processing parameters of the multiple groups of matching stamping dies are optimized respectively, and the stamping processing combination with the greatest adaptability is output as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die group and an optimal stamping parameter; through the optimal stamping die group, the connecting pins and connecting holes of the target chain link are stamped according to the optimal stamping parameters, that is, by optimizing the stamping process and die selection, the precision tolerance can be effectively controlled, and the matching accuracy of the connecting pins and connecting holes can be improved, thereby effectively improving the product quality of the chain link and ensuring the stability and durability of the saw chain during use.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0011] Figure 1 A schematic diagram of a process flow of a chain link forming method in saw chain production in the present application; Figure 2 This is a schematic structural diagram of a chain link forming platform in saw chain production in the present application.

[0012] Description of reference numerals: Demand quantification analysis module 11, adaptive stamping die determination module 12, stamping processing combination optimization module 13, chain link stamping processing module 14. DETAILED DESCRIPTION

[0013] This application provides a chain link forming method and platform in saw chain production, which solves the technical problem that the matching accuracy between the connecting pin and the connecting hole in the traditional chain link stamping processing method is unstable, thereby affecting the performance of the chain link. By optimizing the stamping process and mold selection, the precision tolerance can be effectively controlled, and the matching accuracy between the connecting pin and the connecting hole can be improved, thereby effectively improving the product quality of the chain link and ensuring the stability and durability of the saw chain during use.

[0014] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0015] For example, please refer to the attached Figure 1 The present application provides a chain link forming method in saw chain production, which is applied to a chain link forming platform in saw chain production, and specifically comprises the following steps: Step 1: Obtain the chainsaw product attributes and usage scenarios of the target saw chain, perform a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain links based on the chainsaw product attributes and usage scenarios, and determine the expected matching tolerance.

[0016] Furthermore, step one of this application also includes: Taking the chain saw product attributes and usage scenarios as feature constraints, the matching tolerances of connecting pins and connecting holes are retrieved based on big data to determine the sample matching tolerance set and the sample working time set; the sample matching tolerances whose sample working time meets the expected qualified working time are selected, and the standard sample matching tolerance set is obtained after redundant processing, and the sample surplus time mean set and the sample data frequency set are calculated; the adaptation weight is set based on the sample surplus time mean, and the sample data frequency set is optimized and corrected according to the adaptation weight set to determine the corrected data frequency set; the standard sample matching tolerance corresponding to the maximum data frequency in the corrected data frequency set is selected and set as the expected matching tolerance.

[0017] Specifically, first, the chain saw product attributes and usage scenarios of the target saw chain are obtained, among which the chain saw product attributes include chain type (circular saw chain, bow saw chain, step saw chain, etc., each chain has different design and usage requirements, so the matching tolerances of the connecting pins and connecting holes may be different), chain link structure (composed of multiple small components, such as chain teeth, chain link plates, connecting pins, etc.), etc.; usage scenarios include workload (working frequency, load size, operating intensity, etc.), working environment (such as gardening, high temperature, high humidity, etc.), etc. In modern manufacturing, using big data technology to conduct in-depth analysis of the attributes and usage scenarios of chain saw products to optimize the matching tolerances of connecting pins and connecting holes has become an important means to improve product performance and extend service life. Through big data analysis, corresponding processing tolerances can be accurately formulated according to different chain saw types, usage environments and operating requirements to ensure the efficient operation and durability of the chain. Next, taking the chain saw product attributes and usage scenarios as feature constraints, the fitting tolerances of the connecting pins and connecting holes are retrieved based on big data to obtain sample fitting tolerance sets and sample working time sets. The fitting tolerance refers to the connecting pin diameter and the connecting hole aperture tolerance, and the working time refers to the normal service life of the product.

[0018] Configure the expected qualified working time, which refers to the target working time set according to the usage scenario and product performance requirements of the chain saw. For example, the chain is expected to work stably for more than a certain number of hours under high load and high-speed cutting. Then, multiple sample working times in the sample working time set are screened according to the expected qualified working time, and sample matching tolerances whose sample working time is greater than the expected qualified working time are selected, and the sample matching tolerances with the same values ​​are processed redundantly, that is, the sample matching tolerances with the same values ​​are grouped into one category to obtain a standard sample matching tolerance set, and the number of data of each standard sample matching tolerance in the sample matching tolerance set is counted, which is set as the sample data frequency. The sample data frequency reflects the frequency of occurrence of each matching tolerance in the actual usage scenario, and the sample data frequency set is obtained. Then, for each standard sample fit tolerance, its mean surplus time needs to be calculated. The surplus time refers to the part of the actual working time that exceeds the expected qualified working time under a given fit tolerance, and the sample surplus time mean set is obtained. The surplus time mean can reflect the performance of each type of fit tolerance in actual use that exceeds the expected working time, thereby helping to evaluate the durability and stability of different fit tolerances.

[0019] Next, the adaptation weight is set based on the mean value of the sample surplus time, wherein the mean value of the sample surplus time is positively correlated with the adaptation weight, that is, the larger the mean value of the sample surplus time, the larger the corresponding adaptation weight, and vice versa, the lower the adaptation weight, that is, the longer the surplus time, the greater the matching tolerance indicates that the expected working time can be exceeded during operation, which is more conducive to improving the durability and stability of the chain saw chain link; the adaptation weight set is obtained, wherein the adaptation weight corresponds to the standard sample matching tolerance and the sample data frequency. Then, the sample data frequency set is optimized and corrected according to the adaptation weight set, that is, the adaptation weight is multiplied by the corresponding sample data frequency, and the product of the two is used as the correction data frequency to obtain the correction data frequency set. The goal of frequency correction is to ensure that the application and distribution of the sample matching tolerance matches the actual work requirements by adjusting the sample data frequency, and the optimized data frequency can reflect the actual application effect of the matching tolerance.

[0020] Finally, the standard sample matching tolerance corresponding to the maximum data frequency in the correction data frequency set is selected as the expected matching tolerance (e.g., 0.015 mm to 0.035 mm). By selecting the standard sample matching tolerance corresponding to the maximum data frequency as the expected matching tolerance, the matching accuracy can be maximized, and the matching effect between the connecting pin and the connecting hole of the chain saw chain during use can be improved. This matching tolerance can provide the best matching effect under the same working environment, ensuring the reliability and durability of the chain saw chain.

[0021] Step 2: Based on the expected matching tolerance, matching selection is performed in the stamping die selection library to determine multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die.

[0022] Furthermore, step 2 of this application also includes: A stamping die selection library is obtained, wherein the stamping die selection library contains a plurality of connecting pin stamping dies and connecting hole stamping dies of different sizes and shapes; and matching selection is performed in the stamping die selection library to obtain a plurality of groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping dies and a connecting hole stamping dies of the same shape, and the matching tolerance of each group of matching stamping dies is smaller than the expected matching tolerance in order to meet the expected matching tolerance.

[0023] Specifically, first, a stamping die selection library is obtained, wherein the stamping die selection library can be set according to the actual processing scenario, and includes connecting pin stamping dies and connecting hole stamping dies of multiple sizes (such as inner and outer diameters, lengths, depths, etc.) and shapes (such as round, conical, etc.).

[0024] In the production of chain saw chain links, the processing accuracy of the connecting pins and connecting holes has an important impact on the performance of the entire chain link. In order to ensure that the matching accuracy meets the expected requirements, accurate mold selection and matching of matching tolerances must be performed. Next, based on the expected matching tolerance requirements, qualified molds are retrieved and selected in the mold selection library. When selecting, it is necessary to ensure that the processing accuracy of the selected mold meets the matching tolerance requirements, and multiple sets of matching stamping molds are obtained, wherein each set of matching stamping molds includes a connecting pin stamping mold and a connecting hole stamping mold of the same shape, that is, the selected connecting pin mold and connecting hole mold should have similar shape designs and can be matched in the same production process; and the matching tolerance of each set of matching stamping molds is less than the expected matching tolerance. By matching and screening molds according to the expected matching tolerance in the stamping mold selection library, it is ensured that the matching tolerance of each set of matching molds is less than the expected matching tolerance, thereby achieving higher processing accuracy and ensuring the precise matching of the connecting pin and the connecting hole.

[0025] Step three: Taking maximizing the matching accuracy as the optimization goal, optimize the stamping processing parameters of the multiple groups of matching stamping dies respectively, and output the stamping processing combination with the greatest adaptability as the optimal processing combination, wherein the optimal processing combination includes the optimal stamping die group and the optimal stamping parameters.

[0026] Furthermore, step three of this application also includes: Obtain material properties of the material to be processed, wherein the material properties include material hardness and material elasticity; randomly select a first group of adaptive stamping dies from the multiple groups of adaptive stamping dies, wherein the first group of adaptive stamping dies includes a first connecting pin die and a first connecting hole die; obtain a stamping process parameter space, and randomly select multiple initial stamping parameters, wherein the stamping process parameters include stamping pressure, stamping stroke and stamping speed.

[0027] Specifically, first, the material properties of the material to be processed (such as alloy steel, etc.) are obtained, where the material properties include material hardness and material elasticity. The hardness of the material refers to its ability to resist local plastic deformation (such as indentation or scratching). Materials of different hardness have an important influence on the wear of the stamping die, the demand for stamping force and the selection of the die; material elasticity refers to the ability of the material to restore its original shape when subjected to external force, which is usually expressed by the Young's modulus (elastic modulus) of the material. Materials with greater elasticity will have greater elastic rebound during the stamping process (that is, the ability of the material to recover after deformation), which affects the dimensional accuracy after stamping.

[0028] Next, any group of adaptive stamping dies is randomly selected from the multiple groups of adaptive stamping dies as the first group of adaptive stamping dies, wherein the first group of adaptive stamping dies includes a first connecting pin die and a first connecting hole die. Further obtain the stamping processing parameter space, wherein the stamping processing parameters include stamping pressure, stamping stroke and stamping speed, and the stamping processing parameter space refers to the range of all possible stamping parameter combinations, which can be set based on the stamping equipment type and material properties; then randomly select multiple initial stamping parameters in the stamping processing parameter space, usually by randomly selecting multiple initial parameter combinations in the stamping parameter space, random selection can ensure that a larger stamping parameter space is covered, and increase the probability of finding the optimal parameter combination, such as, within the upper and lower limits of the stamping parameters, uniformly and randomly selecting multiple parameter combinations to avoid too many or too few selections in a certain area.

[0029] Perform a stamping process simulation according to the material hardness, material elasticity, the first connecting pin mold, the first connecting hole mold and a plurality of initial stamping parameters, and output a plurality of first simulated connecting pin diameters and a plurality of first simulated connecting hole apertures; Furthermore, the present application also includes the following steps: Collect the first connecting pin mold attributes of the first connecting pin mold and the first connecting hole mold attributes of the first connecting hole mold, wherein the mold attributes include shape, size and wear feature distribution, and the wear feature distribution can be obtained by extracting features from the mold image; use the material hardness and material elasticity as material constraints, and the first connecting pin mold attributes and the first connecting hole mold attributes as feature constraints, retrieve the stamping process log, and collect sample stamping parameter sets, sample connecting pin diameter sets and sample connecting hole aperture sets; use sample stamping parameters as input, and sample connecting pin diameters and sample connecting hole apertures as supervision, and use the sample stamping parameter sets, sample connecting pin diameter sets and sample connecting hole aperture sets to supervise the BP neural network until convergence to obtain a stamping process simulation plug-in; use the stamping process simulation plug-in to simulate the stamping process for the multiple initial stamping parameters, and output multiple first simulated connecting pin diameters and multiple first simulated connecting hole apertures.

[0030] Specifically, first, the first connecting pin mold attributes of the first connecting pin mold and the first connecting hole mold attributes of the first connecting hole mold are collected, wherein the mold attributes include shape, size and wear feature distribution, and the mold shape refers to the appearance and geometric structure of the mold, usually including the shape contours of the connecting pin mold and the connecting hole mold. The shape attribute determines the contact method between the mold and the material during the stamping process, thereby affecting the processing accuracy; the mold size refers to the various dimensional indicators of the mold, such as the diameter, thickness, aperture, etc. of the mold. These dimensions directly determine the accuracy requirements of the connecting pins and connecting holes after forming, affecting the fitting tolerance and product quality; the wear feature distribution can be obtained by extracting features from the mold image. Wear will cause the size of the mold to change, thereby affecting the stamping accuracy. The wear feature distribution includes the wear distribution area (common wear types include flattening, pits, cracks, etc.), wear depth and area, etc.

[0031] Next, taking the material hardness and material elasticity as material constraints and the first connecting pin mold attributes and the first connecting hole mold attributes as feature constraints, the stamping processing log of the stamping equipment is retrieved, sample stamping parameters related to the target processing conditions are selected, and the sample stamping parameter set, as well as the sample connecting pin diameter set and the sample connecting hole aperture set processed using the sample stamping parameters are collected and acquired.

[0032] Furthermore, a stamping process simulation plug-in is constructed based on a BP neural network. The stamping process simulation plug-in is a BP neural network model that can be iteratively optimized in machine learning, including an input layer, multiple hidden layers and an output layer, wherein the input data of the input layer is the stamping parameters, and the output data of the output layer is the connecting pin diameter and the connecting hole aperture; then, the sample stamping parameters are used as input, the sample connecting pin diameter and the sample connecting hole aperture are used as supervision, and the sample stamping parameter set, the sample connecting pin diameter set and the sample connecting hole aperture set are used as training data to perform supervised training on the stamping process simulation plug-in. First, the input data (stamping parameters) is predicted by the model, and the predicted values ​​of the connecting pin diameter and the connecting hole aperture are output; then, the error (such as mean square error) between the predicted value and the true value is calculated, and then the model parameters are updated through a back propagation algorithm or other optimization algorithms (such as gradient descent) to minimize the error; iterative training is continued, and in each iteration, the model is adjusted and optimized using the training data until the loss function converges, and the trained stamping process simulation plug-in is output. By performing stamping process simulation based on BP neural network, the intelligence, efficiency and accuracy of stamping process simulation can be improved.

[0033] Finally, the stamping process simulation plug-in is used to perform stamping process simulation on the multiple initial stamping parameters, and multiple first simulated connecting pin diameters and multiple first simulated connecting hole apertures are output.

[0034] A plurality of fitting adaptabilities are calculated and determined according to the plurality of first simulated connection pin diameters and the plurality of first simulated connection hole diameters.

[0035] Furthermore, the present application also includes the following steps: Subtract the diameters of the multiple first simulated connecting pins from the diameters of the multiple first simulated connecting holes to obtain multiple simulated fitting deviations; randomly select a first simulated fitting deviation, calculate a first fitting fitness based on the first simulated fitting deviation and a benchmark fitting deviation, and add the first fitting fitness to the multiple fitting fitnesses, wherein the first fitting fitness is the inverse of the absolute value of the difference between the first simulated fitting deviation and the benchmark fitting deviation.

[0036] Specifically, first, the diameters of the multiple first simulated connection holes are respectively subtracted from the diameters of the multiple first simulated connection pins, that is, the diameters of the first simulated connection holes are subtracted from the corresponding first simulated connection pins, and the difference between the two is set as the simulated fit deviation to obtain multiple simulated fit deviations. Then, a first simulated fit deviation is randomly selected from the multiple simulated fit deviations, and a first fit fitness is calculated based on the first simulated fit deviation and the reference fit deviation (the reference fit deviation is a set target value, usually representing the fit accuracy of the ideal connection pin and the connection hole), wherein the first fit fitness is the reciprocal of the absolute value of the difference between the first simulated fit deviation and the reference fit deviation, and the first fit fitness is obtained. The larger the fit fitness, the better the stamping effect that characterizes the stamping processing parameters; and multiple fit fitnesses of multiple simulated fit deviations are obtained in sequence using the same method.

[0037] Taking the stamping process parameter space as a constraint, the stamping process parameters are iteratively optimized according to the multiple matching fitnesses, and the first optimal stamping process parameters are output. The first stamping process combination is obtained in combination with the first group of matching stamping dies, wherein the first stamping process combination is marked with a first combination fitness, and the first combination fitness is the matching fitness of the first optimal stamping process parameter; multiple groups of stamping process combinations and multiple combination fitnesses are obtained in turn, and the stamping process combination with the maximum combination fitness is selected as the optimal processing combination.

[0038] Furthermore, the present application also includes the following steps: The initial stamping parameters are marked as initial solutions, and the multiple initial solutions are arranged from large to small according to the multiple matching fitnesses to construct an initial solution sequence; the first M solutions of the initial solution sequence are selected as good solutions, and the last P solutions are set as differential solutions, wherein the sum of M and P is the number of initial solutions, P is Q times of M, and Q is an integer greater than 10 and less than 50; based on the M good solutions, the P differential solutions are randomly clustered to obtain M solution sets, and in each solution set, the good solution is used as the optimization direction, and the differential solutions in the solution set are adjusted once according to the adaptive optimization step length to obtain M updated solution sets, wherein if the updated differential solution does not satisfy the stamping process parameter space, this adjustment is not performed.

[0039] Specifically, first, the initial stamping parameters are marked as initial solutions to obtain multiple initial solutions, and then the multiple initial solutions are arranged from large to small according to the multiple matching fitnesses to construct an initial solution sequence; further, the first M solutions of the initial solution sequence are selected as good solutions, and the last P solutions are set as differential solutions, wherein the sum of M and P is the number of initial solutions, P is Q times of M, Q is an integer greater than 10 and less than 50, and the values ​​of M and P can be set according to the number of initial solutions. Next, based on the M good solutions, the P differential solutions are randomly clustered and divided to obtain M solution sets, wherein the number of differential solutions in each solution set is the same; then, in each solution set, the good solution is used as the optimization direction, and the differential solutions in the solution set are adjusted once according to the adaptive optimization step length, wherein, if the updated differential solution does not satisfy the stamping processing parameter space, this adjustment is not performed, and M updated solution sets are obtained.

[0040] Furthermore, the present application also includes the following steps: For each solution set, the fitness of the good solutions in the solution set and the fitness deviations of multiple poor solutions are calculated respectively to obtain multiple fitness differences; the maximum fitness difference among the multiple fitness differences is selected, and the ratios of the multiple fitness differences to the maximum fitness difference are calculated respectively to obtain multiple precision compensation coefficients; the multiple precision compensation coefficients are multiplied by the initial optimization step length to obtain multiple compensated optimization step lengths as the adaptive optimization step length of each solution set.

[0041] Specifically, for each solution set, the fitness of the good solution in the solution set and the fitness deviation of multiple poor solutions are calculated respectively to obtain multiple fitness differences; then, the maximum fitness difference among the multiple fitness differences is selected, and the ratios of the multiple fitness differences to the maximum fitness difference are calculated respectively, and the ratios are set as the accuracy compensation coefficient to obtain multiple accuracy compensation coefficients, which represent the accuracy requirements relative to the maximum deviation, that is, the larger the fitness difference, the larger the corresponding compensation coefficient.

[0042] The initial optimization step length is obtained, and the initial optimization step length includes the stamping pressure adjustment step length, the stamping stroke adjustment step length, and the stamping speed adjustment step length; then the multiple precision compensation coefficients are multiplied by the initial optimization step length, and the product of the two is used as the compensation optimization step length, and multiple compensation optimization step lengths are obtained as the adaptive optimization step length of each solution set. Through this method of dynamically adjusting the step length, the parameters can be adjusted more finely during the optimization process, avoiding the possibility of missing a better solution due to overly extensive adjustments, thereby improving the accuracy of the overall optimization. This method is particularly suitable for refining the optimization when approaching the optimal solution, reducing the instability caused by excessive adjustments, and ensuring that more accurate stamping processing parameters are finally obtained.

[0043] Identify the M updated solution sets, and if the fitness of the difference solution in the updated solution set is greater than the fitness of the good solution, replace the good solution in the solution set with the difference solution; continue iterative optimization until the predetermined number of optimizations is reached, output M current solution sets, and select the good solution of the best current solution set as the first optimal stamping processing parameter, wherein the best current solution set is the solution set with the largest sum of fitness among the M current solution sets. Obtain multiple groups of stamping processing combinations and multiple combination fitnesses in turn, and select the stamping processing combination with the largest combination fitness as the optimal processing combination.

[0044] Specifically, the M updated solution sets are then identified. If the fitness of the difference solution in the updated solution set is greater than the fitness of the good solution, the difference solution is used to replace the good solution in the solution set. The iterative optimization is continued until a predetermined number of optimization times (such as 1000 times) is reached, and M current solution sets are output. The solution set with the largest sum of fitness among the M current solution sets is selected as the optimal solution set, and then the good solution of the optimal current solution set is set as the first optimal stamping processing parameter.

[0045] Then, the first stamping process combination is obtained according to the first optimal stamping process parameters and the first group of matching stamping dies, wherein the first stamping process combination is marked with a first combination fitness, and the first combination fitness is the matching fitness of the first optimal stamping process parameters. Using the same optimization method, multiple groups of stamping process combinations and multiple combination fitnesses are obtained in turn, and the stamping process combination with the maximum combination fitness is selected as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die set and an optimal stamping parameter. By selecting the stamping process combination with the maximum combination fitness as the optimal processing combination, high matching accuracy and efficient production can be achieved in the production of chain links. This method ensures that during the stamping process, the matching tolerance of the connecting pin and the connecting hole is effectively controlled, thereby improving the performance and quality of the product.

[0046] Step 4: Using the optimal stamping die set, stamping the connecting pins and connecting holes of the target chain link is performed according to the optimal stamping parameters.

[0047] Specifically, the optimal stamping die set is finally used to perform stamping processing on the connecting pins and connecting holes of the target chain link according to the optimal stamping parameters. By using the optimal stamping die set and the optimal stamping parameters to perform stamping processing on the connecting pins and connecting holes of the target chain link, it is possible to ensure that the processing accuracy meets the expected matching tolerance requirements, reduce errors, and improve product consistency and performance. This process can significantly improve production efficiency in actual production, and ensure the matching accuracy of the connecting pins and connecting holes of each chain link, thereby ensuring the overall quality and durability of the chain.

[0048] In summary, the chain link forming method in saw chain production provided by the present application has the following technical effects: By acquiring the chain saw product attributes and usage scenarios of the target saw chain, a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain link is performed according to the chain saw product attributes and usage scenarios to determine the expected matching tolerance; matching and selection are performed in the stamping die selection library based on the expected matching tolerance to determine multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die; with maximizing the matching accuracy as the optimization goal, the stamping processing parameters of the multiple groups of matching stamping dies are optimized respectively, and the stamping processing combination with the greatest adaptability is output as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die group and an optimal stamping parameter; through the optimal stamping die group, the connecting pins and connecting holes of the target chain link are stamped according to the optimal stamping parameters, that is, by optimizing the stamping process and die selection, the precision tolerance can be effectively controlled, and the matching accuracy of the connecting pins and connecting holes can be improved, thereby effectively improving the product quality of the chain link and ensuring the stability and durability of the saw chain during use.

[0049] Embodiment 2: Based on the same inventive concept as the chain link forming method in the production of a saw chain in the above embodiment, the present application also provides a chain link forming platform in the production of a saw chain, please refer to the attached Figure 2 ,include: The demand quantification analysis module 11 is used to obtain the chain saw product attributes and usage scenarios of the target saw chain, and perform a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain links according to the chain saw product attributes and usage scenarios to determine the expected fitting tolerance; the adaptation stamping die determination module 12 is used to match and select in the stamping die selection library based on the expected fitting tolerance to determine multiple groups of adaptation stamping dies, wherein each group of adaptation stamping dies includes a connecting pin stamping die and a connecting hole stamping die; the stamping processing combination optimization module 13 is used to optimize the stamping processing parameters of the multiple groups of adaptation stamping dies respectively with maximizing the fitting accuracy as the optimization goal, and output the stamping processing combination with the greatest fitness as the optimal processing combination, wherein the optimal processing combination includes an optimal stamping die group and an optimal stamping parameter; the chain link stamping processing module 14 is used to perform stamping processing of the connecting pins and connecting holes of the target chain link according to the optimal stamping parameters through the optimal stamping die group.

[0050] Furthermore, the chain link forming platform in the production of a saw chain is also used for: taking the chain saw product attributes and usage scenarios as feature constraints, searching the fitting tolerances of connecting pins and connecting holes based on big data, and determining a sample fitting tolerance set and a sample working time set; selecting sample fitting tolerances whose sample working times meet the expected qualified working times, obtaining a standard sample fitting tolerance set after redundant processing, and calculating a sample surplus time mean set and a sample data frequency set; setting an adaptation weight based on the sample surplus time mean, optimizing and correcting the sample data frequency set according to the adaptation weight set, and determining a corrected data frequency set; selecting the standard sample fitting tolerance corresponding to the maximum data frequency in the corrected data frequency set and setting it as the expected fitting tolerance.

[0051] Furthermore, the chain link forming platform in the production of a saw chain is also used to: obtain a stamping die selection library, wherein the stamping die selection library contains a plurality of connecting pin stamping dies and connecting hole stamping dies of different sizes and shapes; based on satisfying the expected fitting tolerance as a processing constraint, matching selection is performed in the stamping die selection library to obtain a plurality of groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping dies and a connecting hole stamping dies of the same shape, and the fitting tolerance of each group of matching stamping dies is smaller than the expected fitting tolerance.

[0052] Furthermore, the chain link forming platform in the production of a saw chain is also used to: obtain material properties of the material to be processed, wherein the material properties include material hardness and material elasticity; randomly select a first group of adaptive stamping dies from the multiple groups of adaptive stamping dies, wherein the first group of adaptive stamping dies includes a first connecting pin die and a first connecting hole die; obtain a stamping processing parameter space, and randomly select a plurality of initial stamping parameters, wherein the stamping processing parameters include stamping pressure, stamping stroke and stamping speed; perform stamping processing simulation according to the material hardness, material elasticity, the first connecting pin die, the first connecting hole die and the plurality of initial stamping parameters, and output a plurality of first simulated connecting pin diameters and A plurality of first simulated connection hole diameters; a plurality of matching fitnesses are calculated and determined according to the plurality of first simulated connection pin diameters and the plurality of first simulated connection hole diameters; with the stamping process parameter space as a constraint, the stamping process parameters are iteratively optimized according to the plurality of matching fitnesses, and the first optimal stamping process parameters are outputted; a first stamping process combination is obtained in combination with the first group of matching stamping dies, wherein the first stamping process combination is marked with a first combination fitness, and the first combination fitness is the matching fitness of the first optimal stamping process parameters; a plurality of groups of stamping process combinations and a plurality of combination fitnesses are obtained in turn, and the stamping process combination with the maximum combination fitness is selected as the optimal processing combination.

[0053] Furthermore, the chain link forming platform in the production of a saw chain is also used to: collect the first connecting pin mold attributes of the first connecting pin mold, and the first connecting hole mold attributes of the first connecting hole mold, wherein the mold attributes include shape, size and wear feature distribution, and the wear feature distribution can be obtained by extracting features from the mold image; using the material hardness and material elasticity as material constraints, and the first connecting pin mold attributes and the first connecting hole mold attributes as feature constraints, retrieving the stamping process log, and collecting sample stamping parameter sets, sample connecting pin diameter sets, and sample connecting hole aperture sets; using sample stamping parameters as input, and sample connecting pin diameters and sample connecting hole apertures as supervision, using the sample stamping parameter set, sample connecting pin diameter set, and sample connecting hole aperture set to supervise training the BP neural network until convergence, and obtaining a stamping process simulation plug-in; using the stamping process simulation plug-in to perform stamping process simulation on the multiple initial stamping parameters, and output multiple first simulated connecting pin diameters and multiple first simulated connecting hole apertures.

[0054] Furthermore, the chain link forming platform in the production of a saw chain is also used to: subtract the multiple first simulated connecting pin diameters from the multiple first simulated connecting hole diameters to obtain multiple simulated fitting deviations; randomly select a first simulated fitting deviation, calculate a first fitting fitness based on the first simulated fitting deviation and a benchmark fitting deviation, and add it to the multiple fitting fitnesses, wherein the first fitting fitness is the inverse of the absolute value of the difference between the first simulated fitting deviation and the benchmark fitting deviation.

[0055] Furthermore, the chain link forming platform in the production of a saw chain is also used to: mark the initial stamping parameters as initial solutions, arrange the multiple initial solutions from large to small according to the multiple matching fitnesses, and construct an initial solution sequence; select the first M solutions of the initial solution sequence as good solutions, and the last P solutions as differential solutions, wherein the sum of M and P is the number of initial solutions, P is Q times of M, and Q is an integer greater than 10 and less than 50; perform random equal-value clustering on the P differential solutions based on the M good solutions to obtain M solution sets, and in each solution set, take the good solution as the optimization direction, and select the optimal solution according to the adaptive optimization step length. The differential solutions in the solution set are adjusted once to obtain M updated solution sets, wherein if the updated differential solutions do not satisfy the stamping process parameter space, no adjustment is performed; the M updated solution sets are identified, and if the fitness of the differential solutions in the updated solution set is greater than the fitness of the good solutions, the good solutions in the solution set are replaced by the differential solutions; the iterative optimization is continued until a predetermined number of optimization times is reached, M current solution sets are output, and the good solutions of the optimal current solution set are selected as the first optimal stamping process parameters, wherein the optimal current solution set is the solution set with the largest sum of fitness among the M current solution sets.

[0056] Furthermore, the chain link forming platform in the production of a saw chain is also used to: for each solution set, respectively calculate the fitness of the good solution and the fitness deviations of multiple difference solutions in the solution set to obtain multiple fitness differences; select the maximum fitness difference among the multiple fitness differences, and respectively calculate the ratios of the multiple fitness differences to the maximum fitness difference to obtain multiple precision compensation coefficients; use the multiple precision compensation coefficients multiplied by the initial optimization step length to obtain multiple compensated optimization step lengths as the adaptive optimization step length of each solution set.

[0057] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The chain segment forming method and specific examples in the aforementioned embodiment 1 are also applicable to the chain segment forming platform in the production of a saw chain in this embodiment. Through the aforementioned detailed description of the chain segment forming method in the production of a saw chain, those skilled in the art can clearly understand the chain segment forming platform in the production of a saw chain in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the platform disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0058] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0059] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A chain link forming method in saw chain production, characterized in that: Methods include: Acquire the chain saw product attributes and usage scenarios of the target saw chain, perform a quantitative analysis of the connection requirements of the connecting pins and connecting holes of the target chain links according to the chain saw product attributes and usage scenarios, and determine the expected matching tolerance; Based on the expected matching tolerance, matching selection is performed in the stamping die selection library to determine multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die; Taking maximizing the matching accuracy as the optimization goal, the stamping processing parameters of the multiple sets of adapted stamping dies are optimized respectively, and the stamping processing combination with the greatest adaptability is output as the optimal processing combination, wherein the optimal processing combination includes the optimal stamping die set and the optimal stamping parameters; The optimal stamping die set is used to perform stamping processing on the connecting pins and connecting holes of the target chain link according to the optimal stamping parameters.

2. The chain link forming method in saw chain production according to claim 1, characterized in that: According to the product attributes and usage scenarios of the chain saw, the connection requirements of the connecting pins and connecting holes of the target chain links are quantitatively analyzed to determine the expected matching tolerances, including: Taking the chain saw product attributes and usage scenarios as feature constraints, the matching tolerance of connecting pins and connecting holes is retrieved based on big data to determine the sample matching tolerance set and sample working time set; Select the sample working hours that meet the sample matching tolerance of the expected qualified working hours, obtain the standard sample matching tolerance set after redundancy processing, and calculate the sample surplus time mean set and sample data frequency set; Setting an adaptation weight based on the mean value of the sample surplus duration, optimizing and correcting the sample data frequency set according to the adaptation weight set, and determining a corrected data frequency set; The standard sample matching tolerance corresponding to the maximum data frequency in the correction data frequency set is selected and set as the expected matching tolerance.

3. The chain link forming method in saw chain production according to claim 1, characterized in that: Based on the expected matching tolerance, matching selection is performed in the stamping die selection library to determine multiple groups of suitable stamping dies, including: Acquire a stamping die selection library, wherein the stamping die selection library contains a plurality of connecting pin stamping dies and connecting hole stamping dies of different sizes and shapes; Taking satisfying the expected fitting tolerance as a processing constraint, matching selection is performed in the stamping die selection library to obtain multiple groups of matching stamping dies, wherein each group of matching stamping dies includes a connecting pin stamping die and a connecting hole stamping die of the same shape, and the fitting tolerance of each group of matching stamping dies is smaller than the expected fitting tolerance.

4. The chain link forming method in saw chain production according to claim 1, characterized in that: Taking maximizing the matching accuracy as the optimization goal, the multiple sets of stamping processing parameters of the adapted stamping dies are optimized respectively, and the stamping processing combination with the greatest adaptability is output as the optimal processing combination, including: Acquiring material properties of the material to be processed, wherein the material properties include material hardness and material elasticity; Randomly selecting a first group of adapting stamping dies from the plurality of groups of adapting stamping dies, wherein the first group of adapting stamping dies includes a first connecting pin die and a first connecting hole die; Acquire a stamping process parameter space and randomly select a plurality of initial stamping parameters, wherein the stamping process parameters include stamping pressure, stamping stroke and stamping speed; Perform a stamping process simulation according to the material hardness, material elasticity, the first connecting pin mold, the first connecting hole mold and a plurality of initial stamping parameters, and output a plurality of first simulated connecting pin diameters and a plurality of first simulated connecting hole apertures; Calculate and determine a plurality of fitting adaptabilities according to the plurality of first simulated connection pin diameters and the plurality of first simulated connection hole diameters; Taking the stamping process parameter space as a constraint, performing iterative optimization of the stamping process parameters according to the multiple matching fitnesses, outputting the first optimal stamping process parameters, and combining the first group of matching stamping dies to obtain a first stamping process combination, wherein the first stamping process combination is marked with a first combination fitness, and the first combination fitness is the matching fitness of the first optimal stamping process parameters; A plurality of stamping process combinations and a plurality of combination fitnesses are obtained in sequence, and the stamping process combination with the maximum combination fitness is selected as the optimal process combination.

5. The chain link forming method in saw chain production according to claim 4, characterized in that: A stamping process simulation is performed according to the material hardness, material elasticity, a first connecting pin mold, a first connecting hole mold and a plurality of initial stamping parameters, and a plurality of first simulated connecting pin diameters and a plurality of first simulated connecting hole apertures are output, including: Collecting first connecting pin mold attributes of the first connecting pin mold and first connecting hole mold attributes of the first connecting hole mold, wherein the mold attributes include shape, size and wear feature distribution, and the wear feature distribution can be obtained by extracting features from the mold image; Taking the material hardness and material elasticity as material constraints, taking the first connecting pin mold attribute and the first connecting hole mold attribute as feature constraints, searching the stamping process log, and collecting a sample stamping parameter set, a sample connecting pin diameter set, and a sample connecting hole aperture set; Taking sample stamping parameters as input, taking sample connecting pin diameter and sample connecting hole diameter as supervision, using the sample stamping parameter set, sample connecting pin diameter set and sample connecting hole diameter set, supervised training is performed on the BP neural network until convergence, thereby obtaining a stamping processing simulation plug-in; The stamping process simulation plug-in is used to perform stamping process simulation on the multiple initial stamping parameters, and a plurality of first simulated connecting pin diameters and a plurality of first simulated connecting hole apertures are output.

6. The chain link forming method in saw chain production according to claim 4, characterized in that: Calculating and determining a plurality of fit adaptabilities according to the plurality of first simulated connection pin diameters and the plurality of first simulated connection hole diameters includes: Subtract the diameters of the plurality of first simulated connecting pins from the diameters of the plurality of first simulated connecting holes to obtain a plurality of simulated fitting deviations; A first simulated fit deviation is randomly selected, and a first fit fitness is calculated according to the first simulated fit deviation and the benchmark fit deviation, and added to the multiple fit fitnesses, wherein the first fit fitness is the reciprocal of the absolute value of the difference between the first simulated fit deviation and the benchmark fit deviation.

7. The chain link forming method in saw chain production according to claim 4, characterized in that: Taking the stamping process parameter space as a constraint, performing iterative optimization of the stamping process parameters according to the multiple matching fitnesses, and outputting the first optimal stamping process parameters, including: Marking the initial stamping parameters as initial solutions, arranging the multiple initial solutions from large to small according to the multiple matching fitnesses, and constructing an initial solution sequence; The first M solutions of the initial solution sequence are selected as good solutions, and the last P solutions are selected as poor solutions, where the sum of M and P is the number of initial solutions, P is Q times of M, and Q is an integer greater than 10 and less than 50; Based on the M good solutions, the P differential solutions are randomly clustered and divided into equal values ​​to obtain M solution sets, and in each solution set, the differential solutions in the solution set are adjusted once according to the adaptive optimization step length with the good solutions as the optimization direction to obtain M updated solution sets, wherein if the updated differential solution does not satisfy the stamping process parameter space, this adjustment is not performed; Identify the M update solution sets, and if the fitness of the difference solution in the update solution set is greater than the fitness of the good solution, replace the good solution in the solution set with the difference solution; Continue to iterate and optimize until the predetermined number of optimization times is reached, output M current solution sets, and select the best solution of the best current solution set as the first optimal stamping processing parameter, wherein the best current solution set is the solution set with the largest sum of fitness among the M current solution sets.

8. The chain link forming method in saw chain production according to claim 7, characterized in that: Get the adaptation and search for Uber, including: For each solution set, the fitness of the good solution and the fitness deviations of multiple poor solutions in the solution set are calculated respectively to obtain multiple fitness differences; Selecting a maximum fitness difference among the multiple fitness differences, and respectively calculating ratios of the multiple fitness differences to the maximum fitness difference to obtain multiple precision compensation coefficients; The multiple precision compensation coefficients are multiplied by the initial optimization step length to obtain multiple compensation optimization step lengths as the adaptive optimization step length of each solution set.

9. A chain link forming platform in saw chain production, characterized in that: The steps for implementing the chain link forming method in saw chain production according to any one of claims 1 to 8 include: A demand quantification analysis module, used to obtain the chain saw product attributes and usage scenarios of the target saw chain, and to perform a connection demand quantification analysis of the connection pins and connection holes of the target chain links according to the chain saw product attributes and usage scenarios, and to determine an expected matching tolerance; An adaptable stamping die determination module is used to select matches in a stamping die selection library based on the expected matching tolerance, and determine multiple groups of adaptable stamping dies, wherein each group of adaptable stamping dies includes a connecting pin stamping die and a connecting hole stamping die; A stamping processing combination optimization module is used to optimize the stamping processing parameters of the multiple sets of adapted stamping dies respectively with the maximum matching accuracy as the optimization target, and output the stamping processing combination with the greatest fitness as the optimal processing combination, wherein the optimal processing combination includes the optimal stamping die set and the optimal stamping parameters; The chain link stamping processing module is used to perform stamping processing on the connecting pins and connecting holes of the target chain link according to the optimal stamping parameters through the optimal stamping die set.

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