Method and device for determining injection mold nozzle parameters of a connector busbar

Abstract

The present invention provides a method and device for determining the injection mold sprue parameters of a connector busbar. The determination method includes: obtaining the target parameters of the connector busbar; determining a three-dimensional model of the connector busbar according to the target parameters of the connector busbar; obtaining the optional sprue parameters of the injection mold matching the three-dimensional model; obtaining a plurality of evaluation indexes corresponding to the optional sprue parameters according to the optional sprue parameters of the injection mold; and determining the optimal combination parameters of the optional sprue parameters according to the plurality of evaluation indexes. Embodiments of the present invention can accurately plan the position and quantity of the sprue, and significantly improve the product quality of the connector busbar.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of plastic processing, and particularly to a method and device for determining the gating parameters of an injection mold for a connector bus bar. Background Art

[0002] In the injection molding production of a connector bus bar, the design and performance of the injection mold play a decisive role in the product quality and production efficiency. During the flow and cooling of the plastic in the mold cavity, it is greatly affected by the set gating position and quantity. If the gating position and quantity are not set reasonably, it will lead to defects such as uneven mold temperature, poor cooling and setting, and internal stress concentration. Summary of the Invention

[0003] The technical problem to be solved by the embodiments of the present invention is to provide a method and device for determining the gating parameters of an injection mold for a connector bus bar, which can accurately plan the gating position and quantity and significantly improve the product quality of the connector bus bar.

[0004] To solve the above technical problem, the technical solution of the embodiments of the present invention is as follows:

[0005] A method for determining the gating parameters of an injection mold for a connector bus bar includes:

[0006] Obtaining the target parameters of the connector bus bar;

[0007] Determining the three-dimensional model of the connector bus bar according to the target parameters of the connector bus bar;

[0008] Obtaining the optional gating parameters of the injection mold matching the three-dimensional model;

[0009] Obtaining a plurality of evaluation indexes corresponding to the optional gating parameters according to the optional gating parameters of the injection mold;

[0010] Determining the optimal combination parameters of the optional gating parameters according to the plurality of evaluation indexes.

[0011] Optionally, the obtaining the target parameters of the connector bus bar includes:

[0012] Obtaining the geometric shape, dimensional accuracy, and wall thickness distribution of the connector bus bar.

[0013] Optionally, the determining the three-dimensional model of the connector bus bar according to the target parameters of the connector bus bar includes:

[0014] Obtaining the physical property parameters of the injection material of the connector bus bar;

[0015] Determine the three-dimensional model of the connector bus bar according to the physical property parameters of the injection molding material and the target parameters of the connector bus bar.

[0016] Optionally, obtain the optional gate parameters of the injection mold matching the three-dimensional model, including:

[0017] Obtain the positions and quantities where the gates of the injection mold can be set;

[0018] According to P(x) = {S|S⊆x}, determine the optional gate parameters, where the optional gate parameters are combinations of the positions and quantities where the gates can be set,

[0019] where x = (x1,..., x n ), x1,..., x n are the positions where the gates can be set, n is the quantity of gates that can be set, S is any subset of the array x, and P(x) is the set of all subsets of the array x.

[0020] Optionally, according to the optional gate parameters of the injection mold, obtain multiple evaluation indicators corresponding to the optional gate parameters, including:

[0021] Conduct mold flow analysis on the three-dimensional model of the connector bus bar to obtain a mold temperature distribution contour map, mold cooling time data, and a residual stress distribution contour map corresponding to the array x;

[0022] According to the mold temperature distribution contour map, determine the mold temperature evaluation indicator corresponding to the array x;

[0023] According to the mold cooling time data, determine the cooling time evaluation indicator corresponding to the array x;

[0024] According to the residual stress distribution contour map, determine the cooling effect evaluation indicator corresponding to the array x.

[0025] Optionally, according to the mold temperature distribution contour map, determine the mold temperature evaluation indicator corresponding to the array x, including:

[0026] According to the mold temperature distribution contour map, obtain the total difference A between the regional temperature values of each area of the mold and the set temperature range i and the standard deviation B of the specific temperature values of each area of the mold i ,

[0027] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the quantity of gates that can be set;

[0028] According to the total difference A i and the standard deviation B i , determine the mold temperature evaluation indicator R corresponding to the array xi .

[0029] Optionally, according to the mold cooling time data, determine the cooling time evaluation index corresponding to the array x, including:

[0030] According to the mold cooling time data, determine the first difference C between the overall mold cooling time and the set cooling time i , and the second difference D between the maximum cooling time and the minimum cooling time of each region of the mold i ,

[0031] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the number of toppings that can be set;

[0032] According to the first difference C i and the second difference D i , determine the cooling time evaluation index S corresponding to the array x i .

[0033] Optionally, according to the residual stress distribution nephogram, determine the cooling effect evaluation index corresponding to the array x, including:

[0034] According to the residual stress distribution nephogram, determine the change rate E of the temperature per unit distance of the overall mold i , and the standard deviation F of the residual stress in each region of the mold i ,

[0035] where i is the index exponent of all combinations of the positions and quantities where the toppings can be set, i = n(n + 1) / 2, and n is the number of toppings that can be set;

[0036] According to the change rate E i and the standard deviation F i , determine the cooling effect evaluation index T corresponding to the array x i .

[0037] Optionally, according to the multiple evaluation indexes, determine the optimal combination parameters of the optional topping parameters, including:

[0038] According to Y i =rR i +sS i +tT i Determine the fitness values of the evaluation indexes corresponding to all optional topping parameters;

[0039] where Y i is the fitness value of the evaluation index corresponding to the optional topping parameter, R i is the mold temperature evaluation index corresponding to the array x, S i is the cooling time evaluation index corresponding to the array x, Ti It is the evaluation index of the cooling effect corresponding to the array x. i = n(n + 1) / 2, where n is the number of toppings that can be set, and r, s, t are weight coefficients, and r + s + t = 1;

[0040] According to Z = min(Y i ) to determine the minimum value of the evaluation index fitness value corresponding to all optional topping parameters;

[0041] Among them, Z is the minimum value of the evaluation index fitness value corresponding to all optional topping parameters, and Y i is the evaluation index fitness value corresponding to the optional topping parameters;

[0042] Determine the position and quantity of the topping setting corresponding to the minimum value of the evaluation index fitness value of all optional topping parameters;

[0043] Determine the position and quantity of the topping setting corresponding to the minimum value of the fitness value as the optimal parameters of the optional topping parameters.

[0044] An embodiment of the present invention also provides a device for determining the topping parameters of an injection mold for a connector bus bar, including:

[0045] An acquisition module for acquiring the target parameters of the connector bus bar and the optional topping parameters of the injection mold matching the 3D model;

[0046] A processing module for determining the 3D model of the connector bus bar according to the target parameters of the connector bus bar; obtaining multiple evaluation indexes corresponding to the optional topping parameters according to the optional topping parameters of the injection mold; and determining the optimal combination parameters of the optional topping parameters according to the multiple evaluation indexes.

[0047] The above solution of the embodiment of the present invention has at least the following beneficial effects:

[0048] The above solution of the embodiment of the present invention constructs a 3D model by acquiring the target parameters of the connector bus bar, and based on this, determines the optional topping parameters of the injection mold and their corresponding evaluation indexes, and then obtains the optimal combination parameters. This process can accurately plan the position and quantity of the toppings, effectively avoiding the problem of uneven mold temperature caused by unreasonable settings. When filling the mold cavity with plastic, the reasonably distributed toppings can make the plastic flow into each part evenly, ensuring that the temperature everywhere in the mold tends to be consistent, thereby reducing product defects caused by temperature differences, such as local deformation, surface defects, etc., and significantly improving the quality of the connector bus bar.

[0049] The determined optimal combination of gating parameters can optimize the cooling process of the plastic within the mold. Appropriate gating positions and quantities enable the cooling medium to act more uniformly on the mold, promoting a consistent cooling rate for the plastic and avoiding issues such as inconsistent product shrinkage and dimensional deviations caused by uneven cooling.

[0050] An unreasonable gating setup is often an important cause of stress concentration within the product. This method can effectively reduce the occurrence of such situations through a scientific parameter determination process. The optimized gating parameters result in a more uniform internal stress distribution when the plastic fills and cools within the cavity, reducing the risk of defects such as cracking and warping in the product due to internal stress concentration.

[0051] Since this method can significantly improve product quality and reduce product defects caused by unreasonable mold gating parameters, it greatly reduces the scrap rate. During the production process, the generation of scrap not only wastes raw materials and energy but also increases production costs and production time. Description of the Drawings

[0052] Figure 1 is a flowchart showing the method for determining the gating parameters of an injection mold for a connector busbar provided by an embodiment of the present invention.

[0053] Figure 2 is a module diagram of a device for determining the gating parameters of an injection mold for a connector busbar provided by an embodiment of the present invention. Detailed Embodiments

[0054] Hereinafter, exemplary embodiments of the present invention will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be fully conveyed to those skilled in the art.

[0055] As Figure 1 shown, an embodiment of the present invention provides a method for determining the gating parameters of an injection mold for a connector busbar, including:

[0056] Step 11, obtaining the target parameters of the connector busbar;

[0057] Step 12, determining the three-dimensional model of the connector busbar according to the target parameters of the connector busbar;

[0058] Step 13, obtaining the optional gating parameters of the injection mold matching the three-dimensional model;

[0059] Step 14, obtaining multiple evaluation indicators corresponding to the optional gating parameters according to the optional gating parameters of the injection mold;

[0060] Step 15: Determine the optimal combination of optional gating parameters according to the multiple evaluation metrics.

[0061] In this example, a 3D model is constructed by obtaining the target parameters of the connector busbar, and based on this, the optional gating parameters of the injection mold and their corresponding evaluation metrics are determined, and then the optimal combination of parameters is obtained. This process can accurately plan the position and quantity of the gates, effectively avoiding the problem of uneven mold temperature caused by unreasonable settings. When filling the mold cavity with plastic, the gates with reasonable distribution can make the plastic flow into each part evenly, ensuring that the temperature of each part of the mold tends to be consistent, thereby reducing product defects caused by temperature differences, such as local deformation, surface flaws, etc., and significantly improving the quality of the connector busbar.

[0062] The determined optimal combination of gating parameters can optimize the cooling process of the plastic in the mold. Appropriate gate position and quantity can make the cooling medium act on the mold more evenly, prompting the plastic to cool at a consistent speed and avoiding problems such as inconsistent product shrinkage and dimensional deviation caused by uneven cooling.

[0063] Unreasonable gate settings are often an important cause of internal stress concentration in products. This method can effectively reduce the occurrence of this situation through a scientific parameter determination process. The optimized gating parameters make the internal stress distribution of the plastic more uniform when filling and cooling in the cavity, reducing the risk of product defects such as cracking and warping caused by internal stress concentration.

[0064] Since this method can significantly improve product quality and reduce product defects caused by unreasonable mold gating parameters, the scrap rate is greatly reduced. In the production process, the generation of scrap not only wastes raw materials and energy but also increases production costs and production time.

[0065] In an optional embodiment of the present invention, in Step 11, the obtaining of the target parameters of the connector busbar includes:

[0066] Step 111: Obtain the geometric shape, dimensional accuracy, and wall thickness distribution of the connector busbar.

[0067] In Step 12, the determining of the 3D model of the connector busbar according to the target parameters of the connector busbar includes:

[0068] Step 121: Obtain the physical property parameters of the injection molding material of the connector busbar;

[0069] Step 122: Determine the 3D model of the connector busbar according to the physical property parameters of the injection molding material and the target parameters of the connector busbar.

[0070] Specifically, the physical property parameters may include melt viscosity, thermal conductivity, specific heat capacity, shrinkage rate, and elastic modulus.

[0071] In this example, target parameters such as the geometry, dimensional accuracy, and wall thickness distribution of the connector busbar are obtained through step 111, providing accurate basic data for subsequent construction of the 3D model. These parameters are the core features of the connector busbar. Accurately obtaining them enables the 3D model to truly restore the actual form of the product, avoiding design deviations caused by discrepancies between the model and the actual product. When constructing the 3D model, based on the accurate geometry and dimensional accuracy, the positions and sizes of each part can be accurately determined, making the model highly consistent with the actual product in terms of appearance and dimensions.

[0072] Step 121 obtains physical property parameters such as the melt viscosity, thermal conductivity, specific heat capacity, shrinkage rate, and elastic modulus of the injection molding material, and in step 122, the 3D model is determined by combining these parameters with the target parameters. This can fully consider the influence of material properties on product molding during the model construction process.

[0073] In an alternative embodiment of the present invention, in step 13, the optional gate parameters of the injection mold matching the 3D model are obtained, including:

[0074] Step 131 obtains the positions and quantities where the gates of the injection mold can be set;

[0075] Step 132 determines the optional gate parameters according to P(x) = {S|S⊆x}, where the optional gate parameters are combinations of the positions and quantities where the gates can be set,

[0076] where x = (x1,..., x n )), x1,..., x n are the positions where the gates can be set, n is the quantity of gates that can be set, S is any subset of the array x, and P(x) is the set of all subsets of the array x.

[0077] In this example, by obtaining the positions and quantities where the gates of the injection mold can be set through step 131 and then using P(x) = {S|S⊆x} in step 132 to determine the optional gate parameters, all possible combinations of gate positions and quantities can be listed comprehensively and systematically. This means that no potential gate setting scheme will be missed, providing a rich selection space for subsequent evaluation and selection. When designing an injection mold, different gate settings have an important impact on the flow path and filling effect of the plastic melt. The comprehensive listing of schemes helps to find the most suitable gate setting method for the 3D model of the connector busbar.

[0078] Analyzing all possible combinations of gating parameters can provide in-depth understanding of the performance of each setting during the plastic filling and cooling processes. By simulating the flow of the plastic melt under different combinations and its impact on the final product quality, the advantages and disadvantages of various solutions can be more accurately evaluated. This comprehensive exploration helps to discover some gating settings that might otherwise be overlooked but can significantly improve product quality and production efficiency.

[0079] A reasonable gating setting can optimize the flow path of the plastic melt in the mold cavity, enabling the melt to fill the cavity more evenly and reducing defects caused by poor flow, such as short shots and air traps. By evaluating multiple optional gating parameter combinations, the most ideal solution for melt flow can be found, thereby improving the molding quality of the product. For a complex-shaped connector busbar, an appropriate gating setting can ensure that the melt can smoothly fill into every corner, avoiding local underfilling.

[0080] An improper gating setting may lead to stress concentration inside the product, thus affecting the mechanical properties and service life of the product. By comprehensively considering various optional gating parameter combinations, a solution that can make the internal stress distribution more uniform can be selected, reducing the risks of cracking and deformation caused by internal stress problems in the product. A reasonable gating setting can make the plastic shrink evenly during the cooling process, reducing the generation of internal stress.

[0081] In an optional embodiment of the present invention, in step 14, according to the optional gating parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional gating parameters are obtained, including:

[0082] Step 141, perform mold flow analysis on the three-dimensional model of the connector busbar to obtain a mold temperature distribution contour map, mold cooling time data, and a residual stress distribution contour map corresponding to the array x;

[0083] Step 142, determine the mold temperature evaluation indicator corresponding to the array x according to the mold temperature distribution contour map;

[0084] Step 143, determine the cooling time evaluation indicator corresponding to the array x according to the mold cooling time data;

[0085] Step 144, determine the cooling effect evaluation indicator corresponding to the array x according to the residual stress distribution contour map.

[0086] In this example, through Mold Flow Analysis in step 141, a contour map of the mold temperature distribution is obtained, and then in step 142, the mold temperature evaluation index is determined, enabling accurate grasp of the mold temperature distribution under different optional nozzle parameters. This helps to identify areas with uneven temperature, and uneven temperature may cause defects such as product deformation and shrinkage marks. Based on these evaluation indexes, the nozzle parameters can be adjusted to make the mold temperature distribution more uniform, thereby improving the molding quality of the connector busbar and ensuring the dimensional accuracy and appearance quality of the product.

[0087] The contour map of the residual stress distribution obtained in step 141 and the cooling effect evaluation index determined in step 144 enable us to clearly understand the residual stress situation inside the product. Excessive residual stress will reduce the mechanical properties and reliability of the product and easily cause problems such as cracking during product use. By analyzing the evaluation index and adjusting the nozzle parameters, the residual stress of the product can be effectively reduced, and the strength and durability of the product can be improved.

[0088] Accurate evaluation indexes help to determine the most suitable nozzle parameters, making the injection molding process more stable. A stable production process can reduce product quality problems and production failures caused by parameter fluctuations, reduce the scrap rate, and improve production efficiency and production continuity.

[0089] In an optional embodiment of the present invention, in step 142, according to the contour map of the mold temperature distribution, the mold temperature evaluation index corresponding to the array x is determined, including:

[0090] Step 1421, according to the contour map of the mold temperature distribution, obtain the total difference A between the regional temperature values of each area of the mold and the set temperature range i , and the standard deviation B of the specific temperature values of each area of the mold i ,

[0091] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the number of settings that the nozzle can be set;

[0092] Step 1422, according to the total difference A i and the standard deviation B i , determine the mold temperature evaluation index R corresponding to the array x i .

[0093] Specifically, compare the temperature value of each area with the upper and lower limits of the set temperature range, calculate the difference from the interval boundary,

[0094] Add up the differences of all areas to obtain the total difference A i ;

[0095] According to B i = Determine the standard deviation of the specific temperature values in each area of the mold,

[0096] where m is the number of areas, is the temperature value of each area, k is the average temperature value of each area, and j is the index exponent of the temperature value of each area;

[0097] According to R i =aA i +bB i Determine the mold temperature evaluation index corresponding to the array x,

[0098] where R i is the mold temperature evaluation index corresponding to the array x, A i is the total difference between the specific temperature value of each area of the mold and the set temperature range, B i is the standard deviation of the specific temperature value of each area of the mold, and a and b are weight coefficients, and a + b = 1.

[0099] In step 143, according to the mold cooling time data, determine the cooling time evaluation index corresponding to the array x, including:

[0100] Step 1431, according to the mold cooling time data, determine the first difference C between the overall mold cooling time and the set cooling time i , and the second difference D between the maximum cooling time and the minimum cooling time of each area of the mold i ,

[0101] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the number of times the topping can be set;

[0102] Step 1432, according to the first difference C i and the second difference D i , determine the cooling time evaluation index S corresponding to the array x i .

[0103] Specifically, compare the overall cooling time data with the set cooling time, and calculate the difference C i ;

[0104] Compare the maximum cooling time and the minimum cooling time of each area of the mold, and calculate the difference D i ;

[0105] According to S i =cC i +dD i Determine the cooling time evaluation index corresponding to the array x,

[0106] where S i is the cooling time evaluation index corresponding to the array x, C iis the difference between the overall cooling time of the mold and the set cooling time, D i is the difference between the maximum cooling time and the minimum cooling time of each area of the mold, c and d are weighting coefficients, and c + d = 1.

[0107] In step 144, according to the residual stress distribution contour map, determine the cooling effect evaluation index corresponding to the array x, including:

[0108] Step 1441, according to the residual stress distribution contour map, determine the temperature change rate E per unit distance of the overall mold i , and the standard deviation F of the residual stress in each area of the mold i ,

[0109] Among them, i is the index exponent of all combinations of the positions and quantities where the toppings can be set, i = n(n + 1) / 2, and n is the number of toppings that can be set;

[0110] Step 1442, according to the change rate E i and the standard deviation F i , determine the cooling effect evaluation index T corresponding to the array x i .

[0111] Specifically, according to E i = determine the temperature change rate per unit distance of the overall mold,

[0112] Among them, E i is the temperature change rate per unit distance of the overall mold, is the average value of the temperature change amount per unit distance of each point of the overall mold, is the unit distance of each point of the overall mold;

[0113] According to F i = determine the standard deviation of the specific temperature values of each area of the mold,

[0114] Among them, m is the number of areas, is the temperature value of each area, g is the average temperature value of each area, and l is the index exponent of the temperature value of each area;

[0115] According to T i =eE i +fF i determine the cooling effect evaluation index corresponding to the array x,

[0116] Among them, T i is the cooling effect evaluation index corresponding to the array x, E i is the temperature change rate per unit distance of the overall mold, F iσ is the standard deviation of the residual stress in each area of the mold, and e and f are weighting coefficients, with e + f = 1.

[0117] In this example, the total difference A between the regional temperature values of each area of the mold and the set temperature range is calculated in step 142 i and the standard deviation B of the specific temperature values i , and based on this, the mold temperature evaluation index R is determined i . This can accurately measure the temperature distribution of the mold. The total difference reflects the deviation degree of the overall temperature from the set range, and the standard deviation reflects the discreteness of the temperature distribution. This helps to discover abnormal temperature areas, timely adjust the nozzle parameters, make the mold temperature closer to the set range and more evenly distributed, and avoid defects such as sink marks and deformation in the product caused by uneven temperature, thereby improving the quality of the connector busbar.

[0118] In step 143, the first difference C between the overall cooling time of the mold and the set cooling time is calculated i and the second difference D between the maximum cooling time and the minimum cooling time of each area of the mold i , and then the cooling time evaluation index S is determined i . The first difference can intuitively reflect whether the overall cooling time meets the expectation, and the second difference can reflect the difference in the cooling time of each area. Based on these indexes, selecting appropriate nozzle parameters can shorten the overall cooling time, reduce the difference in the cooling time of each area, improve production efficiency, and shorten the injection molding cycle.

[0119] In step 144, the rate of change E of the temperature within the unit distance of the overall mold i and the standard deviation F of the residual stress in each area of the mold are determined i to obtain the cooling effect evaluation index T i . The rate of change of temperature reflects the uniformity of the cooling process, and the standard deviation of residual stress is related to the distribution of internal residual stress in the product. A reasonable cooling effect can reduce the internal residual stress in the product, reduce the risk of cracking and deformation, ensure the mechanical properties and dimensional stability of the product, and improve the product quality.

[0120] By comprehensively optimizing the nozzle parameters based on each evaluation index, the temperature control and cooling process during the injection molding process can be made more stable and efficient, reducing production interruptions or adjustments caused by temperature and cooling problems, making the production process smoother, improving production continuity, and thus enhancing the overall production efficiency.

[0121] Each evaluation index quantifies key factors such as mold temperature, cooling time, and cooling effect through specific calculation methods. This quantitative evaluation method provides clear and accurate basis for decision-makers, enabling them to more scientifically compare the advantages and disadvantages of different nozzle parameter combinations, thus making more reasonable decisions, selecting the optimal nozzle parameters, and improving the accuracy and reliability of decisions.

[0122] Each evaluation index evaluates the injection molding process from different perspectives and is comprehensively considered through weight coefficients (such as a, b, c, d, e, f). This way of comprehensive consideration of multiple factors more comprehensively reflects the influence of the nozzle parameters on the injection molding process and product quality, avoids the limitations of single-factor decision-making, and helps to find the best solution that takes into account both product quality and production efficiency.

[0123] In an optional embodiment of the present invention, in step 15, according to the multiple evaluation indexes, determining the optimal combined parameters of the optional nozzle parameters includes:

[0124] Step 151, according to Y i =rR i +sS i +tT i Determine the fitness values of the evaluation indexes corresponding to all optional nozzle parameters,

[0125] wherein, Y i is the fitness value of the evaluation index corresponding to the optional nozzle parameter, R i is the mold temperature evaluation index corresponding to the array x, S i is the cooling time evaluation index corresponding to the array x, T i is the cooling effect evaluation index corresponding to the array x, i = n(n + 1) / 2, n is the number of nozzles that can be set, r, s, t are weight coefficients, and r + s + t = 1;

[0126] Step 152, according to Z = min(Y i ) to determine the minimum value of the fitness values of the evaluation indexes corresponding to all optional nozzle parameters,

[0127] wherein, Z is the minimum value of the fitness values of the evaluation indexes corresponding to all optional nozzle parameters, and Y i is the fitness value of the evaluation index corresponding to the optional nozzle parameter;

[0128] Step 153, determine the position and quantity of the nozzle setting corresponding to the minimum value of the fitness values of the evaluation indexes corresponding to all optional nozzle parameters;

[0129] Step 154, determine the position and quantity of the nozzle setting corresponding to the minimum value of the fitness value as the optimal parameters of the optional nozzle parameters.

[0130] In this example, in step 151, the fitness value of the evaluation index is calculated through the formula Y i =rR i +sS i +tT i The mold temperature evaluation index R i and the cooling time evaluation index Si and the cooling effect evaluation index T i Combined. Mold temperature, cooling time, and cooling effect all have important impacts on product quality, and this comprehensive consideration can fully reflect the influence of the gate parameters on product quality.

[0131] Find the minimum value Z of the evaluation index fitness value through step 152, and determine the corresponding gate setting position and quantity as the optimal parameters in steps 153 and 154. This enables the precise selection of the gate parameter combination that can achieve the best product quality state. For example, when injecting molded connector busbars, the optimal gate parameters can ensure uniform filling of the mold cavity with plastic, making the performance of each part of the product more stable and consistent.

[0132] Different gate parameters have different impacts on mold temperature, cooling time, and cooling effect. By comprehensively evaluating the fitness value of the index, a balance point can be found to optimize production efficiency to the greatest extent while ensuring product quality.

[0133] After determining the optimal gate parameters, the number of adjustments due to inappropriate parameters can be reduced during the production process. Stable gate parameters contribute to maintaining the continuity and stability of production, avoiding frequent debugging and shutdowns, and improving production efficiency.

[0134] Appropriate gate parameters can optimize mold temperature and the cooling process, reducing the energy consumption required for heating and cooling.

[0135] By finding the minimum value of the evaluation index fitness value to determine the optimal gate parameters, the best solution can be accurately screened out from among numerous optional gate parameter combinations.

[0136] The present invention precisely controls the mold temperature, discovers and solves the problem of uneven temperature by calculating relevant temperature indicators, and avoids defects such as product deformation; optimizes the cooling process, reduces residual stress, and improves mechanical properties; ensures uniform melt flow, prevents situations such as short shots, and guarantees the filling effect of complex-shaped products.

[0137] Shorten the cooling time, select appropriate gate parameters according to the cooling time evaluation index, and reduce the molding cycle; stabilize production, reduce product problems and failures caused by parameter fluctuations, reduce the scrap rate, and avoid frequent debugging and shutdowns.

[0138] Reduce the scrap rate and reduce waste of raw materials and energy; save energy, optimize the temperature and cooling process, and reduce equipment energy consumption.

[0139] Construct a quantitative evaluation system, form indicators by specifically calculating and quantifying key factors, and then comprehensively calculate the fitness value to provide a scientific basis; comprehensively consider multiple factors, use weight coefficients to fully reflect the influence of gate parameters, avoid one-sided decision-making, and find the best solution.

[0140] As Figure 2 shown, an embodiment of the present invention further provides a device 20 for determining the injection mold sprue parameters of a connector busbar, including:

[0141] An acquisition module 21, configured to acquire the target parameters of the connector busbar and the optional sprue parameters of the injection mold matching the three-dimensional model;

[0142] A processing module 22, configured to determine the three-dimensional model of the connector busbar according to the target parameters of the connector busbar; obtain multiple evaluation indexes corresponding to the optional sprue parameters according to the optional sprue parameters of the injection mold; and determine the optimal combination parameters of the optional sprue parameters according to the multiple evaluation indexes.

[0143] Optionally, acquiring the target parameters of the connector busbar includes:

[0144] Acquiring the geometric shape, dimensional accuracy, and wall thickness distribution of the connector busbar.

[0145] Optionally, determining the three-dimensional model of the connector busbar according to the target parameters of the connector busbar includes:

[0146] Acquiring the physical property parameters of the injection material of the connector busbar;

[0147] Determining the three-dimensional model of the connector busbar according to the physical property parameters of the injection material and the target parameters of the connector busbar.

[0148] Optionally, acquiring the optional sprue parameters of the injection mold matching the three-dimensional model includes:

[0149] Acquiring the positions and quantities where the sprue of the injection mold can be set;

[0150] Determining the optional sprue parameters according to P(x)={S|S⊆x}, where the optional sprue parameters are the combinations of the positions and quantities where the sprue can be set,

[0151] where x=(x1,...,x n ), x1,...,x n are the positions where the sprue can be set, n is the quantity where the sprue can be set, S is any subset of the array x, and P(x) is the set of all subsets of the array x.

[0152] Optionally, obtaining multiple evaluation indexes corresponding to the optional sprue parameters according to the optional sprue parameters of the injection mold includes:

[0153] Perform mold flow analysis on the 3D model of the connector busbar to obtain the mold temperature distribution contour map, mold cooling time data, and residual stress distribution contour map corresponding to the array x;

[0154] Determine the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution contour map;

[0155] Determine the cooling time evaluation index corresponding to the array x according to the mold cooling time data;

[0156] Determine the cooling effect evaluation index corresponding to the array x according to the residual stress distribution contour map.

[0157] Optionally, determining the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution contour map includes:

[0158] Obtain the total difference A between the regional temperature value of each area of the mold and the set temperature range according to the mold temperature distribution contour map i , and the standard deviation B of the specific temperature values of each area of the mold i ,

[0159] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the number of settings that the nozzle can be set;

[0160] According to the total difference A i and the standard deviation B i , determine the mold temperature evaluation index R corresponding to the array x i .

[0161] Optionally, determining the cooling time evaluation index corresponding to the array x according to the mold cooling time data includes:

[0162] Determine the first difference C between the overall mold cooling time and the set cooling time according to the mold cooling time data i , and the second difference D between the maximum cooling time and the minimum cooling time of each area of the mold i ,

[0163] where i is the index exponent of the array x, i = n(n + 1) / 2, and n is the number of settings that the nozzle can be set;

[0164] According to the first difference C i and the second difference D i , determine the cooling time evaluation index S corresponding to the array x i .

[0165] Optionally, determining the cooling effect evaluation index corresponding to the array x according to the residual stress distribution contour map includes:

[0166] Determine the rate of change E of the temperature within the unit distance of the overall die according to the residual stress distribution contour map i and the standard deviation F of the residual stress in each region of the die i ,

[0167] where i is the index exponent of all combinations of the positions and quantities at which the toppings can be set, i = n(n + 1) / 2, and n is the number of toppings that can be set;

[0168] According to the rate of change E i and the standard deviation F i , determine the cooling effect evaluation index T corresponding to the array x i .

[0169] Optionally, according to the multiple evaluation indexes, determine the optimal combination parameters of the optional topping parameters, including:

[0170] According to Y i =rR i +sS i +tT i Determine the evaluation index fitness values corresponding to all optional topping parameters;

[0171] where Y i is the evaluation index fitness value corresponding to the optional topping parameters, R i is the die temperature evaluation index corresponding to the array x, S i is the cooling time evaluation index corresponding to the array x, T i is the cooling effect evaluation index corresponding to the array x, i = n(n + 1) / 2, n is the number of toppings that can be set, r, s, t are weight coefficients, and r + s + t = 1;

[0172] According to Z = min(Y i ) determine the minimum value of the evaluation index fitness values corresponding to all optional topping parameters;

[0173] where Z is the minimum value of the evaluation index fitness values corresponding to all optional topping parameters, and Y i is the evaluation index fitness value corresponding to the optional topping parameters;

[0174] Determine the positions and quantities of the topping settings corresponding to the minimum value of the evaluation index fitness values of all optional topping parameters;

[0175] Take the positions and quantities of the topping settings corresponding to the minimum fitness value as the optimal parameters of the optional topping parameters.

[0176] It should be noted that this device corresponds to the above-mentioned method, and all implementation manners in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0177] The above is the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for determining the injection mold sprue parameters of a connector bus bar, characterized in that, Including: Obtain the target parameters of the connector busbar; Determine the 3D model of the connector busbar according to the target parameters of the connector busbar; Obtain the optional nozzle parameters of the injection mold matching the 3D model; Obtain multiple evaluation indexes corresponding to the optional nozzle parameters according to the optional nozzle parameters of the injection mold; Determine the optimal combination parameters of the optional nozzle parameters according to the multiple evaluation indexes; Among them, obtaining the optional nozzle parameters of the injection mold matching the 3D model includes: Obtain the positions and quantities where the nozzles of the injection mold can be set; According to P ( x )={ S | S ⊆ x}, determine the optional topping parameters, where the optional topping parameters are the combination of the positions where the toppings can be set and the quantities Among them, x = ([[]]END]] x 1,..., x n ) x 1,... x n are the positions where the toppings can be set, n is the number of toppings that can be set, S is an array x of any subset, P ( x ) is the set of all subsets of the array x ; Among them, obtaining multiple evaluation indexes corresponding to the optional nozzle parameters according to the optional nozzle parameters of the injection mold includes: Perform mold flow analysis on the 3D model of the connector busbar to obtain an array x The corresponding mold temperature distribution contour map, mold cooling time data, and residual stress distribution contour map; Determine an array based on the mold temperature distribution contour map x corresponding mold temperature evaluation indicators; Determine an array based on the mold cooling time data x The corresponding cooling time evaluation index Determine an array according to the residual stress distribution contour map x corresponding cooling effect evaluation index; Among them, determining the optimal combination parameters of the optional nozzle parameters according to the multiple evaluation indexes includes: According to Y i =r R i + sS i + tT i Determine the fitness values of the evaluation indicators corresponding to all optional topping parameters; Among them, Y i is the fitness value of the evaluation index corresponding to the optional topping parameter, R i is an array x corresponding to the evaluation index of the mold temperature, S i is an array x corresponding to the evaluation index of the cooling time, T i is an array x corresponding to the evaluation index of the cooling effect, i=n ( n +1) / 2, n is the number of toppings that can be set, r, s, t is the weight coefficient, and r + s + t = 1; According to Z = min ( Y i )Determine the minimum value of the evaluation index fitness corresponding to all optional topping parameters; Among them, Z is the minimum value of the fitness of the evaluation index corresponding to all optional topping parameters, Y i is the fitness of the evaluation index corresponding to the optional topping parameters; Determine the positions and quantities of the nozzle settings corresponding to the minimum fitness value of the evaluation indexes corresponding to all optional nozzle parameters; Determine the positions and quantities of the nozzle settings corresponding to the minimum fitness value as the optimal parameters of the optional nozzle parameters.

2. The method for determining the injection mold gate parameters of the connector bus bar according to claim 1, characterized in that, The obtaining of the target parameters of the connector busbar includes: Obtain the geometric shape, dimensional accuracy and wall thickness distribution of the connector busbar.

3. The method for determining the injection mold nozzle parameters of the connector bus bar according to claim 2, wherein The determining of the 3D model of the connector busbar according to the target parameters of the connector busbar includes: Obtain the physical property parameters of the injection material of the connector busbar; Determine the 3D model of the connector busbar according to the physical property parameters of the injection material and the target parameters of the connector busbar.

4. The method for determining the injection mold nozzle parameters of the connector bus bar according to claim 1, wherein Determine an array based on the mold temperature distribution contour map x The corresponding mold temperature evaluation indicators include: According to the mold temperature distribution nephogram, obtain the total difference between the regional temperature values of each area of the mold and the set temperature range A i , and the standard deviation of the specific temperature values of each area of the mold B i , Among them, i is the index exponent of the array x , and i=n ( n +1) / 2 n is the number of toppings that can be set; Based on the total difference A i and the standard deviation B i , determine the array x corresponding mold temperature evaluation index R i .

5. The method for determining the injection mold nozzle parameters of the connector bus bar according to claim 1, characterized in that Determine an array based on the mold cooling time data x The corresponding cooling time evaluation indicators include: Determine the first difference between the overall cooling time of the mold and the set cooling time according to the mold cooling time data C i , and the second difference between the maximum cooling time and the minimum cooling time of each area of the mold D i , Among them, i is the index exponent of the array x , i=n ( n +1) / 2, n is the number of toppings that can be set; Based on the first difference C i and the second difference D i , determine the array x corresponding cooling time evaluation index S i .

6. The method for determining the injection mold runner parameters of the connector bus bar according to claim 1, wherein, Based on the residual stress distribution nephogram, determine the array x corresponding cooling effect evaluation indexes, including: Based on the residual stress distribution contour map, determine the rate of change of temperature per unit distance of the overall die, E i and the standard deviation of the residual stress in each region of the die. F i , wherein, i is the index exponent for all combinations of the positions and quantities where the toppings can be set, i=n ( n + 1) / 2, n is the quantity of toppings that can be set; According to the rate of change E i and the standard deviation F i , determine the array x corresponding cooling effect evaluation index T i .

7. A device for determining the injection mold sprue parameters of a connector bus bar, characterized in that, Including: An obtaining module, configured to obtain the target parameters of the connector busbar and the optional nozzle parameters of the injection mold matching the 3D model; Among them, obtaining the optional nozzle parameters of the injection mold matching the 3D model includes: Obtain the positions and quantities where the nozzles of the injection mold can be set; According to P (( x )) = { S |[[]] S ⊆ x}, the optional topping parameters are determined. The optional topping parameters are the combination of the positions where the toppings can be set and the quantities. Among them, x = ([[]]END]] x 1,..., x n ) x 1,..., x n is the position where the topping can be set, n is the number of toppings that can be set, S is an array x of any subset, P ([[]]END]] x ) is the set of all subsets of the array x ; A processing module, configured to determine the 3D model of the connector busbar according to the target parameters of the connector busbar; obtain multiple evaluation indexes corresponding to the optional nozzle parameters according to the optional nozzle parameters of the injection mold; determine the optimal combination parameters of the optional nozzle parameters according to the multiple evaluation indexes; Among them, obtaining multiple evaluation indexes corresponding to the optional nozzle parameters according to the optional nozzle parameters of the injection mold includes: Perform mold flow analysis on the 3D model of the connector busbar to obtain an array x The corresponding mold temperature distribution contour map, mold cooling time data, and residual stress distribution contour map; Determine an array based on the mold temperature distribution contour map x The corresponding mold temperature evaluation index Determine an array based on the mold cooling time data x The corresponding cooling time evaluation index Based on the residual stress distribution nephogram, determine the array x corresponding cooling effect evaluation index; Among them, determining the optimal combination parameters of the optional nozzle parameters according to the multiple evaluation indexes includes: According to Y i =r R i + sS i + tT i Determine the fitness values of the evaluation indicators corresponding to all optional topping parameters; Among them, Y i is the fitness value of the evaluation index corresponding to the optional topping parameter, R i is an array x corresponding to the evaluation index of the mold temperature, S i is an array x corresponding to the evaluation index of the cooling time, T i is an array x corresponding to the evaluation index of the cooling effect, i=n ( n +1) / 2, n is the number of toppings that can be set, r, s, t is the weight coefficient, and r + s + t = 1; According to Z = min ( Y i ) determine the minimum value of the evaluation index fitness corresponding to all optional topping parameters; Among them, Z is the minimum value of the evaluation index fitness corresponding to all optional topping parameters, Y i is the evaluation index fitness corresponding to the optional topping parameter; Determine the positions and quantities of the nozzle settings corresponding to the minimum fitness value of the evaluation indexes corresponding to all optional nozzle parameters; Determine the positions and quantities of the nozzle settings corresponding to the minimum fitness value as the optimal parameters of the optional nozzle parameters.

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