Method and device for determining pouring parameters of injection mold of connector busbar

Abstract

The invention provides a method and a device for determining a pouring head parameter of an injection mold of a connector busbar. The determining method comprises the following steps: acquiring a target parameter of the connector busbar; determining a three-dimensional model of the connector busbar according to the target parameters of the connector busbar; obtaining optional pouring parameters of the injection mold matched with the three-dimensional model; according to the selectable pouring head parameters of the injection mold, a plurality of evaluation indexes corresponding to the selectable pouring head parameters are obtained; and according to the plurality of evaluation indexes, determining an optimal combination parameter of the selectable pouring head parameters. According to the embodiment of the invention, the positions and the number of the pouring heads can be precisely planned, and the product quality of the connector busbar is remarkably improved.

Description

Technical Field

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

[0002] In the injection molding production of connector busbars, the design and performance of the injection mold play a decisive role in product quality and production efficiency. The flow and cooling of plastic in the mold cavity are greatly affected by the position and number of the set pouring heads. Improper setting of the position and number of pouring heads will lead to defects such as uneven mold temperature, poor cooling and shaping, 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 injection mold pouring head parameters of a connector bus, which can accurately plan the position and quantity of the pouring head and significantly improve the product quality of the connector bus.

[0004] To solve the above technical problems, the technical solutions of the embodiments of the present invention are as follows:

[0005] A method for determining injection mold casting parameters of a connector busbar, comprising:

[0006] Get the target parameters of the connector bus;

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

[0008] Acquire optional pouring parameters of the injection mold matching the three-dimensional model;

[0009] According to the optional pouring head parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional pouring head parameters are obtained;

[0010] According to the multiple evaluation indicators, the optimal combination parameters of the optional topping parameters are determined.

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

[0012] Capture the geometry, dimensional accuracy, and wall thickness distribution of connector busbars.

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

[0014] Obtaining physical property parameters of the injection molding material of the connector busbar;

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

[0016] Optionally, obtaining optional pouring head parameters of the injection mold matching the three-dimensional model includes:

[0017] Obtaining the positions and quantities at which the pouring heads of the injection mold can be set;

[0018] According to P(x)={S|S⊆x}, the optional topping parameters are determined, where the optional topping parameters are a combination of the position and quantity of the toppings that can be set.

[0019] Where x=(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 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 pouring head parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional pouring head parameters are obtained, including:

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

[0022] Determine the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution cloud map;

[0023] Determine the cooling time evaluation index corresponding to the array x according to the mold cooling time data;

[0024] According to the residual stress distribution cloud map, the cooling effect evaluation index corresponding to the array x is determined.

[0025] Optionally, determining the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution cloud map includes:

[0026] According to the mold temperature distribution cloud map, the total difference A between the regional temperature value of each area of ​​the mold and the set temperature range is obtained. i , and the standard deviation B of the specific temperature values ​​of each area of ​​the mold i ,

[0027] Where i is the index of array x, i=n(n+1) / 2, and n is the number of toppings that can be set;

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

[0029] Optionally, determining a cooling time evaluation index corresponding to the array x according to the mold cooling time data includes:

[0030] According to the mold cooling time data, determine the first difference C between the mold overall 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 ,

[0031] Where i is the index of 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, determining the cooling effect evaluation index corresponding to the array x according to the residual stress distribution cloud map includes:

[0034] According to the residual stress distribution cloud diagram, the temperature change rate E of the entire mold per unit distance is determined. i , and the standard deviation of residual stress in each area of ​​the mold F i ,

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

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

[0037] Optionally, according to the multiple evaluation indicators, determining the optimal combination parameters of the optional topping parameters includes:

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

[0039] Among them, 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 array x, S iis the cooling time evaluation index corresponding to 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;

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

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

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

[0043] The position and quantity of the toppings corresponding to the minimum fitness value are determined as the optimal parameters of the optional topping parameters.

[0044] An embodiment of the present invention further provides a device for determining injection mold casting parameters of a connector busbar, comprising:

[0045] An acquisition module for acquiring target parameters of the connector bus and optional gating parameters of the injection mold matched with the three-dimensional model;

[0046] A processing module is used to determine the three-dimensional model of the connector bus according to the target parameters of the connector bus; obtain multiple evaluation indicators corresponding to the optional pouring parameters according to the optional pouring parameters of the injection mold; and determine the optimal combination parameters of the optional pouring parameters according to the multiple evaluation indicators.

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

[0048] The above scheme of the embodiment of the present invention constructs a three-dimensional model by acquiring the target parameters of the connector bus, and based on this, determines the optional pouring head parameters of the injection mold and their corresponding evaluation indicators, and then obtains the optimal combination parameters. This process can accurately plan the position and number of pouring heads, and effectively avoid the problem of uneven mold temperature caused by unreasonable settings. When the plastic fills the mold cavity, the reasonably distributed pouring heads can make the plastic flow evenly into various parts, ensuring that the temperature of the mold is 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.

[0049] The optimal pouring parameter combination can optimize the cooling process of the plastic in the mold. The appropriate pouring position and quantity can make the cooling medium act more evenly on the mold, promote the uniform cooling speed of the plastic, and avoid problems such as inconsistent product shrinkage and dimensional deviation caused by uneven cooling.

[0050] Unreasonable pouring head 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 pouring head parameters make the internal stress distribution more uniform when the plastic is filled and cooled in the cavity, reducing the risk of defects such as cracking and warping caused by internal stress concentration.

[0051] Since this method can significantly improve product quality and reduce product defects caused by unreasonable mold pouring parameters, it can greatly reduce the scrap rate. In the production process, the generation of scrap not only wastes raw materials and energy, but also increases production costs and production time. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a flow chart of a method for determining injection mold pouring parameters of a connector bus provided by an embodiment of the present invention.

[0053] Figure 2 It is a module schematic diagram of a device for determining injection mold pouring parameters of a connector bus provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying 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 in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

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

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

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

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

[0059] Step 14, according to the optional pouring head parameters of the injection mold, obtaining a plurality of evaluation indicators corresponding to the optional pouring head parameters;

[0060] Step 15: Determine the optimal combination parameters of the optional topping parameters based on the multiple evaluation indicators.

[0061] In this example, a three-dimensional model is constructed by obtaining the target parameters of the connector bus, and based on this, the optional pouring parameters of the injection mold and their corresponding evaluation indicators are determined to obtain the optimal combination parameters. This process can accurately plan the position and number of pouring heads, and effectively avoid the problem of uneven mold temperature caused by unreasonable settings. When the plastic fills the mold cavity, the reasonably distributed pouring heads can make the plastic flow evenly into various parts, ensuring that the temperature of the mold is 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.

[0062] The optimal pouring parameter combination can optimize the cooling process of the plastic in the mold. The appropriate pouring position and quantity can make the cooling medium act more evenly on the mold, promote the uniform cooling speed of the plastic, and avoid problems such as inconsistent product shrinkage and dimensional deviation caused by uneven cooling.

[0063] Unreasonable pouring head 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 pouring head parameters make the internal stress distribution more uniform when the plastic is filled and cooled in the cavity, reducing the risk of 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 pouring parameters, it can greatly reduce the scrap rate. 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 step of obtaining target parameters of the connector bus includes:

[0066] Step 111, obtaining the geometric shape, dimensional accuracy and wall thickness distribution of the connector bus.

[0067] In step 12, determining the three-dimensional model of the connector bus according to the target parameters of the connector bus includes:

[0068] Step 121, obtaining physical property parameters of the injection molding material of the connector bus;

[0069] Step 122 : determining a three-dimensional model of the connector bus according to the physical property parameters of the injection molding material and the target parameters of the connector bus.

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

[0071] In this example, step 111 is used to obtain target parameters such as the geometry, dimensional accuracy, and wall thickness distribution of the connector bus, providing accurate basic data for the subsequent construction of the three-dimensional model. These parameters are the core features of the connector bus. Accurately obtaining them can enable the three-dimensional model to truly restore the actual form of the product and avoid design deviations caused by the inconsistency between the model and the actual product. When constructing a three-dimensional model, based on accurate geometry and dimensional accuracy, the position and size of each part can be accurately determined, so that the model is highly consistent with the actual product in appearance and size.

[0072] Step 121 obtains physical performance parameters of the injection material, such as melt viscosity, thermal conductivity, specific heat capacity, shrinkage, and elastic modulus, and determines a three-dimensional model in combination with these parameters and target parameters in step 122. In this way, the influence of material properties on product molding can be fully considered during the model building process.

[0073] In an optional embodiment of the present invention, in step 13, obtaining optional pouring head parameters of the injection mold matching the three-dimensional model includes:

[0074] Step 131, obtaining the position and quantity of the pouring head of the injection mold that can be set;

[0075] Step 132, according to P(x)={S|S⊆x}, determine the optional topping parameters, wherein the optional topping parameters are the combination of the position and quantity of the toppings that can be set.

[0076] Where x=(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 any subset of the array x, and P(x) is the set of all subsets of the array x.

[0077] In this example, the positions and quantities of the injection mold pouring tips that can be set are obtained through step 131, and the optional pouring tips parameters are determined by using P(x)={S|S⊆x} in step 132, which can comprehensively and systematically list all possible combinations of pouring tips positions and quantities. This means that no potential pouring setting scheme will be missed, providing a rich selection space for subsequent evaluation and selection. When designing an injection mold, different pouring settings have an important impact on the flow path and filling effect of the plastic melt. A comprehensive list of schemes helps to find the pouring setting method that best suits the connector bus 3D model.

[0078] Analyzing all possible combinations of pouring parameters can provide a deep understanding of the performance of each setting during plastic filling and cooling. By simulating the flow of plastic melt under different combinations and the impact on the quality of the final product, the pros and cons of various solutions can be more accurately evaluated. This comprehensive exploration helps to discover some pouring setting solutions that may be overlooked but have a significant effect on improving product quality and production efficiency.

[0079] Reasonable pouring head settings can optimize the flow path of the plastic melt in the mold cavity, allowing the melt to fill the cavity more evenly and reduce defects caused by poor flow, such as short shots and trapped air. By evaluating a variety of optional pouring head parameter combinations, the most ideal solution for melt flow can be found, thereby improving the molding quality of the product. For connector buses with complex shapes, appropriate pouring head settings can ensure that the melt can be smoothly filled into every corner to avoid local insufficient filling.

[0080] Improper topping settings may lead to internal stress concentration in the product, thus affecting the mechanical properties and service life of the product. By fully considering various optional topping parameter combinations, a solution can be selected that can make the internal stress distribution more uniform, reducing the risk of cracking, deformation, etc. caused by internal stress problems. Reasonable topping settings can make the plastic shrink evenly during the cooling process and reduce the generation of internal stress.

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

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

[0083] Step 142, determining the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution cloud map;

[0084] Step 143, determining a cooling time evaluation index corresponding to the array x according to the mold cooling time data;

[0085] Step 144: determine the cooling effect evaluation index corresponding to the array x according to the residual stress distribution cloud map.

[0086] In this example, the mold flow analysis is performed in step 141 to obtain the mold temperature distribution cloud map, and then the mold temperature evaluation index is determined in step 142, so that the temperature distribution of the mold under different optional pouring parameters can be accurately grasped. This helps to find areas with uneven temperature, which may cause defects such as deformation and shrinkage marks on the product. Based on these evaluation indicators, the pouring parameters can be adjusted to make the mold temperature distribution more uniform, thereby improving the molding quality of the connector bus and ensuring the product dimensional accuracy and appearance quality.

[0087] The residual stress distribution cloud map obtained in step 141 and the cooling effect evaluation index determined in step 144 can give us a clear understanding of the residual stress inside the product. Excessive residual stress will reduce the mechanical properties and reliability of the product and easily cause problems such as cracking during use. By analyzing the evaluation index and adjusting the pouring 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 indicators help determine the most suitable pouring parameters and make the injection molding process more stable. A stable production process can reduce product quality problems and production failures caused by parameter fluctuations, reduce scrap rates, and improve production efficiency and production continuity.

[0089] In an optional embodiment of the present invention, in step 142, determining the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution cloud map includes:

[0090] Step 1421, according to the mold temperature distribution cloud map, obtain the total difference A between the regional temperature value 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 of array x, i=n(n+1) / 2, and n is the number of toppings that can be set;

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

[0093] Specifically, the temperature value of each area is compared with the upper and lower limits of the set temperature range, and the difference with the interval boundary is calculated.

[0094] Add the differences of all regions to get 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 settings that the nozzle can have;

[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 iThe 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 weight coefficients, and c+d=1.

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

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

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

[0110] Step 1442: according to the change rate E i and 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 rate of change of temperature per unit distance of the entire mold,

[0112] Among them, E i is the rate of change of temperature per unit distance of the entire mold, is the average value of the temperature change per unit distance at each point of the entire mold. It is the unit distance of each point of the whole mold;

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

[0114] Where m is the number of regions, is the temperature value of each region, g is the average temperature value of each region, and l is the index of the temperature value of each region;

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

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

[0117] In this example, the total difference A between the regional temperature value of each area of ​​the mold and the set temperature range is calculated in step 142. i And the standard deviation of the specific temperature value B i , and determine the mold temperature evaluation index R accordingly i , which can accurately measure the mold temperature distribution. The total difference reflects the degree of deviation of the overall temperature from the set range, and the standard deviation reflects the discreteness of the temperature distribution. This helps to find abnormal temperature areas and adjust the pouring parameters in time to make the mold temperature closer to the set range and more evenly distributed, avoiding defects such as shrinkage marks and deformation of the product due to uneven temperature, thereby improving the quality of the connector bus.

[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 determine the cooling time evaluation index S i The first difference can directly reflect whether the overall cooling time meets expectations, and the second difference can reflect the difference in cooling time in each area. Selecting appropriate pouring parameters based on these indicators can shorten the overall cooling time, reduce the difference in cooling time in each area, improve production efficiency, and shorten the injection molding cycle.

[0119] In step 144, the temperature change rate E of the entire mold per unit distance is determined. i and the standard deviation of residual stress in each area of ​​the mold F i To get the cooling effect evaluation index T i The temperature change rate reflects the uniformity of the cooling process, and the residual stress standard deviation is related to the distribution of residual stress inside the product. Reasonable cooling effect can reduce the residual stress inside the product, reduce the risk of cracking and deformation, ensure the mechanical properties and dimensional stability of the product, and improve product quality.

[0120] The optimization of pouring parameters based on comprehensive evaluation indicators can make the temperature control and cooling process in the injection molding process more stable and efficient, reduce production interruptions or adjustments caused by temperature and cooling problems, make the production process smoother, improve production continuity, and thus improve overall production efficiency.

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

[0122] Each evaluation index evaluates the injection molding process from different angles and is comprehensively considered through weight coefficients (such as a, b, c, d, e, and f). This multi-factor comprehensive consideration method more comprehensively reflects the impact of pouring 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, determining the optimal combination parameters of the optional topping parameters according to the multiple evaluation indicators includes:

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

[0125] Among them, 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 array x, S i is the cooling time evaluation index corresponding to 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;

[0126] Step 152, according to Z=min(Y i ) Determine the minimum fitness value of the evaluation index corresponding to all optional topping parameters,

[0127] Among them, Z is the minimum fitness value of the evaluation index corresponding to all optional topping parameters, Y i The fitness value of the evaluation indicator corresponding to the optional topping parameter;

[0128] Step 153, determining the position and quantity of toppings corresponding to the minimum fitness value of the evaluation index corresponding to all optional topping parameters;

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

[0130] In this example, step 151 is performed by formula Y i =rR i +sS i +tT i Calculate the fitness value of the evaluation index and set the mold temperature evaluation index R i , Cooling time evaluation index Si And cooling effect evaluation index T i In summary, mold temperature, cooling time and cooling effect will have an important impact on product quality. This comprehensive consideration can fully reflect the impact of topping parameters on product quality.

[0131] The minimum value Z of the fitness value of the evaluation index is found through step 152, and the corresponding pouring head setting position and quantity are determined as the optimal parameters in steps 153 and 154. This makes it possible to accurately select the pouring head parameter combination that can achieve the best product quality. For example, when injecting a connector bus, the optimal pouring head parameters can ensure that the plastic fills the mold cavity evenly, making the performance of each part of the product more stable and consistent.

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

[0133] After determining the optimal topping parameters, the number of adjustments due to inappropriate parameters can be reduced during the production process. Stable topping parameters help maintain the continuity and stability of production, avoid frequent debugging and downtime, and improve production efficiency.

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

[0135] The optimal topping parameters are determined by finding the minimum fitness value of the evaluation index, and the best solution can be accurately screened out from many optional topping parameter combinations.

[0136] The present invention accurately 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 flow of the melt, prevents short shots, and ensures the filling effect of products with complex shapes.

[0137] Shorten the cooling time, select appropriate pouring parameters based on the cooling time evaluation index, and shorten the molding cycle; stabilize production, reduce product problems and failures caused by parameter fluctuations, reduce scrap rate, and avoid frequent debugging and shutdown.

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

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

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

[0141] An acquisition module 21 is used to acquire target parameters of the connector bus and optional pouring parameters of the injection mold matching the three-dimensional model;

[0142] The processing module 22 is used to determine the three-dimensional model of the connector bus according to the target parameters of the connector bus; obtain multiple evaluation indicators corresponding to the optional pouring parameters according to the optional pouring parameters of the injection mold; and determine the optimal combination parameters of the optional pouring parameters according to the multiple evaluation indicators.

[0143] Optionally, obtaining target parameters of the connector bus includes:

[0144] Capture the geometry, dimensional accuracy, and wall thickness distribution of connector busbars.

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

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

[0147] A three-dimensional model of the connector bus is determined according to the physical property parameters of the injection molding material and the target parameters of the connector bus.

[0148] Optionally, obtaining optional pouring head parameters of the injection mold matching the three-dimensional model includes:

[0149] Obtaining the positions and quantities at which the pouring heads of the injection mold can be set;

[0150] According to P(x)={S|S⊆x}, the optional topping parameters are determined, where the optional topping parameters are a combination of the position and quantity of the toppings that can be set.

[0151] Where x=(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 any subset of the array x, and P(x) is the set of all subsets of the array x.

[0152] Optionally, according to the optional pouring head parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional pouring head parameters are obtained, including:

[0153] Performing mold flow analysis on the three-dimensional model of the connector busbar to obtain a mold temperature distribution cloud map, mold cooling time data, and a residual stress distribution cloud map corresponding to the array x;

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

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

[0156] According to the residual stress distribution cloud map, the cooling effect evaluation index corresponding to the array x is determined.

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

[0158] According to the mold temperature distribution cloud map, the total difference A between the regional temperature value of each area of ​​the mold and the set temperature range is obtained. i , and the standard deviation B of the specific temperature values ​​of each area of ​​the mold i ,

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

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

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

[0162] According to the mold cooling time data, determine the first difference C between the mold overall 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 ,

[0163] Where i is the index of array x, i=n(n+1) / 2, and n is the number of toppings that 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 cloud map includes:

[0166] According to the residual stress distribution cloud diagram, the temperature change rate E of the entire mold per unit distance is determined. i , and the standard deviation of residual stress in each area of ​​the mold F i ,

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

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

[0169] Optionally, according to the multiple evaluation indicators, determining the optimal combination parameters of the optional topping parameters includes:

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

[0171] Among them, 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 array x, S i is the cooling time evaluation index corresponding to 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 fitness value of the evaluation index corresponding to all optional topping parameters;

[0173] Among them, Z is the minimum fitness value of the evaluation index corresponding to all optional topping parameters, Y i The fitness value of the evaluation indicator corresponding to the optional topping parameter;

[0174] Determine the location and quantity of toppings corresponding to the minimum fitness value of the evaluation index corresponding to all optional topping parameters;

[0175] The position and quantity of the toppings corresponding to the minimum fitness value are determined as the optimal parameters of the optional topping parameters.

[0176] It should be noted that the device is a device corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0177] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining injection mold casting parameters of a connector bus, characterized in that: include: Get the target parameters of the connector bus; Determining a three-dimensional model of the connector bus according to target parameters of the connector bus; Acquire optional pouring parameters of the injection mold matching the three-dimensional model; According to the optional pouring head parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional pouring head parameters are obtained; According to the multiple evaluation indicators, the optimal combination parameters of the optional topping parameters are determined.

2. The method for determining injection mold casting parameters of a connector busbar according to claim 1, characterized in that: The step of obtaining target parameters of the connector bus includes: Capture the geometry, dimensional accuracy, and wall thickness distribution of connector busbars.

3. The method for determining injection mold casting parameters of a connector busbar according to claim 2, characterized in that: Determining the three-dimensional model of the connector bus according to the target parameters of the connector bus includes: Obtaining physical property parameters of the injection molding material of the connector busbar; A three-dimensional model of the connector bus is determined according to the physical property parameters of the injection molding material and the target parameters of the connector bus.

4. The method for determining injection mold casting parameters of a connector busbar according to claim 1, characterized in that: Obtain optional pouring parameters of the injection mold matching the 3D model, including: Obtaining the positions and quantities at which the pouring heads of the injection mold can be set; According to P(x)={S|S⊆x}, the optional topping parameters are determined, where the optional topping parameters are a combination of the position and quantity of the toppings that can be set. Where x=(x1,...,x n ), x1, ..., x n is the position where the topping can be set, n is the number of toppings 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.

5. The method for determining injection mold casting parameters of a connector busbar according to claim 4, characterized in that: According to the optional pouring head parameters of the injection mold, a plurality of evaluation indicators corresponding to the optional pouring head parameters are obtained, including: Performing mold flow analysis on the three-dimensional model of the connector busbar to obtain a mold temperature distribution cloud map, mold cooling time data, and a residual stress distribution cloud map corresponding to the array x; Determine the mold temperature evaluation index corresponding to the array x according to the mold temperature distribution cloud map; Determine the cooling time evaluation index corresponding to the array x according to the mold cooling time data; According to the residual stress distribution cloud map, the cooling effect evaluation index corresponding to the array x is determined.

6. The method for determining injection mold casting parameters of a connector busbar according to claim 5, characterized in that: According to the mold temperature distribution cloud map, the mold temperature evaluation index corresponding to the array x is determined, including: According to the mold temperature distribution cloud map, the total difference A between the regional temperature value of each area of ​​the mold and the set temperature range is obtained. i , and the standard deviation B of the specific temperature values ​​of each area of ​​the mold i , Where i is the index of array x, i=n(n+1) / 2, and n is the number of toppings that can be set; According to the total difference A i and standard deviation B i , determine the mold temperature evaluation index R corresponding to the array x i .

7. The method for determining injection mold casting parameters of a connector busbar according to claim 5, characterized in that: According to the mold cooling time data, the cooling time evaluation index corresponding to the array x is determined, including: According to the mold cooling time data, determine the first difference C between the mold overall 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 , Where i is the index of array x, i=n(n+1) / 2, and n is the number of toppings that can be set; 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 .

8. The method for determining injection mold casting parameters of a connector busbar according to claim 5, characterized in that: According to the residual stress distribution cloud map, the cooling effect evaluation index corresponding to the array x is determined, including: According to the residual stress distribution cloud diagram, the temperature change rate E of the entire mold per unit distance is determined. i , and the standard deviation of residual stress in each area of ​​the mold F i , Where i is the index of all combinations of the positions and quantities of toppings that can be set, i=n(n+1) / 2, n is the number of toppings that can be set; According to the change rate E i and standard deviation F i , determine the cooling effect evaluation index T corresponding to the array x i .

9. The method for determining injection mold casting parameters of a connector busbar according to any one of claims 5 to 8, characterized in that: According to the multiple evaluation indicators, the optimal combination parameters of the optional topping parameters are determined, including: According to Y i =rR 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 the mold temperature evaluation index corresponding to array x, S i is the cooling time evaluation index corresponding to 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; According to Z=min(Y i ) Determine the minimum fitness value of the evaluation index corresponding to all optional topping parameters; Among them, Z is the minimum fitness value of the evaluation index corresponding to all optional topping parameters, Y i The fitness value of the evaluation indicator corresponding to the optional topping parameter; Determine the location and quantity of toppings corresponding to the minimum fitness value of the evaluation index corresponding to all optional topping parameters; The position and quantity of the toppings corresponding to the minimum fitness value are determined as the optimal parameters of the optional topping parameters.

10. A device for determining injection mold casting parameters of a connector bus, characterized in that: include: An acquisition module for acquiring target parameters of the connector bus and optional gating parameters of the injection mold matched with the three-dimensional model; A processing module is used to determine the three-dimensional model of the connector bus according to the target parameters of the connector bus; obtain multiple evaluation indicators corresponding to the optional pouring parameters according to the optional pouring parameters of the injection mold; and determine the optimal combination parameters of the optional pouring parameters according to the multiple evaluation indicators.

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