Methods for controlling the opening and closing stroke of an electric injection molding machine

Abstract

This application discloses a method for controlling the opening and closing stroke of an electric injection molding machine, including the following steps: S1: Obtain the key geometric parameters of the elbow system in the five-hinge-point inclined double-curved elbow clamping mechanism, based on the moving platen stroke (S m ) and ball screw drive stroke (S o S1: Based on the theoretical formula of the ball screw drive stroke and the moving template stroke, adjust the main variable conditions of the mechanism kinematic chain to obtain the data correlation point between the ball screw drive stroke and the moving template stroke; S2: Construct the moving template stroke (S) based on the data obtained in step S1. m ) and ball screw drive stroke (S o A function mapping model between ) forms S m =f(S) o S3: Establish the inverse fitting function, forming S... o =(S m This application achieves inverse control by accurately fitting the relationship between the template and the ball screw stroke, thereby reducing the error caused by interpolation, improving the system control accuracy during mold opening and closing, significantly improving computational efficiency, saving storage space, and further reducing costs.

Description

Technical Field

[0001] This application relates to the field of electric injection molding machine technology, and in particular to a method for controlling the opening and closing stroke of an electric injection molding machine. Background Technology

[0002] Electric injection molding machines are injection molding machines that use AC servo motors, along with components such as ball screws, toothed belts, and gears, to drive various mechanisms. They effectively ensure the stability of plasticization and metering, enabling high-quality injection molding of everything from general-purpose resins to engineering plastics.

[0003] Currently, electric injection molding machines commonly employ five-hinged, inclined, double-cranked toggle mold closing mechanisms to achieve mold closing and opening. These mechanisms typically use ball screws as drive elements, utilizing linear reciprocating motion to move the moving platen to complete mold closing or opening operations. Existing technologies often employ open-loop control, using the ball screw's drive stroke as the basis for estimating the moving platen displacement. However, due to the complex structure of the five-hinged toggle mechanism and the nonlinear coupling relationships between multiple kinematic pairs, the ball screw drive stroke and the moving platen displacement do not form a linear or analytical mapping relationship. Therefore, existing technologies generally use interpolation or lookup table methods to establish an approximate mapping between the two. However, these methods struggle to maintain control accuracy when the mechanism exhibits high nonlinearity or significant dynamic response changes, easily leading to positional deviations that affect product dimensional accuracy and injection molding quality.

[0004] Therefore, there is an urgent need for a control method that can accurately describe the relationship between the ball screw drive stroke and the actual displacement of the moving platen, in order to improve the control accuracy and product quality of the injection molding process. Summary of the Invention

[0005] The purpose of this application is to provide a method for controlling the opening and closing stroke of an electric injection molding machine. By accurately fitting the relationship between the template and the ball screw drive stroke, reverse control is achieved, thereby reducing the error caused by the use of interpolation method to improve the system control accuracy, greatly improving the calculation efficiency, saving storage space and further reducing costs.

[0006] To achieve the above objectives, the technical solution adopted in this application is: a method for controlling the opening and closing stroke of an electric injection molding machine, comprising the following steps: S1: obtaining the key geometric parameters of the elbow system in the five-hinge-point inclined double-curved elbow mold closing mechanism, based on the moving platen stroke (S m ) and ball screw drive stroke (S o S1: Based on the theoretical formula of the mechanism's kinematic chain, adjust the variable conditions to obtain the data correlation points between the moving template stroke and the ball screw drive stroke; S2: Construct the moving template stroke (S) based on the data obtained in step S1. m ) and ball screw drive stroke (S o A function mapping model between ) forms Sm =f(S) o S3: Establish the inverse fitting function, forming S... o = (S) m Function mapping of ).

[0007] Compared with existing technologies, the advantages of this application are as follows: Traditional control methods calculate the position of the moving template based on the ball screw drive stroke. This invention adopts a reverse design, that is, using the target moving template stroke as input, it reverses the required ball screw drive stroke, thereby driving the mold closing mechanism to complete the expected motion trajectory, realizing reverse drive control and ensuring the requirements of the mold opening process; through mathematical models and kinematic simulations, a precise mapping relationship between the template stroke and the ball screw drive stroke is established, achieving accurate fitting of the template and ball screw drive stroke relationship; thereby reducing the error caused by the use of interpolation methods to improve the system control accuracy, ensuring that the actual stroke of the ball screw can be accurately calculated given the template stroke, and replacing the traditional interpolation method with a fitting function simplifies system storage and computational complexity, saves storage space, significantly improves computational efficiency, saves storage space, and further reduces costs.

[0008] As an improvement, in step S1, the five-hinge-point inclined double-crank elbow mold-closing mechanism includes a first crank-slider group and a second crank-slider group. The first crank-slider group includes a large crankshaft L1, a large connecting rod L2, and a moving template. The second crank-slider group includes a small crankshaft L3, a small connecting rod L4, and a crosshead. The large crankshaft is fixedly connected to the small crankshaft and rotates synchronously around the hinge point D at the same angular velocity. The crosshead drives the connection point B to make the moving template reciprocate linearly along the horizontal guide rail. Through the above improvement, by obtaining the variable conditions of the mechanism's kinematic chain through key positions, kinematic relationships can be established and a fitting dataset can be generated, which facilitates data analysis and further enables reverse control.

[0009] As an improvement, step S1 includes step S11: the variable conditions of the mechanism kinematic chain include the mechanism position variable, and the stroke of the moving template (S) is established according to the transmission mechanism between the moving template and the ball screw. m ) and ball screw drive stroke (S o The motion relationship model of the mechanism is used to derive the corresponding stroke transformation equations from the position variables of the mechanism, forming a calculation expression: S m =( + ) ; ; In the formula, The angle of rotation of the elbow lever. These represent the oblique angle and the elbow wedge angle of the mechanism, respectively; L1~L4 are the length parameters of each link of the mechanism; and L5 is the distance parameter between the intersection point of the small crankshaft link L3 and the small connecting rod L4 and the hinge point D. The angle of the inclined mounting of the mechanism, The angle between the small connecting rod and the horizontal line. The angle between the connecting rod and the horizontal line. The angle between the large and small elbows. H is the angle at which the toggle rotates from the initial mold-closing position; H is the vertical distance from the hinge point D to the center of the crosshead; H1 is the half-length dimension of the crosshead; S m and S o and represent the stroke of the moving template and the crosshead, respectively; through the above improvements, based on the transmission structure between the moving template and the ball screw, and based on the geometric constraints and kinematic characteristics of the toggle mechanism, the relationship between the driving stroke of the template and the ball screw can be accurately fitted.

[0010] As an improvement, an equal probability sampling method is set, and the elbow rotation angle is sampled within a preset range. Randomly select N sample points and calculate the corresponding ball screw drive stroke S for each. o With dynamic template stroke S m This generates a numerical dataset containing N pairs of samples. Through the above improvements, while keeping all structural parameters unchanged, the dataset is evenly distributed in the angle space, which can fully cover the entire motion range of the mold closing mechanism from mold opening to mold closing, and serve as the basic input for subsequent forward and inverse function fitting modeling, providing data support for high-precision modeling of complex nonlinear relationships.

[0011] As an improvement, step S2 further includes step S22: obtaining N sets of sample data According to the template schedule S m Sort the data in ascending order, perform first-order difference processing on the data, and calculate the slope between adjacent points:

[0012] i = 1, 2, ..., N 1;

[0013] Based on the obtained slope sequence Construct slope change curves and identify local slope abrupt change points. Or at the point of significant transition of second-order difference For the larger one, determine the corresponding interval partitioning points x1, x2, ..., x3. k Through the above improvements, by introducing a piecewise polynomial function fitting strategy, the... and The mapping relationship between them is modeled in partitions to improve the overall fitting accuracy and local response sensitivity.

[0014] As an improvement, step S2 further includes step S23: constructing a fitting function, based on the divided stage intervals, in each segmented interval Inside, use n j A polynomial function of order 1 is fitted, and the coefficients of the selected polynomial are parametrically solved using the least squares method. The sum of squared residuals is constructed as the objective function. By taking the partial derivative of each coefficient and setting it to zero, a system of linear equations is formed. Solving the system of linear equations yields the optimal polynomial coefficients that minimize the sum of squared fitting errors. The optimal polynomial system that minimizes the sum of squared fitting errors is then established, and a derivative continuity constraint is introduced. Through the above improvements, the fitting coefficients are solved and the model is optimized. By taking the partial derivative of each coefficient and setting it to zero, a normal system of equations that satisfies the condition of minimizing errors can be obtained. By solving the above system of linear equations, the optimal polynomial coefficients that minimize the sum of squared fitting errors can be obtained, ensuring the continuity of the overall fitting function at each segment junction and ensuring that the fitting curve has smooth transition characteristics.

[0015] As an improvement, step S3 includes step S31: establishing a dynamic template (S based on a data-driven inverse fitting modeling method). m ) to ball screw drive stroke (S o The function mapping relationship is obtained, and inverse solution and model optimization are performed. Through the above improvements, the data-driven inverse fitting modeling method can fully realize the application requirements of inversely calculating the required screw displacement from the target template stroke in actual control.

[0016] As an improvement, step S3 further includes step S32: by inverse data fitting, with S m As the independent variable, S o As the dependent variable, based on the fitted dataset The inverse mapping model is reconstructed. Through the above improvements, inverse solution and model optimization, and through the strategy of inverse data fitting, the inverse mapping model is reconstructed, thereby establishing a stable and high-precision inverse mapping relationship throughout the entire working range.

[0017] As an improvement, step S3 further includes step S33: when the function value is in the low stroke segment, a composite logarithmic fitting function is used to represent it. When the function value is located in the middle or high displacement segment, a low-order polynomial model is used, and the fitting function for the middle segment is expressed as follows: The high-segment fitting function is expressed as follows: In the formula, a k b k The parameters to be fitted are... This represents a logarithmic function with base 2. Through the above improvements, the inverse model selects multinomial logarithmic functions and polynomial functions for piecewise modeling in each sub-interval. In the low-stroke segment, a composite logarithmic fitting function is used to improve the modeling accuracy. In the medium-to-high displacement segment, the data distribution tends to be smoother, and the trend is more suitable for low-order polynomial modeling.

[0018] As an improvement, step S3 further includes step S34: using the least squares method to optimize the fitting of the coefficients of each piecewise function, constructing the sum of squared fitting residuals as the objective function, and constructing a system of linear equations by taking the partial derivative of each coefficient and setting its partial derivative to zero; solving the system of linear equations to obtain the optimal polynomial coefficients that minimize the sum of squared fitting errors; fitting the optimal polynomial system that minimizes the sum of squared fitting errors, and introducing derivative continuity constraints. Through the above improvements, the fitting curve is smoothed at the connection points of each segment to ensure that the overall function has good continuity and smoothness at the boundary points. Attached Figure Description

[0019] Figure 1 A simplified kinematic diagram of the five-hinge-point inclined double-curved elbow mold closing mechanism of this application;

[0020] Figure 2 A graph of data after sampling 500 samples;

[0021] Figure 3 This is a mapping relationship diagram of the fitting of the moving template displacement based on the ball screw displacement input;

[0022] Figure 4 This is a mapping diagram of the ball screw displacement fitted based on the displacement input of the moving template;

[0023] Figure 5 This is a diagram showing the fitting mapping relationship of the moving template displacement based on interpolation.

[0024] Figure 6 This is a diagram showing the displacement fitting mapping relationship of a ball screw based on interpolation.

[0025] Figure 7 The mapping relationship between the displacement fitting of the moving template without smoothness is shown in the figure.

[0026] Figure 8 This is a mapping diagram for the displacement fitting of a ball screw without smoothness. Detailed Implementation

[0027] The present application will now be further described in conjunction with specific embodiments. It should be noted that, in the description of this specification, the use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicates that the specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0028] In the description of this application, it should be noted that the terms "center", "lateral", "longitudinal", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., which indicate the orientation and positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and should not be construed as limiting the specific protection scope of this application.

[0029] It should be noted that the terms "first," "second," etc., in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0030] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0031] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0032] The terms “comprising” and “having”, and any variations thereof, in the specification and claims of this application are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0033] This application discloses a method for controlling the mold opening and closing stroke of an electric injection molding machine, such as... Figure 1-8 As shown, the process includes the following steps: S1: Kinematic modeling and data collection, obtaining the key geometric parameters of the elbow-bar system in the five-hinge inclined double-curved elbow mold-closing mechanism, based on the dynamic template stroke (S m ) and ball screw drive stroke (S o S1: Using the theoretical formula of the motion chain, adjust the variable conditions of the mechanism's kinematic chain to obtain the data correlation points between the moving template stroke and the ball screw drive stroke; S2: Construct the fitting function. Based on the data obtained in step S1, select an appropriate function type to construct the moving template stroke (S... m ) and ball screw drive stroke (S o A function mapping model between ) forms S m =f(S) o S3: Establish an inverse fitting function. For application scenarios in actual control systems where the target travel distance of the moving template is a known quantity, further establish an inverse fitting function. By inverting the original fitting function or constructing a new fitting model, form S... o = (S) m The function mapping is used to calculate the required drive stroke of the ball screw from the template stroke, thereby achieving precise control of the mold opening process.

[0034] It should be noted that this application, by collecting actual data on the ball screw drive stroke and the corresponding moving template stroke, and combining the kinematic characteristics and geometric constraints of the five-hinged double-curved elbow mold clamping mechanism, establishes a functional mapping relationship between the moving template stroke and the ball screw drive stroke using a fitting modeling method, thereby achieving high-precision control of the actual stroke of the moving template in the mold clamping mechanism. Unlike the traditional control method's "forward design" approach of calculating the moving template position based on the ball screw drive stroke, this invention adopts a "reverse design" concept. That is, using the target moving template stroke as input, the required ball screw drive stroke is calculated backward, thereby driving the mold clamping mechanism in reverse to complete the expected motion trajectory, achieving reverse drive control. By optimizing the design objectives, the relationship between the template and the ball screw drive stroke is accurately fitted, improving system control accuracy and simplifying system storage and computational complexity.

[0035] Specifically, such as Figure 1 As shown, in the five-hinge inclined double-crank elbow mold-closing mechanism used in this invention, the power transmission between the ball screw and the moving template is jointly completed by the first crank-slider group and the second crank-slider group. In step S1, the five-hinge inclined double-crank elbow mold-closing mechanism includes the first crank-slider group and the second crank-slider group. The first crank-slider group includes a large crankshaft L1, a large connecting rod L2, and a moving template. The second crank-slider group includes a small crankshaft L3, a small connecting rod L4, and a crosshead. The large crankshaft and the small crankshaft are fixedly connected and rotate synchronously around the hinge point D with the same angular velocity. The crosshead drives the connection point B to make the moving template reciprocate linearly along the horizontal guide rail.

[0036] It should be noted that, Figure 1 The solid line represents the limit position of the mechanism under mold closing condition, and the dashed line corresponds to the limit position under mold opening condition. The moving platen acts as a slider in this mechanism, the crosshead is used as a slider element, and the large crankshaft rod L1 and the small crank elbow rod L3 are rigidly connected to form a whole.

[0037] Specifically, step S1 includes step S11: the variable conditions of the mechanism kinematic chain include the mechanism position variable, and the moving template stroke (S) is established according to the transmission mechanism between the moving template and the ball screw. m ) and ball screw drive stroke (S o The motion relationship model is used to derive the corresponding stroke transformation equations from the mechanism position variables (including elbow angle, link length, arrangement angle, etc.), forming the calculation expression: S m =( + ) ; .

[0038] In the formula, represents the rotation angle of the elbow, represents the oblique angle and the elbow wedge angle, respectively; L1~L4 are the length parameters of each link of the mechanism; L5 is the distance parameter between the intersection point of the small crankshaft link L3 and the small connecting rod L4 and the hinge point D; represents the oblique mounting angle of the mechanism; represents the angle between the small connecting rod and the horizontal line (wedge angle); represents the angle between the large connecting rod and the horizontal line; represents the angle between the large and small elbows; represents the angle of rotation of the elbow from the initial position of mold closing; H is the vertical distance from the hinge point D to the center of the crosshead; H1 is the half-length dimension of the crosshead; S... m and S o and represent the travel distances of the moving template and the crosshead, respectively.

[0039] Specifically, step S2 includes step S21: setting an equal probability sampling method, and within a preset range, sampling the elbow rotation angle. Randomly select N sample points and calculate the corresponding ball screw drive stroke S for each. o With dynamic template stroke S m This generates a numerical dataset containing N pairs of samples. .

[0040] Example 1: As Figure 2 As shown, while keeping all structural parameters unchanged, in order to fully cover the motion characteristics of the entire workspace, an equal probability sampling method is adopted to sample the elbow rotation angle within a reasonable design range. 500 sample points were randomly selected. Each set of rotation angle values ​​was substituted into the kinematic model described above to calculate the corresponding ball screw drive stroke. With dynamic template stroke This generates a numerical dataset containing 500 paired samples. This dataset is uniformly distributed in the angle space, which can fully cover the entire motion range of the mold closing mechanism from mold opening to mold closing, and serves as the basic input for subsequent forward and inverse function fitting modeling, providing data support for high-precision modeling of complex nonlinear relationships.

[0041] Understandably, due to the highly nonlinear and inconsistent segmental variation in the mapping relationship between the moving template stroke and the ball screw drive stroke, it is difficult to simultaneously ensure accuracy and stability using a single global function for fitting, which can easily lead to problems such as excessive fitting deviation or numerical oscillations in certain regions. Therefore, a piecewise polynomial function fitting strategy is adopted to... and The mapping relationship between them is modeled in partitions to improve the overall fitting accuracy and local response sensitivity.

[0042] Specifically, step S2 also includes step S22: obtaining N sets of sample data According to the template schedule S mSort the data in ascending order, perform first-order difference processing on the data, and calculate the slope between adjacent points: i = 1, 2, ..., N 1; Based on the obtained slope sequence Construct a slope variation curve, then analyze the trend of this curve throughout the entire travel range, and identify local slope abrupt change points. Or at the point of significant transition of second-order difference For the larger one, determine the corresponding interval partitioning points x1, x2, ..., x3. k .

[0043] Specifically, step S2 also includes step S23: constructing the fitting function, based on the divided stage intervals, in each segment interval Inside, use n j Fitting is performed using a polynomial function of order 1.

[0044] Right now: ,in, Let be the multinomial coefficient of the j-th segment.

[0045] Preferably, the fitting coefficients are solved and the model is optimized. To obtain the optimal polynomial fitting function within each segmented interval, the least squares method is used to solve for the parameters of the selected polynomials, and the sum of squared fitting residuals is constructed as the objective function: .

[0046] in, This represents the true value of the i-th template stroke in the sample. This represents the predicted value of the fitted function at that point. This is achieved by adjusting each coefficient... Taking the partial derivatives and setting them to zero, we obtain the normal equations that satisfy the condition for minimizing the error: 0, m=0,1,…… Arranging the above system of equations, we can form the following system of linear equations in matrix form: .

[0047] in, The coefficient matrix, whose elements are represented as: p,q=0,1,…… ; Let be the vector of polynomial coefficients to be determined; Let the right-hand term vector be represented as follows: p=0,1,……, .

[0048] Preferably, by solving the above system of linear equations, the optimal polynomial coefficients that minimize the sum of squared fitting errors can be obtained. Then, to ensure the continuity of the overall fitting function at each segment junction, the fitting function must satisfy the following condition at the junction points: = If necessary, introduce derivative continuity constraints: = This is to ensure that the fitted curve has smooth transition characteristics.

[0049] Example 2: As Figure 3 As shown, the experimental results of the fitting function are analyzed.

[0050] First-stage fitting: The ball screw displacement is within the range of 0~85mm, and the following fifth-order polynomial is used for fitting: .

[0051] in, x represents the displacement of the moving template; x represents the displacement of the ball screw. , = -1.4927e-08, =1.7395e-05, = -1.5153e-04, = 0.0233, = -0.0925. When the ball screw displacement = 65mm, substituting into the above formula, the moving template displacement can be calculated as = 5.2924mm, which has an error of 0.0476mm compared with the corresponding original given data of 5.34mm.

[0052] Second-stage fitting: When the ball screw displacement is within the range of 85~445mm, the following fifth-order polynomial is used for fitting: .

[0053] in, =3.914837e-08, = -5.85635e-05, =0.032683886, =-5.793008, =369.3053885. For example, when the ball screw displacement = 395mm, substituting into the above formula, the moving template displacement can be calculated as =524.3295, which has an error of 0.0795 mm compared to the corresponding original given data of 524.25 mm.

[0054] Specifically, step S3 includes step S31: After completing the forward mapping model construction of the ball screw drive stroke and the moving template stroke, based on the data-driven inverse fitting modeling method, the moving template stroke (S) is established. m ) to ball screw drive stroke (S o The function mapping relationship is determined, and the inverse solution and model optimization are performed.

[0055] Specifically, step S3 also includes step S32: fitting the data in reverse, with S m As the independent variable, S o As the dependent variable, based on the fitted dataset The inverse mapping model is then reconstructed. Since the forward model is a highly nonlinear relationship, its inverse function is difficult to solve analytically directly. Therefore, inverse solution and model optimization are performed through step S32.

[0056] Preferably, considering the function characteristics of different segments, the inverse model uses multinomial logarithmic functions and polynomial functions for segmented modeling in each sub-interval, thereby establishing a stable and high-precision inverse mapping relationship throughout the entire working range.

[0057] Specifically, step S3 further includes step S33: When the function value is in the low stroke segment, the data change rate is significantly nonlinear, conventional polynomial fitting is difficult to converge, and the fitting error is relatively large. A composite logarithmic fitting function is adopted, and the fitting function is expressed as:

[0058] When the function value is in the middle or high displacement range, the data distribution tends to be smooth, and the trend is more suitable for modeling with low-order polynomials. The fitting function for the middle range is expressed as: ; The high-segment fitting function is expressed as: ; In the formula, a k b k The parameters to be fitted are... It represents a logarithmic function with base 2.

[0059] Specifically, step S3 also includes step S34: using the least squares method to optimize the fitting of the coefficients of each piecewise function, constructing the sum of squared fitting residuals as the objective function, and constructing a linear equation system by taking the partial derivative of each coefficient and setting its partial derivative to zero; solving the linear equation system to obtain the optimal polynomial coefficients with the minimum sum of squared fitting errors; fitting the optimal polynomial system with the minimum sum of squared fitting errors, and introducing derivative continuity constraints.

[0060] Example 3: Analysis of experimental results for fitting function in the low stroke segment. When the displacement range of the moving template is 0 ~ 35 mm, the original data distribution within this range exhibits strong nonlinear characteristics, resulting in poor fitting performance of traditional linear or polynomial models. Therefore, a fourth-order logarithmic polynomial model is selected for modeling. The fitting function expression is as follows: ; Where x represents the displacement S of the moving template m , =0.00748246, =0.06791582, =1.1941003, =10.458000, =31.492866. When the displacement of the moving template x=2.2mm, substituting into the above formula, the displacement of the lead screw can be calculated as =45.04643, which has an error of 0.04643mm compared with the corresponding original given data of 45.0mm.

[0061] Example 4: Analysis of experimental results for the fitting function in the middle stroke segment. When the displacement of the moving template is within the range of 35~155 mm, the data distribution in the middle stroke segment is relatively smooth, making it suitable for fitting with a fourth-order polynomial function. The expression of the fitting function is as follows: + + + ; in, = -1.785110e-07, = 8.6516e-05, = -0.016958, = 2.2116234, = 70.82277. When the displacement of the moving template x = 61.28 mm, substituting into the above formula, the displacement of the lead screw can be calculated as follows: =160.0615, which is 0.0615mm different from the original given data of 160mm.

[0062] Example 5: Analysis of experimental results for fitting function in high stroke segment. The displacement of the moving template is in the range of 155~642mm. The following formula is used for fitting: + + + ; in, = 3.54869978e-07, = -0.000483, = 0.6508975, = 134.93843; When the displacement of the moving template x = 3196.4 mm, substituting into the above formula, the displacement of the lead screw can be calculated as follows: =305.2325, which is 0.2325mm different from the original given data of 305mm.

[0063] It is understandable that, such as Figure 5 and Figure 6 As shown, the traditional interpolation method is significantly inferior to the method proposed in this design in terms of both fitting accuracy and transition smoothness. Figure 7 and Figure 8 As shown, the data results further demonstrate the performance of the proposed stage function before and after smoothing: before smoothing, the function exhibits significant fluctuations at the contact point, while after smoothing, it achieves better continuity and transition, verifying the advantages of this method in segmented connection processing.

[0064] The basic principles, main features, and advantages of this application have been described above. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are merely the principles of this application. Various changes and modifications can be made to this application without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claims. The scope of protection claimed by this application is defined by the appended claims and their equivalents.

Claims

1. A method for controlling the mold opening and closing stroke of an electric injection molding machine, characterized in that, Includes the following steps: S1: Obtain the key geometric parameters of the elbow system in the five-hinge-point inclined double-curved elbow mold closing mechanism, based on the moving template stroke (S m ) and ball screw drive stroke (S o The theoretical formula of the mechanism's kinematic chain is used to adjust the variable conditions to obtain the data correlation points between the moving template stroke and the ball screw drive stroke. S2: Construct the dynamic template process based on the data obtained in step S1 (S m ) and ball screw drive stroke (S o A function mapping model between ) forms S m =f(S) o Fitting expressions in the form of ) S3: Establish the inverse fitting function to form S o = (S) m Function mapping of ) Step S3 includes step S31: establishing a dynamic template stroke (S) based on a data-driven inverse fitting modeling method. m ) to ball screw drive stroke (S o The function mapping relationship is determined, and the inverse solution and model optimization are performed. Step S3 further includes step S32: fitting the data in reverse order to S m As the independent variable, S o As the dependent variable, based on the fitted dataset Reconstruct the inverse mapping model; Step S3 further includes step S33: When the function value is in the lower range of the stroke, a composite logarithmic fitting function is used, which is expressed as: ； When the function value is located in the middle or high displacement segment, a low-order polynomial model is used, and the fitting function for the middle segment is expressed as: ； The high-segment fitting function is expressed as follows ; In the formula, a k b k The parameters to be fitted are... It represents a logarithmic function with base 2.

2. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 1, characterized in that: In step S1, the five-hinge inclined double-crank elbow mold closing mechanism includes a first crank-slider group and a second crank-slider group. The first crank-slider group includes a large crankshaft L1, a large connecting rod L2, and a moving template. The second crank-slider group includes a small crankshaft L3, a small connecting rod L4, and a crosshead. The large crankshaft is fixedly connected to the small crankshaft and rotates synchronously around the hinge point D at the same angular velocity. The crosshead drives the connection point B to make the moving template reciprocate linearly along the horizontal guide rail.

3. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 2, characterized in that, Step S1 includes step S11: The variable conditions of the mechanism kinematic chain include the mechanism position variable. Based on the transmission mechanism between the moving template and the ball screw, the stroke (S) of the moving template is established. m ) and ball screw drive stroke (S o The motion relationship model of the mechanism is used to derive the corresponding stroke transformation equations through the position variables of the mechanism, forming a calculation expression: S m =（ + ） ； ； In the formula, The angle of rotation of the elbow lever. These represent the oblique angle and the elbow wedge angle of the mechanism, respectively; L1~L4 are the length parameters of each link of the mechanism; and L5 is the distance parameter between the intersection point of the small crankshaft link L3 and the small connecting rod L4 and the hinge point D. The angle of the inclined mounting of the mechanism, The angle between the small connecting rod and the horizontal line. The angle between the connecting rod and the horizontal line. The angle between the large and small elbows. H is the angle at which the toggle rotates from the initial mold-closing position; H is the vertical distance from the hinge point D to the center of the crosshead; H1 is the half-length dimension of the crosshead; S m S0 and S0 represent the travel distances between the moving template and the crosshead, respectively.

4. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 1, characterized in that, Step S2 includes step S21: setting an equal probability sampling method, and within a preset range, sampling the elbow rotation angle. Randomly select N sample points and calculate the corresponding ball screw drive stroke S for each. o With the dynamic template stroke S m This generates a numerical dataset containing N pairs of samples. .

5. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 4, characterized in that, Step S2 further includes step S22: obtaining N sets of sample data According to the template schedule S m Sort the data in ascending order, perform first-order difference processing on the data, and calculate the slope between adjacent points: ,i=1,2,……,N 1; Based on the obtained slope sequence Construct slope change curves and identify local slope abrupt change points. Or at the point of significant transition of second-order difference For the larger one, determine the corresponding interval partitioning points x1, x2, ..., x3. k .

6. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 5, characterized in that, Step S2 further includes step S23: constructing a fitting function, based on the divided stage intervals, in each segment interval Inside, use n j A polynomial function of order 1 is fitted, and the coefficients of the selected polynomial are parametrically solved using the least squares method. The sum of squared residuals is constructed as the objective function. By taking the partial derivative of each coefficient and setting it to zero, a system of linear equations is formed. Solving the system of linear equations yields the optimal polynomial coefficients that minimize the sum of squared fitting errors. The optimal polynomial system that minimizes the sum of squared fitting errors is then determined, and a derivative continuity constraint is introduced.

7. The method for controlling the mold opening and closing stroke of an electric injection molding machine as described in claim 1, characterized in that, Step S3 further includes step S34: using the least squares method to optimize the fitting of the coefficients of each piecewise function, constructing the sum of squared fitting residuals as the objective function, and constructing a linear equation system by taking the partial derivative of each coefficient and setting its partial derivative to zero; solving the linear equation system to obtain the optimal polynomial coefficients with the minimum sum of squared fitting errors; and introducing a derivative continuity constraint to obtain the optimal polynomial system with the minimum sum of squared fitting errors.

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