Injection speed determination method and device, injection molding method and device and electronic equipment

Abstract

The invention provides an injection speed determination method and device, an injection molding method and device and electronic equipment, and belongs to the field of intelligent manufacturing, and the method comprises the steps that an injection molding machine is controlled to conduct injection according to multiple different set injection speeds, the actual filling time and the actual injection pressure peak value at each set injection speed are obtained, and a relative viscosity index is obtained through calculation; and determining the change trend characteristics of the relative viscosity index along with the set injection speed based on the relative viscosity index, and determining the target injection speed of the injection molding machine. The physical principle that the injection pressure and the filling time represent the viscosity under the constant volume is utilized, a rheology curve can be constructed without an external rheometer, the optimal process point is automatically locked by identifying the stable trend of the curve, the problems that traditional injection molding depends on empirical machine adjustment, and the flowability cannot be objectively quantified are solved, and the production efficiency is improved. And accurate and automatic setting of scientific mold testing and process parameters is realized.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing, and in particular to an injection speed determination and injection molding method, apparatus, and electronic device. Background Technology

[0002] Injection molding is one of the most widely used plastic processing technologies in modern manufacturing. The quality of its products largely depends on the setting of process parameters, among which injection speed is a key factor affecting melt filling behavior and the final product performance. As injection-molded products develop towards precision and thinner walls, the requirements for the control precision of the injection molding process are increasing. In actual production and mold testing, how to quickly and accurately determine the optimal injection speed suitable for the current mold and material characteristics, and establish a scientific process window, is a common technical need in the field of injection molding.

[0003] To determine the appropriate injection speed, existing technologies typically employ trial and error or utilize auxiliary measuring equipment. Trial and error relies heavily on the experience of senior process engineers, gradually approaching a feasible range by repeatedly adjusting the injection speed and observing product appearance defects (such as short shots, flash, and scorching). Furthermore, some high-precision molding scenarios introduce online rheometers or in-mold pressure sensors to assist in judgment by measuring the actual shear viscosity of the melt within the runner or the mold cavity pressure curve. Some injection molding machine control systems also attempt to indirectly assess the filling state by monitoring single variables such as peak injection pressure or filling time.

[0004] However, the aforementioned existing technologies have significant limitations in practical applications. On the one hand, the trial-and-error process relying on human experience lacks objective data support, has poor adaptability to new molds or materials, and the results obtained by different personnel are inconsistent, making it difficult to standardize process parameters. On the other hand, although rheometers or in-mold sensors can provide relatively accurate data, their equipment costs are high and their installation and debugging are complex, making it difficult to popularize them on ordinary injection molding machines. In addition, existing monitoring methods based on a single variable fail to establish a stable physical correlation between injection molding machine operating data and material rheological properties, making them susceptible to fluctuations in the injection molding process when assessing material flowability. They cannot accurately reflect the true rheological behavior of the material in the current mold runner, and therefore cannot automatically and accurately lock the optimal process speed point. Summary of the Invention

[0005] This invention provides an injection speed determination and injection molding method, apparatus, and electronic device to solve the problems of existing injection molding processes where the setting of injection speed relies on manual experience and lacks objective basis, and existing measurement methods are difficult to accurately quantify the true rheological properties of materials due to high equipment costs or weak physical correlation. It achieves the effect of constructing a scientific rheological model using the data built into the injection molding machine without the need for expensive external instruments, and accurately locking the optimal process speed by automatically analyzing the rheological trend.

[0006] This invention provides a method for determining injection speed, comprising: According to the method for determining injection speed provided by the present invention, The injection molding machine is controlled to inject at multiple different set injection speeds to obtain the actual filling time and peak injection pressure during the actual operation of the injection molding machine at each set injection speed; each injection is based on a predetermined reference filling volume as the filling cutoff condition. The relative viscosity index corresponding to each set injection speed is calculated based on the product of the actual filling time and the peak value of the actual injection pressure. Based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed, determine the trend characteristics of the relative viscosity index as a function of the set injection speed; Based on the aforementioned trend characteristics, the target injection speed of the injection molding machine is determined.

[0007] According to a method for determining injection speed provided by the present invention, determining the trend characteristics of the relative viscosity index as a function of a set injection speed includes: Determine the convergence characteristics of the relative viscosity index as a function of the set injection speed; Based on the aforementioned convergence characteristics, the critical turning point at which the relative viscosity index enters the stable range is identified. The injection speed corresponding to the critical inflection point is determined as the target injection speed.

[0008] According to the injection speed determination method provided by the present invention, the change convergence feature is the range distribution feature of the relative viscosity index over the entire range; The step of identifying the critical turning point where the relative viscosity index enters the stable range based on the aforementioned convergence characteristics includes: The maximum and minimum viscosity indices are identified from all the calculated relative viscosity indices to calculate the range between the maximum and minimum viscosity indices; The target viscosity threshold is calculated based on the minimum viscosity index, the range, and the preset threshold coefficient. Using the target viscosity threshold as a benchmark for determining whether the relative viscosity index has entered a stable range, in the sequence of set injection speeds, two adjacent set injection speeds in which the relative viscosity index crosses the target viscosity threshold are identified as the target speed range; Determine whether there exists a set injection speed within the target speed range where the relative viscosity index is equal to the target viscosity threshold; If it exists, the set injection speed, in which the relative viscosity index is equal to the target viscosity threshold, is directly determined as the target injection speed; If it does not exist, determine the critical turning point from the target speed range.

[0009] According to a method for determining injection speed provided by the present invention, determining the critical inflection point from the target speed range includes: Obtain the set injection speed at the two endpoints of the target speed range and the relative viscosity index corresponding to each endpoint; Based on the numerical ratio between the relative viscosity index at each endpoint of the interval and the target viscosity threshold, a linear interpolation calculation is performed on the set injection speed at the two endpoints of the interval, and the calculation result is determined as the critical inflection point.

[0010] According to the injection speed determination method provided by the present invention, the change convergence feature is the rate of change of the relative viscosity index with respect to the set injection speed; The step of identifying the critical turning point where the relative viscosity index enters the stable range based on the aforementioned convergence characteristics includes: The relationship between the set injection speed and the relative viscosity index is fitted using a preset nonlinear rheological function model to generate a continuous rheological curve function. Calculate the first derivative of the rheological curve function with respect to the set injection speed to obtain the rate of change of injection speed; The critical inflection point is determined based on the trend of the change rate of the injection speed.

[0011] According to a method for determining injection speed provided by the present invention, determining the critical inflection point based on the changing trend of the injection speed change rate includes: According to the set injection speed from low to high, find the set injection speed corresponding to the first time when the absolute value of the rate of change of the injection speed is less than the preset stable slope threshold, and take it as the critical turning point. or, Calculate the second derivative of the rheological curve function with respect to the set injection speed to obtain the rate of curvature change; By combining the rate of change of injection speed and the rate of change of curvature, the inflection point where the rate of change of curvature changes abruptly and the rate of change of injection speed is in a downward trend is identified; The inflection point is taken as the critical turning point.

[0012] According to a method for determining injection speed provided by the present invention, the reference filling volume is predetermined based on the following steps: Control the injection molding machine to perform test shots and gradually adjust the injection volume until the filling rate of the mold cavity reaches the preset underfill ratio range; The injection volume when the fill rate is within the specified underfill ratio range is locked as the reference fill volume; The underfill ratio ranges from 95% to 98% of the total volume of the mold cavity.

[0013] According to the injection speed determination method provided by the present invention, before controlling the injection molding machine to inject at multiple different set injection speeds, the method further includes initializing the parameters of the injection molding machine: Turn off the pressure holding function of the injection molding machine and set the pressure holding pressure and pressure holding time to zero to ensure that the obtained actual injection pressure peak only reflects the flow resistance during the filling stage; The maximum injection pressure limit of the injection molding machine is adjusted to the upper limit allowed by the equipment to prevent data truncation when acquiring the actual peak injection pressure.

[0014] According to a method for determining injection speed provided by the present invention, the injection molding machine is controlled to inject at multiple different set injection speeds, including: Within the permissible speed range of the injection molding machine, a stepped speed sequence covering from low speed to high speed or from high speed to low speed is generated; The injection speed of the injection molding machine is adjusted sequentially according to the stepped speed sequence to perform the injection action.

[0015] The present invention also provides an injection molding method, comprising: Run any of the above-described injection speed determination methods to obtain the target injection speed; The target injection speed is sent to the controller of the injection molding machine via a communication interface to update the injection speed in the process parameters of the injection molding machine to the target injection speed. The injection molding machine is controlled to perform injection molding operations at the target injection speed.

[0016] The present invention also provides an injection speed determining device, comprising: The data acquisition module controls the injection molding machine to inject at multiple different set injection speeds to obtain the actual filling time and peak injection pressure of the injection molding machine during actual operation at each set injection speed; each injection uses a predetermined reference filling volume as the filling cutoff condition. The index calculation module calculates the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the peak value of the actual injection pressure. The trend analysis module determines the trend characteristics of the relative viscosity index as a function of the set injection speed, based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed. The speed determination module determines the target injection speed of the injection molding machine based on the changing trend characteristics.

[0017] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the injection speed determination method or injection molding method as described above.

[0018] The injection speed determination and injection molding method, apparatus, and electronic equipment provided by this invention utilize the physical principle of characterizing viscosity by injection pressure and filling time at a constant volume. Rheological curves can be constructed without an external rheometer. By identifying the stable trend of the curve, the optimal process point is automatically locked. This solves the problem of traditional injection molding relying on experience to adjust the machine and being unable to objectively quantify flowability. It enables scientific mold trials and precise and automated setting of process parameters. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the injection speed determination method provided by the present invention.

[0021] Figure 2 This is a schematic diagram illustrating the influence of different control factors on injection pressure during the injection molding process, provided by the present invention.

[0022] Figure 3 This is a schematic diagram of the process for determining the trend of viscosity index change with a set injection speed, provided by the present invention.

[0023] Figure 4This is one of the flowcharts for determining the target injection speed provided by the present invention.

[0024] Figure 5 This is the second schematic diagram of the process for determining the target injection speed provided by the present invention.

[0025] Figure 6 This is one of the flowcharts for determining critical inflection points provided by the present invention.

[0026] Figure 7 This is the second flowchart illustrating the process of determining critical inflection points provided by the present invention.

[0027] Figure 8 This is a simulation diagram of determining the critical inflection point provided by the present invention.

[0028] Figure 9 This is a schematic diagram of the injection speed determining device provided by the present invention.

[0029] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0031] It should be noted that, in the description of this invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Those skilled in the art will understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0032] The terms "first," "second," etc., used in this invention are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more.

[0033] The following is combined Figures 1-10 This invention describes the injection speed determination and injection molding method, apparatus, and electronic equipment provided by the present invention.

[0034] This invention provides a method for determining injection speed. Through scientific data collection and analysis, it automatically finds the optimal injection process parameters suitable for a specific mold and material. The executing entity can be any electronic device with data processing and control capabilities, such as the built-in controller of an injection molding machine, an independent auxiliary control computer connected to the injection molding machine, an industrial personal computer, or a cloud server. In the following description, the method is illustrated using an example of running on a control device (e.g., an intelligent auxiliary control terminal connected to the injection molding machine).

[0035] Figure 1 This is a flowchart illustrating the injection speed determination method provided by the present invention, as shown below. Figure 1 As shown, including but not limited to the following steps: Step 1: Control the injection molding machine to inject at multiple different set injection speeds to obtain the actual filling time and actual peak injection pressure during the actual operation of the injection molding machine at each set injection speed; each injection is based on a predetermined reference filling volume as the filling cutoff condition.

[0036] In injection molding, injection speed is a key variable affecting melt filling behavior. To investigate the rheological properties of the injection material in the current mold runner, the control equipment pre-controls the injection molding machine to perform a series of trial molding actions. Here, "injection molding machine" refers to molding equipment capable of performing standard processes such as plastic melting, injection, pressure holding, and cooling, without specifying a particular model.

[0037] The control device sends commands to the injection molding machine, instructing it to inject material sequentially at multiple different preset injection speeds. These preset injection speeds can be random or a sequence of speed gradients from high to low or low to high (e.g., covering a wide range of injection speeds allowed by the injection molding machine), with the aim of obtaining the material's flow behavior at different shear rates. It is important to note that the preset injection speeds here are control command values. In actual operation, the actual actions of the injection molding machine may deviate due to limitations in machine response and load resistance. Therefore, this embodiment obtains real feedback data.

[0038] In performing these injection actions, this embodiment adheres to a strict physical premise: each injection uses a pre-determined reference filling volume as the filling cutoff condition. The reference filling volume refers to the melt injection amount pre-selected as a uniform benchmark before the experiment begins. The filling cutoff condition means that regardless of the current injection speed, once the injection screw advances to a position representing this reference filling volume (e.g., reaching a specific V / P switching position or injection endpoint), the injection action immediately terminates.

[0039] The above limitations are made in this embodiment to ensure that the volume variable in the fluid dynamics formula remains constant in subsequent calculations, thereby eliminating the interference of changes in filling volume on pressure readings.

[0040] During each injection, the electronic equipment collects at least two key rheological characteristic data in real time through the communication interface with the injection molding machine or external sensors: actual filling time and actual peak injection pressure. Actual filling time refers to the actual time taken for the injection screw to move from the start to the point where the filling stop condition is reached. Actual peak injection pressure refers to the maximum pressure value experienced by the injection cylinder or the tip of the injection screw during the filling process, reflecting the power required for the melt to overcome flow channel resistance.

[0041] Step 2: Calculate the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the peak value of the actual injection pressure.

[0042] After acquiring physical data at multiple speeds, the control device processes the data using its built-in computational logic. This embodiment is based on the engineering simplification principle of Poiseuille's law in fluid mechanics: under the premise of unchanged flow channel structure and locked filling volume, the relative viscosity index of the injection melt is mainly proportional to the product of the actual peak injection pressure and the actual filling time. Based on this principle, this embodiment calculates the relative viscosity index by multiplying the collected actual filling time and the actual peak injection pressure at each test point.

[0043] It should be noted that the relative viscosity index proposed in this embodiment is not the absolute viscosity value measured by a capillary rheometer in physics, but rather a relative quantitative indicator in engineering. It can intuitively characterize the magnitude of the flow resistance of the injection molded melt under the current specific mold runner and process conditions. Through this calculation method, this embodiment cleverly transforms the injection molding machine into an online rheological tester.

[0044] Step 3: Based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed, determine the trend characteristics of the relative viscosity index as a function of the set injection speed.

[0045] After completing calculations for multiple sets of experiments, the control equipment will summarize the data and construct a mapping relationship with the set injection speed as the independent variable and the relative viscosity index as the dependent variable. This mapping relationship is physically represented by the rheological curve of the material.

[0046] Subsequently, the control equipment analyzes the obtained mapping relationship to determine its trend characteristics. These trend characteristics can be viewed as a mathematical description of the rheological curve morphology, reflecting the degree or regularity of material viscosity changes with varying injection speed. The aim is to extract regular characteristics from discrete data points that can guide process decisions.

[0047] Typically, non-Newtonian fluids (such as injection-molded melts) exhibit shear-thinning properties, meaning that as the velocity increases, the viscosity index initially decreases significantly and then gradually levels off. The process of determining these changing trend characteristics can involve identifying changes in the slope, curvature, numerical drop distribution, or a trend towards a stable state in the distribution of data points.

[0048] Step 4: Determine the target injection speed of the injection molding machine based on the changing trend characteristics.

[0049] Finally, based on the analyzed trend characteristics, the control equipment automatically determines the target injection speed most suitable for current production. This target injection speed typically corresponds to an optimal process point or process window on the rheological curve.

[0050] For example, according to empirical rheological theory, the optimal injection speed often lies in the transition region where viscosity no longer decreases significantly with increasing speed. In this transition region, fluctuations in injection speed have a relatively small impact on viscosity, resulting in the most stable process. This embodiment identifies characteristic points in the aforementioned trend that conform to this physical law and sets their corresponding injection speeds as the target injection speed. This not only avoids filling difficulties caused by excessively low injection speeds but also avoids the risks of excessive shear heat or material degradation caused by excessively high injection speeds.

[0051] The injection speed determination method provided by this invention utilizes the physical principle of characterizing viscosity by injection pressure and filling time at a constant volume. It can construct a rheological curve without the need for an external rheometer, and automatically lock the optimal process point by identifying the stable trend of the curve. This solves the problem of traditional injection molding relying on experience to adjust the machine and being unable to objectively quantify flowability, and realizes the precise and automated setting of scientific mold trials and process parameters.

[0052] It is particularly important to emphasize that the reason why this embodiment chooses to use the actual filling time and the actual peak injection pressure to evaluate the injection melt viscosity is necessary to explain in conjunction with the internal mechanism of injection molding.

[0053] In the parameter settings of the injection molding process, there are numerous control factors such as melt temperature, mold temperature, injection speed, and holding pressure. However, in actual mold trials and production, how to determine the key rheological characteristic data from these complex variables is the core problem that this embodiment aims to solve.

[0054] Figure 2 This is a schematic diagram illustrating the influence of different control factors on injection pressure during the injection molding process, provided by the present invention. The horizontal axis represents the values ​​of different control factors, and the vertical axis represents the injection pressure (also known as filling pressure, in MPa). Figure 2 The diagram illustrates the impact of various control factors on injection pressure (i.e., flow resistance), including: injection molding material (hereinafter referred to as material), injection molding material temperature (referred to as plastic temperature), mold temperature, maximum flow rate percentage, maximum injection pressure percentage, holding time, holding pressure switching percentage, and maximum holding pressure percentage. This invention, through analysis of extensive experimental data, finds that compared to control factors such as mold temperature and holding time, injection speed (i.e., flow resistance) is significantly more important than flow rate. Figure 1 The percentage of maximum flow rate shown is the variable that has the most significant impact on flowability and is the easiest to dynamically adjust in real time. Although the melt temperature of the injection melt also affects viscosity, the melt temperature is usually constant throughout a specific production cycle. Therefore, this invention creatively chooses to lock in other variables and focus on finding the optimal process window by adjusting the injection speed, which is an efficient decision-making path based on scientific experimental verification.

[0055] Furthermore, the ease of molding injection-molded products is strongly correlated with the dynamic viscosity of the material during the filling process. However, traditional absolute viscosity measurements rely on expensive online rheometers, which are limited by installation location and cannot accurately reflect the true complex flow conditions inside the mold cavity. This invention introduces a relative viscosity index to find a low-cost, highly responsive alternative index to characterize the actual flow state of materials in current molds.

[0056] This embodiment has a solid foundation in fluid mechanics theory for calculating the relative viscosity index. According to Poiseuille's law, the pressure drop of a fluid flowing in a pipe... With traffic Fluid viscosity and channel geometry, such as flow length ,radius The following relationship exists: ; In injection molding, flow rate This can be expressed as the filling volume V divided by the filling time t, i.e. Substituting this into the above relational formula and transforming it, we get: .

[0057] In the control logic of this application, since step 1 explicitly defines the filling cutoff condition as a predetermined reference filling volume, the filling volume... V These are forcibly locked as constants. Furthermore, for the same mold set, its runner length L and radius r are also fixed physical constants. Therefore, in the above formula... This can be considered as a constant engineering coefficient K. Therefore, the above relationship formula can ultimately be simplified to: .

[0058] In this way, it can be determined Under specific boundary conditions with constant volume, the product of the actual injection pressure peak (representing ΔP) and the actual filling time t is strictly positively correlated with the melt viscosity η. This is why this invention needs to collect, and only needs to collect, these two data points.

[0059] This invention cleverly avoids the direct measurement of complex fluid parameters, reducing the elusive viscosity to the product of the two most easily obtainable basic variables in injection molding machines. This simplification approach not only has rigorous physical significance but also greatly lowers the threshold and cost of technical implementation.

[0060] In order to accurately capture the laws of material rheological behavior from discrete experimental data, this invention provides an analysis method based on change convergence characteristics. Figure 3 This is a schematic diagram of the process for determining the trend of viscosity index change with a set injection speed, as provided by the present invention. Figure 3 As shown, it mainly includes, but is not limited to: Step 31: Determine the convergence characteristics of the relative viscosity index as a function of the set injection speed.

[0061] Step 32: Based on the aforementioned convergence characteristics, identify the critical turning point where the relative viscosity index enters the stable range.

[0062] Step 33: Determine the set injection speed corresponding to the critical inflection point as the target injection speed.

[0063] Because polymer melts typically exhibit shear-thinning properties like non-Newtonian fluids, as the injection speed (shear rate) increases, the orientation of the material's molecular chains strengthens, and the flow resistance (characterized by the relative viscosity index) decreases rapidly. However, this decrease is not indefinite; once the speed reaches a certain level, the rate of viscosity reduction gradually diminishes, and the curve flattens out.

[0064] In this embodiment, the control device can analyze the constructed velocity-viscosity correlated data sequence to extract the convergence characteristics reflecting the transition from drastic change to a stable state. These convergence characteristics can be numerical convergence, such as the current relative viscosity index narrowing from the theoretical minimum, or rate-of-change convergence, such as the slope of the tangent line gradually approaching zero, quantifying the degree to which the current process state approaches the ideal flow state.

[0065] After obtaining the convergence characteristics of the change, this embodiment identifies a critical process node. This node is not the point of lowest viscosity, as excessive speed may lead to material degradation or flash, but rather the critical inflection point where the cost-effectiveness is highest. Before the critical inflection point, increasing the injection speed yields significant viscosity reduction benefits, resulting in a substantial improvement in flowability. After the critical inflection point, further increasing the injection speed yields negligible viscosity reduction benefits and may even lead to material degradation or flash.

[0066] This embodiment compares the calculated change convergence feature with a preset rheological stability criterion, such as a numerical threshold or slope threshold. When the change convergence feature satisfies the rheological stability criterion, it is determined that the flow state of the material has entered a relatively stable steady range. The starting position of the steady range or a specific position near it is identified as the critical inflection point.

[0067] Ultimately, by setting the injection speed directly to the x-axis corresponding to the identified critical inflection point, the production process is kept within a region of good material flowability, ensuring product quality such as full filling and no shrinkage marks. At the same time, it avoids equipment wear and energy waste caused by using extremely high speeds, thus achieving robust optimization of the process.

[0068] This invention transforms the current fuzzy thinking of finding inflection points by relying on experience to observe curves into a standardized decision-making process that can be executed by a computer by introducing analytical logic of change convergence characteristics and critical inflection points. This ensures that the target speed determined each time has a high degree of consistency and scientific rigor.

[0069] Figure 4 This is one of the flowcharts for determining the target injection rate provided by the present invention, such as... Figure 4 As shown, this embodiment provides a method for quantifying the aforementioned convergence characteristics of change by calculating the numerical distribution characteristics of the data, and identifying critical inflection points based on this. By utilizing the range distribution characteristics of the relative viscosity index across the entire range, it can effectively adapt to the differences in viscosity bases of different materials and molds. Specifically, it includes, but is not limited to, the following steps: Step 311: Identify the maximum viscosity index and the minimum viscosity index from all the calculated relative viscosity indices, and calculate the range between the maximum viscosity index and the minimum viscosity index.

[0070] This embodiment will iterate through the set of relative viscosity indices calculated for all set injection speeds. Find the maximum viscosity index from it. and minimum viscosity index Then calculate the range between the two: .

[0071] The obtained range represents the total magnitude of the change in the relative viscosity index of the injection-molded material within the current experimental speed range, i.e., the range distribution characteristics within the full range, providing a global reference scale for subsequent judgment on whether the relative viscosity index has dropped to the appropriate level.

[0072] Step 312: Calculate the target viscosity threshold based on the minimum viscosity index, the range, and the preset threshold coefficient.

[0073] To determine the critical inflection point at which the relative viscosity index enters a stable range, this embodiment establishes a threshold value. The control device reads a pre-stored threshold coefficient. For example, 5%, 10%, or 20%. The threshold coefficient reflects the user's expectation of the degree of viscosity optimization; for example, how many percentage points higher the final viscosity than the minimum limit is acceptable. The formula for calculating the target viscosity threshold is as follows: ; in, The target viscosity threshold; This is the threshold coefficient. The meaning of this formula is: based on the theoretically achievable minimum viscosity index, a certain percentage upward is allowed as the target value for optimal processing. This threshold line is represented as a horizontal line on the rheological curve, truncating the steep and gentle sections of the curve.

[0074] Step 313: Using the target viscosity threshold as a benchmark for determining whether the relative viscosity index has entered a stable range, identify two adjacent set injection speeds in the sequence of set injection speeds where the relative viscosity index crosses the target viscosity threshold, and use them as the target speed range.

[0075] The control device will then iterate through the data sequence again, searching for the intersection of data points and the threshold line. Specifically, it will look for two adjacent points. n -1 and n This makes the relative viscosity index at the previous point... Greater than the target viscosity threshold The relative viscosity index at the next point Less than or equal to the target viscosity threshold This leap indicates that it is precisely between these two speeds that the material's viscosity properties reach the expected optimization standard and enter a stable range. These two adjacent injection speed settings... and The range formed by this can be locked into the target speed range.

[0076] Step 314: Determine whether there is a set injection speed in the target speed range where the relative viscosity index is equal to the target viscosity threshold.

[0077] If it exists, the set injection speed, in which the relative viscosity index is equal to the target viscosity threshold, is directly determined as the target injection speed; If it does not exist, determine the critical turning point from the target speed range.

[0078] Figure 5 This is the second schematic diagram of the process for determining the target injection speed provided by the present invention, see reference. Figure 5 As shown, in this embodiment, after determining the target velocity range, meticulous logical judgments are performed to ensure accurate output results. If, by sheer coincidence, the viscosity value at a certain test point happens to equal the calculated target viscosity threshold, then... If the speed at that test point is perfect, it can be directly identified as the critical inflection point. However, in most cases, the test points are discrete, and the threshold line will pass between two test points. In this case, further refined calculations are needed within the target speed range, such as using interpolation to determine the critical inflection point.

[0079] The injection speed determination method provided by this invention, by determining the target viscosity threshold based on the range and finding the target speed range based on the target viscosity threshold, can adaptively handle materials with different viscosity ranges. Regardless of whether the viscosity base of the material itself is high or low, it can objectively and stably find the critical region where the rheological properties undergo qualitative change based on its own relative change range.

[0080] Figure 6 This is one of the flowcharts for determining critical inflection points provided by the present invention, such as... Figure 6 As shown, when there is no test point in the target velocity range that directly hits the target viscosity threshold, i.e. In order to obtain more accurate process parameters than discrete sampling points, this embodiment uses a linear interpolation algorithm to calculate critical inflection points from within the interval. Specific steps include, but are not limited to: Step 315: Obtain the set injection speed at the two endpoints of the target speed range and the relative viscosity index corresponding to each endpoint of the range; Step 316: Based on the numerical ratio between the relative viscosity index and the target viscosity threshold at each interval endpoint, perform linear interpolation calculation on the set injection speed at the two interval endpoints, and determine the calculation result as the critical inflection point.

[0081] Specifically, in this embodiment, the left endpoint of the target velocity range (lower velocity, higher viscosity) is denoted as point A. , The endpoint (higher speed, lower viscosity) is denoted as point B. , If these two endpoints are the measured data closest to the target threshold line, they form the basis of local linearization.

[0082] Assuming that within a sufficiently small injection speed range, the relative viscosity index will exhibit an approximately linear relationship with the injection speed, this embodiment utilizes the principle of similar triangles to calculate the target viscosity threshold. and The precise x-coordinates corresponding to these points are calculated using the following logic: First, calculate the viscosity drop across the entire target velocity range: ; Secondly, calculate the viscosity drop from the target threshold to the starting point of the interval: ; Then, calculate the proportion of the target elevation difference to the total elevation difference: ; Finally, this ratio is applied to the velocity axis to calculate the increment of the target injection velocity, and then added to the initial injection velocity, i.e.: .

[0083] Calculated It was identified as a critical inflection point.

[0084] The injection speed determination method provided by this invention effectively breaks through the limitations of physical experiment sampling accuracy by introducing a linear interpolation mechanism. For example, even if only coarse-grained gradients such as 10%, 20%, and 30% are set in the DOE experimental design, this embodiment can still calculate precise process values ​​such as "23.5%" that lie between the gradients. This allows the final determined target injection speed to infinitely approximate the true inflection point of the material's rheological properties. While ensuring control accuracy, it eliminates the need to infinitely increase the number of experiments to approximate the target speed, greatly improving the efficiency of trial molding.

[0085] Figure 7 This is the second flowchart illustrating the process of determining critical inflection points provided by this invention, as shown below. Figure 7As shown, this embodiment also provides another implementation method for determining critical inflection points, which is used to explore the continuous change law of rheological curves at a deeper level. It is particularly suitable for scenarios with extremely high control accuracy requirements or where it is necessary to eliminate the influence of random fluctuations in experimental data.

[0086] Unlike the previous embodiment, the convergence feature here is the rate of change of the relative viscosity index with respect to a set injection speed, specifically including but not limited to: Step 321: Fit the relationship between the set injection speed and the relative viscosity index using a preset nonlinear rheological function model to generate a continuous rheological curve function.

[0087] Step 322: Calculate the first derivative of the rheological curve function with respect to the set injection speed to obtain the injection speed change rate.

[0088] Step 323: Determine the critical inflection point based on the trend of the change rate of the injection speed.

[0089] Considering that in the real physical world, the rheological behavior (shear thinning) of polymer melts usually follows a power law, this embodiment no longer treats the collected data as isolated points, but rather as samples, and uses a preset nonlinear mathematical model to perform regression analysis to obtain the rheological curve function.

[0090] Preferably, the preset nonlinear rheological function model adopts a power function form, and its function expression is: .in, x Represents injection speed. y Represents the relative viscosity index. A and B It is the constant to be fitted.

[0091] Furthermore, the optimal value can be calculated using the least squares method or other regression algorithms. A and B The value of is used to obtain a continuous and smooth rheological curve function that can pass through or approximate all measured points.

[0092] Once a continuous rheological curve function is obtained, its first derivative can be calculated. For the power-law model described above, the functional expression for the first derivative is: .

[0093] The calculated first derivative represents the rate of change of injection speed, i.e., the slope of the tangent line of the rheological curve, quantifying how much the relative viscosity index decreases with each unit increase in injection speed. The larger the absolute value of the tangent line slope, the higher the benefit of increasing the speed; the smaller the absolute value of the slope (approaching 0), the lower the benefit of increasing the speed.

[0094] Finally, this embodiment identifies the critical inflection point by analyzing how the rate of change of injection speed (tangent slope) changes with injection speed.

[0095] As the injection speed x increases, the rate of change of injection speed... The absolute value of the injection rate will gradually decrease, meaning the curve will become flatter. This embodiment can identify the point where the rate of change of injection rate begins to become negligible, i.e., the point where the absolute value of the rate of change of injection rate drops below a certain preset standard. This point marks the material's flow behavior officially entering the "shear-thinning plateau period," and this location is determined as the critical inflection point.

[0096] This invention, through this fitting and differentiation method, elevates the judgment of critical inflection points from the intuitive observation of curve curvature to the rational mathematical analysis level. It can keenly capture subtle trends in rheological property changes, providing a more theoretically profound decision-making basis for high-precision injection molding.

[0097] Figure 8 This is a simulation diagram of determining the critical inflection point provided by the present invention, such as... Figure 8 As shown, this embodiment provides a method for determining the critical inflection point based on the changing trend of the injection speed rate, including but not limited to: According to the set injection speed in ascending order, find the set injection speed corresponding to the first time the absolute value of the rate of change of the injection speed is less than the preset stable slope threshold, and use it as the critical turning point.

[0098] A stable slope threshold can be preset, for example =0.5, which represents the boundary where viscosity change is no longer significant. Then, starting from the low-speed end, the rheological curve is scanned towards the high-speed end, and the tangent slope at each point is calculated in real time, thus obtaining the injection speed change rate.

[0099] At low injection speeds, the absolute value of the tangent slope is typically large due to the strong shear-thinning effect. However, as the injection speed increases, the absolute value of the tangent slope gradually decreases. When the absolute value of the tangent slope at a certain point first falls below the stable slope threshold, it means that the rheological curve is sufficiently flat, and the viscosity reduction benefit from further increasing the injection speed is no longer below the preset standard. At this point, this point can be identified as the critical inflection point, and the corresponding set injection speed can be used as the target injection speed.

[0100] As another optional embodiment, the present invention also provides another method for determining critical inflection points, mainly including: Calculate the second derivative of the rheological curve function with respect to the set injection speed to obtain the rate of curvature change; By combining the rate of change of injection speed and the rate of change of curvature, the inflection point where the rate of change of curvature changes abruptly and the rate of change of injection speed is in a downward trend is identified; The inflection point is taken as the critical turning point.

[0101] This embodiment provides a more rigorous mathematical determination method, which aims to find the location where the rheological curve is most severely curved, that is, the point of maximum curvature or knee point in geometry.

[0102] Specifically, the rheological function corresponding to the rheological curve is first differentiated twice to obtain the second derivative, which reflects the rate of change of the tangent slope, i.e., the curvature of the rheological curve. Simultaneously, the first derivative (ensuring viscosity is decreasing) and the second derivative of the rheological function are monitored. On the rheological curve, at the angle where the transition from a steep region to a flat region occurs, the value of the second derivative usually exhibits an extreme value or a significant abrupt change. This embodiment, by identifying this curvature abrupt change characteristic, can accurately locate the geometric inflection point where the efficiency of flowability improvement undergoes a qualitative change as a critical inflection point. Therefore, the set injection speed corresponding to the critical inflection point can be used as the target injection speed.

[0103] The method for determining the critical inflection point provided in this invention ensures, from a mathematical perspective, that the selected process point is precisely located at the optimal balance position for input-output ratio, making it particularly suitable for precision injection molding scenarios with extremely narrow molding windows and extremely high requirements for process stability.

[0104] It should be noted that in order to ensure that the collected pressure data can purely reflect the frictional resistance of the injection molding material melt in the runner, the venting resistance at the end of the mold cavity, the reaction force of the melt being compressed, and the interference caused by overflow, flash, etc. must be eliminated. Therefore, the predetermined reference filling volume used in the injection speed determination method provided in step 1 of the above embodiments is generally not set arbitrarily.

[0105] As an optional embodiment, the present invention provides a specific implementation method for determining the reference filling volume, which mainly includes, but is not limited to: Control the injection molding machine to perform test shots and gradually adjust the injection volume until the filling rate of the mold cavity reaches the preset underfill ratio range; The injection volume when the fill rate is within the specified underfill ratio range is locked as the reference fill volume; The underfill ratio ranges from 95% to 98% of the total volume of the mold cavity.

[0106] Specifically, several trial injections are conducted before formally collecting rheological data. Initially, the injection volume (usually controlled by metering stroke) is set to a conservative value, and then finely increased mold by mold. During this process, the filling status of the product is visually observed or detected by sensors.

[0107] When the filling degree of the product reaches 95% to 98%, that is, when there is a slight material shortage at the end of the product that is visible to the naked eye, but the main structure is complete, the adjustment will stop and the corresponding screw metering stroke or injection volume will be locked and defined as the reference filling volume.

[0108] It should be noted that the selection of a short-fill ratio range of 95% to 98% of the total mold cavity volume in this embodiment is mainly based on the following considerations: On the one hand, if the filling rate reaches 100% of the mold, the pressure inside the mold cavity will instantly change from flow resistance to melt compressive force, resulting in a surge peak at the end of the pressure curve that is unrelated to viscosity, which seriously contaminates the data. Therefore, using underfilling can effectively avoid this compression stage.

[0109] On the other hand, if the fill rate is too low, such as only 50%, the melt may not have flowed through the thinnest or most complex areas of the product, and the measured pressure cannot represent the maximum resistance during the filling process. Setting a fill rate of 95% to 98% covers most of the flow length and stops the machine just before the mold is full, which is the best balance point for obtaining pure rheological data.

[0110] In this way, in all subsequent variable speed scanning experiments, no matter how the injection speed is set, the injection molding machine will strictly execute this locked stroke, ensuring that each injection stops at the same underfill position, thereby guaranteeing the physical validity of the calculation result calculated by multiplying the actual filling time and the actual peak injection pressure.

[0111] To further ensure that the obtained actual injection pressure peak is genuine and unmanipulated test data, this embodiment includes a crucial parameter initialization step before formally starting the multi-level injection velocity scan, which mainly includes, but is not limited to: Turn off the pressure holding function of the injection molding machine and set the pressure holding pressure and pressure holding time to zero to ensure that the obtained actual injection pressure peak only reflects the flow resistance during the filling stage; The maximum injection pressure limit of the injection molding machine is adjusted to the upper limit allowed by the equipment to prevent data truncation when acquiring the actual peak injection pressure.

[0112] In conventional production, the process immediately switches to the holding pressure stage after the injection phase to compensate for cooling and shrinkage. However, in the rheological test of this embodiment, the presence of the holding pressure stage severely interferes with the judgment of the moment when filling ends, and the holding pressure is often a fixed value set manually, independent of the material viscosity. If the sensor reads the holding pressure, the calculated relative viscosity index will be completely distorted.

[0113] Therefore, this embodiment will forcibly modify the holding pressure and holding time parameters of the injection molding machine to 0, ensuring that the injection molding machine stops thrusting immediately after completing the injection action. The purpose of this operation is to ensure that the actual injection pressure peak obtained only reflects the flow resistance during the filling stage, eliminating any subsequent pressure interference.

[0114] Furthermore, injection molding machines typically have system pressure limiting. When the actual pressure exceeds the maximum injection pressure limit, the machine activates its self-protection mechanism, forcibly limiting the output of hydraulic oil or the motor, resulting in a clipping effect on the pressure curve. Additionally, under conditions of low temperature or extremely high injection speed, the instantaneous pressure required to propel the melt is extremely high, potentially exceeding the conventionally set maximum injection pressure limit. Once the data is clipped, the measured peak injection pressure becomes an erroneous constant value, causing the rheological curve to become a straight line in that region, failing to reflect the true viscosity change.

[0115] In view of this, during the experiment, the maximum injection pressure limit was temporarily increased to the physical upper limit allowed by the injection molding machine hardware, such as 210 bar or higher. The purpose of this operation is to prevent data truncation when acquiring the actual injection pressure peak value, and to ensure that the injection molding machine can output stably even under extreme conditions, thereby recording the true resistance peak value required for material flow.

[0116] Based on the above embodiments, as an optional embodiment, after ensuring the correctness of the under-injection volume and the collection environment, a specific implementation method for controlling the injection molding machine to inject at multiple different set injection speeds is further provided.

[0117] To plot a complete rheological curve that includes the characteristics of the critical inflection point, this embodiment does not randomly select a few predetermined injection speed points during trial molding. Instead, it employs a systematic scanning strategy, specifically including: Within the permissible speed range of the injection molding machine, a stepped speed sequence covering from low speed to high speed or from high speed to low speed is generated; The injection speed of the injection molding machine is adjusted sequentially according to the stepped speed sequence to perform the injection action.

[0118] This embodiment first reads the maximum injection speed (e.g., 500 mm / s) from the current injection molding machine specifications table, and uses this as a benchmark to generate a speed sequence containing multiple gradients. This stepped speed sequence is typically designed to cover a wide range, for example, from 5% to 95% of the machine's capacity.

[0119] An optional stepped velocity sequence is set as follows: [10%, 20%, 30%, ..., 90%, 95%]. This wide range setting is crucial because scanning only within a narrow range (such as 40%-60%) may miss regions where the material viscosity changes drastically, making it impossible to identify the true critical inflection point.

[0120] Subsequently, the injection molding machine can be controlled to adjust the set injection speed step by step according to a stepped speed sequence. Generally, a monotonic sequence from high speed to low speed (or from low speed to high speed) can be used to maintain a relatively stable thermal state and reduce experimental errors.

[0121] Each time the injection speed is adjusted, the injection molding machine performs a complete injection cycle and collects a corresponding set of actual filling time and actual injection pressure peak values.

[0122] By using this step-by-step, full-range scanning method, this embodiment can obtain rheological response data of the material across the entire range from low to high shear rates, providing sufficient data support for accurately constructing complete rheological curves and identifying the optimal critical inflection point.

[0123] Based on the above embodiments, the present invention further provides an injection molding method, which mainly includes the following implementation steps: Step 1: Obtain the target injection speed.

[0124] Step 2: The target injection speed is sent to the controller of the injection molding machine via the communication interface to update the injection speed in the process parameters of the injection molding machine to the target injection speed.

[0125] Step 3: Control the injection molding machine to perform the injection molding operation at the target injection speed.

[0126] The core innovation of the injection molding method provided in this embodiment lies in how to determine the injection speed. The injection speed determination method provided in any of the above embodiments can be used, and will not be described in detail here.

[0127] The injection molding method provided by this invention utilizes the physical principle of characterizing viscosity by injection pressure and filling time at a constant volume. It can construct rheological curves without the need for an external rheometer and automatically lock the optimal process point by identifying the stable trend of the curve. This solves the problem of traditional injection molding relying on experience to adjust the machine and being unable to objectively quantify flowability, and realizes the precise and automated setting of scientific mold trials and process parameters.

[0128] Figure 9 This is a schematic diagram of the injection speed determining device provided by the present invention, as shown below. Figure 9 As shown, it mainly includes, but is not limited to: The data acquisition module 101 controls the injection molding machine to inject at multiple different set injection speeds to obtain the actual filling time and peak value of the actual injection pressure during the actual operation of the injection molding machine at each set injection speed; each injection uses a predetermined reference filling volume as the filling cutoff condition. The index calculation module 102 calculates the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the peak value of the actual injection pressure. The trend analysis module 103 determines the trend characteristics of the relative viscosity index as a function of the set injection speed, based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed. The speed determination module 104 determines the target injection speed of the injection molding machine based on the changing trend characteristics.

[0129] It should be noted that the injection speed determination device provided in this embodiment can execute and implement the injection speed determination method provided in any of the above embodiments when it is running, and will not be described in detail here.

[0130] The injection speed determination device provided by this invention utilizes the physical principle of characterizing viscosity by injection pressure and filling time at a constant volume. It can construct a rheological curve without the need for an external rheometer and automatically lock the optimal process point by identifying the stable trend of the curve. This solves the problem of traditional injection molding relying on experience to adjust the machine and being unable to objectively quantify flowability, and realizes the precise and automated setting of scientific mold trials and process parameters.

[0131] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 10As shown, the electronic device may include a processor 1010, a communications interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communications interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. The processor 1010 can call logic instructions in the memory 1030 to execute an injection speed determination method. This method includes: controlling an injection molding machine to inject at multiple different set injection speeds to obtain the actual filling time and peak actual injection pressure during the actual operation of the injection molding machine at each set injection speed; using a predetermined reference filling volume as the filling cutoff condition for each injection; calculating the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the peak actual injection pressure; determining the trend characteristics of the relative viscosity index with respect to the set injection speed based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed; and determining the target injection speed of the injection molding machine based on the trend characteristics.

[0132] Furthermore, the logical instructions in the aforementioned memory 1030 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0133] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer is able to execute the injection speed determination method provided in the above embodiments, the method including: controlling an injection molding machine to inject at multiple different set injection speeds respectively, to obtain the actual filling time and actual injection pressure peak value during the actual operation of the injection molding machine at each set injection speed; using a predetermined reference filling volume as the filling cutoff condition for each injection; calculating the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the actual injection pressure peak value; determining the variation trend characteristics of the relative viscosity index with the set injection speed based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed; and determining the target injection speed of the injection molding machine according to the variation trend characteristics.

[0134] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the injection speed determination method provided in the above embodiments. The method includes: controlling an injection molding machine to inject at multiple different set injection speeds to obtain the actual filling time and peak actual injection pressure during the actual operation of the injection molding machine at each set injection speed; using a predetermined reference filling volume as the filling cutoff condition for each injection; calculating the relative viscosity index corresponding to each set injection speed based on the product of the actual filling time and the peak actual injection pressure; determining the trend characteristics of the relative viscosity index with respect to the set injection speed based on all the set injection speeds and the relative viscosity index corresponding to each set injection speed; and determining the target injection speed of the injection molding machine according to the trend characteristics.

[0135] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0136] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An injection rate determination method characterized by, The method comprises: controlling an injection molding machine to perform injection at a plurality of different set injection speeds respectively, to obtain actual filling time and actual injection pressure peak value of the injection molding machine during actual operation at each of the set injection speeds; each injection is performed with a predetermined reference filling volume as a filling stop condition; based on the product of the actual filling time and the actual injection pressure peak value, a relative viscosity index corresponding to each of the set injection speeds is calculated; based on all of the set injection speeds and the relative viscosity index corresponding to each of the set injection speeds, a variation trend feature of the relative viscosity index with respect to the set injection speed is determined; according to the variation trend feature, a target injection speed of the injection molding machine is determined.

2. The injection rate determination method according to claim 1, characterized in that, The determination of the variation trend feature of the relative viscosity index with respect to the set injection speed comprises: determining a variation convergence feature of the relative viscosity index with respect to the variation of the set injection speed; based on the variation convergence feature, a critical turning point at which the relative viscosity index enters a stable interval is identified; the set injection speed corresponding to the critical turning point is determined as the target injection speed.

3. The injection rate determination method according to claim 2, characterized in that, The variation convergence feature is a range distribution feature of the relative viscosity index in a full range; the identification of the critical turning point at which the relative viscosity index enters the stable interval based on the variation convergence feature comprises: from all of the calculated relative viscosity indexes, a maximum viscosity index and a minimum viscosity index are identified, to calculate a range between the maximum viscosity index and the minimum viscosity index; according to the minimum viscosity index, the range, and a preset threshold coefficient, a target viscosity threshold value is calculated; the target viscosity threshold value is taken as a reference for judging that the relative viscosity index enters the stable interval, two adjacent set injection speeds at which the relative viscosity index crosses the target viscosity threshold value are identified as a target speed interval in a sequence of the set injection speeds; it is judged whether there is a set injection speed at which the relative viscosity index is equal to the target viscosity threshold value in the target speed interval; if there is, the set injection speed at which the relative viscosity index is equal to the target viscosity threshold value is directly determined as the target injection speed; if there is not, the critical turning point is determined from the target speed interval.

4. The injection rate determination method according to claim 3, characterized in that The determination of the critical turning point from the target speed interval comprises: obtaining the set injection speed of two interval endpoints of the target speed interval and the relative viscosity index corresponding to each of the interval endpoints; based on the numerical proportional relationship between the relative viscosity index of each of the interval endpoints and the target viscosity threshold value, the set injection speeds of the two interval endpoints are calculated by linear interpolation, and the calculation result is determined as the critical turning point.

5. The injection rate determination method according to claim 2, characterized in that, The variation convergence feature is a variation rate of the relative viscosity index with respect to the set injection speed; the identification of the critical turning point at which the relative viscosity index enters the stable interval based on the variation convergence feature comprises: a preset nonlinear rheological function model is used to fit the corresponding relationship between the set injection speed and the relative viscosity index, to generate a continuous rheological curve function; calculating a first derivative of the rheological curve function with respect to the set injection speed, to obtain an injection speed change rate; determining the critical turning point based on a change trend of the injection speed change rate.

6. The injection rate determination method according to claim 5, characterized in that The determining the critical turning point based on the change trend of the injection speed change rate comprises: finding, in order of the set injection speed from low to high, a set injection speed corresponding to a first time when an absolute value of the injection speed change rate is less than a preset stable slope threshold, as the critical turning point; alternatively, calculating a second derivative of the rheological curve function with respect to the set injection speed, to obtain a curvature change rate; finding, in combination of the injection speed change rate and the curvature change rate, an inflection point position at which the curvature change rate has a sudden change and the injection speed change rate is in a downward trend; taking the inflection point position as the critical turning point.

7. The injection rate determination method of claim 1, wherein The reference filling volume is determined in advance based on the following steps: controlling the injection molding machine to perform a trial injection and gradually adjusting an injection amount until a filling rate of a mold cavity reaches a preset underfilling proportion range; locking the injection amount when the filling rate is in the underfilling proportion range as the reference filling volume; The underfilling proportion range is 95% to 98% of the total volume of the mold cavity.

8. The injection rate determination method of claim 1, wherein Before controlling the injection molding machine to perform injection respectively according to a plurality of different set injection speeds, the method further comprises parameter initialization setting of the injection molding machine: turning off the pressure maintaining function of the injection molding machine and setting the pressure maintaining pressure and the pressure maintaining time to zero, to ensure that the actual injection pressure peak value obtained only reflects the flow resistance in the filling stage; adjusting the maximum injection pressure limit value of the injection molding machine to the upper limit value allowed by the equipment, to prevent data truncation when the actual injection pressure peak value is obtained.

9. The injection rate determination method of claim 1, wherein, The controlling the injection molding machine to perform injection respectively according to a plurality of different set injection speeds comprises: generating a stepwise speed sequence covering from low speed to high speed or from high speed to low speed within a permissible speed range of the injection molding machine; adjusting the set injection speed of the injection molding machine according to the stepwise speed sequence to perform injection actions in sequence.

10. A method of injection molding, characterized in that, The method comprises: running the injection speed determination method according to any one of claims 1-9 to obtain the target injection speed; sending the target injection speed to a controller of the injection molding machine through a communication interface, to update the injection speed in a process parameter of the injection molding machine to the target injection speed; controlling the injection molding machine to perform injection molding work at the target injection speed.

11. An injection rate determining device, characterized in that The method comprises: a data acquisition module, which controls the injection molding machine to perform injection respectively according to a plurality of different set injection speeds, to obtain actual filling time and actual injection pressure peak value of the injection molding machine in an actual running process at each set injection speed; each injection is performed with a predetermined reference filling volume as a filling stop condition; an index calculation module, which calculates a relative viscosity index corresponding to each set injection speed based on a product of the actual filling time and the actual injection pressure peak value. a trend analysis module configured to determine a trend feature of the relative viscosity index with respect to the set injection speed based on all the set injection speeds and the relative viscosity index corresponding to each of the set injection speeds; a speed determination module configured to determine a target injection speed of the injection molding machine according to the trend feature.

12. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the injection speed determination method according to any one of claims 1 to 9 or the injection molding method according to claim 10 when executing the computer program.

Images