Method and system for controlling cycling stability in injection molding production

Abstract

The invention discloses a control method and system for cycle stability in injection molding production, and the method comprises the steps: in the technical scheme, obtaining the actual injection speed and actual injection pressure of injection molding equipment in the injection molding production, so as to obtain the actual injection molding track of the injection molding equipment; an actual injection molding track deviation of actual injection molding is obtained according to the actual injection molding track and a preset ideal injection molding track; under the condition that the actual injection molding track deviation is larger than a preset deviation threshold value, the influence degree of the actual injection molding track deviation on the circulation stability is calculated through the injection speed weight and the injection pressure weight of injection molding equipment; and finally, under the condition that the influence degree is greater than a preset influence degree threshold value, generating an optimal control strategy of the injection molding equipment by adopting a self-adaptive tuning algorithm. According to the technical scheme, the cycle stability of injection molding production can be improved, and the purpose of improving the stability of the quality of injection molding products is achieved.

Description

Technical Field

[0001] This invention relates to the field of injection molding production control technology, and in particular to a method and system for controlling the cycle stability in injection molding production. Background Technology

[0002] Injection molding is a highly efficient and precise plastic molding process. Its principle involves injecting molten plastic material into an injection mold cavity using injection molding equipment, and then cooling and solidifying it to obtain a plastic product of the desired shape. Cyclic stability is a crucial performance characteristic of injection molding, enabling the equipment to continuously and stably output products that meet quality standards, and minimizing fluctuations in key indicators such as process parameters, equipment condition, and product quality.

[0003] Before injection molding production, an ideal injection trajectory needs to be set according to the product. During the injection molding process, the injection molding equipment needs to be controlled according to the ideal injection trajectory to obtain the desired injection molded product. However, due to limitations in the responsiveness to control commands, there will be deviations between the actual injection trajectory and the ideal injection trajectory of the injection molding equipment. This affects the cycle stability of injection molding production and causes instability in the quality of injection molded products. Summary of the Invention

[0004] This invention provides a method and system for controlling cyclic stability in injection molding production, which is used to improve the cyclic stability of injection molding production, thereby improving the stability of injection molded product quality.

[0005] Specifically, the present invention provides a method for controlling cycle stability in injection molding production, comprising: The actual injection speed and actual injection pressure of the injection molding equipment are obtained, and the actual injection trajectory of the injection molding equipment is obtained based on the actual injection speed and actual injection pressure. Obtain a preset ideal injection trajectory, calculate the deviation of the actual injection trajectory based on the actual injection trajectory and the ideal injection trajectory, and determine whether the deviation of the actual injection trajectory is greater than a preset deviation threshold. If so, the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment are obtained, and the correlation between the historical injection trajectory deviation and the historical mold temperature fluctuation is extracted to obtain the injection speed weight and injection pressure weight of the injection molding equipment. The impact of the actual injection trajectory deviation on cycle stability is calculated based on the injection speed weight and injection pressure weight. When the degree of influence exceeds a preset influence threshold, an adaptive optimization algorithm is used to generate an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation, and the injection molding equipment is controlled according to the optimized control strategy.

[0006] Furthermore, the step of controlling the injection molding equipment according to the optimized control strategy further includes: Obtain the actual operating parameters of the injection molding equipment and determine whether the actual operating parameters match the process requirements of the injection molding production; If not, the injection molding equipment is adjusted based on the geometric characteristics of the product produced by injection molding.

[0007] Furthermore, the step of determining whether the actual operating parameters match the process requirements of the injection molding production includes: Obtain the standard operating parameters of the injection molding equipment, calculate the deviation between the actual operating parameters and the standard operating parameters, and determine whether the deviation is within the preset deviation range; If not, then obtain the predicted operating parameters of the injection molding equipment, and obtain the predicted failure rate of the injection molding equipment based on the predicted operating parameters; If the predicted failure rate is greater than the set failure rate threshold, it is determined that the actual operating parameters do not match the process requirements of the injection molding production.

[0008] Furthermore, after the step of controlling the injection molding equipment according to the optimized control strategy, the method further includes: After the injection molding process is completed, the final injection trajectory of the injection molding equipment is obtained, and an operation log of the cycle stability during the injection molding process is generated based on the final injection trajectory.

[0009] Furthermore, after the step of generating the operation log of the cycle stability in the injection molding production based on the final injection trajectory, the method further includes: The injection molding process parameters are generated based on the final injection trajectory, and the cycle mode of the injection molding process is obtained based on the injection molding process parameters. Determine whether the loop pattern is an abnormal loop pattern; If so, identify the quality risk points in the final injection trajectory and obtain the parameter adjustment strategy corresponding to each quality risk point to generate an optimization report for the injection molding equipment.

[0010] Further, the step of calculating the deviation of the actual injection trajectory based on the actual injection trajectory and the ideal injection trajectory includes: Based on the actual injection trajectory, obtain the actual average injection speed and actual average injection pressure within a set time period before the current moment; Based on the ideal injection trajectory, obtain the ideal average injection speed and ideal average injection pressure within a set time period before the current moment; The difference between the actual average injection speed and the ideal average injection speed, and the difference between the actual average injection pressure and the ideal average injection pressure are calculated to obtain the actual injection trajectory deviation.

[0011] Furthermore, after the step of obtaining the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment, the method further includes: Determine whether the historical mold temperature fluctuations are evenly distributed; If so, then perform the step of extracting the correlation between the historical injection trajectory deviation and the historical mold temperature fluctuation. If not, return to the step of obtaining the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment.

[0012] Furthermore, after the step of generating an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation using an adaptive tuning algorithm, the method further includes: Obtain the historical control strategies of the injection molding equipment, and determine whether the optimized control strategy is within an acceptable range based on the optimized control strategy; If so, then the step of controlling the injection molding equipment according to the optimized control strategy shall be performed; If not, the actual mold temperature of the injection molding equipment is obtained, and the optimized control strategy is adjusted according to the actual mold temperature.

[0013] Furthermore, after the step of obtaining the actual injection speed and actual injection pressure of the injection molding equipment, the method further includes: The actual mold temperature of the injection molding equipment is obtained, and the abnormal cycle pattern of the injection molding equipment is obtained based on the actual injection speed. The abnormal pressure range of the injection molding equipment is obtained based on the actual injection pressure, and the abnormal temperature distribution of the injection molding equipment is obtained based on the actual mold temperature. Based on the abnormal cycle patterns, abnormal pressure ranges, and abnormal temperature distributions, the potential failure modes of the injection molding equipment are predicted. Optimize the control parameters of the injection molding equipment based on the potential failure modes.

[0014] On the other hand, the present invention also provides a control system for cyclic stability in injection molding production, which includes a processor and a memory, the memory storing executable computer program instructions; The processor executes the computer program instructions to implement the method for controlling cycle stability in injection molding production as described in any of the above-mentioned methods.

[0015] In the technical solution of this invention, the actual injection speed and actual injection pressure of the injection molding equipment can be obtained during injection molding production to obtain the actual injection trajectory of the injection molding equipment. The actual injection trajectory deviation is then calculated based on the actual injection trajectory and a preset ideal injection trajectory. If the actual injection trajectory deviation exceeds a preset deviation threshold, the influence of this deviation on cycle stability is calculated using the injection speed weight and injection pressure weight of the injection molding equipment. Finally, if the influence exceeds a preset influence threshold, an adaptive tuning algorithm is used to generate an optimized control strategy for the injection molding equipment. Since the injection speed weight and injection pressure weight can reflect the correlation between the injection trajectory deviation and the mold temperature fluctuation, and the mold temperature of the injection molding equipment is positively correlated with cycle stability, the technical solution of this invention can accurately calculate the influence of the actual injection trajectory deviation on cycle stability. Therefore, by using an adaptive tuning algorithm to generate an optimized control strategy for the injection molding equipment, the cycle stability of injection molding production can be improved, ensuring the quality of the injection molded products. Attached Figure Description

[0016] Figure 1 This is a schematic flowchart of a method for controlling cyclic stability in injection molding production according to one embodiment of the present invention; Figure 2 This is a schematic flowchart illustrating the control method of an embodiment of the present invention, which controls an injection molding equipment according to a generated optimized control strategy. Figure 3 This is a schematic flowchart illustrating the process of determining whether the actual operating parameters of the injection molding equipment match the process requirements of injection molding production in a control method according to an embodiment of the present invention. Figure 4 This is a schematic flowchart illustrating the method for generating an optimization report for an injection molding equipment in a control method according to an embodiment of the present invention; Figure 5 This is a schematic flowchart illustrating the calculation of the actual injection trajectory deviation of an injection molding machine in a control method according to an embodiment of the present invention; and Figure 6 This is a schematic flowchart illustrating the identification and handling of potential faults in an injection molding equipment in a control method according to an embodiment of the present invention. Detailed Implementation

[0017] In the description of this embodiment, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer 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.

[0018] Reference Figure 1 , Figure 1 This is a schematic flowchart of a method for controlling cycle stability in injection molding production according to an embodiment of the present invention. The control method includes the following steps: Step S101: Obtain the actual injection speed and actual injection pressure of the injection molding equipment, and obtain the actual injection trajectory of the injection molding equipment based on the actual injection speed and actual injection pressure. Step S102: Obtain the preset ideal injection trajectory, and calculate the deviation of the actual injection trajectory of the injection molding equipment based on the actual injection trajectory of the injection molding equipment and the ideal injection trajectory; Step S103: Determine whether the actual injection trajectory deviation of the injection molding equipment is greater than the preset deviation threshold; If so, proceed to step S104; Step S104: Obtain the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment, and extract the correlation between the historical injection trajectory deviation and the historical mold temperature fluctuation to obtain the injection speed weight and injection pressure weight of the injection molding equipment. Step S105: Calculate the degree of influence of the actual injection trajectory deviation of the injection molding equipment on the cycle stability based on the injection speed weight and injection pressure weight of the injection molding equipment. Step S106: Determine whether the influence of the actual injection trajectory deviation of the injection molding equipment on the cycle stability is greater than the preset influence threshold. If so, proceed to step S106; Step S106: An adaptive tuning algorithm is used to generate an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation of the injection molding equipment, and the injection molding equipment is controlled according to the optimized control strategy.

[0019] In step S101 above, the injection molding equipment includes a hopper, a screw, a barrel, and a nozzle. The hopper stores plastic granules, and the screw rotates within the barrel to convey and heat the plastic granules. The heated and plasticized plastic is then injected into the injection mold. In this embodiment, a displacement sensor is mounted on the screw, and a pressure sensor is mounted within the cavity of the injection mold. The displacement sensor detects the screw's feed speed, which is the actual injection speed of the injection molding equipment. The pressure sensor detects the pressure at which the plastic is injected into the injection mold, which is the actual injection pressure of the injection molding equipment.

[0020] Assuming the current time is t after the injection molding process has started, the actual injection speed detected by the displacement sensor is: The actual injection pressure detected by the pressure sensor is The actual injection trajectory of the injection molding equipment for in This is a splicing function used to splice the injection speed and injection pressure according to time, so as to represent the injection speed and injection pressure of the injection molding equipment at each moment.

[0021] In step S102 above, the obtained ideal injection trajectory includes the ideal injection speed and ideal injection pressure at each moment. The actual injection trajectory deviation of the injection molding equipment includes the speed deviation between the actual injection speed and its corresponding ideal injection speed at each moment, and the pressure deviation between the actual injection pressure and its corresponding ideal injection pressure.

[0022] Assuming the ideal injection speed at time t in the preset ideal injection trajectory is... Ideal injection pressure is Actual injection speed at the current moment With ideal injection speed speed deviation between ,but Assume the actual injection pressure at the current moment. Compared with the ideal injection pressure Pressure deviation between ,but In step S103 above, the preset deviation threshold includes a preset speed deviation threshold and a preset pressure deviation threshold. If the actual injection trajectory deviation of the injection molding equipment is at the current moment, the speed deviation... The speed deviation exceeds the preset speed deviation threshold, or the pressure deviation at the current moment... If the deviation exceeds the preset pressure deviation threshold, it can be determined whether the actual injection trajectory deviation of the injection molding equipment exceeds the preset deviation threshold.

[0023] In step S104 above, the obtained historical injection trajectory deviation includes historical injection speed deviation and historical injection pressure deviation, the obtained historical mold temperature fluctuation includes the difference between historical mold temperature and standard mold temperature, and the correlation between the obtained historical injection trajectory deviation and historical mold temperature fluctuation includes the injection speed deviation weight and injection speed weight of the injection molding equipment.

[0024] In this embodiment, the Pearson correlation algorithm can be used to calculate the injection speed deviation weight and injection speed weight to obtain the correlation between historical injection trajectory deviation and historical mold temperature, specifically including: Suppose that historical injection trajectory deviation and historical mold temperature fluctuation were acquired for n consecutive time points, where the historical injection trajectory deviation at time point i includes historical injection speed deviation. Deviation from historical injection pressure The historical module temperature fluctuation at time i is ,but in Let the historical module temperature be at time i. Let the ideal mold temperature be . Assume the injection speed deviation weight is . Injection pressure weighting ,but in, This represents the average of historical injection rate deviations. This represents the average historical injection pressure deviation. This represents the average historical mold temperature.

[0025] Injection speed weighting reflects the correlation between injection speed deviation and mold temperature, while injection pressure weighting reflects the correlation between injection pressure deviation and target temperature. Furthermore, since mold temperature is positively correlated with the cycle stability of injection molding production, injection speed weighting reflects the correlation between injection speed deviation and cycle stability, and injection pressure weighting reflects the correlation between injection pressure deviation and cycle stability.

[0026] In step S105 above, let P be the degree of influence of the actual injection trajectory deviation of the injection molding equipment at the current moment on the cycle stability. If the degree of influence P is greater than the preset influence threshold, it can be determined that the actual injection trajectory deviation of the injection molding equipment has a significant impact on the cycle stability. Therefore, it is necessary to optimize the control parameters of the injection molding equipment to improve the cycle stability of the injection molding equipment.

[0027] In step S106 above, the adaptive optimization algorithm can be selected by the user. For example, the gradient descent algorithm can be used, that is, the gradient descent algorithm is used to obtain the optimized control strategy of the injection molding equipment based on the actual injection trajectory deviation of the injection molding equipment. Methods for using the gradient descent algorithm for optimized control strategies include: First, initialize the injection speed deviation adjustment and injection pressure deviation adjustment; Then, the injection speed deviation adjustment amount and the injection pressure deviation adjustment amount are updated according to the preset gradient descent rule; Finally, the updated injection speed deviation adjustment amount and injection pressure deviation adjustment amount are obtained.

[0028] In this embodiment, according to the preset gradient descent rule, the calculation formula used in each update of the injection speed deviation adjustment and injection pressure deviation adjustment is as follows: in, The learning step size for injection speed. The learning step size for injection pressure. This is the injection speed deviation adjustment amount before the update. This is the injection pressure deviation adjustment amount before the update. This is the updated injection speed deviation adjustment amount. This is the updated injection pressure deviation adjustment amount. The objective function is denoted as .

[0029] After updating the injection speed deviation adjustment amount and injection pressure deviation adjustment amount a set number of times according to the preset gradient descent rule, or after the value of the objective function is less than the preset target value, the final injection speed deviation adjustment amount is obtained. and the final injection pressure deviation adjustment amount Then, the target injection speed of the injection molding equipment is calculated using the following formula. and target injection pressure : Finally, the target injection speed is obtained based on the performance of the injection molding equipment. and target injection pressure The required control parameters are the optimal control strategy.

[0030] In summary, this embodiment obtains the actual injection speed and actual injection pressure of the injection molding equipment during injection molding production to obtain the actual injection trajectory. Based on this actual injection trajectory and a preset ideal injection trajectory, the actual injection trajectory deviation is calculated. Then, when the actual injection trajectory deviation exceeds a preset deviation threshold, the impact of this deviation on cycle stability is calculated using the injection speed weight and injection pressure weight of the injection molding equipment. Finally, when the impact exceeds a preset impact threshold, an adaptive tuning algorithm is used to generate an optimized control strategy for the injection molding equipment. Since the injection speed weight and injection pressure weight reflect the correlation between the injection trajectory deviation and mold temperature fluctuations, and the mold temperature of the injection molding equipment is positively correlated with cycle stability, this embodiment can accurately calculate the impact of the actual injection trajectory deviation on cycle stability. Therefore, by using an adaptive tuning algorithm to generate an optimized control strategy for the injection molding equipment, the cycle stability of injection molding production can be improved, ensuring the quality of the injection-molded products.

[0031] In some embodiments of the present invention, the method for controlling the injection molding equipment according to the generated optimized control strategy in step S106 is as follows: Figure 2 As shown, it includes the following steps: Step S201: Obtain the actual operating parameters of the injection molding equipment and determine whether the actual operating parameters match the process requirements of injection molding production; If not, proceed to step S202; Step S202: Feedback control of the injection molding equipment is performed based on the geometric characteristics of the product produced by injection molding.

[0032] In step S201 above, the actual operating parameters of the injection molding equipment obtained include the actual mold temperature, actual injection pressure, and actual injection speed. After obtaining the actual operating parameters of the injection molding equipment, it can be determined whether the actual operating parameters match the process requirements of injection molding production based on the consistency between the actual operating parameters and the preset standard operating parameters.

[0033] For example, in this embodiment, the deviation between the actual operating parameters of the injection molding equipment and its corresponding standard operating parameters can be calculated, and it can be determined whether the deviation is within the preset deviation range. If it is, it is determined that the actual operating parameters of the injection molding equipment do not match the process requirements of injection molding production; if not, it is determined that the actual operating parameters of the injection molding equipment do not match the process requirements of injection molding production.

[0034] In step S202 above, the method for feedback control of the injection molding equipment based on the geometric characteristics of the injection-molded product includes: First, the PID (Proportional-Integral-Derivative) algorithm is used to obtain the optimized injection speed of the injection molding equipment based on the actual injection speed of the injection molding equipment; Then, the optimal injection pressure of the injection molding equipment is obtained based on the geometric characteristics of the product produced by injection molding; Finally, the injection molding equipment is controlled based on the optimized injection speed and optimized injection pressure.

[0035] In this embodiment, the method for obtaining the optimized injection speed of the injection molding equipment based on the actual injection speed of the injection molding equipment includes: in, To optimize the injection speed of the injection molding equipment at any given moment, The standard injection speed of the injection molding equipment at time t. This represents the actual injection speed of the injection molding equipment at the current moment. This represents the injection speed deviation of the injection molding equipment at the current moment. This is a preset proportional coefficient, with a preferred value of 0.8; This is a preset integral coefficient, which is preferably set to 0.1; The preset differential coefficient is 0.05.

[0036] In this embodiment, the method for obtaining the optimal injection pressure of the injection molding equipment based on the geometric characteristics of the product produced by injection molding includes: using finite element analysis software to establish a finite element analysis model of the injection mold based on the geometric characteristics of the injection mold; and then obtaining the optimal injection pressure of the injection molding equipment at the optimized injection speed, which is the optimal injection pressure of the injection molding equipment.

[0037] In this embodiment, the method for obtaining optimized injection pressure under optimized injection speed includes: First, determine the optimal injection pressure range based on the actual injection pressure of the injection molding equipment. Then, obtain the injection pressure with the smallest mold temperature fluctuation at the optimized injection speed through the finite element analysis model of the injection mold. This injection pressure is the optimal injection pressure of the injection molding equipment.

[0038] In this embodiment, let the detected actual injection pressure of the injection molding equipment at the current moment be... The optimal injection pressure range is [ , ],in To set the pressure deviation, temperature detection points are set at multiple locations in the finite element analysis model of the injection mold. In this embodiment, the average temperature value of each temperature detection point is used as the mold temperature of the injection molding equipment.

[0039] In this embodiment, after obtaining the optimized injection speed and injection pressure of the injection molding equipment, control parameters corresponding to the optimized operating parameters of the injection molding equipment can be obtained based on the equipment performance. The injection molding equipment can then be controlled according to these control parameters to improve the cycle stability of the injection molding production process.

[0040] This embodiment detects the actual operating parameters of the injection molding equipment to provide real-time feedback control, thereby further improving the cycle stability of the injection molding production process.

[0041] In some embodiments of the present invention, the method for determining whether the actual operating parameters of the injection molding equipment match the process requirements of injection molding production in step S201 is as follows: Figure 3 As shown, it includes the following steps: Step S211: Obtain the standard operating parameters of the injection molding equipment, calculate the deviation between the actual operating parameters of the injection molding equipment and the standard operating parameters, and determine whether the deviation is within the preset deviation range; If not, proceed to step S212; Step S212: Obtain the predicted operating parameters of the injection molding equipment based on the actual operating parameters of the injection molding equipment, and obtain the predicted failure rate of the injection molding equipment based on the predicted operating parameters. Step S213: Determine whether the predicted failure rate of the injection molding equipment is greater than the set failure rate threshold; If so, proceed to step S214; Step S214 determines that the actual operating parameters of the injection molding equipment do not match the process requirements of injection molding production.

[0042] In step S211 above, the standard operating parameters obtained include the standard mold temperature, standard injection pressure and standard injection speed of the injection molding equipment, and the deviation between the actual operating parameters of the injection molding equipment and the standard operating parameters includes the deviation between the actual mold temperature and the standard mold temperature, the deviation between the actual injection pressure and the standard injection pressure, and the deviation between the actual injection speed and the standard injection speed.

[0043] If the deviation between the actual mold temperature and the standard mold temperature is not within the preset temperature difference range, or the deviation between the actual injection pressure and the standard injection pressure is not within the preset pressure difference range, or the deviation between the actual injection speed and the standard injection speed is not within the preset speed difference range, then it is determined that the deviation between the actual operating parameters of the injection molding equipment and the standard operating parameters is not within the preset deviation range.

[0044] In step S212 above, the actual operating parameters of the injection molding equipment at multiple consecutive times before the current time can be obtained, and the operating parameter curve of the injection molding equipment can be constructed with time as the independent variable and the actual operating parameters as the dependent variable. Then, the predicted operating parameters of the injection molding equipment can be predicted based on the operating parameter curve.

[0045] In this embodiment, the correspondence between the operating parameter range and the failure rate can be preset, and after obtaining the predicted operating parameters of the injection molding equipment, the operating parameter range in which the predicted operating parameters are located can be obtained, and the operating parameter range can be used as the predicted failure rate of the injection molding equipment.

[0046] In step S213 above, if the predicted failure rate of the injection molding equipment is greater than the set failure rate threshold, it is determined that the injection molding equipment may affect the quality of the injection molded products due to the excessively high predicted failure rate. Therefore, in step S214, it is determined that the actual operating parameters of the injection molding equipment do not match the process requirements of injection molding production.

[0047] This embodiment can accurately determine whether the actual operating parameters of the injection molding equipment do not match the process requirements of injection molding production based on the predicted operating parameters of the injection molding equipment. Then, based on the judgment result, feedback control can be performed on the injection molding equipment, which can further improve the cycle stability of the injection molding equipment in injection molding production.

[0048] In some embodiments of the present invention, after controlling the injection molding equipment according to the optimized control strategy produced in step S106, the method further includes: After the injection molding process is completed, the final injection trajectory of the injection molding equipment is obtained, and an operation log of the cycle stability in the injection molding production is generated based on the final injection trajectory.

[0049] In this embodiment, the injection pressure, mold temperature and injection speed of the injection molding equipment at each moment in the injection molding production can be obtained based on the final injection trajectory of the injection molding equipment, and the injection pressure, mold temperature and injection speed at each moment can be recorded to generate an operation log of the cycle stability in the injection molding production.

[0050] This embodiment generates a cycle stability operation log after the injection molding process is completed, which can provide a reference for the injection molding equipment in future injection molding processes.

[0051] In some embodiments of the present invention, after generating an operation log of the cycle stability in injection molding production based on the final injection trajectory of the injection molding equipment, an optimization report of the injection molding equipment based on the final injection trajectory of the injection molding equipment is also performed.

[0052] The method for generating the optimization report for the injection molding equipment in this embodiment is as follows: Figure 4 As shown, it includes the following steps: Step S301: Generate the operation process parameters of injection molding production based on the final injection trajectory, and obtain the cyclic stability characteristics of injection molding production based on the operation process parameters; Step S302: Obtain the cycle mode of injection molding production based on the cycle stability characteristics of injection molding production, and determine whether the cycle mode is an abnormal cycle mode. If so, proceed to step S303; Step S303: Identify quality risk points in the final injection trajectory and obtain the parameter adjustment strategy corresponding to each quality risk point; Step S304: Generate an optimization report for the injection molding equipment based on the quality risk points in the final injection trajectory and their corresponding parameter adjustment strategies.

[0053] In step S301 above, the final injection trajectory can be divided into multiple time periods, and then the average operating parameters in each time period, such as average injection speed, average injection pressure and average mold temperature, can be obtained. The average operating parameters in each time period are used as the cyclic stability characteristics of the final injection trajectory.

[0054] In step S302 above, multiple historical final injection molding trajectories can be obtained in advance. Then, the k-means algorithm is used to cluster them according to the similarity between the historical final injection molding trajectories, and the cluster center of each cluster is obtained. Based on the number of abnormal operating parameters in each cluster center, the anomaly level of each cluster is obtained.

[0055] In this embodiment, each historical final injection trajectory is divided into m time periods, and there are h types of running process parameters in the historical final injection trajectory. Then, the similarity between the k-th historical final injection trajectory and the u-th historical final injection trajectory is... ,but in, The weights of the parameters for the i-th type of operation process are... Let be the similarity between the k-th historical final injection trajectory and the i-th time period in the u-th historical final injection trajectory, and in Let be the average value of the j-th type of operation process parameter in the k-th historical final injection trajectory during the i-th time period. It represents the average value of the j-th type of operation process parameter in the i-th time period within the u-th historical final injection trajectory.

[0056] Then, the similarity between the cyclic stability characteristics of the final injection trajectory and each cluster center is calculated. The cluster with the highest similarity between the cluster center and the cyclic stability characteristics of the final injection trajectory is taken as the cluster to which the final injection trajectory belongs. If the anomaly level of this cluster is greater than the set level, the cyclic mode of injection production is judged to be an abnormal cyclic mode.

[0057] In this embodiment, preset parameter adjustment strategies for various types of quality risk points can be pre-set. For example, if one type of quality risk point is characterized by the difference between the mold temperature and the standard mold temperature being greater than a first preset difference, the difference between the injection speed and the standard injection speed being greater than a first preset speed difference, and the injection pressure being greater than a first preset pressure difference, then the preset parameter adjustment strategy corresponding to this quality risk point can be: increasing the coolant flow rate by a first flow rate, decreasing the injection speed by a first speed, and decreasing the injection pressure by a first pressure. In step S303 above, the quality risk points in the final injection trajectory can be obtained based on the deviation between the final injection trajectory and the standard injection trajectory. Then, the preset parameter adjustment strategy corresponding to the type of the quality risk point can be obtained, and this preset parameter adjustment strategy can be used as the parameter adjustment strategy for the quality risk point.

[0058] After injection molding is completed, this embodiment also generates an optimization report for the injection molding equipment based on the final injection trajectory of the injection molding equipment. This report can provide reliable response strategies for quality risk points that may occur in subsequent injection molding production.

[0059] In some embodiments of the present invention, the method for calculating the deviation of the actual injection trajectory of the injection molding equipment based on the actual injection trajectory of the injection molding equipment and the ideal injection trajectory in step S102 is as follows: Figure 5 As shown, it includes the following steps: Step S111: Based on the actual injection trajectory of the injection molding equipment, obtain the actual average injection speed and actual average injection pressure of the injection molding equipment within a set time period before the current moment. Step S112: Based on the ideal injection trajectory of the injection molding equipment, obtain the ideal average injection speed and ideal average injection pressure of the injection molding equipment within a set time period before the current moment. Step S113: Calculate the difference between the actual average injection speed and the ideal average injection speed of the injection molding equipment within a set time period, and the difference between the actual average injection pressure and the ideal average injection pressure, so as to obtain the actual injection trajectory deviation of the injection molding equipment.

[0060] This embodiment calculates the actual injection trajectory deviation of the injection molding equipment based on the actual average injection speed and actual average injection pressure within a set time period before the current moment, as well as the ideal average injection speed and ideal average injection pressure. This ensures that the calculated actual injection trajectory deviation is a continuous deviation, improves the accuracy of obtaining the degree of influence of the actual injection trajectory deviation on the cycle stability, and thus ensures the cycle stability of the injection molding equipment in injection molding production.

[0061] In some embodiments of the present invention, after obtaining the historical injection trajectory deviation and historical mold temperature of the injection molding equipment, step S104 further includes: Determine whether the historical mold temperature fluctuations of the injection molding equipment are evenly distributed. If so, then perform the steps described above to determine the correlation between historical injection trajectory deviation and historical mold temperature; If not, return to the steps for obtaining the historical injection trajectory deviation and historical mold temperature of the injection molding equipment.

[0062] In this embodiment, the standard deviation of each historical mold temperature can be calculated first. If the standard deviation is greater than the preset variance threshold, it is determined that the historical mold temperature distribution of the injection molding equipment is uneven.

[0063] In this embodiment, assuming a uniform distribution of historical mold temperature fluctuations in the injection molding equipment, the injection speed weight and injection pressure weight are extracted based on the acquired historical injection trajectory deviation and historical mold temperature fluctuations. Therefore, based on these injection speed and injection pressure weights, the impact of the actual injection trajectory deviation on cycle stability can be accurately calculated, thereby improving the cycle stability of the injection molding equipment in injection molding production.

[0064] In some embodiments of the present invention, after generating an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation of the injection molding equipment using an adaptive tuning algorithm, the method further includes: Obtain the historical control strategies of the injection molding equipment, and determine whether the generated optimized control strategy is within an acceptable range based on the historical control strategies; If so, then execute the steps to control the injection molding equipment according to the generated optimized control strategy; If not, obtain the actual mold temperature of the injection molding equipment and adjust and optimize the control strategy based on the actual mold temperature.

[0065] In this embodiment, the slope of change of each historical control parameter of the injection molding equipment can be obtained based on adjacent control parameters in the historical control strategy of the injection molding equipment, and the smallest slope of change is taken as the optimal slope of change. After obtaining the optimized control strategy of the injection molding equipment, the expected slope of change of the injection molding equipment can be calculated based on the optimal control strategy and the actual control parameters of the injection molding equipment. If the difference between the expected slope of change of the injection molding equipment and the above-mentioned optimal slope of change is greater than the set slope threshold, it can be determined that the generated optimized control strategy is within the acceptable range; otherwise, it is determined that the generated optimized control strategy is not within the acceptable range.

[0066] In this embodiment, the adjustment amount of the injection speed and injection pressure of the injection molding equipment in the optimization control strategy can be reduced based on the deviation between the actual mold temperature and the ideal mold temperature of the injection molding equipment. Moreover, the greater the deviation between the actual mold temperature and the ideal mold temperature of the injection molding equipment, the greater the magnitude of the reduction in the adjustment amount.

[0067] After obtaining the optimized control strategy for the injection molding equipment, this embodiment also determines whether the optimized control strategy is within an acceptable range. Therefore, it can prevent the optimized control strategy of the injection molding equipment from exceeding the acceptable range and affecting the cycle stability of injection molding production.

[0068] In some embodiments of the present invention, after obtaining the actual injection speed and actual injection pressure of the injection molding equipment in step S101, the method further includes: identifying and handling potential faults of the injection molding equipment based on the actual injection speed and actual injection pressure of the injection molding equipment.

[0069] In this embodiment, the process of identifying and handling potential faults in the injection molding equipment based on the actual injection speed and actual injection pressure is as follows: Figure 6 As shown, it includes the following steps: Step S121: Obtain the actual mold temperature of the injection molding equipment, obtain the abnormal cycle mode of the injection molding equipment based on the obtained actual injection speed, obtain the abnormal pressure range of the injection molding equipment based on the obtained actual injection pressure, and obtain the abnormal temperature distribution of the injection molding equipment based on the obtained actual mold temperature. Step S122: Based on the abnormal cycle pattern, abnormal pressure range, and abnormal temperature distribution of the injection molding equipment, determine the potential faults of the injection molding equipment; Step S123: Adjust the control parameters of the injection molding equipment according to the potential faults of the injection molding equipment.

[0070] In step S121 above, the actual injection speed of the injection molding equipment at multiple consecutive moments can be obtained first, and the moment when the deviation from the ideal injection speed is greater than the set speed deviation threshold can be taken as the abnormal injection speed moment of the injection molding equipment. Then, Fourier transform is performed on the abnormal injection speed moment to obtain the abnormal injection speed cycle of the injection molding equipment, so as to obtain the abnormal cycle mode of the injection molding equipment.

[0071] In this embodiment, the actual injection pressure of the injection molding equipment at multiple consecutive moments can be obtained first, and the standard deviation of each injection pressure can be calculated. Then, the preset pressure range in which the standard deviation is located can be used as the abnormal pressure range of the injection molding equipment.

[0072] This embodiment can obtain the actual mold temperature of the injection molding equipment at multiple consecutive moments, calculate the deviation between each actual mold temperature and the ideal mold temperature, and use the preset temperature difference range and duration of the deviation as the temperature anomaly distribution of the injection molding equipment.

[0073] In step S122 above, the abnormal injection speed frequency of the injection molding equipment can be obtained from the abnormal cycle mode of the injection molding equipment. If the frequency is greater than the set frequency threshold, it can be determined that there is mechanical vibration in the injection molding equipment. Therefore, in step S123, it is necessary to adjust the parameters of the servo motor to reduce the intensity of mechanical vibration of the injection molding equipment.

[0074] In step S122 above, if the standard deviation of the actual injection pressure of the injection molding equipment at multiple consecutive moments exceeds the set standard deviation threshold, it can be determined that the injection pressure distribution of the injection molding equipment is uneven, possibly due to abnormal raw material flowability. Therefore, in step S123 above, it is necessary to adjust the preheating temperature of the raw material for injection production according to the abnormal pressure range of the injection molding equipment.

[0075] In step S122 above, if the deviation between the actual mold temperature and the ideal mold temperature of the injection molding equipment is greater than the set temperature deviation threshold and the duration is greater than the set duration threshold, it can be determined that the temperature of the injection mold is abnormal. Therefore, in step S123 above, the heating power of the injection molding equipment is adjusted according to the deviation.

[0076] This embodiment can identify potential failure modes of injection molding equipment based on the actual injection speed, actual injection pressure, and actual mold temperature during injection molding production, and adjust the control parameters of the injection molding equipment accordingly, thereby improving the reliability of the injection molding equipment in injection molding production.

[0077] This invention also provides a control system for cycle stability in injection molding production, including a control device and injection molding equipment. The control device includes a processor, a memory, a communication interface, and a communication bus. The processor, memory, and communication interface communicate with each other via the communication bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer program instructions. The internal memory provides an environment for the operation of the operating system and computer program instructions in the non-volatile storage medium. The communication interface of the control device is used for wired or wireless communication with external terminals. Wireless communication can be achieved through WIFI, carrier networks, NFC (Near Field Communication), or other technologies. The memory of the control device stores computer program instructions, which, when executed by the processor, can implement multiple embodiments of the control method for cycle stability in injection molding production.

[0078] The terms "first" or "second," etc., used to designate numbers or ordinal numbers in this specification are for descriptive purposes only and should not be construed as indicating relative importance or implying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this specification, "a plurality of" means at least two, such as two, three, or more, unless otherwise expressly and specifically defined.

[0079] While various embodiments of the invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of the invention. The appended claims are intended to define the scope of the invention and therefore cover any modular compositions, equivalents, or alternatives within the scope of these claims.

Claims

1. A method for controlling cyclic stability in injection molding production, characterized in that, include: The actual injection speed and actual injection pressure of the injection molding equipment are obtained, and the actual injection trajectory of the injection molding equipment is obtained based on the actual injection speed and actual injection pressure. Obtain a preset ideal injection trajectory, calculate the deviation of the actual injection trajectory based on the actual injection trajectory and the ideal injection trajectory, and determine whether the deviation of the actual injection trajectory is greater than a preset deviation threshold. If so, the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment are obtained, and the correlation between the historical injection trajectory deviation and the historical mold temperature fluctuation is extracted to obtain the injection speed weight and injection pressure weight of the injection molding equipment. The impact of the actual injection trajectory deviation on cycle stability is calculated based on the injection speed weight and injection pressure weight. When the degree of influence exceeds a preset influence threshold, an adaptive optimization algorithm is used to generate an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation, and the injection molding equipment is controlled according to the optimized control strategy.

2. The control method according to claim 1, characterized in that, The step of controlling the injection molding equipment according to the optimized control strategy further includes: Obtain the actual operating parameters of the injection molding equipment and determine whether the actual operating parameters match the process requirements of the injection molding production; If not, the injection molding equipment is adjusted based on the geometric characteristics of the product produced by injection molding.

3. The control method according to claim 2, characterized in that, The step of determining whether the actual operating parameters match the process requirements of the injection molding production includes: Obtain the standard operating parameters of the injection molding equipment, calculate the deviation between the actual operating parameters and the standard operating parameters, and determine whether the deviation is within the preset deviation range; If not, then obtain the predicted operating parameters of the injection molding equipment, and obtain the predicted failure rate of the injection molding equipment based on the predicted operating parameters; If the predicted failure rate is greater than the set failure rate threshold, it is determined that the actual operating parameters do not match the process requirements of the injection molding production.

4. The control method according to claim 1, characterized in that, After the step of controlling the injection molding equipment according to the optimized control strategy, the method further includes: After the injection molding process is completed, the final injection trajectory of the injection molding equipment is obtained, and an operation log of the cycle stability during the injection molding process is generated based on the final injection trajectory.

5. The control method according to claim 4, characterized in that, After the step of generating the operation log of the cycle stability in the injection molding production based on the final injection trajectory, the method further includes: The injection molding process parameters are generated based on the final injection trajectory, and the cycle mode of the injection molding process is obtained based on the injection molding process parameters. Determine whether the loop pattern is an abnormal loop pattern; If so, identify the quality risk points in the final injection trajectory and obtain the parameter adjustment strategy corresponding to each quality risk point to generate an optimization report for the injection molding equipment.

6. The control method according to claim 1, characterized in that, The step of calculating the deviation of the actual injection trajectory based on the actual injection trajectory and the ideal injection trajectory includes: Based on the actual injection trajectory, obtain the actual average injection speed and actual average injection pressure within a set time period before the current moment; Based on the ideal injection trajectory, obtain the ideal average injection speed and ideal average injection pressure within a set time period before the current moment; The difference between the actual average injection speed and the ideal average injection speed, and the difference between the actual average injection pressure and the ideal average injection pressure are calculated to obtain the actual injection trajectory deviation.

7. The control method according to claim 1, characterized in that, After the steps of obtaining the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment, the method further includes: Determine whether the historical mold temperature fluctuations are evenly distributed; If so, then perform the step of extracting the correlation between the historical injection trajectory deviation and the historical mold temperature fluctuation. If not, return to the step of obtaining the historical injection trajectory deviation and historical mold temperature fluctuation of the injection molding equipment.

8. The control method according to claim 1, characterized in that, After the step of generating an optimized control strategy for the injection molding equipment based on the actual injection trajectory deviation using an adaptive tuning algorithm, the method further includes: Obtain the historical control strategies of the injection molding equipment, and determine whether the optimized control strategy is within an acceptable range based on the optimized control strategy; If so, then the step of controlling the injection molding equipment according to the optimized control strategy shall be performed; If not, the actual mold temperature of the injection molding equipment is obtained, and the optimized control strategy is adjusted according to the actual mold temperature.

9. The control method according to claim 1, characterized in that, After the step of obtaining the actual injection speed and actual injection pressure of the injection molding equipment, the method further includes: The actual mold temperature of the injection molding equipment is obtained, and the abnormal cycle pattern of the injection molding equipment is obtained based on the actual injection speed. The abnormal pressure range of the injection molding equipment is obtained based on the actual injection pressure, and the abnormal temperature distribution of the injection molding equipment is obtained based on the actual mold temperature. Based on the abnormal cycle patterns, abnormal pressure ranges, and abnormal temperature distributions, the potential failure modes of the injection molding equipment are predicted. Optimize the control parameters of the injection molding equipment based on the potential failure modes.

10. A control system for cyclic stability in injection molding production, characterized in that, The control system includes a processor and a memory, the memory storing executable computer program instructions; The processor executes the computer program instructions to implement the method for controlling cycle stability in injection molding production as described in any one of claims 1-9.

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