Cavity temperature inversion method and system based on measured pressure and digital twin model
By coupling and calibrating the digital twin simulation model with measured pressure data, the problem of accurate acquisition of melt temperature inside the mold cavity was solved, achieving high-precision temperature inversion without the need for additional sensors, thus improving the analytical accuracy and production stability of the injection molding process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-12
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies struggle to accurately acquire the temperature of the melt inside the mold cavity without a temperature sensor. Furthermore, existing multi-sensor solutions are complex, costly, and have poor adaptability, making it impossible to simultaneously acquire pressure and temperature signals.
By constructing a digital twin simulation model and using measured pressure data to invert the cavity temperature, combined with iterative calibration of rheological parameters, material PVT parameters, and interfacial thermal conductivity coefficients, the accurate inversion of the melt temperature inside the cavity is achieved, reducing the number of sensors and improving the accuracy and reliability of temperature acquisition.
It achieves high-precision inversion of the melt temperature inside the mold cavity, reduces hardware costs and operational complexity, ensures the spatiotemporal synchronization of pressure and temperature data, and improves the accuracy of process analysis and production stability.
Smart Images
Figure CN122165611A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of mold measurement and control technology, and relates to a method and system for inverting mold cavity temperature based on measured pressure and digital twin model. Background Technology
[0002] In injection molding, melt pressure and mold cavity temperature are core physical quantities that are coupled and mutually influential, jointly determining the final quality and performance of the injection molded product. Pressure directly affects the filling, compression, and holding effects of the melt, and is directly related to defects such as dimensional stability, shrinkage, and flash. Temperature, on the other hand, regulates melt viscosity, fluidity, and cooling rate, affecting the surface quality, internal stress, and crystallinity of the product, and is crucial for ensuring product consistency.
[0003] Currently, while techniques for measuring pressure or temperature individually during injection molding are relatively mature and can solve some molding quality problems, due to the coupling characteristics of pressure and temperature, individual measurements cannot fully reflect the true molding state within the mold cavity, making it difficult to achieve precise analysis and refined control of the injection molding process. In contrast, simultaneously acquiring pressure and temperature signals at the same location can achieve a "1+1>2" technical effect, more comprehensively capturing the physical state changes of the melt within the mold cavity and providing more reliable data support for process optimization and defect diagnosis.
[0004] Existing measurement solutions mainly fall into two categories: one is single-sensor measurement, where a pressure sensor or temperature sensor is installed only at the top or bottom of the ejector pin. This can only acquire one signal and cannot utilize the coupling relationship between the two for process analysis, resulting in a limited measurement dimension. The other is multi-sensor separate installation, where the pressure sensor is installed at the top of the ejector pin and the temperature sensor at the rear, enabling multi-signal acquisition. However, this type of solution has a complex mechanism design, dispersed sensor installation positions, and cannot simultaneously acquire pressure and temperature signals at the same location. Furthermore, its overall structure lacks versatility and is difficult to flexibly adapt to molds of different specifications. It is particularly unsuitable for scenarios requiring frequent mold changes, such as trial molding, increasing equipment costs and operational complexity. In addition, the melt temperature history at specific points inside the mold cavity is difficult to measure directly, and existing technologies lack effective indirect calculation methods. Summary of the Invention
[0005] The purpose of this invention is to address the aforementioned problems in the existing technology by proposing a method and system for inverting mold cavity temperature based on measured pressure and a digital twin model. The technical problem to be solved is: how to improve the accuracy of obtaining the melt temperature inside the mold cavity without a temperature sensor.
[0006] The objective of this invention can be achieved through the following technical solution: a method for inverting cavity temperature based on measured pressure and a digital twin model, comprising the following steps:
[0007] S1. Model Construction and Simulation: Construct a digital twin simulation model corresponding to the injection molding process, input initial material parameters and process conditions into the digital twin simulation model, run the digital twin simulation model, and obtain the simulated pressure curve at a specified position in the mold cavity;
[0008] S2. Data Acquisition and Calibration: Real-time acquisition of measured pressure curves at the same designated location during the same injection molding process; using the measured pressure curves as a benchmark, adjusting one or more core injection parameters in the digital twin simulation model to ensure that the deviation between the simulated pressure curves and the measured pressure curves is within a preset allowable range.
[0009] S3. Temperature Inversion Output: When the deviation between the simulated pressure curve and the measured pressure curve is within the preset allowable range, the melt temperature curve obtained by the digital twin simulation model at this time is extracted as the inversion result of the melt temperature at that point in the actual injection molding process.
[0010] When calculating the melt temperature inside the mold cavity using this cavity temperature inversion method, the process begins with a simulation based on a constructed digital twin model to obtain the simulated pressure curve of the melt inside the mold cavity. Then, a pressure sensor module collects the measured pressure curve at the same specified location within the mold cavity during the injection molding process, comparing the simulated and measured pressure curves. If the deviation exceeds a preset tolerance range, the core injection parameters in the digital twin model are adjusted until the deviation between the simulated and measured pressure curves is within the preset tolerance range. At this point, the melt temperature curve output by the digital twin model is extracted and used as the true inversion result of the melt temperature inside the mold cavity during the actual injection molding process. This method, through the coupling calibration of the digital twin model and the measured pressure curve, utilizes the coupling relationship between pressure and temperature to converge the melt temperature parameters in reverse, ensuring that the simulation model remains consistent with the actual injection molding process. This achieves accurate inversion of the melt temperature inside the mold cavity without the need for additional temperature sensors, improving the accuracy and reliability of temperature acquisition. Meanwhile, this method achieves pressure measurement and real-time temperature calculation from the same source and point based on measured melt pressure data, overcoming the shortcomings of traditional multi-sensor separate installation and time-division measurement, ensuring the spatiotemporal synchronization and direct correlation of pressure and temperature data, significantly improving the accuracy of process analysis, and avoiding process judgment deviations caused by data asynchrony.
[0011] In the aforementioned method for inverting mold cavity temperature based on measured pressure and a digital twin model, in step S1, the material parameters include rheological parameters, thermal property parameters, material PVT parameters, and mechanical property parameters; the process conditions include filling parameters, holding pressure parameters, cooling parameters, and injection molding machine parameters. By fully inputting material parameters such as rheology, thermal properties, and PVT, as well as process conditions such as filling, holding pressure, and cooling, the digital twin simulation model more closely resembles the actual injection molding physical process, improving the initial accuracy of the simulation pressure curve and laying a reliable foundation for subsequent calibration and temperature inversion.
[0012] In the above-described method for inverting mold cavity temperature based on measured pressure and a digital twin model, in step S2, the core injection molding parameters include rheological parameters; the calibration operation includes:
[0013] Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the filling stage, the rheological parameters in the digital twin model are adjusted so that the deviation between the shape of the simulated pressure curve and the measured pressure curve during the filling stage is within a preset allowable range.
[0014] This step, by adjusting the rheological parameters, achieves accurate fitting of the pressure curve during the filling stage, thereby improving the accuracy of temperature inversion during the filling stage.
[0015] In the above-mentioned method for inverting the cavity temperature based on measured pressure and digital twin model, the operation of adjusting the rheological parameters in step S2 includes: adjusting the zero-shear viscosity coefficient and temperature offset coefficient that affect the melt viscosity.
[0016] By precisely adjusting the core coefficients that affect melt viscosity, the melt flow resistance and temperature sensitivity are made consistent with the actual material, further reducing the deviation between simulation and measured pressure and improving the accuracy of temperature inversion.
[0017] In the above-described cavity temperature inversion method based on measured pressure and digital twin model, in step S2, the core injection molding parameters also include material PVT parameters; the calibration operation further includes:
[0018] Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the pressure holding stage and / or cooling stage, the material PVT parameters in the digital twin model are adjusted so that the deviation between the simulated pressure curve and the measured pressure curve during the pressure holding stage and / or cooling stage is within a preset allowable range.
[0019] To address the significant impact of pressure variations on specific volume during the holding / cooling phase, the pressure curve for this phase is fitted by adjusting the material's PVT parameters. This makes the simulation more closely reflect the melt compression and cooling behavior, thereby improving the stability of the full-cycle temperature inversion.
[0020] In the above-described method for inverting mold cavity temperature based on measured pressure and a digital twin model, in step S2, the core injection molding parameter further includes the interfacial thermal conductivity coefficient between the melt and the mold; the calibration operation also includes:
[0021] Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the pressure holding stage and / or cooling stage, the interfacial thermal conductivity coefficient in the digital twin model is adjusted so that the deviation between the shape of the simulated pressure curve and the measured pressure curve during the pressure holding stage and / or cooling stage is within a preset allowable range.
[0022] By optimizing the thermal conductivity coefficient at the interface between the melt and the mold, the simulated temperature and pressure fields are made closer to the actual heat dissipation process, further improving the realism and accuracy of temperature inversion during the holding / cooling stage.
[0023] In the above-mentioned cavity temperature inversion method based on measured pressure and digital twin model, the cavity temperature inversion method also includes an anomaly early warning step:
[0024] The system monitors the pressure changes of the measured pressure curve and the temperature fluctuations of the inverted melt temperature curve during the injection molding process in real time. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold within a unit time, or when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold within a predetermined time period, an early warning signal is generated to provide an abnormality reminder.
[0025] By quantitatively monitoring the pressure rise gradient and temperature fluctuation amplitude, injection molding anomalies can be identified in real time and timely warnings can be issued, avoiding product defects caused by sudden pressure increases and abnormal temperature fluctuations, thereby improving production stability and product qualification rate.
[0026] A cavity temperature inversion system based on measured pressure and a digital twin model includes:
[0027] The pressure sensing module is used to collect the measured pressure curve at a specified point inside the mold cavity;
[0028] The data processing module has a pre-built digital twin simulation model corresponding to the injection molding process. It is used to receive the measured pressure curve and run the digital twin simulation model to obtain the simulated pressure curve. Based on the comparison results between the measured pressure curve and the simulated pressure curve, it adjusts one or more core injection parameters in the digital twin simulation model to complete the calibration, and extracts the melt temperature curve output by the digital twin simulation model after calibration.
[0029] The human-computer interaction module is used to simultaneously output the measured pressure curve and the inverted melt temperature curve;
[0030] Both the pressure sensing module and the human-computer interaction module are connected to the data processing module.
[0031] This system can achieve pressure acquisition and temperature inversion using only a pressure sensing module and a digital twin model, reducing the number of sensors, lowering hardware costs and installation complexity. The system has a simple structure, high integration, and strong adaptability, and can simultaneously output pressure and temperature curves to achieve integrated monitoring of multiple parameters.
[0032] In the aforementioned cavity temperature inversion system based on measured pressure and digital twin model, the pressure sensing module is integrated inside the ejector component of the mold, i.e., inside the mold ejector pin.
[0033] In the aforementioned cavity temperature inversion system based on measured pressure and a digital twin model, the pressure sensing module employs a miniature pressure sensor.
[0034] In the aforementioned cavity temperature inversion system based on measured pressure and a digital twin model, the data processing module includes:
[0035] The pressure comparison submodule is used to receive the measured pressure curve transmitted by the pressure sensing module, compare it with the simulated pressure curve generated by the digital twin simulation model, and determine whether the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range.
[0036] The parameter calibration submodule is used to adjust the core injection molding parameters in the digital twin simulation model according to the comparison results output by the pressure comparison submodule, until the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range. The core injection molding parameters include at least rheological parameters, material PVT parameters and interfacial thermal conductivity.
[0037] The temperature inversion submodule is used to extract the melt temperature curve obtained from the digital twin simulation model after the parameter calibration submodule has completed the calibration. This curve is used as the inversion result of the melt temperature at that point in the actual injection molding process and is synchronously transmitted to the human-computer interaction module for output.
[0038] Through the coordinated operation of the pressure comparison, parameter calibration, and temperature inversion sub-modules, the system achieves automatic comparison of simulated and measured pressures, iterative parameter calibration, and accurate temperature extraction, thereby improving the automation level and reliability of the inversion results.
[0039] In the aforementioned cavity temperature inversion system based on measured pressure and a digital twin model, the data processing module further includes:
[0040] The abnormal warning submodule is used to monitor the pressure change of the measured pressure curve and the temperature fluctuation of the inverted melt temperature curve in real time. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold within a unit time, or when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold within a predetermined time period, an early warning signal is generated and transmitted to the human-machine interaction module for abnormal reminder.
[0041] The abnormal warning submodule enables real-time identification and alerts for pressure and temperature anomalies, facilitating rapid intervention by operators, ensuring continuous and stable injection molding processes, and reducing the generation of defective products.
[0042] Compared with existing technologies, the cavity temperature inversion method and system based on measured pressure and digital twin model has the following advantages:
[0043] 1. Based on the constructed digital twin simulation model, this invention realizes the reception of measured pressure curves, the generation of simulated pressure curves, and the synchronous comparison between the two, ensuring the synchronization and accuracy of pressure data acquisition and temperature data inversion. It effectively avoids measurement errors caused by the difference in response time between different sensors, and provides a more reliable and efficient multi-parameter monitoring solution for precision machining fields such as mold manufacturing and injection molding.
[0044] 2. This invention obtains the melt temperature curve by collecting the measured pressure curve at a specified point in the mold cavity and combining it with the digital twin simulation model. This eliminates the need for additional melt temperature sensors, effectively reducing the number of sensors used and thus lowering the hardware cost and maintenance complexity of the system.
[0045] 3. This invention can also monitor and warn of abnormal fluctuations in pressure and temperature in real time, guiding operators to intervene in a timely manner, avoiding batch defects, and improving production efficiency and product quality. Attached Figure Description
[0046] Figure 1 This is the control flowchart of the present invention.
[0047] Figure 2 This is a schematic diagram of the control structure of the present invention.
[0048] In the diagram, 1 is the pressure sensing module; 2 is the data processing module; 21 is the pressure comparison submodule; 22 is the parameter calibration submodule; 23 is the temperature inversion submodule; 24 is the anomaly warning submodule; and 3 is the human-computer interaction module. Detailed Implementation
[0049] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.
[0050] like Figure 1 As shown, the cavity temperature inversion method based on measured pressure and digital twin model, when applied, first enters the model construction and simulation step. Based on the 3D model of the target injection molded product, mold structure, gating system, and other information, a high-fidelity digital twin simulation model corresponding to the injection molding process is established in commercial injection molding simulation software, such as Moldex3D. Next, initial material parameters and process conditions are input into the digital twin simulation model. Material parameters include, but are not limited to: rheological parameters, such as shear viscosity curve, melt mass flow rate, glass transition temperature, and thermal properties. Energy parameters; such as specific heat capacity, thermal conductivity, and transition temperature; material PVT parameters, such as PVT curve and solid / melt density; mechanical property parameters, such as elastic modulus, Poisson's ratio, shear modulus, linear expansion coefficient, and stress-strain curve; process conditions including but not limited to: filling parameters: melt temperature, mold temperature, injection rate, and maximum machine injection force; holding pressure parameters: holding pressure and holding time; cooling parameters: cooling time, ejection temperature, coolant temperature and flow rate; injection molding machine parameters: maximum injection volume, screw diameter, hydraulic response time, and release distance.
[0051] Then, the digital twin simulation model is run to obtain the simulated pressure curve at a specified location within the mold cavity;
[0052] The data acquisition and calibration process begins with production on an actual injection molding machine. A miniature pressure sensor is installed inside the ejector pin of the mold, its position corresponding to a specified location in the simulation model. During injection molding, the measured pressure curve at that point in the same injection molding process is acquired in real time. Then, using the measured pressure curve as a benchmark, the simulated pressure curve obtained from the digital twin simulation model is compared with it. The comparison includes point-by-point comparison of the overall trend, peak value, time-series changes, and fluctuation amplitude of the two pressure curves. The deviation between the two curves is calculated, and it is determined whether it is within a preset allowable range. This deviation can be calculated as the root mean square error (RMSE). If the deviation exceeds the preset allowable range, such as RMSE > 1 MPa, a calibration operation is initiated: one or more core injection parameters in the digital twin simulation model are adjusted to ensure that the deviation between the simulated pressure curve and the measured pressure curve is within the preset allowable range. Specifically:
[0053] Filling stage calibration: This mainly involves adjusting the rheological parameters in the digital twin model, specifically the zero-shear viscosity coefficient and temperature offset coefficient, which affect melt viscosity. By comparing the pressure rise and peak value during the filling stage, if the measured peak pressure is lower than the simulated pressure value, it indicates that the actual melt viscosity may be lower than the model's set value. In this case, adjust the zero-shear viscosity coefficient in the rheological model to reduce it, or adjust the temperature offset coefficient to effectively reduce the model viscosity, bringing the simulated pressure peak value closer to the measured value.
[0054] Calibration during the holding / cooling stage: This mainly involves adjusting the material's PVT parameters and the interfacial thermal conductivity between the melt and the mold. The curves showing pressure maintenance and decrease during the holding stage are compared. If the pressure decay during holding does not match the measured values, or the predicted shrinkage of the product is inaccurate, the material's PVT parameters can be adjusted. Simultaneously, combined with the cooling rate, the interfacial thermal conductivity can be adjusted to match the actual cooling and curing behavior on the pressure decay.
[0055] Iteratively adjust one or more core injection molding parameters in the digital twin simulation model, such as rheological parameters, material PVT parameters, and / or the interfacial thermal conductivity coefficient between the melt and the mold. Rerun the digital twin simulation model. Repeat this process until the deviation between the simulated pressure curve and the measured pressure curve is within the preset allowable range. At this point, it is considered that the digital twin model has completed high-precision calibration using measured pressure data and can accurately reflect the current actual injection molding process.
[0056] Once calibration is complete, the temperature inversion output step begins. From the currently calibrated digital twin simulation model, the melt temperature data of the measurement point throughout the entire injection molding cycle is extracted to form a melt temperature curve. This curve is the melt temperature history of the same point obtained from the measured pressure and has high reliability.
[0057] Abnormal warning steps:
[0058] During the injection molding process, the pressure changes of the measured pressure curve and the temperature fluctuations of the inverted melt temperature curve are monitored in real time and compared with preset pressure gradient thresholds and temperature fluctuation amplitude thresholds. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold (e.g., 100 MPa / s) per unit time, this value can be set according to the material process. Alternatively, when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold (e.g., ±5 degrees Celsius) within a predetermined time period, an early warning signal is generated to remind the operator to intervene in a timely manner, thereby improving safety.
[0059] like Figure 2As shown, the cavity temperature inversion method based on measured pressure and a digital twin model operates on a cavity temperature inversion system based on measured pressure and a digital twin model. This system includes: a pressure sensing module 1 integrated within the mold ejector pin, specifically employing a miniature pressure sensor, used to acquire measured pressure curves at designated points within the mold cavity; a data processing module 2, pre-loaded with a digital twin simulation model corresponding to the injection molding process, used to receive the measured pressure curves and run the digital twin simulation model for calibration; and a human-machine interface module 3, used to simultaneously output the measured pressure curves and the inverted melt temperature curves, such as a touchscreen or industrial computer interface. Both the pressure sensing module 1 and the human-machine interface module 3 are connected to the data processing module 2.
[0060] Data processing module 2 specifically includes:
[0061] The pressure comparison submodule 21 is used to receive the measured pressure curve transmitted by the pressure sensing module 1, compare it with the simulated pressure curve generated by the digital twin simulation model, and determine whether the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range.
[0062] The parameter calibration submodule 22 is used to adjust the core injection molding parameters in the digital twin simulation model according to the comparison results output by the pressure comparison submodule 21 and the strategy adopted in the method, until the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range. The core injection molding parameters include at least rheological parameters, material PVT parameters and interfacial thermal conductivity.
[0063] The temperature inversion submodule 23 is used to extract the melt temperature curve obtained by the digital twin simulation model after the parameter calibration submodule 22 has completed the calibration. This curve is used as the inversion result of the melt temperature at that point in the actual injection molding process and is synchronously transmitted to the human-machine interaction module 3 for output.
[0064] The abnormal warning submodule 24 is used to monitor the pressure change of the measured pressure curve and the temperature fluctuation of the inverted melt temperature curve in real time. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold within a unit time, or when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold within a predetermined time period, an early warning signal is generated and transmitted to the human-machine interaction module 3 for abnormal reminder.
[0065] This system and method use precisely measurable measured pressure curves as the physical benchmark. By iteratively adjusting key physical property parameters in the digital twin simulation model, the simulation output of the model closely matches the actual collected data in the pressure dimension. Since pressure and temperature are strongly coupled physical fields in the model, when the digital twin simulation model is calibrated accurately in the pressure dimension, the temperature field calculated by the digital twin simulation model itself has extremely high reliability. This enables an indirect, high-precision inversion from measurable pressure to unmeasurable temperature.
[0066] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.
Claims
1. A method for inverting mold cavity temperature based on measured pressure and a digital twin model, characterized in that, The method for retrieving the cavity temperature includes the following steps: S1. Model Construction and Simulation: Construct a digital twin simulation model corresponding to the injection molding process, input initial material parameters and process conditions into the digital twin simulation model, run the digital twin simulation model, and obtain the simulated pressure curve at a specified position in the mold cavity; S2. Data Acquisition and Calibration: Real-time acquisition of measured pressure curves at the same designated location during the same injection molding process; using the measured pressure curves as a benchmark, adjusting one or more core injection parameters in the digital twin simulation model to ensure that the deviation between the simulated pressure curves and the measured pressure curves is within a preset allowable range. S3. Temperature Inversion Output: When the deviation between the simulated pressure curve and the measured pressure curve is within the preset allowable range, the melt temperature curve obtained by the digital twin simulation model at this time is extracted as the inversion result of the melt temperature at that point in the actual injection molding process.
2. The method for inverting cavity temperature based on measured pressure and digital twin model according to claim 1, characterized in that, In step S1, the material parameters include rheological parameters, thermal property parameters, material PVT parameters, and mechanical property parameters; the process conditions include filling parameters, holding pressure parameters, cooling parameters, and injection molding machine parameters.
3. The method for inverting cavity temperature based on measured pressure and digital twin model according to claim 1, characterized in that, In step S2, the core injection molding parameters include rheological parameters; the calibration operation includes: Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the filling stage, the rheological parameters in the digital twin model are adjusted so that the deviation between the shape of the simulated pressure curve and the measured pressure curve during the filling stage is within a preset allowable range.
4. The method for inverting cavity temperature based on measured pressure and digital twin model according to claim 3, characterized in that, In step S2, the operation of adjusting the rheological parameters includes adjusting the zero-shear viscosity coefficient and the temperature offset coefficient that affect the melt viscosity.
5. The method for inverting cavity temperature based on measured pressure and digital twin model according to claim 3 or 4, characterized in that, In step S2, the core injection molding parameters also include material PVT parameters; the calibration operation further includes: Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the pressure holding stage and / or cooling stage, the material PVT parameters in the digital twin model are adjusted so that the deviation between the simulated pressure curve and the measured pressure curve during the pressure holding stage and / or cooling stage is within a preset allowable range.
6. The method for inverting cavity temperature based on measured pressure and digital twin model according to claim 5, characterized in that, In step S2, the core injection molding parameters also include the interfacial thermal conductivity coefficient between the melt and the mold; the calibration operation also includes: Based on the comparison results between the measured pressure curve and the simulated pressure curve obtained during the pressure holding stage and / or cooling stage, the interfacial thermal conductivity coefficient in the digital twin model is adjusted so that the deviation between the shape of the simulated pressure curve and the measured pressure curve during the pressure holding stage and / or cooling stage is within a preset allowable range.
7. The method for inverting cavity temperature based on measured pressure and digital twin model according to any one of claims 1-4, characterized in that, The cavity temperature inversion method also includes an anomaly early warning step: The system monitors the pressure changes of the measured pressure curve and the temperature fluctuations of the inverted melt temperature curve during the injection molding process in real time. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold within a unit time, or when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold within a predetermined time period, an early warning signal is generated to provide an abnormality reminder.
8. A cavity temperature inversion system based on measured pressure and a digital twin model, characterized in that, include: The pressure sensing module (1) is used to collect the measured pressure curve at a specified point in the mold cavity; The data processing module (2) has a pre-set digital twin simulation model corresponding to the injection molding process. It is used to receive the measured pressure curve and run the digital twin simulation model to obtain the simulated pressure curve. Based on the comparison results between the measured pressure curve and the simulated pressure curve, it adjusts one or more core injection parameters in the digital twin simulation model to complete the calibration and extracts the melt temperature curve output by the digital twin simulation model after calibration. The human-computer interaction module (3) is used to synchronously output the measured pressure curve and the inverted melt temperature curve; The pressure sensing module (1) and the human-computer interaction module (3) are both connected to the data processing module (2).
9. The cavity temperature inversion system based on measured pressure and digital twin model according to claim 8, characterized in that, The data processing module (2) includes: The pressure comparison submodule (21) is used to receive the measured pressure curve transmitted by the pressure sensing module (1), compare it with the simulated pressure curve generated by the digital twin simulation model, and determine whether the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range. The parameter calibration submodule (22) is used to adjust the core injection molding parameters in the digital twin simulation model according to the comparison results output by the pressure comparison submodule (21) until the deviation between the measured pressure curve and the simulated pressure curve is within the preset allowable range. The core injection molding parameters include at least rheological parameters, material PVT parameters and interfacial thermal conductivity coefficient. The temperature inversion submodule (23) is used to extract the melt temperature curve obtained by the digital twin simulation model at this time after the parameter calibration submodule (22) completes the calibration, and use it as the inversion result of the melt temperature at this point in the actual injection molding process, and transmit it synchronously to the human-computer interaction module (3) for output.
10. The cavity temperature inversion system based on measured pressure and digital twin model according to claim 9, characterized in that, The data processing module (2) further includes: The abnormal warning submodule (24) is used to monitor the pressure change of the measured pressure curve and the temperature fluctuation of the melt temperature curve obtained by inversion in real time. When the pressure rise gradient of the measured pressure curve exceeds the preset pressure gradient threshold in a unit time, or when the fluctuation amplitude of the melt temperature curve exceeds the preset temperature fluctuation amplitude threshold in a predetermined time period, an early warning signal is generated and transmitted to the human-machine interaction module (3) for abnormal reminder.