Dynamic equivalent temperature control system for improving hot gas bulging forming performance of high-strength steel

Abstract

The invention discloses a dynamic equivalent temperature control system for improving hot gas bulging forming performance of high-strength steel, which comprises a main control unit, a dynamic equivalent temperature model is operated by the main control unit, and the model can calculate the equivalent temperature of a comprehensive thermal deformation effect through acquired data; the dynamic prediction and compensation module is used for comparing the equivalent temperature with a preset ideal curve and generating an instruction through a prediction control algorithm; the multi-area independent temperature control heating module executes the instruction to dynamically regulate and control heating and cooling, so that the equivalent temperature tracks an ideal curve in real time; according to the method, a dynamic equivalent temperature integrating multiple physical field parameters such as heat, force and deformation history is introduced as a controlled variable, so that a control system can more truly reflect an instantaneous softening state and plastic potential of a material under a complex thermal-mechanical coupling condition, and a stable forming window of the high-strength steel is expanded; and the ultimate deformability of the material is greatly improved on the premise of ensuring no rupture.

Description

Technical Field

[0001] This invention relates to the field of thermoplastic deformation technology of metals, and in particular to a dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel. Background Technology

[0002] Hot gas expansion forming is a process that combines internal air pressure expansion with axial feeding and forming at high temperature. Currently, the temperature control of this process mostly adopts a control method based on a preset temperature-time curve, or is supplemented by PID feedback control based on the actual temperature measurement of the tube blank surface. These methods usually take the set temperature of the heating system or the measured surface temperature of the tube blank as the only controlled variable, so that the forming process proceeds along a preset thermal path.

[0003] In the aforementioned traditional methods, the plastic flow, deformation resistance, and final microstructure evolution of high-strength steel during hot gas expansion forming are not solely determined by temperature in the thermal field. Rather, they are the result of strong coupling effects of multiple physical fields, including heat (temperature), force (internal air pressure, axial force), and deformation (strain, strain rate). Controlling only the surface temperature cannot reflect the influence of mechanical conditions such as internal air pressure changes and strain rate fluctuations on the actual softening state of the material, resulting in a narrow process window and making it difficult to simultaneously achieve products with high formability and low springback. Traditional PID control has a lag and cannot proactively and predictively adjust for sudden temperature changes caused by drastic deformation. Different regions of the billet experience different strain histories during deformation, resulting in significant differences in their thermodynamic states. Existing homogenization or simple zonal temperature control strategies are insufficient for targeted local adjustments, easily leading to problems such as localized thinning, wrinkling, or uneven performance in the finished product.

[0004] Therefore, in response to the problems mentioned above, this invention proposes a dynamic equivalent temperature control system to improve the hot gas expansion forming performance of high-strength steel. Summary of the Invention

[0005] To overcome the problems of existing methods failing to consider multi-field coupling effects, having lag in control response, lacking predictability, and being unable to meet the local changes during deformation, this invention proposes a dynamic equivalent temperature control system to improve the hot gas expansion forming performance of high-strength steel. By constructing an equivalent temperature that integrates multiple physical field parameters as a new controlled variable, and using a model predictive control algorithm, the equivalent temperature is made to track a preset ideal trajectory, thereby achieving active and optimized control of the material forming performance.

[0006] The technical solution of this invention is: a dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel, comprising: The main control unit runs a dynamic equivalent temperature model, which is a hybrid model based on physical mechanisms and data-driven approaches. Its input variables include at least the actual billet surface temperature collected in real time by the sensor module. Internal air pressure of the tube blank Axial feed displacement With the real-time strain rate of the tube blank The output of this dynamic equivalent temperature model is the equivalent temperature. The equivalent temperature It is a virtual parameter that integrates the coupling effects of heat, force, and deformation history, and its mathematical expression is: ; in, , The material-related coupling coefficients are pre-calibrated using a high-strength steel material property database. and For reference pressure and reference strain rate, For the Mises equivalent stress calculated based on real-time data, The main control unit calculates the real-time equivalent temperature by integrating over time t. With a preset ideal equivalent temperature curve corresponding to the optimal plasticity and resilience of high-strength steel. The comparison is performed, with the material properties database stored in the main control unit. It contains the rheological stress curves, plastic strain ratios and thermophysical property parameters of high-strength steel at different temperatures and strain rates. The multi-zone independent temperature-controlled heating module, electrically connected to the main control unit, includes a ring heater array, which is divided into N independently controlled heating rings along the tube blank axis, where N≥3; N high-frequency pulse power supplies, each electrically connected to one of the N heating rings, are used to receive adjustment commands from the main control unit and output pulse currents with adjustable duty cycles to the corresponding heating rings; and a cooling medium injection unit, integrated into the ring heater array, is used to inject atomized cooling medium into designated rings when rapid cooling is required. The sensor module, electrically connected to the main control unit, includes multiple non-contact infrared thermometers that are aligned at a specific angle with the surface of the tube blank to measure the actual surface temperature of the tube blank. A pressure sensor, installed on the air inlet pipe of the air-expanding forming equipment, is used to measure the internal air pressure of the tube blank. Laser displacement sensor, used to measure axial feed displacement. One or more optical strain measurement units are used to calculate the real-time strain rate of the tube blank in real time using digital image correlation. ; The dynamic prediction and compensation module is integrated into the main control unit. The dynamic prediction and compensation module, based on... and The deviation and its changing trend are analyzed using a predictive control algorithm to generate adjustment commands and send them to multi-zone independent temperature control heating modules. This enables closed-loop control of the forming zone temperature, ensuring the equivalent temperature throughout the forming process remains constant. Dynamically track the ideal equivalent temperature curve ; The main control unit automatically switches to the pressure holding and gradient cooling module after detecting the end of the air expansion forming stage. Based on the geometry of the final formed part, this module applies a gradient cooling strategy to different areas of the tube blank through a multi-region independent temperature control heating module. The cooling rate of the non-molded area is controlled to be higher than that of the molded area, so as to coordinate the residual stress distribution in different areas. Human-computer interaction interface for displaying real-time equivalent temperature Ideal equivalent temperature curve The system displays data from various sensors and its status, and allows operators to manually adjust the ideal equivalent temperature curve. or coupling coefficient , .

[0007] Preferably, the predictive control algorithm used in the dynamic prediction and compensation module is a constrained model predictive control algorithm, and its optimization objective function J is to minimize the equivalent temperature in the next prediction time domain. The predicted value and The deviation is considered, and the power change rate of the multi-zone independent temperature control heating module and the flow rate of the cooling medium are taken as constraints. The optimization objective function J is formulated as follows: ; Where t represents the current time; This indicates the prediction time domain, i.e., the future time step considered in the optimization problem; This represents the control time domain, specifically the future time step in which control commands change. ≤ ; In the future The predicted equivalent temperature at time t is derived by the dynamic equivalent temperature model based on historical data and future hypothetical control inputs. In the future Ideal equivalent temperature setpoint at any given time; This represents a control vector, whose elements include, but are not limited to: future... The heating power vector applied to the N heating rings at any given time The cooling medium flow vector of the cooling medium injection unit ; = - This represents the change in the control vector between adjacent time points, i.e., the intensity of the control action; Q and R are weight matrices, where Q is a positive definite or semi-positive definite matrix used to penalize the tracking error of the equivalent temperature on the ideal trajectory; R is a positive definite matrix used to penalize excessively large or too frequent control actions.

[0008] Preferably, the cooling medium is a mixture of atomized deionized water and compressed air, and its injection flow rate and duration are directly controlled by the dynamic prediction and compensation module.

[0009] Preferably, the equivalent temperature The calculation period is no more than 100 milliseconds.

[0010] Preferably, the ideal equivalent temperature curve It is set to rapidly rise to a peak value in the initial stage of forming to promote material softening; to slowly decrease in the main deformation stage to maintain high plasticity and control grain growth; and to rise slightly again at the end of forming to suppress springback.

[0011] The beneficial effects of this invention are: 1. This invention introduces a dynamic equivalent temperature that integrates multiple physical field parameters such as heat, force, and deformation history as the controlled variable, enabling the control system to more realistically reflect the instantaneous softening state and plastic potential of the material under complex thermo-mechanical coupling conditions. This expands the stable forming window of high-strength steel and significantly improves the material's ultimate deformation capability without causing cracking, thus achieving deeper and more complex structure forming.

[0012] 2. This invention employs a dynamic prediction and compensation module based on a constrained model predictive control algorithm. This module can predict the change trend of the equivalent temperature over a future period based on real-time process data and calculate the optimal control command sequence in advance. This proactively suppresses temperature fluctuations caused by sudden changes in deformation conditions, thereby significantly improving the timeliness and stability of control.

[0013] 3. By leveraging the synergistic effect of multi-region independent temperature-controlled heating modules and dynamic equivalent temperature models, this invention can sense and respond to the different thermodynamic demands of different axial rings of the tube blank due to their different strain histories, thereby adjusting specific regions to effectively balance material flow, significantly reduce or eliminate local thinning and wrinkling tendencies, and ensure a more uniform wall thickness distribution of the formed parts. Attached Figure Description

[0014] Figure 1 The diagram shown is a schematic representation of the system framework of the present invention. Figure 2 The diagram shown illustrates the workflow of this invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Please see Figure 1 This invention provides an embodiment of a dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel: In this embodiment, the main control unit is described as follows: The main control unit runs a dynamic equivalent temperature model, which is a hybrid model based on physical mechanisms and data-driven approaches. The model is as follows: ; in, The actual surface temperature of the tube blank is collected in real time by a non-contact infrared thermometer in the multi-sensor information fusion subsystem.

[0017] The internal air pressure of the tube blank is collected by a high-precision pressure sensor. For reference pressure, the initial expansion pressure is set to 1 MPa in this embodiment. The purpose is to make the logarithmic term zero in the initial stage and to normalize the influence of the pressure dimension.

[0018] The real-time strain rate of the tube blank is calculated by an optical strain measurement unit (e.g., a high-speed camera system based on digital image correlation (DIC) technology) by analyzing the temporal changes of speckle images on the tube blank surface. The reference strain rate is set to 0.01 / s, which is a typical value for quasi-static forming and is used for normalization.

[0019] The axial feed displacement is measured by a laser displacement sensor, and its derivative is the axial feed speed.

[0020] The Mises equivalent stress is an intermediate calculation variable. In this embodiment, it is calculated by querying the flow stress curves of the high-strength steel at different temperatures and strain rates pre-stored in the material property database, combined with real-time measurements. and The result is obtained through interpolation calculation.

[0021] , , These are the material coupling coefficients. These three coefficients need to be calibrated through prior material testing. For example, for 22MnB5 high-strength steel, through a series of thermal simulation tests at different temperatures, strain rates, and stress states, and by fitting the experimental data using a multivariate nonlinear regression algorithm, the following coefficients can be calibrated: =12.5, =-8.2, =0.00015. The sign of the coefficient reflects whether the parameter's "contribution" to the equivalent temperature is positive or negative; for example, negative... The value indicates that the equivalent temperature decreases as the strain rate increases. This is the opposite of the temperature rise effect that may occur in materials under high strain rates. It focuses more on reflecting the increased difficulty of plastic forming caused by the strain rate strengthening effect, which needs to be compensated by equivalent cooling.

[0022] Integral term The mechanical work used to accumulate during the forming process reflects the influence of deformation history on the internal energy state of the material. (displacement) and The product of stresses approximates the power, while the integral over time represents the accumulated deformation energy.

[0023] In this embodiment, the multi-zone independent temperature control heating module is described as follows: In this embodiment, the heater is divided into 5 (N=5) independent heating rings along the tube blank axis. Each ring is composed of a high-frequency induction coil or a resistance heating strip, and its energy output can be controlled independently.

[0024] In this embodiment, each heating ring is equipped with an independent solid-state high-frequency induction power supply or pulse resistance heating power supply. The main control unit sends 0-10V analog signals or PWM signals to these power supplies to control their output power, with a power adjustment range of 0-30kW.

[0025] In this embodiment, a ring of micro-nozzles is integrated on the inner side of each heating ring for spraying atomized cooling medium (a mixture of deionized water and compressed air is used in this embodiment). The flow rate of the mixed gas is controlled by a proportional valve to achieve different intensities of cooling control, from slight cooling to rapid quenching.

[0026] In this embodiment, the sensor module is described as follows: Five non-contact infrared thermometers (corresponding to the heating rings) with response wavelengths of 2.0-2.5μm are selected to avoid measurement errors caused by changes in the emissivity of objects at high temperatures. The measurement accuracy is ±1.5℃, and the sampling frequency is 100Hz. A pressure sensor is installed on the pipeline at the intensifier outlet, with a range of 0-50MPa and an accuracy of ±0.1%FS. A laser displacement sensor is used to measure the displacement of the axial propulsion mechanism, with an accuracy of ±0.01mm. The optical strain measurement unit uses a stereo DIC system composed of two high-speed cameras, with a frame rate of no less than 200fps. By processing images in real time, the strain rate of the maximum principal strain zone on the tube blank surface is calculated. .

[0027] In this embodiment, the dynamic prediction and compensation module is described as follows: The objective function J for this module is: ; Where t represents the current time; This represents the prediction time domain, i.e., the future time step considered in the optimization problem. It is set to 10 steps, corresponding to an actual time of 1.0 second (assuming the control period is 100ms). This represents the control time domain, specifically the future time step in which control commands change. ≤ Set to 5 steps, or 0.5 seconds; In the future The predicted equivalent temperature at time t is derived by the dynamic equivalent temperature model based on historical data and future hypothetical control inputs. In the future Ideal equivalent temperature setpoint at any given time; This represents the control vector, which contains the heating power vectors of the five heating rings. ], and the cooling medium flow vector of the 5 cooling medium injection units [ There are 10 variables in total. = - This represents the change in the control vector between adjacent time points, i.e., the intensity of the control action; Q and R are weight matrices, where Q is a positive definite or semi-positive definite matrix used to penalize the tracking error of the equivalent temperature on the ideal trajectory; R is a positive definite matrix used to penalize excessively large or too frequent control actions.

[0028] The constraints are as follows: the upper and lower limits of heating power are 0-30KW, the upper and lower limits of cooling flow rate are 0-20L / min, the power change rate is limited to -5-5KW / step, and the flow rate change rate is limited to -5-5(L / min) / step.

[0029] Within each control cycle (100ms), the main control unit solves the constrained optimization problem and sends the first calculated control command to the heating and cooling device.

[0030] In this embodiment, the ideal equivalent temperature curve is the target set by the process, and is pre-determined based on the material property database and process experiments. For 22MnB5 steel, its The curve is as follows: Phase 1 (Heating and Initial Deformation, 0-10s): Rapidly increase from the initial temperature of 850℃ to the peak temperature of 880℃. The high temperature in this phase is used to fully soften the material, thus facilitating initial deformation.

[0031] Stage 2 (Stable forming, 10-25s): The temperature is slowly and linearly reduced from 880℃ to 860℃. The slow cooling helps maintain sufficient plasticity to complete the large deformation while inhibiting excessive growth of austenite grains.

[0032] Stage 3 (Final Forming and Holding Pressure, 25-30s): In the last 2-3 seconds, the temperature rises slightly to 865℃. This step reduces the material's yield stress through a brief temperature recovery, thereby more effectively suppressing springback during the holding pressure stage.

[0033] Please see Figure 2 The present invention provides Embodiment 1: This embodiment illustrates the process of fabricating an S-shaped bent pipe fitting from a 22MnB5 high-strength boron steel tube blank with dimensions of φ60mm×2mm×200mm.

[0034] (1) Before starting, the operator selects and loads the corresponding process formula for the 22MnB5 high-strength steel S-shaped bending pipe fitting to be processed through the human-machine interface. The formula includes basic parameters such as the initial heating temperature of the pipe blank of 850℃, the target maximum bulging pressure of 20MPa, and the total axial feed of 30mm, as well as the ideal equivalent temperature curve optimized in advance according to the material property database. The curve specifies a three-stage temperature profile: in the initial forming stage (0-10 seconds), the temperature rapidly increases from 850°C to 880°C; in the stable forming stage (10-25 seconds), the temperature slowly and linearly decreases from 880°C to 860°C; and in the final forming and holding stage (25-30 seconds), the temperature rises slightly back to 865°C. This serves as the benchmark for dynamic tracking of the entire forming process.

[0035] (2) After the system starts, the multi-zone independent temperature control heating module starts working first. The main control unit adjusts the power output of the five axial heating rings to a stable state through PID control according to the preset initial temperature curve, so that the stationary tube blank is uniformly heated and stabilized at the initial temperature of 850℃. At the same time, the sensor module starts running and feeds back the surface temperature of each zone. Ensure all sensor readings are normal and the initial thermal state of the tube blank meets the conditions for initiating gas expansion forming. At this point, the internal gas pressure of the tube blank is... Zero, axial feed displacement Zero, real-time strain rate It is also zero, so the dynamic equivalent temperature is zero. The initial calculated value is equal to the surface temperature. The measured value.

[0036] (3) When the axial feed and internal pressurization program is started, the laser displacement sensor in the sensor module captures the axial feed displacement in real time. The pressure sensor monitors the change in air pressure inside the tube. The optical strain measurement unit analyzes the surface image of the tube blank using DIC technology to calculate the real-time strain rate of the key areas, based on the rising curve. All of this data, along with the surface temperature measured by the infrared thermometer, The data is synchronously fed into the main control unit, where it is calculated by the dynamic equivalent temperature model, and the equivalent temperature reflecting the thermo-mechanical-deformation coupling effect is output in real time. Its value, due to the addition of the pressure and strain rate terms, begins to correlate with the simple surface temperature. Differences arise.

[0037] (4) The dynamic prediction and compensation module in the main control unit will calculate the equivalent temperature in real time within each 100-millisecond control cycle. Compared to the ideal curve The current and future values ​​are compared, and an optimization problem is solved based on a constrained model predictive control algorithm. This problem aims to minimize the prediction time domain within the next 1 second. and The prediction deviation is minimized, while the rate of change of heating power and cooling flow rate are limited to a safe range. After solving, the optimal real-time control command sequence is obtained, and the first command is immediately sent to the heating and cooling devices.

[0038] (5) The multi-zone independent temperature control heating module receives and executes adjustment commands from the main control unit. For example, when the system predicts the strain rate of the outer region of the S-shaped pipe bend, the module will adjust the temperature control accordingly. Sudden increase leading to equivalent temperature There are lower When the trend is observed, the output power of the corresponding high-frequency pulse power supply is immediately increased for heat compensation. When the system calculates the effect of air pressure... Peak arrival leads to More than In case of risk, the corresponding ring's cooling medium injection valve will be opened for atomized cooling. Through the combined action of the five independent heating and cooling actions of the five rings, the equivalent temperature field of the entire tube blank is dynamically and stably tracked by the preset value. curve.

[0039] (6) During the forming process, if an abnormal increase in local strain rate occurs due to fluctuations in material properties or changes in friction conditions, the dynamic equivalent temperature model will quickly detect it. The terms and integral terms sense this change and calculate the equivalent temperature of the local region. If the target is being deviated from, the dynamic prediction and compensation module will adjust the control strategy of the relevant ring zone in advance. This will not only increase the energy input of the region, but may also coordinate the temperature field of its adjacent ring zones to form a "thermal field" that guides the flow of materials. This will adaptively avoid local over-thinning or wrinkling and eliminate potential defects in their infancy.

[0040] (7) When the forming process enters the final stage, and the main control unit detects that the axial feed is about to be completed and the air pressure enters the pressure holding state, the system strictly follows the instructions. The command at the end of the curve controls the relevant ring belt to perform a small-amplitude heating operation. This operation uses a dynamic equivalent temperature model to allow the material to undergo final molding and stress relaxation in a low yield stress state, thereby actively suppressing the springback of the part after unloading and ensuring that the S-shaped bending tube can obtain a high-precision final geometric surface.

[0041] (8) When the pressure holding stage ends, the main control unit confirms that the entire hot gas expansion forming cycle is completed. First, it shuts down the internal air pressure source and the axial feed mechanism, and then controls the heating module to stop heating and starts the cooling module to cool the mold and pipe.

[0042] This invention provides Embodiment 2: This embodiment illustrates the process of fabricating an asymmetrical pipe fitting with a boss from a 22MnB5 high-strength boron steel tube blank with dimensions of φ60mm×2mm×200mm.

[0043] The initial temperature is set to 840℃, the maximum expansion pressure is 25MPa, and the axial feed is controlled by a variable speed. The curve was adjusted according to the characteristics of asymmetric deformation, and a lower temperature was set during the boss forming stage to control the thinning.

[0044] The difficulty in forming this part lies in the severe localized thinning in the boss area. In the system of this invention, the DIC system monitors the strain rate in the boss area. The abnormally high level caused localized [effects] in the area. When the calculated value is too low, the dynamic prediction and compensation module recognizes this situation and not only increases the heating power of the ring but also reduces the power of adjacent rings, forming a local "thermal field" that guides the material to flow towards the protrusion region. At the same time, the integral term accumulates the deformation energy of this region. When the accumulated energy reaches a certain threshold, the model will slightly improve. The design promotes material softening, and together they effectively control localized thinning.

[0045] This invention provides comparative examples: This comparative example uses the same S-shaped pipe mold and pipe blank as Example 1, and performs the forming operation using Comparative Example 1 and Comparative Example 2, wherein: Comparative Example 1 uses traditional PID temperature control with independent temperature control in 5 zones, but the control objective is to make each zone... Follow a preset and with Traditional temperature curves with similar shapes.

[0046] Comparative Example 2 uses a preset and fixed heating power curve and cooling timing, without any real-time feedback.

[0047] After the forming process is completed, the parts obtained in the above embodiments and comparative examples are tested, and the indicators are shown in Table 1.

[0048] Table 1 Comparative Example 1: Due to PID control, air pressure cannot be sensed. and strain rate The system blindly maintains the surface temperature even when these parameters fluctuate. This causes the actual softening state of the material to deviate from the ideal state. For example, under high strain rates, the material is difficult to deform, but it is still kept at high temperature, which may lead to coarse grains or local overheating. Under high pressure, the material is actually easier to deform, but the temperature is not adjusted accordingly, which may cause excessive thinning. In the end, the uniformity of the wall thickness and the springback control of the formed part are not as good as in Example 1.

[0049] Comparative Example 2 is unable to cope with minor fluctuations in the geometry and friction conditions of the tube blank, resulting in an extremely unstable forming process. Either insufficient energy leads to premature breakage in non-target areas, or excessive energy causes severe thinning of the mold area, resulting in extremely low part forming consistency and pass rate.

[0050] Table 2 As shown in Table 2, Examples 1 and 2 are superior to the comparative example in terms of minimum wall thickness and wall thickness uniformity. This indicates that the dynamic equivalent temperature model is effective for local strain rates. The response and multi-regional coordinated control of MPC can proactively guide the material flow to high-risk areas, avoiding excessive local thinning.

[0051] As can be seen from the table above, the springback of the molded part of the present invention is much smaller than that of the comparative example, indicating that... Temperature recovery strategy and equivalent temperature in the final segment of the curve The consideration of the entire deformation history (integral term) is very effective, allowing the stress state of the material to be better relaxed at the end of the forming process.

[0052] As can be seen from the table above, the boss filling in Example 2 is fuller, and the finer grain size indicates that the dynamic temperature control strategy of the present invention can effectively suppress grain growth at high temperatures. The failure of Comparative Example 2 illustrates the importance of feedback and predictive control. Compared with Comparative Example 1, which only controls the surface temperature, the present invention, through the control of the equivalent temperature, shows stronger anti-interference ability and robustness.

[0053] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel, characterized in that, Including: The main control unit runs a dynamic equivalent temperature model, which is a hybrid model based on physical mechanisms and data-driven approaches. Its input variables include at least the actual billet surface temperature collected in real time by the sensor module. Internal air pressure of the tube blank Axial feed displacement With the real-time strain rate of the tube blank The output of this dynamic equivalent temperature model is the equivalent temperature. The equivalent temperature It is a virtual parameter that integrates the coupling effects of heat, force, and deformation history, and its mathematical expression is: in, , The material-related coupling coefficients are pre-calibrated using a high-strength steel material property database. and For reference pressure and reference strain rate, For the Mises equivalent stress calculated based on real-time data, The main control unit calculates the real-time equivalent temperature by integrating over time t. With a preset ideal equivalent temperature curve corresponding to the optimal plasticity and resilience of high-strength steel. Compare; A multi-zone independent temperature control heating module, electrically connected to the main control unit, is used to heat high-strength steel; The sensor module, electrically connected to the main control unit, is used to collect multi-physics field data in real time during the forming process; The dynamic prediction and compensation module is integrated into the main control unit. The dynamic prediction and compensation module, based on... and The deviation and its changing trend are analyzed using a predictive control algorithm to generate adjustment commands and send them to multi-zone independent temperature control heating modules. This enables closed-loop control of the forming zone temperature, ensuring the equivalent temperature throughout the forming process remains constant. Dynamically track the ideal equivalent temperature curve .

2. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that, The multi-zone independent temperature control heating module includes: A ring heater array, which is divided into N independently controlled heating rings along the tube blank axis, where N≥3; N high-frequency pulse power supplies are electrically connected to N heating rings one by one, and are used to receive adjustment commands from the main control unit and output pulse currents with adjustable duty cycles to the corresponding heating rings. The cooling medium injection unit, integrated into the annular heater array, is used to inject atomized cooling medium into a designated annular zone when rapid cooling is required.

3. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that, The sensor module includes: Multiple non-contact infrared thermometers are aimed at the surface of the tube blank at a specific angle to measure the actual surface temperature of the tube blank. ; A pressure sensor, installed on the air inlet pipe of the air forming equipment, is used to measure the air pressure inside the tube blank. ; Laser displacement sensor, used to measure axial feed displacement. ; One or more optical strain measurement units are used to calculate the real-time strain rate of the tube blank in real time using digital image correlation. .

4. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The dynamic prediction and compensation module employs a constrained model predictive control algorithm, whose objective function J is to minimize the equivalent temperature in the next prediction time domain. The predicted value and The deviation is considered, and the power change rate of the multi-zone independent temperature control heating module and the flow rate of the cooling medium are taken as constraints. The optimization objective function J is formulated as follows: Where t represents the current time; This indicates the prediction time domain, i.e., the future time step considered in the optimization problem; This represents the control time domain, specifically the future time step in which control commands change. ≤ ; In the future The predicted equivalent temperature at time t is derived by the dynamic equivalent temperature model based on historical data and future hypothetical control inputs. In the future The ideal equivalent temperature setpoint at any given time; This represents the control vector, whose elements include, but are not limited to: future... The heating power vector applied to the N heating rings at any given time The cooling medium flow vector of the cooling medium injection unit ; = - This represents the change in the control vector between adjacent time points, i.e., the intensity of the control action; Q and R are weight matrices, where Q is a positive definite or semi-positive definite matrix used to penalize the tracking error of the equivalent temperature on the ideal trajectory; R is a positive definite matrix used to penalize excessively large or too frequent control actions.

5. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The system also includes a pressure holding and gradient cooling module. After the main control unit detects that the gas expansion forming stage has ended, it automatically switches to this module. Based on the geometry of the final formed part, this module applies a gradient cooling strategy to different areas of the tube blank through a multi-region independent temperature control heating module. The cooling rate of the non-molded area is controlled to be higher than that of the molded area, so as to coordinate the residual stress distribution in different areas.

6. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The material property database is stored within the main control unit and includes the rheological stress curves, plastic strain ratios, and thermophysical property parameters of high-strength steel at different temperatures and strain rates. The coupling coefficient... , This was obtained by fitting experimental data from the database.

7. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The system also includes a human-machine interface for displaying real-time equivalent temperature. Ideal equivalent temperature curve The system displays data from various sensors and its status, and allows operators to manually adjust the ideal equivalent temperature curve. or coupling coefficient , .

8. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 2, characterized in that: The cooling medium is a mixture of atomized deionized water and compressed air, and its injection flow rate and duration are directly controlled by a dynamic prediction and compensation module.

9. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The equivalent temperature The calculation period is no more than 100 milliseconds.

10. The dynamic equivalent temperature control system for improving the hot gas expansion forming performance of high-strength steel according to claim 1, characterized in that: The ideal equivalent temperature curve It is set to rapidly rise to a peak value in the initial stage of forming to promote material softening; to slowly decrease in the main deformation stage to maintain high plasticity and control grain growth; and to rise slightly again at the end of forming to suppress springback.

Images