Intelligent forging cooperative control system for strain clamp

Abstract

The invention relates to the technical field of forging control, in particular to an intelligent forging cooperative control system for a strain clamp, which is characterized in that full-band coupling analysis is carried out on acoustic signals of forgings through an acoustic multi-mode sensing module, and a material grain boundary slip characteristic quantity and a three-dimensional temperature field distribution map are synchronously generated; the local distortion of the temperature field is corrected by using the spatial distribution rule of the slip characteristic quantity; the phase change pre-judgment decision-making module converts the corrected temperature field into a thermal activation energy field, a grain boundary dynamic recombination response network is constructed by coupling the grain boundary slip characteristic quantity, and a pressure peak floating threshold value and a temperature maintaining window which are adaptively adjusted along with the phase change state are output; the cross-domain cooperative execution module constructs a double-rail driving mechanism in a forging loop, a main driving rail plans a forging hammer stroke curve based on a pressure peak floating threshold value, and an auxiliary feedback rail converts a grain boundary slip characteristic quantity into a dynamic correction factor to adjust an impact energy gradient; a window self-adaptive strategy is implemented in a temperature loop, and efficient focusing of energy in a superplastic deformation area is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forging control, in particular to an intelligent forging collaborative control system for strain clamp. BACKGROUND

[0002] The current strain clamp forging process has room for improvement in real-time monitoring and process control of the temperature field, including:

[0003] On the one hand, widely used contact sensors such as thermocouples may be limited by the density of the points and the local physical property changes of the material when reflecting the internal temperature distribution of complex-shaped forgings. There is a certain delay or incompleteness in the response to local temperature distortion caused by grain boundary sliding or material heterogeneity. The integrity and accuracy of the temperature field reconstruction are challenged.

[0004] On the other hand, the existing control system is not perfect in terms of collaborative sensing and control mechanism of the dynamic correlation between the internal micro-deformation state of the material (such as grain boundary sliding state) and the macro forging process parameters (such as pressure, temperature). This may lead to inaccurate identification of the key trigger time and required energy window of superplastic phase transition, and the adaptability of forging force or the distribution of temperature field cannot match the dynamic changes of the material in real time. This sensing deviation and lag in process parameters affect the uniformity of the grain boundary reorganization process of the forgings to some extent, and may affect the structural consistency and service reliability of the final product. SUMMARY

[0005] The present application aims to provide an intelligent forging collaborative control system for strain clamp to solve the problems raised in the background art. The specific technology includes how to accurately reconstruct the internal three-dimensional temperature field of the forgings and eliminate local measurement distortion to solve the temperature field distortion problem caused by material heterogeneity, and how to establish a control mechanism of grain boundary dynamic evolution and forging parameters to solve the timing prediction and energy regulation inaccuracy of superplastic phase transition triggering.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] The intelligent forging collaborative control system for strain clamp includes an acoustic multi-modal sensing module, a phase transition prediction decision module, and a cross-domain collaborative execution module, wherein:

[0008] The acoustic multimodal perception module achieves collaborative perception by analyzing the acoustic scattering signal through full-band coupling. Based on the Doppler frequency shift phenomenon of acoustic waves in the high-temperature material of the forging, it analyzes the acoustic frequency offset at different spatial positions to reconstruct the three-dimensional temperature field distribution map, solving the problem of visualizing the spatial distribution of the macroscopic temperature field. Based on the abnormal attenuation characteristics of acoustic wave energy at the grain boundaries of the material, it extracts the characteristic components related to lattice distortion in the acoustic wave attenuation spectrum to generate the material grain boundary slip characteristic quantity, realizing the quantitative characterization of the microscopic deformation state.

[0009] The acoustic multimodal perception module utilizes the spatial distribution law of the material's grain boundary slip characteristic quantity, that is, the high-value area of ​​the characteristic quantity corresponds to the active area of ​​local deformation of the material, and dynamically corrects the local distortion in the three-dimensional temperature field distribution map. By automatically calibrating the temperature measurement distortion area and using an interpolation algorithm to eliminate the temperature field measurement deviation caused by local material heterogeneity, the temperature field reconstruction accuracy is significantly improved, providing a reliable data basis for phase change prediction.

[0010] The phase change prediction and decision module converts the corrected three-dimensional temperature field distribution map into a thermal activation energy field. By extracting the temperature gradient value of each spatial coordinate point, it calculates the activation energy distribution required for atomic migration per unit volume based on the material phase change kinetic model and establishes a mapping relationship between the temperature field and the material phase change energy.

[0011] The phase transformation prediction decision module couples the material grain boundary slip characteristic quantity to construct a grain boundary dynamic reorganization response network. When the thermal activation energy field value enters the critical interval and the growth rate of the material grain boundary slip characteristic quantity exceeds the set slope, it is judged as a precursor to superplastic phase transformation triggering. The pressure peak floating threshold is dynamically calculated according to the phase transformation triggering precursor timing, and the threshold is adaptively adjusted with the migration of the thermal activation energy field peak coordinate to ensure that the forging intensity matches the material phase transformation state in real time; the temperature maintenance window boundary is set based on the thermal activation energy value of the material grain boundary slip active zone, and the window action duration is dynamically adjusted in conjunction with the slip acceleration to form a precise temperature control strategy synchronized with the grain boundary evolution.

[0012] The cross-domain collaborative execution module establishes a dual-loop dynamic control mechanism. In the forging control loop, the dual-track drive unit in the cross-domain collaborative execution module plans the forging hammer stroke curve using the pressure peak floating threshold as the target benchmark through the main drive track. The pressure peak floating threshold is converted into the forging hammer downward displacement sequence by using the material constitutive equation, and the maximum stroke acceleration constraint is set to ensure the stability of the forging hammer's kinetic energy output.

[0013] The double-track driving unit converts the material grain boundary sliding characteristic quantity into a dynamic correction factor through a secondary feedback track: a difference operation is performed on the grain boundary sliding characteristic quantity to obtain a sliding acceleration variable; when the sliding acceleration exceeds a preset sliding acceleration change rate threshold, a forging hammer impact energy gradient compensation coefficient is generated; the sliding acceleration change rate threshold is calculated based on a material characteristic database, historical forging data and a superplastic phase transition tolerance model; the forging hammer impact energy gradient compensation coefficient is dynamically superimposed on the forging hammer stroke curve to real-time increase the forging hammer impact energy intensity to suppress the unstable state of grain boundary sliding.

[0014] In the temperature control loop, the coil power initial value is set with the temperature maintenance window as the energy distribution base; the window adjustment unit in the cross-domain collaborative execution module adjusts the window boundary in real time according to the sliding trend of the material grain boundary sliding characteristic quantity; when the sliding acceleration variable is continuously positive and its change rate exceeds the preset sliding acceleration change rate threshold, the temperature value boundary compression strategy is triggered, and the upper limit value of the window temperature is reduced by a preset compression ratio to accelerate the energy aggregation in the phase transition zone;

[0015] When it is monitored that the spatial distribution density of the sliding active zone coordinates is greater than a preset regional coverage density threshold, the window core scope contraction strategy is triggered, and the original window action coverage area is contracted and focused to the high-density coordinate set of the sliding active zone, so that the dynamic focusing of the energy density of the superplastic deformation zone is finally realized, and the grain boundary recombination efficiency is improved.

[0016] Compared with the prior art, the beneficial effects of the present application are:

[0017] Through acoustic multi-modal perception, the forging temperature field and grain boundary sliding are cooperatively analyzed, and the measurement deviation caused by local heterogeneity is eliminated; based on the dynamic coupling mechanism of the thermal activation energy field and the grain boundary sliding characteristics, the superplastic phase transition trigger timing and the pressure / temperature control threshold are accurately predicted; by using the double-track driving and window adaptive strategy, the cross-domain collaborative control of forging energy and temperature field is realized, and the grain boundary recombination uniformity is improved; finally, the superplastic deformation efficiency of the forging is optimized while avoiding local overburning, the fatigue life of the strain clamp is prolonged, and core control support is provided for intelligent manufacturing of power fittings. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The figure is a schematic diagram of the overall module of the present application;

[0019] Figure 2 The figure is a schematic diagram of the cross-domain collaborative execution module unit of the present application.

[0020] In the figure: 100, acoustic multi-modal perception module; 200, phase transition prediction decision module; 300, cross-domain collaborative execution module; 301, double-track driving unit; 302, window adjustment unit. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0022] Next, see Figure 1 The present invention provides a technical solution: a collaborative control system for intelligent forging of tension wire clamps, including an acoustic multimodal perception module 100, a phase change prediction and decision module 200, and a cross-domain collaborative execution module 300.

[0023] The acoustic multimodal sensing module 100 transmits high-frequency sound waves into the forging through a wide-band acoustic wave detector array, collects scattered signals formed after the sound waves propagate inside the material, and performs coupled analytical processing on the collected full-band acoustic wave signals, specifically including:

[0024] Based on the Doppler frequency shift phenomenon produced when sound waves propagate in high-temperature materials, the three-dimensional temperature field distribution map inside the forging is reconstructed by analyzing the sound wave frequency offset at different spatial positions;

[0025] Based on the abnormal attenuation characteristics of acoustic wave energy at the grain boundaries of the material, the characteristic components related to lattice distortion in the acoustic wave attenuation spectrum are extracted to generate the material grain boundary slip characteristic quantity that characterizes the microscopic deformation state;

[0026] The spatial distribution law of the material grain boundary slip characteristic quantity (i.e., the high-value area of ​​the characteristic quantity corresponds to the active area of ​​local deformation of the material) is used to dynamically correct the local distortion in the three-dimensional temperature field distribution map. When the grain boundary slip characteristic quantity shows abnormal fluctuation at a certain spatial coordinate point, it is automatically calibrated as a temperature measurement distortion area; the temperature gradient distribution of the adjacent normal area is mapped to the distortion area through the interpolation algorithm to eliminate the temperature field measurement deviation caused by the local heterogeneity of the material. The process finally outputs the calibrated three-dimensional temperature field distribution map and the material grain boundary slip characteristic quantity that are synchronized in time and space, providing distortion-free multi-physics field perception data for subsequent modules.

[0027] The phase change prediction decision module 200 first converts the corrected three-dimensional temperature field distribution map output by the acoustic multimodal perception module 100 into a thermal activation energy field. Specifically, by extracting the temperature gradient value of each spatial coordinate point in the temperature field, the activation energy distribution required for atomic migration per unit volume is calculated based on the material phase change kinetic model. The grain boundary slip characteristic quantity of the synchronously coupled material is used to construct a grain boundary dynamic reorganization response network, where the thermal activation energy field provides atomic diffusion energy barrier data and the material grain boundary slip characteristic quantity carries dislocation motion rate information. When the thermal activation energy field value enters the critical range and the growth rate of the material grain boundary slip characteristic quantity exceeds the set slope, it is determined to be a precursor to the triggering of superplastic phase change. The phase change extension path is predicted based on the matching relationship between the spatial concentration of the material grain boundary slip characteristic quantity and the gradient direction of the thermal activation energy field, where:

[0028] Dynamically calculate the pressure peak floating threshold according to the phase change trigger precursor time sequence, so that the pressure peak floating threshold can be adaptively adjusted as the peak coordinate of the thermal activation energy field migrates;

[0029] The window boundary is set based on the thermal activation energy value of the active zone of grain boundary slip of the material, and the window action duration is dynamically adjusted in conjunction with the slip acceleration to generate a temperature maintenance window.

[0030] The process by which the phase change prediction and decision module 200 converts the corrected three-dimensional temperature field distribution map into a thermal activation energy field is the core step in the system's understanding of the thermally driven atomic motion state within the material. This process begins with the analysis of the corrected three-dimensional temperature field distribution map. The specific implementation process is as follows:

[0031] First, traverse each spatial coordinate point in the temperature field and accurately extract the temperature gradient value of the point and its adjacent area, which reflects the spatial rate and direction of temperature change inside the material;

[0032] Subsequently, a stored material phase transformation kinetic model specific to the forged tension clamp material (this model includes theoretical frameworks such as diffusion coefficients, activation energy, and the Arrhenius equation) is called up. Based on the quantitative relationships provided by this kinetic model, calculations are performed for each spatial coordinate point (or unit representing the smallest volume element). The core of this model is to consider the atomic migration phenomenon at the microscale as a thermally activated process. The goal of the calculation is to determine the energy barrier—the activation energy—required to overcome lattice constraints and allow atoms to migrate to adjacent locations under the current specific local temperature field and temperature gradient conditions. The result of the calculation is not a single value, but rather a field reflecting the spatial distribution of energy barriers within the entire forging region (forging), that is, the distribution of activation energy required for atomic migration per unit volume. This activation energy distribution field (thermal activation energy field) quantifies the magnitude of the thermodynamic driving force required to complete phase transformation (here, mainly triggering superplasticity) in different regions of the material. It is a key input parameter for predicting the location and timing of phase transformation, providing the most fundamental information on atomic diffusion energy barriers for the subsequent construction of a dynamic reorganization response network for grain boundaries.

[0033] The process of generating the pressure peak floating threshold in the phase transformation prediction decision module 200 is the core decision-making mechanism for predicting the starting point of superplastic phase transformation and setting the optimal forging pressure accordingly. This process is based on the coordinated monitoring of the thermal activation energy field and the material grain boundary slip characteristic quantity. Two key criteria are continuously monitored: first, whether the thermal activation energy field value enters a pre-set or model-calculated critical interval as a whole or locally (this interval represents that the atomic diffusion capacity within the material has approached the theoretical threshold value for achieving large-scale coordinated migration); second, whether the growth rate of the material grain boundary slip characteristic quantity within a specific time window exceeds a set slope threshold (this threshold represents the critical point where grain boundary slip transitions from linear to nonlinear acceleration); if and only if these two conditions are met at the same time, the current state is determined to be a superplastic phase transformation triggering precursor for imminent large-scale superplastic deformation; once the precursor is determined to have appeared, the stage of dynamic calculation of the pressure peak is entered; the core principle of the calculation is that the pressure peak floating threshold must be adaptively adjusted in close accordance with the dynamic process of phase transformation initiation and expansion; the specific method is:

[0034] Track the temporal evolution of the appearance of phase change precursors (i.e., the time sequence of the appearance of precursors and the changes in spatial concentration), and monitor in real time the migration direction of the peak coordinates of the thermal activation energy field, i.e., the change in the position of the region with the highest current activation energy and the most likely to undergo phase change in the material); based on the changing trend of the precursor state over time and the spatial movement trajectory of the energy field peak coordinates, use a preset dynamic decision-making algorithm (which may include feedback control theory or empirical model) to dynamically calculate the optimal, also floating, pressure threshold; its "floating" feature is reflected in the fact that the pressure threshold is not a fixed value, but will change dynamically according to the migration of the phase change core area, aiming to provide the forging process with a pressure benchmark that best matches the current phase change state and position, thereby accurately guiding the forging hammer action to adapt to the phase change-induced material softening zone.

[0035] See also Figure 2 The dual-track drive unit 301 in the cross-domain collaborative execution module 300 constructs a dual-track drive mechanism in the forging control loop, that is, a forging control system consisting of a main / slave dual track, wherein:

[0036] The main drive rail uses the pressure peak floating threshold output by the phase change prediction and decision module 200 as the target benchmark, plans the forging hammer stroke curve according to the real-time deformation resistance map of the forging, and specifically converts the pressure threshold into the forging hammer downward displacement sequence through the material constitutive equation, and sets the maximum stroke acceleration constraint;

[0037] The secondary feedback track converts the material grain boundary slip characteristic quantity continuously input by the acoustic multimodal perception module 100 into a dynamic correction factor. The conversion process includes:

[0038] Performing differential operation on the grain boundary slip characteristic quantity to obtain the slip acceleration variable;

[0039] When the slip acceleration exceeds the preset slip acceleration rate threshold, a forging hammer impact energy gradient compensation coefficient is generated; wherein, according to the material characteristic database, the historical forging data and the theoretical model of the superplastic phase transition tolerance to slip instability, a slip acceleration rate safety boundary or trigger line is calculated and set as the preset slip acceleration rate threshold; when the actual slip acceleration rate exceeds the preset threshold, it indicates that the acceleration rate of the grain boundary slip may exceed the limit of the stable deformation of the material in the target superplastic state, and intervention is needed to control the heat input;

[0040] The compensation coefficient is dynamically superimposed on the stroke reference curve of the main driving rail to increase the forging hammer impact energy intensity in the grain boundary slip active area;

[0041] After the dual-rail output signals are fused by the servo control system, the hydraulic actuator is driven to realize the grain boundary slip response type precision forging.

[0042] The window adjustment unit 302 in the cross-domain collaborative execution module 300 implements a window adaptive strategy in the temperature control loop, the core of which is to use the temperature maintenance window generated and continuously updated by the phase change pre-judgment decision module 200 as the reference framework for energy input distribution; the process starts with the power distributor receiving the key parameters of the temperature maintenance window, i.e. the temperature boundary values of the window (especially the current target control temperature upper limit), the action time range, and the core scope space coordinate set of the current window; according to the window parameters, the power distributor first determines the spatial distribution matrix of the inductor coil power density, i.e. calculates the initial power density setting value for the entire forging area (especially the area covered by the window) to ensure that the energy input basis matches the predicted phase change maintenance demand.

[0043] The key of the window adaptive strategy is to dynamically track and respond to the slip trend represented by the material grain boundary slip characteristic quantity, which is embodied in the direction of the slip acceleration variable (obtained by differential operation on the grain boundary slip characteristic quantity) and its rate of change (i.e. the change speed of the acceleration); according to the real-time change of the material grain boundary slip characteristic quantity, the three key boundary dimensions of the temperature maintenance window (temperature value, time domain, and spatial domain) are actively adjusted; when the slip acceleration variable is continuously positive (indicating continuous acceleration of the grain boundary slip) and its rate of change (speed increase) exceeds the preset slip acceleration rate threshold, the temperature value boundary compression strategy is triggered, and the temperature upper limit of the window is reduced according to the preset compression ratio, thereby actively controlling the temperature level of the region to prevent overheating from causing abnormal grain growth or material performance degradation;

[0044] In addition, when the duration of the material's grain boundary slip characteristic quantity maintaining a stable state (its numerical fluctuation amplitude is less than the preset characteristic quantity variance threshold) for a period of time reaches or exceeds the window minimum stable time threshold, the window action duration extension strategy is triggered, and the window end time point is extended to the estimated end time of the slip characteristic stability period, ensuring continuous and stable phase transformation conditions until the natural transition to the superplastic forming stage is completed; when the spatial distribution density of the monitored slip active area coordinates (i.e., the frequency of high-value points of grain boundary slip characteristic quantity per unit volume or area) is greater than the preset regional coverage density critical value, it indicates that the grain boundary slip active area is highly concentrated, and the window core scope contraction strategy is triggered at this time, specifically including:

[0045] The area covered by the original window is shrunk and focused to a high-density coordinate set in the slip-active zone, concentrating key control resources in the local area that needs to be maintained the most. Based on the adjustment results of the window boundary (whether it is a change in the upper temperature limit, an extension of the action time, or a contraction of the core action domain), the power distributor immediately performs energy density redistribution and updates and reorganizes the spatial distribution matrix of the induction coil power density in real time. The core of this is to significantly increase the power density value of the induction coil within the more focused space covered by the core action domain boundary after the reorganization, thereby achieving targeted and precise enhanced injection of energy intensity in the key area where superplastic deformation is most active and requires continuous energy maintenance. This method of dynamically adjusting the window boundary and focusing energy according to the slip trend effectively overcomes the shortcomings of static heating, ensures the high efficiency of energy input, and ultimately ensures that the superplastic deformation zone obtains the most ideal and sustainable thermodynamic environment.

[0046] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A collaborative control system for intelligent forging of tension clamps, characterized in that: The system comprises an acoustic multimodal perception module (100), a phase change prediction and decision module (200), and a cross-domain collaborative execution module (300), wherein: The acoustic multimodal sensing module (100) generates a material grain boundary slip characteristic quantity and a three-dimensional temperature field distribution map by analyzing the full-band coupling of the acoustic wave scattering signal inside the forging, and corrects the local distortion in the three-dimensional temperature field distribution map using the spatial distribution law of the material grain boundary slip characteristic quantity; The phase change prediction decision module (200) converts the corrected three-dimensional temperature field distribution map into a thermal activation energy field, couples the material grain boundary slip characteristic quantity to construct a grain boundary dynamic reorganization response network, predicts the superplastic phase change triggering sequence and outputs the pressure peak threshold and temperature maintenance window; The cross-domain collaborative execution module (300) constructs a dual-track driving mechanism in the forging control loop, wherein the main driving track plans the forging hammer stroke curve with the pressure peak threshold as the target benchmark, and the auxiliary feedback track converts the material grain boundary slip characteristic quantity into a dynamic correction factor for adjusting the forging hammer impact energy gradient; and: The cross-domain collaborative execution module (300) implements a window adaptive strategy in a temperature control loop, sets an initial value of coil power based on a temperature maintenance window as an energy distribution basis, adjusts the window boundary of the temperature maintenance window in real time based on the slip trend of a material grain boundary slip characteristic quantity, and focuses on the energy density of a superplastic deformation zone.

2. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The process of full-band coupling analysis specifically includes: Based on the Doppler frequency shift phenomenon of sound waves propagating in high-temperature materials of forgings, the sound wave frequency offset at different spatial positions is analyzed to reconstruct the three-dimensional temperature field distribution map inside the forgings; Based on the abnormal attenuation characteristics of acoustic wave energy at the grain boundaries of the material, the characteristic components related to lattice distortion in the acoustic wave attenuation spectrum are extracted to generate the material grain boundary slip characteristic quantity that characterizes the microscopic deformation state.

3. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The process of correcting the local distortion in the three-dimensional temperature field distribution map specifically includes: By utilizing the spatial distribution law of the characteristic quantity of grain boundary slip of the material, that is, the high-value area of ​​the characteristic quantity corresponds to the active area of ​​local deformation of the material, the local distortion in the three-dimensional temperature field distribution map is dynamically corrected, the temperature measurement distortion area is automatically calibrated, and the temperature field measurement deviation caused by local heterogeneity of the material is eliminated through the interpolation algorithm.

4. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The process of the phase change prediction decision module (200) converting the corrected three-dimensional temperature field distribution map into a thermal activation energy field specifically includes: The temperature gradient value of each spatial coordinate point in the temperature field is extracted, and the activation energy distribution required for atomic migration within a unit volume is calculated based on the material phase change kinetic model.

5. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The process of generating the pressure peak floating threshold specifically includes: When the thermal activation energy field value enters the critical interval and the growth rate of the material grain boundary slip characteristic quantity exceeds the set slope, it is determined to be a precursor to superplastic phase transformation triggering. The pressure peak floating threshold is dynamically calculated according to the phase transformation triggering precursor timing, so that the pressure peak floating threshold is adaptively adjusted as the peak coordinate of the thermal activation energy field migrates.

6. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The generation rules of the temperature maintenance window include: The window boundary is set based on the thermal activation energy value of the active zone of grain boundary slip of the material, and the window action duration is dynamically adjusted in conjunction with the slip acceleration.

7. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The cross-domain collaborative execution module (300) includes a dual-track driving unit (301), and the process of the dual-track driving unit (301) planning the forging hammer stroke curve using the main driving track specifically includes: The pressure peak floating threshold is converted into a forging hammer downward displacement sequence through the material constitutive equation, and the maximum stroke acceleration constraint is set.

8. The intelligent forging collaborative control system for tension clamps according to claim 7 is characterized in that: The process of the dual-track driving unit (301) converting the material grain boundary slip characteristic quantity into a dynamic correction factor using the auxiliary feedback track specifically includes: A differential operation is performed on the grain boundary slip characteristic quantity to obtain the slip acceleration variable; when the slip acceleration exceeds a preset slip acceleration change rate threshold, a forging hammer impact energy gradient compensation coefficient is generated; the preset slip acceleration change rate threshold is calculated based on a material property database, historical forging data, and a theoretical model of the tolerance of superplastic phase transformation to slip instability; The forging hammer impact energy gradient compensation coefficient is dynamically superimposed on the forging hammer stroke curve of the main drive rail to improve the forging hammer impact energy intensity.

9. The intelligent forging collaborative control system for tension clamps according to claim 1 is characterized in that: The cross-domain collaborative execution module (300) includes a window adjustment unit (302). When the window adjustment unit (302) adjusts the window boundary of the temperature maintenance window, when the slip acceleration variable continues to be positive and its change rate exceeds a preset slip acceleration change rate threshold, a temperature value boundary compression strategy is triggered to reduce the temperature upper limit of the window according to a preset compression ratio.

10. The intelligent forging collaborative control system for tension clamps according to claim 9 is characterized in that: When the window adjustment unit (302) adjusts the window boundary of the temperature maintenance window, when it is monitored that the spatial distribution density of the coordinates of the active sliding area is greater than a preset regional coverage density threshold, the window core scope contraction strategy is triggered to contract the area covered by the original window effect and focus on the high-density coordinate set of the active sliding area.

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