A smart forging collaborative control system for tension clamps

Abstract

This invention relates to the field of forging control technology, specifically to an intelligent forging collaborative control system for tension clamps. This system uses an acoustic multimodal sensing module to perform full-band coupling analysis of the acoustic signal from the forging, simultaneously generating material grain boundary slip characteristics and a three-dimensional temperature field distribution map. It then uses the spatial distribution law of the slip characteristics to correct local distortions in the temperature field. A phase transformation prediction and decision module converts the corrected temperature field into a thermally activated energy field, couples the grain boundary slip characteristics to construct a grain boundary dynamic recombination response network, and outputs a pressure peak floating threshold and a temperature maintenance window that adaptively adjust with the phase transformation state. A cross-domain collaborative execution module constructs a dual-track drive mechanism in the forging circuit. The main drive track plans the forging hammer stroke curve based on the pressure peak floating threshold, while the secondary feedback track converts the grain boundary slip characteristics into a dynamic correction factor to adjust the impact energy gradient. A window adaptive strategy is implemented in the temperature circuit to achieve efficient focusing of energy in the superplastic deformation zone.

Description

Technical Field

[0001] This invention relates to the field of forging control technology, specifically to an intelligent forging collaborative control system for tension clamps. Background Technology

[0002] There is room for improvement in the current forging process of tension clamps in terms of real-time temperature field monitoring and process control, including:

[0003] On the one hand, widely used contact sensors such as thermocouples may be limited by the density of the sampling points and the changes in local physical properties of the material when reflecting the internal temperature distribution of complex-shaped forgings. This results in a certain delay or incomplete response to local temperature distortions caused by grain boundary slip or material heterogeneity, posing challenges to the integrity and accurate reconstruction of the temperature field.

[0004] On the other hand, existing control systems lack a sufficiently robust mechanism for coordinating the perception and control of the dynamic correlation between the microscopic deformation state of the material (such as grain boundary slip) and macroscopic forging process parameters (such as pressure and temperature). This may result in inaccurate identification of the critical triggering timing and required energy window for superplastic phase transformation, and the failure of the forging force or temperature field distribution to match the dynamic changes of the material in real time. This perception deviation and control lag of process parameters affects the uniformity of the grain boundary remodeling process in the forging to some extent, and may also impact the structural consistency and service reliability of the final product. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent forging collaborative control system for tension clamps to solve the problems mentioned in the background art. The specific technologies include how to achieve accurate reconstruction of the three-dimensional temperature field inside the forging and eliminate local measurement distortion to solve the problem of temperature field distortion caused by material heterogeneity; and how to establish a control mechanism for the dynamic evolution of grain boundaries and forging parameters to solve the problem of inaccurate timing prediction and energy regulation of superplastic phase transformation triggering.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] This intelligent forging collaborative control system for tension clamps includes an acoustic multimodal sensing module, a phase change prediction and decision-making module, and a cross-domain collaborative execution module, wherein:

[0008] The acoustic multimodal sensing module achieves collaborative sensing by coupling and analyzing the scattered acoustic wave signal across the entire frequency band. Based on the Doppler frequency shift phenomenon of acoustic waves in high-temperature forging materials, it analyzes the frequency shift of acoustic waves at different spatial locations to reconstruct a three-dimensional temperature field distribution map, solving the problem of visualizing the spatial distribution of the macroscopic temperature field. Furthermore, 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 grain boundary slip characteristic quantity of the material, realizing the quantitative characterization of the microscopic deformation state.

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

[0010] The phase transition prediction and decision module transforms the corrected three-dimensional temperature field distribution map into a thermally activated energy field. By extracting the temperature gradient values ​​at each spatial coordinate point, it calculates the activation energy distribution required for atomic migration per unit volume based on the material phase transition dynamics model, and establishes a mapping relationship between the temperature field and the material phase transition energy.

[0011] The phase transformation prediction and 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 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 superplastic phase transformation. The pressure peak floating threshold is dynamically calculated based on the phase transformation precursor time sequence, and the threshold is adaptively adjusted as the thermal activation energy field peak coordinate migrates to ensure that the forging pressure 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 active grain boundary slip region of the material, and the window duration is dynamically adjusted in conjunction with the slip acceleration to form a precise temperature control strategy synchronized with grain boundary evolution.

[0012] The cross-domain collaborative execution module constructs 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 with the pressure peak floating threshold as the target benchmark through the main drive track. By adopting the material constitutive equation, the pressure peak floating threshold is transformed into the forging hammer downward displacement sequence, and the maximum stroke acceleration constraint is set to ensure the stability of the forging hammer kinetic energy output.

[0013] The dual-track drive unit converts the grain boundary slip characteristic quantity of the material into a dynamic correction factor through the secondary feedback track: it performs differential operation on the grain boundary slip characteristic quantity to obtain the slip acceleration variable; when the slip acceleration exceeds the preset slip acceleration change rate threshold, it generates the forging hammer impact energy gradient compensation coefficient; the slip acceleration change rate threshold is calculated based on the material property database, historical forging data and superplastic phase transformation tolerance model; the forging hammer impact energy gradient compensation coefficient is dynamically superimposed on the forging hammer stroke curve to increase the forging hammer impact energy intensity in real time to suppress the grain boundary slip instability state.

[0014] In the temperature control loop, the initial value of the coil power is set based on 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 slip trend of the material grain boundary slip characteristic quantity. When the slip acceleration variable is continuously positive and its rate of change exceeds the preset slip acceleration rate of change threshold, the temperature value boundary compression strategy is triggered to reduce the upper limit of the window temperature according to the preset compression ratio to accelerate the energy accumulation in the phase transition region.

[0015] When the spatial distribution density of the coordinates of the active slip region is detected to be greater than the preset critical value of the region coverage density, the window core domain shrinkage strategy is triggered, which shrinks and focuses the original window coverage area to the high-density coordinate set of the active slip region, ultimately achieving dynamic focusing of the energy density of the superplastic deformation region and improving the grain boundary reorganization efficiency.

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

[0017] By employing acoustic multimodal sensing, the temperature field and grain boundary slip of forgings are analyzed collaboratively, eliminating measurement biases caused by local heterogeneity. Based on the dynamic coupling mechanism of thermally activated energy field and grain boundary slip characteristics, the triggering timing of superplastic phase transformation and pressure / temperature control thresholds are accurately predicted. Cross-domain collaborative control of forging energy and temperature field is achieved using dual-track drive and window adaptive strategies, improving the uniformity of grain boundary remodeling. Ultimately, while avoiding local overheating, the efficiency of superplastic deformation of forgings is optimized, and the fatigue life of tension clamps is extended, providing core control support for the intelligent manufacturing of power fittings. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall modules of the present invention;

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

[0020] In the diagram: 100, Acoustic multimodal perception module; 200, Phase change prediction and decision-making module; 300, Cross-domain collaborative execution module; 301, Dual-track drive unit; 302, Window adjustment unit. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and 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.

[0022] Next, please refer to Figure 1 The present invention provides a technical solution: a tension clamp intelligent forging collaborative control system, including an acoustic multimodal sensing 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 emits high-frequency sound waves into the forging through a wide-frequency domain acoustic wave detector array, and collects the scattered signals formed after the sound waves propagate inside the material. It then performs coupled analytical processing on the collected full-frequency acoustic wave signals, specifically including:

[0024] Based on the Doppler frequency shift phenomenon generated 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 shift at different spatial locations.

[0025] Based on the abnormal attenuation characteristics of acoustic energy at the material grain boundaries, characteristic components related to lattice distortion in the acoustic attenuation spectrum are extracted to generate material grain boundary slip characteristic quantities that characterize the micro-deformation state.

[0026] By utilizing the spatial distribution law of grain boundary slip characteristic quantities (i.e., high value areas of characteristic quantities correspond to active local deformation areas of the material), local distortions in the three-dimensional temperature field distribution map are dynamically corrected. When the grain boundary slip characteristic quantity shows abnormal fluctuations at a certain spatial coordinate point, it is automatically identified as a temperature measurement distortion area. The temperature gradient distribution of adjacent normal areas is mapped to the distortion area through an interpolation algorithm, eliminating the temperature field measurement deviation caused by the local heterogeneity of the material. This process finally outputs a spatiotemporally synchronized calibrated three-dimensional temperature field distribution map and material grain boundary slip characteristic quantities, providing distortion-free multiphysics sensing data for subsequent modules.

[0027] The phase transition prediction and decision module 200 first converts the corrected three-dimensional temperature field distribution map output by the acoustic multimodal sensing module 100 into a thermally activated energy field. Specifically, it extracts the temperature gradient values ​​at each spatial coordinate point in the temperature field and calculates the activation energy distribution required for atomic migration per unit volume based on the material phase transition dynamics model. Simultaneously, it couples the material grain boundary slip characteristic quantities to construct a grain boundary dynamic reorganization response network, where the thermally activated energy field provides atomic diffusion barrier data, and the material grain boundary slip characteristic quantities carry dislocation motion rate information. When the thermally activated energy field value enters the critical range and the growth rate of the material grain boundary slip characteristic quantities exceeds the set slope, it is determined to be a precursor to a superplastic phase transition. Based on the matching relationship between the spatial aggregation degree of the material grain boundary slip characteristic quantities and the gradient direction of the thermally activated energy field, the phase transition propagation path is predicted, where:

[0028] The pressure peak floating threshold is dynamically calculated based on the phase change trigger precursor timing, so that the pressure peak floating threshold is adaptively adjusted as the peak coordinate of the thermal activation energy field migrates.

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

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

[0031] First, we traverse every spatial coordinate point in the temperature field and accurately extract the temperature gradient value of that point and its neighboring region, which reflects the spatial rate and direction of temperature change inside the material.

[0032] Subsequently, a stored material phase transition kinetic model specific to the forged tension clamp material is invoked (this model includes theoretical frameworks such as diffusion coefficient, activation energy, and Arrhenius equation). 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 treat atomic migration at the microscale as a thermally activated process. The goal of the calculation is to determine the energy barrier required to overcome lattice constraints and allow atoms to migrate to adjacent positions under the current specific local temperature field and temperature gradient conditions—that is, the activation energy. The result of the calculation is not a single value, but rather generates a field reflecting the spatial distribution of energy barriers within the entire forging region (forging), i.e., 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 for different regions of the material to complete the phase transition (mainly triggering superplasticity here), and is a key input parameter for predicting the location and time of the phase transition, providing the most basic atomic diffusion energy barrier information for the subsequent construction of the grain boundary dynamic reorganization response network.

[0033] The generation process of the pressure peak fluctuation threshold in the phase transformation prediction decision module 200 is the core decision mechanism for predicting the onset 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 the pre-set or model-calculated critical range as a whole or locally (this range represents that the atomic diffusion ability inside 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 in a specific time window exceeds a set slope threshold (this threshold represents the critical point for grain boundary slip to transition from linear to nonlinear acceleration). If and only if these two conditions are met simultaneously, the current state is determined to be a precursor to a superplastic phase transformation that is about to undergo large-scale superplastic deformation. Once the precursor is determined, the dynamic calculation stage of the pressure peak value begins. The core principle of the calculation is that the pressure peak fluctuation threshold must be adaptively adjusted in close accordance with the dynamic process of phase transformation initiation and expansion. The specific method is:

[0034] The system tracks the temporal evolution of precursors to phase transition (i.e., the temporal order and spatial concentration of precursors), and monitors in real time the migration direction of the peak coordinates of the thermally activated energy field (i.e., the change in the location of the region with the highest current activation energy and the most likely to undergo phase transition first). Based on the changing trend of the precursor state over time and the spatial movement trajectory of the peak coordinates of the energy field, a pre-set dynamic decision-making algorithm (which may include feedback control theory or empirical models) is used to dynamically calculate the optimal, and also floating, pressure threshold. Its "floating" characteristic is reflected in the fact that the pressure threshold is not a fixed value, but will dynamically change according to the migration of the core phase transition region. This aims to provide a pressure benchmark that best matches the current phase transition state and location for the forging process, thereby accurately guiding the forging hammer action to adapt to the phase transition-induced material softening zone.

[0035] Please see 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, constructs a forging control system composed of main / secondary dual tracks, wherein:

[0036] The main drive rail uses the pressure peak floating threshold output by the phase transformation prediction and decision module 200 as the target benchmark. Based on the real-time deformation resistance spectrum of the forging, the forging hammer stroke curve is planned. Specifically, the pressure threshold is converted into the forging hammer downward displacement sequence through the material constitutive equation, and the maximum stroke acceleration constraint is set.

[0037] The secondary feedback track converts the continuously input material grain boundary slip characteristics of the acoustic multimodal sensing module 100 into dynamic correction factors. This conversion process includes:

[0038] Perform a difference operation on the grain boundary slip characteristic quantities to obtain the slip acceleration variable;

[0039] When the slip acceleration exceeds a preset slip acceleration change rate threshold, a forging hammer impact energy gradient compensation coefficient is generated. Based on the material property database, historical forging data, and a theoretical model of the tolerance of slip instability to superplastic phase transformation, a safety boundary or trigger line for the slip acceleration change rate is calculated and set as the preset slip acceleration change rate threshold. When the actual slip acceleration change rate exceeds this preset threshold, it indicates that the grain boundary slip acceleration rate may exceed the limit of stable deformation of the material in the target superplastic state, and intervention is required to control the heat input.

[0040] The compensation coefficient is dynamically superimposed onto the travel reference curve of the main drive rail to enhance the impact energy intensity of the forging hammer in the active grain boundary slip region.

[0041] The dual-rail output signals are fused by the servo control system to drive the hydraulic actuator to achieve grain boundary slip response 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. Its core is to use the temperature maintenance window generated and continuously updated by the phase change prediction decision module 200 as the benchmark framework for energy input allocation. The process begins with the power distributor receiving the key parameters of the temperature maintenance window, namely the temperature boundary value of the window (especially the current target control temperature upper limit), the action time range, and the spatial coordinate set of the core action domain of the current window. Based on the window parameters, the power distributor first determines the spatial distribution matrix of the induction coil power density, that is, calculates the initial power density set value for the entire forging area (especially the area covered by the window) to ensure that the basis of energy injection is consistent with the predicted phase change maintenance requirements.

[0043] The key to the window adaptive strategy lies in dynamically tracking and responding to the slip trend characterized by the grain boundary slip feature quantity of the material. This trend is specifically reflected in the direction and rate of change of the slip acceleration variable (obtained by differential operation on the grain boundary slip feature quantity) (i.e., the rate of change of acceleration). Based on the real-time changes of the grain boundary slip feature quantity of the material, the three key boundary dimensions (temperature value, time domain, and spatial domain) of the temperature maintenance window are actively and finely adjusted. When the slip acceleration variable is continuously positive (indicating that the grain boundary slip is continuously accelerating) and its rate of change (speed increase) exceeds the preset slip acceleration rate of change threshold, the temperature value boundary compression strategy is triggered, and the upper limit of the window temperature is reduced according to the preset compression ratio, thereby actively controlling the temperature level of the region and preventing overheating from causing abnormal grain growth or material performance degradation.

[0044] Furthermore, when the duration of a stable state (with its numerical fluctuation amplitude less than a preset characteristic variance threshold) of the material grain boundary slip characteristic quantity reaches or exceeds the minimum stable time threshold of the window, a window duration extension strategy is triggered, extending the window's termination time to the estimated end of the stable period of the slip characteristic, ensuring continuous and stable phase transformation conditions until the natural transition of the superplastic forming stage is completed; when the spatial distribution density of the active slip region 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 critical value of region coverage density, it indicates that the active grain boundary slip region is highly concentrated, and at this time, a window core domain contraction strategy is triggered, specifically including:

[0045] The original window's coverage area is contracted and focused onto a high-density coordinate set within the active slip region, concentrating key control resources on the most critical local area requiring maintenance. Based on the window boundary adjustments (whether due to changes in the upper temperature limit, extended application time, or contraction of the core domain), the power distributor immediately performs energy density redistribution, updating and reorganizing the spatial distribution matrix of the induction coil's power density in real time. The core principle lies in significantly increasing the induction coil's power density within the more focused space covered by the reorganized, smaller core domain boundary. This allows for targeted and precise energy enhancement within the critical region where superplastic deformation is most active and requires continuous energy maintenance. This dynamic adjustment of the window boundary and focus of energy based on slip trends effectively overcomes the shortcomings of static heating, ensures high energy input efficiency, and ultimately guarantees the most ideal and sustainable thermodynamic environment for the superplastic deformation region.

[0046] The foregoing has shown and described 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 embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent forging collaborative control system for strain clamp, characterized in that, The application relates to a multi-modal acoustic sensing module (100), a phase transition pre-judgment decision module (200) and a cross-domain collaborative execution module (300), wherein: The acoustic multi-modal sensing module (100) generates material grain boundary slip characteristic quantities and a three-dimensional temperature field distribution map by full-band coupling analysis of internal acoustic wave scattering signals of a forging, and corrects local distortion in the three-dimensional temperature field distribution map by using the spatial distribution law of the material grain boundary slip characteristic quantities; The phase transition pre-judgment 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 quantities to construct a grain boundary dynamic recombination response network, predicts an ultraplastic phase transition triggering time sequence and outputs a pressure peak value floating threshold and a temperature maintenance window; The cross-domain collaborative execution module (300) constructs a double-track driving mechanism in a forging pressure control loop, wherein a main driving track plans a forging hammer stroke curve with the pressure peak value floating threshold as a target reference, and a vice feedback track converts the material grain boundary slip characteristic quantities into a dynamic correction factor for adjusting a forging hammer impact energy gradient; and The cross-domain collaborative execution module (300) implements a window self-adaptive strategy in a temperature control loop, sets a coil power initial value with the temperature maintenance window as an energy distribution base, adjusts a window boundary of the temperature maintenance window in real time through a slip trend of the material grain boundary slip characteristic quantities, and focuses on energy density of an ultraplastic deformation area.

2. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The full-band coupling analysis process specifically comprises the following steps: Based on Doppler frequency shift phenomena of acoustic wave propagation in high-temperature materials of a forging, frequency offset amounts of acoustic waves at different spatial positions are analyzed, and a three-dimensional temperature field distribution map inside the forging is reconstructed; According to abnormal attenuation characteristics of acoustic wave energy at material grain boundaries, feature components related to lattice distortion in an acoustic wave attenuation spectrum are extracted, and material grain boundary slip characteristic quantities representing micro-deformation states are generated.

3. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The process of correcting local distortion in the three-dimensional temperature field distribution map specifically comprises the following steps: The spatial distribution law of the material grain boundary slip characteristic quantities, i.e. a high-value area of the characteristic quantities corresponds to a material local deformation active area, is used to dynamically correct local distortion in the three-dimensional temperature field distribution map, automatically calibrate a temperature measurement distortion area and eliminate temperature field measurement deviations caused by material local heterogeneity through an interpolation algorithm.

4. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The process that the phase transition pre-judgment decision module (200) converts the corrected three-dimensional temperature field distribution map into a thermal activation energy field specifically comprises the following steps: Temperature gradient values of each spatial coordinate point in the temperature field are extracted, and a distribution of activation energy required for atomic migration in a unit volume is calculated according to a material phase transition dynamics model.

5. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The generation process of the pressure peak value floating threshold specifically comprises the following steps: When the thermal activation energy field value enters a critical interval and a material grain boundary slip characteristic quantity increases at a speed exceeding a set slope, it is determined that it is a precursor of an ultraplastic phase transition, the pressure peak value floating threshold is dynamically calculated according to a phase transition precursor time sequence, and the pressure peak value floating threshold is adaptively adjusted with the thermal activation energy field peak coordinate migration.

6. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The generation rule of the temperature maintenance window comprises the following steps: A thermal activation energy value of a material grain boundary slip active area is used as a reference to set a window boundary, and the window boundary is dynamically adjusted in association with a slip acceleration.

7. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, The cross-domain cooperative execution module (300) comprises a double-track driving unit (301), and a process in which the double-track driving unit (301) plans a forging hammer stroke curve by using a main driving track specifically comprises: The pressure peak floating threshold is converted into a forging hammer down-pressing displacement sequence by a material constitutive equation, and a maximum stroke acceleration constraint is set.

8. The intelligent forging collaborative control system for strain clamp according to claim 7, characterized in that, The double-track driving unit (301) converts material grain boundary sliding characteristic quantities into a dynamic correction factor by using a secondary feedback track, and a process specifically comprises: A difference operation is performed on the grain boundary sliding characteristic quantities 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; wherein the preset sliding acceleration change rate threshold is calculated according to a material characteristic database, historical forging data and a theoretical model of superplastic phase transition tolerance to sliding instability; The forging hammer impact energy gradient compensation coefficient is dynamically superimposed on the forging hammer stroke curve of the main driving track, so as to improve the forging hammer impact energy intensity.

9. The intelligent forging collaborative control system for strain clamp according to claim 1, characterized in that, When the window adjustment unit (302) adjusts the window boundary of the temperature maintenance window, when the sliding acceleration variable continuously has a positive value and its change rate exceeds the preset sliding acceleration change rate threshold, a temperature value boundary compression strategy is triggered, and the temperature upper limit value of the window is reduced according to a preset compression ratio.

10. The intelligent forging collaborative control system for strain clamp according to claim 9, 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 sliding active area coordinates is greater than a preset area coverage density critical value, a window core action scope contraction strategy is triggered, and the area covered by the original window action is contracted and focused to the high-density coordinate set of the sliding active area.

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