Automatic air cylinder clamping system and method

Abstract

The invention discloses an automatic air cylinder clamping system and method, and belongs to the technical field of air cylinder clamping, and the system comprises a map drawing module which is used for drawing a three-dimensional clamping force distribution map; the risk prediction module is used for synchronously predicting a deformation deviation risk value in the clamping process; the model calculation module is used for generating a dynamic attenuation coefficient; and the air cylinder adjusting module is used for dynamically adjusting the opening degree of a multi-stage cushion valve and the servo pressurization rate of the automatic air cylinder set through a self-adaptive control strategy till the clamping force error is stabilized within a preset threshold value. The technical problems that in the automatic air cylinder clamping process, due to environment interference and system errors, the clamping force is unstable, and the workpiece clamping precision is low are solved, and the technical effects that the clamping force stability is improved through dynamic compensation and self-adaptive adjustment, the deformation risk is reduced, and the clamping precision is improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of cylinder clamping, and particularly to an automated cylinder clamping system and method. Background Art

[0002] The in-depth application of automation technology in the industrial manufacturing field has put forward higher requirements for the workpiece clamping system. Especially in the process of precision manufacturing and assembly, the stability and accuracy of clamping the workpiece are crucial. The traditional cylinder clamping device generally adopts a uniform pressure control strategy, which is difficult to meet the force distribution requirements of complex clamping objects such as special-shaped workpieces and composite materials. The existing control methods based on fixed parameters in the prior art cannot effectively cope with multi-source interferences such as mechanical vibration, air pressure fluctuation, and temperature change, resulting in insufficient clamping force stability and a significant increase in the risk of workpiece deformation. Especially in the fields of aerospace and precision electronics, the workpiece material has a large hardness difference and complex structural characteristics, and the conventional clamping scheme is likely to cause local stress concentration, resulting in irreversible workpiece damage. The current clamping system generally lacks the ability to predict real-time risks during the clamping process and can only respond laggingly in the event of sudden working condition changes, seriously affecting the processing quality and efficiency. The strong coupling relationship between environmental interference factors and the characteristics of the clamping object makes it a huge challenge for traditional control algorithms in parameter tuning. Summary of the Invention

[0003] This application provides an automated cylinder clamping system and method, aiming to solve the technical problems of unstable clamping force and low workpiece clamping accuracy caused by environmental interference and system errors during the automated cylinder clamping process, and achieving the technical effects of improving the clamping force stability, reducing the deformation risk, and enhancing the clamping accuracy through dynamic compensation and adaptive adjustment.

[0004] In view of the above problems, this application provides an automated cylinder clamping system and method.

[0005] In the first aspect disclosed in this application, an automated cylinder clamping system is provided. The system includes: a map formulation module, configured to obtain structural basic features including surface topography features and workpiece size features based on the workpiece to be clamped, and formulate a three-dimensional clamping force distribution map with the material hardness data as a constraint condition; a risk prediction module, configured to match the target pressure sequence of each execution unit in the automated cylinder group based on the three-dimensional clamping force distribution map, and simultaneously predict the deformation offset risk value during the clamping process; a model calculation module, configured to introduce environmental interference factors and input them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, where the environmental interference factors include the vibration spectrum of the positioning plate, the air pressure pipeline volatility, and the temperature gradient field; a cylinder adjustment module, configured to dynamically adjust the opening degree of the multi-stage buffer valve and the servo boosting rate of the automated cylinder group through an adaptive control strategy according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient until the clamping force error is stabilized within a preset threshold.

[0006] Another aspect disclosed in the present application provides an automated cylinder clamping method, which includes: based on the workpiece to be clamped, obtaining structural basic features including surface topography features and workpiece size features, and formulating a three-dimensional clamping force distribution map with the material hardness data as a constraint condition; based on the three-dimensional clamping force distribution map, matching the target pressure sequence of each execution unit in the automated cylinder group, and simultaneously predicting the deformation offset risk value during the clamping process; introducing environmental interference factors and inputting them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, where the environmental interference factors include the vibration spectrum of the positioning plate, the air pressure pipeline volatility, and the temperature gradient field; according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient, dynamically adjusting the opening degree of the multi-stage buffer valve and the servo boosting rate of the automated cylinder group through an adaptive control strategy until the clamping force error is stabilized within a preset threshold.

[0007] One or more technical solutions provided in the present application have at least the following technical effects or advantages: Through the map formulation module, based on the workpiece to be clamped, obtaining structural basic features including surface topography features and workpiece size features, and formulating a three-dimensional clamping force distribution map with the material hardness data as a constraint condition; through the risk prediction module, based on the three-dimensional clamping force distribution map, matching the target pressure sequence of each execution unit in the automated cylinder group, and simultaneously predicting the deformation offset risk value during the clamping process; through the model calculation module, introducing environmental interference factors and inputting them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, where the environmental interference factors include the vibration spectrum of the positioning plate, the air pressure pipeline volatility, and the temperature gradient field; through the cylinder adjustment module, according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient, dynamically adjusting the opening degree of the multi-stage buffer valve and the servo boosting rate of the automated cylinder group through an adaptive control strategy until the clamping force error is stabilized within a preset threshold. It solves the technical problems of unstable clamping force and low workpiece clamping accuracy caused by environmental interference and system errors during the automated cylinder clamping process, and achieves the technical effects of improving the clamping force stability, reducing the deformation risk, and enhancing the clamping accuracy through dynamic compensation and adaptive adjustment.

[0008] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically exemplified below. Description of the Drawings

[0009] Figure 1 It is a structural schematic diagram of an automated cylinder clamping system provided by an embodiment of the present application.

[0010] Figure 2 This application example provides a schematic flow diagram of an automated cylinder clamping method.

[0011] Figure 3 This application example provides a schematic diagram of the positioning plate structure of an automated cylinder clamping system.

[0012] Explanation of reference numerals: Map formulation module 11, risk prediction module 12, model calculation module 13, cylinder adjustment module 14, bottom surface of the positioning plate 21, plane height of the positioning plate 22, round positioning hole of the positioning plate 23, distance between two positioning holes of the positioning plate 24, waist-shaped positioning hole of the positioning plate 25. Detailed implementation manners

[0013] By providing an automated cylinder clamping system and method, this application solves the technical problems of unstable clamping force and low workpiece clamping accuracy caused by environmental interference and system errors during the automated cylinder clamping process, and achieves the technical effects of improving the stability of the clamping force, reducing the risk of deformation, and enhancing the clamping accuracy through dynamic compensation and adaptive adjustment.

[0014] Next, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited by the example embodiments described here. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts belong to the scope of protection of this application. Additionally, it should be noted that for the sake of description, only the parts related to this application are shown in the accompanying drawings, rather than all of them.

[0015] Embodiment 1, as Figure 1 、 Figure 3 shown, this application example provides an automated cylinder clamping system, which includes: A map formulation module 11, configured to obtain structural basic features including surface topography features and workpiece size features based on the workpiece to be clamped, and formulate a three-dimensional clamping force distribution map with the material hardness data as a constraint condition.

[0016] Specifically, the clamping system is a precisely designed mechanical device mainly used to fix and position components to ensure the stability and accuracy of the components during the machining or inspection process. The core component of the clamping system is the positioning plate. The flatness requirement of the bottom surface of the positioning plate is 0.02, and the plane height of the positioning plate is 19.15±0.015. These precise designs ensure the close contact and assembly accuracy between the positioning plate and the component to be fixed. Multiple round holes and waist-shaped holes are designed on the positioning plate for positioning and fixing components. The positioning hole diameter of the round hole on the positioning plate is 10.001, and the positioning hole diameter of the waist-shaped hole on the positioning plate is 8.00. These hole diameters match the corresponding dimensions on the component to be fixed, achieving precise positioning. In addition, the distance between the two positioning holes on the positioning plate is 209.75±0.01. This precise distance design further ensures the stability and accuracy of the component during the assembly process. The clamping system achieves a stable connection through specific hole diameter and distance designs. Figure 3 Multiple clamping elements and connecting components are shown in it, and they work together to clamp and fix the components. To ensure the quality and performance of the clamping system, all the dimensions with digital identifiers are inspected to ensure the assembly accuracy and product quality.

[0017] Specifically, in the atlas formulation module 11, first, the structural basic features of the workpiece to be clamped are obtained from the workpiece database, including the surface topography features and dimensional features of the workpiece, such as the shape, texture, surface roughness, length, width, height, etc. of the workpiece. These parameters are the basis for determining the clamping force distribution. Subsequently, since the material of the workpiece to be clamped will directly affect its deformation characteristics and the distribution of the clamping force, the material hardness data of the workpiece to be clamped is measured and used as a constraint condition to further calculate and design the distribution of the clamping force. Then, the obtained structural basic features and material hardness data are integrated to formulate a three-dimensional clamping force distribution atlas. This atlas can reflect the clamping force intensity and variation in different regions, ensuring that the workpiece will not deform or be damaged due to uneven force distribution during the clamping process, thereby optimizing the clamping effect and ensuring the clamping accuracy and workpiece safety.

[0018] Furthermore, with the material hardness data as the constraint condition, a three-dimensional clamping force distribution atlas is formulated, including: Obtain the structural basic features of the workpiece to be clamped, and use an ultrasonic flaw detector to detect the material hardness data; integrate the structural basic features and the material hardness data, and set a three-dimensional clamping force distribution atlas, and the three-dimensional clamping force distribution atlas includes at least three clamping force gradient partitions.

[0019] In a preferred embodiment, after obtaining the basic structural features of the workpiece to be clamped through a workpiece database, 3D scanning technology, or measuring tools, a detection device such as an ultrasonic flaw detector is used to test the material hardness of the workpiece. The ultrasonic flaw detector can evaluate the hardness of the material by emitting ultrasonic waves and measuring the changes in the echo signals. This process is based on the fact that ultrasonic waves propagate faster in materials with higher hardness. The specific steps are as follows: the ultrasonic flaw detector emits high-frequency ultrasonic pulses into the material through the probe, and then calculates the propagation speed of the ultrasonic waves in the material by measuring the time from the emission to the reception of the ultrasonic waves. Generally, in materials with higher hardness, the propagation speed of ultrasonic waves is usually faster. Then, the propagation speed is divided by the standard propagation speed, and the result of the division is multiplied by the standard hardness value corresponding to the standard propagation speed to obtain the hardness data of the material. This method is applicable to different types of materials, such as metals, plastics, ceramics, etc. After obtaining the basic structural features and material hardness data, a clamping force distribution model is constructed using the surface topography features, workpiece size features, and material hardness and other feature data of the workpiece to be clamped. These feature data will determine the clamping force magnitude at each position during the clamping process. To clearly represent the distribution of the clamping force on the workpiece surface, a three-dimensional coordinate system is established, usually based on the geometric shape and size of the workpiece to determine the coordinate axes. Subsequently, the gradient partition of the clamping force is divided according to the morphological features of the workpiece, resulting in at least three gradient partitions, which respectively represent different intensity clamping force regions (such as high, medium, and low intensity regions). These regions are based on data such as the surface morphology and material hardness of the workpiece to specifically determine the clamping force intensity within each partition. After that, a mechanical model (such as finite element analysis, mechanical analysis, etc.) is used to calculate the clamping force distribution in different regions. This calculation process takes into account the structural features and material hardness of different parts and calculates the clamping force magnitude of different parts according to the geometric features and hardness data of the workpiece. Based on the calculation results, a clamping force distribution map is drawn in the three-dimensional coordinate system to obtain a three-dimensional clamping force distribution map containing at least three clamping force gradient partitions. This three-dimensional clamping force distribution map usually uses different colors or heights to represent the changes in the clamping force, which can clearly show the clamping force intensity in different regions (i.e., each gradient partition) to meet the requirements of different parts of the workpiece, ensure the stability and accuracy of the clamping process, and provide basic data for subsequent risk prediction.

[0020] A risk prediction module 12, configured to match the target pressure sequence of each execution unit in the automated cylinder group based on the three-dimensional clamping force distribution map and synchronously predict the deformation offset risk value during the clamping process.

[0021] Specifically, in the risk prediction module 12, based on the three-dimensional clamping force distribution map, precise pressure configuration is carried out for the automated cylinder group. First, the map contains the clamping force gradient distribution in different regions. The system divides the automated cylinder group into multiple execution units according to these gradient regions, and each execution unit corresponds to a specific clamping force region. Subsequently, according to the clamping force gradient region where each execution unit is located, a corresponding target pressure value sequence is matched. These target pressure values ensure that each execution unit generates appropriate pressure, thereby achieving precise clamping of the workpiece. At the same time, the system also performs risk prediction synchronously. In this process, finite element analysis software is used to simulate the action of the clamping force on the workpiece, calculate the stress and strain conditions of each part of the workpiece, display the possible deformation of the workpiece under the action of the clamping force, and quantify the deformation offset risk value based on this. This deformation offset risk value can help adjust the pressure distribution in real time, avoid clamping failures caused by uneven clamping force or workpiece deformation, and ensure the stability and accuracy of the entire clamping process.

[0022] Further, based on the three-dimensional clamping force distribution map, matching the target pressure sequences of each execution unit in the automated cylinder group includes: According to the clamping force gradient partition of the three-dimensional clamping force distribution map, the automated cylinder group is divided into multiple execution units corresponding to the number of partitions, and each execution unit corresponds to a clamping force gradient partition; for the multiple execution units in the automated cylinder group, combining the spatial position and the force density requirements of the gradient partition, the target pressure values of each execution unit are configured to obtain the target pressure sequence.

[0023] In a feasible implementation, according to the clamping force gradient partition information in the three-dimensional clamping force distribution map, the system divides the automated cylinder group into multiple execution units. Each execution unit corresponds to a specific clamping force gradient partition in the clamping force gradient map. The clamping force intensities in these regions are different. The task of each execution unit is to apply appropriate pressure according to the clamping force gradient in its region. In addition, each clamping force gradient partition also represents different force density requirements. Force density refers to the pressure value that needs to be applied per unit area, and this value usually varies according to the shape, material, and clamping method of the workpiece. After determining the gradient partition, the system configures a target pressure value for each execution unit according to the spatial position of each execution unit and the force density requirement of the clamping force gradient partition corresponding to this position. The target pressure value is matched based on the clamping requirements of the workpiece and the force density requirement of the gradient partition, combined with prior experience, to ensure uniform pressure distribution during the clamping process and meet the clamping accuracy requirements of the workpiece. Once the target pressure value is configured for each execution unit, the target pressure values of all execution units are combined into a target pressure sequence in order. This target pressure sequence represents the pressure adjustment sequence of each execution unit in the automated cylinder group and is used to guide subsequent clamping operations to ensure that each execution unit can apply appropriate pressure according to the gradient partition it is in, achieving a stable and uniform clamping effect.

[0024] Furthermore, with the optimization objectives of clamping force uniformity, load balance of execution units, and energy consumption efficiency, the local curvature of the surface topography feature is introduced as a weight correction factor to optimize the configuration of the target pressure value. At the same time, based on historical clamping data, a finite element analysis model is constructed in comparison with the three-dimensional clamping force distribution map. The stress-strain distribution under the clamping state is simulated by the finite element analysis model, the deformation offset risk value is quantified, and it is judged whether to trigger the pressure compensation mechanism, which is used to dynamically correct the target pressure sequence.

[0025] In a feasible implementation, after obtaining the target pressure sequence, there may be certain errors in this target pressure sequence due to deformation offset. Therefore, the optimization objectives are the clamping force uniformity, the load balance of the execution units, and the energy consumption efficiency, and the local curvature of the workpiece surface topography features is introduced. The local curvature is a parameter describing the degree of bending of the surface shape, and different curvature values will affect the force distribution of the workpiece during the clamping process. By using the local curvature as a weight correction factor, the configuration of the target pressure value can be adjusted, so that during the clamping process, the change in the surface shape of the workpiece can be fully considered, and then the distribution of the clamping force can be optimized to make the clamping force more uniform, while avoiding local over-clamping or under-clamping. Subsequently, the historical clamping data is compared with the three-dimensional clamping force distribution map. These historical data include the actual pressure values and clamping effects during the previous workpiece clamping process. By analyzing these data, it is possible to evaluate which areas may have uneven clamping force or excessive force density. Then, based on the historical clamping data and the three-dimensional clamping force distribution map, a finite element analysis (FEA) model is constructed. This model numerically simulates the stress-strain distribution of the workpiece under the clamping state. Finite element analysis can accurately predict the deformation of the workpiece during the clamping process, identify the high-stress areas, and calculate the clamping force uniformity index (by extracting the pressure distribution in the clamping area of the workpiece and calculating the standard deviation of the pressure), the load balance index of the execution units (by separately summing up the total clamping force in the action area of each execution unit and calculating the ratio of the deviation between the maximum value and the minimum value), and the energy consumption efficiency index (by calculating the ratio of the overall stress change caused by the unit clamping force applied by each unit to the work or energy parameter input in the simulation). Then, subtract these several indexes from 1 and weight the obtained differences to get a deformation offset risk value describing the quality of the current target pressure value. This risk value reflects the degree of workpiece deformation that may be caused by uneven clamping force or unreasonable force density distribution. If this deformation offset risk value is greater than or equal to the preset deformation offset risk value, a pressure compensation mechanism will be triggered. The goal of this mechanism is to dynamically correct the target pressure sequence to offset the impact of the deformation offset. Specifically, the pressure compensation mechanism will calculate the pressure amplitude to be adjusted according to the magnitude of the deformation risk value. The larger the deformation risk value, the greater the pressure adjustment amplitude. For the workpiece area with a large curvature, appropriate adjustments will be made according to its surface shape to avoid pressure concentration or unevenness caused by curvature differences. After the adjustment is completed, the adjusted target pressure sequence will be analyzed by finite element again, and the deformation offset risk value will be recalculated. This process is iterated until the deformation offset risk value is less than the preset deformation offset risk value. At this time, the current target pressure sequence will be output. In summary, based on the above steps, the system dynamically corrects the target pressure sequence to ensure that during the clamping process, the pressure value can be adjusted in real time according to the actual deformation of the workpiece.In this way, through real-time pressure adjustment, deformation offset can be effectively prevented, and the clamping force uniformity, load balance, and energy efficiency optimization can be ensured. It can also effectively avoid deformation or damage caused by uneven clamping.

[0026] The model calculation module 13 is used to introduce environmental interference factors and input them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient. Among them, the environmental interference factors include the vibration spectrum of the positioning plate, the volatility of the pneumatic pipeline, and the temperature gradient field.

[0027] Specifically, in the model calculation module 13, first, the system identifies and collects environmental interference factors that may affect the clamping process. These interference factors include, but are not limited to, the vibration of the positioning plate, pneumatic pressure fluctuations, temperature, etc. By collecting these interference factors, interference data such as the vibration spectrum of the positioning plate, the volatility of the pneumatic pipeline, and the temperature gradient field can be obtained. Among them, the vibration spectrum of the positioning plate reflects the vibration frequency and amplitude characteristics of the positioning plate caused by mechanical structure or external disturbances during the clamping process. This data can be collected in real time through an acceleration sensor or a laser vibrometer installed on the positioning plate; the volatility of the pneumatic pipeline is used to characterize the stability of the pneumatic pressure change in the gas source system at different time periods. The continuous pneumatic pressure readings can be obtained through a pressure sensor installed on the air inlet pipeline of the cylinder, and the volatility can be obtained through statistical analysis. For example, the volatility can be quantified by calculating the standard deviation of the pneumatic pressure change; the temperature gradient field describes the temperature distribution difference between the fixture and the workpiece in space. This data can be measured through a thermocouple or an infrared temperature sensor array arranged at multiple points. After obtaining this environmental interference data, the data will be input into a pre-trained interference compensation model. This model has been trained based on historical data and experimental results and can effectively identify the influence of these interference factors on the clamping process and calculate a dynamic attenuation coefficient. This dynamic attenuation coefficient is used to correct the clamping force. It automatically adjusts according to the current environmental conditions to ensure the stability and accuracy of the clamping force. In this way, the compensation of the clamping force can be dynamically adjusted in real time according to the environmental interference factors, reducing the adverse effects brought by environmental factors, thereby improving the reliability and accuracy of the automatic cylinder clamping system.

[0028] Furthermore, introducing environmental interference factors and inputting them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient includes: Performing data noise reduction preprocessing on the vibration spectrum of the positioning plate, the volatility of the pneumatic pipeline, and the temperature gradient field in the environmental interference factors to obtain preprocessed data; based on the preprocessed data, using an interference compensation model under the Transformer architecture to generate a dynamic attenuation coefficient.

[0029] In a feasible implementation manner, after collecting the vibration spectrum of the positioning plate, the volatility of the pneumatic pipeline, and the temperature gradient field, algorithms such as wavelet transform, Kalman filter, or S-G filter are used to filter out high-frequency or random noise, retain the main characteristic trends, and then identify and remove mutation points or invalid data through sliding window statistics or Z-score method. Subsequently, the vibration spectrum of the positioning plate, the volatility of the pneumatic pipeline, and the temperature gradient field after removing high-frequency noise, random noise, mutation points, and invalid data are standardized to obtain preprocessed data, making it adapt to the input format of the subsequent model. The standardization is carried out using max-min normalization. After that, the preprocessed data is input into an interference compensation model constructed based on the Transformer architecture. This model uses its multi-head attention mechanism to extract features of interference information at different times and of different types, identify the correlation between environmental disturbances, and through the forward propagation process of the model, output a dynamic attenuation coefficient for clamping force correction. This dynamic attenuation coefficient numerically reflects the degree of influence that each interference factor may have on the clamping accuracy under the current environmental conditions, serving as an important basis for the subsequent cylinder adjustment module to dynamically adjust the clamping force.

[0030] For the interference compensation model, the sample vibration spectrum of the positioning plate, the sample volatility of the pneumatic pipeline, and the sample temperature gradient field are divided into a training set and a validation set, and then labeled using the corresponding sample dynamic attenuation coefficients. After the data preparation is completed, a Transformer is used to construct an interference compensation model structure, including an input layer, a multi-head self-attention mechanism, a feed-forward network, an output layer, etc. Then, the weights of the Transformer model are initialized using the random initialization method, and the training set is input into the initialized interference compensation model for forward propagation. The data is passed layer by layer through the input layer, the multi-head self-attention mechanism, the feed-forward network, and the output layer to generate a prediction result of the dynamic attenuation coefficient. Subsequently, the mean square error (MSE) loss function is used to calculate the loss value between the prediction result and the sample dynamic attenuation coefficient, and the gradient of the loss with respect to the weights of each layer is calculated layer by layer through the backpropagation algorithm. Then, the Adam optimizer is used to optimize the model parameters and adjust the weights to minimize the value of the loss function. Through batch training, the above process is repeated until the maximum number of iterations is reached or the loss function converges. After the training is completed, the validation set is used to verify the model performance and evaluate the accuracy of the model in the dynamic attenuation coefficient prediction task. If the error of the prediction result reaches the expectation, the current interference compensation model is output as the final model. Otherwise, hyperparameters such as the learning rate, batch size, and number of training epochs are adjusted to further optimize the prediction accuracy of the model and improve the interference compensation ability.

[0031] The cylinder adjustment module 14 is used to dynamically adjust the opening degree of the multi-stage buffer valve and the servo supercharging rate of the automated cylinder group through an adaptive control strategy according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient until the clamping force error is stabilized within a preset threshold.

[0032] Specifically, in the cylinder adjustment module 14, after obtaining the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient, an adaptive control strategy is obtained. This adaptive control strategy records how to dynamically adjust the valve opening degree according to the target pressure sequence and how to plan the servo supercharging rate according to the deformation offset risk value and the dynamic attenuation coefficient. The system dynamically adjusts the control parameters of the cylinder group through this adaptive control strategy, including the opening degree of the multi-stage buffer valve and the servo supercharging rate. Among them, the buffer valve is used to adjust the flow rate and pressure of the air flow inside the cylinder. By adjusting its opening degree, the reaction speed and stability of the cylinder are controlled to avoid too fast or too slow clamping processes. The adjustment amount of the opening degree of the buffer valve is calculated from the difference between the target pressure value and the actual pressure value and is used to guide the fuzzy control algorithm to dynamically adjust the valve opening in real time. Thus, in the process of the clamping force gradually approaching the target value, the relationship between the air flow response speed and the clamping stability is balanced; the servo supercharging rate controls the change rate of the cylinder pressure. By adjusting the supercharging rate, it is ensured that the cylinder group reaches the preset target pressure within a stable time. Specifically, according to this adjustment amount, the deformation offset risk value, and the dynamic attenuation coefficient, a gradient path of pressure change is planned, which is manifested as a gradual decrease in the change amplitude of the supercharging rate to cope with the clamping force fluctuations caused by environmental interference or workpiece stress changes and ensure that the clamping process has continuity and flexible response capabilities. After the adjustment starts, the system continuously monitors the clamping force and adjusts the valve opening degree and the supercharging rate through real-time feedback until the clamping force error is stabilized within the preset threshold to ensure that the clamping force during the clamping process is accurate and uniform and the deformation risk is minimized to the greatest extent. In summary, the opening degree of the buffer valve and the servo supercharging rate are used as two coupled control variables. The former controls the instantaneous gas flow, and the latter controls the cumulative pressure change. Driven by the adaptive control strategy, the two are linked and adjusted together to gradually approach the target clamping state.

[0033] Further, based on the difference between the target pressure sequence and the actual pressure value, the adjustment amount of the opening degree of the multi-stage buffer valve is determined and the fuzzy control algorithm is used to dynamically adjust the valve opening degree; according to the adjustment amount of the opening degree of the multi-stage buffer valve, combined with the deformation offset risk value and the dynamic attenuation coefficient, the gradient change path of the servo supercharging rate is planned.

[0034] In an alternative embodiment, the difference between the target pressure value and the actual pressure value in the target pressure sequence is calculated. The target pressure sequence is determined according to the workpiece and the clamping requirements, while the actual pressure value is measured in real time by a pressure sensor. The difference between the two is the pressure error, which reflects the deviation between the current clamping force and the target clamping force. Then, the calculated pressure error is input into the opening adjustment amount calculation formula to obtain the opening adjustment amount of the multi-stage buffer valve. Subsequently, the calculated opening adjustment amount of the multi-stage buffer valve is used as the input signal of the fuzzy control algorithm. The fuzzy control algorithm first converts the opening adjustment amount into a fuzzy set, usually including fuzzy terms such as "increase", "decrease", or "remain unchanged". The fuzzy control rule base will determine the adjustment method of the valve opening according to the magnitude and change trend of the opening adjustment amount. For example, when the opening adjustment amount is large and changes rapidly, the fuzzy control algorithm may choose to quickly increase the valve opening. If the opening adjustment amount is small or changes slowly, it may choose to adjust gradually. In the fuzzy reasoning process, the fuzzy control algorithm will combine the empirical rules in the control rule base and comprehensively consider factors such as the change speed of the opening adjustment amount and the response characteristics of the valve opening to deduce a suitable valve opening adjustment amount. This adjustment amount is converted into a specific control signal through defuzzification to adjust the valve opening, so that the pressure of the cylinder group can smoothly approach the target value. While determining the opening adjustment amount of the buffer valve, the servo boost rate is planned in combination with the deformation offset risk value and the dynamic attenuation coefficient. Specifically, first, the preliminary servo boost rate is determined according to the opening adjustment amount of the buffer valve and the deformation offset risk value. If the deformation offset risk value is high, the boost rate will be slowed down to reduce the risk of workpiece deformation and avoid over-clamping. On the contrary, if the deformation risk is low, a higher boost rate will be selected to accelerate the clamping process. Subsequently, in combination with the dynamic attenuation coefficient, the change path of the boost rate is adjusted. The dynamic attenuation coefficient reflects the influence of environmental factors. The system dynamically adjusts the boost rate according to factors such as the current air pressure fluctuation and temperature gradient. If the environmental interference is strong (for example, the air pressure fluctuation is large), the change amplitude of the boost rate will be reduced to ensure the stability of the clamping process. If the environment is relatively stable, the boost rate can be allowed to increase rapidly. Then, based on these factors, a gradient change path of the boost rate is calculated. This path defines how the boost rate changes during the entire clamping process. The change path of the boost rate can be gradually increasing, gradually decreasing, or adjusted as needed to ensure that the clamping force gradually stabilizes to the target value and remains within the preset error range. Through the above steps, adaptive pressure regulation and precise clamping force control are achieved, which can cope with complex environmental changes and ensure the stability, accuracy, and efficiency of the clamping process.

[0035] Further, the opening adjustment amount of the multi-stage buffer valve Calculation formula: ; where is the proportionality coefficient, is the integral coefficient, is the target pressure value, is the actual pressure value.

[0036] In a feasible implementation manner, the calculation formula for the opening adjustment amount is specifically as follows: ; where is the opening adjustment amount; is the proportionality coefficient, controlling the proportional relationship between the opening adjustment and the pressure error; is the integral coefficient, responsible for dealing with the cumulative error and further optimizing the adjustment process; is the target pressure value; is the current actual pressure value. The calculation formula for the opening adjustment amount dynamically calculates the opening of the buffer valve to ensure that the pressure during the clamping process gradually approaches the target value.

[0037] Furthermore, collect the positioning hole diameter of the positioning plate, perform associated mapping based on the positioning hole diameter of the positioning plate, and extract the temperature gradient field distribution characteristics; based on the temperature gradient field distribution characteristics, dynamically adjust the response threshold of the automatic cylinder group with stability as the goal, and perform a unidirectional decreasing correction on the gradient change path of the servo boosting rate.

[0038] In a feasible implementation, the positioning aperture data of the round holes on the positioning plate is collected. This aperture data is generally from 10.00 mm to 10.005 mm, and is used to determine the precise position and stability of the positioning plate in the cylinder. The size and distribution of the positioning holes will affect the clamping process of the cylinder. Therefore, according to the size of these positioning holes, through correlation mapping, it is associated with the distribution characteristics of the temperature gradient field to obtain the distribution characteristics of the temperature gradient field. The purpose of this step is to understand how temperature changes affect the clamping state of the positioning holes and the workpiece, because the change of the temperature gradient field will cause the material to expand or contract, thus affecting the clamping force. Specifically, a larger positioning aperture will result in an increase in the gap between the workpiece and the fixture, a decrease in the system stiffness, and a response lag and weakening of the force feedback during the application of the clamping force; while a smaller aperture enhances the positioning accuracy, but is more likely to form local stress concentration when the temperature rises, resulting in clamping deformation. These mechanical property changes caused by the aperture change will be transmitted to the servo control module in the form of clamping error or unstable clamping response. For this reason, the positioning aperture is used as an index parameter for structural rigidity and thermal deformation sensitivity, and is embedded in the decision-making logic of the servo boost control to adjust the correlation function between the response threshold and the boost rate, thereby constructing a closed-loop adjustment path between the structural size - environmental interference - pressure control. Subsequently, the distribution characteristics of the temperature gradient field are used to evaluate the stability of the overall clamping state. Temperature changes will affect the clamping force. Especially in a high-temperature environment, it may cause excessive expansion or stress concentration, affecting the clamping accuracy. By analyzing the temperature change characteristics, the system dynamically adjusts the response threshold of the automatic cylinder group according to the actual situation of the temperature gradient field to cope with the change of the clamping force under different temperature conditions. The response threshold refers to the tolerance of the cylinder to the pressure change under specific temperature conditions. When the temperature gradient is large, the response threshold will be lowered to avoid unstable clamping force caused by temperature fluctuations. Finally, based on these temperature characteristics and response adjustments, a one-way decreasing correction is started on the gradient change path of the servo boost rate. The servo boost rate determines the rate of change of the internal pressure of the cylinder. If the boost rate is too fast, it may cause an overreaction of the system or workpiece deformation, especially in an environment with large temperature fluctuations. To avoid this situation, through the one-way decreasing correction, the change of the boost rate becomes smoother. That is to say, the system will slow down the change of the boost rate when the temperature changes greatly to avoid workpiece deformation or unstable clamping force caused by too fast boosting, ensure that the pressure gradually approaches the target value, thereby ensuring the clamping stability while effectively controlling the response of the cylinder group and ensuring a smooth transition and precise control of the clamping process.

[0039] Table 1: Positioning Hole - Temperature Gradient Table Positioning aperture (mm) Temperature (°C) Temperature gradient (°C) Response threshold adjustment (bar / °C) Servo boost rate (bar / s) Final clamping force (N) 10.002 30 2 3 1.2 9.8 10.003 35 3 2.8 1.1 10.2 10.001 40 4 3.2 0.9 9.6 10.004 45 5 3 0.8 10 10.005 50 6 3.5 0.7 9.9 Among them, the table shows data such as positioning aperture, temperature, temperature gradient, response threshold, pressurization rate, and clamping force. These data are used to evaluate the influence of temperature on the clamping state and dynamically adjust the response of the cylinder system according to these factors to ensure the stability of the clamping force.

[0040] Furthermore, collect the waist-shaped positioning aperture of the positioning plate, decouple the parameters of the long axis length, short axis length, and the angle between the long axis direction of the waist-shaped positioning hole parameters and the force direction of the workpiece to be clamped, and establish a mapping relationship of the clamping force distribution; according to the mapping relationship of the clamping force distribution, fit the influence coefficient of the waist-shaped positioning hole parameters on the pressure distribution to obtain the reference pressure correction amount of each execution unit in the automatic cylinder group.

[0041] In a feasible implementation, collect data of the waist-shaped positioning aperture, including the long axis length, short axis length, and its long axis direction of the waist-shaped positioning hole. Among them, the long axis length refers to the maximum diameter of the waist-shaped hole, representing the longest part of the hole; the short axis length refers to the shortest diameter of the waist-shaped hole, representing the shortest part of the hole; the long axis direction refers to the direction pointed by the maximum diameter of the waist-shaped hole, usually represented by an angle or a direction vector in the coordinate system. The system decouples the angle between these geometric parameters of the waist-shaped positioning hole and the force direction of the workpiece to be clamped, that is, transforms the long axis length, short axis length, and long axis direction into several independent variables (for example, the angle between the long axis direction and the force direction), and expresses their mutual relationship with a mathematical formula. The purpose of this step is to transform the complex geometric and mechanical relationships into parameters that can be quantified and optimized, so that the system can more accurately control the clamping force. The decoupling process can usually be solved by mathematical methods such as matrix transformation or linear regression, so as to obtain the influence of the waist-shaped positioning hole parameters on the force of the workpiece, in order to further optimize the clamping force distribution. Exemplarily, construct a linear regression equation, , where, , , , are the coefficients to be fitted, representing the influence degree of each parameter on the clamping force, is the constant term (intercept) used to correct the deviation. In order to perform linear regression, a set of experimental data needs to be collected. These data include the long axis length (a), short axis length (b), long axis direction (θ), force direction ( ), and the corresponding clamping force (F). These data can be obtained through experimental measurement. Record each parameter and the corresponding clamping force, and then use the least squares method to perform linear regression fitting to obtain the coefficients , , , and the constant term , the goal of the least squares method is to minimize the difference between the actual value and the predicted value of the clamping force. Subsequently, based on the above decoupling results, a clamping force distribution mapping relationship is established. This mapping relationship reflects how the geometric parameters of the waist-shaped positioning holes affect the clamping force at various parts of the workpiece. Different waist-shaped positioning hole parameters (such as the lengths and directions of the major and minor axes) will result in different mechanical distributions, thereby affecting the uniformity of the clamping force and the stability of the workpiece. Then, according to the clamping force distribution mapping relationship, the influence coefficient of the waist-shaped positioning hole parameters on the pressure distribution is further fitted. This fitting process determines the linear or nonlinear relationship between the major axis direction, major axis length, minor axis length, and pressure through a regression model. Further, to connect the structural characteristics and control behavior in a closed loop, the above fitting coefficient is introduced as an influencing factor in the servo boost control logic to form a mapping function of "waist-shaped hole parameter - clamping error - control compensation". When a difference is detected between the structural characteristics of the waist-shaped positioning hole (such as the major axis direction or eccentricity) and the current clamping target, the change curve of the servo boost rate will be automatically adjusted. For example, when the major axis direction deviates significantly from the force direction, it is recognized that there is a risk of asymmetry in the clamping area. At this time, the initial boost speed will be reduced and the pressure stabilization time will be extended to avoid workpiece rotation or deformation caused by asymmetric clamping. This servo control adjustment strategy is executed based on the real-time feedback of the structural parameters and is the core bridge between the pressure correction amount and the actual control curve, thereby enhancing the dynamic response accuracy and environmental adaptability of the clamping system. Finally, the difference between the target clamping force value and the current clamping force in the clamping force distribution mapping relationship is calculated, and then the calculation result is divided by the influence coefficient to calculate the reference pressure correction amount for each execution unit. The reference pressure correction amount is used to adjust the target pressure values of each execution unit in the automated cylinder group to ensure that the pressure of each unit in the cylinder group is evenly distributed during the clamping process, thereby improving the clamping accuracy and stability. In this way, the clamping force can be accurately corrected according to the parameters of the waist-shaped positioning holes to ensure the stability and accuracy of the workpiece during the clamping process.

[0042] In summary, the automated cylinder clamping system provided by the embodiments of the present application has the following technical effects: The clamping force distribution map formulation module 11 is configured to obtain structural basic features including surface topography features and workpiece size features based on the workpiece to be clamped, and formulate a three-dimensional clamping force distribution map with the material hardness data as a constraint condition; the risk prediction module 12 is configured to match the target pressure sequence of each execution unit in the automated cylinder group based on the three-dimensional clamping force distribution map, and simultaneously predict the deformation offset risk value during the clamping process; the model calculation module 13 is configured to introduce environmental interference factors and input them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, where the environmental interference factors include the vibration spectrum of the positioning plate, the air pressure pipeline volatility, and the temperature gradient field; the cylinder adjustment module 14 is configured to dynamically adjust the opening degree of the multi-stage buffer valve and the servo boosting rate of the automated cylinder group through an adaptive control strategy according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient until the clamping force error is stabilized within a preset threshold. Through the above steps, the technical problems of unstable clamping force and low workpiece clamping accuracy caused by environmental interference and system errors during the clamping process of the automated cylinder are solved, and the technical effects of improving the clamping force stability, reducing the deformation risk, and enhancing the clamping accuracy through dynamic compensation and adaptive adjustment are achieved.

[0043] Embodiment 2, based on the same inventive concept as the automated cylinder clamping system in the foregoing embodiment, as Figure 2 shown, the embodiment of the present application provides an automated cylinder clamping method, and the method includes: Based on the workpiece to be clamped, obtain structural basic features including surface topography features and workpiece size features, and formulate a three-dimensional clamping force distribution map with the material hardness data as a constraint condition; based on the three-dimensional clamping force distribution map, match the target pressure sequence of each execution unit in the automated cylinder group, and simultaneously predict the deformation offset risk value during the clamping process; introduce environmental interference factors and input them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, where the environmental interference factors include the vibration spectrum of the positioning plate, the air pressure pipeline volatility, and the temperature gradient field; according to the target pressure sequence, the deformation offset risk value, and the dynamic attenuation coefficient, dynamically adjust the opening degree of the multi-stage buffer valve and the servo boosting rate of the automated cylinder group through an adaptive control strategy until the clamping force error is stabilized within a preset threshold.

[0044] Further, the method includes: Obtain the structural basic features of the workpiece to be clamped, and use an ultrasonic flaw detector to detect the material hardness data; fuse the structural basic features and the material hardness data, and set a three-dimensional clamping force distribution map, where the three-dimensional clamping force distribution map includes at least three clamping force gradient partitions.

[0045] Further, the method includes: According to the clamping force gradient partition of the three-dimensional clamping force distribution atlas, the automated cylinder group is divided into multiple execution units corresponding to the corresponding number, and each execution unit corresponds to a clamping force gradient partition; for the multiple execution units in the automated cylinder group, in combination with the force density requirements of the spatial position and the gradient partition, the target pressure value of each execution unit is configured to obtain a target pressure sequence.

[0046] Further, the method includes: Taking the clamping force uniformity, the load balance of the execution unit, and the energy consumption efficiency as the optimization objectives, introducing the local curvature of the surface topography features as a weight correction factor to optimize the configuration of the target pressure value; at the same time, based on the historical clamping data, a finite element analysis model is constructed in comparison with the three-dimensional clamping force distribution atlas; the stress-strain distribution in the clamping state is simulated by the finite element analysis model, the deformation offset risk value is quantified, and it is judged whether to trigger the pressure compensation mechanism, and the pressure compensation mechanism is used to dynamically correct the target pressure sequence.

[0047] Further, the method includes: Perform data noise reduction preprocessing on the positioning plate vibration spectrum, the air pressure pipeline volatility, and the temperature gradient field in the environmental interference factors to obtain preprocessed data; based on the preprocessed data, use the interference compensation model under the Transformer architecture to generate a dynamic attenuation coefficient.

[0048] Further, the method includes: Based on the difference between the target pressure sequence and the actual pressure value, determine the opening adjustment amount of the multi-stage buffer valve, and dynamically adjust the valve port opening using the fuzzy control algorithm; according to the opening adjustment amount of the multi-stage buffer valve, in combination with the deformation offset risk value and the dynamic attenuation coefficient, plan the gradient change path of the servo boosting rate.

[0049] Further, the method includes: The opening adjustment amount of the multi-stage buffer valve Calculation formula: ; where is the proportionality coefficient, is the integral coefficient, is the target pressure value, is the actual pressure value.

[0050] Further, the method includes: Collect the positioning hole diameter of the positioning plate, perform associated mapping with the positioning hole diameter of the positioning plate, and extract the temperature gradient field distribution characteristics; based on the temperature gradient field distribution characteristics, dynamically adjust the response threshold of the automated cylinder group with stability as the goal, and perform a unidirectional decreasing correction on the gradient change path of the servo boosting rate.

[0051] Further, the method includes: Collect the waist-shaped positioning hole diameters of the positioning plate, decouple the parameters of the major axis length, minor axis length, and the angle between the major axis direction of the waist-shaped positioning hole parameters and the force direction of the workpiece to be clamped, and establish a mapping relationship of the clamping force distribution; according to the mapping relationship of the clamping force distribution, fit the influence coefficient of the waist-shaped positioning hole parameters on the pressure distribution, and obtain the reference pressure correction amount of each execution unit in the automatic cylinder group.

[0052] Any step of the method described above can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor to implement any one of the methods in the embodiments of the present application, without further limitation here.

[0053] Furthermore, the first or second described above may not only represent an order relationship, but may also represent a certain specific concept, and / or refer to the selection of multiple elements individually or in whole. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and variations.

Claims

1. Automated cylinder clamping system, characterized in that: include: A map drawing module is used to obtain the structural basic features including surface morphology features and workpiece size features based on the workpiece to be clamped, and to draw up a three-dimensional clamping force distribution map with material hardness data as a constraint condition; A risk prediction module, used to match the target pressure sequence of each execution unit in the automated cylinder group based on the three-dimensional clamping force distribution map, and simultaneously predict the deformation offset risk value during the clamping process; A model calculation module is used to introduce environmental interference factors and input them into a pre-trained interference compensation model to generate a dynamic attenuation coefficient, wherein the environmental interference factors include a positioning plate vibration spectrum, an air pressure pipeline fluctuation rate, and a temperature gradient field; The cylinder adjustment module is used to dynamically adjust the multi-stage buffer valve opening and servo boost rate of the automated cylinder group through an adaptive control strategy according to the target pressure sequence, deformation offset risk value and dynamic attenuation coefficient until the clamping force error is stabilized within a preset threshold.

2. The automated cylinder clamping system according to claim 1, characterized in that: Using the material hardness data as a constraint, a three-dimensional clamping force distribution map is developed, including: Obtain the basic structural features of the workpiece to be clamped, and use an ultrasonic flaw detector to detect the material hardness data; The structural basic features are integrated with the material hardness data to set a three-dimensional clamping force distribution map, wherein the three-dimensional clamping force distribution map includes at least three clamping force gradient partitions.

3. The automated cylinder clamping system according to claim 2, characterized in that: Based on the three-dimensional clamping force distribution map, the target pressure sequence of each execution unit in the automated cylinder group is matched, including: According to the clamping force gradient partition of the three-dimensional clamping force distribution map, the automated cylinder group is divided into a corresponding number of multiple execution units, each execution unit corresponds to a clamping force gradient partition; For multiple actuators in the automated cylinder group, the target pressure value of each actuator is configured in combination with the force density requirements of the spatial position and gradient partition to obtain the target pressure sequence.

4. The automated cylinder clamping system according to claim 3, characterized in that: Taking the uniformity of clamping force, load balance of actuators and energy efficiency as optimization targets, the local curvature of the surface morphology is introduced as a weight correction factor to optimize the configuration of the target pressure value. At the same time, based on the historical clamping data and in comparison with the three-dimensional clamping force distribution map, a finite element analysis model is constructed; The finite element analysis model is used to simulate the stress-strain distribution in the clamping state, quantify the deformation offset risk value, and determine whether to trigger the pressure compensation mechanism, which is used to dynamically correct the target pressure sequence.

5. The automated cylinder clamping system according to claim 4, characterized in that: Environmental interference factors are introduced and input into the pre-trained interference compensation model to generate dynamic attenuation coefficients, including: Performing data noise reduction preprocessing on the positioning plate vibration spectrum, air pressure pipeline fluctuation rate and temperature gradient field in the environmental interference factors to obtain preprocessed data; Based on the preprocessed data, a dynamic attenuation coefficient is generated using an interference compensation model under a Transformer architecture.

6. The automated cylinder clamping system according to claim 5, characterized in that: include: Based on the target pressure sequence, the difference between the target pressure sequence and the actual pressure value is used to determine the opening adjustment amount of the multi-stage buffer valve. , the fuzzy control algorithm is used to dynamically adjust the valve opening; According to the opening adjustment of the multi-stage buffer valve , combined with the deformation offset risk value and the dynamic attenuation coefficient, the gradient change path of the servo boost rate is planned.

7. The automated cylinder clamping system according to claim 6, characterized in that: The opening adjustment amount of the multi-stage buffer valve The calculation formula is: ； in, is the proportionality coefficient, is the integration coefficient, is the target pressure value, is the actual pressure value.

8. The automated cylinder clamping system according to claim 6, characterized in that: Collecting the positioning aperture of the circular hole of the positioning plate, performing correlation mapping with the positioning aperture of the circular hole of the positioning plate, and extracting the distribution characteristics of the temperature gradient field; Based on the temperature gradient field distribution characteristics, the response threshold of the automated cylinder group is dynamically adjusted with stability as the goal, and a unidirectional decreasing correction is performed on the gradient change path of the servo boost rate.

9. The automated cylinder clamping system according to claim 8, characterized in that: The diameter of the waist-shaped positioning hole of the positioning plate is collected, and the major axis length, minor axis length and major axis direction of the waist-shaped positioning hole parameters are parametrically decoupled from the angle of the force direction of the workpiece to be clamped, and a clamping force distribution mapping relationship is established; According to the clamping force distribution mapping relationship, the influence coefficient of the waist-shaped positioning hole parameters on the pressure distribution is fitted to obtain the reference pressure correction value of each execution unit in the automated cylinder group.

10. Automated cylinder clamping method, characterized in that: The method is performed by the automated cylinder clamping system according to any one of claims 1 to 9, comprising: Based on the workpiece to be clamped, the structural basic features including surface morphology and workpiece size features are obtained, and the three-dimensional clamping force distribution map is formulated with the material hardness data as the constraint condition; Based on the three-dimensional clamping force distribution map, the target pressure sequence of each actuator in the automated cylinder group is matched, and the deformation offset risk value during the clamping process is simultaneously predicted; Introducing environmental interference factors and inputting them into the pre-trained interference compensation model to generate a dynamic attenuation coefficient, wherein the environmental interference factors include the vibration spectrum of the positioning plate, the fluctuation rate of the air pressure pipeline, and the temperature gradient field; According to the target pressure sequence, deformation offset risk value and dynamic attenuation coefficient, the multi-stage buffer valve opening and servo boost rate of the automated cylinder group are dynamically adjusted through an adaptive control strategy until the clamping force error is stabilized within a preset threshold.

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