Rolling control method and system for ultrathin foil

Abstract

The invention discloses a rolling control method and system for ultrathin foils, and relates to the field of precise rolling of the ultrathin foils, and the rolling control method comprises the following steps: collecting incoming basic parameters of the ultrathin foils, and setting a rolling process target; based on basic parameters of supplied materials, initial crystal texture information of the ultrathin foil is measured by using an online X-ray diffractometer, and the initial crystal texture information is input into a crystal plasticity rapid calculation model to predict a plate shape defect map and a transverse friction unevenness distribution cloud map; according to the plate shape defect atlas and the transverse friction unevenness distribution cloud atlas, a rolling mill executing mechanism and a lubricating unit are pre-adjusted; the ultrathin foil enters a roll gap to be rolled, and the rolling process is subjected to basic control through an automatic thickness control unit and an automatic tension control unit; according to the invention, the crossing from passive feedback to active predictive regulation is realized, and the rolling precision, stability and yield of the ultrathin foil are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of precision rolling of ultrathin foil materials, and in particular to a method and system for controlling the rolling pressure of ultrathin foil materials. Background Technology

[0002] In the field of precision rolling of ultrathin foil, the current mainstream technology is a multivariable feedback system with automatic thickness control and automatic shape control as its core. This system relies on the thickness gauge and shape gauge at the mill exit to detect the geometric dimensions of the strip in real time, and dynamically adjusts the roll pressing, bending, and other mechanisms through PID and other control algorithms to stabilize the thickness and shape of the finished product. It is effective in suppressing conventional fluctuations and is the foundation of industrial production.

[0003] However, when the foil thickness enters the micrometer level, the control mode based on exit geometry feedback reveals its fundamental limitations. The problem is that it cannot sense and respond to the changes in the intrinsic physical state that determine the rolling quality and safety. The deformation behavior and limits of ultrathin foils are heavily dependent on intrinsic factors such as their microcrystalline texture and the friction state of the roll gap interface. Existing technologies can only compensate after macroscopic defects appear, which is a post-event remedy. It is impossible to predict the tendency of plate shape defects caused by its anisotropy before the material enters the roll gap, nor can it quantify the risk of local stress concentration and fracture caused by uneven friction in real time. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a rolling control method for ultrathin foil materials, which solves the core problem of insufficient perception of the internal physical state in the prior art, resulting in control lag.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a rolling control method for ultrathin foil materials, which includes collecting the basic parameters of the incoming ultrathin foil materials and setting rolling process targets; Based on the basic parameters of the incoming material, the initial crystal texture information of the ultrathin foil is measured using an online X-ray diffractometer. The initial crystal texture information is then input into a rapid crystal plasticity calculation model to predict the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. Based on the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map, the mill actuator and lubrication unit are pre-adjusted. The ultrathin foil material enters the roll gap for rolling, and the rolling process is basically controlled by an automatic thickness control unit and an automatic tension control unit. The rolling process parameters are collected and combined with the local stress-strain state and transverse friction non-uniformity distribution cloud map calculated by the crystal plasticity rapid calculation model. The parameters are then input into the toughness fracture criterion formula to calculate the real-time damage accumulation value and assess the fracture risk. Based on the assessment results, the rolling mill process parameters and lubrication parameters are dynamically adjusted. The real-time plate shape distribution data of the rolled ultrathin foil was measured using a plate shape meter. The actual interface friction state distribution was calculated based on the lateral distribution of rolling force and the inversion of the roll vibration spectrum. The real-time plate shape distribution data was compared with the plate shape defect spectrum, and the actual interface friction state distribution was verified with the lateral friction non-uniformity distribution cloud map. Based on the comparison and verification results, the parameters of the rapid calculation model for crystal plasticity were self-learned and corrected. The rolled and verified ultrathin foil is wound up by a winding machine to obtain the finished ultrathin foil.

[0007] As a preferred embodiment of the rolling control method for the ultrathin foil material described in this invention, the following steps are included: collecting the basic parameters of the incoming ultrathin foil material and setting the rolling process target: Set the target exit thickness, target tension, and target sheet shape for ultrathin foil rolling in the control interface; Based on the set target exit thickness, target tension and target plate shape, start the rolling mill production line to unwind and thread the ultra-thin foil strip; During the unwinding and threading process of ultra-thin foil strip, the thickness gauge, tension meter and speed measuring instrument at the inlet section collect the inlet thickness, inlet tension and running speed of the incoming material to obtain the basic parameters of the incoming ultra-thin foil. The rolling process targets are set based on the inlet thickness, inlet tension, and running speed, along with the target outlet thickness, target tension, and target shape.

[0008] As a preferred embodiment of the rolling control method for the ultrathin foil described in this invention, the method includes: based on the basic parameters of the incoming material, measuring the initial crystal texture information of the ultrathin foil using an online X-ray diffractometer, inputting the initial crystal texture information into a rapid crystal plasticity calculation model to predict the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map, and pre-adjusting the rolling mill actuator and lubrication unit according to the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map, including the following steps: Based on the incoming material parameters, an online X-ray diffractometer is triggered to rapidly scan the surface of the moving ultrathin foil to obtain the initial crystal texture information of the ultrathin foil. Based on the initial crystal texture information of the ultrathin foil obtained by online X-ray diffraction, the initial crystal texture information is transmitted to a pre-built and calibrated fast calculation model of crystal plasticity; The initial crystal texture information is calculated based on the crystal plasticity fast calculation model. According to the crystal plasticity theory, the slip behavior of different grain orientations in rolling deformation is simulated. The output is a plate shape defect map reflecting the difference in transverse flow resistance and a transverse friction non-uniformity distribution cloud map that quantitatively describes the relative slip trend of the contact surface. Based on the plate shape defect map and the transverse friction non-uniformity distribution cloud map, the plate shape adjustment requirements inferred from the plate shape defect map and the friction control requirements indicated by the transverse friction non-uniformity distribution cloud map are combined to calculate the pre-adjustment parameters for the rolling mill actuator and the pre-adjustment parameters for the lubrication unit. The pre-adjustment intervention degree for the current ultrathin foil strip is obtained by comprehensively calculating the normalized offset of the pre-adjustment parameters relative to the reference parameters. The pre-adjustment parameters for the mill actuator and the lubrication unit are sent to the mill actuator and the lubrication unit, so that the pre-adjustment of the mill actuator and the lubrication unit with pre-adjustment intervention degree can be obtained before the ultra-thin foil enters the roll gap.

[0009] As a preferred embodiment of the rolling control method for the ultrathin foil material described in this invention, the ultrathin foil material enters the roll gap for rolling, and the rolling process is basically controlled by an automatic thickness control unit and an automatic tension control unit, including the following steps: Based on the pre-adjusted mill actuator and lubrication unit, the ultra-thin foil enters the roll gap for rolling; During the rolling process of ultra-thin foil entering the roll gap, the automatic thickness control unit adjusts the roll pressing position based on the target exit thickness and the feedback signal from the exit thickness gauge. The feedback control loop of the thickness automatic control unit and the tension automatic control unit operates based on the initial process parameters set by the pre-adjustment intervention degree.

[0010] As a preferred embodiment of the rolling control method for the ultrathin foil material described in this invention, the method includes: collecting rolling process parameters, combining the rolling process parameters with the local stress-strain state and transverse friction non-uniformity distribution cloud map calculated by the crystal plasticity rapid calculation model, inputting them into the toughness fracture criterion formula to calculate the real-time damage accumulation value and assess the fracture risk, and dynamically adjusting the rolling mill process parameters and lubrication parameters based on the assessment results, including the following steps: The rolling process continues, collecting rolling force, front tension, back tension and rolling speed of the object to obtain rolling process parameters. The local stress and strain state corresponding to the current rolling state is obtained from the continuously running crystal plasticity rapid calculation model. Based on the correlation statistical analysis of the friction non-uniformity value and the fracture location in historical rolling data, a friction non-uniformity threshold is set. Based on rolling process parameters, local stress and strain state, and transverse friction non-uniformity distribution cloud map, areas in the transverse friction non-uniformity distribution cloud map where the friction non-uniformity value exceeds the friction non-uniformity threshold are identified as high-risk areas. The frictional stress derived from the local stress-strain state, pre-adjustment intervention degree, and lateral friction non-uniformity distribution cloud map is linearly superimposed to form a stress state correction function, which corrects the local stress state in high-risk areas and quantifies the additional impact of pre-adjustment operation on the local stress state. Based on the corrected stress tensor, hydrostatic pressure and equivalent stress are obtained through tensor calculation. The corrected stress triaxiality is obtained by dividing the hydrostatic pressure by the equivalent stress. Based on mechanical tests of ultrathin foil under different local stress states, the relationship between fracture strain data and corresponding local stress state parameters was obtained by fitting the test results, and the benchmark fracture strain scaling factor, deviatoric stress asymmetry shape parameter and stress triaxiality sensitivity scale parameter were calibrated. In the actual rolling process, the strain increment calculated by the crystal plasticity fast calculation model is used to calculate the damage increment by substituting the corrected stress triaxiality, Lode angle parameter, strain increment, reference fracture strain scaling factor, deviatoric stress asymmetry shape parameter and stress triaxiality sensitivity scale parameter into the ductile fracture criterion formula. The local stress state and current strain increment of the high-risk area are analyzed by the ductile fracture criterion to obtain the damage increment of the corrected stress triaxiality. Based on the damage increment of the corrected stress triaxiality, the high-risk area is continuously accumulated during the rolling process to obtain the real-time damage accumulation value of the high-risk area. Mechanical property tests were conducted on ultrathin foils under different stress states to calibrate critical damage values. Based on the statistical distribution of safety and fracture cases in historical rolling data, fracture thresholds were set. When the real-time cumulative damage value exceeds the fracture threshold, a fracture risk is determined. Based on the fracture risk assessment result, instructions for dynamically adjusting the mill process parameters and lubrication parameters are generated. The generated instructions for dynamically adjusting the rolling mill process parameters and lubrication parameters are issued and executed to dynamically adjust the rolling mill process parameters and lubrication parameters.

[0011] As a preferred embodiment of the rolling control method for the ultrathin foil material described in this invention, the method includes: measuring the real-time shape distribution data of the rolled ultrathin foil material using a shape meter; calculating the actual interface friction state distribution based on the lateral distribution of rolling force and the inversion of the roll vibration spectrum; comparing the real-time shape distribution data with the shape defect map; verifying the actual interface friction state distribution with the lateral friction non-uniformity distribution cloud map; and performing parameter self-learning correction on the rapid calculation model of crystal plasticity based on the comparison and verification results, including the following steps: The real-time shape distribution data of the ultrathin foil was obtained by measuring the shape distribution data of the ultrathin foil after rolling using a shape measuring instrument; the lateral distribution data of rolling force was obtained from the rolling mill control record, and the roll vibration spectrum was extracted from the vibration sensor signal; By collecting a large amount of rolling force, vibration and friction data under known lubrication conditions during the commissioning phase and training a neural network, a mapping relationship of the actual interface friction state distribution was established. Based on the transverse distribution data of rolling force and the vibration spectrum of rolls, the actual interface friction state distribution is calculated by inverting the mapping relationship of the actual interface friction state distribution. By comparing real-time plate shape distribution data with plate shape defect maps point by point, the plate shape prediction error is calculated. By comparing the actual interface friction state distribution with the transverse friction non-uniformity distribution cloud map point by point, the friction state prediction error is calculated. Based on the plate shape prediction error, friction state prediction error, and pre-adjustment intervention degree, the parameters of the rapid calculation model for crystal plasticity are self-learned and corrected to evaluate the short-term effects and long-term impacts of pre-adjustment intervention.

[0012] As a preferred embodiment of the rolling control method for the ultrathin foil of the present invention, the ultrathin foil that has completed rolling and verification is wound up by a winding machine to obtain the finished ultrathin foil, including the following steps: The rolled and verified ultrathin foil is conveyed to the winding machine station, where the winding machine winds up the rolled and verified ultrathin foil with constant tension. The winding machine unwinds the completed ultra-thin foil roll to obtain the finished ultra-thin foil roll.

[0013] Secondly, the present invention provides a rolling control system for ultrathin foil, including a data acquisition module for acquiring the basic parameters of the incoming ultrathin foil and setting the rolling process target; The pre-adjustment module, based on the incoming material parameters, uses an online X-ray diffractometer to measure the initial crystal texture information of the ultrathin foil. The initial crystal texture information is input into the crystal plasticity rapid calculation model to predict the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. The rolling mill actuator and lubrication unit are pre-adjusted according to the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. The control module, in which the ultrathin foil enters the roll gap for rolling, uses an automatic thickness control unit and an automatic tension control unit to perform basic control of the rolling process; The judgment module collects rolling process parameters, combines the rolling process parameters with the local stress-strain state and transverse friction non-uniformity distribution cloud map calculated by the crystal plasticity rapid calculation model, inputs them into the toughness fracture criterion formula to calculate the real-time damage accumulation value and judge the fracture risk, and dynamically adjusts the rolling mill process parameters and lubrication parameters according to the judgment results. The correction module uses a shape meter to measure the real-time shape distribution data of the rolled ultrathin foil. Based on the lateral distribution of rolling force and the inversion of the roll vibration spectrum, it calculates the actual interface friction state distribution. It compares the real-time shape distribution data with the shape defect map and verifies the actual interface friction state distribution with the lateral friction non-uniformity distribution cloud map. Based on the comparison and verification results, it performs parameter self-learning correction on the crystal plasticity rapid calculation model. The finished product module winds up the rolled and verified ultrathin foil material by a winding machine to obtain the finished ultrathin foil material.

[0014] Thirdly, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the rolling control method for ultrathin foil as described in the first aspect of the present invention.

[0015] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the rolling control method for ultrathin foil as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: Based on incoming material parameters and online crystal texture measurement, the crystal plasticity model is used to predict plate shape defects and friction distribution patterns, and feedforward pre-adjustment is performed on the mill actuator and lubrication system. During the rolling process, combined with real-time process parameters and local stress-strain state calculated by the model, the cumulative damage value is calculated in real time and the fracture risk is judged by the toughness fracture criterion. The process parameters are dynamically adjusted, and the measured plate shape and inverted friction data after rolling are compared and verified with the predicted values. The crystal plasticity model is self-learned and corrected, and the material micro-properties, interface friction state and macro-process control are deeply coupled, realizing the leap from passive feedback to active prediction and control, effectively improving the accuracy, stability and yield of ultra-thin foil rolling. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method for controlling the rolling process of ultra-thin foil materials.

[0019] Figure 2 This is a schematic diagram of the rolling control of ultra-thin foil materials.

[0020] Figure 3 This is a flowchart for parameter self-learning correction. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0024] Reference Figures 1-3 As one embodiment of the present invention, this embodiment provides a method for controlling the rolling of ultrathin foil, comprising the following steps: S1. Collect the basic parameters of the incoming ultrathin foil and set the rolling process target.

[0025] S1.1 Set the target exit thickness, target tension, and target plate shape for ultra-thin foil rolling in the control interface; Furthermore, on the human-machine interface of the main control console of the rolling mill, the operator can manually input or call up preset process specifications to set the target exit thickness, target tension, and target plate shape to be achieved in this rolling process. The target exit thickness specifies the final thickness that the ultra-thin foil should achieve after rolling, the target tension specifies the stable tension range that the ultra-thin foil needs to maintain during the rolling process, and the target plate shape specifies the flatness requirements of the transverse profile of the ultra-thin foil exit.

[0026] S1.2. Based on the set target exit thickness, target tension and target plate shape, start the rolling mill production line to unwind and thread the ultra-thin foil strip.

[0027] Furthermore, based on the set target exit thickness, target tension, and target strip shape, after the operator confirms that the parameters are correct, the start command of the rolling mill production line is triggered. After the start command is issued, the uncoiler starts to rotate, the ultra-thin foil strip is slowly unwound, and the strip head is guided into the rolling mill unit through the guide plate table and other threading devices to complete the threading process.

[0028] S1.3 During the unwinding and threading process of the ultra-thin foil strip, the thickness gauge, tension meter and speed meter at the inlet section collect the inlet thickness, inlet tension and running speed of the incoming material to obtain the basic parameters of the incoming ultra-thin foil.

[0029] Furthermore, during the unwinding and threading process of the ultra-thin foil strip, as the strip runs smoothly through the entry section, a thickness gauge installed in the entry section continuously measures the entry thickness of the strip, a tension meter continuously measures the entry tension of the strip, and a speed meter continuously measures the operating speed of the production line. The measurement actions are performed synchronously, and the real-time data of the entry thickness, entry tension, and operating speed are collected and summarized to form the basic parameters of the incoming ultra-thin foil. The basic parameters of the incoming material quantify the initial physical state of the ultra-thin foil strip before it enters the roll gap, providing an indispensable initial condition benchmark for subsequent rolling behavior prediction based on the crystal plasticity rapid calculation model, feedforward pre-adjustment of strip shape and friction state, and damage assessment.

[0030] S1.4. The rolling process target is set based on the inlet thickness, inlet tension, and running speed, along with the target outlet thickness, target tension, and target plate shape.

[0031] Furthermore, by integrating the inlet thickness, inlet tension, and running speed with the target outlet thickness, target tension, and target plate shape, the inlet parameters represent the initial state of the rolling process, while the target parameters represent the final state that the rolling process needs to achieve. The combination of these two sets of parameters is jointly established as the complete rolling process target for this rolling process.

[0032] S2. Based on the incoming material parameters, the initial crystal texture information of the ultrathin foil is measured using an online X-ray diffractometer. The initial crystal texture information is then input into the crystal plasticity rapid calculation model to predict the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. The mill actuator and lubrication unit are then pre-adjusted based on the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map.

[0033] S2.1 Based on the incoming material parameters, trigger an online X-ray diffractometer to rapidly scan the surface of the moving ultrathin foil to obtain the initial crystal texture information of the ultrathin foil.

[0034] Furthermore, based on the incoming material parameters, when the ultrathin foil roll reaches the online X-ray diffractometer measurement station, the online X-ray diffractometer is triggered to emit an X-ray beam of a specific wavelength to rapidly scan the surface of the moving ultrathin foil. The X-rays interact with the surface grains of the ultrathin foil to generate a diffraction pattern. By analyzing the position and intensity distribution of the diffraction peaks in the diffraction pattern, the orientation distribution data of the surface grains of the ultrathin foil, i.e., the initial crystal texture information, is obtained.

[0035] S2.2 Based on the initial crystal texture information of the ultrathin foil obtained by online X-ray diffraction, the initial crystal texture information is transmitted to the pre-built and calibrated crystal plasticity fast calculation model.

[0036] Furthermore, the initial crystal texture information of the ultrathin foil obtained by online X-ray diffraction is transmitted in real time via a data bus to a crystal plasticity fast calculation model that has been pre-built in the computing unit and calibrated with historical rolling data, and used as input data for the crystal plasticity fast calculation model.

[0037] It should be noted that complete crystal orientation information of a large number of ultrathin foil samples with different initial textures was obtained by electron backscatter diffraction technology. A series of mechanical property tests were conducted on these samples under different stress states on a material testing machine to obtain stress-strain response data. A rapid calculation model for crystal plasticity was established, and the parameters were repeatedly adjusted through optimization algorithms to achieve the best fit between the macroscopic stress-strain response simulated by the rapid calculation model for crystal plasticity and the experimental measurement results. A set of optimal parameters for the rapid calculation model for crystal plasticity was determined, enabling the rapid calculation model for crystal plasticity to accurately predict subsequent deformation behavior based on the input initial crystal texture information.

[0038] S2.3. Based on the crystal plasticity fast calculation model, the initial crystal texture information is calculated. According to the crystal plasticity theory, the slip behavior of different grain orientations in rolling deformation is simulated. The output is a plate shape defect map reflecting the difference in transverse flow resistance and a transverse friction non-uniformity distribution cloud map that quantitatively describes the relative slip trend of the contact surface.

[0039] Furthermore, after receiving the initial crystal texture information, the rapid calculation model for crystal plasticity calculates the ease of initiation of each slip system under rolling deformation conditions for different grain orientations based on crystal plasticity theory, simulating the macroscopic plastic flow behavior of polycrystalline aggregates. By solving the entire deformation field, it predicts the differences in plastic flow resistance at different transverse positions of the strip due to crystallographic anisotropy, and quantifies these differences into a plate shape defect map. Based on the relative slip trend when grains with different orientations contact the roll, it derives the relative kinematic potential between the roll and foil interface and quantifies it into a transverse friction non-uniformity distribution cloud map.

[0040] S2.4. Based on the plate shape defect map and the transverse friction non-uniformity distribution cloud map, combined with the plate shape adjustment requirements inferred from the plate shape defect map and the friction control requirements indicated by the transverse friction non-uniformity distribution cloud map, the pre-adjustment parameters for the rolling mill actuator and the pre-adjustment parameters for the lubrication unit are calculated.

[0041] Furthermore, by analyzing the plate shape defect map, the predicted plate shape defect types and severity are identified, and the plate shape adjustment requirements for eliminating defects are inferred. To suppress the central wave, the positive bending roll force needs to be increased. By analyzing the transverse friction non-uniformity distribution cloud map, areas with friction coefficients significantly higher than the average level are identified, indicating the need for enhanced lubrication and friction control. Combining the plate shape adjustment requirements and friction control requirements, and based on the control characteristics of the mill actuator and lubrication unit, the specific pre-adjustment parameters for the mill actuator and the lubrication unit are calculated respectively.

[0042] It should be noted that, based on the plate shape defect map, the deviation of the transverse thickness distribution or tension distribution shown in the map is analyzed to infer the plate shape adjustment requirements required to correct the deviation. To compensate for the central wave, the adjustment amount of the positive bending roll force needs to be calculated. Based on the transverse friction non-uniformity distribution cloud map, the area with a friction coefficient significantly higher than the average level in the cloud map is identified, indicating the friction control requirements required to reduce local friction energy. For example, the increase ratio of lubrication nozzle flow is calculated for the insufficient lubrication area. A collaborative calculation process is initiated, which simultaneously considers the coupling effect between the plate shape adjustment requirements and the friction control requirements. Through optimization algorithms, a set of optimal solutions that can effectively correct plate shape defects and simultaneously optimize the interface friction state are calculated, namely, the specific pre-adjustment parameters of the mill actuator (such as the bending roll force setting value and the roll tilt amount) and the specific pre-adjustment parameters of the lubrication unit.

[0043] S2.5. By comprehensively calculating the normalized offset of the pre-adjustment parameters relative to the reference parameters, the pre-adjustment intervention degree for the current ultra-thin foil strip is obtained.

[0044] The expression for the pre-adjustment intervention degree is: ; in, To adjust the intervention level, For the weight of the rolling mill actuator, These are the reference parameters for the rolling mill actuator. Preset parameters for the rolling mill actuator, These are the pre-adjusted parameters for the lubrication unit. These are the reference parameters for the lubrication unit. The weight of the lubrication unit.

[0045] Furthermore, the pre-adjustment parameters of the rolling mill actuator and the lubrication unit are compared with their corresponding reference parameters to calculate their relative offsets. The normalized offsets are then weighted and calculated to obtain a dimensionless scalar that comprehensively characterizes the intensity of the current pre-adjustment operation, namely, the pre-adjustment intervention degree for the current ultra-thin foil strip.

[0046] It should be noted that, based on the plate shape adjustment requirements inferred from the analysis of the plate shape defect map and the friction control requirements indicated by the analysis of the transverse friction non-uniformity distribution cloud map, the plate shape adjustment requirements are mapped to adjustment commands for the mill actuator. To compensate for the predicted edge thinning defects, the plate shape adjustment requirements are quantified as the micron-level position adjustment amount required by the roll tilting device. The friction control requirements are mapped to adjustment commands for the lubrication unit. For the high friction areas identified in the friction non-uniformity distribution cloud map, the friction control requirements are quantified as the percentage increase in the injection flow rate of the corresponding lubrication nozzle. A collaborative calculation algorithm is activated, simultaneously considering the mechanical response characteristics of the mill actuator and the hydrodynamic characteristics of the lubricant, and coupling optimization is performed on the preliminary adjustment commands obtained by mapping. This ensures that the roll adjustment taken to improve the plate shape will not aggravate the local friction non-uniformity, and the enhanced lubrication taken to reduce friction will not lead to plate shape loss of control. A set of mutually coordinated and optimal pre-adjustment parameters for the mill actuator and the lubrication unit is output.

[0047] S2.6. Send the pre-adjustment parameters of the mill actuator and the lubrication unit to the mill actuator and the lubrication unit, so that the mill actuator and the lubrication unit with the pre-adjustment intervention degree can be obtained before the ultra-thin foil enters the roll gap.

[0048] Furthermore, the pre-adjustment parameters of the rolling mill actuator and the lubrication unit will be issued to the rolling mill actuator and the lubrication unit in the form of control commands. The rolling mill actuator and the lubrication unit will receive and execute these commands to complete the parameter settings, thereby completing the pre-adjustment settings of the rolling mill actuator and the lubrication unit with pre-adjustment intervention degree before the head of the ultra-thin foil strip enters the roll gap.

[0049] S3. The ultra-thin foil enters the roll gap for rolling, and the thickness automatic control unit and tension automatic control unit are used to perform basic control of the rolling process.

[0050] S3.1 Based on the pre-adjusted mill actuator and lubrication unit, the ultra-thin foil enters the roll gap for rolling.

[0051] Furthermore, since the mill's actuators and lubrication units have been pre-adjusted based on the predicted plate shape defect map and the transverse friction non-uniformity distribution cloud map, the ultrathin foil is in an optimized, non-uniform roll gap mechanical environment from the very beginning. This proactive intervention allows the strip to compensate for the flow non-uniformity and friction abnormalities that may be caused by the anisotropy of its microcrystals in the early stages of rolling deformation, thereby reducing the generation of unfavorable stress states. This provides a more stable and ideal process starting point for subsequent thickness and tension control, fundamentally reducing the probability of sudden plate shape defects and fracture risks, and improving the stability of the rolling process and the consistency of finished product quality.

[0052] S3.2 During the rolling process of ultra-thin foil entering the roll gap, the thickness automatic control unit adjusts the roll pressing position based on the target exit thickness and the feedback signal from the exit thickness gauge.

[0053] Furthermore, during the rolling process of the ultrathin foil entering the roll gap, the automatic thickness control unit continuously operates. The automatic thickness control unit uses the target exit thickness as a reference value and receives the feedback signal of the actual exit thickness of the ultrathin foil detected by the X-ray thickness gauge installed on the exit side of the mill in real time. The PID controller inside the automatic thickness control unit calculates the position adjustment amount of the hydraulic pressing cylinder based on the deviation between the target exit thickness and the actual exit thickness, and drives the hydraulic servo to adjust the pressing position of the roll, thereby stabilizing the exit thickness of the ultrathin foil within the target range.

[0054] It should be noted that the PID controller inside the automatic thickness control unit continuously receives the actual exit thickness feedback signal from the exit thickness gauge and compares the actual exit thickness feedback signal with the preset target exit thickness, calculating the thickness deviation value between the two in real time. The thickness deviation value is input into the PID control algorithm, which generates a control signal based on the response characteristics of the proportional, integral, and derivative components to the deviation. The control signal is sent to the hydraulic servo unit, which converts the electrical signal into precise mechanical displacement, driving the piston rod of the hydraulic pressing cylinder to extend or retract, thereby directly adjusting the pressing position of the roll, changing the actual opening of the roll gap, and ultimately causing the actual exit thickness to converge with the target exit thickness, achieving stable thickness control.

[0055] S3.3. The feedback control loop of the thickness automatic control unit and the tension automatic control unit is operated based on the initial process parameters set by the pre-adjustment intervention degree.

[0056] Furthermore, the feedback control loops used in the thickness automatic control unit and the tension automatic control unit do not start from zero or based on default parameters, but rather start and run under the initial process parameter reference set by the pre-adjustment intervention degree. The pre-adjustment intervention degree already includes plate shape and friction state information predicted based on the initial crystal texture information. Therefore, the basic adjustment process of thickness automatic control and tension automatic control is carried out under non-uniform initial roll gap conditions and interface friction conditions that have been proactively optimized. This allows the basic control to operate at a working point that is closer to the ideal state, effectively reducing the burden of subsequent adjustments and improving control stability.

[0057] S4. Collect rolling process parameters, combine the rolling process parameters with the local stress-strain state and transverse friction non-uniformity distribution cloud map calculated by the crystal plasticity rapid calculation model, input and substitute into the toughness fracture criterion formula to calculate the real-time damage accumulation value and judge the fracture risk, and dynamically adjust the rolling mill process parameters and lubrication parameters according to the judgment results.

[0058] S4.1 During the rolling process, the rolling force, front tension, back tension and rolling speed of the object are continuously collected to obtain the rolling process parameters. The local stress and strain state corresponding to the current rolling state is obtained from the continuously running crystal plasticity rapid calculation model. Based on the correlation statistical analysis of the friction non-uniformity value and the fracture location in the historical rolling data, the friction non-uniformity threshold is set.

[0059] Furthermore, during the rolling process, rolling force, front tension, back tension, and rolling speed are continuously and synchronously collected and summarized into rolling process parameters. The local stress-strain state corresponding to the current rolling instant is obtained from the continuously running crystal plasticity rapid calculation model. Based on the statistical analysis of a large number of historical rolling data records, it is determined that there is a significant correlation between the friction non-uniformity value and the final fracture location of the strip. A friction non-uniformity threshold is set for risk identification.

[0060] S4.2 Based on rolling process parameters, local stress and strain state, and transverse friction non-uniformity distribution cloud map, identify areas in the transverse friction non-uniformity distribution cloud map where the friction non-uniformity value exceeds the friction non-uniformity threshold as high-risk areas.

[0061] Furthermore, the rolling process parameters, local stress and strain states, and the transverse friction non-uniformity distribution cloud map generated by the crystal plasticity rapid calculation model are traversed and scanned. All local areas in the cloud map whose friction non-uniformity values ​​exceed the set friction non-uniformity threshold are identified and marked as high-risk areas.

[0062] S4.3. Based on the local stress-strain state, pre-adjustment intervention degree and lateral friction non-uniformity distribution cloud map, the friction stress is linearly superimposed to form a stress state correction function, which corrects the local stress state in high-risk areas and quantifies the additional influence of pre-adjustment operation on the local stress state.

[0063] The expression for the stress state correction function is: ; in, The corrected stress tensor. It is a local stress-strain state. The coupling coefficient is... To adjust the intervention level, The contour map of lateral friction non-uniformity distribution is located in the lateral position. The value at that location, This is the reference stress.

[0064] Furthermore, the two key factors of active process intervention (pre-adjustment intervention degree) and interface physical state (lateral friction non-uniformity) are directly coupled to the calculation of the local stress field in a linear superposition quantification method. This is achieved by linking the local stress-strain state with the... By combining the additional stress terms, the true stress tensor after pre-adjustment and correction for actual friction conditions can be accurately calculated. This allows for a quantitative assessment of the additional impact of each pre-adjustment operation on the internal stress state of the material, thus directly linking macroscopic equipment adjustments with microscopic material mechanical responses. This provides crucial stress input that reflects real working conditions for subsequent physical-based accurate fracture risk assessment.

[0065] It is important to note that the fundamental difference from existing technologies lies in the fact that existing technologies, when performing stress analysis or fracture risk assessment, typically treat the rolling process as a black box or gray box directly determined by equipment parameters (such as rolling force and tension). The stress calculation models either ignore the microscopic effects of pre-adjustment intervention and interface friction, or only make extremely rough approximations using empirical coefficients. In contrast, this stress state correction function constructs a clear causal transmission path: it treats the degree of pre-adjustment intervention (cause) and friction state (cause) as independent variables that directly affect the stress field (effect). This physical and structured modeling method transforms the prediction of stress state from a static and passive estimation to a dynamic, interpretable, and high-precision calculation linked to real-time process operations, achieving a deep characterization of the physical essence of complex rolling interface conditions.

[0066] S4.4. Based on the corrected stress tensor, the hydrostatic pressure and equivalent stress are obtained through tensor calculation. The hydrostatic pressure is divided by the equivalent stress to obtain the corrected stress triaxiality.

[0067] The expression for hydrostatic pressure is: ; in, For hydrostatic pressure, For the maximum principal stress, The intermediate principal stress, It is the minimum principal stress.

[0068] The equivalent stress expression is: ; in, This is the equivalent stress.

[0069] Furthermore, the modified stress tensor is used as input, and the arithmetic mean of the stress tensor is calculated to obtain the hydrostatic pressure characterizing the hydrostatic pressure state. According to the Mises yield criterion, the second deviatoric stress invariant is calculated using the principal stress components of the stress tensor, and then substituted into the equivalent stress formula to obtain the equivalent stress characterizing the shape change energy efficiency. The hydrostatic pressure is divided by the equivalent stress, and the division operation is performed to obtain the modified stress triaxiality used for toughness damage assessment.

[0070] S4.5. Based on the mechanical tests of ultrathin foil under different local stress states, the relationship between the fracture strain data and the corresponding local stress state parameters is obtained by fitting the test, and the benchmark fracture strain scaling factor, the deviatoric stress asymmetry shape parameter and the stress triaxiality sensitivity scale parameter are calibrated.

[0071] Furthermore, in a laboratory environment, a series of mechanical property tests covering different stress states (such as uniaxial tension, pure shear, and notched tension) were conducted on the same batch of ultrathin foil samples. The actual strain data of each sample up to the point of fracture were measured and recorded. By fitting the relationship between the fracture strain data measured in the test and the corresponding local stress state parameters (stress triaxiality and Lod angle parameters), three constants that uniquely characterize the fracture characteristics of the material were determined: the reference fracture strain scaling factor, the deviatoric stress asymmetry shape parameter, and the stress triaxiality sensitivity scale parameter.

[0072] It should be noted that, through mechanical experiments and rigorous data fitting, the complex characteristic of macroscopic fracture toughness of a specific ultrathin foil material has been extracted and calibrated into three material constants with clear physical meaning: the baseline fracture strain scaling factor, the deviatoric stress asymmetry shape parameter, and the stress triaxiality sensitivity scale parameter. In the subsequent online rolling process, the material damage accumulation can be quantitatively and predictably assessed based on the real-time stress state, providing a crucial material constitutive data foundation for proactively avoiding fracture risks. This represents a fundamental shift from qualitative judgments based on experience to quantitative predictions based on physical models.

[0073] S4.6 In the actual rolling process, the strain increment calculated by the crystal plasticity rapid calculation model is used to calculate the damage increment by substituting the corrected stress triaxiality, Lod angle parameter, strain increment, reference fracture strain scaling factor, deviatoric stress asymmetry shape parameter and stress triaxiality sensitivity scale parameter into the ductile fracture criterion formula.

[0074] The expression for damage increment is: ; in, For the increase in damage, For the strain increment, For the corrected stress triaxiality, For the Lode angle parameters, As the benchmark fracture strain scaling factor, This is a parameter for the stress triaxiality sensitivity scale. The shape parameter is the shape parameter for the asymmetric deviatoric stress.

[0075] Furthermore, by incorporating the strain increment reflecting the current actual deformation degree, the corrected stress triaxiality and Lod angle parameters accurately characterizing the current stress state's danger level, as well as the benchmark fracture strain scaling factor, deviatoric stress asymmetry shape parameter, and stress triaxiality sensitivity scale parameter describing the material's inherent fracture characteristics into a unified ductile fracture criterion formula, it is possible to calculate the percentage of life consumed by the material due to plastic deformation within the current tiny time step, i.e., the damage increment. This makes the judgment of fracture risk no longer dependent on macroscopic empirical thresholds, but rather based on the continuous, dynamic, and accurate accumulation of the physical process of material damage evolution, achieving a forward-looking and quantitative assessment of fracture risk.

[0076] It should be noted that the fundamental difference between this technology and existing technologies lies in the fact that existing technologies typically assess fracture risk based on the extreme values ​​of macroscopic process parameters (such as maximum rolling force and maximum tension) or simple equivalent plastic strain accumulation, neglecting the decisive influence of stress state on the damage evolution rate. The core difference of this technology lies in the introduction of a modified stress triaxiality key variable, through… The calculations revealed the dynamic impact of pre-adjustment interventions and interfacial friction processes on the actual stress state within the material. Therefore, the damage calculation model of this method can keenly capture that even with the same strain increment, the damage caused by unit strain increases dramatically under different stress states. This represents a paradigm shift from monitoring whether macroscopic parameters are exceeded to real-time calculation of microscopic damage physical quantities, improving the accuracy and timeliness of early warning for fractures in high-risk areas.

[0077] S4.7. The local stress state and current strain increment of the high-risk area after modification are analyzed by the ductile fracture criterion to obtain the damage increment of the modified stress triaxiality. Based on the damage increment of the modified stress triaxiality, the high-risk area is continuously accumulated during the rolling process to obtain the real-time damage accumulation value of the high-risk area.

[0078] Furthermore, by continuously applying the ductile fracture criterion to the local stress state of high-risk areas, which is updated in real time by the stress state correction function, the precise damage increment, determined by the current true stress level and strain increment, is continuously accumulated independently for each high-risk area. This ultimately yields a real-time damage accumulation value specific to that area that evolves over time. This shifts the monitoring focus from the macroscopic average state of the entire roll of strip to the precise tracking of the microscopic damage evolution process at potential tear origins. Consequently, before the microscopic damage accumulation reaches a critical value, warnings can be issued and local interventions triggered only for specific high-risk areas. This represents a leap from extensive overall safety control to refined local damage life management, improving the safety and yield of ultrathin foil rolling.

[0079] S4.8 Conduct mechanical property tests on ultrathin foils under different stress states, calibrate the critical damage value, and set the fracture threshold by combining the statistical distribution of safety and fracture cases in historical rolling data.

[0080] Furthermore, by analyzing the mechanical property test data of ultrathin foil samples, the critical damage value when the material fractures was determined; combined with the statistical distribution characteristics of successful rolling and fracture cases in the factory's historical rolling data records, an engineering safety fracture threshold slightly lower than the critical damage value was set for online risk assessment.

[0081] S4.9 When the real-time cumulative damage value exceeds the fracture threshold, a fracture risk is determined. Based on the fracture risk assessment result, instructions for dynamically adjusting the mill process parameters and lubrication parameters are generated.

[0082] Furthermore, the system monitors the real-time damage accumulation value of high-risk areas in real time. When the real-time damage accumulation value of any high-risk area exceeds the set fracture threshold, it immediately determines that there is a fracture risk in that area. Based on the result of this fracture risk assessment, a set of dynamic adjustment instructions aimed at reducing the damage accumulation rate of the area are generated, including adjustments to rolling mill process parameters (such as rolling force and tension) and lubrication parameters.

[0083] S4.10. Issue and execute the generated instructions for dynamically adjusting the rolling mill process parameters and lubrication parameters to dynamically adjust the rolling mill process parameters and lubrication parameters.

[0084] Furthermore, by transforming proactive risk assessment into immediate and precise process interventions, and by executing dynamic adjustment commands, key parameters such as rolling force, tension, or local lubrication can be proactively and rapidly adjusted for identified high-risk areas. Before micro-damage accumulation reaches a critical value, the mechanical state and interface conditions within the roll gap can be changed in real time, fundamentally reducing the local stress level that leads to a surge in damage and effectively interrupting or delaying the damage accumulation process. This capability upgrades the fracture protection strategy from the traditional passive mode of over-limit alarm-emergency shutdown to a proactive mode of risk prediction-proactive fine-tuning-continuous production. While maximizing production continuity, it also improves the safety and stability of the ultra-thin foil rolling process.

[0085] S5. Measure the real-time plate shape distribution data of the rolled ultrathin foil using a plate shape meter. Calculate the actual interface friction state distribution based on the lateral distribution of rolling force and the inversion of the roll vibration spectrum. Compare the real-time plate shape distribution data with the plate shape defect map, and verify the actual interface friction state distribution with the lateral friction non-uniformity distribution cloud map. Perform parameter self-learning correction on the crystal plasticity rapid calculation model based on the comparison and verification results.

[0086] S5.1. After the ultra-thin foil is rolled, the real-time shape distribution data of the ultra-thin foil is measured using a shape measuring instrument; the transverse distribution data of the rolling force is obtained from the rolling mill control record, and the vibration spectrum of the roll is extracted from the vibration sensor signal.

[0087] Furthermore, when the ultrathin foil completes the rolling process and its tail passes through the shape measuring area of ​​the mill exit, the shape measuring instrument scans the surface profile of the ultrathin foil across its entire width, measuring the real-time shape distribution data of the ultrathin foil. The rolling force distribution data along the roll body during the current stable rolling stage is extracted from the historical data records of the mill control system, i.e., the transverse distribution data of the rolling force. The characteristic vibration spectrum related to the rolling process, i.e., the roll vibration spectrum, is extracted from the signals recorded by the vibration acceleration sensor installed on the roll bearing seat through spectrum analysis.

[0088] S5.2. By collecting a large amount of rolling force, vibration and friction data under known lubrication conditions during the commissioning phase and training a neural network, a mapping relationship of the actual interface friction state distribution is established.

[0089] Furthermore, during the mill commissioning phase, a series of different and known lubrication conditions were intentionally set up. Rolling tests were conducted under each lubrication condition, and rolling force lateral distribution data and roll vibration spectrum data were collected simultaneously. At the same time, the actual friction state distribution data of the roll gap interface under the corresponding working conditions was obtained through indirect measurement or verified numerical simulation methods. Using the large pairs of collected rolling force lateral distribution data and roll vibration spectrum as input features, and the corresponding actual friction state distribution data as output labels, a neural network model was trained. The trained neural network model constitutes the mapping relationship from the rolling force lateral distribution and roll vibration spectrum to the actual interface friction state distribution.

[0090] It should be noted that in the large number of paired datasets collected, each set of data contains an input feature vector consisting of rolling force lateral distribution data and roll vibration spectrum data, and a corresponding actual friction state distribution data as an output label. These data are used to perform supervised learning on the initialized neural network. The network prediction value is calculated through forward propagation, and the weights and bias parameters of each layer in the network are iteratively adjusted based on the error between the prediction value and the true label using the backpropagation algorithm. This process is repeated until the prediction error of the network on the entire dataset converges to a preset tolerance range. At this point, the trained neural network has the ability to accurately invert the actual interface friction state distribution from the new rolling force lateral distribution and roll vibration spectrum data.

[0091] S5.3 Based on the transverse distribution data of rolling force and the vibration spectrum of rolls, the actual interface friction state distribution is calculated by inverting the mapping relationship of the actual interface friction state distribution.

[0092] Furthermore, the lateral distribution data of rolling force and the roll vibration spectrum data collected during the current rolling process are preprocessed and feature extracted to form a multi-dimensional feature vector. This feature vector is then used as input to the trained neural network model. The neural network model performs forward propagation calculations, sequentially passing through the input layer, the hidden layer, and the nonlinear transformation of the activation function. Finally, a data sequence corresponding to the input feature vector and reflecting the magnitude of the friction coefficient at each point within the entire roll width is generated at the output layer. The actual interface friction state distribution is obtained through inversion calculation.

[0093] S5.4. Compare the real-time plate shape distribution data with the plate shape defect map point by point to calculate the plate shape prediction error. Compare the actual interface friction state distribution with the transverse friction non-uniformity distribution cloud map point by point to calculate the friction state prediction error.

[0094] The expression for the plate shape prediction error is: ; in, For plate shape prediction error, This represents the number of horizontal measurement points. For horizontal position index, For real-time plate shape distribution data in the first The measured value of the point, For the plate shape defect spectrum in the first Predicted value of a point.

[0095] The expression for the friction state prediction error is: ; in, For the friction state prediction error, The actual interface friction state distribution is in the th... Inversion calculation value of the point, The cloud map of lateral friction non-uniformity distribution is shown in the first... Predicted value of a point.

[0096] Furthermore, by comparing the real-time plate shape distribution data measured by the plate shape analyzer with the plate shape defect spectrum predicted by the crystal plasticity model point by point, the plate shape prediction error is calculated. This error objectively quantifies the accuracy of the model in predicting macroscopic geometric quality. At the same time, by comparing the actual interface friction state distribution obtained by inversion with the predicted transverse friction non-uniformity distribution cloud map point by point, the friction state prediction error is calculated. This error deeply verifies the reliability of predicting the physical state of the micro-interface. These two specific and quantifiable error values ​​provide accurate and multi-dimensional feedback signals for the subsequent parameter self-learning correction of the model.

[0097] It should be noted that the fundamental difference between this technology and existing technologies is that existing technologies usually rely only on a single macroscopic geometric index for model verification or process optimization. The core difference of this technology is that it introduces direct verification of the prediction accuracy of microscopic physical quantities (interface friction state). By calculating the friction state prediction error, it is possible to directly evaluate whether the model's ability to predict the core intrinsic mechanism of the rolling process—interface friction behavior—is accurate. This realizes a paradigm shift from only caring about whether the result (plate shape) is correct to simultaneously requiring the prediction of the intrinsic physical cause (friction) to be correct. The dual verification based on the physical mechanism makes the model correction more profound and fundamental.

[0098] S5.5. Based on the plate shape prediction error, friction state prediction error, and pre-adjustment intervention degree, the parameters of the rapid calculation model for crystal plasticity are self-learned and corrected to evaluate the short-term effects and long-term impacts of pre-adjustment intervention.

[0099] Furthermore, short-term effect assessment: analyze the immediate deviation between measured and predicted values ​​under the current pre-adjusted intervention level.

[0100] Long-term impact assessment: Based on the pre-adjustment intervention degree corresponding to different ultrathin foil rolls, and the record of the changes in plate shape prediction error and friction state prediction error between the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map predicted by the crystal plasticity rapid calculation model under the pre-adjustment intervention degree and the actual measurement results over time, the correlation between the change trend of prediction error of different pre-adjustment intervention degrees and the crystal plasticity rapid calculation model is analyzed. Based on the comprehensive assessment results, the parameters describing the relationship between material response and intervention effect in the crystal plasticity rapid calculation model are corrected, and the prediction accuracy of the crystal plasticity rapid calculation model under the influence of pre-adjustment intervention degree is optimized.

[0101] Specifically, the plate shape prediction error and friction state prediction error are combined with the pre-adjustment intervention degree defined for the current ultrathin foil roll to perform parameter self-learning correction on the crystal plasticity rapid calculation model. The correction process includes dual evaluation: the short-term effect evaluation focuses on analyzing the instantaneous deviation of the plate shape prediction error between the measured plate shape distribution data and the plate shape defect map, and the friction state prediction error between the measured friction state distribution and the transverse friction non-uniformity distribution cloud map under the current specific pre-adjustment intervention degree.

[0102] The long-term impact assessment is based on historical data records from the production of multiple rolls of ultra-thin foil strips. It analyzes the correlation between different pre-adjustment intervention levels and the long-term trends of plate shape prediction errors and friction state prediction errors over time, arising from the differences between the plate shape defect maps and transverse friction non-uniformity distribution cloud maps predicted by the rapid calculation model for crystal plasticity and the actual measurement results. By combining the immediate bias information from the short-term effect assessment and the correlation analysis results from the long-term impact assessment, an optimization algorithm is used to adjust specific parameters in the rapid calculation model for crystal plasticity that describe the relationship between material response and the pre-adjustment intervention effect, thereby optimizing the prediction accuracy of the rapid calculation model for crystal plasticity under the influence of pre-adjustment intervention levels.

[0103] S6. The rolled and verified ultra-thin foil is wound up by a winding machine to obtain the finished ultra-thin foil.

[0104] S6.1 The rolled and inspected ultra-thin foil is conveyed to the winding machine station, and the winding machine winds the rolled and inspected ultra-thin foil with constant tension.

[0105] Furthermore, after the ultrathin foil is rolled, the shape is measured and the actual interface friction state distribution is inverted and calculated, which is considered to be the completion of the rolling and verification process. The ultrathin foil is then pulled by the conveying equipment so that its tail end completely leaves the mill roll gap and smoothly reaches the coiler station. The coiler jaws clamp the head of the ultrathin foil, and the main drive motor of the coiler runs according to the constant tension value set by the tension control unit. It begins to coil the rolled and verified ultrathin foil at a constant linear speed and tension, tightly winding it onto the drum to form a roll.

[0106] S6.2 The winding machine unwinds the completed ultra-thin foil roll to obtain the finished ultra-thin foil roll.

[0107] Furthermore, once the entire roll of ultrathin foil is completely wound onto the winding machine's drum, the main drive of the winding machine stops rotating; the winding machine's drum support mechanism performs an unwinding action, the expansion and contraction drum shrinks its diameter, or auxiliary equipment such as an unwinding trolley is used to lift and remove the ultrathin foil roll from the winding machine's drum; the removed ultrathin foil roll, having completed all rolling, inspection, and winding processes, is the finished ultrathin foil roll.

[0108] This embodiment also provides a rolling control system for ultrathin foil, including: a data acquisition module for acquiring the basic parameters of the incoming ultrathin foil and setting the rolling process target; The pre-adjustment module, based on the incoming material parameters, uses an online X-ray diffractometer to measure the initial crystal texture information of the ultrathin foil. The initial crystal texture information is input into the crystal plasticity rapid calculation model to predict the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. The rolling mill actuator and lubrication unit are pre-adjusted according to the plate shape defect spectrum and the transverse friction non-uniformity distribution cloud map. The control module, in which the ultrathin foil enters the roll gap for rolling, uses an automatic thickness control unit and an automatic tension control unit to perform basic control of the rolling process; The judgment module collects rolling process parameters, combines the rolling process parameters with the local stress-strain state and transverse friction non-uniformity distribution cloud map calculated by the crystal plasticity rapid calculation model, inputs them into the toughness fracture criterion formula to calculate the real-time damage accumulation value and judge the fracture risk, and dynamically adjusts the rolling mill process parameters and lubrication parameters according to the judgment results. The correction module uses a shape meter to measure the real-time shape distribution data of the rolled ultrathin foil. Based on the lateral distribution of rolling force and the inversion of the roll vibration spectrum, it calculates the actual interface friction state distribution. It compares the real-time shape distribution data with the shape defect map and verifies the actual interface friction state distribution with the lateral friction non-uniformity distribution cloud map. Based on the comparison and verification results, it performs parameter self-learning correction on the crystal plasticity rapid calculation model. The finished product module winds up the rolled and verified ultrathin foil material by a winding machine to obtain the finished ultrathin foil material.

[0109] This embodiment also provides a computer device applicable to the rolling control method for ultra-thin foil materials, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the rolling control method for ultra-thin foil materials as proposed in the above embodiment.

[0110] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0111] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the rolling control method for ultra-thin foil as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0112] In summary, this invention, based on incoming material parameters and online crystal texture measurement, uses a crystal plasticity model to predict plate shape defects and friction distribution patterns, and performs feedforward pre-adjustment of the mill actuator and lubrication system. During the rolling process, it combines real-time process parameters and local stress-strain state calculated by the model, calculates the cumulative damage value in real time and judges the fracture risk through the toughness fracture criterion, dynamically adjusts process parameters, and compares and verifies the predicted values ​​with the post-rolling measured plate shape and inverted friction data. It also performs parameter self-learning correction on the crystal plasticity model, deeply coupling the material's microscopic properties, interface friction state, and macroscopic process control, realizing a leap from passive feedback to active prediction and control, and effectively improving the accuracy, stability, and yield of ultra-thin foil rolling.

[0113] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method of roll control of an ultrathin foil, characterized by: The application relates to a method for realizing real-time damage accumulation value calculation and fracture risk judgment of ultra-thin foil during rolling. The method comprises the following steps: collecting basic parameters of incoming ultra-thin foil and setting rolling process targets; based on the basic parameters of the incoming ultra-thin foil, measuring initial crystal texture information of the ultra-thin foil by using an online X-ray diffractometer, inputting the initial crystal texture information into a crystal plasticity fast calculation model to predict a plate shape defect map and a transverse friction unevenness distribution cloud map, and pre-adjusting rolling mill actuators and lubricating units according to the plate shape defect map and the transverse friction unevenness distribution cloud map; the ultra-thin foil enters a roll gap for rolling, and a thickness automatic control unit and a tension automatic control unit are used to perform basic control on the rolling process; collecting rolling process parameters, combining the rolling process parameters with local stress and strain states and the transverse friction unevenness distribution cloud map calculated by the crystal plasticity fast calculation model, inputting the parameters into a ductile fracture criterion formula to perform real-time damage accumulation value calculation and fracture risk judgment, and dynamically adjusting rolling mill process parameters and lubricating parameters according to the judgment result; measuring real-time plate shape distribution data of the rolled ultra-thin foil by using a plate shape meter, calculating an actual interface friction state distribution based on rolling force transverse distribution and roll vibration frequency spectrum inversion, comparing the real-time plate shape distribution data with the plate shape defect map, and checking the actual interface friction state distribution with the transverse friction unevenness distribution cloud map, and performing parameter self-learning correction on the crystal plasticity fast calculation model according to the comparison and checking results; 2. The method of roll control of an ultrathin foil as claimed in claim 1, wherein: the ultra-thin foil after rolling and checking is coiled by a coiling machine to obtain finished ultra-thin foil. The method comprises the following steps: collecting basic parameters of incoming ultra-thin foil and setting rolling process targets; setting target outlet thickness, target tension and target plate shape of the ultra-thin foil rolling on a control interface; based on the set target outlet thickness, target tension and target plate shape, starting a rolling mill production line to make the ultra-thin foil strip coil uncoiled and threaded; 3. The method of roll control of an ultrathin foil as claimed in claim 2, wherein: during the uncoiling and threading of the ultra-thin foil strip coil, an entry thickness gauge, a tension gauge and a speed meter at an entry section collect entry thickness, entry tension and running speed of the incoming material to obtain the basic parameters of the incoming ultra-thin foil; based on the entry thickness, entry tension and running speed and the target outlet thickness, target tension and target plate shape, setting the rolling process targets. based on the basic parameters of the incoming ultra-thin foil, measuring initial crystal texture information of the ultra-thin foil by using an online X-ray diffractometer, inputting the initial crystal texture information into a crystal plasticity fast calculation model to predict a plate shape defect map and a transverse friction unevenness distribution cloud map, and pre-adjusting rolling mill actuators and lubricating units according to the plate shape defect map and the transverse friction unevenness distribution cloud map, which comprises the following steps: based on the basic parameters of the incoming ultra-thin foil, triggering the online X-ray diffractometer to quickly scan the surface of the moving ultra-thin foil to obtain initial crystal texture information of the ultra-thin foil; based on the initial crystal texture information of the ultra-thin foil measured by the online X-ray diffractometer, transmitting the initial crystal texture information to a pre-constructed and calibrated crystal plasticity fast calculation model; The initial crystal texture information input is calculated based on the crystal plasticity fast calculation model, the slip behavior of different grain orientations in rolling deformation is simulated according to the crystal plasticity theory, and the shape defect atlas reflecting the difference of transverse flow resistance and the transverse friction non-uniformity distribution cloud map quantitatively describing the relative slip trend of the contact surface are output; Based on the shape defect atlas and the transverse friction non-uniformity distribution cloud map, combined with the shape adjustment requirement inferred from the shape defect atlas and the friction regulation requirement indicated by the transverse friction non-uniformity distribution cloud map, the pre-adjustment parameters for the rolling mill actuator and the pre-adjustment parameters for the lubricating unit are comprehensively calculated; The pre-adjustment intervention degree for the current ultra-thin foil coil is obtained through the comprehensive calculation of the normalized offset of the pre-adjustment parameters relative to the reference parameters; The pre-adjustment parameters for the rolling mill actuator and the pre-adjustment parameters for the lubricating unit are sent to the rolling mill actuator and the lubricating unit, and the pre-adjustment of the rolling mill actuator and the lubricating unit with the pre-adjustment intervention degree is obtained before the ultra-thin foil enters the roll gap.

4. The method of roll control of an ultrathin foil as claimed in claim 3, wherein: The ultra-thin foil enters the roll gap for rolling, and the thickness automatic control unit and the tension automatic control unit are used for basic control of the rolling process, including the following steps: Based on the pre-adjusted rolling mill actuator and lubricating unit, the ultra-thin foil enters the roll gap for rolling; During the rolling process of the ultra-thin foil entering the roll gap, the thickness automatic control unit adjusts the roll gap position according to the feedback signal of the outlet thickness gauge based on the target outlet thickness; The feedback control loop of the thickness automatic control unit and the tension automatic control unit is operated based on the initial process parameter reference set by the pre-adjustment intervention degree.

5. The method of roll control of an ultrathin foil as claimed in claim 4, wherein: The rolling process parameters are collected, the rolling process parameters, the local stress and strain state calculated by the crystal plasticity fast calculation model, and the transverse friction non-uniformity distribution cloud map are combined, and the real-time damage accumulation value calculation and fracture risk judgment are performed by inputting into the ductile fracture criterion formula, and the rolling process parameters and lubrication parameters are dynamically adjusted according to the judgment result, including the following steps: During the rolling process, the rolling force, front tension, back tension and rolling speed are continuously collected to obtain the rolling process parameters, the local stress and strain state corresponding to the current rolling state is obtained from the continuously running crystal plasticity fast calculation model, and the friction non-uniformity threshold value is set based on the correlation statistical analysis of the friction non-uniformity values in the historical rolling data and the fracture position; Based on the rolling process parameters, the local stress and strain state, and the transverse friction non-uniformity distribution cloud map, the area where the friction non-uniformity value exceeds the friction non-uniformity threshold value in the transverse friction non-uniformity distribution cloud map is identified as a high-risk area; Based on the local stress and strain state, the pre-adjustment intervention degree and the friction stress derived from the transverse friction non-uniformity distribution cloud map, a stress state correction function is constructed by linear superposition, the local stress state of the high-risk area is corrected, and the additional influence of the pre-adjustment operation on the local stress state is quantified; Based on the corrected stress tensor, the hydrostatic pressure and the equivalent stress are obtained through tensor operation, and the corrected stress triaxiality is obtained by dividing the hydrostatic pressure by the equivalent stress; Based on the mechanical test of the ultra-thin foil under different local stress states, the relationship between the test data of the fracture strain and the corresponding local stress state parameters is fitted, and the reference fracture strain scale factor, the partial stress asymmetry shape parameter and the stress triaxiality sensitivity scale parameter are calibrated; In the actual rolling process, the strain increment calculated by the crystal plasticity fast calculation model is obtained, and the corrected stress triaxiality, the Lode angle parameter, the strain increment, the reference fracture strain scale factor, the partial stress asymmetry shape parameter and the stress triaxiality sensitivity scale parameter are substituted into the ductile fracture criterion formula to calculate the damage increment; The local stress state and the current strain increment of the corrected high-risk area are analyzed by the ductile fracture criterion to obtain the damage increment of the corrected stress triaxiality, and the real-time damage accumulation value of the high-risk area is obtained by continuously accumulating the high-risk area in the rolling process based on the damage increment of the corrected stress triaxiality; The mechanical properties of the ultra-thin foil under different stress states are tested, the critical damage value is calibrated, and the fracture threshold is set by combining the statistical distribution of the safety and fracture cases in the historical rolling data; When the real-time damage accumulation value exceeds the fracture threshold, it is determined that there is a fracture risk, and the instructions for dynamically adjusting the rolling process parameters and the lubrication parameters are generated based on the results of the fracture risk judgment; The generated instructions for dynamically adjusting the rolling process parameters and the lubrication parameters are executed, and the dynamic adjustment of the rolling process parameters and the lubrication parameters is performed.

6. The method of roll control of an ultrathin foil as claimed in claim 5, wherein: The real-time plate shape distribution data of the rolled ultra-thin foil is measured by the plate shape instrument, the actual interface friction state distribution is calculated based on the rolling force transverse distribution and the roll vibration frequency spectrum inversion, the real-time plate shape distribution data is compared with the plate shape defect atlas, and the actual interface friction state distribution is verified with the transverse friction non-uniformity distribution cloud map, and the parameter self-learning correction of the crystal plasticity fast calculation model is performed according to the comparison and verification results, including the following steps: The real-time plate shape distribution data of the ultra-thin foil is measured by the plate shape instrument after the rolling of the ultra-thin foil is completed; the rolling force transverse distribution data is obtained from the rolling mill control record, and the roll vibration frequency spectrum is extracted from the vibration sensor signal; The actual interface friction state distribution mapping relationship is established by collecting a large amount of rolling force, vibration and friction data under known lubrication conditions in the debugging stage and training the neural network; The actual interface friction state distribution is calculated based on the rolling force transverse distribution data and the roll vibration frequency spectrum through the actual interface friction state distribution mapping relationship inversion; The real-time plate shape distribution data is compared with the plate shape defect atlas point by point, the plate shape prediction error is calculated, the actual interface friction state distribution is compared with the transverse friction non-uniformity distribution cloud map point by point, and the friction state prediction error is calculated; Based on the plate shape prediction error, the friction state prediction error and the pre-adjustment intervention degree, the parameter self-learning correction of the crystal plasticity fast calculation model is performed, and the short-term effect and long-term impact of the pre-adjustment intervention are evaluated.

7. The method of roll control of an ultrathin foil as claimed in claim 6, wherein: The ultra-thin foil after rolling and verification is coiled by the coiler to obtain the finished ultra-thin foil, including the following steps: The ultra-thin foil material after rolling and checking is transported to a coiler station, and the coiler coils the ultra-thin foil material after rolling and checking with constant tension; The coiler uncoils the coiled ultra-thin foil material to obtain a finished product ultra-thin foil material.

8. A roll control system for an ultrathin foil, based on the roll control method for an ultrathin foil according to any one of claims 1 to 7, characterized by: The method comprises a data acquisition module, which acquires the incoming basis parameters of the ultra-thin foil material and sets rolling process targets; A pre-adjustment module, based on the incoming basis parameters, measures the initial crystal texture information of the ultra-thin foil material by using an online X-ray diffractometer, inputs the initial crystal texture information into a crystal plasticity fast calculation model to predict a plate shape defect map and a transverse friction unevenness distribution cloud map, and pre-adjusts rolling mill actuators and lubrication units according to the plate shape defect map and the transverse friction unevenness distribution cloud map; A control module, when the ultra-thin foil material enters a roll gap for rolling, uses a thickness automatic control unit and a tension automatic control unit to perform basic control on the rolling process; A judgment module, which acquires rolling process parameters, combines the rolling process parameters with the local stress-strain state and the transverse friction unevenness distribution cloud map calculated by the crystal plasticity fast calculation model, inputs them into a ductile fracture criterion formula to perform real-time damage accumulation value calculation and fracture risk judgment, and dynamically adjusts rolling mill process parameters and lubrication parameters according to the judgment result; A correction module, which measures real-time plate shape distribution data of the ultra-thin foil material after rolling by using a plate shape meter, calculates the actual interface friction state distribution based on rolling force transverse distribution and roll vibration frequency spectrum inversion, compares the real-time plate shape distribution data with the plate shape defect map, and checks the actual interface friction state distribution with the transverse friction unevenness distribution cloud map, and according to the comparison and checking results, performs parameter self-learning correction on the crystal plasticity fast calculation model; A finished product module, which coils the ultra-thin foil material after rolling and checking by using a coiler to obtain a finished product ultra-thin foil material. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the ultra-thin foil material rolling control method of any one of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the ultra-thin foil material rolling control method of any one of claims 1-7.

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