Laminate processing method and production line

Abstract

The invention discloses a laminate processing method and a production line, and relates to the technical field of laminate processing, and the method comprises the following steps: matching unwinding control parameters of corresponding unwinding equipment based on material parameters and processing attributes of metal sheets so as to convey the metal sheets into a polishing machine; corresponding polishing information is determined on the basis of roughness analysis and polishing influence analysis of the metal sheets, and the polishing machine polishes the metal sheets on the basis of the polishing information; the first heating device preheats the polished metal sheets on the basis of a first self-adaptive controller; calendaring the preheated metal sheets by a calendaring device to obtain an initial laminate; the second heating device reheats the initial laminate based on the second self-adaptive controller; the shearing mechanism is used for shearing the initial laminate subjected to reheating treatment to obtain a target laminate, and the winding machine is used for winding the target laminate. According to the invention, a complete process of laminate processing is formed, so that the quality of the obtained target laminate is more reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of laminate processing, and particularly relates to a laminate processing method and production line. Background Art

[0002] A laminate is a structure formed by pressing multiple metal sheets, which is widely used in fields such as equipment manufacturing. The processing quality of the laminate affects the reliability of equipment use. In this regard, how to improve the processing quality of the laminate has become the research focus of each enterprise. In current laminate processing methods, usually, the polishing information of the metal sheets is determined through manual analysis. However, this method is too dependent on the professional qualities of relevant personnel and cannot ensure the reliability of the obtained polishing information, affecting the polishing quality. At the same time, currently, during the heating process of the metal sheets, there is a lack of adaptive control during the heating process, resulting in a large deviation between the heat treatment of the metal sheets and the expected effect, making it impossible for each metal sheet to form the required laminate well, seriously affecting the processing quality of the laminate. At the same time, how to form a complete and comprehensive process for the processing of the laminate is also a problem that needs to be considered. Only in this way can the processing reliability of the laminate be improved. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a laminate processing method and production line, forming a complete process for laminate processing, making the quality of the obtained target laminate more reliable.

[0004] To solve the above technical problems, the present invention provides a laminate processing method, which is applied to a laminate processing production line. The laminate processing production line includes a plurality of unwinding devices, a polishing machine, a plurality of heating devices, a rolling device, a shearing mechanism, and a winding machine. The method includes: Based on the material parameters and processing attributes of each metal sheet, matching the unwinding control parameters of the corresponding unwinding device, and each unwinding device transports each metal sheet into the polishing machine based on the corresponding unwinding control parameters; Based on the roughness analysis and polishing influence analysis of each metal sheet, determining the corresponding polishing information, and the polishing machine performs polishing treatment on each metal sheet based on the corresponding polishing information, and transports each polished metal sheet into the first heating device; The first heating device performs preheating treatment on each polished metal sheet based on the first adaptive controller, and transports each preheated metal sheet into the rolling device; The rolling device performs rolling treatment on each preheated metal sheet to obtain an initial laminate; The second heating device performs reheating treatment on the initial laminate based on the second adaptive controller to obtain the initial laminate after reheating treatment; The shearing mechanism shears the initial laminate after reheating treatment to obtain the target laminate, and the coiling machine coils the target laminate.

[0005] Optionally, matching the unwinding control parameters of the corresponding unwinding equipment based on the material parameters and processing attributes of each metal sheet includes: Determining the starting rotation speeds of the corresponding unwinding equipment based on the material parameters of each metal sheet in combination with the coil diameter data; Matching the operating rotation speeds of the corresponding unwinding equipment based on the processing attributes of each metal sheet, and taking the starting rotation speed and the operating rotation speed as the unwinding control parameters of the corresponding unwinding equipment.

[0006] Optionally, determining the corresponding polishing information based on the roughness analysis and polishing influence analysis of each metal sheet includes: Performing apparent feature value analysis on the apparent images of each metal sheet to obtain the corresponding apparent feature values, and determining the first roughness data of each metal sheet based on the apparent feature values; Inputting the apparent images of each metal sheet into a roughness analysis model to obtain second roughness data, where the roughness analysis model includes a feature extraction network, a cross-mixed attention module, and a graph convolutional channel attention module; Determining the target roughness data based on the first roughness data and the second roughness data; Performing material polishing influence analysis and flat polishing influence analysis based on the material parameters and flatness of each metal sheet to obtain first polishing influence data and second polishing influence data; Performing environmental polishing influence analysis using real-time environmental information based on a topology network to obtain third polishing influence data; Determining the corresponding polishing information based on the target roughness data, the first polishing influence data, the second polishing influence data, and the third polishing influence data.

[0007] Optionally, the first heating device preheats each metal sheet after polishing treatment based on a first adaptive controller, including: Constructing a first adaptive controller based on a PID controller and a state error system; During the process of the first heating device preheating each metal sheet after polishing treatment, calculating the first deviation value between the current temperature of each metal sheet after polishing treatment and the first preset target temperature; Obtaining the temperature change curve of the preheating of the past metal sheets under the control of the PID parameters, and establishing a fuzzy rule based on the temperature change curve; Generating the adjustment control parameters of the first heating device based on the first deviation value using the first adaptive controller in combination with the fuzzy rule, and optimizing the adjustment control parameters based on the whale optimization algorithm to obtain the optimized adjustment control parameters; The first heating device adjusts the temperature during the preheating process based on the optimized adjustment control parameters.

[0008] Optionally, the first adaptive controller constructed based on the PID controller and the state error system includes: Establish an object model for each metal sheet after polishing, construct a fractional-order complex network system based on the object model, and construct a state error system based on the fractional-order complex network system; Calculate the transfer function based on the preset proportional coefficient, preset integral coefficient, and preset differential coefficient, and generate a conventional PID controller based on the transfer function; Tune the parameters of the conventional PID controller to obtain the PID controller with tuned parameters; Construct a first adaptive controller based on the PID controller with tuned parameters and the state error system.

[0009] Optionally, the rolling device performs a rolling process on each metal sheet after preheating to obtain an initial laminate, including: Determine the control parameters of the rolling device based on the viscoelastic model and material parameters of each metal sheet after preheating and the preset desired laminate thickness; The rolling device performs a rolling process on each metal sheet after preheating based on the control parameters to obtain an initial laminate.

[0010] Optionally, the second heating device performs a reheating process on the initial laminate based on the second adaptive controller, including: During the reheating process of the initial laminate, detect the real-time temperature of the initial laminate during reheating and calculate the second deviation value between the real-time temperature and the second preset target temperature; Based on the second adaptive controller, generate adjustment parameters using the second deviation value, and adjust the control parameters of the second heating device in real time based on the adjustment parameters.

[0011] Optionally, the shearing mechanism shears the initial laminate after reheating to obtain a target laminate, including: Cool the initial laminate after reheating to obtain the cooled initial laminate; Analyze the shearing parameters of the cooled initial laminate to obtain shearing control parameters, perform laminate shearing simulation based on the shearing control parameters, and obtain the laminate shearing simulation result; Evaluate the shearing quality based on the laminate shearing simulation result to obtain the shearing quality evaluation coefficient; Optimize the shearing control parameters using the optimization space based on the shearing quality evaluation coefficient to obtain the optimized shearing control parameters; The shearing mechanism shears the cooled initial laminate based on optimized shearing control parameters to obtain the target laminate.

[0012] Optionally, the rewinder performs a rewinding process on the target laminate, including: Determining the rewinding control parameters of the rewinder based on the thickness data and material parameters of the target laminate in combination with the processing attributes, and the rewinder performs a rewinding process on the target laminate based on the rewinding control parameters.

[0013] In addition, the present invention also provides a laminate processing production line, which includes a plurality of unwinding devices, a polishing machine, a plurality of heating devices, a calendering device, a shearing mechanism, and a rewinder. The laminate processing production line is configured to execute the above laminate processing method.

[0014] In the embodiments of the present invention, the unwinding control parameters of the corresponding unwinding device are matched based on the material parameters and processing attributes of each metal sheet, so that the matched unwinding control parameters are more in line with the actual situation of each metal sheet. Based on the roughness analysis and polishing influence analysis of each metal sheet, the corresponding polishing information is determined, and the polishing machine performs a polishing process on each metal sheet based on the corresponding polishing information, which can ensure the reliability of the polishing information analysis and effectively improve the polishing quality of each metal sheet. The first heating device preheats each metal sheet after polishing based on the first adaptive controller, which can effectively regulate the preheating process of each metal sheet and avoid a large deviation between the actual preheating effect and the expected effect. Based on the viscoelastic model and material parameters of each metal sheet after preheating in combination with the preset expected laminate thickness, the control parameters of the calendering device are determined to calender each metal sheet after preheating to obtain the initial laminate, so that the thickness of the obtained initial laminate reaches the expected thickness. The second heating device reheats the initial laminate based on the second adaptive controller, the shearing mechanism shears the initial laminate after reheating to obtain the target laminate, and the rewinder performs a rewinding process on the target laminate, forming a complete process of laminate processing and making the quality of the obtained target laminate more reliable. Description of the Drawings

[0015] Figure 1 is a flowchart of the laminate processing method in the embodiments of the present invention; Figure 2 is a structural diagram of the laminate processing production line in the embodiments of the present invention. Detailed Embodiments

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0017] Embodiment 1: Please refer to Figure 1 , Figure 1 which is a schematic flow chart of the method for processing laminates in the embodiments of the present invention. The method is applied to a laminate processing production line, and the laminate processing production line includes a plurality of unwinding devices, a polishing machine, a plurality of heating devices, a rolling device, a shearing mechanism, and a winding machine; the method includes: S11: Based on the material parameters and processing attributes of each metal sheet, match the unwinding control parameters of the corresponding unwinding device, and each unwinding device transmits each metal sheet to the polishing machine based on the corresponding unwinding control parameters; In the specific implementation process of the present invention, the matching of the unwinding control parameters of the corresponding unwinding device based on the material parameters and processing attributes of each metal sheet includes: determining the starting rotation speed of each corresponding unwinding device based on the material parameters of each metal sheet in combination with the coil diameter data; matching the operating rotation speed of each corresponding unwinding device based on the processing attributes of each metal sheet, and taking the starting rotation speed and the operating rotation speed as the unwinding control parameters of the corresponding unwinding device.

[0018] Specifically, the starting rotation speed of each corresponding unwinding device is determined based on the material parameters of each metal sheet in combination with the coil diameter data. The material parameters include the material type, tensile properties, thickness, etc. of the metal sheet, and the coil diameter data includes the winding radius of the metal sheet and the unwinding parameters of the unwinding device, etc. The starting rotation speed of each corresponding unwinding device is matched in the database through the material parameters of each metal sheet in combination with the coil diameter data. The operating rotation speed of each corresponding unwinding device is matched based on the processing attributes of each metal sheet, and the starting rotation speed and the operating rotation speed are taken as the unwinding control parameters of the corresponding unwinding device. The processing attribute is the processing method and process of the value metal sheet. The intermittent stop parameters for each metal sheet, such as the intermittent stop duration and the intermittent stop distance, etc., are determined according to the processing attributes of each metal sheet. The operating rotation speed of each unwinding device is determined according to the intermittent stop parameters, and the starting rotation speed and the operating rotation speed are taken as the unwinding control parameters of the corresponding unwinding device. Different metal sheets are unwound by different unwinding devices. At the same time, in order to synchronize the subsequent processing, the starting rotation speed and the operating rotation speed can be adjusted so that each metal sheet can be transmitted to the polishing machine simultaneously. Each unwinding device transmits each metal sheet to the polishing machine based on the corresponding unwinding control parameters.

[0019] S12: Determine corresponding polishing information based on the roughness analysis and polishing influence analysis of each metal sheet. The polishing machine polishes each metal sheet based on the corresponding polishing information and transfers the polished metal sheets to the first heating device; In the specific implementation process of the present invention, the determination of the corresponding polishing information based on the roughness analysis and polishing influence analysis of each metal sheet includes: performing apparent feature value analysis on the apparent images of each metal sheet to obtain corresponding apparent feature values, and determining the first roughness data of each metal sheet based on the apparent feature values; inputting the apparent images of each metal sheet into a roughness analysis model to obtain second roughness data, where the roughness analysis model includes a feature extraction network, a cross-mixed attention module, and a graph convolutional channel attention module; determining target roughness data based on the first roughness data and the second roughness data; performing material polishing influence analysis and flatness polishing influence analysis based on the material parameters and flatness of each metal sheet to obtain first polishing influence data and second polishing influence data; performing environmental polishing influence analysis based on real-time environmental information using a topology network to obtain third polishing influence data; determining the corresponding polishing information based on the target roughness data, the first polishing influence data, the second polishing influence data, and the third polishing influence data.

[0020] Specifically, the roughness of the metal sheet is usually not recorded in its parameter table, but its roughness is one of the factors determining the polishing information. Therefore, it is necessary to analyze the roughness of each metal sheet. Analyze the apparent feature values of the apparent images of each metal sheet, collect the apparent images of each metal sheet through the corresponding imaging device, divide the apparent images into grids to obtain the apparent image grid set, perform discrete cosine transform on each apparent image grid to obtain discrete cosine coefficients, extract the direct current coefficient and the alternating current coefficient according to the discrete cosine coefficients, calculate the feature values according to the direct current coefficient and the alternating current coefficient, calculate the average value of the feature values of each grid to obtain the corresponding apparent feature value, and determine the first roughness data of each metal sheet based on the apparent feature value, that is, match the first roughness of each metal sheet according to the apparent feature value. Input the apparent images of each metal sheet into the roughness analysis model to obtain the second roughness data. The roughness analysis model includes a feature extraction network, a cross-mixed attention module, and a graph convolutional channel attention module. The apparent sample images of the metal sheet samples at the same position are collected by configuring image acquisition devices with different light sources as the training image set. The cross-mixed attention module calculates the self-attention mechanism using the features of different rows and columns. It extracts the feature information of different light sources and performs spatial feature fusion on the feature information. The graph convolutional channel attention module calculates the correlation between each channel between different light sources in a self-attention manner as the information of the edges in the graph convolution and splices them in the channel dimension to obtain the mixed channel feature information. The feature extraction network is a multi-branch structure. The initial roughness analysis model is trained through the training image set to obtain a trained roughness analysis model. Training the model with the apparent sample images of metal sheets with different light sources can avoid the influence of the apparent images of metal sheets on the roughness analysis of the model. At the same time, the cross-mixed attention module and the graph convolutional channel attention module are introduced, enabling the model to have stronger feature learning ability, improving the analysis efficiency and accuracy, and finally outputting the second roughness through the roughness analysis model. Determine the target roughness data based on the first roughness data and the second roughness data. The target roughness can be calculated through the first roughness data, the second roughness data, and their corresponding weight coefficients. Calculating the target roughness data through the first roughness data and the second roughness data can avoid the one-sidedness and limitations brought by single roughness analysis.Based on the material parameters and flatness of each metal sheet, material polishing impact analysis and flatness polishing impact analysis are carried out. Different material parameters and flatness of the metal sheet will affect polishing. The flatness can be the difference between the highest point and the lowest point between the surface of each metal sheet and a preset reference plane. Input the material parameters of each metal sheet into the material polishing impact analysis model to obtain the first polishing impact data, that is, the impact degree of different materials on polishing. Input the flatness of each metal sheet into the flatness polishing impact analysis model. The material polishing impact analysis model and the flatness polishing impact analysis model can use a deep convolutional neural network to obtain the second polishing impact data, that is, the impact degree of different flatness on polishing. Based on the topological network, environmental polishing impact analysis is carried out using real-time environmental information. Detect the real-time environmental information of the current environment. The real-time environmental information includes air dust particles, temperature, humidity, etc. For example, if there are too many air dust particles, they will adhere to the surface of the metal sheet, resulting in scratches during the polishing process. If the temperature is too high, it will accelerate the volatilization of the polishing machine, etc. A feature data matrix is constructed through the polishing state environmental impact record data set. According to the feature data matrix, several environmental impact factors are generated. The several environmental impact factors are evaluated to obtain the corresponding environmental impact characteristic values. A topological network is constructed through the environmental impact factors and the corresponding environmental impact characteristic values. Input the real-time environmental information into the topological network to obtain the impact degree of the environmental information on polishing, that is, obtain the third polishing impact data. Determine the corresponding polishing information based on the target roughness data, the first polishing impact data, the second polishing impact data, and the third polishing impact data. Determine the target polishing impact data according to the first polishing impact data, the second polishing impact data, and the third polishing impact data. The target polishing impact data can be determined through weight coefficients. Determine the corresponding polishing information for each metal sheet according to the target roughness data and the target polishing impact data. The polishing machine polishes each metal sheet based on the corresponding polishing information to obtain each polished metal sheet and transmits each polished metal sheet to the first heating device.

[0021] S13: The first heating device preheats each polished metal sheet based on the first adaptive controller and transmits the preheated metal sheets to the rolling device; In the specific implementation process of the present invention, the first heating device preheats each polished metal sheet based on a first adaptive controller, including: constructing a first adaptive controller based on a PID controller and a state error system; during the preheating process of each polished metal sheet by the first heating device, calculating a first deviation value between the current temperature of each polished metal sheet and a first preset target temperature; obtaining the temperature change curve of the preheating of past metal sheets under PID parameter control, and establishing fuzzy rules based on the temperature change curve; generating an adjustment control parameter of the first heating device by combining the first deviation value with the first adaptive controller and the fuzzy rules, and optimizing the adjustment control parameter based on the whale optimization algorithm to obtain an optimized adjustment control parameter; the first heating device adjusts the temperature during the preheating process based on the optimized adjustment control parameter.

[0022] Further, constructing the first adaptive controller based on the PID controller and the state error system includes: establishing an object model of each polished metal sheet, constructing a fractional-order complex network system based on the object model, and constructing a state error system based on the fractional-order complex network system; calculating a transfer function based on a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient, and generating a conventional PID controller based on the transfer function; performing parameter tuning on the conventional PID controller to obtain a PID controller after parameter tuning; constructing a first adaptive controller based on the PID controller after parameter tuning and the state error system.

[0023] Specifically, the polished metal sheets are transported to the first heating device for preheating, so that each metal sheet has viscosity after preheating, so as to be able to roll each metal sheet subsequently. During the preheating process, the heating temperature of the metal sheet will inevitably deviate. In this regard, the temperature needs to be adjusted in time according to the deviation to avoid affecting subsequent processing. An object model of each polished metal sheet is established. The object model is an abstraction of the entity of each metal sheet, which is used as the controlled object. Through the controlled object and the corresponding function, a preset-level abstraction is made, and then the corresponding object model is formed. Based on the object model, a fractional-order complex network system is constructed, and a differential equation corresponding to the object model is established. The fractional-order derivative is taken as the fractional-order order, and the fractional-order derivative is the fractional-order derivative in the sense of Caputo. The fractional-order complex network system is constructed by using the corresponding differential equation through the fractional-order order. Based on the fractional-order complex network system, a state error system is constructed. Considering the existence of uncertainty and unpredictable non-linear states, a non-periodic orbit and an equivalent perturbation of the parameter corresponding to the non-linear state are introduced to construct the target state equation. Based on the target state equation, the state error system between the object model and the fractional-order complex network system is constructed. The transfer function is calculated based on the preset proportional coefficient, preset integral coefficient, and preset differential coefficient. Based on the transfer function, a conventional Proportion Integration Differentiation (PID) controller is generated. The parameters of the conventional PID controller are tuned. Based on the object model, an equivalent treatment is performed to obtain an equivalent model, and the equivalent model is decomposed and calculated to obtain the first-order derivative and the second-order derivative. Based on the first-order derivative and the second-order derivative, a first-order inertia transfer function is generated by combining a preset filtering constant. The first-order inertia transfer function is decomposed to obtain the target parameters, and the parameters of the conventional PID controller are tuned based on the target parameters to obtain the PID controller with tuned parameters. Based on the PID controller with tuned parameters and the state error system, a first adaptive controller is constructed. The equivalent perturbation of the state error system is observed through an extended state observer to obtain an extended state vector. The extended state feedback compensation is obtained by using the preset bandwidth parameter through the extended state vector. The first adaptive controller is constructed according to the extended state feedback compensation and the PID controller with tuned parameters. During the preheating process of the polished metal sheets by the first heating device, the current temperature of each metal sheet is detected by the temperature detector built in the first heating device, and the first deviation value between the current temperature of each polished metal sheet and the first preset target temperature is calculated.Obtain the temperature change curve of the preheating of past metal sheets under PID parameter control. By using PID parameters to simulate the preheating process of past metal sheets, corresponding data is obtained. Based on the corresponding data, the temperature change curve is plotted, and then the temperature change curve is stored in the corresponding database. Through the corresponding database, the temperature change curve can be quickly obtained, and fuzzy rules are established based on the temperature change curve. The dynamic characteristics of temperature change are extracted from the temperature change curve. By the dynamic characteristics, an adjustment speed rule, a static error elimination rule, and a controller oscillation error elimination rule are set. The adjustment speed rule, the static error elimination rule, and the controller oscillation error elimination rule constitute the fuzzy rules. The adjustment speed rule is that when the current real-time temperature is much lower than the preset target temperature, the adjustment speed should be increased to reach the preset target temperature as soon as possible. When the current real-time temperature is lower than the preset target temperature, but the difference between it and the preset target temperature is not large, the adjustment speed can be appropriately slowed down. The static error elimination rule is that in order to make the temperature of the heating device reach the preset target temperature value as soon as possible and be stable, the integral action should be increased in the adjacent area of the preset target temperature. The controller oscillation error elimination rule is to introduce an early differential control signal to quickly correct the deviation generated by the controller and reduce the possible overshoot. Based on the first deviation value, the first adaptive controller combines the fuzzy rules to generate the adjustment control parameters of the first heating device. The first deviation value is input into the first adaptive controller through the fuzzy rules for calculation to obtain the adjustment control parameters, which are the adjustment coefficients for the temperature parameters of the first heating device. And the adjustment control parameters are optimized based on the whale optimization algorithm. According to the whale optimization algorithm, the adjustment control parameters are optimized in the optimization space until the preset number of iterations. When the optimization iteration ends, the optimized adjustment control parameters are obtained. The first heating device adjusts the temperature during the preheating process based on the optimized adjustment control parameters. During the preheating process, the temperature deviation value is continuously detected to adjust the temperature through the first adaptive controller until the preheating process ends, so that the first heating device can correct the deviation in time, and then the preheated metal sheets are transported to the rolling device.

[0024] S14: The rolling device performs rolling treatment on each preheated metal sheet to obtain an initial laminate; In the specific implementation process of the present invention, the rolling device performs rolling treatment on each preheated metal sheet to obtain an initial laminate, including: determining the control parameters of the rolling device based on the viscoelastic model and material parameters of each preheated metal sheet in combination with the preset expected laminate thickness; the rolling device performs rolling treatment on each preheated metal sheet based on the control parameters to obtain an initial laminate.

[0025] Specifically, based on the viscoelastic models and material parameters of the preheated metal sheets and in combination with a preset desired laminate thickness, control parameters of the rolling device are determined. A corresponding viscoelastic model is constructed through the viscoelastic stress, pure viscous stress component, and strain rate tensor of the preheated metal sheets. The preset desired laminate thickness is the desired thickness after the laminate is formed by rolling. Corresponding control parameters are matched according to the viscoelastic model, material parameters, and the preset desired laminate thickness. The control parameters include driving power, rolling accuracy, etc. The rolling device performs rolling treatment on the preheated metal sheets based on the control parameters to obtain an initial laminate, and then transports the initial laminate to a second heating device.

[0026] S15: The second heating device performs reheating treatment on the initial laminate based on the second adaptive controller to obtain the reheated initial laminate. In the specific implementation process of the present invention, the second heating device performing reheating treatment on the initial laminate based on the second adaptive controller includes: during the reheating treatment of the initial laminate, detecting the real-time temperature of the initial laminate during reheating and calculating a second deviation value between the real-time temperature and a second preset target temperature; generating an adjustment parameter based on the second deviation value by using the second adaptive controller, and adjusting the control parameters of the second heating device in real time based on the adjustment parameter.

[0027] Specifically, the second heating device performs reheating treatment on the initial laminate to further and better bond the metal sheets in the initial laminate together. During the reheating treatment of the initial laminate, detecting the real-time temperature of the initial laminate during reheating and calculating a second deviation value between the real-time temperature and a second preset target temperature. Generating an adjustment parameter based on the second deviation value by using the second adaptive controller. The construction steps of the second adaptive controller are the same as those of the first adaptive controller, replacing the object model with the object model of the initial laminate, and then the remaining steps are the same. And adjusting the control parameters of the second heating device in real time based on the adjustment parameter. The second heating device adjusts the temperature during the reheating process according to the adjusted control parameters to avoid temperature deviation until the initial laminate reaches the preset temperature of the reheating process, and then transports the reheated target laminate to a shearing mechanism.

[0028] S16: The shearing mechanism shears the reheated initial laminate to obtain a target laminate, and a coiler performs coiling treatment on the target laminate.

[0029] In the specific implementation process of the present invention, the shearing mechanism shears the initial laminate after reheating treatment to obtain a target laminate, including: cooling the initial laminate after reheating treatment to obtain the cooled initial laminate; analyzing the shearing parameters of the cooled initial laminate to obtain shearing control parameters, performing laminate shearing simulation based on the shearing control parameters to obtain a laminate shearing simulation result; evaluating the shearing quality based on the laminate shearing simulation result to obtain a shearing quality evaluation coefficient; optimizing the shearing control parameters using the optimization space based on the shearing quality evaluation coefficient to obtain optimized shearing control parameters; and the shearing mechanism shears the cooled initial laminate based on the optimized shearing control parameters to obtain the target laminate.

[0030] Further, the winding machine winds the target laminate, including: determining the winding control parameters of the winding machine based on the thickness data and material parameters of the target laminate in combination with the processing attributes, and the winding machine winds the target laminate based on the winding control parameters.

[0031] Specifically, to cool the initial laminate after reheating treatment, a cooling device is provided in the shearing mechanism, and the initial laminate is cooled by the cold air outlet of the cooling device to obtain the cooled initial laminate. Analyzing the shearing parameters of the cooled initial laminate, that is, analyzing the shearing control parameters of the shearing mechanism for the cooled initial laminate. The shearing control parameters include the power of the shearing mechanism, the shearing width, etc. Performing laminate shearing simulation based on the shearing control parameters, inputting the shearing control parameters into the simulation software for laminate shearing simulation to obtain a laminate shearing simulation result. Evaluating the shearing quality based on the laminate shearing simulation result, performing quality evaluations such as shearing accuracy and shearing surface roughness on the laminate shearing simulation result according to the shearing quality evaluation model. The shearing quality evaluation model is constructed by multiple linear regression and random forest models to obtain a shearing quality evaluation coefficient. Optimizing the shearing control parameters using the optimization space based on the shearing quality evaluation coefficient, and the shearing control parameters can be optimized using the shearing quality evaluation coefficient through an optimization algorithm based on the optimization space to obtain optimized shearing control parameters. The shearing mechanism shears the cooled initial laminate based on the optimized shearing control parameters to obtain the target laminate. Determining the winding control parameters of the winding machine based on the thickness data and material parameters of the target laminate in combination with the processing attributes, and the winding machine winds the target laminate based on the winding control parameters. After completing the winding process of the target laminate, the overall processing process of the laminate is completed.

[0032] In the embodiments of the present invention, the unwinding control parameters of the corresponding unwinding equipment are matched based on the material parameters and processing attributes of each metal sheet, so that the matched unwinding control parameters are more in line with the actual situation of each metal sheet. Based on the roughness analysis and polishing influence analysis of each metal sheet, the corresponding polishing information is determined, and the polishing machine polishes each metal sheet based on the corresponding polishing information, which can ensure the reliability of the polishing information analysis and effectively improve the polishing quality of each metal sheet. The first heating device preheats each metal sheet after polishing treatment based on the first adaptive controller, which can effectively regulate the preheating process of each metal sheet and avoid a large deviation between the actual preheating effect and the expected effect. Based on the viscoelastic model and material parameters of each metal sheet after preheating treatment and combined with the preset expected laminate thickness, the control parameters of the rolling device are determined to roll each metal sheet after preheating treatment to obtain an initial laminate, so that the thickness of the obtained initial laminate reaches the expected thickness. The second heating device reheats the initial laminate based on the second adaptive controller, the shearing mechanism shears the initial laminate after reheating treatment to obtain the target laminate, and the winding machine winds the target laminate, forming a complete process for laminate processing, making the quality of the obtained target laminate more reliable.

[0033] Embodiment 2: Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of the laminate processing production line in the embodiments of the present invention.

[0034] As Figure 2 shown, the laminate processing production line includes a plurality of unwinding devices 1, a polishing machine, a plurality of heating devices, a rolling device 3, a shearing mechanism 5, and a winding machine 6, so that the laminate processing production line executes the laminate processing method in the above embodiments.

[0035] In the specific implementation process of the present invention, the unwinding device 1 is used to unwind each metal sheet, the polishing machine is used to polish each metal sheet, the heating devices include a first heating device 2 and a second heating device 4, the first heating device 2 is used to preheat each metal sheet, the second heating device 4 is used for reheating treatment, the rolling device 3 is used to roll each metal sheet to form an initial laminate, the shearing mechanism 5 is used to perform cooling and shearing treatment on the initial laminate, and the winding machine 6 is used to wind the laminate. Figure 2 The shown laminate processing production line does not limit all components, and may include more or fewer components than shown, or combine certain components. The specific implementation manner of the laminate processing production line can refer to the above embodiments and will not be elaborated here.

[0036] In the embodiments of the present invention, the unwinding control parameters of the corresponding unwinding equipment are matched based on the material parameters and processing attributes of each metal sheet, so that the matched unwinding control parameters are more in line with the actual situation of each metal sheet. The corresponding polishing information is determined based on the roughness analysis and polishing influence analysis of each metal sheet, and the polishing machine polishes each metal sheet based on the corresponding polishing information, which can ensure the reliability of the polishing information analysis and effectively improve the polishing quality of each metal sheet. The first heating device 2 preheats each metal sheet after polishing based on the first adaptive controller, which can effectively control the preheating process of each metal sheet and avoid a large deviation between the actual preheating effect and the expected effect. The control parameters of the rolling device are determined based on the viscoelastic model and material parameters of each metal sheet after preheating and in combination with the preset expected laminate thickness, so as to roll each metal sheet after preheating to obtain an initial laminate, and make the thickness of the obtained initial laminate reach the expected thickness. The second heating device 4 reheats the initial laminate based on the second adaptive controller, the shearing mechanism 5 shears the initial laminate after reheating to obtain the target laminate, and the winding machine 6 winds the target laminate, forming a complete process for laminate processing, and making the quality of the obtained target laminate more reliable.

[0037] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium can include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.

[0038] In addition, the above has introduced in detail a laminate processing method and production line provided by the embodiments of the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A layer plate processing method, characterized in that: Applied to a layer plate processing production line, the layer plate processing production line includes a plurality of unwinding devices, a polishing machine, a plurality of heating devices, a calendering device, a shearing mechanism and a winding machine; the method includes: Matching unwinding control parameters of corresponding unwinding devices based on material parameters and processing properties of each metal sheet, each unwinding device transfers each metal sheet to the polishing machine based on the corresponding unwinding control parameters; Based on the roughness analysis and polishing influence analysis of each metal sheet, corresponding polishing information is determined, the polishing machine performs polishing processing on each metal sheet based on the corresponding polishing information, and transmits each metal sheet after the polishing processing to the first heating device; The first heating device performs preheating treatment on each metal sheet after the polishing treatment based on the first adaptive controller, and transmits each metal sheet after the preheating treatment to the calendering device; The calendering device performs calendering treatment on each metal sheet after the preheating treatment to obtain an initial layer plate; The second heating device reheats the initial layer plate based on the second adaptive controller to obtain the initial layer plate after the reheating treatment; The shearing mechanism shears the initial layer plate after the reheating treatment to obtain the target layer plate, and the winding machine winds the target layer plate.

2. The layer processing method according to claim 1, characterized in that: The unwinding control parameters of the unwinding device corresponding to the material parameters and processing properties of each metal sheet are matched, including: Determine the starting speed of each unwinding device based on the material parameters of each metal sheet and the coil diameter data; The operating speed of each unwinding device is matched based on the processing properties of each metal sheet, and the starting speed and the operating speed are used as the unwinding control parameters of each unwinding device.

3. The layer processing method according to claim 1, characterized in that: The determining of corresponding polishing information based on the roughness analysis and polishing influence analysis of each metal sheet includes: Performing an apparent characteristic value analysis on the apparent image of each metal sheet to obtain a corresponding apparent characteristic value, and determining first roughness data of each metal sheet based on the apparent characteristic value; Inputting the surface image of each metal sheet into a roughness analysis model to obtain second roughness data, wherein the roughness analysis model includes a feature extraction network, a cross-hybrid attention module, and a graph convolution channel attention module; determining target roughness data based on the first roughness data and the second roughness data; Perform material polishing influence analysis and flat polishing influence analysis based on material parameters and flatness of each metal sheet to obtain first polishing influence data and second polishing influence data; Perform environmental polishing impact analysis based on topological network using real-time environmental information to obtain third polishing impact data; Corresponding polishing information is determined based on the target roughness data, the first polishing influence data, the second polishing influence data, and the third polishing influence data.

4. The layer processing method according to claim 1, characterized in that: The first heating device performs preheating treatment on each metal sheet after polishing based on the first adaptive controller, including: Constructing the first adaptive controller based on the PID controller and the state error system; During the preheating process of each polished metal sheet by the first heating device, calculating a first deviation value between the current temperature of each polished metal sheet and the first preset target temperature; Obtain the temperature change curve of the metal sheet preheating in the past under the control of PID parameters, and establish fuzzy rules based on the temperature change curve; Based on the first deviation value, a first adaptive controller is used in combination with a fuzzy rule to generate a regulating control parameter of the first heating device, and the regulating control parameter is optimized based on a whale optimization algorithm to obtain an optimized regulating control parameter; The first heating device performs temperature regulation during the preheating process based on the optimized regulation control parameters.

5. The layer processing method according to claim 4, characterized in that: The first adaptive controller is constructed based on the PID controller and the state error system, comprising: Establishing an object model of each metal sheet after polishing, constructing a fractional-order complex network system based on the object model, and constructing a state error system based on the fractional-order complex network system; Calculating a transfer function based on a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient, and generating a conventional PID controller based on the transfer function; Performing parameter tuning on the conventional PID controller to obtain a PID controller after parameter tuning; The first adaptive controller is constructed based on the PID controller after parameter tuning and the state error system.

6. The layer processing method according to claim 1, characterized in that: The calendering device performs calendering on each metal sheet after preheating to obtain an initial layer plate, comprising: Determine the control parameters of the calendering device based on the viscoelastic model and material parameters of each metal sheet after preheating combined with the preset desired layer thickness; The calendering device performs calendering on each metal sheet after the preheating treatment based on the control parameters to obtain an initial layer.

7. The layer processing method according to claim 1, characterized in that: The second heating device reheats the initial layer based on the second adaptive controller, comprising: During the reheating process of the initial layer plate, detecting the real-time temperature of the initial layer plate during the reheating process, and calculating a second deviation value between the real-time temperature and a second preset target temperature; The second adaptive controller generates an adjustment parameter using the second deviation value, and adjusts the control parameter of the second heating device in real time based on the adjustment parameter.

8. The layer processing method according to claim 1, characterized in that: The shearing mechanism shears the initial layer plate after the reheating treatment to obtain the target layer plate, including: Cooling the initial layer plate after the reheating treatment to obtain a cooled initial layer plate; Perform shear parameter analysis on the initial laminate after cooling to obtain shear control parameters, perform laminate shear simulation based on the shear control parameters, and obtain laminate shear simulation results; Perform shear quality evaluation based on the laminate shear simulation results and obtain the shear quality evaluation coefficient; Based on the shear quality evaluation coefficient, the shear control parameters are optimized using the optimization space to obtain the optimized shear control parameters; The shearing mechanism shears the cooled initial layer plate based on the optimized shearing control parameters to obtain the target layer plate.

9. The layer processing method according to claim 1, characterized in that: The winding machine performs a winding process on the target layer plate, including: The winding control parameters of the winding machine are determined based on the thickness data and material parameters of the target layer plate in combination with the processing attributes, and the winding machine performs winding processing on the target layer plate based on the winding control parameters.

10. A layer plate processing production line, characterized in that: The ply processing production line includes a plurality of unwinding devices, a polishing machine, a plurality of heating devices, a calendering device, a shearing mechanism and a winding machine. The ply processing production line is configured to perform the ply processing method described in any one of claims 1 to 9.

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