Self-adaptive switching control method and system for punching, shearing and folding all-in-one machine

Abstract

The invention provides a self-adaptive switching control method and system for a punching, shearing and folding all-in-one machine, and relates to the technical field of automatic control. The method comprises the steps that machining target parameters are obtained for process analysis, and process requirement parameters are determined; collecting state data of the processed plate; based on a preset process control path before processing, matching analysis is carried out by utilizing the process demand parameters and the state data of the processed plate, and process deviation parameters of the current state data are identified; and by taking the process deviation parameter as an adjustment target quantity, performing path process parameter compensation or process path adjustment on a pre-processing preset process control path to obtain self-adaptive control information. The punching, shearing and folding all-in-one machine solves the technical problems that in the prior art, due to dependence on fixed control logic, machining precision and machining efficiency are limited, and the technical effects that the flexibility and adaptability of the punching, shearing and folding all-in-one machine are enhanced, and then the production efficiency and the size precision of machined parts are improved are achieved.

Description

Technical Field

[0001] This application relates to the field of automation control technology, and particularly to an adaptive switching control method and system for a punching, shearing and folding integrated machine. Background Art

[0002] A punching, shearing and folding integrated machine is an intelligent processing equipment integrating punching, shearing and folding functions, and is widely used in the sheet metal processing industry. This equipment can complete a variety of processing processes on one machine, reducing the process conversion time and improving production efficiency.

[0003] At present, the switching control of the punching, shearing and folding integrated machine mainly relies on fixed control logic, that is, performing punching, shearing, folding and other processes according to preset processing paths and process parameters. This method is usually based on a standardized process flow and is applicable to specific types of sheets and processing requirements. However, due to the differences in the physical properties (such as thickness, hardness, elasticity, etc.) of different materials, and unpredictable factors such as material deformation and stress release may occur during the processing, it is difficult for the fixed control logic to adjust the processing parameters in real time, thus affecting the processing accuracy and efficiency, and it is difficult to meet the complex and changeable processing requirements. Summary of the Invention

[0004] This application provides an adaptive switching control method and system for a punching, shearing and folding integrated machine, which solves the technical problem that in the prior art, due to the switching control of the punching, shearing and folding integrated machine relying on fixed control logic, it is difficult to dynamically adjust according to different processing requirements and the real-time changes of the sheet state, resulting in limited processing accuracy and processing efficiency, and achieves the technical effect of enhancing the flexibility and adaptability of the punching, shearing and folding integrated machine, thereby improving production efficiency and the dimensional accuracy of processed parts.

[0005] In view of the above problems, on the one hand, this application provides an adaptive switching control method for a punching, shearing and folding integrated machine, and the method includes: obtaining processing target parameters, performing process analysis on the processing target parameters to determine process requirement parameters; collecting state data of the processed sheet by deploying a sensor array; obtaining a preset process control path before processing; based on the preset process control path before processing, using the process requirement parameters and the state data of the processed sheet for matching analysis to identify the process deviation parameters of the current state data; using the process deviation parameters as the adjustment target quantity, compensating the path process parameters or adjusting the process path of the preset process control path before processing to obtain adaptive control information.

[0006] On the other hand, the present application also provides an adaptive switching control system for a punching, shearing and folding integrated machine. The system includes: a target parameter analysis module, configured to obtain processing target parameters, perform process analysis on the processing target parameters, and determine process requirement parameters; a sheet state acquisition module, configured to acquire state data of the processed sheet by deploying a sensor array; a preset path acquisition module, configured to acquire a preset process control path before processing; a process deviation identification module, configured to perform matching analysis based on the preset process control path before processing, using the process requirement parameters and the state data of the processed sheet, and identify process deviation parameters of the current state data; and a compensation adjustment module, configured to use the process deviation parameters as an adjustment target quantity, perform path process parameter compensation or process path adjustment on the preset process control path before processing, and obtain adaptive control information.

[0007] One or more technical solutions provided in the present application have at least the following beneficial effects: By performing process analysis on the processing target parameters to determine process requirement parameters, a customized process requirement framework is provided for subsequent processing operations, clarifying the specific processing targets. By deploying a sensor array to acquire state data of the processed sheet, various states of the sheet are accurately sensed, providing real-time and comprehensive state information of the processed sheet for subsequent adaptive control. By acquiring the preset process control path before processing, a basic operation framework is provided for the entire processing process, and at the same time, a comparison benchmark is provided for matching analysis with other parameters. By performing matching analysis on the process requirement parameters and the state data of the processed sheet with the preset process control path, the deviation between the current processing state and the ideal state can be accurately found, clarifying the subsequent adjustment targets. According to the previously identified process deviation parameters, the preset process control path is compensated or adjusted to obtain adaptive control information, enabling the punching, shearing and folding integrated machine to dynamically adjust the processing process according to the actual situation, ensuring the accuracy and efficiency of processing.

[0008] In summary, the present application improves the processing accuracy of the punching, shearing and folding integrated machine and the quality of processed parts, and enhances the flexibility and adaptability of the equipment, enabling it to more accurately respond to changes in different processing requirements and sheet states, effectively improving production efficiency and automation level, and providing strong support for the high-efficiency and accurate processing of the punching, shearing and folding integrated machine in the field of intelligent manufacturing.

[0009] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are hereinafter specifically exemplified. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1It is a schematic flow chart of the adaptive switching control method for a punching, shearing and folding integrated machine provided by an embodiment of the present application.

[0011] Figure 2 It is a schematic flow chart of identifying the process deviation parameters of the current state data in the adaptive switching control method for a punching, shearing and folding integrated machine provided by an embodiment of the present application.

[0012] Figure 3 It is a schematic flow chart of compensating the path process parameters for the preset process control path before processing in the adaptive switching control method for a punching, shearing and folding integrated machine provided by an embodiment of the present application.

[0013] Figure 4 It is a schematic structural diagram of the adaptive switching control system for a punching, shearing and folding integrated machine provided by an embodiment of the present application.

[0014] Explanation of reference numerals: target parameter analysis module 10, sheet state acquisition module 20, preset path acquisition module 30, process deviation identification module 40, compensation adjustment module 50. Detailed implementation manners

[0015] By providing an adaptive switching control method and system for a punching, shearing and folding integrated machine, an embodiment of the present application solves the technical problems in the prior art that the switching control of the punching, shearing and folding integrated machine depends on a fixed control logic and it is difficult to dynamically adjust according to different processing requirements and the real-time changes of the sheet state, resulting in limited processing accuracy and processing efficiency, and achieves the technical effect of enhancing the flexibility and adaptability of the punching, shearing and folding integrated machine, thereby improving the production efficiency and the dimensional accuracy of the processed parts.

[0016] Embodiment 1, as Figure 1 shown, an embodiment of the present application provides an adaptive switching control method for a punching, shearing and folding integrated machine, and the method includes: Step S1: Obtain the processing target parameters, perform process analysis on the processing target parameters, and determine the process requirement parameters.

[0017] Specifically, the processing target parameters refer to the targets such as dimensions, tolerances, shapes, surface quality, etc. that the product needs to achieve during the processing. For example, when manufacturing a metal bracket, the processing target parameters may include a bending angle of 90°, a sheet thickness of 3 mm, a shearing tolerance of ±0.1 mm, etc. The process requirement parameters refer to the processing parameters that specifically need to be set in order to meet the processing targets, such as punching force, shearing speed, bending force, etc. For example, for a 3-mm thick steel plate, a pressure of 50 kN may be required during bending. First, extract the processing target parameters from the design drawings or numerical control programs, which are usually provided by CAD (Computer-Aided Design) software or CAM (Computer-Aided Manufacturing) systems. Then, use an analysis algorithm based on the process database to analyze these parameters and determine the suitable processing methods and process requirement parameters in combination with material properties (such as hardness, ductility, etc.).

[0018] Step S1 clarifies the specific targets and requirements of the processing, converts the processing targets into specific and operable process requirement parameters, provides an accurate guiding direction for the subsequent processing process, and avoids the blindness of the processing.

[0019] Step S2: Collect the state data of the processed sheet by deploying a sensor array.

[0020] Specifically, the sensor array is a system composed of multiple sensors for real-time collection of various state information of the processed sheet, such as deformation, stress, temperature, etc. The state data of the processed sheet refers to the data describing the physical properties and changes of the sheet during the processing, such as thickness, residual stress, temperature gradient, etc. Install a variety of sensors on the punching, shearing and folding integrated machine, including: laser thickness gauge, strain gauge, infrared thermal imager, etc. The laser thickness gauge is used to measure the minute changes in the sheet thickness; the strain gauge is used to measure the residual stress of the sheet to ensure that no accidental deformation occurs after bending or stamping; the infrared thermal imager is used to detect the temperature distribution during the processing. Collect data in real time through the sensors and transmit the data to the control system through a data acquisition card. For example, use an NI data acquisition card to collect the data of the laser thickness gauge. Integrate the data collected by different sensors according to the time series to form comprehensive sheet state data.

[0021] Collecting the state data of the processed sheet in real time through the sensor array can sense the actual processing situation, provide data support for subsequent adaptive adjustment, and improve the processing accuracy and consistency.

[0022] Step S3: Obtain the preset process control path before processing.

[0023] Specifically, the pre - processing preset process control path refers to the optimal processing sequence and parameters set in advance based on material properties, historical processing data, and success rate analysis. For example, for a certain sheet metal part, the processing sequence may be punching first, then shearing, and finally bending to ensure processing accuracy. According to material testing and historical data, physical characteristics such as the material properties, thickness, and shape of the sheet are determined. For example, the ductility and hardness of aluminum alloy sheets. Based on the physical characteristics and historical processing record data, a search algorithm (such as a genetic algorithm) is used to find the process control path with the highest processing success rate. The matched process path and parameters are stored in the control system as the reference path before processing. Exemplarily, when processing aerospace aluminum alloy components, it is found through analyzing the past 1000 processing historical data that bending first and then drilling can reduce hole deformation compared to drilling first and then bending. Therefore, this path is automatically recommended as the pre - processing preset process control path.

[0024] By presetting the process control path, a basic processing operation framework and reference are provided, reducing the preparation time before processing and improving production efficiency.

[0025] Step S4: Based on the pre - processing preset process control path, use the process requirement parameters and the state data of the processed sheet for matching analysis to identify the process deviation parameters of the current state data.

[0026] Specifically, the process deviation parameters refer to the differences between the actual processing state and the ideal processing state, including dimensional deviation, stress deviation, temperature anomalies, etc. Using data fitting and optimization algorithms, the process requirement parameters, the collected state data of the processed sheet, and the pre - processing preset process control path are input into a data analysis system or control algorithm for comparative analysis to check the matching degree between the two. Through the matching analysis, the deviation parameters between the actual state data and the preset path are found. For example, a control system based on the PID (Proportional - Integral - Derivative) control algorithm can be used. Through the algorithm, mathematical operations and logical analysis are performed on these three to identify the process deviation parameters. For example, it is identified that the sheet thickness deviation is 0.2 mm.

[0027] Through the matching analysis, the process deviations in the processing process can be accurately identified, providing an accurate target quantity for subsequent adjustments, thereby improving the processing accuracy and quality.

[0028] Step S5: Using the process deviation parameters as the adjustment target quantity, perform path process parameter compensation or process path adjustment on the pre - processing preset process control path to obtain adaptive control information.

[0029] Specifically, the identified process deviation parameters are used as the adjustment target quantity. According to the process deviation parameters, the process parameters of the preset process path are adjusted, and the preset process path is re-planned. For example, the processing parameters are automatically adjusted through a feedback control algorithm (such as PID control) to adapt to the actual state of the sheet metal. The adjusted process parameters and path are stored in the control system to generate adaptive control information. For example, a PLC (programmable logic controller) is used to store and execute the adaptive control information.

[0030] By adjusting the processing parameters in real time or optimizing the process path, the adaptive ability of the punching, shearing and folding machine is improved, enabling it to dynamically respond to changes in the processing state and improve the processing accuracy and efficiency.

[0031] Further, step S3 includes: Step S31: Obtain the physical characteristics of the processed sheet metal. The physical characteristics of the processed sheet metal include material properties, thickness, shape, and size, where the material properties include ductility, hardness, expansion coefficient, and elasticity.

[0032] Step S32: Based on the physical characteristics and combined with historical processing record data, perform a punching, shearing and folding process path matching search with the goal of maximizing the processing success probability to obtain the preset process control path before processing.

[0033] Specifically, the physical characteristics of the processed sheet metal refer to the key material properties that affect the processing quality and accuracy, including material properties, thickness, shape, size and other characteristics. Material properties are the basic mechanical properties of the material, such as ductility, hardness, expansion coefficient, elasticity, etc. For example, stainless steel has a higher hardness, while aluminum alloy has better ductility. The thickness of the sheet metal affects the shear force, bending springback, etc. For example, a 1mm thick sheet is easier to bend than a 3mm thick sheet, but is prone to deformation. Shape refers to the initial shape of the sheet metal, such as a rectangular plate, a circular plate, etc. Different shaped sheet metals require different processing paths. For example, circular sheet metal may require additional positioning processes. Size refers to the specific size information such as the length and width of the sheet metal, which affects the selection of the punching, shearing and folding path. Through material testing and historical data recording, information such as the material properties, thickness, shape, and size of the sheet metal is obtained. Exemplarily, first, the sheet metal is measured by sensors. A laser thickness gauge is used to measure the thickness of the sheet metal, a 3D scanner or machine vision system is used to scan the shape of the sheet metal to obtain complete geometric information, and a hardness tester is used to measure the material hardness, such as Brinell hardness (HB) or Rockwell hardness (HRC). The measured physical characteristics are matched with a material database (containing mechanical property data of different materials). For example, the sheet metal is identified as "Q235 steel plate", and then its hardness, ductility and other information are extracted from the database. The obtained physical characteristic data is stored in the database or control system to provide basic data for subsequent process path matching search.

[0034] Historical processing record data stores the successful or failed experiences of processing similar materials in the past, including parameters such as shearing, bending, stamping, etc. Using search algorithms (such as genetic algorithms, simulated annealing algorithms, etc.) combined with historical processing record data, the physical characteristics of the current sheet are analyzed by matching to find the most likely successful process path. The matched process path and parameters are stored in the control system as the reference path before processing. For example, in the past, on sheets with the same thickness and material, the process path with the smallest bending angle error was considered the path with the highest processing success probability.

[0035] By combining historical data and the physical characteristics of the current sheet, the most likely successful process path is selected, which improves the rationality and reliability of the process path setting, increases the processing success rate, and reduces the trial - and - error cost and scrap rate.

[0036] Furthermore, step S32 includes: Step S321: Using the physical characteristics as an index, search in the historical processing record data to obtain matching record data.

[0037] Step S322: Extract positive examples and negative examples according to the matching record data to obtain a positive example sample set and a negative example sample set.

[0038] Step S323: Fit the influence relationship between the process control path and the processing quality according to the positive example sample set and the negative example sample set, evaluate the success probability of the process processing path based on the influence relationship, and obtain the process processing path with the highest processing success probability as the pre - set process control path before processing. The pre - set process control path before processing includes the processing switching sequence of punching, shearing, and folding processes and the corresponding path process parameters.

[0039] Specifically, physical characteristics such as the material, thickness, shape, and size of the sheet are used as retrieval keywords. For example, using "thickness 2mm, Q235 steel, rectangular plate" as the index field, search for historical processing records similar to the physical characteristics of the current sheet in the historical processing record data to obtain matching record data, which serves as the basis for subsequent analysis. In the actual operation process, database indexes (such as balanced multi - way search tree index, hash index) can be used to improve the search efficiency. For example, establish a combined index of "sheet thickness + material + shape" in the SQL database to accelerate the matching. Vector similarity search (such as FAISS, Annoy) is used to match multi - dimensional physical characteristics to improve the retrieval accuracy.

[0040] Analyze each of the obtained matching record data one by one, and judge whether each record is a positive example (a case of successful processing) or a negative example (a case of failed processing) according to the pre-set processing quality standards. The success criteria include meeting the processing accuracy requirements, having no obvious defects, and stable equipment operation, etc. For example, if the success criterion is set that the dimensional error of the processed part is within ±0.1 mm to be qualified, then the records with dimensional errors within this range are extracted as positive examples, and the records outside this range are extracted as negative examples. Screen the cases of successful processing from the historical data as the "positive example sample set", and at the same time screen the cases of failed processing from the historical data as the "negative example sample set". Through the extraction of positive and negative examples, the historical processing record data is divided into two types of sample sets, success and failure, providing a targeted data source for fitting the influence relationship between the process control path and the processing quality in the follow-up.

[0041] Use regression analysis (such as linear regression, logistic regression) or machine learning algorithms (such as decision tree algorithm) to fit the influence relationship between the process control path and the processing quality according to the positive example sample set and the negative example sample set, and find out the influence of process parameters (such as bending angle, shear force) on the processing quality. Exemplarily, for regression analysis, the parameters in the process control path (such as the order and parameter values of punching, shearing, and folding) are used as independent variables, and the processing quality indicators (such as dimensional accuracy, surface roughness) are used as dependent variables, and a regression equation is established through the data of the positive example sample set and the negative example sample set. For the decision tree algorithm, a decision tree is constructed with the process control path and the processing quality results as nodes and branches to obtain an influence relationship model between the process control path and the processing quality. Predict the success probability of different process processing paths according to the fitted influence relationship, calculate the processing success probability under different process processing paths, and select the process path with the highest success probability as the preset process control path. The preset process control path includes the processing switching order of punching, shearing, and folding processes and the corresponding path process parameters.

[0042] Evaluating the success probability of the process processing path by fitting the influence relationship can scientifically select the process processing path with the highest processing success probability as the preset process control path before processing, improving the rationality and reliability of the preset process control path, and helping to improve the processing success rate and product quality.

[0043] Furthermore, step S2 includes: Step S21: Deploy a sensor array, including a laser thickness gauge, a strain gauge, and an infrared thermal imager. Real-time collect the deformed thickness of the sheet through the laser thickness gauge to obtain the local deformation of the sheet; collect the residual stress distribution of the sheet through the strain gauge; collect the microscopic temperature gradient of the processed sheet through the infrared imager.

[0044] Step S22: Integrate the local deformation, residual stress distribution, and micro temperature gradient data of the sheet according to the acquisition time to obtain the state data of the processed sheet.

[0045] Specifically, a laser thickness gauge is deployed in the processing area of the punching, shearing, and folding machine to ensure that it can cover the entire surface of the processed sheet. It can detect the thickness change of the sheet in real time during processing. Based on the data collected by the laser thickness gauge, a thickness distribution map of the sheet can be generated, thereby obtaining the local deformation of the sheet, which helps to determine whether uneven deformation or material loss has occurred. Strain gauges are deployed at the key stress points of the sheet, such as the bending area and punching area, to collect the residual stress distribution of the sheet in real time. Based on the data collected by the strain gauges, a residual stress distribution map of the sheet can be generated to analyze the stress state of the sheet and prevent problems such as warping and cracking after processing. An infrared thermal imager is deployed above or on the side of the processing area to ensure that it can cover the entire surface of the processed sheet. Based on the infrared radiation principle, it monitors the temperature change of the sheet during processing. Based on the data collected by the infrared thermal imager, a temperature distribution map of the sheet can be generated to analyze the micro temperature gradient of the processed sheet and prevent material property changes (such as metal tempering and thermal deformation) caused by local overheating.

[0046] During the data acquisition process, each sensor will attach a corresponding time stamp when collecting data. After obtaining the original data of the local deformation, residual stress distribution, and micro temperature gradient of the sheet, align the data from different sensors according to the time dimension, and combine the spatial information to correlate and integrate these three types of data to form complete sheet state data. For example, during processing, record that "at a certain time point, the thickness of the sheet = 2.1 mm, stress = 5 MPa, temperature = 150 °C". In actual operation, a time stamp alignment method (such as the NTP protocol) is used for data time synchronization to ensure the time consistency of all sensor data. For example, the sampling time interval of the laser thickness gauge is 1 ms, the strain gauge is 10 ms, and the infrared thermal imager is 50 ms. Data alignment needs to be performed through an interpolation algorithm. The Kalman filter algorithm is used to fuse the data of different sensors to improve the measurement accuracy. For example, if the thickness measured by the laser thickness gauge does not match the stress measured by the strain gauge, the data can be corrected through the filter algorithm. Finally, SCADA (Supervisory Control and Data Acquisition System) is used for real-time data monitoring. For example, the thickness, stress, and temperature change curves of the sheet are displayed on the industrial control screen. The data is stored in an industrial big data platform (such as SQL database, time series database InfluxDB) for subsequent analysis.

[0047] Through multi-dimensional real-time monitoring and data fusion, complete sheet state information is obtained, enabling subsequent process adjustments to optimize the processing path based on accurate real-time data, improving the intelligent manufacturing ability of the punching, shearing, and folding machine, and enhancing the processing accuracy and stability.

[0048] Further, step S1 includes: Step S11: Establish the influence correspondence between the punching, shearing, and folding processes and the result parameters of the processed product. The influence correspondence includes the structural form influence relationship and the appearance parameter influence relationship.

[0049] Step S12: Perform product part and appearance parameter matching analysis on the processing target parameters according to the influence correspondence to obtain the processing correspondence between the processing target parameters and the punching, shearing, and folding processes, as well as the process requirement parameters. Among them, the process requirement parameters characterize the processing parameter requirements of the punching, shearing, and folding processes corresponding to achieving the processing target parameters.

[0050] Specifically, the result parameters of the processed product refer to the key indicators such as the form, dimensional accuracy, and appearance quality of the processed product, such as structural form parameters (such as bending angle, punching hole position) and appearance parameters (such as surface roughness, edge burr situation). The influence correspondence refers to the influence relationship of different processes on the quality of the final product, including the structural form influence relationship and the appearance parameter influence relationship. The structural form influence relationship describes how the punching, shearing, and folding processes affect the structural form of the processed product. For example, the stamping process may form specific holes or shapes on the product, thereby changing the structural form of the product; the bending process will change the product from a flat surface to a three-dimensional structure, changing its overall structural layout. The appearance parameter influence relationship describes the influence of the punching, shearing, and folding processes on the appearance parameters of the product. For example, if the accuracy of the shearing process is insufficient, it may cause the edges of the product to be uneven, affecting the flatness of the appearance; improper selection and operation of the die during the bending process may leave scratches on the surface of the product, affecting appearance parameters such as the smoothness of the product.

[0051] Collect a large amount of product data after punching, shearing, and folding processes, including the structural form, appearance parameters of the product, and the specific process parameters used. Then, analyze these data through regression analysis or deep learning models (such as neural networks) to find the correlation rules between the punching, shearing, and folding processes and the result parameters of the processed product, thereby establishing the structural form influence relationship and the appearance parameter influence relationship. For example, use orthogonal experiments to design different combinations of process parameters, measure the result parameters of the processed product, use the Pandas and Scikit-learn libraries in Python for data analysis and model establishment to obtain the relationship model between the process parameters and the result parameters, and then use historical processing data to train and optimize the established influence correspondence model to improve the accuracy and reliability of the model.

[0052] According to the established corresponding relationship between the punching, shearing, and folding processes and the result parameters of the processed products, the product parts and appearance parameters in the processing target parameters are decomposed and analyzed. For product parts, according to their shape, structure, etc., suitable punching, shearing, and folding process combinations and corresponding process parameters are found in the corresponding relationship. For appearance parameters, similarly based on the corresponding relationship, the process operation methods and parameters that can meet the appearance requirements are determined. Integrate these process operation methods and parameters to obtain the processing corresponding relationship between the processing target parameters and the punching, shearing, and folding processes and the process requirement parameters. For example, if the product part in the processing target parameters is a corner that needs to be precisely bent and the appearance requirement is a smooth surface, then find suitable bending process parameters, such as suitable bending dies, bending pressure, bending speed, etc., in the structural form influence relationship and the appearance parameter influence relationship to ensure that the bending angle is precise and the surface is smooth.

[0053] Through matching analysis, the processing corresponding relationship between the processing target parameters and the punching, shearing, and folding processes and the process requirement parameters can be obtained, which makes the processing process have clear process guidance, helps improve processing efficiency, reduces the blindness of process selection, and improves product quality.

[0054] Furthermore, as Figure 2 shown, step S4 includes: Step S41: Identify the current processing process and obtain the post-processing control path according to the pre-set process control path before processing.

[0055] Step S42: Obtain the requirement parameters of the current matching process from the process requirement parameters according to the current processing process.

[0056] Step S43: Targeting the requirement parameters of the current matching process, perform process parameter simulation according to the state data of the processed sheet and the post-processing control path to obtain the process simulation processing result.

[0057] Step S44: Perform differential tracing based on the process simulation processing result and the requirement parameters of the current matching process to obtain the process deviation parameters of the current state data.

[0058] Specifically, the control system software, sensor monitoring system, or intelligent manufacturing system (MES) or ERP system of the punching, shearing and folding machine is used to identify the currently ongoing processing process. Then, the corresponding processing process in the pre-processing preset process control path is matched with the obtained pre-processing preset process control path as the current matching process, and then the part after the current matching process is extracted, that is, the post-processing control path. For example, in an automated punching, shearing and folding processing system, the current stage is determined by sensors or program logic, and then the process control parameters and operation sequence of shearing and bending are separated from the pre-stored complete process control path data as the post-processing control path.

[0059] The identified process requirement parameters are filtered and extracted to determine the process requirement parameters corresponding to the identified current matching process. For example, in a database storing process requirement parameters for stamping, shearing, bending, etc., when the current matching process is determined to be shearing, the required parameters such as the cutting angle of the shearing tool and the shearing speed are obtained by querying the fields related to the shearing process in the database.

[0060] The state data of the sheet metal being processed (such as local deformation, residual stress distribution, and micro-temperature gradients) and the post-processing control path (including the process operation sequence and process parameters) are input into a pre-established process simulation model or simulation software to simulate the process parameters. This process generates a prediction of the subsequent processing, known as the process simulation result. For example, a finite element model of the sheet metal can be established using finite element analysis software. The sheet metal state data serves as the model's initial conditions, and the post-processing control path serves as the loading conditions. The simulation program is then run to obtain the process simulation result. Alternatively, virtual machining platforms (such as Simulink and SolidWorks) can be used to simulate the effects of punching, shearing, and folding processes on the sheet metal, predicting the final results and obtaining the process simulation result. The process simulation result includes predictions of product shape, size, quality, and other aspects.

[0061] The process simulation results are compared with the required parameters of the current matching process one by one, and the difference between each parameter is calculated. For example, for dimensional parameters, the difference between the simulation results and the required parameters in terms of length and width is calculated; for quality parameters, the difference in aspects such as surface roughness and hardness is calculated. Then, based on the size and direction of the difference, the process deviation parameters are determined.

[0062] By obtaining process deviation parameters through process simulation and differential tracing, possible deviations can be predicted before processing, providing accurate target quantities for subsequent deviation analysis and process adjustments, thereby achieving precise control of the processing process, avoiding problems in actual processing, and improving processing accuracy and product quality.

[0063] Further, as Figure 3 shown, step S5 includes: Step S51: According to the pre - set process control path before processing, analyze the processing nodes and corresponding processing parameters of punching, shearing, and folding processes, and construct a processing graph structure.

[0064] Step S52: Map the acquisition process time nodes of the process deviation parameters to the processing graph structure. Based on the processing graph structure, with the required parameters of the current matching process as the target, perform graph structure decomposition to obtain path process parameter compensation information.

[0065] Step S53: Obtain the adaptive control information according to the path process parameter compensation information.

[0066] Specifically, the processing graph structure represents the logical relationship between various process steps through a graph data structure, providing a visual framework for subsequent analysis and operations, which helps to more intuitively and clearly understand the process flow and parameter relationship of the entire punching, shearing, and folding processes. Extract each processing node of the punching, shearing, and folding processes and the corresponding processing parameters from the pre - set process control path before processing. For example, for the stamping process, the processing nodes may be punching, blanking, etc., and the corresponding processing parameters include stamping pressure, die size, etc. Then, according to these processing nodes and parameters, using a graph construction method, take the processing nodes as the nodes of the graph, and the processing parameters as the attributes of the nodes or the weights of the edges, etc., to construct the processing graph structure.

[0067] The acquisition process time node of process deviation parameters refers to the time point or time period in the processing corresponding to the acquisition of process deviation parameters, which reflects the time position where the process deviation occurs. Corresponding the acquisition process time node of process deviation parameters to the relevant processing nodes in the processing drawing structure. For example, if the process deviation parameter is collected at a certain time during the bending process, find the corresponding bending processing node in the processing drawing structure. Then, aiming at the required parameters of the current matching process, use graph algorithms (such as the shortest path algorithm, connected component algorithm, etc.) to decompose the processing drawing structure containing deviation information, analyze the relationship between the processing nodes related to the deviation and their upstream and downstream nodes, calculate the numerical value and direction of the processing parameters that need to be adjusted, etc., so as to obtain the path process parameter compensation information. Exemplarily, the process deviation parameter is a bending angle deviation of +2°. Find the bending node in the processing drawing, and trace back forward to analyze whether it is an error caused by stamping positioning error or material deformation caused by shear stress. Use the graph structure decomposition algorithm (such as Dijkstra algorithm) to analyze the influencing path and adjust the relevant process parameters. If blanking causes bending error, adjust the blanking positioning accuracy; if shearing causes residual stress, adjust the shearing speed. Through deviation mapping and graph structure decomposition, the deviation source can be accurately found, and the optimal compensation parameters can be calculated to improve the processing accuracy.

[0068] The adaptive control information is a new process control instruction generated after adjusting the path process parameters, enabling the equipment to dynamically adjust the processing strategy. According to the path compensation information, generate new control instructions, for example: increase the pressure of the stamping machine by a certain value or increase the springback compensation of the bending. Through the PLC (Programmable Logic Controller) or CNC control system, transmit the adjustment information to the equipment execution layer to achieve closed-loop control.

[0069] Through adaptive control, the punching, shearing and bending integrated machine can dynamically adjust the process parameters according to the real-time deviation, ensure high precision and high consistency, and improve the processing stability and product quality.

[0070] Furthermore, obtaining the adaptive control information in step S5 further includes: Step S54: When the path process parameter compensation information cannot meet the required parameters of the current matching process, based on the processing drawing structure, identify the dependency relationships of each processing node.

[0071] Step S55: According to the dependency relationships of each processing node, perform process sequence switching adjustment, compensate the process deviation parameters, and obtain the adaptive control information, where the adaptive control information is process path switching adjustment information or a combination of process path switching adjustment information and path process parameter compensation information.

[0072] Specifically, in the previous steps, process deviations are compensated by adjusting process parameters (such as blanking pressure, shearing speed, bending angle, etc.). However, in some cases, even if these parameters are adjusted, the final processing quality requirements still cannot be met. At this time, it is necessary to consider the adjustment of process sequence switching. When it is determined that the process parameter compensation information of the path cannot meet the requirements, graph traversal algorithms (such as depth-first search algorithm, breadth-first search algorithm) are used to traverse the processing graph structure, and the forward and backward dependencies of each processing node are analyzed, that is, the mutual influence between each processing step (such as blanking, shearing, bending). At the same time, the knowledge rule base of the processing technology can be combined to analyze and organize the traversal results to obtain accurate dependencies. For example, by checking the directed edges between nodes in the processing graph structure (if represented by a directed graph), the direction of the edges can represent the sequence of the processing order, that is, the dependency. By analyzing the attributes of the nodes and the characteristics of the edges, identify which nodes must be processed before or after other nodes, and which nodes' outputs are the inputs of other nodes, etc. The identification of the dependencies of the processing nodes provides a basis for possible subsequent process sequence switching adjustments, helps to comprehensively consider the mutual influence between each link in the processing process, and thus formulate a more reasonable adaptive control strategy.

[0073] According to the identified dependencies of each processing node, determine the order of the processing nodes that can be switched and adjusted. For example, if it is found that the process deviation of a certain node cannot be solved by parameter compensation in the current order and there are other feasible orders, then the process sequence is switched. Then, according to this switching adjustment, recalculate the compensation method for the process deviation parameters to obtain the process path switching adjustment information. If the adjustment of process parameters also needs to be combined, then combine the process path switching adjustment information with the path process parameter compensation information to form the final adaptive control information. In the actual operation process, a logical judgment algorithm can be used to judge whether the process sequence needs to be switched and how to switch according to the dependencies and process deviation situations. At the same time, combine the mathematical calculation model to recalculate the process deviation compensation method, and finally convert the information into an executable instruction form according to the requirements of the punching, shearing and bending integrated machine control system.

[0074] Through the adjustment of process sequence switching and the combination with the path process parameter compensation information, it is possible to respond to process deviation situations more flexibly and comprehensively, improve the ability of adaptive control, and further ensure the accuracy of the processing process and the product quality.

[0075] Furthermore, after obtaining the adaptive control information, it further includes: Step S56: According to the processing target parameters, obtain the structural form and appearance parameter targets of the processed product, construct a product structure model, and fit the structural form and appearance parameter targets of the processed product into the product structure model for positioning and marking.

[0076] Step S57: According to the adaptive control information and the state data of the processed sheet material, perform product structure processing positioning, project it into the product structure model, and conduct a production simulation evaluation of the positioned product structure based on the projection data. When the product structure simulation evaluation result is consistent with the processing target parameters of the positioning mark, determine the adaptive control information.

[0077] Specifically, after determining the adaptive control information, a simulation model can be constructed according to the product structure to conduct real-time simulation verification of the adaptive control information, ensuring the effectiveness and accuracy of the adaptive control information.

[0078] First, extract the structural form and appearance parameter targets of the processed product from the processing target parameters. For example, for a metal box, the structural form target is a cuboid shape with specific length, width, and height dimensions, and the appearance parameter target is a smooth surface without scratches, etc. Then, use computer-aided design (CAD) software or 3D modeling software (such as SolidWorks) to construct a product structure model, fit the extracted structural form and appearance parameter targets into the model according to the actual structural relationship of the product, and perform positioning marks by setting specific marking points, colors, or attribute values, etc., clearly marking the processing target parameters corresponding to the key processing areas on the model. Constructing a product structure model with positioning marks provides a standard reference for subsequent production simulation evaluation, facilitating an intuitive comparison of the differences between the actual processing results and the processing target parameters, and thus accurately judging the effectiveness of the adaptive control information.

[0079] With the help of digital twin technology, simulate the processing operation of the processed sheet material based on the adaptive control information, and at the same time combine the state data of the processed sheet material (such as local deformation of the sheet material, residual stress distribution, etc.) to determine the product structure processing positioning. For example, according to the process parameter adjustment and process sequence adjustment in the adaptive control information, perform simulation processing such as punching, shearing, and folding on the sheet material, and consider the current state of the sheet material to ensure the accuracy of the processing position and form. Then, project the simulation processing results into the previously constructed product structure model, compare and analyze the projection data with the processing target parameters of the positioning mark, such as calculating the shape deviation, dimension error, etc., judge whether the processing error exceeds the allowable range, and obtain the production simulation evaluation result. If the evaluation result shows that the product structure simulation evaluation result is consistent with the processing target parameters of the positioning mark (within the allowable error range), it is determined that the current adaptive control information is effective and can be used in the actual processing process.

[0080] Through production simulation evaluation, it is possible to verify the adaptive control information before actual processing, ensure that the adaptive control information can accurately guide the processing process to meet the requirements of the processing target parameters, and improve the processing accuracy and product quality.

[0081] In summary, the adaptive switching control method for the punching, shearing and folding integrated machine provided by the embodiments of the present application has the following beneficial effects: In the embodiments of the present application, first, the processing target parameters are obtained and subjected to process analysis to determine the process requirement parameters, ensuring that the processing process can accurately match the product requirements. Subsequently, by deploying a sensor array, the state data of the processed sheet is collected, including the deformation thickness, residual stress distribution, and microscopic temperature gradient, so as to comprehensively perceive the physical state of the sheet and provide data support for subsequent process optimization. Based on the state data of the processed sheet, combined with the physical characteristics of the sheet and historical processing records, a matching search method is used to select the process path with the highest processing success probability, and the preset process control path before processing is obtained to ensure the rationality of the initial process path. During the actual processing, based on the preset path before processing, the process requirement parameters are matched and analyzed with the state data of the processed sheet to identify the process deviation parameters of the current state data. Taking the process deviation parameters as the adjustment target, by analyzing the processing nodes and processing parameters, a processing graph structure is constructed, and combined with the process time nodes, the path process parameter compensation information is calculated. When the path process parameter compensation cannot fully meet the processing requirements, the dependency relationship of the processing nodes is further analyzed, and the process sequence is switched and adjusted to ensure the comprehensiveness and accuracy of the process optimization. Finally, combined with the adaptive control information and the sheet state data, the processing positioning and simulation evaluation are carried out through the product structure model to ensure that the final adaptive control information can meet the requirements of the processing target parameters.

[0082] Generally speaking, through the combination of real-time data collection, process path optimization, and intelligent control strategies, the embodiments of the present application realize the intelligent, precise, and automated processing of the punching, shearing and folding integrated machine under different process requirements and sheet states, improve the processing accuracy, production efficiency, and flexible adaptation ability of the equipment, and provide strong support for the efficient and precise processing of the punching, shearing and folding integrated machine in the field of intelligent manufacturing.

[0083] Embodiment 2, as Figure 4 shown, based on the same inventive concept as the foregoing Embodiment 1, the embodiments of the present application provide an adaptive switching control system for a punching, shearing and folding integrated machine, and the system includes: A target parameter analysis module 10, configured to obtain processing target parameters, perform process analysis on the processing target parameters, and determine process requirement parameters.

[0084] A sheet state acquisition module 20, configured to collect state data of a processed sheet by deploying a sensor array.

[0085] A preset path acquisition module 30, configured to obtain a preset process control path before processing.

[0086] The process deviation identification module 40 is used to perform matching analysis on the process requirement parameters and the state data of the processed sheet based on the preset process control path before processing, and identify the process deviation parameters of the current state data.

[0087] The compensation adjustment module 50 is used to take the process deviation parameters as the adjustment target quantity, perform path process parameter compensation or process path adjustment on the preset process control path before processing, and obtain adaptive control information.

[0088] Furthermore, the preset path acquisition module 30 in the embodiment of the present application is further used to perform the following steps: Obtain the physical characteristics of the processed sheet, where the physical characteristics of the processed sheet include material properties, thickness, shape, and size, and the material properties include ductility, hardness, expansion coefficient, and elasticity; based on the physical characteristics and combined with historical processing record data, perform a matching search for the punching, shearing, and folding process paths with the goal of maximizing the processing success probability, and obtain the preset process control path before processing.

[0089] Furthermore, the preset path acquisition module 30 in the embodiment of the present application is further used to perform the following steps: Search in the historical processing record data with the physical characteristics as the index to obtain matching record data; perform positive example extraction and negative example extraction according to the matching record data to obtain a positive example sample set and a negative example sample set; fit the influence relationship between the process control path and the processing quality according to the positive example sample set and the negative example sample set, evaluate the success probability of the process processing path based on the influence relationship, and obtain the process processing path with the highest processing success probability as the preset process control path before processing, where the preset process control path before processing includes the processing switching sequence of punching, shearing, and folding processes and the corresponding path process parameters.

[0090] Furthermore, the sheet state acquisition module 20 in the embodiment of the present application is further used to perform the following steps: Deploy a sensor array, including a laser thickness gauge, a strain gauge, and an infrared thermal imager. Real-time collect the deformed thickness of the sheet through the laser thickness gauge to obtain the local deformation of the sheet; collect the residual stress distribution of the sheet through the strain gauge; collect the microscopic temperature gradient of the processed sheet through the infrared imager; integrate the local deformation of the sheet, the residual stress distribution, and the microscopic temperature gradient data according to the collection time to obtain the state data of the processed sheet.

[0091] Furthermore, the target parameter analysis module 10 in the embodiment of the present application is further used to perform the following steps: Establish the corresponding relationship between the punching, shearing, and folding processes and the result parameters of the processed products. The corresponding relationship includes the structural form influence relationship and the appearance parameter influence relationship. Perform product part and appearance parameter matching analysis on the processing target parameters according to the corresponding relationship to obtain the processing corresponding relationship between the processing target parameters and the punching, shearing, and folding processes, as well as the process requirement parameters. Among them, the process requirement parameters characterize the processing parameter requirements of the punching, shearing, and folding processes to achieve the processing target parameters.

[0092] Further, the process deviation identification module 40 in the embodiment of the present application is further configured to perform the following steps: Identify the current processing process, and obtain the post-processing control path according to the pre-processing preset process control path; obtain the requirement parameters of the current matching process from the process requirement parameters according to the current processing process; take the requirement parameters of the current matching process as the target, and perform process processing parameter simulation based on the state data of the processed sheet and the post-processing control path to obtain the process simulation processing result; perform difference tracing according to the process simulation processing result and the requirement parameters of the current matching process to obtain the process deviation parameters of the current state data.

[0093] Further, the compensation adjustment module 50 in the embodiment of the present application is further configured to perform the following steps: According to the pre-processing preset process control path, analyze the processing nodes and corresponding processing parameters of the punching, shearing, and folding processes, and construct a processing diagram structure; map to the processing diagram structure according to the acquisition process time nodes of the process deviation parameters. Based on the processing diagram structure, take the requirement parameters of the current matching process as the target, and perform diagram structure decomposition to obtain path process parameter compensation information; obtain the adaptive control information according to the path process parameter compensation information.

[0094] Further, the compensation adjustment module 50 in the embodiment of the present application is further configured to perform the following steps: When the path process parameter compensation information cannot meet the requirement parameters of the current matching process, based on the processing diagram structure, identify the dependency relationship of each processing node; perform process sequence switching adjustment according to the dependency relationship of each processing node to compensate for the process deviation parameters to obtain the adaptive control information, and the adaptive control information is the process path switching adjustment information or a combination of the process path switching adjustment information and the path process parameter compensation information.

[0095] Further, the compensation adjustment module 50 in the embodiment of the present application is further configured to perform the following steps: According to the processing target parameters, obtain the structural form and appearance parameter targets of the processed product, construct a product structure model, and fit the structural form and appearance parameter targets of the processed product into the product structure model for positioning and marking; according to the adaptive control information and the state data of the processed sheet, perform product structure processing positioning, project it into the product structure model, and perform production simulation evaluation of the positioned product structure based on the projection data. When the product structure simulation evaluation result is consistent with the processing target parameters of the positioning mark, determine the adaptive control information.

[0096] Through the foregoing detailed description of the adaptive switching control method for the punching, shearing and folding integrated machine in this specification, those skilled in the art can clearly know the adaptive switching control system for the punching, shearing and folding integrated machine in this embodiment. For the system disclosed in Embodiment 2, since it corresponds to the method disclosed in Embodiment 1, it has corresponding functional modules and beneficial effects. For the relevant parts, reference can be made to the description in the method part.

[0097] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An adaptive switching control method for a punching, shearing and folding integrated machine, characterized in that, Including: Obtain the processing target parameters, perform process analysis on the processing target parameters, and determine the process requirement parameters; Collect the state data of the processed sheet by deploying a sensor array; Obtain the preset process control path before processing; Based on the preset process control path before processing, perform matching analysis using the process requirement parameters and the state data of the processed sheet to identify the process deviation parameters of the current state data; Using the process deviation parameters as the adjustment target quantity, perform path process parameter compensation or process path adjustment on the preset process control path before processing to obtain adaptive control information.

2. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 1, wherein, Obtain the preset process control path before processing, including: Obtain the physical characteristics of the processed sheet, where the physical characteristics of the processed sheet include material properties, thickness, shape, and size, and the material properties include ductility, hardness, expansion coefficient, and elasticity; Based on the physical characteristics and combined with historical processing record data, perform a matching search for the punching, shearing, and folding process paths with the goal of maximizing the processing success probability to obtain the preset process control path before processing.

3. The adaptive switching control method for the punching, shearing and folding integrated machine according to claim 2, wherein, Obtain the preset process control path before processing, including: Search in the historical processing record data using the physical characteristics as an index to obtain the matching record data; Extract positive examples and negative examples according to the matching record data to obtain a positive example sample set and a negative example sample set; Fit the influence relationship between the process control path and the processing quality according to the positive example sample set and the negative example sample set, evaluate the success probability of the process processing path based on the influence relationship, and obtain the process processing path with the highest processing success probability as the preset process control path before processing. The preset process control path before processing includes the processing switching sequence of punching, shearing, and folding processes and the corresponding path process parameters.

4. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 1, wherein, Collect the state data of the processed sheet by deploying a sensor array, including: Deploy a sensor array, including a laser thickness gauge, a strain gauge, and an infrared thermal imager. The deformation thickness of the sheet is collected in real time by the laser thickness gauge to obtain the local deformation of the sheet; the residual stress distribution of the sheet is collected by the strain gauge; the microscopic temperature gradient of the processed sheet is collected by the infrared imager; Integrate the local deformation of the sheet, the residual stress distribution, and the microscopic temperature gradient data according to the collection time to obtain the state data of the processed sheet.

5. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 1, characterized in that Perform process analysis on the processing target parameters to determine the process requirement parameters, including: Establish the influence correspondence relationship between the punching, shearing, and folding processes and the processing product result parameters, where the influence correspondence relationship includes the structural form influence relationship and the appearance parameter influence relationship; According to the influence correspondence relationship, perform matching analysis on the processing target parameters for the product part and appearance parameters to obtain the processing correspondence relationship between the processing target parameters and the punching, shearing, and folding processes and the process requirement parameters. Among them, the process requirement parameters represent the processing parameter requirements for the punching, shearing, and folding processes to achieve the processing target parameters.

6. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 1, wherein, Based on the preset process control path before processing, perform matching analysis using the process requirement parameters and the state data of the processed sheet to identify the process deviation parameters of the current state data, including: Identify the current processing technology, and obtain the post-processing control path according to the pre-set process control path before processing; Obtain the required parameters of the current matching process from the process requirement parameters according to the current processing technology; Taking the required parameters of the current matching process as the target, perform process parameter simulation based on the state data of the processed sheet and the post-processing control path to obtain the process simulation result; Perform differential tracing based on the process simulation result and the required parameters of the current matching process to obtain the process deviation parameters of the current state data; 7. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 6, wherein Taking the process deviation parameters as the adjustment target quantity, perform path process parameter compensation or process path adjustment on the pre-set process control path before processing to obtain adaptive control information, including: According to the pre-set process control path before processing, analyze the processing nodes and corresponding processing parameters of punching, shearing, and folding processes, and construct a processing diagram structure; Map to the processing diagram structure according to the acquisition process time node of the process deviation parameters. Based on the processing diagram structure, taking the required parameters of the current matching process as the target, perform diagram structure decomposition to obtain path process parameter compensation information; Obtain the adaptive control information according to the path process parameter compensation information; 8. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 7, wherein, Obtaining the adaptive control information also includes: When the path process parameter compensation information cannot meet the required parameters of the current matching process, identify the dependency relationship of each processing node based on the processing diagram structure; Perform process sequence switching adjustment according to the dependency relationship of each processing node, compensate the process deviation parameters, and obtain the adaptive control information. The adaptive control information is a combination of process path switching adjustment information or process path switching adjustment information and path process parameter compensation information; 9. The adaptive switching control method for a punching, shearing and folding integrated machine according to claim 8, characterized in that, After obtaining the adaptive control information, it also includes: According to the processing target parameters, obtain the structural form and appearance parameter target of the processed product, construct a product structure model, and fit the structural form and appearance parameter target of the processed product into the product structure model for positioning and marking; Perform product structure processing positioning according to the adaptive control information and the state data of the processed sheet, project it into the product structure model, and perform production simulation evaluation of the positioned product structure according to the projection data. When the product structure simulation evaluation result is consistent with the processing target parameters of the positioning mark, determine the adaptive control information; 10. An adaptive switching control system for a punching, shearing and folding integrated machine, characterized in that, The system is used to execute the adaptive switching control method for a punching, shearing, and folding machine according to any one of claims 1-9, including: A target parameter analysis module, configured to obtain processing target parameters, perform process analysis on the processing target parameters, and determine process requirement parameters; A sheet state acquisition module, configured to acquire state data of the processed sheet by deploying a sensor array; A pre-set path acquisition module, configured to acquire a pre-set process control path before processing; A process deviation identification module, configured to perform matching analysis on the basis of the pre-set process control path before processing, using the process requirement parameters and the state data of the processed sheet, and identify the process deviation parameters of the current state data; A compensation adjustment module, which is used to take the process deviation parameter as an adjustment target quantity, perform path process parameter compensation or process path adjustment on the preset process control path before processing, and obtain adaptive control information.

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