A bending machine system based on real-time springback compensation and a method for dynamic calibration of bending angle

Abstract

The present invention relates to the field of bending machines, and in particular to a bending machine system based on real-time rebound compensation and a method for dynamic calibration of bending angles, comprising a bending machine slider, a workbench, a linear guide rail, a sensor and a compensation calculation module, and an electric control cabinet; an upper mold is provided at the bottom of the bending machine slider, a lower mold matching the upper mold is provided above the workbench, a material to be bent is placed on the lower mold, the linear guide rails are symmetrically arranged on both sides of the workbench, angle detectors are symmetrically arranged on the linear guide rails, a high-precision angle sensor is built in the angle detector for real-time collection of material bending angle data, and the data is uploaded to a control system of the electric control cabinet through a communication module; a sensor and a compensation calculation module are built in the electric control cabinet, and a free-degree rotating arm is provided on the electric control cabinet. Through real-time feedback, dynamic compensation and intelligent decision-making, the accuracy and efficiency bottlenecks caused by material rebound are solved, and the system has significant industrial application value.

Description

Technical Field

[0001] The present invention relates to the field of bending machines, and in particular to a bending machine system based on real-time rebound compensation and a method for dynamic calibration of bending angles. Background Art

[0002] In traditional sheet metal bending processing, the material will rebound after bending due to its own elastic properties, causing the actual bending angle to deviate from the target angle. Existing technologies usually rely on the operator's experience to perform manual compensation adjustments, and multiple bending attempts are required to achieve the target angle, which is inefficient and has poor consistency. In addition, traditional bending machines lack a real-time angle feedback mechanism, and the compensation process relies on static parameters, which cannot dynamically adapt to changes in working conditions of different materials, thicknesses or mold combinations. In response to the above-mentioned technical deficiencies, the present invention provides a bending machine system based on real-time rebound compensation and a method for dynamic calibration of the bending angle. Through real-time feedback, dynamic compensation and intelligent decision-making, the accuracy and efficiency bottlenecks caused by material rebound are solved, while the requirements for operator skills are reduced. It is suitable for high-precision sheet metal processing fields such as aerospace and automobile manufacturing, and has significant beneficial effects of industrial application value. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems existing in the prior art and to propose a method for dynamic calibration of bending angles.

[0004] In order to achieve the above-mentioned objectives, the present invention adopts the following technical solutions: a bending machine system based on real-time rebound compensation, comprising a bending machine slider, a workbench, a linear guide rail, a sensor and a compensation calculation module, and an electric control cabinet; an upper mold is provided at the bottom of the bending machine slider, a lower mold matching the upper mold is provided above the workbench, and the material to be bent is placed on the lower mold, the linear guide rails are symmetrically arranged on both sides of the workbench, and angle detectors are symmetrically arranged on the linear guide rails, and a high-precision angle sensor is built into the angle detector for real-time collection of material bending angle data and uploading it to the control system of the electric control cabinet through a communication module; a sensor and a compensation calculation module are built into the electric control cabinet, and a degree of freedom rotating arm is provided on the electric control cabinet, and the sensor and compensation calculation module control the superimposed compensation angle during the secondary bending of the bending machine slider according to the target angle formula: target angle θ0=180°-A-(B+C), where B+C is the material rebound angle Δθ, and A is the base angle of the lower mold.

[0005] Furthermore, the sensor and compensation calculation module have a built-in iterative compensation algorithm, and the specific steps include:

[0006] S1. After the material is bent for the first time, the actual bending angle θ1 of the material is obtained through the angle detector;

[0007] S2. Calculate the material rebound angle Δθ = θ1 - target angle θ 0， Among them, θ0 is the user-set value;

[0008] S3. Generate compensation value according to the formula compensation angle C=K×Δθ, where K is the material rebound coefficient, and its value range is 0.8≤K≤1.2. It is generated by fitting the mapping relationship between Δθ and material type and thickness in historical bending data;

[0009] S4. Add the compensation angle C to the secondary bending instruction to make the secondary bending angle θ1+C, and update the K value in real time to achieve dynamic optimization.

[0010] Furthermore, the control system has a built-in multi-dimensional material database, and the storage fields of the multi-dimensional material database at least include material type a, thickness range, material rebound coefficient K, historical data of compensation angle C and corresponding material rebound angle Δθ;

[0011] When the user inputs the target angle θ0, the system matches the compensation strategy through the following steps:

[0012] According to the material type a and thickness range, the springback coefficient is set to Ka and the historical compensation angle is set to Ca, and the associated springback coefficient Ka and historical compensation angle Ca are extracted from the multi-dimensional material database;

[0013] Combined with the real-time bending pressure F, the compensation angle C'=C is corrected by the formula a ×K a ×(1+λF), where λ is the pressure influence factor, ranging from 0.01 to 0.05, and is used to dynamically adjust the compensation value;

[0014] The corrected C' is embedded in the secondary bending instruction. At the same time, the current compensation result and the material springback angle Δθ are transmitted back to the multi-dimensional material database. The mapping relationship between the springback coefficient Ka and the historical compensation angle Ca is updated to achieve data closed-loop optimization.

[0015] A method for dynamic calibration of the bending angle of a bending machine system based on real-time springback compensation according to any one of the above methods comprises the following steps:

[0016] S1, when the material is bent for the first time, the angle detector collects the actual bending angle θ1 of the material in real time;

[0017] S2, calculate the actual bending angle after material springback θ2 = θ1-Δθ;

[0018] S3. If θ2 does not reach the target angle θ0, the compensation angle C=θ0-θ2 is set, and the secondary bending angle is controlled to θ1+C;

[0019] S4. The compensation data is stored in the control system through the communication module and is used for subsequent bending of the same batch of materials.

[0020] Furthermore, a pressure sensor is integrated into the linkage mechanism between the freedom arm and the bending machine slider to monitor the dynamic resistance value F during the bending process in real time. d The control system is configured to convert the dynamic resistance value F d The compensation algorithm is input synchronously with the angle change Δφ of the freedom arm, through the formula: Calculate the compensation angle, where α is the weight coefficient of the angle change and β is the dynamic resistance value F d The weight coefficient of the two dynamically adjusts the range of the compensation angle C according to the material properties; the compensation angle C is used to correct the displacement trajectory of the bending machine slider to optimize the bending accuracy.

[0021] Furthermore, the visual interactive interface of the bending process includes the following modules:

[0022] Target angle input module: provides digital input controls or knob adjustment controls for setting the target angle of the bending process;

[0023] Real-time angle curve display area: Dynamically displays the comparison curve of the actual bending angle θ1 of the material and the target angle, and simultaneously marks the calculation result of the compensation angle C;

[0024] Historical compensation data retrieval button: After triggering, the compensation angle C and dynamic resistance value F of the historical bending process are displayed in the form of a table or chart d and the associated data of weight coefficients α and β;

[0025] Abnormal rebound warning function: When the real-time monitored compensation angle C deviation exceeds the preset threshold, an alarm is issued and bending is automatically suspended;

[0026] The visual interactive interface communicates with the main control unit in the control system via a data bus to achieve closed-loop control of parameter input, real-time monitoring and process correction.

[0027] Furthermore, a high-precision simulation module is integrated into the control system, and the high-precision simulation module is configured to perform the following steps:

[0028] (a) Receive the material characteristic parameters of material type a input by the user: including elastic modulus E, thickness range t, yield strength And preset rebound coefficient K;

[0029] (b) Based on elastic modulus E, thickness range t, and yield strength And the preset rebound coefficient K, the bending rebound dynamic model is established through finite element analysis, and the theoretical rebound angle deviation ΔR is calculated. The formula is: , where θ0 is the preset bending target angle;

[0030] (c) comparing the theoretical springback angle deviation ΔR with actual springback data in a multi-dimensional material database, and generating a compensation scheme through an iterative optimization algorithm, the compensation scheme comprising:

[0031] (1) Compensation angle calculation formula: , where α, β, and γ are dynamic weight coefficients, Δφ is the angle change of the freedom arm, and F d It is the dynamic resistance value monitored in real time;

[0032] (2) Bending machine slider displacement trajectory correction parameters , where λ1 is the displacement correction factor, S 初始 Indicates the initial state value or base value, S 修正 Indicates the corrected state value;

[0033] (3) The compensation angle calculation results and the corrected displacement trajectory of the bending machine slider are displayed in real time through a visual interactive interface, and the compensation scheme is automatically synchronized to the motion control unit of the bending machine to achieve closed-loop compensation control in the subsequent bending process; the high-precision simulation module supports user-defined multi-dimensional material parameter library, and adjusts the optimization range of weight coefficients α, β, γ and displacement correction factor λ1 through a visual interactive interface.

[0034] Compared with the existing technology, the advantages of the present invention are:

[0035] The present invention provides a bending machine system based on real-time rebound compensation and a method for dynamic calibration of the bending angle. Through real-time feedback, dynamic compensation and intelligent decision-making, it solves the accuracy and efficiency bottlenecks caused by material rebound, while reducing the requirements for operator skills. It is suitable for high-precision sheet metal processing fields such as aerospace and automobile manufacturing, and has significant beneficial effects in industrial application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a three-dimensional structural diagram of the present invention;

[0037] Figure 2 This is the main view of the present invention;

[0038] Figure 3 It is a side view of the present invention;

[0039] Figure 4 This is an application state diagram of the bending process of the material of the present invention;

[0040] In the figure: 1. Bending machine slider, 2. Workbench, 3. Linear guide, 4. Electric control cabinet, 5. Upper mold, 6. Lower mold, 7. Angle detector, 8. Freedom arm. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0042] Example 1, please refer to the accompanying drawings in the specification Figure 1-Figure 3 As shown in the figure, a bending machine system based on real-time rebound compensation includes a bending machine slider 1, a workbench 2, a linear guide 3, a sensor and compensation calculation module, and an electric control cabinet 4; an upper mold 5 is provided at the bottom of the bending machine slider 1, and a lower mold 6 matching the upper mold 5 is provided above the workbench 2, and the material to be bent is placed on the lower mold 6, the linear guide 3 is symmetrically arranged on both sides of the workbench 2, and an angle detector 7 is symmetrically arranged on the linear guide 3, and a high-precision angle sensor is built in the angle detector 7 for real-time collection of material bending angle data and uploading it to the control system of the electric control cabinet 4 through the communication module; a sensor and a compensation calculation module are built in the electric control cabinet 4, and a degree of freedom rotating arm 8 is provided on the electric control cabinet 4, and the compensation calculation module controls the superimposed compensation angle during the secondary bending of the bending machine slider 1 according to the target angle formula: target angle θ0=180°-A-(B+C), where B+C is the material rebound angle Δθ, and A is the base angle of the lower mold 6.

[0043] The specific implementation steps in this plan are as follows:

[0044] System composition and installation: A replaceable upper die 5 is installed at the bottom of the bending machine slider 1 to apply bending pressure. The workbench 2 is fixed above the bending machine frame, and a lower die 6 is installed above the workbench 2. In this embodiment, the lower die 6 matches the upper die 5 and is made of the same material. It is used to support the material to be bent (such as 304 stainless steel plate, thickness 2-5mm). High-precision linear guides 3 are installed symmetrically on both sides of the workbench 2. Each linear guide 3 is equipped with an angle detector 7 (such as model: KTR-HG35, accuracy of ±0.1°). The angle detector 7 is equipped with a high-dynamic response angle sensor to detect the actual bending angle of the material in real time during the bending process. Electronic control system: The electronic control cabinet 4 is equipped with a control system (such as a Siemens S7-1200 industrial PLC), sensors, and a compensation calculation module (based on an algorithm developed in Python). A free-degree-of-freedom swing arm 8 is connected to the outside of the electronic control cabinet 4 to adjust the compensation displacement trajectory of the bending machine slider 1.

[0045] Parameter setting and initialization:

[0046] The base angle of the lower mold 6 (A): pre-determined based on the geometry of the upper mold 5 and the lower mold 6 (for example, if the theoretical bending angle is 90° when the upper mold 5 and the lower mold 6 are closed, then A = 90°);

[0047] Material rebound angle Δθ: obtained through material pre-experimentation (e.g., the rebound angle B+C=3° for 304 stainless steel at 2mm thickness);

[0048] Target angle formula: Target angle θ0 = 180° - A - (B + C). For example, if the final bending angle is 85°, the target angle after compensation is θ0 = 180° - A - (B + C), θ0 = 180° - 90° - 3° = 87°.

[0049] In this implementation, the algorithm system in the sensor and compensation calculation module (based on the algorithm program developed in Python) adopts a PID closed-loop control algorithm to compare the target angle θ0 with the actual bending angle θ1 in real time and dynamically correct the compensation value. Before processing each batch of materials, the material rebound angle Δθ can be automatically calibrated by trial bending three times to ensure compensation accuracy. The angle detector 7 is laser calibrated once a week to eliminate mechanical wear errors.

[0050] The beneficial effects achieved in this embodiment are: after testing, the system can reduce the material bending angle error from ±2° of the traditional process to ±0.5°, and the rebound compensation response time is ≤50ms. It is suitable for high-precision bending scenarios such as automotive sheet metal and aviation aluminum alloy, and the production efficiency is improved by more than 30%. This solution effectively solves the bending accuracy problem caused by material springback through real-time detection, dynamic compensation and closed-loop control technology, and significantly improves the stability and consistency of the bending process.

[0051] Example 2, based on the above-mentioned Example 1, an iterative compensation algorithm is built into the sensor and compensation calculation module, and the specific steps include:

[0052] S1. After the material is bent for the first time, the actual bending angle θ1 of the material is obtained through the angle detector;

[0053] S2. Calculate the actual rebound angle of the material Δθ = θ1 - target angle θ 0， Among them, θ0 is the user-set value;

[0054] S3. Generate compensation value according to the formula compensation angle C=K×Δθ, where K is the material rebound coefficient, and its value range is 0.8≤K≤1.2. It is generated by fitting the mapping relationship between Δθ and material type and thickness in historical bending data;

[0055] S4. Add the compensation angle C to the secondary bending instruction to make the secondary bending angle θ1+C, and update the K value in real time to achieve dynamic optimization.

[0056] In this embodiment, the entire process of the embodiment can be embodied through system configuration and parameter optimization, iterative compensation algorithm implementation steps, and closed-loop optimization and calibration:

[0057] System configuration and parameter optimization: Equipped with a servo motor-driven high-precision press brake, such as the AMADA HG-1003, with a maximum pressure of 100 tons and a repeatability of ±0.01mm. Angle detector 7: Using a laser angle sensor (model: KEYENCEL K-H050, resolution ±0.05°), installed on the linear guides 3 on both sides of the press brake worktable 2. An electronic control system (such as a Siemens S7-1200 industrial PLC) and sensor and compensation calculation module (based on a Python-developed algorithm program) support real-time data communication (Ethernet / IP protocol). A material parameter library is established: Initial values ​​of the rebound coefficient K for common materials such as 304 stainless steel and 6061 aluminum alloy are pre-stored. For example: 304 stainless steel (thickness 2mm): K = 1.0; 6061 aluminum alloy (thickness 3mm): K = 0.9. A K value mapping table is fitted using historical bending data to associate the corresponding relationship between material type, thickness, and rebound angle Δθ.

[0058] The implementation steps of the iterative compensation algorithm are as follows: the first bending and data collection, the operator sets the target angle θ0 (such as 90°), and places the material to be bent (for example: 304 stainless steel, thickness 2mm) on the lower mold 6; the bending machine performs the first bending, and the angle detector 7 collects the actual bending angle θ1 (for example, 88.5°) in real time; calculate the actual rebound angle Δθ: the sensor and compensation calculation module calculate the material rebound angle according to the formula: Δθ= θ1 -θ0=88.5°-90°=-1.5° (exceeding ± a certain accuracy means it does not meet the standard); dynamically generate the compensation angle C: the system calls the material parameter library, matches the initial K value (K=1.0) corresponding to the current material type and thickness, and calculates the compensation angle according to the formula: C=K×Δθ=1.0×(-1.5°)=-1.5° (negative compensation means the bending angle needs to be increased); if there is a similar working condition in the historical data (when Δθ=-1.5°, the actual K is corrected to 1.1), then dynamically adjust the K value to 1.1 to optimize the compensation accuracy; Secondary bending and K value update: superimpose the compensation angle C to the secondary bending instruction, the secondary bending angle is θ1+C=88.5°+(-1.5°)=87° (the actual bending angle after compensation approaches the target angle). After the secondary bending is completed, detect the actual bending angle θ2 (for example, 89.8°), calculate Δθ2=89.8°-90°=-0.2°; update the K value in reverse according to Δθ2: K {new} =K {old} ×(1+α×Δθ2) (α is the learning rate, the default is 0.05), for example, K {old} =K=1.1→K {new} =1.1×(1+0.05×-0.2)=1.089; Closed-loop optimization and calibration: Dynamic learning mechanism: After every 10 bends, the system automatically calculates the Δθ value, corrects the k value, and updates the multi-dimensional material database; Abnormal processing: If the deviation is greater than ±0.3° after three consecutive compensations, an alarm is triggered and a prompt is given to check the wear of the upper mold 5 or the lower mold 6 or the consistency of the material; Calibration process: After starting the machine daily, a bending test is performed on a standard test block (angle 85°±0.1°) to calibrate the sensor zero drift.

[0059] The effects achieved in this embodiment are: in terms of precision improvement, the bending angle error of 304 stainless steel is reduced from ±1.5° to ±0.3°, and the compensation response time is <30ms. Adaptive capability: the system can train the k-value mapping model through 200 historical bending data, and the compensation accuracy is improved by 40%; application scenarios: suitable for fields such as precision electronic housings and aerospace structural parts that require an angle tolerance of ≤±0.5°.

[0060] In Example 3, based on the above Example 1, the control system has a built-in multi-dimensional material database, and the storage fields of the multi-dimensional material database at least include material type a, thickness range, rebound coefficient K, historical compensation angle C and corresponding material rebound angle Δθ;

[0061] When the user inputs the target angle θ0, the system matches the compensation strategy through the following steps:

[0062] According to the material type a and thickness range, set the rebound coefficient to K a , the historical compensation angle is C a , extract the associated rebound coefficient K from the database a and historical compensation angle C a ;

[0063] Combined with the real-time bending pressure F (collected by the arm pressure sensor), the compensation angle is corrected by the formula , where λ is the pressure influence factor, ranging from 0.01 to 0.05, and is used to dynamically adjust the compensation value;

[0064] The corrected C' is embedded in the secondary bending instruction. At the same time, the compensation result and the material springback angle Δθ are sent back to the multi-dimensional material database to update the springback coefficient K. a and historical compensation angle C a The mapping relationship is established to achieve data closed-loop optimization.

[0065] In the above embodiment, the system is first configured and a multi-dimensional material database is constructed: the bending machine is equipped with a high-precision servo control system (such as TRUMPF TruBend 5000) and an integrated arm pressure sensor (model: HBM U10M, range 0-200kN, accuracy ±0.1%). The database fields include: material type a (such as SUS304, AL6061-T6); thickness range (segmented storage, such as 1-3mm, 3-5mm); material rebound coefficient K (dynamically updated value, initial value based on experimental data); historical compensation angle Ca (the average of the last 10 compensation angles); material rebound angle Δθ (the difference between the target angle and the target angle is recorded);

[0066] Table 1: Sample data table, as follows:

[0067] Material Type Thickness range <![CDATA[Rebound coefficient K a > Historical compensation angle Ca Δθ mean SUS304 2-3mm 1.05 +1.2° -0.3°

[0068] Compensation strategy matching and parameter extraction:

[0069] User input: Enter the target angle θ0 (e.g. θ0 = 85°) on the operation interface, select material type a (SUS304), and thickness (2.5mm);

[0070] Multi-dimensional material database query: The system matches the nearest neighbor entry based on material type a and thickness range (such as SUS304 with a thickness of 2-3mm) and extracts the initial parameters: Ka = 1.05 (current material rebound coefficient); Ca = +1.2° (historical compensation angle average);

[0071] Real-time pressure data fusion and compensation correction:

[0072] Pressure data acquisition: The arm pressure sensor collects the real-time bending pressure F (for example, F=75kN) and calculates the pressure deviation ΔF=(F-F0) / F0 (F0 is the theoretical pressure value);

[0073] Compensation angle correction formula:

[0074] Parameter description: λ = 0.03 (pressure influence factor, set according to material plasticity); Substitute into the calculation: C = 1.2° × 1.05 × (1 + 0.03 × 0.02) = 1.26° × 1.0006 ≈ 1.2608°;

[0075] Secondary bending instruction: add the corrected compensation angle C = 1.26° to the target angle, and the secondary bending target value is θ0 + C = 85° + 1.26° = 86.26°;

[0076] Data closed-loop feedback and dynamic optimization:

[0077] Deviation feedback: After the secondary bending is completed, the angle detector measures the bending angle θ'=85.9°, and calculates Δθ=θ'-θ0=+0.9°;

[0078] Update the multi-dimensional material database: associate and store the current compensation angle C = 1.26° with △θ = +0.9°; recalculate Ka and Ca based on the latest 10 data points; , that is, Ka=1.05×(1-0.02×0.9)=1.0311; Ca new =(ΣC) / 10 (the sliding window mean is updated to 1.25°)

[0079] Abnormal handling: If △θ>1° for three consecutive times, the "material parameter abnormality" alarm is triggered, prompting manual calibration or replacement of the upper mold 5 or lower mold 6.

[0080] In this embodiment, by integrating the multi-dimensional material database with real-time pressure data, dynamic matching and closed-loop optimization of the compensation strategy are achieved, which significantly reduces the angle deviation under complex working conditions and reduces the dependence on manual parameter adjustment, providing a scalable technical framework for intelligent bending processes.

[0081] Example 4, a method for dynamic calibration of the bending angle of a bending machine system based on real-time springback compensation, comprising the following steps:

[0082] S1. When the material is bent for the first time, the angle detector 7 collects the actual bending angle θ1 of the material in real time. The operator inputs the target angle θ0 (e.g., 90°) and places the material to be bent (e.g., a 2mm thick 6061 aluminum alloy plate) on the lower die 6. The press brake performs the first bend, and the angle detector collects the actual bending angle θ1 (e.g., θ1 = 92.5°) at the moment the bend is completed in real time.

[0083] S2. Calculate the actual angle θ2 after material rebound = θ1 - Δθ (Δθ is the material rebound angle). After the material rebounds naturally, use the angle detector to measure the actual angle θ2 in the stable state again (for example, θ2 = 89.3°). Calculate the material rebound angle △θ: △θ = θ1 - θ2 = 92.5° - 89.3° = 3.2°.

[0084] S3. If θ2 does not reach the target angle θ0, the compensation angle C = θ0-θ2, and the secondary bending angle is controlled to θ1+C; determine whether θ2 reaches the target angle θ0. If θ2 = 89.3° < θ0 = 90°, generate the compensation angle C; C = θ0-θ2 = 90°-89.3° = 0.7°; correct the secondary bending target angle to: θ1+C = 92.5° + 0.7° = 93.2°; the control system drives the bending machine slider 1 to move down to 93.2° for the second time to complete the compensation bending;

[0085] S4. Compensation data is stored in the control system through the communication module for subsequent bending of the same batch of materials. The compensation parameters (C = 0.7°, △θ = 3.2°) are uploaded to the multi-dimensional material database through the communication module and the material batch number (such as Lot#2024-06-A1) is associated and stored. When subsequent materials from the same batch are bent, the system automatically calls the compensation angle C of that batch and directly applies it to the initial bending instruction, which can reduce the number of secondary compensations.

[0086] Data closed-loop optimization mechanism: Real-time feedback correction: After completing 5 bends, the system calculates the mean and variance of the compensation angle C. If the variance is greater than 0.3°, the dynamic adjustment algorithm is triggered to optimize the C value; Batch data association: The multi-dimensional material database stores material properties (supplier, hardness), compensation parameters and ambient temperature and humidity by batch, establishes a multi-dimensional mapping model, and improves the generalization ability of the compensation strategy; Abnormal warning: If the θ2 deviation is greater than ±0.5° after 3 consecutive compensations, the system prompts "Material property abnormality" and suspends production to avoid batch scrap.

[0087] In this embodiment, real-time angle detection, dynamic compensation calculation, and closed-loop batch data management effectively address the issue of insufficient bending precision caused by material springback, significantly reducing reliance on manual parameter adjustment and improving the efficiency and stability of mass production. Furthermore, the system possesses adaptive learning capabilities, making it scalable to a variety of materials and complex working conditions, demonstrating its high industrial application value.

[0088] In embodiment 5, a pressure sensor is integrated into the linkage mechanism between the freedom arm 8 and the bending machine slider 1 to monitor the dynamic resistance value F during the bending process in real time. d The system is configured to convert the dynamic resistance value F d The compensation algorithm is input synchronously with the angle change Δφ of the freedom arm 8, through the formula: The bending compensation angle is calculated, where α is the weight coefficient of the angle change and β is the weight coefficient of the dynamic resistance. The two are used to dynamically adjust the range of the compensation angle C according to the material properties; the compensation angle C is used to correct the displacement trajectory of the bending machine slider 1 to optimize the bending accuracy.

[0089] In this embodiment, the implementation steps of the dynamic compensation algorithm are:

[0090] Data acquisition and synchronization input:

[0091] During the bending process, the pressure sensor collects the dynamic resistance value F in real time (for example, F=82.5kN), and the angle encoder synchronously records the angle change △φ of the freedom arm 8 (for example, △φ=5.3°).

[0092] The data is transmitted to the control system through the RS485 communication protocol and input into the sensor and compensation algorithm module;

[0093] Dynamic matching of weight coefficients:

[0094] Based on material type a (e.g., 5052 aluminum alloy, 3mm thickness), a multi-dimensional material database is called to obtain initial weight coefficients: α = 0.15 (weight coefficient for angle variation); β = 0.02 (weight coefficient for dynamic resistance). If similar working conditions exist in historical data (e.g., F = 80-85kN, Δφ = 5-6°), α and β are dynamically optimized using a machine learning model (linear regression).

[0095] Compensation angle calculation:

[0096] According to the formula: , generating a compensation angle C = 2.445°, which is used to correct the displacement trajectory of the bending machine slider 1;

[0097] Bending machine slider 1 displacement trajectory optimization and secondary bending:

[0098] The control system converts the compensation angle C into the displacement trajectory increment of the bending machine slider 1 (for example, ΔS=0.5mm) and adds it to the original bending instruction; the bending machine slider 1 moves down to the correction position for the second time to complete high-precision bending, with the measured angle error ≤±0.3°;

[0099] Data closed-loop optimization:

[0100] Weight coefficient self-learning: After every 50 bends, the control system refits α and β based on historical data (F, Δφ, C and Δθ) and updates them to the multi-dimensional material database; fitting formula: α2=α1+γ×(Δφ 实际 −Δφ 预测 ), where γ is the learning rate (default 0.01), Δφ 实际 and △φ 预测 are the actual angle deviation and the predicted angle deviation respectively; α1 represents the fitting of the first angle change, and α2 represents the fitting of the second angle change;

[0101] Abnormal working condition processing: If the deviation is greater than ±0.5° after 5 consecutive compensations, the "system calibration" mode is triggered and the standard test block is automatically bent to reset α and β;

[0102] Environmental compensation: Through the integrated temperature sensor (model: PT100), the β value is dynamically adjusted according to the temperature and humidity of the workshop (temperature and humidity compensation coefficient 0.001% / ℃).

[0103] In this embodiment, by integrating high-precision pressure sensors and angle encoders, combined with a dynamic weight coefficient algorithm, dual feedback compensation of the dynamic resistance value and compensation angle in the bending process is achieved, which significantly improves the bending accuracy under complex working conditions, can adapt to diverse materials and production environments, and provides a highly reliable technical solution for intelligent manufacturing.

[0104] In Example 6, the visual interactive interface of the bending process includes the following modules:

[0105] Target angle input module: provides digital input controls or knob adjustment controls for setting the target angle θ0 of the bending process;

[0106] Real-time angle curve display area: Dynamically displays the comparison curve of the actual bending angle θ1 and the target angle θ0 of the material, and simultaneously marks the calculation result of the compensation angle C;

[0107] Historical compensation data retrieval button: After triggering, the compensation angle C and dynamic resistance value F of the historical bending process are displayed in the form of a table or chart d and the associated data of weight coefficients α and β;

[0108] Abnormal rebound warning function: When the real-time monitored compensation angle C deviation exceeds the preset threshold, an alarm will be issued through at least one of the following methods: interface highlight flashing, pop-up warning and buzzer prompt, and the bending process will be automatically suspended;

[0109] The visual interactive interface communicates with the main control unit in the control system via a data bus to achieve closed-loop control of parameter input, real-time monitoring and process correction.

[0110] In the above embodiment, the data bus is built based on the EtherCAT protocol to achieve high-frequency data synchronization (transmission delay < 2ms) between the main control unit, sensors and interactive interface. The multi-dimensional material database uses a time series database (InfluxDB) to store bending process parameters, historical compensation data and alarm records.

[0111] The functional modules of the visual interactive interface include:

[0112] Module 1, target angle input module:

[0113] Digital input control: supports manual input of target angles (e.g., θ0=85.0°) with accuracy to one decimal place. Knob adjustment control: A physical knob (model: APEM MHPS series) is integrated into the control panel, with a rotation step of 0.1°, supporting quick fine-tuning. Data verification: If the input target angle exceeds the safety range of upper mold 5 and lower mold 6 (e.g., <30° or >150°), the interface automatically prompts "Angle out of limit" and prohibits execution.

[0114] Module 2, real-time angle curve display area:

[0115] Dynamic Curve: Developed based on the Qt framework, the horizontal axis is time (seconds) and the vertical axis is angle (°). The following curves are displayed simultaneously: target angle θ0 (red dashed line); actual bending angle θ1 of the material (blue solid line, sampling frequency 100Hz); compensation angle C (green bar graph, with calculated values ​​such as C=2.3°); Data Annotation: Hovering the mouse displays the angle change of the 8-degree-of-freedom arm at the current time point (such as Δφ=+0.5°) and compensation parameters (α=0.12, β=0.018);

[0116] Module 3, historical compensation data retrieval function:

[0117] Table 2: Data display table, as follows:

[0118] Arranged in reverse chronological order, the fields include compensation angle C, dynamic resistance value F d (unit: kN), weight coefficients α, β, and angular variation Δφ of the degree of freedom arm 8 (see the data display table in Table 2 below for examples):

[0119] Timestamp C（°） <![CDATA[F d (kN)]]> α β Δφ 2024-06-01 14:30 2.3 78.4 0.12 0.018 +0.2°

[0120] Chart mode: support line chart (display C and F d Time series correlation) and scatter plot (analysis of the distribution patterns of α, β and Δφ)

[0121] Data screening: can be filtered by material type, thickness range, time period, and support export of CSV format reports;

[0122] Module 4: Abnormal rebound warning function

[0123] Trigger conditions:

[0124] The compensation angle C deviation exceeds the threshold (default ±1.0°, customizable);

[0125] Δφ>±0.5° for three consecutive times;

[0126] Alarm method:

[0127] The interface highlights and flashes: the background of the curve area turns yellow, and the red border of the C value display box flashes (frequency 2Hz);

[0128] Pop-up warning: Displays "Abnormal rebound, code E102" and lists possible causes (such as wear of upper mold 5 and lower mold 6, abnormal material hardness);

[0129] Buzzer prompt: The built-in buzzer (model: TDK PS1240P02BT) emits a continuous buzzer sound (85dB, can be turned off manually);

[0130] Automatic shutdown: After the alarm is triggered, the bending machine will immediately pause and enter a safety lock state, and will need manual confirmation before recovery;

[0131] Closed-loop control process:

[0132] Parameter input and initialization: The operator sets the target angle θ0 = 85° and selects the material type a (e.g., SUS304, thickness 2mm) through the touch screen. The system automatically loads the preset α and β values ​​(α = 0.15, β = 0.02).

[0133] First bending and data collection: The bending machine slider 1 performs bending, the pressure sensor collects F = 75.6 kN, the angle sensor records θ1 = 87.5°, and the compensation angle C = 0.15 × Δφ + 0.02 × 75.6 = 2.01° is calculated. In this embodiment, Δφ > ± 0.5°, Δφ = 3.32°.

[0134] Real-time monitoring and correction:

[0135] The interface dynamically updates the curve to show the trend of θ1 converging toward the target angle;

[0136] If the measured θ2=85.3° (Δφ=+0.3°), the system determines it as qualified and stores the data;

[0137] If the measured θ2=84.1° (Δφ=-0.9°), an alarm is triggered and the prompt "Insufficient compensation, it is recommended to increase the β value" is displayed;

[0138] Historical data optimization: After each batch of materials is bent, the system automatically analyzes the historical data, recommends optimized values ​​for α and β (such as α=0.16, β=0.022), and updates them to the multi-dimensional material database.

[0139] In this embodiment, by integrating a visual interactive interface and a closed-loop control algorithm, transparent management and real-time optimization of bending process parameters are achieved, which significantly improves operational convenience and processing accuracy.

[0140] In embodiment 7, a high-precision simulation module is integrated into the control system, and the high-precision simulation module is configured to perform the following steps:

[0141] (a) Receive the material characteristic parameters of material type a input by the user: including elastic modulus E, thickness range t, yield strength And preset rebound coefficient K;

[0142] (b) Based on the above parameters, a bending springback dynamic model is established through finite element analysis, and the theoretical springback angle deviation ΔR is calculated using the following formula: , where θ0 is the preset bending target angle;

[0143] (c) comparing the theoretical springback angle deviation ΔR with actual springback data in a multi-dimensional material database, and generating a compensation scheme through an iterative optimization algorithm, the compensation scheme comprising:

[0144] (1) Compensation angle calculation formula: , where α, β, and γ are dynamic weight coefficients, Δφ is the angle change of the freedom arm 8, and F d It is the dynamic resistance value monitored in real time;

[0145] (2) Bending machine slider 1 displacement trajectory correction parameters , where λ1 is the displacement correction factor; S 初始 Indicates the initial state value or base value, S 修正 Indicates the corrected state value;

[0146] (3) The simulation curve, compensation angle calculation results and corrected displacement trajectory are displayed in real time through a visual interface, and the compensation scheme is automatically synchronized to the motion control unit of the bending machine to achieve closed-loop compensation control in the subsequent bending process; the high-precision simulation module supports user-defined material parameter libraries and adjusts the optimization range of weight coefficients α, β, γ and displacement correction factor λ1 through an interactive interface.

[0147] In this embodiment, the software architecture of the high-precision simulation module includes a finite element analysis engine: customized and developed based on the ANSYS APDL kernel, supporting material nonlinearity and contact analysis; a user interface: a desktop application developed in C#, providing material parameter input, simulation result visualization, and weight coefficient adjustment functions. In this embodiment, the steps for generating a bending springback dynamic model and compensation solution include:

[0148] Step S1: Material parameter input and model initialization:

[0149] The user enters the material characteristic parameters of material type a through the interface: including elastic modulus E=210MPa (example: SUS304 stainless steel), thickness t=2.5mm, yield strength 520MPa; preset rebound coefficient K=1.2 (empirical value);

[0150] The target angle θ0 = 100°, and the high-precision simulation module calls the finite element analysis engine to generate the theoretical rebound angle deviation ΔR: ;

[0151] Step S2: Historical data comparison and compensation calculation

[0152] Query the system's historical database to match similar working conditions (e.g., actual compensation angle C = 5.2° when ΔR = 5.0°). Combined with real-time data: angle change of freedom arm 8 Δφ = 6.8°; bending resistance F = 92.3kN.

[0153] Dynamic weight coefficient adjustment:

[0154] α=0.18 (angle weight)

[0155] β=0.015 (resistance weight)

[0156] γ=0.25 (simulation bias weight)

[0157] Compensation angle calculation: ;

[0158] Step S3: Correction of displacement trajectory of bending machine slider 1

[0159] Initial displacement S 初始=15.0mm, displacement correction factor λ1=0.05, displacement after correction: ;

[0160] The correction parameters are synchronized to the motion control unit (such as ACS motion controller), and the bending machine slider 1 is driven to perform bending according to the correction parameters;

[0161] Visual interaction and closed-loop optimization:

[0162] The simulation curve shows:

[0163] The interface dynamically displays the springback curve (red), real-time bending angle (blue), and compensation angle superposition effect (green) predicted by the finite element analysis engine. It supports mouse interaction and clicks on the curve node to view the detailed stress distribution cloud map.

[0164] Parameter adjustment and optimization:

[0165] The user can manually adjust the weight coefficient range (e.g., limit α∈[0.1,0.3]), and the system automatically verifies the rationality of the parameters; after every 10 bends, the combination of α, β, and γ is optimized through the genetic algorithm;

[0166] Abnormal handling: If the deviation between the simulation predicted ΔR and the actual value is greater than 20%, the "FEM engine mismatch" warning will be triggered, prompting you to recalibrate the material parameters;

[0167] Table 3: Implementation effect verification table, as follows:

[0168] index Traditional methods This program Angular error (°) ±2.5 ±0.4 Rebound response compensation time (ms) 200 50

[0169] Improved efficiency: The pre-calculation time of the high-precision simulation module is less than 5 seconds, which reduces the machine adjustment time by 90% compared with the traditional trial-and-error method;

[0170] In the high-strength steel bending process for a certain automobile B-pillar, the batch production qualification rate increased from 75% to 98%;

[0171] In this implementation, the dynamic prediction and precise control of bending springback are achieved by integrating a high-precision simulation module with a multi-source data fusion compensation algorithm. The control system supports user-defined material libraries and weighting parameters. Combined with a visual interactive interface and self-optimization mechanism, it significantly reduces the development cycle and scrap rate of complex material bending processes, providing an intelligent solution for high-end manufacturing.

[0172] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A bending machine system based on real-time springback compensation, characterized in that: The invention comprises a bending machine slider (1), a workbench (2), a linear guide rail (3), a sensor and a compensation calculation module, and an electric control cabinet (4); an upper mold (5) is provided at the bottom of the bending machine slider (1), a lower mold (6) matching the upper mold (5) is provided above the workbench (2), and a material to be bent is placed on the lower mold (6); the linear guide rails (3) are symmetrically provided on both sides of the workbench (2), an angle detector (7) is symmetrically provided on the linear guide rails (3), and a high-precision sensor is built into the angle detector (7). An angle sensor is used to collect material bending angle data in real time and upload it to the control system of the electric control cabinet (4) through a communication module; a sensor and a compensation calculation module are built into the electric control cabinet (4), and a free-degree rotating arm (8) is provided on the electric control cabinet (4); the sensor and the compensation calculation module control the superimposed compensation angle during the secondary bending of the bending machine slider (1) according to the target angle formula: target angle θ0=180°-A-(B+C), wherein B+C is the material rebound angle Δθ, and A is the base angle of the lower mold (6); The sensor and compensation calculation module have built-in iterative compensation algorithms, and the specific steps include: S1. After the material is bent for the first time, the actual bending angle θ1 of the material is obtained through the angle detector; S2. Calculate the material rebound angle Δθ = θ1 - target angle θ0, where θ0 is the user-set value; S3. Generate compensation value according to the formula compensation angle C=K×Δθ, where K is the material rebound coefficient, and its value range is 0.8≤K≤1.

2. It is generated by fitting the mapping relationship between Δθ and material type and thickness in historical bending data; S4, superimpose the compensation angle C on the secondary bending instruction to make the secondary bending angle θ1+C, and update the K value in real time to achieve dynamic optimization; A pressure sensor is integrated into the linkage mechanism between the freedom arm (8) and the bending machine slider (1) for real-time monitoring of the dynamic resistance value Fd during the bending process; the control system is configured to synchronously input the dynamic resistance value Fd and the angle change Δφ of the freedom arm (8) into the compensation algorithm, through the formula: The compensation angle is calculated, wherein α is a weight coefficient of the angle variation, and β is a weight coefficient of the dynamic resistance value Fd, and the two are used to dynamically adjust the range of the compensation angle C according to the material characteristics; the compensation angle C is used to correct the displacement trajectory of the bending machine slider (1) to optimize the bending accuracy.

2. A bending machine system based on real-time springback compensation according to claim 1, characterized in that: The control system has a built-in multi-dimensional material database, the storage fields of which at least include material type a, thickness range, material rebound coefficient K, historical data of compensation angle C, and corresponding material rebound angle Δθ. When the user inputs a target angle θ0, the system matches the compensation strategy through the following steps: according to the material type a and thickness range, the rebound coefficient is set to Ka and the historical compensation angle is set to Ca, and the associated rebound coefficient Ka and historical compensation angle Ca are extracted from the multi-dimensional material database; Combined with the real-time bending pressure F, the compensation angle C' is corrected by the formula: C' = Ca × Ka × (1 + λF), where λ is the pressure influencing factor with a value range of 0.01 to 0.05, which is used to dynamically adjust the compensation value. The corrected C' is embedded in the secondary bending instruction, and the current compensation result and the material rebound angle Δθ are transmitted back to the multi-dimensional material database. The mapping relationship between the rebound coefficient Ka and the historical compensation angle Ca is updated to achieve data closed-loop optimization.

3. A bending machine system based on real-time springback compensation according to claim 1, characterized in that: The visual interactive interface of the bending process includes the following modules: Target angle input module: provides digital input controls or knob adjustment controls for setting the target angle of the bending process; Real-time angle curve display area: Dynamically displays the comparison curve of the actual bending angle θ1 of the material and the target angle, and simultaneously marks the calculation result of the compensation angle C; Historical compensation data retrieval button: After triggering, the related data of compensation angle C, dynamic resistance value Fd and weight coefficients α and β in the historical bending process are displayed in table or chart form; Abnormal rebound warning function: When the real-time monitored compensation angle C deviation exceeds the preset threshold, an alarm is issued and bending is automatically suspended; The visual interactive interface communicates with the main control unit in the control system via a data bus to achieve closed-loop control of parameter input, real-time monitoring and process correction.

4. A bending machine system based on real-time springback compensation according to claim 1, characterized in that: A high-precision simulation module is integrated into the control system, and the high-precision simulation module is configured to perform the following steps: (a) Receive the material characteristic parameters of material type a input by the user: including elastic modulus E, thickness range t, yield strength And preset rebound coefficient K; (b) Based on elastic modulus E, thickness range t, yield strength And the preset rebound coefficient K, the bending rebound dynamic model is established through finite element analysis, and the theoretical rebound angle deviation ΔR is calculated. The formula is: , where θ0 is the preset bending target angle; (c) comparing the theoretical springback angle deviation ΔR with actual springback data in a multi-dimensional material database, and generating a compensation scheme through an iterative optimization algorithm, the compensation scheme comprising: (1) Compensation angle calculation formula: , where α, β, and γ are dynamic weight coefficients, Δφ is the angle change of the freedom arm (8), and Fd is the dynamic resistance value monitored in real time; (2) Bending machine slider (1) displacement trajectory correction parameters , where λ1 is the displacement correction factor; Sinitial represents the initial state value or base value, and Scorrection represents the corrected state value; (3) The calculation results of the compensation angle and the corrected displacement trajectory of the bending machine slider (1) are displayed in real time through a visual interactive interface, and the compensation scheme is automatically synchronized to the motion control unit of the bending machine to realize closed-loop compensation control in the subsequent bending process; the high-precision simulation module supports user-defined multi-dimensional material parameter library, and adjusts the optimization range of weight coefficients α, β, γ and displacement correction factor λ1 through a visual interactive interface.

5. A method for dynamic calibration of the bending angle of a press brake system based on real-time springback compensation according to any one of claims 1 to 4, characterized in that: The following steps are involved: S1, when the material is bent for the first time, the angle detector collects the actual bending angle θ1 of the material in real time; S2, calculate the actual bending angle after material springback θ2 = θ1-Δθ; S3. If θ2 does not reach the target angle θ0, the compensation angle C=θ0-θ2 is set, and the secondary bending angle is controlled to θ1+C; S4. The compensation data is stored in the control system through the communication module and is used for subsequent bending of the same batch of materials.

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