Intelligent die-cutting machine system and control method

Abstract

The invention relates to the technical field of precision machining equipment, in particular to an intelligent die-cutting machine system and a control method, a bus type motion control framework is adopted, a 201fps double-camera visual system is integrated, and + / -0.02 mm positioning precision is achieved through an innovative automatic calibration algorithm. The control software adopts a full PC architecture, integrates a visual processing module, a motion control module, a process management module and the like, and supports one-key remodeling and intelligent parameter optimization. The pressure adjusting device can automatically adjust punching pressure according to material characteristics, and equipment health prediction is achieved in cooperation with a digital twinning system. Compared with traditional equipment, the production capacity of the system is improved by 89%, the remodeling time is shortened to 5 minutes, the comprehensive energy consumption is reduced by 18%, and the system is particularly suitable for die cutting machining of precise products such as 5G electronic elements and flexible display screens.

Description

[Technical field]

[0001] The present invention relates to the technical field of precision machining equipment, and in particular to an intelligent die-cutting machine system and a control method. [Background technology]

[0002] The die-cutting machine of the prior art has the following technical defects:

[0003] 1. The motion control system adopts pulse control, which has problems such as complex wiring (each axis driver needs to be connected separately), poor anti-interference ability, and insufficient scalability;

[0004] 2. The visual system and motion control system have separate architectures, and the image processing frame rate is low (<60fps), resulting in insufficient dynamic alignment accuracy (±0.1mm);

[0005] 3. The mechanical calibration process is complicated, requires professional calibration tools and takes up to 2-3 hours;

[0006] 4. The switching of production modes depends on manual experience, and the mechanical parameters need to be readjusted when different products are changed;

[0007] 5. Equipment status monitoring and process parameters lack digital management, making it difficult to achieve predictive maintenance. [Summary of the invention]

[0008] In order to overcome the above problems, the present invention proposes an intelligent die-cutting machine system and a control method that can effectively solve the above problems.

[0009] A technical solution provided by the present invention to solve the above technical problems is: to provide an intelligent die-cutting machine system and control method, including an EtherCAT master station controller;

[0010] Distributed motion control slave station, including at least 3 servo drive units;

[0011] Dual-camera vision system, including 201fps industrial camera and adaptive light source control system;

[0012] Full PC architecture control software, integrating visual processing module, motion control module, and process management module;

[0013] The digital pressure regulating device includes a high-precision mold adjusting shaft and a pressure feedback sensor.

[0014] Preferably, the EtherCAT master station controller adopts an RT-3316 motion control card, supports synchronous control of more than or equal to 32 axes, and a communication cycle is less than or equal to 1 ms.

[0015] Preferably, the dual-camera vision system calibration method comprises:

[0016] The driving platform moves along a preset path and collects calibration images;

[0017] Calculate the homography matrix from the camera coordinate system to the mechanical coordinate system;

[0018] The LM algorithm is used to optimize the calibration parameters;

[0019] Store calibration data in non-volatile memory.

[0020] Preferably, the adaptive light source control system comprises:

[0021] Multi-channel digital controller, output PWM dimming signal;

[0022] A light intensity feedback module, including a photoelectric sensor array;

[0023] Light source intensity calculation model: P = K1×R+K2×v, where R is the material reflectivity and v is the conveying speed.

[0024] Preferably, the digital pressure regulating device performs the following steps:

[0025] Step a. Receiving a punching quality detection signal;

[0026] Step b. Calculate the theoretical pressure value F = (E×A×ΔL) / L0+η×v;

[0027] Step c. driving the mold adjustment axis to adjust the height in steps of 0.005 mm;

[0028] Step d. Verify that the deviation between the actual pressure and the theoretical value is ≤ 2%.

[0029] A method for controlling an intelligent die-cutting machine comprises the following steps:

[0030] Step S1: Establish a master-slave communication link through the EtherCAT bus;

[0031] Step S2: Execute the automatic calibration procedure to obtain the vision-motion coordinate system conversion parameters;

[0032] Step S3: setting light source parameters and exposure time according to material characteristics;

[0033] Step S4: Real-time visual detection and calculation of position compensation;

[0034] Step S5: synchronously controlling the movement of the punching axis and the feeding axis;

[0035] Step S6: monitor the pressure parameters and automatically adjust the position of the mold adjustment axis.

[0036] Preferably, the position compensation amount in step S4 is calculated using the following formula:

[0037] ΔX = α × (x_actual - x_target)

[0038] ΔY=β×(y_actual-y_target)

[0039] Δθ=γ×arctan((y2-y1) / (x2-x1))

[0040] Among them, α, β, and γ are dynamic adjustment coefficients, and their value range is 0.8-1.2.

[0041] Preferably, the electronic cam curve in S5 satisfies:

[0042] The speed curve of the punching axis is a trapezoidal wave;

[0043] The feed axis speed curve is a sine wave;

[0044] The phase difference between the two axes is maintained at 90°±5°.

[0045] Compared with the prior art, the intelligent die-cutting machine system and control method of the present invention have the following beneficial effects:

[0046] 1. Improved production accuracy: die-cutting positioning accuracy reaches ±0.02mm (traditional equipment ±0.1mm);

[0047] 2. Efficiency improvement: Maximum production capacity is 8500pcs / h, which is 89% higher than traditional equipment;

[0048] 3. Shortened changeover time: the calibration process is automated, and the changeover time is ≤ 5 minutes;

[0049] 4. Reduced energy consumption: The bus architecture reduces wiring by 75% and reduces overall energy consumption by 18%. [Specific implementation method]

[0050] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0051] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are limited to relative positions rather than absolute positions.

[0052] In addition, in the present invention, descriptions such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0053] The intelligent die-cutting machine system and control method of the present invention relate to the technical field of precision mechanical processing equipment, and specifically to an intelligent die-cutting machine system based on the deep integration of industrial bus architecture and machine vision technology, which is especially suitable for die-cutting processing of precision electronic components such as flexible circuit boards and optical film materials.

[0054] Specifically, the intelligent die-cutting machine system and control method of the present invention are an intelligent die-cutting machine system and control method based on EtherCAT bus and high-precision visual system.

[0055] An intelligent die-cutting machine system of the present invention is characterized by comprising:

[0056] EtherCAT master controller;

[0057] Distributed motion control slave station, including at least 3 servo drive units;

[0058] Dual-camera vision system, including 201fps industrial camera and adaptive light source control system;

[0059] Full PC architecture control software, integrating visual processing module, motion control module, and process management module;

[0060] The digital pressure regulating device includes a high-precision mold adjusting shaft and a pressure feedback sensor.

[0061] The EtherCAT master controller adopts the RT-3316 motion control card, supports synchronous control of 32 axes or more, and the communication cycle is less than or equal to 1ms.

[0062] The dual-camera vision system calibration method comprises:

[0063] The driving platform moves along a preset path and collects calibration images;

[0064] Calculate the homography matrix from the camera coordinate system to the mechanical coordinate system;

[0065] The LM algorithm is used to optimize the calibration parameters;

[0066] Store calibration data in non-volatile memory.

[0067] The adaptive light source control system comprises:

[0068] Multi-channel digital controller, output PWM dimming signal;

[0069] A light intensity feedback module, including a photoelectric sensor array;

[0070] Light source intensity calculation model: P = K1×R+K2×v, where R is the material reflectivity and v is the conveying speed.

[0071] The digital pressure regulating device performs the following steps:

[0072] Step a. Receiving a punching quality detection signal;

[0073] Step b. Calculate the theoretical pressure value F = (E×A×ΔL) / L0+η×v;

[0074] Step c. driving the mold adjustment axis to adjust the height in steps of 0.005 mm;

[0075] Step d. Verify that the deviation between the actual pressure and the theoretical value is ≤ 2%.

[0076] An intelligent die-cutting machine control method of the present invention comprises the following steps:

[0077] Step S1: Establish a master-slave communication link through the EtherCAT bus;

[0078] Step S2: Execute the automatic calibration procedure to obtain the vision-motion coordinate system conversion parameters;

[0079] Step S3: setting light source parameters and exposure time according to material characteristics;

[0080] Step S4: Real-time visual detection and calculation of position compensation;

[0081] Step S5: synchronously controlling the movement of the punching axis and the feeding axis;

[0082] Step S6: monitor the pressure parameters and automatically adjust the position of the mold adjustment axis.

[0083] The position compensation amount in step S4 is calculated using the following formula:

[0084] ΔX = α × (x_actual - x_target)

[0085] ΔY=β×(y_actual-y_target)

[0086] Δθ=γ×arctan((y2-y1) / (x2-x1))

[0087] Among them, α, β, and γ are dynamic adjustment coefficients, and their value range is 0.8-1.2.

[0088] The electronic cam curve in S5 satisfies:

[0089] The speed curve of the punching axis is a trapezoidal wave;

[0090] The feed axis speed curve is a sine wave;

[0091] The phase difference between the two axes is maintained at 90°±5°.

[0092] A non-transitory computer-readable storage medium storing a control program, the program comprising:

[0093] Visual processing module, which realizes image acquisition, feature extraction and coordinate conversion;

[0094] Motion control module, generates EtherCAT communication messages and parses slave data;

[0095] Process management module, storing ≥100 sets of process parameter recipes;

[0096] Equipment health monitoring module predicts the remaining life of key components.

[0097] The device health monitoring module performs:

[0098] Collect servo motor current, temperature and vibration data;

[0099] Calculate the bearing wear index W = ∫(I 2 (t)+T(t))dt;

[0100] When W ≥ threshold, a maintenance warning is generated;

[0101] Automatically adjust motion parameters to reduce load.

[0102] The present invention discloses an intelligent die-cutting machine system and control method based on EtherCAT bus and high-precision visual system. The system adopts a bus-type motion control architecture, integrates a 201fps dual-camera visual system, and achieves ±0.02mm positioning accuracy through an innovative automatic calibration algorithm. The control software adopts a full PC architecture, integrates visual processing, motion control, process management and other modules, and supports one-key mold change and intelligent parameter optimization. The pressure regulating device can automatically adjust the punching pressure according to the material properties, and cooperates with the digital twin system to realize equipment health prediction. Compared with traditional equipment, the system has an 89% increase in production capacity, a shortened mold change time of 5 minutes, and a 18% reduction in comprehensive energy consumption. It is particularly suitable for die-cutting processing of precision products such as 5G electronic components and flexible displays.

[0103] The system consists of five innovative modules:

[0104] 1. EtherCAT bus motion control architecture: adopts master-slave topology and integrates 32-axis synchronous control capability;

[0105] 2. Dual-camera self-calibration vision system: equipped with 201fps high-speed industrial camera and adaptive optical components;

[0106] 3. Intelligent punching pressure adjustment module: including digital die adjustment axis and pressure feedback system;

[0107] 4. Full PC architecture control software: integrating three core functions: visual processing, motion control, and process management;

[0108] 5. Production data middle platform: realize digital twin mapping of equipment status monitoring and process parameters.

[0109] Features of bus motion control architecture:

[0110] Using RT-3316EtherCAT master card, the slave devices supporting cycle synchronization accuracy of ≤1μs include:

[0111] High-precision linear motor (positioning accuracy ±0.5μm);

[0112] Digital servo drive (supporting CiA402 protocol);

[0113] Intelligent IO module (128-point distributed IO).

[0114] The present invention adopts an adaptive light source control system:

[0115] Light source intensity P = K1 × material reflectivity + K2 × movement speed;

[0116] Exposure time T = 1 / (2×v), v is the material conveying speed.

[0117] Intelligent punching control algorithm

[0118] Pressure Regulation Model:

[0119] F=(E×A×ΔL) / L0+η×v

[0120] in:

[0121] F: Punching pressure

[0122] E: Material elastic modulus

[0123] ΔL: displacement of the mold adjustment axis

[0124] η: Viscous damping coefficient.

[0125] The software architecture of the present invention adopts a microservice architecture, including:

[0126] Visual processing services (SYMV image processing optimization module);

[0127] Motion control service (EtherCAT master driver);

[0128] Process management services (SQLite database);

[0129] Support multi-task parallel processing and real-time priority allocation:

[0130] Task Priority:

[0131] 1. Security monitoring (RTOS level);

[0132] 2. Motion control (1ms cycle);

[0133] 3. Visual processing (10ms cycle).

[0134] The high-speed precision die-cutting operation process of an intelligent die-cutting machine system of the present invention includes: A. System power-on initialization and execution of automatic calibration program:

[0135] The platform moves to the origin;

[0136] Move along the path of X+→X-Y+→Y-R+→2R-;

[0137] Collect images of calibration plates at each position;

[0138] Calculate the transformation matrix between the camera coordinate system and the mechanical coordinate system;

[0139] B. Production parameter settings;

[0140] C. Start continuous production:

[0141] The visual system detects the position of the Mark point in real time;

[0142] The motion controller calculates the position compensation ΔX, ΔY, Δθ;

[0143] The UVW platform completes position correction within 200ms;

[0144] The punching axis and the feeding axis move synchronously according to the electronic cam curve.

[0145] An intelligent pressure regulation process of an intelligent die-cutting machine system of the present invention includes:

[0146] When the punching residual rate is detected to be > 0.5%:

[0147] A. The pressure regulation algorithm calculates the required ΔL value;

[0148] B. The mold adjustment axis can adjust the height in 0.005mm / step;

[0149] C. Pressure sensor verifies the actual pressure value;

[0150] D. Automatically generate and store the pressure-mass relationship curve.

[0151] Compared with the prior art, the intelligent die-cutting machine system and control method of the present invention have the following beneficial effects:

[0152] 1. Improved production accuracy: die-cutting positioning accuracy reaches ±0.02mm (traditional equipment ±0.1mm);

[0153] 2. Efficiency improvement: Maximum production capacity is 8500pcs / h, which is 89% higher than traditional equipment;

[0154] 3. Shortened changeover time: the calibration process is automated, and the changeover time is ≤ 5 minutes;

[0155] 4. Reduced energy consumption: The bus architecture reduces wiring by 75% and reduces overall energy consumption by 18%.

[0156] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any modifications, equivalent substitutions and improvements made within the concept of the present invention should be included in the patent protection scope of the present invention.

Claims

1. An intelligent die-cutting machine system, characterized in that: include: EtherCAT master controller; Distributed motion control slave station, including at least 3 servo drive units; Dual-camera vision system, including 201fps industrial camera and adaptive light source control system; Full PC architecture control software, integrating visual processing module, motion control module, and process management module; The digital pressure regulating device includes a high-precision mold adjusting shaft and a pressure feedback sensor.

2. The intelligent die-cutting machine system according to claim 1, characterized in that: The EtherCAT master controller adopts the RT-3316 motion control card, supports synchronous control of 32 axes or more, and the communication cycle is less than or equal to 1ms.

3. The intelligent die-cutting machine system according to claim 1, characterized in that: The dual-camera vision system calibration method comprises: The driving platform moves along a preset path and collects calibration images; Calculate the homography matrix from the camera coordinate system to the mechanical coordinate system; The LM algorithm is used to optimize the calibration parameters; Store calibration data in non-volatile memory.

4. The intelligent die-cutting machine system according to claim 1, characterized in that: The adaptive light source control system comprises: Multi-channel digital controller, output PWM dimming signal; A light intensity feedback module, including a photoelectric sensor array; Light source intensity calculation model: P = K1×R+K2×v, where R is the material reflectivity and v is the conveying speed.

5. The intelligent die-cutting machine system according to claim 1, characterized in that: The digital pressure regulating device performs the following steps: Step a. Receiving a punching quality detection signal; Step b. Calculate the theoretical pressure value F = (E×A×ΔL) / L0+η×v; Step c. driving the mold adjustment axis to adjust the height in steps of 0.005 mm; Step d. Verify that the deviation between the actual pressure and the theoretical value is ≤ 2%.

6. A method for controlling an intelligent die-cutting machine, characterized in that: The steps include: Step S1: Establish a master-slave communication link through the EtherCAT bus; Step S2: Execute the automatic calibration procedure to obtain the vision-motion coordinate system conversion parameters; Step S3: setting light source parameters and exposure time according to material characteristics; Step S4: Real-time visual detection and calculation of position compensation; Step S5: synchronously controlling the movement of the punching axis and the feeding axis; Step S6: monitor the pressure parameters and automatically adjust the position of the mold adjustment axis.

7. The intelligent die-cutting machine control method according to claim 6, characterized in that: The position compensation amount in step S4 is calculated using the following formula: ΔX = α × (x_actual - x_target) ΔY=β×(y_actual-y_target) Δθ=γ×arctan((y2-y1) / (x2-x1)) Among them, α, β, and γ are dynamic adjustment coefficients, and their value range is 0.8-1.

2.

8. The intelligent die-cutting machine control method according to claim 6, characterized in that: The electronic cam curve in S5 satisfies: The speed curve of the punching axis is a trapezoidal wave; The feed axis speed curve is a sine wave; The phase difference between the two axes is maintained at 90°±5°.