Application method of cutting machine blade stress control system based on mechanical model optimization

Abstract

This invention discloses an application method for a paper cutter blade force control system based on a mechanical model optimization, comprising the following steps: S1, the system establishes a mechanical model, which, after processing, can be fed back to the PLC control system in real time; S2, the system can adjust the cutting pressure of the blade in real time to adapt to different paper thicknesses, densities, and materials; S3, combining experimental data, a blade life prediction model based on fatigue theory and a finite element analysis model is used to predict the blade's service life, and the cutting process is automatically adjusted according to the actual stress conditions to maximize the blade's service life; S4, a two-factor experimental design method is used, taking different paper types as experimental variables and cross-analyzing them with multiple factors such as blade cutting pressure, paper feed speed, and cutting accuracy. According to this invention, it is ensured that the paper cutter can always accurately control the cutting force and blade pressure under different paper types and operating conditions, improving cutting accuracy and extending the blade's service life.

Description

Technical Field

[0001] This invention relates to the technical field of paper cutters, and in particular to the application method of a force control system for paper cutter blades based on mechanical model optimization. Background Technology

[0002] Traditional paper cutters experience significant variations in cutting force on their blades during operation, especially when processing different types and thicknesses of paper. This can lead to premature blade wear or reduced cutting accuracy. While some blade stress analysis methods and mechanical models exist, most remain at the theoretical research stage, lacking effective practical applications and hindering real-time monitoring and optimization of blade stress. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the purpose of this invention is to provide an application method for a paper cutter blade force control system based on a mechanical model optimization. Through precise calculation and dynamic adjustment of the blade force, this invention can monitor the blade force state in real time, optimize cutting parameters, thereby improving cutting accuracy, extending blade life, and effectively reducing equipment maintenance costs. To achieve the above-mentioned objectives and other advantages of this invention, an application method for a paper cutter blade force control system based on a mechanical model optimization is provided, comprising: S1. The system establishes a mechanical model to calculate the cutting force and pressure on the blade's rear face when cutting different types of paper (such as newsprint, offset paper, and offset printing paper). After processing, the data can be fed back to the PLC control system in real time. S2. Based on the cutting force data calculated in S1, the system can adjust the cutting pressure of the blade in real time to adapt to different paper thicknesses, densities, and materials. By controlling the servo motor to adjust the blade pressure, the system can precisely control the force during the cutting process, avoiding excessive pressure that could cause blade wear or paper damage. S3. Based on experimental data, the blade life prediction model and finite element analysis model based on fatigue theory are used to predict the blade life and automatically adjust the cutting process according to the actual stress conditions to maximize the blade life. S4. This invention also designs a two-factor experimental design method, using different paper types (such as newsprint, offset paper, and offset printing paper) as experimental variables, and conducting cross-analysis with multiple factors such as blade cutting pressure, paper feed speed, and cutting accuracy. Based on the experimental data, a multi-factor optimization model is established to provide optimal process parameters for paper cutter operation under different conditions in actual production; Preferably, in step S1, the mechanical model in the control system of the paper cutter can be integrated with the PLC control system to calculate the required cutting force in real time based on the characteristics of the paper, such as thickness, density, material, and current cutting conditions, such as blade angle and paper feed speed, and adjust the blade pressure and cutting angle.

[0004] Preferably, in step S2, the data is transmitted to the central processing unit to calculate the blade stress state. The calculation result will serve as the basis for adjusting the cutting process parameters. The servo driver is located in the middle of the motion control system, receiving instructions from the host computer controller, namely position, speed, or torque, and outputting voltage and current signals to the servo motor to realize the host computer's motion commands. During the operation of the paper cutter, the cutting angle, cutting pressure, and paper feed speed are dynamically adjusted. Before each adjustment, the system calculates the optimal range of cutting process parameters to ensure that the blade stress is within a predetermined threshold.

[0005] Preferably, in step S3, the life prediction system combines historical data and uses a "fatigue index" model to assess the remaining service life of the cutting tool. By combining the Ansys finite element analysis model with experimental data, the system predicts the tool's service life and automatically adjusts the cutting process based on actual stress conditions to maximize the tool's service life. When the predicted service life falls below a predetermined threshold, the system will issue a maintenance reminder to the operator to ensure timely tool replacement.

[0006] Preferably, in step S4, a multi-factor experimental design method is designed, using different paper types as experimental variables, such as newsprint, offset paper, and offset printing paper, to analyze the effects of these variables on cutting angle, cutting pressure, and paper feed speed. Through a multi-factor optimization model, optimal paper cutting process parameters are provided for different paper types in actual production.

[0007] Compared with the prior art, the advantages and positive effects of the present invention are: (1) Improve the cutting accuracy and stability of the paper cutter: By real-time force monitoring and dynamic adjustment, the blade is subjected to the optimal force during each cutting process, thereby improving the cutting accuracy.

[0008] (2) Extend blade life: By predicting and optimizing life, excessive blade wear can be reduced, blade life can be extended, and replacement frequency can be reduced.

[0009] (3) Improve production efficiency: The dynamic adjustment system automatically optimizes the cutting process according to different paper materials and thicknesses, thereby improving production efficiency.

[0010] (4) Reduced maintenance costs: The system’s life prediction and optimization functions reduce the frequency of blade replacement and lower the maintenance costs of the equipment. Attached Figure Description

[0011] Figure 1 The flowchart is shown below for the force monitoring system of the paper cutter blade force control system based on mechanical model optimization according to the present invention. Figure 2 This is a PLC wiring diagram of the control system for the application method of the paper cutter blade force control system based on mechanical model optimization according to the present invention. Figure 3 This is a schematic diagram of the blade mechanical analysis model for the application method of the paper cutter blade force control system based on mechanical model optimization according to the present invention. Figure 4 A schematic diagram illustrating the position control of a servo motor in the application method of the paper cutter blade force control system based on mechanical model optimization according to the present invention. Figure 5 This is a three-dimensional finite element analysis model of the blade in the application method of the paper cutter blade force control system based on mechanical model optimization according to the present invention. Detailed implementation The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] Reference Figure 1 The application method of the force control system for paper cutter blades based on mechanical model optimization includes: S1. The system establishes a mechanical model to calculate the cutting force of the blade and the pressure on the blade's rear face when cutting different types of paper. After processing, the data can be fed back to the PLC control system in real time; types of paper include newsprint, offset paper, and offset printing paper.

[0013] S2. Based on the aforementioned force monitoring data, the system can adjust the cutting angle and cutting pressure of the blade in real time to adapt to different paper thicknesses and materials. Through automated control, the system improves paper cutting accuracy while avoiding excessive blade wear. S3. Combining experimental data and finite element analysis models, predict the service life of the blade and automatically adjust the cutting process according to the actual stress conditions to maximize the service life of the blade. S4. This invention also designs a multi-factor experimental design method, using different paper types as experimental variables and cross-analyzing them with multiple factors such as cutting angle, cutting pressure, and paper feed speed. Based on the experimental data, a multi-factor optimization model is established to provide optimal process parameters for paper cutter operation under different conditions in actual production. Step S1: First, Pro / Engineer was used to simulate and analyze the blade drop pattern of the paper cutter to find the change in the angle β between the blade and the paper. By measuring the angle between the blade edge and the worktable at different positions, the angle pressure between the blade and the worktable at the maximum cutting resistance was selected. Then, the cutting force was calculated. In the formula: It is the maximum area of ​​the paper cross-section swept by the blade during oblique cutting. This refers to burst strength. The required cutting force for each cut is calculated using a mechanical model. A high-performance computer or embedded system with sufficient processing power (e.g., a quad-core processor and 8GB of memory) is configured to process sensor data, perform mechanical analysis, and predict lifespan. The paper cutter's PLC system is linked to the control system of this invention, responsible for executing adjustment commands calculated by the central processing unit, enabling real-time adjustment of parameters such as cutting angle, blade pressure, and paper feed speed. The display and feedback module displays real-time monitoring data, analysis results, and alarm information, facilitating real-time monitoring and adjustment by the operator.

[0014] Step S2 involves measuring the force exerted on the blade during each cutting process. Once the control system processes the monitored real-time data, it generates corresponding control signals. These signals include adjustments to the blade cutting pressure. These control signals are transmitted to the servo motor control system. The servo motor adjusts the pressure between the blade and the paper to maintain the cutting pressure within an optimal range. If the paper is thick or stiff, the system may require increased cutting pressure, and vice versa. The servo motor achieves this by adjusting the force on the blade-paper contact surface. Different threshold values ​​are set by the system's built-in mechanical model based on different paper types, thicknesses, and cutting speeds. Cutting force range: 50N to 500N. Cutting pressure range: 100N / mm. 2 Up to 1000 N / mm 2 When the cutting force exceeds this range, the system will automatically adjust the blade pressure or paper feed speed to avoid blade damage or decreased cutting accuracy. When the paper cutter detects that it is processing thicker paper, the control system will increase the cutting pressure from 100 N / mm². 2 Increased to 150 N / mm 2 Simultaneously, the paper feed speed is reduced to keep the blade force within the optimized range. Cutting angle: The optimized angle range is 30° to 60° to ensure the best cutting effect and blade life. Cutting pressure: Real-time adjustment range is 100N / mm. 2 Up to 1200 N / mm 2 The feed rate depends on the paper thickness and type. The feed speed is dynamically adjusted based on the cutting pressure and paper type, typically between 20 m / min and 50 m / min.

[0015] Step S3 employs a blade life prediction model based on fatigue theory. By cumulatively analyzing the stress data from each cut, the remaining service life of the blade is predicted. The specific steps are as follows: The system calculates the fatigue index based on the stress data from each cut, such as cutting force and cutting pressure. The fatigue index is modeled based on common material fatigue theories, and the cumulative damage to the blade is calculated based on factors such as cutting force and the number of cuts. When the accumulated fatigue index reaches a set threshold (e.g., 500 N·h), the system predicts the remaining life of the blade. Combining this with the Ansys finite element analysis model, a 3D model of the blade is established, meshed, and a load is applied to the blade model according to the stress conditions during cutting. The deformation of the blade is then calculated and verified against experimental data to predict the blade's service life. During the blade's service life, if the system detects excessive blade wear, such as when the cutting force exceeds a preset threshold, it will automatically adjust the cutting parameters to reduce excessive blade wear and extend the blade's service life. Cutting parameters include reducing the cutting speed and adjusting the pressure.

[0016] Step S4: When designing the experimental scheme, the possible interactions between cutting angle, cutting pressure, and paper feed speed were considered, and a three-way ANOVA method was used for the experimental design. Three-way ANOVA is a statistical method used to analyze the effects of three independent factors on a response variable and their interactions. This method can assess the main effects and second-order interactions, and even third-order interactions, of the three factors on the response variable. We have three factors: Factor A (cutting angle), Factor B (cutting pressure), and Factor C (paper feed speed), each with multiple levels. The overall experimental design is a 3 × 4 × 2 experiment, where each combination of levels for each factor is tested a certain number of times. By comparing the calculated F-value with the critical value, if the F-value of a factor or interaction is significantly greater than the critical value, it indicates that the factor or interaction has a significant effect on the response variable. If the F-value is not significant, it indicates that the effect of the factor or interaction on the response variable is negligible. By combining experimental data with a mechanical model, the system can automatically adjust the cutting process parameters under various paper types to ensure the efficiency and quality of each cut. Factors affecting the testing of a paper cutter include cutting angle, cutting pressure, and paper feed speed. For different types of paper, the cutting pressure and angle of the blade should be dynamically adjusted according to the actual characteristics of the paper. For 0.3mm thick offset paper, the optimized cutting pressure is 500 N / mm². 2 The cutting angle is 45°.

[0017] In summary, the innovative blade stress monitoring and dynamic adjustment control system solves the problems of easy blade wear and poor cutting accuracy in existing paper cutters, improving the performance, blade life, and production efficiency of the cutter. The widespread application of this system will significantly promote technological progress in the paper cutter field and provide a feasible solution for enterprises to reduce production costs. A multi-factor optimization model is established based on experimental data to provide optimal process parameters for paper cutter operation under different conditions in actual production. This method uses mechanical models and mathematical algorithms to calculate and optimize the blade stress in real time, ensuring that the paper cutter can always accurately control the cutting force and blade pressure under different paper types and operating conditions, improving cutting accuracy and extending blade life.

[0018] The number of devices and processing scale described herein are for simplification purposes. Applications, modifications, and variations of this invention will be readily apparent to those skilled in the art. Although embodiments of the invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be applied to various fields suitable for this invention, and further modifications can be readily implemented by those skilled in the art. Therefore, without departing from the general concept defined by the claims and their equivalents, this invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. An application method for a force control system for a paper cutter blade based on mechanical model optimization, characterized in that, Includes the following steps: S1. Real-time force modeling and feedback: Establish a mechanical model of the bevel cutting edge of the paper cutter blade to calculate the theoretical cutting force of the blade when cutting different types of paper in real time. The pressure distribution on the back face of the cutting blade is calculated and the calculated force data is fed back to the PLC control system in real time. S2. Dynamic process parameter compensation: The PLC control system adjusts the cutting parameters of the blade in real time by driving the servo motor according to the theoretical cutting force data, so as to adaptively match the thickness, density and material of different papers; the cutting parameters include cutting pressure, cutting angle and paper feed speed; S3. Life Prediction and Adaptive Process Adjustment: Combining experimental data, the system uses a fatigue-based blade life prediction model and a finite element analysis model to predict the remaining life of the blade by calculating the fatigue index under a single cutting load. When the predicted life is lower than a preset threshold, the system automatically adjusts the cutting process parameters and issues a maintenance alarm to maximize the blade life. S4. Multi-factor process optimization: Using two-factor or three-factor experimental design methods, paper type is used as an experimental variable and cross-analyzed with cutting pressure, paper feed speed and cutting accuracy to construct a multi-factor optimization graph model, providing preset optimal initial process values ​​for different paper types.

2. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: In step S1, the cutting force The calculation formula is: In the formula: This refers to the maximum cross-sectional area of ​​the paper swept by the blade during bevel cutting. The paper's burst strength is measured by the PLC control system, which calculates the real-time angle between the blade edge and the worktable based on the paper's real-time position feedback. The angle parameter is then incorporated into the mechanical model for force correction.

3. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: In step S2, the specific logic of the system performing dynamic adjustment is as follows: when the PLC control system detects that the paper thickness or material density increases, resulting in an increase in real-time cutting force, the system increases the output torque through the servo driver to increase the cutting pressure. The adjustment range is from 100MPa to 150MPa, and at the same time, the paper feeding frequency of the servo motor is reduced to reduce the paper feeding speed, so that the force on the blade is maintained within the safe threshold set by the mechanical model.

4. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 3, characterized in that, The adjustment ranges for each process parameter are set as follows: Cutting angle: to ; Cutting pressure: 100MPa to 1200MPa; Paper feed speed: 20m / min to 50m / min.

5. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: The fatigue index calculation method in step S3 is as follows: extract the maximum cutting force and cutting pressure cyclic load in a single cutting process, and perform linear superposition according to the material fatigue cumulative damage theory; when the cumulative fatigue index reaches the set threshold of 500 Nh, apply load to the three-dimensional mesh model of the blade edge in combination with the finite element analysis model and solve for the deformation, and cross-check with the accuracy data collected by the experiment to determine the final scrap time of the blade.

6. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: In step S4, a multi-factor optimization model is constructed using a three-factor experimental design method. The three factors include cutting angle A, cutting pressure B, and paper feed speed C. The main effects of each factor and their interactions on cutting accuracy are evaluated using a three-factor analysis of variance. Based on the results of the analysis of variance, the system automatically matches a preset combination of cutting process parameters for various paper types.

7. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 6, characterized in that: For paper with different properties, the system executes the following dynamic parameter matching logic: For double-sided offset paper with a thickness of 0.3 mm, the initial optimized cutting pressure is set to 500 MPa and the cutting angle is 45°. When the paper material is switched to newsprint or offset printing paper, the system re-invokes the corresponding combination of cutting pressure and paper feed speed based on the multi-factor optimization model to ensure that the blade force fluctuation during the cutting process is within the steady-state range set by the mechanical model.

8. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: The control system also includes real-time monitoring and feedback correction steps: The actual angle between the blade edge and the worktable at different positions during the cutting stroke is measured in real time using a displacement sensor. ; The actual included angle Feedback is sent to the PLC control system to correct the swept cross-sectional area parameters in the mechanical model in real time. This allows for dynamic updates to the calculated theoretical cutting force. .

9. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 1, characterized in that: The system adopts a distributed processing architecture: Embedded systems or high-performance computers are responsible for running mechanical analysis models, finite element analysis models, and life prediction algorithms; The PLC control system is responsible for receiving adjustment instructions from the embedded system and sending position, speed, or torque control signals to the servo driver to drive the servo motor to perform adjustment actions on blade pressure and paper feed speed.

10. The application method of the paper cutter blade force control system based on mechanical model optimization according to claim 9, characterized in that: The servo driver achieves precise driving of the servo motor through a three-loop control logic consisting of a position loop, a speed loop, and a current loop. The system achieves closed-loop synchronous control of the paper feeding speed and the blade falling frequency by reading the feedback signal from the paper feed roller encoder, ensuring that the cutting position accuracy remains within the preset deviation range when the cutting pressure is dynamically adjusted.

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