A Digital Twin Method and System for Servo Presses Based on Force-Energy-Displacement Conversion

Abstract

This invention belongs to the technical field of real-time monitoring of servo presses. It discloses a digital twin method and system for servo presses based on force-energy-displacement conversion. The method includes the following steps: (1) acquiring press data and setting impact energy of the servo press, and setting a motion control model; (2) calculating the flywheel angular velocity and slide speed of the servo press based on the press data and the motion control model; (3) acquiring forging data and setting a force-energy characteristic conversion model, and then calculating the current deformation energy and total deformation energy of the forging based on the press data, flywheel angular velocity and slide speed to predict the number of forging blows required for forging; (4) displaying the press data, forging data, flywheel angular velocity, slide speed and number of forging blows to complete the digital twin. This invention realizes real-time communication of the press and real-time display of the status of the servo direct-drive CNC electric screw press.

Description

Technical Field

[0001] This invention belongs to the technical field of real-time monitoring of servo presses, and more specifically, relates to a digital twin method and system for servo presses based on force-energy-displacement conversion. Background Technology

[0002] Intelligent forging is a forging process with intelligent sensing and communication capabilities. Its core issue is the integration of the physical and information worlds. Digital twin technology is an effective way to integrate the physical and information worlds. As a new type of intelligent forging technology, digital twins achieve full-process visualization of information by realizing the virtual-real fusion between physical products and their digital twins, ensuring the timeliness of information and timely feedback, and are widely used in the field of intelligent forging.

[0003] Screw presses are widely used equipment in the forging industry, and high-efficiency, energy-saving, and intelligent CNC servo direct-drive CNC electric screw presses represent the latest development trend in forging equipment and are a key research focus both domestically and internationally. However, current servo direct-drive CNC electric screw presses face several challenges during operation: information blockage and untimely feedback in the production process lead to difficulties in guaranteeing processing quality; the press operation is inherently uncertain and random, making it difficult to avoid unexpected situations during forging, and the press cannot dynamically adjust its operating strategy according to changing working conditions; and the degree of deformation of forgings is difficult to predict when forging new types of forgings. Summary of the Invention

[0004] To address the above-mentioned deficiencies or improvement needs of existing technologies, this invention provides a servo press digital twin method and system based on force-energy-displacement conversion, which is used to realize real-time communication during press operation, real-time display and monitoring of the status of servo direct-drive CNC electric screw press, and simulation and prediction of the forging production process.

[0005] To achieve the above objectives, according to one aspect of the present invention, a digital twin method for a servo press based on force-energy-displacement conversion is provided, the method comprising the following steps:

[0006] (1) Obtain the press data of the servo press and set the impact energy, and set the motion control model;

[0007] (2) Based on the press data, the flywheel angular velocity and slide speed of the servo press are calculated by the motion control model;

[0008] (3) Obtain forging data and set up a force-energy characteristic conversion model, and then calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel speed and the slide speed of the slider, so as to predict the number of forging blows required for the forging to form;

[0009] (4) Display the press data, the forging data, the flywheel angular velocity, the slide speed, and the number of forging blows to complete the digital twin.

[0010] Furthermore, in the motion control model, the rotation angle of the main screw of the servo press during the downward movement of the slider is:

[0011]

[0012] Where H is the sliding stroke of the slider and h is the lead of the main screw;

[0013]

[0014] Among them, E G E is the total work done by the slider and main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the gravitational acceleration, and M is the flywheel torque.

[0015]

[0016] Where, d ω / d t J is the angular acceleration of the flywheel. e w is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time;

[0017]

[0018] V t w represents the slider's downward sliding speed. t It is the real-time flywheel angular velocity.

[0019] Furthermore, the mathematical expression of the force-energy characteristic conversion model is:

[0020]

[0021] Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

[0022] Furthermore, the energy E0 of the moving part of the servo press is converted into the forging deformation energy E dThe elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now:

[0023] E0 = E d +E t +E m

[0024] E d =∫Pdλ d

[0025]

[0026] E m =(1-β)E0

[0027] Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. t β represents the elastic deformation of the stressed parts of the servo press, C represents the total stiffness of the servo press, and β represents the energy reduction factor.

[0028] Furthermore, the total deformation energy E of the forging 总 for:

[0029]

[0030] Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

[0031] Furthermore, the deformation energy E of the forging d Total deformation energy E of forging 总 The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

[0032] The present invention also provides a servo press digital twin system based on force-energy-displacement conversion, the system comprising:

[0033] The motion control model module is used to acquire the press data of the servo press and set the impact energy, and to set the motion control model.

[0034] The calculation module is used to calculate the flywheel angular velocity and slide speed of the servo press based on the press data and through the motion control model.

[0035] The prediction module is used to acquire forging data and set a force-energy characteristic conversion model, and then calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel speed and the slide speed of the slider, so as to predict the number of forging blows required to form the forging.

[0036] The display module is used to display the press data, the forging data, the flywheel angular velocity, the slide speed, and the number of forging blows to complete the digital twin.

[0037] The present invention also provides a computer-readable storage medium storing machine-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the servo press digital twin method based on force-energy-displacement conversion as described above.

[0038] In summary, compared with the prior art, the servo press digital twin method and system based on force-energy-displacement conversion provided by this invention have the following advantages:

[0039] 1. By using digital twin technology to acquire data in real time, the problem of limited and delayed information during the operation of servo direct-drive CNC electric screw presses is solved.

[0040] 2. Drive the operation of the digital twin model with the dynamic physical data of the real and timely servo direct-drive CNC electric screw press, and output the same structure as the physical entity to achieve virtual-real integration.

[0041] 3. Based on the patterns contained in the state data and operation data of the press, this invention can realize online pre-simulation of the future operation process of the servo direct drive CNC electric screw press and prediction of the operation results, thereby transforming the unknown into the known to a certain extent.

[0042] 4. When performing physical forging of the virtual predicted forging process, the present invention can adjust the parameters according to environmental changes so that the degree of deformation of the forging meets the actual requirements. Attached Figure Description

[0043] Figure 1 This is a block diagram of a digital twin system for a servo-driven direct-drive CNC electric screw press based on force-energy-displacement conversion, provided in Embodiment 5 of the present invention.

[0044] Figure 2 This is the FSM state transition diagram of Embodiment 5 of the present invention;

[0045] Figure 3 This is a schematic diagram of the forging simulation and prediction principle of embodiment 5 of the present invention;

[0046] Figure 4 This is a diagram illustrating the simulation and prediction process of forging in Embodiment 5 of the present invention.

[0047] Figure 5This is a flowchart illustrating the parameter self-adjustment principle of Embodiment 5 of the present invention;

[0048] Figure 6 This is a flowchart of the method of Embodiment 1 of the present invention;

[0049] Figure 7 This is a structural diagram of the system in Embodiment 2 of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0051] The present invention provides a servo press digital twin method based on force-energy-displacement conversion, which can be implemented in a terminal environment including one or more components such as a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0052] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0053] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0054] The display screen is used to show the user interface of each application.

[0055] In addition, those skilled in the art will understand that the structure of the terminal described above does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0056] In this invention, all subscripts do not represent any specific meaning; they are only used to facilitate the differentiation of parameters.

[0057] Example 1

[0058] like Figure 6 As shown, this embodiment of the invention provides a digital twin method for a servo press based on a force-energy-displacement conversion model, comprising the following steps:

[0059] Step 101: Obtain the press data and set the impact energy of the servo press, and set the motion control model.

[0060] Step 102: Based on the press data, calculate the flywheel angular velocity and slide speed of the servo press using the motion control model.

[0061] Specifically, in the motion control model:

[0062] During the downward movement of the slider, the corresponding rotation angle of the main screw is:

[0063]

[0064] Where H is the sliding stroke of the slider and h is the lead of the main screw;

[0065]

[0066]

[0067] Among them, E G E is the total work done by the slider and the main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and the main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the acceleration due to gravity, and M is the flywheel torque.

[0068]

[0069] Where, d ω / d t J is the angular acceleration of the flywheel. e w is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time;

[0070]

[0071] V t Let ω be the speed at which the slider slides down. t It is the real-time flywheel angular velocity.

[0072] Step 103: Obtain forging data, set up a force-energy characteristic conversion model, and calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, and predict the number of forging blows required to form the forging.

[0073] Specifically, in the force-energy characteristic conversion model:

[0074]

[0075] Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

[0076] Specifically, the energy E0 of the moving part of the servo press includes:

[0077] During the process of striking the forging, the energy E0 of the moving part of the servo press is converted into the deformation energy E of the forging. d The elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now:

[0078] E0 = E d +E t +E m

[0079] E d =∫Pdλ d

[0080]

[0081] E m =(1-β)E0

[0082] Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. t β represents the elastic deformation of the stressed parts of the servo press, C represents the total stiffness of the servo press, and β represents the energy reduction factor.

[0083] Specifically, this also includes calculating the total deformation energy E of the forging. 总 :

[0084]

[0085] Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

[0086] Specifically, the predicted number of forging blows for forming the forging includes:

[0087] Forging deformation energy E d Total deformation energy E of forging 总The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

[0088] Step 104: Display the press data, the forging data, the calculated parameters, and the predicted number of forging blows to complete the digital twin.

[0089] Example 2

[0090] like Figure 7 As shown, this embodiment of the invention also provides a servo press digital twin system based on a force-energy-displacement conversion model, comprising:

[0091] The motion control model module is used to acquire the press data of the servo press and the impact energy set by the user, and to set the motion control model.

[0092] The calculation module is used to calculate the flywheel angular velocity and slide speed of the servo press based on the press data and through the motion control model.

[0093] Specifically, the motion control model includes:

[0094] During the downward movement of the slider, the corresponding rotation angle of the main screw is:

[0095]

[0096] Where H is the sliding stroke of the slider and h is the lead of the main screw;

[0097]

[0098]

[0099] Among them, E G E is the total work done by the slider and main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the gravitational acceleration, and M is the flywheel torque.

[0100]

[0101] Where, d ω / d t J is the angular acceleration of the flywheel. e w is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time;

[0102]

[0103] V t w represents the slider's downward sliding speed. t It is the real-time flywheel angular velocity.

[0104] The prediction module is used to acquire forging data of the forging, set the force-energy characteristic conversion model, and calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, and predict the number of forging blows required to form the forging.

[0105] Specifically, the force-energy characteristic conversion model includes:

[0106]

[0107] Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

[0108] Specifically, the energy E0 of the moving part of the servo press includes:

[0109] During the process of striking the forging, the energy E0 of the moving part of the servo press is converted into the deformation energy E of the forging. d The elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now:

[0110] E0 = E d +E t +E m

[0111] E d =∫Pdλ d

[0112]

[0113] E m =(1-β)E0

[0114] Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. t β represents the elastic deformation of the stressed parts of the servo press, C represents the total stiffness of the servo press, and β represents the energy reduction factor.

[0115] Specifically, this also includes calculating the total deformation energy E of the forging. 总:

[0116]

[0117] Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

[0118] Specifically, the predicted number of forging blows for forming the forging includes:

[0119] Forging deformation energy E d Total deformation energy E of forging 总 The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

[0120] The display module is used to display the press data, the forging data, the calculated parameters, and the predicted number of forging blows to complete the digital twin.

[0121] Example 3

[0122] Embodiment 3 of the present invention also proposes a storage medium that stores multiple instructions, which, when executed, implement the aforementioned servo press digital twin method based on a force-energy-displacement conversion model.

[0123] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0124] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:

[0125] Step 101: Obtain the press data and user-set impact energy of the servo press, and set the motion control model;

[0126] Step 102: Based on the press data, calculate the flywheel angular velocity and slide speed of the servo press using the motion control model;

[0127] Specifically, the motion control model includes:

[0128] During the downward movement of the slider, the corresponding rotation angle of the main screw is:

[0129]

[0130] Where H is the sliding stroke of the slider and h is the lead of the main screw;

[0131]

[0132]

[0133] Among them, E G E is the total work done by the slider and main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the gravitational acceleration, and M is the flywheel torque.

[0134]

[0135] Where, d ω / d t J is the angular acceleration of the flywheel. e w is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time;

[0136]

[0137] V t w represents the slider's downward sliding speed. t It is the real-time flywheel angular velocity.

[0138] Step 103: Obtain the forging data of the forging, set the force-energy characteristic conversion model, and calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, and predict the number of forging blows required to form the forging.

[0139] Specifically, the force-energy characteristic conversion model includes:

[0140]

[0141] Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

[0142] Specifically, the energy E0 of the moving part of the servo press includes:

[0143] During the process of striking the forging, the energy E0 of the moving part of the servo press is converted into the deformation energy E of the forging. d The elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now:

[0144] E0 = Ed +E t +E m

[0145] E d =∫Pdλ d

[0146]

[0147] E m =(1-β)E0

[0148] Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. t β represents the elastic deformation of the stressed parts of the servo press, C represents the total stiffness of the servo press, and β represents the energy reduction factor.

[0149] Specifically, this also includes calculating the total deformation energy E of the forging. 总 :

[0150]

[0151] Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

[0152] Specifically, the predicted number of forging blows for forming the forging includes:

[0153] Forging deformation energy E d Total deformation energy E of forging 总 The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

[0154] Step 104: Display the press data, the forging data, the calculated parameters, and the predicted number of forging blows to complete the digital twin.

[0155] Example 4

[0156] Embodiment 4 of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned servo press digital twin method based on a force-energy-displacement conversion model.

[0157] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0158] The storage medium can be used to store software programs and modules, such as the digital twin method for a servo press with force-energy-displacement conversion in this embodiment of the invention. The processor executes the software programs and modules stored in the storage medium to perform various functional applications and data processing, thus realizing the aforementioned digital twin method for a servo press with force-energy-displacement conversion. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0159] The processor can use the transfer system to call information and applications stored in the storage medium to perform the following steps:

[0160] Step 101: Obtain the press data and user-set impact energy of the servo press, and set the motion control model;

[0161] Step 102: Based on the press data, calculate the flywheel angular velocity and slide speed of the servo press using the motion control model;

[0162] Specifically, the motion control model includes:

[0163] During the downward movement of the slider, the corresponding rotation angle of the main screw is:

[0164]

[0165] Where H is the sliding stroke of the slider and h is the lead of the main screw;

[0166]

[0167]

[0168] Among them, E G E is the total work done by the slider and main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the gravitational acceleration, and M is the flywheel torque.

[0169]

[0170] Where, d ω / d t J is the angular acceleration of the flywheel. ew is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time;

[0171]

[0172] V t w represents the slider's downward sliding speed. t It is the real-time flywheel angular velocity.

[0173] Step 103: Obtain the forging data of the forging, set the force-energy characteristic conversion model, and calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, and predict the number of forging blows required to form the forging.

[0174] Specifically, the force-energy characteristic conversion model includes:

[0175]

[0176] Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

[0177] Specifically, the energy E0 of the moving part of the servo press includes:

[0178] During the process of striking the forging, the energy E0 of the moving part of the servo press is converted into the deformation energy E of the forging. d The elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now:

[0179] E0 = E d +E t +E m

[0180] E d =∫Pdλ d

[0181]

[0182] E m =(1-β)E0

[0183] Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. tβ is the elastic deformation of the stressed component of the servo press, C is the total stiffness of the servo press, and β is the energy reduction factor.

[0184] Specifically, this also includes calculating the total deformation energy E of the forging. 总 :

[0185]

[0186] Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

[0187] Specifically, the predicted number of forging blows for forming the forging includes:

[0188] Forging deformation energy E d Total deformation energy E of forging 总 The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

[0189] Step 104: Display the press data, the forging data, the calculated parameters, and the predicted number of forging blows to complete the digital twin.

[0190] Example 5

[0191] Figure 1 This is a block diagram of a digital twin system according to an embodiment of the present invention. Figure 1 As shown, the digital twin system includes a physical entity module, a digital twin module, a data sensing module, a visual interaction module, and a communication connection module.

[0192] The physical entity module may include a servo-driven CNC electric screw press and physical sensors. In some embodiments, the servo-driven CNC electric screw press may be a conventional screw press. In some embodiments, the physical sensors may include one or more sensors, such as temperature sensors, current sensors, speed sensors, displacement sensors, etc., to acquire data such as motor temperature, motor current, slide speed, and displacement of the servo-driven CNC electric screw press. For multiple presses, multiple identical or different types of sensors can be used to acquire multidimensional arrays.

[0193] In some embodiments, the physical entity module may further include a data acquisition card. The data acquisition card can be used to transmit data acquired by the physical sensors to a PostgreSQL database for monitoring and integration, and then use visualization to display and detect the data in the form of charts. In some embodiments, the data acquisition card can be the NI USB-6009 data acquisition card, which has stable output, high cost-effectiveness, 8-channel analog input, direct USB power supply, and belongs to the NI acquisition system, enabling it to work well with acquisition software to acquire data. After the physical sensors and data acquisition card implement data acquisition functions, these data can be sent to the data sensing module in real time for storage and use.

[0194] The digital twin module can include a virtual press geometric model, a force-energy-displacement conversion physical model, and an FSM operating state switching model. The virtual press geometric model can be used to determine the virtual press model. In some embodiments, the virtual press model can be built using 3D modeling software. In some embodiments, the virtual press geometric model can include a UI interface display, which may display a login interface, the press model, the press operation process, and visualizations of some parameters. In some embodiments, this data can be displayed in the form of charts so that operators or users can understand the status of each parameter. For example, to more easily view and compare the changes and rates of change of parameters, line graphs can be used to depict the press slide speed-time curve, slide displacement-time curve, etc. In some embodiments, the process parameters required for forging by the press can be input through input boxes and fed back to the press to change the operating state of the press. In some embodiments, the press's striking mode can be selected through a drop-down window.

[0195] In some embodiments, the force-energy-displacement conversion physical model may include a motion control model and a force-energy characteristic conversion model for the press, used for motion-energy analysis of the servo press. The press's motion control model performs motion analysis, controlling the operation of the virtual press, particularly the displacement and speed control of the slide within the press. The press's force-energy characteristic conversion model performs energy analysis on the press's operation, calculating the press's electrical energy, kinetic energy, and deformation energy. Specifically, the deformation energy of the forging in a given stroke can be calculated from known parameters such as the impact energy set by the press. The degree of deformation of the forging is obtained from the ratio of the current deformation energy to the total deformation energy of the forging, predicting the number of forging blows required to form the forging. This allows for the simulation and prediction of the forging process using a digital twin.

[0196] In some embodiments, the FSM operating state switching model is used for switching the motion state of the virtual press model, so that the virtual press operates normally under the drive of dynamic physical data or input data.

[0197] The data sensing module can contain structured and unstructured data, which originate from dynamic physical datasets acquired by physical sensors, virtual simulation datasets, and visual interactive datasets. In some embodiments, the data stored in the data sensing module can be divided into state data and motion data. This data can be used to drive the operation of the digital twin module and the visual interactive module.

[0198] The visual interaction module may include a virtual working scene of the press and a user interface. In some embodiments, the virtual working scene of the press can display and monitor the entire operation process and status of the press in real time, and visualize the forging process of the press using the C# language. In some embodiments, the user interface can use user operations as interactive data to drive the operation of the physical and virtual press.

[0199] Figure 2 This is an FSM state transition diagram according to an embodiment of the present invention. A node in the diagram represents a state of the FSM; state 1 is called the "starting state," representing the initial state of the FSM, and state 6 is called the "ending state." Directed line segments represent state changes when input state change conditions are met. If there is no directed edge corresponding to the transition condition in the diagram, the FSM will enter a "dead state," and will remain in this "dead state" thereafter. In some embodiments, the FSM running state switching model is used for the motion state switching of a virtual pressure machine model, enabling the virtual pressure machine to operate under different data.

[0200] Figure 3 and Figure 4 This invention relates to an embodiment of the principle and process diagram of using a digital twin to simulate and predict the forging process of forgings. The user inputs parameters and commands through an interactive interface, and the data sensing module outputs digital and analog commands to drive the virtual press in the digital twin. In some embodiments, the operation of the press can be controlled by a motion control model, and the deformation energy of the forging in a given stroke can be calculated using the force-energy characteristic model of the press. The degree of deformation of the forging is then obtained from the ratio of the deformation energy in that stroke to the total deformation energy of the forging, predicting the number of forging blows required to form the forging. In this way, the forging simulation and prediction of forgings by the press can be realized, to a certain extent transforming the unknown into the predictable, effectively avoiding risks and reducing costs.

[0201] Figure 5This is a flowchart illustrating the parameter self-adjustment principle according to an embodiment of the present invention. In the data sensing module, the actual forging force measured by the tonnage indicator during forging in a servo-driven direct-drive CNC electric screw press is compared with the theoretical forging force calculated in the digital twin. If the actual forging force is less than the theoretical forging force, the set flywheel angular velocity and slide linear velocity are increased accordingly, and other influencing factor coefficients are adjusted to adjust the actual forging force for the next press. If the actual forging force is greater than the theoretical forging force, the set flywheel angular velocity and slide linear velocity are decreased, and other influencing factor coefficients are adjusted to ensure the magnitude of the next forging force, so that the deformation degree of the forging meets the actual requirements. Finally, the set flywheel angular velocity and slide linear velocity when the actual forging force equals the theoretical forging force are output and saved as reference values ​​for subsequent press inputs.

[0202] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0203] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0204] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0205] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0206] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0207] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only storage media (ROM), random access storage media (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0208] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A digital twin method for a servo press based on force-energy-displacement conversion, characterized in that, The method includes the following steps: (1) Obtain the press data of the servo press and set the impact energy, and set the motion control model; (2) Based on the press data, the flywheel angular velocity and slide speed of the servo press are calculated by the motion control model; (3) Obtain forging data and set up a force-energy characteristic conversion model, and then calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, so as to predict the number of forging blows required for the forging to be formed. (4) Display the press data, the forging data, the flywheel angular velocity, the slide speed, and the number of forging blows to complete the digital twin.

2. The servo press digital twin method based on force-energy-displacement conversion as described in claim 1, characterized in that: In the motion control model, the rotation angle of the main screw of the servo press during the downward movement of the slider is: Where H is the sliding stroke of the slider and h is the lead of the main screw; Among them, E G E is the total work done by the slider and main nut under their own weight during the downward impact of the slider, m1 is the sum of the masses of the slider and main nut, α is the helix angle of the screw pair, β1 is the equivalent friction angle of the screw pair, g is the gravitational acceleration, and M is the flywheel torque. Where, d ω / d t J is the angular acceleration of the flywheel. e w is the converted value of the total moment of inertia on the flywheel shaft side. t For the real-time flywheel angular velocity, d w d is the derivative of the flywheel angular velocity. t The derivative of time; V t Let ω be the speed at which the slider slides down. t It is the real-time flywheel angular velocity.

3. The servo press digital twin method based on force-energy-displacement conversion as described in claim 2, characterized in that: The mathematical expression for the force-energy conversion model is: Where E0 is the energy of the moving part of the servo press, J is the sum of the moments of inertia of the rotating parts of the servo press, ω is the angular velocity of the flywheel, m is the mass of the linear motion part of the servo press, and v m is the maximum downward sliding speed of the slider, and h is the lead of the main screw.

4. The servo press digital twin method based on force-energy-displacement conversion as described in claim 3, characterized in that: The energy E0 of the moving part of the servo press is converted into the forging deformation energy E of the forging. d The elastic deformation energy E of the stressed parts of the servo press t and friction loss energy E m ,Right now: E0=E d +E t +E m AND d =∫Pdλ d BY m (1-β)E0 Where P is the forging pressure of the servo press, and λ d λ represents the deformation of the forging. t β represents the elastic deformation of the stressed parts of the servo press, C represents the total stiffness of the servo press, and β represents the energy reduction factor.

5. The servo press digital twin method based on force-energy-displacement conversion as described in claim 4, characterized in that: Total deformation energy E of forging 总 for: Where f(x) is the forging force per unit deformation of the forging, and D is the total deformation of the forging.

6. The servo press digital twin method based on force-energy-displacement conversion as described in claim 5, characterized in that: Forging deformation energy E d Total deformation energy E of forging 总 The ratio represents the degree of deformation of the forging, which is expressed as a percentage. When the cumulative deformation of the forging after multiple forging blows approaches 100%, the forging is considered complete, and the number of forging blows is recorded.

7. A servo press digital twin system based on force-energy-displacement conversion, characterized in that: The system includes: The motion control model module is used to acquire the press data of the servo press and set the impact energy, and to set the motion control model. The calculation module is used to calculate the flywheel angular velocity and slide speed of the servo press based on the press data and through the motion control model. The prediction module is used to acquire forging data and set a force-energy characteristic conversion model, and then calculate the current deformation energy and total deformation energy of the forging based on the press data, the flywheel angular velocity and the slide speed of the slider, so as to predict the number of forging blows required to form the forging. The display module is used to display the press data, the forging data, the flywheel angular velocity, the slide speed, and the number of forging blows to complete the digital twin.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores machine-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the servo press digital twin method based on force-energy-displacement conversion as described in any one of claims 1-6.

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