Digital twin visualization prediction method, device, terminal and medium for industrial control components

Abstract

This application applies to the field of intelligent manufacturing technology and provides a digital twin visualization prediction method, device, terminal, and medium for industrial control components. The method includes: obtaining a digital twin of an industrial control device, wherein the industrial control device includes multiple industrial control components, each of which has an interactive relationship with the other; the digital twin includes digital components corresponding to each industrial control component, and each digital component establishes a digital analog relationship corresponding to the interaction relationship; obtaining operating data of the industrial control device; and predicting the operation of the industrial control device based on the operating data, the digital twin, and the digital analog relationship. This solution enables users to visually predict the operating status of industrial control components, improving the convenience and security of industrial management.

Description

Technical Field

[0001] The present application belongs to the field of intelligent manufacturing technology, and in particular relates to a digital twin visualization prediction method, device, terminal and medium for industrial control components. Background Art

[0002] Digital Twin technology makes full use of data such as physical models, sensor updates, and operation history, integrates multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, and maps industrial products, cities, etc. in virtual space, thereby reflecting the entire life cycle of the corresponding physical equipment.

[0003] As my country's industrial market continues to expand, the use of intelligent control technologies to enable intelligent monitoring and operation of various industrial control applications, equipment, and processes has become a trend in industrial production, leading to the development of intelligent and digital industrial production. However, in existing industrial production processes, complex industrial machinery often experiences unexpected component aging and failure, resulting in significant daily maintenance costs, difficult factory and enterprise management, and reduced production efficiency. Summary of the Invention

[0004] The embodiments of the present application provide a digital twin visualization prediction method, device, terminal and medium for industrial control components to solve the problem in the prior art that when complex industrial machine components age or fail, the maintenance cost is too high, the factory or enterprise management is difficult, and production efficiency is reduced.

[0005] A first aspect of an embodiment of the present application provides a digital twin visualization prediction method for an industrial control component, comprising: obtaining a digital twin of an industrial control device, wherein the industrial control device includes a plurality of industrial control components, each of the industrial control components having an interaction relationship, the digital twin including a digital component corresponding to each of the industrial control components, and establishing a digital analog relationship corresponding to the interaction relationship between the digital components;

[0006] Obtaining operation data of the industrial control equipment;

[0007] Based on the operation data, combined with the digital twin and the digital simulation relationship, the operation of the industrial control equipment is predicted.

[0008] A second aspect of an embodiment of the present application provides a digital twin visualization prediction device for an industrial control component, comprising:

[0009] A digital twin acquisition module is configured to acquire a digital twin of an industrial control device, wherein the industrial control device includes multiple industrial control components, each of which has an interactive relationship with the other. The digital twin includes digital components corresponding to each of the industrial control components, and each of the digital components establishes a digital analog relationship corresponding to the interactive relationship.

[0010] An operation data acquisition module, used to acquire the operation data of the industrial control equipment;

[0011] An operation prediction module is used to perform operation prediction on the industrial control equipment based on the operation data in combination with the digital twin and the digital simulation relationship.

[0012] The digital twin acquisition module is specifically used to:

[0013] Performing skeleton node simulation on each industrial control component in the industrial control device to obtain the digital components corresponding to each industrial control component;

[0014] Capturing operation collision activities of each of the industrial control components in the industrial control device, and analyzing the interaction relationships between the industrial control components based on the captured operation collision activities;

[0015] Based on the interaction relationship, the digital analog relationship is generated.

[0016] A third aspect of an embodiment of the present application provides a terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0017] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0018] A fifth aspect of the present application provides a computer program product, which, when executed on a terminal, enables the terminal to execute the steps of the method described in the first aspect.

[0019] As can be seen from the above, in the embodiments of the present application, digital twins are used to realize visual monitoring and operation of industrial control equipment in the physical world, and then by obtaining the operating data of the industrial control equipment, combined with the digital twins and digital simulation relationships, the operation of the industrial control equipment is predicted, allowing users to better manage equipment and factories and reduce risks that could not be predicted by traditional monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 This is a process of a digital twin visualization prediction method for industrial control components provided in an embodiment of the present application. Figure 1 ;

[0022] Figure 2 This is a process of a digital twin visualization prediction method for industrial control components provided in an embodiment of the present application. Figure 2 ;

[0023] Figure 3 This is a structural diagram of a digital twin visualization prediction device for an industrial control component provided in an embodiment of the present application;

[0024] Figure 4 This is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0026] It will be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0027] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0028] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0029] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0030] In specific implementations, the terminals described in the embodiments of the present application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and / or touch pads). It should also be understood that in some embodiments, the device is not a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., touch screen displays and / or touch pads).

[0031] In the following discussion, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and / or joystick.

[0032] The terminal supports various applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk burning application, a spreadsheet application, a game application, a phone application, a video conferencing application, an email application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and / or a digital video player application.

[0033] Various applications that can be executed on the terminal can use at least one common physical user interface device, such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and corresponding information displayed on the terminal can be adjusted and / or changed between applications and / or within a corresponding application. In this way, the common physical architecture of the terminal (e.g., the touch-sensitive surface) can support a variety of applications with user interfaces that are intuitive and transparent to the user.

[0034] It should be understood that the size of the serial numbers of each step in this embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of this application.

[0035] In order to illustrate the technical solution described in this application, specific embodiments are provided below.

[0036] See also Figure 1 , Figure 1 This is a process of a digital twin visualization prediction method for industrial control components provided in an embodiment of the present application. Figure 1 .like Figure 1 As shown, a digital twin visualization prediction method for industrial control components includes the following steps:

[0037] Step 101: Obtain a digital twin of the industrial control equipment. The industrial control equipment includes multiple industrial control components, and each industrial control component has an interactive relationship. The digital twin includes digital components corresponding to each industrial control component, and a digital analog relationship corresponding to the interaction relationship is established between each digital component.

[0038] Specifically, obtaining the digital twin of the industrial control equipment includes: simulating the skeleton and joint nodes of each industrial control component in the industrial control equipment to obtain the digital components corresponding to each industrial control component; capturing the operation and collision activities of each industrial control component in the industrial control equipment, and analyzing the interaction relationship between each industrial control component based on the captured operation and collision activities; and generating a digital simulation relationship based on the interaction relationship.

[0039] Among them, operational collision refers to the formation of collision bodies by various industrial control components. Different industrial control components are subjected to the action of mutual forces during operation, resulting in collision actions such as traction, dragging, and driving, which are generated by the simulated force of the collision body.

[0040] Among them, the digital twin of industrial control equipment is a dynamic replica of industrial control equipment in the physical world, which can be built through development tools such as Unity3D.

[0041] Specifically, the industrial control equipment can be a single device or a group of devices, such as a CNC machine tool, a robotic arm, etc.

[0042] Before building the digital twin, it includes building a primary preparatory model, a secondary preparatory model through shape-adaptive grid construction, and a final mimicry model through deep reconstruction. The final mimicry model is numbered, stored in a database, and a quick application function is built. The model database is open to authorized users, who can browse specific models at any time to understand the internal structure of industrial control equipment in the physical world.

[0043] Specifically, before building the digital twin, real-world data from industrial control components is collected in real time, including deflection activity index, operating position, implemented functions, and various sensor status data. Each piece of real-world data is assigned a unique ID for synchronization. This collected real-time data is then assigned to the corresponding digital component of the industrial control component in the digital twin via a C# script, ensuring synchronization between the physical industrial control device and the digital twin.

[0044] Among them, by analyzing the collected real data, we can understand the connection status between digital components and industrial control components. For example, if the collected real data suddenly does not change or shifts in a certain direction outside the constant average value range, it can be found that there is a problem with the connection of the corresponding industrial control component.

[0045] Specifically, after confirming that the industrial control components of industrial control equipment are synchronously connected to the corresponding digital components in the digital twin, the digital twin will map the physical industrial control components through the synchronized digital components. When the status of the physical industrial control components changes, the backend calls GetPointState to check whether the current state is normal, whether it is being controlled, or whether it has malfunctioned. If the test result is failure, an error message is transmitted. If the test result is successful or the error message is not significant, the real data is fed back and recorded to the platform.

[0046] The digital components obtained during the synchronization phase and the data fed back during the contact detection phase are encapsulated into a Mobilizable class format and controlled by a Mobilizable Controller (MC). The MC can control, switch, and blend animations by adjusting the bones, joints, and animation speed, start / stop parameters of the movable structure. It can also implement IK (Inverse Kinematics) control through reverse collisions.

[0047] Furthermore, the front-end receives user input data, including commands for manipulating the digital twin, such as moving digital components and clicking trigger buttons. After analyzing this data using the JudgeOperate method, the MC is called to implement the Mobilizable animation of the current digital twin and determine whether the industrial control device can actually perform the action. This judgment process involves performing a data handshake between the front-end data analyzed by the JudgeOperate method and the animation feedback data, converting them into a specific format and transmitting them to the back-end. The back-end then controls the physical industrial control device to perform the corresponding action corresponding to the front-end input.

[0048] Furthermore, the backend returns a request to the frontend. If the backend receives a successful request, the digital twin maintains the state corresponding to the user's frontend operation. If the backend receives a failure or does not respond to the request within a time limit, the digital twin reverts to the state it was in before the user operated on the frontend. The digital twin is then inspected for faults and a warning is issued, notifying the on-site supervisor to repair the physical industrial control equipment. This step allows for rapid identification of fault issues and multi-threaded control, effectively reducing labor costs.

[0049] Step 102: Acquire the operating data of the industrial control equipment.

[0050] Specifically, obtaining the operating data of the industrial control equipment includes: collecting the current weight data, usage time and the pending operation plan corresponding to the industrial control equipment of each industrial control component in the industrial control equipment; obtaining the operating data including the current weight data, usage time and the pending operation plan.

[0051] Among them, the operating data also includes: structural wear offset error, etc.

[0052] Specifically, the industrial control components may be several movable joints, operating units or sensors.

[0053] Step 103: Based on the operation data, combined with the digital twin and digital simulation relationship, the operation of the industrial control equipment is predicted.

[0054] The digital simulation relationship includes a force action simulation relationship corresponding to the interaction relationship.

[0055] Specifically, based on the operation data, combined with the digital twin and digital simulation relationship, the operation of industrial control equipment is predicted, including: based on the usage time and the job plan to be executed in the operation data, combined with the usage loss curve of each industrial control component, predicting the change in the force action simulation relationship between each industrial control component in the action simulation relationship; based on the current weight data, determining the gravity value of each industrial control component; based on the gravity value and the change in the force action simulation relationship, predicting the operation deviation of the industrial control equipment.

[0056] The operational deviation also includes deformation of an object due to tension or looseness of a joint due to friction.

[0057] Specifically, by analyzing the log information and comparing the data between the same type of industrial control components in the past, as well as comparing the current operation status of the industrial control component with the log information of the component in the log, the usage loss curve of each industrial control component is obtained.

[0058] In the embodiments of the present application, digital twins are used to achieve visual monitoring and operation of industrial control equipment in the physical world. Then, by obtaining the operating data of the industrial control equipment and combining it with the digital twins and digital simulation relationships, the operation of the industrial control equipment is predicted, allowing users to better manage equipment and factories and reduce risks that could not be predicted by traditional monitoring.

[0059] The embodiments of the present application also provide different implementation methods of a digital twin visualization prediction method for an industrial control component.

[0060] See also Figure 2 , Figure 2This is a process of a digital twin visualization prediction method for industrial control components provided in an embodiment of the present application. Figure 2 .like Figure 2 As shown, a digital twin visualization prediction method for industrial control components includes the following steps:

[0061] Step 201: Acquire a digital twin of an industrial control device. The industrial control device includes multiple industrial control components, each of which interacts with the other. The digital twin includes digital components corresponding to each industrial control component, and digital analog relationships corresponding to the interaction relationships are established between the digital components.

[0062] The implementation process of this step is the same as the implementation process of step 101 in the aforementioned embodiment, and will not be repeated here.

[0063] Step 202, obtaining the operation data of the industrial control equipment;

[0064] The implementation process of this step is the same as the implementation process of step 102 in the aforementioned embodiment, and will not be repeated here.

[0065] Step 203: Based on the operation data, combined with the digital twin and digital simulation relationship, the operation of the industrial control equipment is predicted.

[0066] The implementation process of this step is the same as the implementation process of step 103 in the aforementioned embodiment, and will not be repeated here.

[0067] In step 204 , the predicted operation prediction results are displayed and arranged according to the set weights of the data of different dimensions to obtain prediction display content; and the prediction display content is output for display.

[0068] This process enables the visualization of prediction results.

[0069] Optionally, the predicted operation prediction results are displayed and arranged according to the set weights of data of different dimensions to obtain prediction display content, including: determining the prediction result data corresponding to each industrial control component in the predicted operation prediction results; determining the set weights of each prediction result data according to the operation importance of each industrial control component; and displaying and arranging the prediction result data according to the set weights to obtain prediction display content.

[0070] In the embodiment of the present application, digital twins are used to realize visual monitoring and operation of industrial control equipment in the physical world. Then, by obtaining the operating data of the industrial control equipment and combining the digital twins and digital simulation relationships, the operation of the industrial control equipment is predicted. According to the set weights of the data in different dimensions, the predicted operation prediction results are displayed and arranged to obtain the predicted display content, allowing users to better manage equipment and factories and reduce risks that could not be predicted by traditional monitoring.

[0071] See also Figure 3 , Figure 3 This is a structural diagram of a digital twin visualization prediction device for an industrial control component provided in an embodiment of the present application. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0072] The digital twin visualization prediction device for industrial control components includes:

[0073] The digital twin acquisition module 301 is used to acquire a digital twin of an industrial control device. The industrial control device includes multiple industrial control components, each of which has an interactive relationship with each other. The digital twin includes digital components corresponding to each industrial control component, and the digital components establish a digital analog relationship corresponding to the interaction relationship.

[0074] Operation data acquisition module 302, used to obtain operation data of industrial control equipment;

[0075] The operation prediction module 303 is used to perform operation prediction on industrial control equipment based on operation data, combined with digital twins and digital simulation relationships.

[0076] The operation prediction module 303 is specifically used to:

[0077] According to the set weights of data of different dimensions, the predicted operation prediction results are displayed and arranged to obtain prediction display content; and the prediction display content is output and displayed.

[0078] The operation prediction module 303 is more specifically used to:

[0079] Determine the prediction result data corresponding to each industrial control component in the predicted operation prediction results; determine the set weight of each prediction result data according to the operation importance of each industrial control component; and display and arrange the prediction result data according to the set weight to obtain the prediction display content.

[0080] The digital simulation relationship includes a force simulation relationship corresponding to the interaction relationship; the operation prediction module 303 is further specifically used to:

[0081] Based on the usage time and pending operation plan in the operation data, combined with the usage loss curve of each industrial control component, the change in the force simulation relationship between each industrial control component in the action simulation relationship is predicted;

[0082] Based on the current weight data, determine the gravity value of each industrial control component;

[0083] Based on the gravity value and the change in the force simulation relationship, the operating deviation of the industrial control equipment is predicted.

[0084] The operation data acquisition module 302 is specifically used to:

[0085] Collect the current weight data, usage time and pending operation plan of each industrial control component in the industrial control equipment respectively;

[0086] Get the operation data including current weight data, usage time and operation plan to be executed.

[0087] The operation data acquisition module 302 is more specifically used to:

[0088] Collect the current weight data, usage time and pending operation plan of each industrial control component in the industrial control equipment respectively;

[0089] Get the operation data including current weight data, usage time and operation plan to be executed.

[0090] The digital twin acquisition module 301 is specifically used to:

[0091] Perform skeleton node simulation on each industrial control component in the industrial control equipment to obtain the digital components corresponding to each industrial control component;

[0092] Capture the operational collision activities of each industrial control component in the industrial control equipment, and analyze the interaction relationship between each industrial control component based on the captured operational collision activities;

[0093] Based on the interaction relationship, digital simulation relationship is generated.

[0094] The digital twin visualization prediction device for industrial control components provided in the embodiment of the present application can implement the various processes of the embodiment of the digital twin visualization prediction method for industrial control components mentioned above, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0095] Figure 4 This is a structural diagram of a terminal provided by an embodiment of the present application. As shown in the figure, the terminal 4 of this embodiment includes: at least one processor 40 ( Figure 4Only one is shown), a memory 41 and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, wherein the processor 40 implements the steps of any of the above-mentioned method embodiments when executing the computer program 42.

[0096] The terminal 4 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 4 can include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will understand that Figure 4 It is only an example of terminal 4 and does not constitute a limitation on terminal 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0097] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0098] The memory 41 may be an internal storage unit of the terminal 4, such as a hard disk or memory of the terminal 4. The memory 41 may also be an external storage device of the terminal 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the terminal 4. Furthermore, the memory 41 may include both an internal storage unit of the terminal 4 and an external storage device. The memory 41 is used to store the computer program and other programs and data required by the terminal. The memory 41 may also be used to temporarily store data that has been output or is about to be output.

[0099] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0100] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0101] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0102] In the embodiments provided in this application, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0103] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0104] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0105] If the integrated module / unit is implemented in the form of 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 present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0106] The present application implements all or part of the processes in the above-mentioned embodiment method, and can also be implemented through a computer program product. When the computer program product runs on a terminal, the terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0107] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A digital twin visualization prediction method for industrial control components, characterized in that: include: Obtaining a digital twin of an industrial control device, wherein the industrial control device includes a plurality of industrial control components, each of the industrial control components having an interaction relationship, the digital twin including digital components corresponding to each of the industrial control components, and each of the digital components establishing a digital analog relationship corresponding to the interaction relationship; the digital analog relationship including a force action analog relationship corresponding to the interaction relationship; Obtaining operation data of the industrial control equipment; Based on the operation data, combined with the digital twin and the digital simulation relationship, predict the operation of the industrial control equipment; The obtaining of the operation data of the industrial control equipment includes: respectively collecting the current weight data, usage time and the to-be-executed operation plan corresponding to each industrial control component in the industrial control equipment; Obtaining operation data including the current weight data, the usage time, and the operation plan to be executed; The step of predicting the operation of the industrial control equipment based on the operation data, in combination with the digital twin and the digital simulation relationship, includes: Based on the usage duration and the to-be-executed operation plan in the operation data and in combination with the usage loss curve of each of the industrial control components, predicting a change in the force action simulation relationship between each of the industrial control components in the action simulation relationship; Determining the gravity value of each of the industrial control components based on the current weight data; Based on the gravity value and the change in the force action simulation relationship, the operation deviation of the industrial control equipment is predicted.

2. The method according to claim 1, characterized in that The obtaining of the digital twin of the industrial control equipment includes: Performing skeleton node simulation on each industrial control component in the industrial control device to obtain the digital components corresponding to each industrial control component; Capturing operation collision activities of each of the industrial control components in the industrial control device, and analyzing the interaction relationships between the industrial control components based on the captured operation collision activities; Based on the interaction relationship, the digital analog relationship is generated.

3. The method according to claim 1, characterized in that After performing operation prediction on the industrial control equipment based on the operation data, in combination with the digital twin and the digital simulation relationship, the method further includes: According to the set weights of different dimensional data, the predicted operation prediction results are displayed and arranged to obtain the predicted display content; The predicted display content is output and displayed.

4. The method according to claim 3, characterized in that The operation prediction results obtained are displayed and arranged according to the set weights of the data of different dimensions to obtain the prediction display content, including: Determining prediction result data corresponding to each of the industrial control components in the predicted operation prediction results; Determining a set weight for each of the prediction result data according to the operational importance of each of the industrial control components; According to the set weights, the prediction result data is displayed and arranged to obtain the prediction display content.

5. A digital twin visualization prediction device for industrial control components, characterized in that: include: A digital twin acquisition module, configured to acquire a digital twin of an industrial control device, wherein the industrial control device includes a plurality of industrial control components, each of which has an interaction relationship with the other. The digital twin includes digital components corresponding to each of the industrial control components, and each of the digital components establishes a digital analog relationship corresponding to the interaction relationship; the digital analog relationship includes a force action analog relationship corresponding to the interaction relationship. An operation data acquisition module, used to acquire the operation data of the industrial control equipment; an operation prediction module, configured to perform operation prediction on the industrial control equipment based on the operation data, in combination with the digital twin and the digital analog relationship; The operation data acquisition module is specifically used to: respectively collecting the current weight data, usage time and the to-be-executed operation plan corresponding to each industrial control component in the industrial control equipment; Obtaining operation data including the current weight data, the usage time, and the operation plan to be executed; Operation prediction module, specifically used for: Based on the usage duration and the to-be-executed operation plan in the operation data and in combination with the usage loss curve of each of the industrial control components, predicting a change in the force action simulation relationship between each of the industrial control components in the action simulation relationship; Determining the gravity value of each of the industrial control components based on the current weight data; Based on the gravity value and the change in the force action simulation relationship, the operation deviation of the industrial control equipment is predicted.

6. The device according to claim 5, characterized in that The digital twin acquisition module is specifically used to: Performing skeleton node simulation on each industrial control component in the industrial control device to obtain the digital components corresponding to each industrial control component; Capturing operation collision activities of each of the industrial control components in the industrial control device, and analyzing the interaction relationships between the industrial control components based on the captured operation collision activities; Based on the interaction relationship, the digital analog relationship is generated.

7. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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