A hot-rolling roller intelligent planning method, monitoring and early warning method and system based on digital twinning

Abstract

The application provides a hot rolling roller intelligent planning method based on digital twinning, utilizes a digital twinning roller operation space model to process roller operation full life cycle data and roller operation dynamic data, obtains virtual space image data, and displays the virtual space image data to an operator, the operator observes the operation condition of the roller through the image of the roller in the virtual space, when there is a new order, the operator observes the operation condition of each roller of the roller group through a virtual space built by digital twinning technology, predicts when the roller needs to be replaced, production personnel perform roller replacement and machine operation, unifies the geographic coordinate data of the digital twinning space where the roller is located and the digital twinning space of the workshop, records the roller operation data according to the system, and provides the production personnel with the current operation state of the roller and other auxiliary maintenance data. The application mainly utilizes digital twinning technology, simulates the analysis of roller operation state characteristic data, and provides the function of selecting a suitable roller according to the rules set according to the industry standard and the on-site production environment.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more particularly to a method, monitoring and early warning method and system for intelligent planning of hot rolling mill rolls based on digital twins. Background Technology

[0002] In a hot strip mill production line, the rolling mill plays a crucial role in the stable rolling of slabs. After rolling a certain number of tons of steel billets, the rolls need to be removed from the mill for grinding and stored in the warehouse for reuse. To ensure product quality stability, production personnel need to control roll changing operations. To accommodate the production of steel plates of different thicknesses, rolls also need to be changed according to order requirements. Therefore, planning and managing roll usage is an essential process.

[0003] Currently, the condition and end-of-life of rolls can only be determined manually based on experience, lacking an information platform to support the full lifecycle management of rolls. Multiple hot rolling production lines with similar or identical units have overlapping production capacities, and multiple rolls of the same type are available, offering numerous choices. On-site staff still need to manually select rolls to meet order requirements. Existing technology can only record the usage of individual rolls and cannot achieve intelligent selection.

[0004] With the maturation of the digital twin concept and the development of technology, a digital twin world is being continuously constructed, from components to complete machines, from products to production lines, from production to services, and from static to dynamic processes. Various products based on digital twins are emerging, and constructing virtual industrial units to solve problems in actual units, providing early warnings of potential issues, and assisting humans in planning and judgment are of great significance. Summary of the Invention

[0005] To address the aforementioned technical problems in roll usage planning, this invention provides a digital twin-based intelligent planning method, monitoring and early warning method, and system for hot rolling rolls. This invention primarily utilizes digital twin technology to simulate and analyze roll operating status characteristic data, providing the function of selecting suitable rolls based on rules set according to industry standards and the on-site production environment.

[0006] The technical means employed in this invention are as follows: A digital twin-based intelligent planning method for hot rolling mill rolls includes: S1. Establish the system's basic dataset; S2. Select hot-rolled thickness as input condition data, and input order feature data; S3. Set the roll detection rules to determine whether the tonnage and mileage of the input order are within the range; S4. Set up the intelligent planning model for the rolls and check whether the current roll needs to be replaced. If the roll needs to be replaced, then the new roll is put on the machine; if the roll does not need to be replaced, then after the rolling is completed, record the rolling production data. S5. Based on the recorded rolling production data, determine whether the planning result is qualified. If qualified, give the planning result; if not qualified, return to step S3.

[0007] Furthermore, in step S1, establishing the system's basic dataset specifically includes: Establish the following tables in the information system: basic information table for rolls, roll usage performance table, roll grinding performance table, roll change information table, and stand roll allocation record table, among which: The basic information table for the rolls includes roll number, roll type, roll working section category, roll condition, matching mark, initial hardness of roll body, initial hardness of roll neck, roll quality grade, roll hardness grade, supplied diameter, minimum usable diameter, actual diameter, roll weight, warehouse code, paired roll number, cumulative rolling tonnage, cumulative rolling mileage, cumulative grinding times, paired mill number, time of commissioning, last loading time, last use time, cumulative rolling tonnage at last loading, and cumulative rolling mileage at last loading. The roll usage performance table includes roll number, roll type, roll working section category, loading time, ending time, rolling weight, rolling length, number of rolled blocks, rolling notes, stand number, stand position, rolling stand number, paired mill number, paired roll number, paired drive side bearing housing number, paired drive side bearing number, paired operating side bearing housing number, and paired operating side bearing number. The actual grinding record of the rolls includes the roll number, roll type, maximum diameter, minimum diameter, maximum crown, minimum crown, maximum grinding amount, and minimum grinding amount. The roll change information table includes the unit number, frame number, roll type, upper roll number, lower roll number, and roll change date; The stand roll allocation record sheet includes the unit number, stand number, roll type, upper roll number, and lower roll number.

[0008] Furthermore, in step S2, the input order feature data is used to determine whether the hot-rolled thickness of the finished product falls within the actual diameter rolling range of the production line unit's rolls.

[0009] Furthermore, step S3 specifically includes: Based on the system's set factors and rules, such as the maximum rolling tonnage of the rolls, the amount of material rolled each time the hot rolling rolls are used, the cumulative rolling tonnage, the cumulative rolling mileage, the cumulative rolling tonnage at the last load, and the cumulative rolling mileage at the last load, it is determined whether the tonnage and mileage of this order are within the range.

[0010] Furthermore, step S4 specifically includes: The intelligent roll planning model verifies the current roll. If it meets the requirements, rolling proceeds normally. If it does not meet the requirements, a suitable roll is selected from the roll library based on the factors of hot rolling thickness, cumulative rolling tonnage, cumulative rolling mileage, last loaded cumulative rolling tonnage, and last loaded cumulative rolling mileage.

[0011] This invention also provides a roll monitoring and early warning method based on the above-mentioned intelligent planning method for hot rolling rolls, comprising: Obtain feature data of the actual main body of the roll; The feature data is used to construct a digital twin roll application model through a preset mapping relationship; Collect the roll running status trajectory data and substitute the roll running data into the digital twin roll running space model to generate roll running dynamic data; Collect coordinate data within the main body of the rolling mill, establish a correlation between the coordinate data and the rolling mill's on / off data, obtain the rolling mill's position data within the entity, and store the rolling mill's position data to obtain the rolling mill's full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of the roll operation and the dynamic data of the roll operation are processed to obtain virtual space image data.

[0012] Furthermore, the acquisition of feature data of the actual main object in the roll running space includes: Create a data model of the physical entity that is the actual main body of the roll running space. The structure of the data model is a set of attribute parameters of the physical entity. The structure of the data model is obtained by determining the set of attribute parameters of the physical entity. The attribute parameters in the set of attribute parameters of the physical entity include the attribute name and data type. Establish a correlation between the data in the attribute parameter set of the physical entity and the actual main body of the roll running space.

[0013] Furthermore, the acquisition of coordinate data within the rolling mill body includes: Acquire map data within the area where the main rolling mill is located; A correlation is established between the geographic location information and the coordinate data of the main rolling mill, and the geographic location information is used to indicate the travel path of maintenance personnel.

[0014] This invention also provides a roll monitoring and early warning system based on the above-mentioned roll monitoring and early warning method, comprising: a data acquisition terminal, a server connected to the data acquisition terminal, an operator terminal connected to the server, and a background control terminal, wherein: The data acquisition terminal includes an intelligent terminal device used to acquire feature data of the actual main object in the roll running space; The server is used to construct a digital twin roll operation space model by using the feature data acquired by the data acquisition terminal through a preset mapping relationship, collect roll operation status trajectory data, and substitute the roll operation status trajectory data into the digital twin roll operation space model to generate roll operation dynamic data, collect coordinate data within the roll operation body, establish a correlation between the coordinate data and the roll operation status trajectory data to obtain the roll operation position data within the entity object, and store the roll operation position data to obtain the roll operation status full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of roll operation and the roll operation dynamic data are processed to obtain virtual space image data.

[0015] Compared with the prior art, the present invention has the following advantages: 1. The roll monitoring and early warning method and system based on digital twin provided by this invention processes the full life cycle data and dynamic data of roll operation based on the digital twin roll operation space model to obtain virtual space image data. The spatial image data is displayed to the operator in virtual space form. The operator can intuitively observe the operation of the roll by observing the image of the roll in the virtual space. When there is a new order, the operator can intuitively observe the operation of each roll in the roll group through the virtual space built by digital twin technology. When it is predicted that roll replacement is needed, the production personnel go to the unit where the old roll is located to perform the roll replacement operation. The geographical coordinate data of the digital twin space where the roll is located is unified with the digital twin space of the factory. Based on the roll operation data recorded by the system, the current operation status of the roll and other auxiliary maintenance data are given to the production personnel.

[0016] 2. Compared with traditional paper documents, digital twin technology has a three-dimensional feel. Production personnel can quickly find corresponding objects such as rollers by displaying the production line in a virtual space. By displaying the roller assembly in a virtual space through digital twin technology, more comprehensive reference data is provided for production rolling. Production personnel can predict the roller usage plan in advance, solving the problems of incomplete effective roller data, easy loss, and reliance on manual labor.

[0017] Based on the above reasons, this invention can be widely applied in fields such as computers. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the intelligent planning method for hot rolling rolls based on digital twins according to the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] like Figure 1 As shown, this invention provides a digital twin-based intelligent planning method for hot rolling mill rolls, comprising: S1. Establish the system's basic dataset; S2. Select hot-rolled thickness as input condition data, and input order feature data; S3. Set the roll detection rules to determine whether the tonnage and mileage of the input order are within the range; S4. Set up the intelligent planning model for the rolls and check whether the current roll needs to be replaced. If the roll needs to be replaced, then the new roll is put on the machine; if the roll does not need to be replaced, then after the rolling is completed, record the rolling production data. S5. Based on the recorded rolling production data, determine whether the planning result is qualified. If qualified, give the planning result; if not qualified, return to step S3.

[0023] In a specific implementation, as a preferred embodiment of the present invention, step S1, establishing the system basic dataset, specifically includes: Establish the following tables in the information system: basic information table for rolls, roll usage performance table, roll grinding performance table, roll change information table, and stand roll allocation record table, among which: The basic information table for the rolls includes roll number, roll type, roll working section category, roll condition, matching mark, initial hardness of roll body, initial hardness of roll neck, roll quality grade, roll hardness grade, supplied diameter, minimum usable diameter, actual diameter, roll weight, warehouse code, paired roll number, cumulative rolling tonnage, cumulative rolling mileage, cumulative grinding times, paired mill number, time of commissioning, last loading time, last use time, cumulative rolling tonnage at last loading, and cumulative rolling mileage at last loading. The roll usage performance table includes roll number, roll type, roll working section category, loading time, ending time, rolling weight, rolling length, number of rolled blocks, rolling notes, stand number, stand position, rolling stand number, paired mill number, paired roll number, paired drive side bearing housing number, paired drive side bearing number, paired operating side bearing housing number, and paired operating side bearing number. The actual grinding record of the rolls includes the roll number, roll type, maximum diameter, minimum diameter, maximum crown, minimum crown, maximum grinding amount, and minimum grinding amount. The roll change information table includes the unit number, frame number, roll type, upper roll number, lower roll number, and roll change date; The stand roll allocation record sheet includes the unit number, stand number, roll type, upper roll number, and lower roll number.

[0024] In a specific implementation, as a preferred embodiment of the present invention, in step S2, the input order feature data is used to determine whether the hot-rolled thickness of the finished product is within the actual diameter rolling range of the production line unit's rolls.

[0025] In a specific implementation, as a preferred embodiment of the present invention, step S3 specifically includes: Based on the system's set factors and rules, such as the maximum rolling tonnage of the rolls, the amount of material rolled each time the hot rolling rolls are used, the cumulative rolling tonnage, the cumulative rolling mileage, the cumulative rolling tonnage at the last load, and the cumulative rolling mileage at the last load, it is determined whether the tonnage and mileage of this order are within the range.

[0026] In a specific implementation, as a preferred embodiment of the present invention, step S4 specifically includes: The intelligent roll planning model verifies the current roll. If it meets the requirements, normal rolling proceeds. If not, a suitable roll is reselected from the roll library based on factors such as hot-rolled thickness, cumulative rolling tonnage, cumulative rolling mileage, and the cumulative rolling tonnage and mileage of the last roll loaded. In this embodiment, when a suitable roll needs to be reselected from the roll library, on-site personnel load the newly selected roll. Roll inspectors determine whether the roll should be repaired or sent to the spare parts area for standby based on the condition of the replaced roll. If an abnormality is found during repair and the roll cannot continue to be used, it is scrapped, and the system dataset is recorded. In specific implementation, as a preferred embodiment of the present invention, the data sources of this technical solution are organic data acquisition, MES system order database, production performance database, and acquisition of roll numbers for rolls entering and leaving the mill; the grinding process is to create a roll grinding order in the system and record the actual diameter of the roll after grinding.

[0027] The present invention also provides a roll monitoring and early warning method based on the intelligent planning method for hot rolling rolls in the above embodiments, comprising: Obtain feature data of the actual main body of the roll; The feature data is used to construct a digital twin roll application model through a preset mapping relationship; Collect the roll running status trajectory data and substitute the roll running data into the digital twin roll running space model to generate roll running dynamic data; Collect coordinate data within the main body of the rolling mill, establish a correlation between the coordinate data and the rolling mill's on / off data, obtain the rolling mill's position data within the entity, and store the rolling mill's position data to obtain the rolling mill's full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of the roll operation and the dynamic data of the roll operation are processed to obtain virtual space image data.

[0028] In a specific implementation, as a preferred embodiment of the present invention, the acquisition of feature data of the actual main object in the roll running space includes: Create a data model of the physical entity that is the actual main body of the roll running space. The structure of the data model is a set of attribute parameters of the physical entity. The structure of the data model is obtained by determining the set of attribute parameters of the physical entity. The attribute parameters in the set of attribute parameters of the physical entity include the attribute name and data type. Establish a correlation between the data in the attribute parameter set of the physical entity and the actual main body of the roll running space.

[0029] In a specific implementation, as a preferred embodiment of the present invention, the acquisition of coordinate data within the rolling mill body includes: Acquire map data within the area where the main rolling mill is located; A correlation is established between the geographic location information and the coordinate data of the main rolling mill, and the geographic location information is used to indicate the travel path of maintenance personnel.

[0030] In a specific implementation, as a preferred embodiment of the present invention, the processing of the full life-cycle data of the roll operation and the dynamic data of the roll operation based on the digital twin roll operation space model to obtain virtual space image data includes: Determine a set of predefined initial data values ​​corresponding to the target roll, and replace the determined set of predefined initial data values ​​with the attribute parameter values ​​corresponding to the current state of the target roll to obtain a real-time physical entity object; Real-time physical entity objects return data and send it to the server.

[0031] The present invention also provides a roll monitoring and early warning system based on the roll monitoring and early warning method in the above embodiments, comprising: a data acquisition terminal, a server terminal connected to the data acquisition terminal, an operator terminal connected to the server terminal, and a background control terminal, wherein: The data acquisition terminal includes an intelligent terminal device used to acquire feature data of the actual main object in the roll running space; The server is used to construct a digital twin roll operation space model by using the feature data acquired by the data acquisition terminal through a preset mapping relationship, collect roll operation status trajectory data, and substitute the roll operation status trajectory data into the digital twin roll operation space model to generate roll operation dynamic data, collect coordinate data within the roll operation body, establish a correlation between the coordinate data and the roll operation status trajectory data to obtain the roll operation position data within the entity object, and store the roll operation position data to obtain the roll operation status full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of roll operation and the roll operation dynamic data are processed to obtain virtual space image data.

[0032] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart planning method for hot rolling mill rolls based on digital twins, characterized in that, include: S1. Establish the system's basic dataset; S2. Select hot-rolled thickness as input condition data, and input order feature data; The input order feature data is used to determine whether the hot-rolled thickness of the finished product falls within the actual diameter rolling range of the production line unit's rolls; S3. Set roll inspection rules to determine whether the tonnage and mileage of the input order are within the range, specifically including: Based on the system's set factors and rules, such as the maximum rolling tonnage of the rolls, the amount of material rolled each time the hot rolling rolls are used, the cumulative rolling tonnage, the cumulative rolling mileage, the cumulative rolling tonnage at the last loading, and the cumulative rolling mileage at the last loading, it is determined whether the tonnage and mileage of this order are within the range. S4. Set up the intelligent roll planning model to verify whether the current roll needs to be changed. If a roll change is needed, install the new roll. If no roll change is needed, record the rolling production data after rolling is completed, including: The intelligent roll planning model verifies the current roll. If it meets the requirements, rolling proceeds normally. If it does not meet the requirements, a suitable roll is selected from the roll library based on the factors of hot rolling thickness, cumulative rolling tonnage, cumulative rolling mileage, last loaded cumulative rolling tonnage, and last loaded cumulative rolling mileage. S5. Based on the recorded rolling production data, determine whether the planning result is qualified. If qualified, give the planning result; if not qualified, return to step S3.

2. The intelligent planning method for hot rolling mill rolls based on digital twins according to claim 1, characterized in that, In step S1, establishing the system's basic dataset specifically includes: Establish the following tables in the information system: basic information table for rolls, roll usage performance table, roll grinding performance table, roll change information table, and stand roll allocation record table, among which: The basic information table for the rolls includes roll number, roll type, roll working section category, roll condition, matching mark, initial hardness of roll body, initial hardness of roll neck, roll quality grade, roll hardness grade, supplied diameter, minimum usable diameter, actual diameter, roll weight, warehouse code, paired roll number, cumulative rolling tonnage, cumulative rolling mileage, cumulative grinding times, paired mill number, time of commissioning, last loading time, last use time, cumulative rolling tonnage at last loading, and cumulative rolling mileage at last loading. The roll usage performance table includes roll number, roll type, roll working section category, loading time, ending time, rolling weight, rolling length, number of rolled blocks, rolling notes, stand number, stand position, rolling stand number, paired mill number, paired roll number, paired drive side bearing housing number, paired drive side bearing number, paired operating side bearing housing number, and paired operating side bearing number. The actual performance table of the roll grinding includes roll number, roll type, maximum diameter, minimum diameter, maximum crown, minimum crown, maximum grinding amount, and minimum grinding amount; The roll change information table includes the unit number, frame number, roll type, upper roll number, lower roll number, and roll change date; The stand roll allocation record sheet includes the unit number, stand number, roll type, upper roll number, and lower roll number.

3. A roll monitoring and early warning method based on the intelligent planning method for hot rolling rolls based on digital twins as described in any one of claims 1-2, characterized in that, include: Obtain feature data of the actual main body of the roll; The feature data is used to construct a digital twin roll application model through a preset mapping relationship; Collect the roll running status trajectory data and substitute the roll running data into the digital twin roll running space model to generate roll running dynamic data; Collect coordinate data within the main body of the rolling mill, establish a correlation between the coordinate data and the rolling mill's on / off data, obtain the rolling mill's position data within the entity, and store the rolling mill's position data to obtain the rolling mill's full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of the roll operation and the dynamic data of the roll operation are processed to obtain virtual space image data.

4. The method for monitoring and early warning of rolling mill rolls according to claim 3, characterized in that, Obtain feature data of the actual main object in the roll running space, including: Create a data model of the physical entity of the actual main body of the roll running space. The structure of the data model is a set of attribute parameters of the physical entity. The structure of the data model is obtained by determining the set of attribute parameters of the physical entity. The attribute parameters in the set of attribute parameters of the physical entity include the attribute name and data type. Establish a correlation between the data in the attribute parameter set of the physical entity and the actual main body of the roll running space.

5. The method for monitoring and early warning of rolling mill rolls according to claim 3, characterized in that, The acquisition of coordinate data within the rolling mill body includes: Acquire map data within the area where the main rolling mill is located; A correlation is established between the geographic location information and the coordinate data of the main rolling mill, and the geographic location information is used to indicate the travel path of maintenance personnel.

6. The method for monitoring and early warning of rolling mill rolls according to claim 3, characterized in that, The virtual space image data is obtained by processing the full life cycle data and dynamic data of the roll operation based on the digital twin roll operation space model, including: Determine a set of predefined initial data values ​​corresponding to the target roll, and replace the determined set of predefined initial data values ​​with the attribute parameter values ​​corresponding to the current state of the target roll to obtain a real-time physical entity object; Real-time physical entity objects return data and send it to the server.

7. A roll monitoring and early warning system based on the roll monitoring and early warning method according to any one of claims 3-6, characterized in that, include: The system comprises: a data acquisition terminal, a server connected to the data acquisition terminal, an operator terminal connected to the server, and a back-end control terminal, wherein: The data acquisition terminal includes an intelligent terminal device, used to acquire feature data of the actual main object in the roll running space; The server is used to construct a digital twin roll operation space model by using the feature data acquired by the data acquisition terminal through a preset mapping relationship, collect roll operation status trajectory data, and substitute the roll operation status trajectory data into the digital twin roll operation space model to generate roll operation dynamic data, collect coordinate data within the roll operation body, establish a correlation between the coordinate data and the roll operation status trajectory data to obtain the roll operation position data within the entity object, and store the roll operation position data to obtain the roll operation status full life cycle data. Based on the digital twin roll operation space model, the full life cycle data of roll operation and the roll operation dynamic data are processed to obtain virtual space image data.

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