Rolling mill abnormal vibration early warning method, device, equipment and medium

Abstract

The application discloses a rolling mill abnormal vibration early warning method, device, equipment and medium, and belongs to the metallurgical technical field.The method comprises the following steps: obtaining target production data of the rolling mill in each time period, the target production data comprising target vibration acceleration and target process parameters, the target process parameters comprising at least one of target rolling force, target front and rear tension, target rolling speed and target front slip value; determining a production energy value corresponding to the starting moment of each time period according to all the target production data in each time period; the starting moments of different time periods are different, and the production energy value is used for representing the fluctuation degree of the target production data; determining the change rate of the production energy corresponding to each starting moment according to the production energy value corresponding to each starting moment; if the change rate corresponding to any starting moment is greater than a preset rate threshold, early warning of the rolling mill abnormal vibration is performed.The method realizes early warning of the rolling mill vibration, and guarantees the surface quality of the strip.

Description

Technical Field

[0001] This application relates to the field of metallurgical technology, and in particular to a method, device, equipment and medium for early warning of abnormal vibration in rolling mills. Background Technology

[0002] Cold continuous rolling, as a core process in the production of high-precision strip and sheet metal, directly determines the dimensional accuracy and surface quality of the product through its dynamic stability. Under high-speed rolling conditions, the mill system is prone to generating harmful vibrations. These vibrations not only directly form periodic vibration marks on the strip surface, significantly reducing product grade and yield, but also drastically amplify the dynamic load on the system, leading to tension instability and strip breakage accidents, resulting in huge economic losses. Therefore, mill vibration has become a core bottleneck restricting the stable operation of the production line and the improvement of product quality, making effective early warning crucial.

[0003] In the prior art, the vibration signal of the rolling mill is acquired, the vibration signal is preprocessed through a preset random resonance system model and the signal-to-noise ratio of the rolling mill vibration signal is extracted. When the signal-to-noise ratio is greater than the signal-to-noise ratio threshold, the rolling mill vibration is given an early warning and corresponding measures are taken to avoid vibration marks on the strip surface.

[0004] When the signal-to-noise ratio is less than the threshold, no warning will be issued. However, obvious vibration marks will appear on the surface of the strip, so this warning method is not accurate enough. Summary of the Invention

[0005] In view of the above problems, this application is made to provide a method, device, equipment and medium for early warning of abnormal vibration of rolling mill, which can monitor the target production data of rolling mill in various time periods. When the target production data fluctuates rapidly in any time period, an early warning of abnormal vibration of rolling mill is issued, thereby realizing early warning of rolling mill vibration, taking countermeasures in time, and improving the surface quality of strip.

[0006] In a first aspect, this application provides a method for early warning of abnormal vibration in a rolling mill, the method comprising: Obtain target production data of the rolling mill within each time period. The target production data includes target vibration acceleration and target process parameters. The target process parameters include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. Based on all target production data within each time period, determine the production energy value corresponding to the start time of each time period; the start times of different time periods are different, and the production energy value is used to characterize the degree of fluctuation of the target production data; Based on the production energy value corresponding to each starting time, determine the rate of change of production energy corresponding to each starting time; If the rate of change at any starting moment is greater than a preset rate threshold, an early warning of abnormal vibration of the rolling mill will be issued.

[0007] Optionally, before obtaining the target production data of the rolling mill within each preset time period, the method includes: Obtain the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters; The start and end times of each time period are determined based on the first sampling frequency and the second sampling frequency.

[0008] Optionally, determining the start and end times of each time period based on the first sampling frequency and the second sampling frequency includes: If the first sampling frequency is greater than or equal to the second sampling frequency, then the time when the target process parameter is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the second sampling frequency is taken as the duration of each time period. If the first sampling frequency is less than the second sampling frequency, then the moment when the target vibration acceleration is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the first sampling frequency is taken as the duration of each time period.

[0009] Optionally, determining the production energy value corresponding to the start time of each time period based on all target production data within each time period includes: Calculate the sum of squares of all target production data within each time period to obtain the production energy value corresponding to the start time of each time period.

[0010] Optionally, the difference between the start times of any two adjacent time periods in the target sequence is equal, and the target sequence is obtained by arranging all time periods in chronological order according to their corresponding start times.

[0011] Optionally, determining the rate of change of production energy at each starting time based on the production energy value at each starting time includes: Calculate the first difference between the first production energy value corresponding to the first start time and the second production energy value corresponding to the second start time; the first start time is any start time among all start times, and the second start time is the start time preceding the first start time in the target sequence; Calculate the second difference between the first start time and the second start time; Calculate the ratio of the first difference to the second difference to obtain the rate of change of production energy at the second starting time.

[0012] Optionally, obtaining the target production data of the rolling mill within each preset time period includes: Obtain the raw production data of the rolling mill within each preset time period; The raw production data is centrally processed to obtain the target production data of the rolling mill for each time period.

[0013] Secondly, this application provides an early warning device for abnormal vibration of a rolling mill, the device comprising: The acquisition module is used to acquire the target production data of the rolling mill within each time period. The target production data includes target vibration acceleration and target process parameters. The target process parameters include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. The first determining module is used to determine the production energy value corresponding to the start time of each time period based on all target production data within each time period; the start times of different time periods are different, and the production energy value is used to characterize the degree of fluctuation of the target production data; The second determining module is used to determine the rate of change of production energy corresponding to each starting time based on the production energy value corresponding to each starting time. The early warning module is used to issue an early warning for abnormal vibration of the rolling mill if the rate of change corresponding to any starting moment is greater than a preset rate threshold.

[0014] Thirdly, this application provides an electronic device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method as described in the first aspect.

[0015] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing the computer to perform the method described in the first aspect.

[0016] The technical solutions provided in this application embodiment have at least the following technical effects or advantages: This application provides a method, apparatus, equipment, and medium for early warning of abnormal vibration in a rolling mill. It acquires target production data of the rolling mill within each time period, using this data as the basis for analyzing abnormal vibration. Based on all target production data within each time period, it determines the production energy value corresponding to the start time of each time period, which characterizes the fluctuation level of the target production data. Based on the production energy value corresponding to each start time, it determines the rate of change of production energy at each start time, understanding the speed of fluctuation in the target production data. If the rate of change at any start time exceeds a preset rate threshold, an early warning of abnormal vibration in the rolling mill is issued, i.e., an early warning is issued when the fluctuation is rapid. This method can detect abnormal vibration in the rolling mill early and allow for timely implementation of corresponding measures to ensure the surface quality of the strip. The target production data includes target vibration acceleration and target process parameters, which include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. The start times differ for different time periods.

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart of an early warning method for abnormal vibration of a rolling mill provided in an embodiment of this application; Figure 2 This is a structural block diagram of an early warning device for abnormal vibration of a rolling mill provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the embodiments of this disclosure and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. Unless otherwise specified, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0020] Figure 1 This is a flowchart of an early warning method for abnormal vibration of a rolling mill provided in an embodiment of this application, as shown below. Figure 1As shown, the method includes: Step S110: Obtain the target production data of the rolling mill within each time period.

[0021] The target production data includes target vibration acceleration and target process parameters. The target process parameters include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value.

[0022] In this embodiment, accelerometers deployed at key locations such as the rolling mill stand and bearing housing convert mechanical vibration into analog voltage signals. These analog voltage signals are transmitted via cables to a data acquisition module, where they are converted into digital signals. These digital signals are then transmitted to a computer via a switch for display and storage. The generated digital signals are uploaded to an industrial control computer via a network switch for storage, yielding the original vibration acceleration. This enables real-time visualization and massive historical data storage. Original process parameters are collected from the L1 level of basic automation data, providing measured data for control system parameter debugging and fault diagnosis. These original process parameters (such as the original rolling speed) are transmitted to the vibration monitoring system via a PLC (Programmable Logic Controller) cabinet.

[0023] Next, the raw production data, such as the original vibration acceleration and raw process parameters, are preprocessed to obtain target production data, such as target vibration acceleration and target process parameters. The number of time periods can be set according to actual conditions, with the latest time period ending at the current time, ensuring that each newly acquired production data point can be incorporated into the analysis of abnormal mill vibration.

[0024] Step S120: Determine the production energy value corresponding to the start time of each time period based on all target production data within each time period.

[0025] The start times for different time periods are different, and the production energy value is used to characterize the degree of fluctuation in the target production data.

[0026] In this embodiment of the application, the target production data is analyzed according to time periods. The fluctuation of production data within each time period is analyzed and characterized by production energy value. The production energy value corresponding to the start time of each time period is obtained, that is, one start time corresponds to one production energy value.

[0027] Step S130: Determine the rate of change of production energy at each starting moment based on the production energy value at each starting moment.

[0028] In this embodiment of the application, the rate of change of production energy at each starting time is determined based on the production energy value at each starting time, and the rate of change is used to characterize the speed of fluctuation of the target production data.

[0029] Step S140: If the rate of change at any starting moment is greater than the preset rate threshold, then an early warning of abnormal vibration of the rolling mill is issued.

[0030] In this embodiment, if the rate of change at any starting moment exceeds a preset rate threshold, it indicates that the target production data is fluctuating rapidly, and the mill may be about to vibrate or is in the early stages of vibration. Therefore, an early warning of abnormal mill vibration is issued so that mill operators can take appropriate measures to reduce vibration and ensure the surface quality of the strip. This method issues an early warning of abnormal mill vibration when either the target vibration acceleration or the target process parameter fluctuates rapidly. Furthermore, if the rate of change at any starting moment within a given time period exceeds the rate threshold, it is considered that the target vibration acceleration or the target process parameter is fluctuating rapidly, allowing for early detection of potential abnormal vibrations in the mill.

[0031] Furthermore, the causes of abnormal rolling vibrations can be analyzed based on the starting time when the rate of change exceeds a preset rate threshold and the starting time when the rate of change recovers to less than or equal to the rate threshold.

[0032] Optionally, before step S110, the method further includes: The first step is to obtain the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters.

[0033] In the embodiments of this application, the production data of the rolling mill are of various types and have different sampling frequencies. Generally, the sampling frequency of process parameters is much lower than that of vibration signals. Therefore, the difference between the sampling frequencies of the target vibration acceleration and the target process parameters can be understood by using the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters.

[0034] The second step is to determine the start and end times of each time period based on the first and second sampling frequencies.

[0035] In this embodiment, the time period in which the time series of the target vibration acceleration and the target process parameters can be matched can be determined based on the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters, which facilitates the subsequent analysis of the degree of fluctuation.

[0036] Optional, the second step includes: If the first sampling frequency is greater than or equal to the second sampling frequency, then the time when the target process parameter is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the second sampling frequency is taken as the duration of each time period. If the first sampling frequency is less than the second sampling frequency, then the moment when the target vibration acceleration is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the first sampling frequency is taken as the duration of each time period.

[0037] In this embodiment, the start time of each time period can be determined based on the smaller of the first sampling frequency and the second sampling frequency. Specifically, if the smaller is the second sampling frequency, the time at which the target process parameter is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the second sampling frequency is taken as the duration of each time period; if the smaller is the first sampling frequency, the time at which the target vibration acceleration is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the first sampling frequency is taken as the duration of each time period.

[0038] For example, the first sampling frequency is 1024 times / second, the second sampling frequency is 20 times / second, and the target process parameters are collected every 50ms starting from 0ms. The start time of each time period can be 50ms, 100ms, 150ms, 200ms, etc. The unit of time in the sampling frequency is seconds, so the duration of the time period is 1 second. That is, the first time period is 0-1000ms, the second time period is 50-1050ms, the third time period is 100-1100ms, the fourth time period is 150-1150ms, etc. There are 20 target process parameters and 1024 target vibration accelerations in each time period.

[0039] Optionally, step S110 includes: Obtain the raw production data of the rolling mill for each preset time period; perform centralized processing on the raw production data to obtain the target production data of the rolling mill for each time period.

[0040] In this embodiment of the application, the preprocessing can be centralized processing, that is, the original production data is centrally processed to eliminate system error interference and obtain the target production data of the rolling mill in each time period.

[0041] In this embodiment, since the vibration acceleration and process parameters are acquired from independent acquisition systems, they differ in sampling frequency, data format, and time accuracy, constituting a typical heterogeneous data stream. To ensure the accuracy of subsequent correlation analysis, the acquired data is aligned to ensure that data from different sources correspond to the same rolling event.

[0042] Specifically, the target production data can be calculated using formulas (1) and (2). Formula (1) is as follows:

[0043] In the formula, The mean, For the i-th original production data, This represents the number of original production data sets. Formula (2) is as follows:

[0044] In the formula, Generate data for the target.

[0045] If we calculate the target vibration acceleration This is the original vibration acceleration; if calculating the target process parameters, These are the original process parameters.

[0046] Optionally, step S120 includes: Calculate the sum of squares of all target production data within each time period to obtain the production energy value corresponding to the start time of each time period.

[0047] In this embodiment of the application, the production energy value corresponding to the start time of each time period can be calculated according to formula (3), which is as follows:

[0048] In the formula, Let be the production energy value corresponding to the start time of the k-th time period. Let k be the number of target production data points within the k-th time period. Generate data for the i-th target within the k-th time period.

[0049] For example, the first sampling frequency is 1024 times / second, and the second sampling frequency is 20 times / second. If the target production data is the target vibration acceleration, then the production energy value is the vibration acceleration energy value. The vibration acceleration energy value is calculated using formula (4), which is as follows:

[0050] In the formula, This represents the vibration acceleration energy value corresponding to the k-th time period. It is 1024. Let S be the vibration acceleration of the j-th target (the vibration acceleration of the first target is the vibration acceleration of the first target collected in the earliest time period, and so on to find the j-th target); S is 51, and k is the sequence number of the time period.

[0051] The start time of each time period can be calculated according to formula (5), which is as follows:

[0052] In the formula, This represents the start time of the k-th time interval corresponding to the target vibration acceleration; The sampling period for the target vibration acceleration (the reciprocal of the first sampling frequency).

[0053] If the target production data is the target process parameter, then the production energy value is the process parameter energy value. The process parameter energy value is calculated using formula (6), which is as follows:

[0054] In the formula, The energy value of the process parameter corresponding to the k-th time period. It is 20. The j-th target process parameter (the first target process parameter is the first target process parameter collected in the earliest time period, and so on to find the j-th one).

[0055] The start time of each time period can be calculated according to formula (7), which is as follows:

[0056] In the formula, This represents the start time of the k-th time period corresponding to the target process parameters; The sampling period for the target process parameters (the reciprocal of the second sampling frequency).

[0057] Optionally, the difference between the start times of any two adjacent time periods in the target sequence is equal, and the target sequence is obtained by arranging all time periods in chronological order according to their corresponding start times.

[0058] This can be understood as all time periods being arranged in chronological order, with the earlier the start time of a time period, the earlier it appears in the sequence. For example, in the target sequence, the first time period is 0-1000ms, the second is 50-1050ms, the third is 100-1100ms, and the fourth is 150-1150ms.

[0059] In this context, the difference between the start times of any two adjacent time periods in the target sequence is equal, making the time periods highly regular. This enables streaming processing of production time series data, reduces processing complexity, and improves the accuracy of processing results.

[0060] Optionally, step S130 includes: Calculate the first difference between the first production energy value corresponding to the first starting time and the second production energy value corresponding to the second starting time; the first starting time is any starting time among all starting times, and the second starting time is the starting time preceding the first starting time in the target sequence; calculate the second difference between the first starting time and the second starting time; calculate the ratio of the first difference to the second difference to obtain the rate of change of production energy corresponding to the second starting time.

[0061] In this embodiment of the application, the rate of change can be calculated according to formula (8), which is as follows:

[0062] In the formula, Let be the rate of change of production energy corresponding to the start time of the k-th time period. This represents the start time of the k-th time interval.

[0063] If the rate of change of vibration acceleration energy is calculated, then E in formula (8) is the vibration acceleration energy value; if the rate of change of process parameter energy is calculated, then E in formula (8) is the process parameter energy value.

[0064] Based on the same concept, embodiments of the present invention also provide an early warning device for abnormal vibration of a rolling mill. Figure 2 This is a structural block diagram of an early warning device for abnormal vibration of a rolling mill provided in an embodiment of this application, as shown below. Figure 2 As shown, the device 200 includes an acquisition module 201, a first determination module 202, a second determination module 203, and an early warning module 204.

[0065] The acquisition module 201 is used to acquire the target production data of the rolling mill in each time period. The target production data includes the target vibration acceleration and the target process parameters. The target process parameters include at least one of the target rolling force, the target front and rear tension, the target rolling speed and the target forward slip value. The first determining module 202 is used to determine the production energy value corresponding to the start time of each time period based on all target production data within each time period; the start times of different time periods are different, and the production energy value is used to characterize the degree of fluctuation of the target production data; The second determining module 203 is used to determine the rate of change of production energy at each starting moment based on the production energy value at each starting moment. The early warning module 204 is used to issue an early warning of abnormal vibration of the rolling mill if the rate of change corresponding to any starting moment is greater than a preset rate threshold.

[0066] Optionally, the device 200 also includes: The acquisition unit is used to acquire the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters; The determining unit is used to determine the start and end times of each time period based on the first sampling frequency and the second sampling frequency.

[0067] Optionally, the determining unit is also used for: If the first sampling frequency is greater than or equal to the second sampling frequency, then the time when the target process parameter is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the second sampling frequency is taken as the duration of each time period. If the first sampling frequency is less than the second sampling frequency, then the moment when the target vibration acceleration is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the first sampling frequency is taken as the duration of each time period.

[0068] Optionally, the first determining module 202 is also used for: Calculate the sum of squares of all target production data within each time period to obtain the production energy value corresponding to the start time of each time period.

[0069] Optionally, the difference between the start times of any two adjacent time periods in the target sequence is equal, and the target sequence is obtained by arranging all time periods in chronological order according to their corresponding start times.

[0070] Optionally, the second determining module 203 is also used for: Calculate the first difference between the first production energy value corresponding to the first start time and the second production energy value corresponding to the second start time; the first start time is any start time among all start times, and the second start time is the start time preceding the first start time in the target sequence; Calculate the second difference between the first start time and the second start time; Calculate the ratio of the first difference to the second difference to obtain the rate of change of production energy at the second starting moment.

[0071] Optionally, the acquisition module 201 is also used for: Obtain the raw production data of the rolling mill for each preset time period; The raw production data is centrally processed to obtain the target production data of the rolling mill for each time period.

[0072] It is understood that the device provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0073] This invention also provides an electronic device that may include a processor and a memory, wherein the processor and the memory may be interconnected via a bus or other means.

[0074] The processor can be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application, or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or other chips, or combinations of the above types of chips.

[0075] Memory may include mass storage for data or instructions. For example, and not limitingly, memory may include hard disk drives (HDDs), floppy disk drives, flash memory, optical disks, magneto-optical disks, magnetic tape, or Universal Serial Bus (USB) drives, or combinations of two or more of these. Where appropriate, memory may include removable or non-removable (or fixed) media. Where appropriate, memory may be internal or external to an electronic device. In a particular embodiment, memory may be non-volatile solid-state memory.

[0076] In one instance, the memory may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0077] The processor reads and executes computer program instructions stored in the memory to implement any of the early warning methods for abnormal vibration of the rolling mill in the above embodiments.

[0078] In one example, the electronic device may further include a communication interface and a bus. The processor, memory, and communication interface are connected via the bus to communicate with each other. The communication interface is primarily used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of this application. Where appropriate, the bus may include one or more buses.

[0079] Furthermore, in conjunction with the early warning method for abnormal mill vibration in the above embodiments, this invention can be implemented using a computer-readable storage medium. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the early warning methods for abnormal mill vibration in the above embodiments.

[0080] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium can be read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0081] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages: This application provides a method, apparatus, equipment, and medium for early warning of abnormal vibration in a rolling mill. It acquires target production data of the rolling mill within each time period, using this data as the basis for analyzing abnormal vibration. Based on all target production data within each time period, it determines the production energy value corresponding to the start time of each time period, which characterizes the fluctuation level of the target production data. Based on the production energy value corresponding to each start time, it determines the rate of change of production energy at each start time, understanding the speed of fluctuation in the target production data. If the rate of change at any start time exceeds a preset rate threshold, an early warning of abnormal vibration in the rolling mill is issued, i.e., an early warning is issued when the fluctuation is rapid. This method can detect abnormal vibration in the rolling mill early and allow for timely implementation of corresponding measures to ensure the surface quality of the strip. The target production data includes target vibration acceleration and target process parameters, which include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. The start times differ for different time periods.

[0082] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0083] Similarly, it should be understood that, in order to simplify this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0084] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. A method for early warning of abnormal vibration in a rolling mill, characterized in that, The method includes: Obtain target production data of the rolling mill within each time period. The target production data includes target vibration acceleration and target process parameters. The target process parameters include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. Based on all target production data within each time period, determine the production energy value corresponding to the start time of each time period; the start times of different time periods are different, and the production energy value is used to characterize the degree of fluctuation of the target production data; Based on the production energy value corresponding to each starting time, determine the rate of change of production energy corresponding to each starting time; If the rate of change at any starting moment is greater than a preset rate threshold, an early warning of abnormal vibration of the rolling mill will be issued.

2. The early warning method for abnormal vibration of a rolling mill according to claim 1, characterized in that, Before acquiring the target production data of the rolling mill within each preset time period, the method includes: Obtain the first sampling frequency of the target vibration acceleration and the second sampling frequency of the target process parameters; The start and end times of each time period are determined based on the first sampling frequency and the second sampling frequency.

3. The early warning method for abnormal vibration of a rolling mill according to claim 2, characterized in that, The step of determining the start and end times of each time period based on the first sampling frequency and the second sampling frequency includes: If the first sampling frequency is greater than or equal to the second sampling frequency, then the time when the target process parameter is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the second sampling frequency is taken as the duration of each time period. If the first sampling frequency is less than the second sampling frequency, then the moment when the target vibration acceleration is collected each time is taken as the start time of each time period, and the unit time corresponding to the unit of the first sampling frequency is taken as the duration of each time period.

4. The early warning method for abnormal vibration of a rolling mill according to claim 1, characterized in that, The step of determining the production energy value corresponding to the start time of each time period based on all target production data within each time period includes: Calculate the sum of squares of all target production data within each time period to obtain the production energy value corresponding to the start time of each time period.

5. The early warning method for abnormal vibration of a rolling mill according to claim 1, characterized in that, The difference between the start times of any two adjacent time periods in the target sequence is equal. The target sequence is obtained by arranging all time periods in chronological order according to their corresponding start times.

6. The early warning method for abnormal vibration of a rolling mill according to claim 5, characterized in that, The step of determining the rate of change of production energy at each starting time based on the production energy value at each starting time includes: Calculate the first difference between the first production energy value corresponding to the first start time and the second production energy value corresponding to the second start time; the first start time is any start time among all start times, and the second start time is the start time preceding the first start time in the target sequence; Calculate the second difference between the first start time and the second start time; Calculate the ratio of the first difference to the second difference to obtain the rate of change of production energy at the second starting time.

7. The early warning method for abnormal vibration of a rolling mill according to claim 1, characterized in that, The acquisition of target production data of the rolling mill within each preset time period includes: Obtain the raw production data of the rolling mill within each preset time period; The raw production data is centrally processed to obtain the target production data of the rolling mill for each time period.

8. An early warning device for abnormal vibration of a rolling mill, characterized in that, The device includes: The acquisition module is used to acquire the target production data of the rolling mill within each time period. The target production data includes target vibration acceleration and target process parameters. The target process parameters include at least one of target rolling force, target front and rear tension, target rolling speed, and target forward slip value. The first determining module is used to determine the production energy value corresponding to the start time of each time period based on all target production data within each time period; the start times of different time periods are different, and the production energy value is used to characterize the degree of fluctuation of the target production data; The second determining module is used to determine the rate of change of production energy corresponding to each starting time based on the production energy value corresponding to each starting time. The early warning module is used to issue an early warning for abnormal vibration of the rolling mill if the rate of change corresponding to any starting moment is greater than a preset rate threshold.

9. An electronic device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1-7.

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