A hot rolling production line process data processing method and system, and a computer device

Abstract

The application provides a hot rolling production line process data processing method and system and computer equipment, comprising: defining data signals collected by sensors according to sensor grouping results, forming a data signal set, and dividing the data signal set into tracking signals and collection target signals; determining the time when the head and tail of the plate strip pass through a preset position by using the biting steel signal in the tracking signal, and forming a time window; extracting an identity code data segment, a plate strip number signal data segment and a roll speed signal data segment according to the time window and the storage position of the collection target signal; selecting a plate strip number, and associating the plate strip number with the identity code data segment, the plate strip number signal data segment and the roll speed signal data segment to obtain rolling process data corresponding to the plate strip number. The application can establish the association between the plate strip rolling process data and the plate strip number, can process and store the hot rolling production line process data, and can timely push the data to an external system and other third-party applications to realize data sharing.

Description

Technical Field

[0001] This invention relates to the field of hot strip rolling technology, and in particular to a method and system for processing process data in a hot rolling production line, as well as computer equipment. Background Technology

[0002] The hot-rolled strip production line is equipped with numerous sensors (temperature, width, flatness, etc.) at different processes and areas. These sensors typically collect data every 10 milliseconds, resulting in a high data acquisition frequency. The collected data is stored in a time-series database. However, currently, it's impossible to determine from the collected data which time range of the sensor data collected along the strip's length during the rolling process falls within the time-series data. In other words, it's impossible to directly establish a correlation between the time-series data segment and the strip number. This further hinders the generation of evaluation metrics (hit rate, mean, variance, etc.) for strip rolling quality based on the strip rolling process data. Furthermore, how to enable external intelligent application systems to conveniently and quickly utilize this data obtained through tracking, acquisition, and processing is also a pressing issue that needs to be addressed. Summary of the Invention

[0003] This invention provides a method and system for processing process data in a hot rolling production line, as well as a computer device, to solve or alleviate the technical problems described above.

[0004] This invention provides a method for processing process data in a hot rolling production line, comprising the following steps: The sensors installed on the hot rolling production line of strip and sheet are grouped, including grouping sensors with the same installation position and measurement position together; Based on the sensor grouping results, all data signals collected by each group of sensors are defined to form a data signal set, and the data signals in the data signal set are divided into tracking signals and target signals. The time taken for the strip head and strip tail to pass through a preset position is determined using the bite signal in the tracking signal, and the time taken for the strip head to pass through the preset position is taken as the start time and the time taken for the strip tail to pass through the preset position is taken as the end time; wherein, the time taken for the strip head and strip tail to pass through the preset position is determined according to the value of the bite signal; A time window is formed based on the start time and the end time, and the identification code data segment, strip number signal data segment, and roll speed signal data segment are extracted from the time series database according to the time window and the storage location of the target signal in the time series database. A random value is selected from the strip number signal data segment as the strip number, and the strip number is associated with the identification code data segment, the strip number signal data segment and the roll speed signal data segment to obtain the rolling process data corresponding to the strip number.

[0005] In one embodiment of the present invention, the method further includes: Obtaining the first step in the hot rolling process of strip and plate The measurement data includes the roll speed and measurement time, and is based on the first measurement. The roll speed and measurement time of each measurement data point are used to calculate the strip's speed at the [number]th [time / item]. The strip length corresponding to each measurement data point; among which... It is a positive integer; According to the strip in the first Based on the strip length corresponding to each measurement data point, the number of sensor measurements within the time window, and the order of the measurement data, calculate the strip length direction of the [number of measurements]. The distance between the location of each measurement data point and the head of the conveyor belt is denoted as . ; In the direction of the strip length The measurement data at the location is used as the first in the time direction of the plate and strip. Measurement data.

[0006] In one embodiment of the present invention, the method further includes: According to the number of sensor measurements within the time window, the data signals in the data signal set are sampled at intervals to reduce the frequency of the data signal set; And / or, based on the set of data signals after frequency reduction, the rolling quality of hot-rolled strip is evaluated using preset feature values; wherein, the preset feature values ​​include at least one of mean, hit rate and variance.

[0007] In one embodiment of the present invention, the method further includes: Data is stored according to a preset document structure, which includes at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment. Furthermore, a unified relational database table schema is adopted to store the feature values ​​calculated through data processing rules.

[0008] In one embodiment of the present invention, the method further includes: Receive and parse data subscription tasks to obtain the corresponding list of subscribed data; wherein, the data subscription task is generated based on the data items required by the data subscription activity initiated by the external system. According to the subscribed data list, the corresponding data is continuously pushed to a pre-generated or real-time generated message queue so that the external system can receive the data through the message queue.

[0009] In one embodiment of the present invention, the process of determining the time for the strip head and the strip tail to pass through a preset position based on the value of the bite signal includes: When the value of the steel bite signal changes from the first value to the second value, the strip head is marked as having passed the preset position, and the time at this moment is recorded as the time when the strip head has passed the preset position, which is also called the start time. When the value of the steel bite signal changes from the second value to the first value, the tail of the strip is marked as having passed the preset position, and the time at this moment is recorded as the time when the tail of the strip passes the preset position, which is also called the end time.

[0010] In one embodiment of the present invention, according to the first The roll speed and measurement time of each measurement data point are used to calculate the strip's speed at the [number]th [time / item]. The strip lengths corresponding to the measured data are:

[0011] In the formula, Indicates the length of the strip. Indicates the first The roll speed of the measured data This indicates the number of sensor measurements within the time window. Indicates the first One measurement data, Indicates the first One measurement data; And, calculate the length direction of the strip. The distance between the location of each measurement data point and the head of the conveyor belt is:

[0012] In the formula, Indicates the length direction of the strip. The location of each measurement data point is the distance from the head of the strip.

[0013] The present invention also provides a process data processing system for a hot rolling production line, the system comprising: The signal definition module is used to group the sensors installed on the hot rolling production line of strip and sheet, including grouping sensors with the same installation position and measurement position into one group; and defining all data signals collected by each group of sensors according to the sensor grouping results to form a data signal set, and dividing the data signals in the data signal set into tracking signals and acquisition target signals; The data tracking module is used to determine the time when the strip head and strip tail pass through a preset position using the bite signal in the tracking signal, and to take the time when the strip head passes through the preset position as the start time and the time when the strip tail passes through the preset position as the end time; wherein, the time when the strip head and strip tail pass through the preset position is determined according to the value of the bite signal; The data acquisition module is used to form a time window based on the start time and the end time, and extract the identification code data segment, strip number signal data segment, and roll speed signal data segment from the time series database according to the time window and the storage location of the target signal in the time series database; and randomly select an acquired value from the strip number signal data segment as the strip number, and associate the strip number with the identification code data segment, the strip number signal data segment, and the roll speed signal data segment to obtain the rolling process data corresponding to the strip number.

[0014] In one embodiment of the present invention, the system further includes: The data processing module is used to evaluate the rolling quality of hot-rolled strip using preset feature values ​​based on the set of down-frequency data signals; wherein the preset feature values ​​include at least one of mean, hit rate and variance; The data storage module is used to store data according to a preset document structure, which includes at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment; and, using a unified relational database table schema, stores feature values ​​calculated by data processing rules. The data sharing module is used to receive and parse data subscription tasks to obtain the corresponding subscription data list; wherein, the data subscription task is generated based on the data items required by the data subscription activity initiated by the external system; and, according to the subscription data list, the corresponding data is continuously pushed to a pre-generated or real-time generated message queue so that the external system can receive the data through the message queue.

[0015] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the hot rolling production line process data processing method described in any one of the above.

[0016] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the hot rolling production line process data processing method described in any one of the above.

[0017] The beneficial effects of this invention are as follows: This invention proposes a data processing method and system for hot rolling production lines, along with a computer device. This involves grouping sensors installed on the hot rolling production line, including grouping sensors with the same installation and measurement positions into one group. Then, according to the sensor grouping results, all data signals collected by each group of sensors are defined to form a data signal set. The data signals in the data signal set are further divided into tracking signals and target signals. The bite signal in the tracking signal is then used to determine the time it takes for the strip head and tail to pass through a preset position. The time when the strip head passes through the preset position is used as the start time, and the time when the strip tail passes through the preset position is used as the start time. The invention uses the time at a preset position as the end time; the time for the strip head and tail to pass through the preset position is determined based on the value of the bite signal; then, a time window is formed based on the start and end times, and according to the time window and the storage location of the target signal in the time-series database, the identification code data segment, strip number signal data segment, and roll speed signal data segment are extracted from the time-series database; finally, a sampled value is randomly selected from the strip number signal data segment as the strip number, and the strip number is associated with the identification code data segment, strip number signal data segment, and roll speed signal data segment to obtain the rolling process data corresponding to the strip number. Therefore, this invention can establish the association between strip rolling process data and strip number, and can also process hot rolling production line process data, store the calculation results according to a unified standard format, and promptly push data to external systems and other third-party applications to achieve data sharing. Thus, this invention can support the continuous emergence of new demands in steel rolling digital analysis applications, significantly improve the end-to-end quality traceability and defect analysis efficiency, and play a significant supporting role in hot-rolled product quality, equipment diagnosis, and lean operation management. Furthermore, this invention can provide a solid data foundation for steel companies to transform into intelligent manufacturing, helping them improve product quality and reduce scrap rates, thus possessing extremely high economic value. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0019] In the attached diagram: Figure 1 This is a schematic diagram illustrating an exemplary system architecture for applying the technical solutions in one or more embodiments of the present invention; Figure 2 This is a flowchart illustrating a hot rolling production line process data processing method according to an embodiment of the present invention. Figure 3 This is a schematic diagram of a document structure provided in one embodiment of the present invention; Figure 4 This is a schematic diagram of a data sharing process provided in one embodiment of the present invention; Figure 5 This is a functional framework diagram of a hot rolling production line process data processing system provided in one embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of a computer device suitable for implementing one or more embodiments of the present invention. Detailed Implementation

[0020] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0022] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0023] Figure 1 A schematic diagram of an exemplary system architecture that can apply the technical solutions of one or more embodiments of the present invention is shown. Figure 1 As shown, the system architecture 100 may include terminal device 110, network 120, and server 130. Terminal device 110 may include various electronic devices such as smartphones, tablets, laptops, and desktop computers. Server 130 may be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. Network 120 may be a communication medium of various connection types capable of providing a communication link between terminal device 110 and server 130, such as a wired communication link or a wireless communication link.

[0024] Depending on the implementation requirements, the system architecture in this embodiment of the invention can have any number of terminal devices, networks, and servers. For example, server 130 can be a server group composed of multiple server devices. Furthermore, the technical solutions provided in this embodiment of the invention can be applied to terminal device 110, or to server 130, or can be implemented jointly by terminal device 110 and server 130; this invention does not impose any special limitations on these applications.

[0025] In one embodiment of the present invention, the terminal device 110 or server 130 can group the sensors installed on the hot rolling production line of strip and plate, including grouping sensors with the same installation position and measurement position into one group; then defining all data signals collected by each group of sensors according to the sensor grouping result to form a data signal set, and dividing the data signals in the data signal set into tracking signals and acquisition target signals; then using the bite signal in the tracking signal to determine the time when the strip head and strip tail pass through the preset position, and taking the time when the strip head passes through the preset position as the start time and the time when the strip tail passes through the preset position as the start time. The set time is used as the end time; the time for the strip head and tail to pass through the preset position is determined based on the value of the bite signal; then, a time window is formed based on the start and end times, and according to the time window and the storage location of the target signal in the time sequence database, the identification code data segment, strip number signal data segment, and roll speed signal data segment are extracted from the time sequence database; finally, a sampled value is randomly selected from the strip number signal data segment as the strip number, and the strip number is associated with the identification code data segment, strip number signal data segment, and roll speed signal data segment to obtain the rolling process data corresponding to the strip number. Using terminal device 110 or server 130 to execute the hot rolling production line process data processing method, the association between strip rolling process data and strip number can be established. Furthermore, the hot rolling production line process data can be processed, the calculation results can be stored in a unified standard format, and data can be promptly pushed to external systems and other third-party applications to achieve data sharing. Digital analysis applications for steel rolling, capable of supporting continuously evolving new demands, significantly improve the ability to trace quality throughout the entire process and the efficiency of defect analysis. They can play a significant supporting role in hot-rolled product quality, equipment diagnosis, and lean operational management. Furthermore, they can provide a solid data foundation for steel companies' transformation towards intelligent manufacturing, helping them improve product quality and reduce scrap rates, thus possessing extremely high economic value.

[0026] The above section introduced an exemplary system architecture for applying the technical solution of this invention. Next, we will continue to introduce the process data processing method for hot rolling production lines of this invention.

[0027] Figure 2A flowchart illustrating a data processing method for a hot rolling production line is shown. Specifically, in an exemplary embodiment, as follows... Figure 2 As shown, this embodiment provides a method for processing process data in a hot rolling production line, including the following steps: S210, grouping the sensors installed on the hot strip rolling production line, including grouping sensors with the same installation and measurement positions together. In some examples, these sensors on the hot strip rolling production line can be grouped according to the grouping principle that sensors with the same installation and measurement positions on the hot strip rolling production line are grouped together.

[0028] S220, according to the sensor grouping results, defines all data signals collected by each group of sensors to form a data signal set, and divides the data signals in the data signal set into tracking signals and target signals; S230, the time for the head and tail of the strip to pass through the preset position is determined by the bite signal in the tracking signal, and the time for the head of the strip to pass through the preset position is taken as the start time and the time for the tail of the strip to pass through the preset position is taken as the end time; wherein, the time for the head and tail of the strip to pass through the preset position is determined according to the value of the bite signal. S240: Based on the start time and end time, a time window is formed, and according to the time window and the storage location of the target signal in the time sequence database, the identification code data segment, the strip number signal data segment and the roll speed signal data segment are extracted from the time sequence database. S250: Randomly select a value from the strip number signal data segment as the strip number, and associate the strip number with the identification code data segment, the strip number signal data segment and the roll speed signal data segment to obtain the rolling process data corresponding to the strip number.

[0029] In some exemplary embodiments, the hot rolling production line process data processing method may further include: Obtaining the first step in the hot rolling process of strip and plate The measurement data includes the roll speed and measurement time, and is based on the first measurement. The roll speed and measurement time of each measurement data point are used to calculate the strip's speed at the [number]th [time / item]. The strip lengths corresponding to the measured data are: In the formula, Indicates the length of the strip. Indicates the first The roll speed of the measured data Indicates the number of sensor measurements within the time window. Indicates the first One measurement data, Indicates the first One measurement data; ,and It is a positive integer; According to the strip in the The strip length corresponding to each measurement data point, the number of sensor measurements within the time window, and the order of the measurement data are used to calculate the strip length direction of the [number of measurements]. The distance between the location of each measurement data point and the head of the conveyor belt is: In the formula, Indicates the length direction of the strip. The location of each measurement data point is the distance from the head of the strip.

[0030] In the direction of the strip length The measurement data at the location is used as the first in the time direction of the plate and strip. Measurement data.

[0031] In some exemplary embodiments, the hot rolling production line process data processing method may further include: sampling the data signals in the data signal set at intervals according to the number of sensor measurements within a time window, so as to reduce the frequency of the data signal set. Specifically, in some examples, if the sensors on the hot rolling production line collect data once every 10 milliseconds, the corresponding data frequency is very high, that is, the amount of data in the strip rolling process will be very large, which will put a certain pressure on data storage and application reading and rendering of charts. Therefore, it is particularly important to reduce the data frequency while ensuring minimal loss of data features. Therefore, a direct downsampling algorithm can be used here to reduce the data frequency in order to meet the data requirements. The direct downsampling algorithm is described as follows: Given the original data Every Sampling once per point: ; It is a positive integer.

[0032] In some exemplary embodiments, the hot-rolling production line process data processing method may further include: evaluating the hot-rolled strip rolling quality using preset feature values ​​based on the set of frequency-reduced data signals; wherein the preset feature values ​​include at least one of mean, hit rate, and variance. In some examples, the hot-rolled strip rolling quality can be evaluated using feature values ​​such as mean, hit rate, and variance as evaluation indicators. Specifically, after obtaining all data signals collected by the sensors, the collected data signals can be processed to calculate feature values ​​from the frequency-reduced process data. The data processing input parameters include data segments and output feature value names. The data segment refers to the data of how many meters the head and tail ends of the strip are removed in the strip length direction; the remaining strip body data segment is used for calculation. The output feature values ​​include hit rate, mean, and variance, and the algorithm implementation is consistent with the mathematical definitions.

[0033] In some exemplary embodiments, the hot rolling production line process data processing method may further include: storing data according to a preset document structure, the preset document structure including at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment; and storing feature values ​​calculated by data processing rules using a unified relational database table schema. In some examples, after binding the strip number to the timing data segment and reducing the frequency, the process data can be stored based on the document-oriented database MongoDB, with a document structure such as... Figure 3 As shown. In Figure 3 In this table, `coilNo` represents the strip number; `memberId` represents the signal number, a unique identifier; `passNo` represents the rolling pass number; `name` represents the signal name; `unit` represents the mathematical unit; `rangeTimeStart` represents the data acquisition start time; `rangeTimeEnd` represents the data acquisition end time; `xloc` is an array type representing the position coordinates of the data along its length; and `yValues` is an array type representing the process data segment. In some examples, feature values ​​calculated through data processing rules can be stored using a unified relational database table schema, as shown in Table 1 below.

[0034] Table 1 Feature Value Storage Table Pattern Serial Number Parameter name Parameter Description type 1 coil_id Steel coil number varchar(20) 2 var_id Feature ID int(11) 3 var_name Feature name varchar(50) 4 var_type Eigenvalue data type varchar(10) 5 value_int int data storage location int(11) 6 value_double double-type data storage location double 7 value_str string data storage location varchar(50) In some exemplary embodiments, the hot rolling production line process data processing method may further include: receiving and parsing a data subscription task to obtain a corresponding subscription data list; wherein the data subscription task is generated based on the data items required by a data subscription activity initiated by an external system; and continuously pushing the corresponding data to a pre-generated or real-time generated message queue according to the subscription data list, so that the external system can receive the data through the message queue. In some examples, for data that has been paid for, in addition to persistent storage in a database, it can also be precisely shared with an external intelligent application system. Specifically, the data sharing process based on the RocketMQ message queue system is as follows: Figure 4 As shown, in Figure 4 In this process, the external system can accurately receive process data associated with the board strip number and feature values ​​generated based on the process data as input data for application functions.

[0035] In some exemplary embodiments, the process of determining the time for the strip head and strip tail to pass through a preset position based on the value of the bite signal includes: when the value of the bite signal changes from a first value to a second value, marking the strip head as having passed through the preset position, and recording this moment as the start time; when the value of the bite signal changes from the second value to the first value, marking the strip tail as having passed through the preset position, and recording this moment as the end time. In some examples, when the bite signal... When the value changes from 0 to 1, it indicates that the conveyor belt head has passed this position, and the time at this moment is recorded as the start time. When the steel bite signal When the value changes from 1 to 0, it indicates that the tail of the conveyor belt has passed this position; the time at this moment is recorded as the end time. .

[0036] In other embodiments of this application, a method for processing process data in a hot rolling production line is provided. First, the sensors are grouped according to the principle that sensors with the same installation and measurement positions on the production line are grouped together. Then, all data signals that can be collected by the sensors within each group are defined to form a data signal set. Among them, the data signal set Each signal includes a unique signal ID, signal name, data type (integer, floating-point), mathematical unit, and storage location in the time-series database (the location is determined by a combination of module number and channel number, denoted as ). ) and other attributes. Data signals in a data signal set can be divided into tracking signals (denoted as...) , (positive integer, representing the sequence number of the tracking signal definition) and the acquired target signal (denoted as...) The tracking signal is used for data tracking and data acquisition, and includes the roll speed signal. , board strip number signal steel bite signal The target signal is the data that needs to be collected, processed, and pushed. The principles of data tracking, collection, processing, storage, and pushing are consistent within each data signal set. Specifically, we will use a data signal set as an example for explanation.

[0037] Step 1: Data Tracking. Utilize the bite signal from the tracking signal. Determine the start and end times of the strip head and tail passing through this position, when the steel bite signal is received. When the value changes from 0 to 1, it indicates that the conveyor belt head has passed this position; the time at this moment is recorded as the start time. When the steel bite signal When the value changes from 1 to 0, it indicates that the tail of the conveyor belt has passed this position; the time at this moment is recorded as the end time. Then the rolling process data of the strip at this position is the time window. The data collected by the internal sensor has a time accuracy of milliseconds. ).

[0038] Step 2: Data Acquisition. Based on the obtained time window. and initial acquisition target signal Extract identification code data segments from the time-series database. n is the time window The number of times the sensor measures. Simultaneously, extract the defined strip number signal data segment from the tracking signal. = and roll speed signal data segment Since the strip number of a steel piece remains unchanged during the rolling process, the data segment is taken. Any one of the collected values ​​is used as the board strip number, denoted as At this moment, the strip number... With rolling process data segment , , The association has been established, indicating that all extracted data segments are from the same board / strip number. The rolling process data for this piece of steel.

[0039] (1) Spacetime transformation In the strip rolling process, the roll speed determines the speed at which the strip moves. Formula 1 can be used to calculate the length of the strip passing through this position in meters, denoted as . . Formula 1: The sampling frequency is once every 10 milliseconds, where, Indicates the first The measured data is the roll speed, with the unit being meters per second. For time window The number of times the sensor measures, Indicates the first The acquisition time of each measurement data point. The correspondence between the data positions in the time and length directions during the strip rolling process is calculated using Formula 2: Formula 2: In the formula, Indicates the length of the strip. For time window The number of times the internal sensor measures. The order of the measurement data. Indicates the length direction of the strip. How many meters is the location of the first measurement data point from the head of the conveyor belt? After conversion, what is the distance in meters from the first measurement data point in the time direction of the conveyor belt? Measurement data That is, along the length of the strip Measurement data at the location. The obtained measurement data values ​​along the length of the strip are expressed as follows: This completes the data conversion of the strip rolling process from the time direction to the length direction.

[0040] (2) Data down-frequency Since the sensors on the hot-rolling production line of strip and sheet collect data every 10 milliseconds, the corresponding data frequency is very high, meaning the data volume during the strip and sheet rolling process is very large. This puts pressure on data storage, application reading, and chart rendering. Therefore, reducing the data frequency while minimizing data feature loss is particularly important. Thus, a direct downsampling algorithm can be used here to reduce the data frequency to meet the data requirements. The direct downsampling algorithm is described as follows: Given the original data... Every Sampling once per point: ; It is a positive integer.

[0041] Step 3: Data Processing. Data processing, as the next step in data acquisition, is responsible for calculating and generating feature values ​​from the reduced-frequency process data. Therefore, the indicators for evaluating the quality of hot-rolled strip can be feature values ​​such as mean, hit rate, and variance. The input parameters for data processing include data segments and output feature value names. A data segment refers to the data of the strip body after removing the head and tail sections along the strip's length direction; the remaining strip body data segments are used for calculation. Output feature values ​​include hit rate, mean, and variance. The algorithm implementation is consistent with the mathematical definitions.

[0042] Step 4: Data storage.

[0043] (1) Process data storage; After the data acquisition is completed and the board strip number is bound to the time sequence data segment and the frequency is reduced, the process data can be stored based on the document-oriented database MongoDB. The document structure is as follows: Figure 3 As shown. In Figure 3 In this context, coilNo represents the strip number; memberId represents the signal number, which is uniquely identified; passNo represents the rolling pass number; name represents the signal name; unit represents the mathematical unit; rangeTimeStart represents the start time of data acquisition; rangeTimeEnd represents the end time of data acquisition; xloc is an array type representing the position coordinates of the data in the length direction; yValues ​​is an array type representing the process data segment.

[0044] (2) Feature value storage; For feature values ​​generated by data processing rules, a unified relational database table model can be used for storage, as shown in Table 1.

[0045] Step 5: Data sharing.

[0046] Besides being persistently stored in a database, the data obtained after data collection and processing can also be precisely shared with external intelligent application systems. The data sharing process based on the RocketMQ message queue system is as follows: Figure 4 As shown. In Figure 4 In this process, the external system can accurately receive process data associated with the board strip number and feature values ​​generated based on the process data as input data for application functions.

[0047] In summary, the hot rolling production line process data processing method proposed in this invention involves grouping sensors installed on the hot rolling production line, including grouping sensors with the same installation and measurement positions into one group; then defining all data signals collected by each group of sensors according to the sensor grouping results to form a data signal set, and dividing the data signals in the data signal set into tracking signals and acquisition target signals; then using the bite signal in the tracking signal to determine the time when the strip head and strip tail pass through the preset position, and using the time when the strip head passes through the preset position as the start time and the time when the strip tail passes through the preset position as the start time. The end time is determined by the start and end times. The time it takes for the strip head and tail to pass through a preset position is determined based on the bite signal value. A time window is then formed based on the start and end times. According to the time window and the storage location of the target signal in the time-series database, the identification code data segment, strip number signal data segment, and roll speed signal data segment are extracted from the time-series database. Finally, a randomly selected value from the strip number signal data segment is used as the strip number, and the strip number is associated with the identification code data segment, strip number signal data segment, and roll speed signal data segment to obtain the rolling process data corresponding to the strip number. Therefore, this method can establish a correlation between strip rolling process data and strip number. It can also process hot-rolling production line process data, store the calculation results in a unified standard format, and promptly push data to external systems and other third-party applications for data sharing. Thus, this method can support the continuous emergence of new demands in steel rolling digital analysis applications, significantly improving the end-to-end quality traceability and defect analysis efficiency. It can play a significant supporting role in hot-rolled product quality, equipment diagnosis, and lean operation management. Furthermore, this method fully describes the tracking, collection, processing, storage, and sharing of data in the hot rolling production process. It can be applied intelligently across multiple hot rolling production lines, providing a solid data foundation for steel companies to transform towards intelligent manufacturing. This helps steel companies improve product quality and reduce scrap rates, and has extremely high economic value.

[0048] In an exemplary embodiment of this application, as Figure 5As shown, a hot rolling production line process data processing system is provided, including: The signal definition module is used to group sensors installed on the hot-rolled strip production line. This includes grouping sensors with the same installation and measurement positions together; and defining all data signals collected by each group of sensors according to the grouping results, forming a data signal set, and further dividing the data signals in the data signal set into tracking signals and target signals. In some examples, these sensors on the hot-rolled strip production line can be grouped according to the principle that sensors with the same installation and measurement positions are grouped together.

[0049] The data tracking module is used to determine the time when the head and tail of the strip pass through the preset position using the bite signal in the tracking signal, and uses the time when the head of the strip passes through the preset position as the start time and the time when the tail of the strip passes through the preset position as the end time; wherein, the time when the head and tail of the strip pass through the preset position is determined according to the value of the bite signal. The data acquisition module is used to form a time window based on the start and end times, and extract the identification code data segment, strip number signal data segment, and roll speed signal data segment from the time series database according to the time window and the storage location of the target signal in the time series database; and randomly select a value from the strip number signal data segment as the strip number, and associate the strip number with the identification code data segment, strip number signal data segment, and roll speed signal data segment to obtain the rolling process data corresponding to the strip number; And a data processing module, used to evaluate the rolling quality of hot-rolled strip using preset feature values ​​based on the set of data signals after frequency reduction; wherein the preset feature values ​​include at least one of mean, hit rate and variance; The data storage module is used to store data according to a preset document structure, which includes at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment; and, using a unified relational database table schema, stores feature values ​​calculated by data processing rules. The data sharing module is used to receive and parse data subscription tasks to obtain the corresponding subscription data list. The data subscription task is generated based on the data subscription activity initiated by the external system to specify the required data items. The module also continuously pushes the corresponding data to a pre-generated or real-time message queue according to the subscription data list, so that the external system can receive the data through the message queue.

[0050] It is understood that the hot rolling production line process data processing system and the hot rolling production line process data processing method provided in the above embodiments belong to the same concept. The specific way in which the hot rolling production line process data processing method is executed has been described in detail in the above method embodiments, and will not be repeated here. In practical applications, the hot rolling production line process data processing system provided in the above embodiments can allocate the above functions to different functional modules as needed. That is, the internal structure of the hot rolling production line process data processing system can be divided into different functional modules, and then all or part of the functions of the corresponding functional modules can be implemented by the hot rolling production line process data processing method described in the above embodiments. For specific implementation processes, please refer to the above embodiments, and no specific limitations are imposed here.

[0051] In summary, the hot rolling production line process data processing system proposed in this invention groups the sensors installed on the hot rolling production line, including grouping sensors with the same installation and measurement positions into one group; then, according to the sensor grouping results, all data signals collected by each group of sensors are defined to form a data signal set, and the data signals in the data signal set are divided into tracking signals and acquisition target signals; then, the bite signal in the tracking signal is used to determine the time when the strip head and strip tail pass through the preset position, and the time when the strip head passes through the preset position is used as the start time, and the time when the strip tail passes through the preset position is used as the start time. The system uses time as the end time; the time for the strip head and tail to pass through the preset position is determined based on the bite signal value; then, a time window is formed based on the start and end times, and according to the time window and the storage location of the target signal in the time-series database, the system extracts the identification code data segment, strip number signal data segment, and roll speed signal data segment from the time-series database; finally, a sampled value is randomly selected from the strip number signal data segment as the strip number, and the strip number is associated with the identification code data segment, strip number signal data segment, and roll speed signal data segment to obtain the rolling process data corresponding to the strip number. Therefore, this system can establish a correlation between strip rolling process data and strip number, process hot rolling production line process data, store calculation results in a unified standard format, and promptly push data to external systems and other third-party applications for data sharing. Thus, this system can support the continuously evolving digital analysis applications of steel rolling, significantly improving the end-to-end quality traceability and defect analysis efficiency, and playing a significant supporting role in hot-rolled product quality, equipment diagnosis, and lean operation management. Furthermore, this system has fully introduced the tracking, collection, processing, storage, and sharing of data in the hot rolling production process. It can be applied intelligently on multiple hot rolling production lines, providing a solid data foundation for steel companies to transform into intelligent manufacturing, helping them improve product quality and reduce scrap rates, and possessing extremely high economic value.

[0052] In an exemplary embodiment of the present invention, a computer device is also provided. The computer device may include a memory, a processor, and a computer program stored in the memory. The processor can execute the computer program to cause the computer device to perform actions such as... Figure 2 The steps of the hot rolling production line process data processing method are shown. Figure 6 A schematic diagram of the structure of a computer device 1000 is shown. (See attached diagram.) Figure 6 As shown, the computer device 1000 includes: a processor 1010, a memory 1020, a power supply 1030, a display unit 1040, and an input unit 1060.

[0053] The processor 1010 is the control center of the computer device 1000. It connects various components via interfaces and lines, and performs various functions of the computer device 1000 by running or executing computer programs / instructions stored in the memory 1020, thereby providing overall monitoring of the computer device 1000. In some embodiments, when the processor 1010 calls a computer program stored in the memory 1020, it can execute, for example... Figure 2 The steps of the hot rolling production line process data processing method are shown. Optionally, the processor 1010 may include one or more processing units; preferably, the processor 1010 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. In some embodiments, the processor 1010 and the memory 1020 may be implemented on a single chip; in other embodiments, they may be implemented on separate chips.

[0054] The memory 1020 mainly includes a program storage area and a data storage area. The program storage area can store the operating system, various applications, etc.; the data storage area can store instruction data created according to the use of the computer device 1000. In addition, the memory 1020 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0055] The computer device 1000 also includes a power supply 1030 (such as a battery) that supplies power to various components. The power supply can be logically connected to the processor 1010 through a power management system, thereby enabling the management of functions such as charging, discharging, and power consumption through the power management system.

[0056] The display unit 1040 can be used to display information input by the user or information provided to the user, and can also be used to display various menus of the computer device 1000, etc. In this embodiment of the invention, it is mainly used to display the display interfaces of various applications in the computer device 1000, as well as text, pictures, and other objects displayed in the display interfaces. The display unit 1040 may include a display panel 1050. The display panel 1050 may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0057] The input unit 1060 can be used to receive information such as numbers or characters input by the user. The input unit 1060 may include a touch panel 1070 and other input devices 1080. The touch panel 1070 can also be referred to as a touch screen, and the touch panel 1070 can collect touch operations on or near the user (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel 1070).

[0058] Specifically, the touch panel 1070 can detect user touch operations and the signals generated by these operations, convert these signals into touch point coordinates and send them to the processor 1010, and receive and execute commands transmitted by the processor 1010. Furthermore, the touch panel 1070 can employ various input methods such as resistive, capacitive, infrared, and surface acoustic waves to achieve interaction. Other input devices 1080 include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, and joystick.

[0059] Of course, the touch panel 1070 can also cover the display panel 1050. When the touch panel 1070 detects a touch operation on or near it, it can transmit the information to the processor 1010 to determine the type of touch event. Subsequently, the processor 1010 provides corresponding visual output on the display panel 1050 based on the type of touch event. Although in Figure 6 In this embodiment, the touch panel 1070 and the display panel 1050 are two separate components to realize the input and output functions of the computer device 1000. However, in some embodiments, the touch panel 1070 and the display panel 1050 can be integrated to realize the input and output functions of the computer device 1000.

[0060] The computer device 1000 may also include one or more sensors, such as pressure sensors, gravity acceleration sensors, proximity sensors, etc. Of course, depending on the specific application scenario, the computer device 1000 may also include other components such as cameras.

[0061] In an exemplary embodiment of the present invention, a computer-readable storage medium is also provided, which stores a computer program / instructions. When executed by a processor, the computer program / instructions enable the computer device to perform the functions described in the present invention. Figure 2 The steps of the hot rolling production line process data processing method are shown.

[0062] It will be understood by those skilled in the art that Figure 6 This is merely an example of a computer device and does not constitute a limitation on the device. The device may include more or fewer components than illustrated, or a combination of certain components, or different components. For ease of description, the above parts are divided into modules (or units) according to their functions and described separately. Of course, in implementing this invention, the functions of each module (or unit) can be implemented in one or more software or hardware components.

[0063] Those skilled in the art will understand that the present invention can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present invention is described in accordance with flowcharts and / or block diagrams of a hot rolling production line process data processing method, a hot rolling production line process data processing system, and computer program products, based on some embodiments. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be applied to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to create a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, produce functions for implementing the process... Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0064] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for processing process data in a hot rolling production line, characterized in that, The method includes: The sensors installed on the hot rolling production line of strip and sheet are grouped, including grouping sensors with the same installation position and measurement position together; Based on the sensor grouping results, all data signals collected by each group of sensors are defined to form a data signal set, and the data signals in the data signal set are divided into tracking signals and target signals. The time taken for the strip head and strip tail to pass through a preset position is determined using the bite signal in the tracking signal, and the time taken for the strip head to pass through the preset position is taken as the start time and the time taken for the strip tail to pass through the preset position is taken as the end time; wherein, the time taken for the strip head and strip tail to pass through the preset position is determined according to the value of the bite signal; A time window is formed based on the start time and the end time, and the identification code data segment, strip number signal data segment, and roll speed signal data segment are extracted from the time series database according to the time window and the storage location of the target signal in the time series database. A random value is selected from the strip number signal data segment as the strip number, and the strip number is associated with the identification code data segment, the strip number signal data segment and the roll speed signal data segment to obtain the rolling process data corresponding to the strip number; The method further includes: Obtaining the first step in the hot rolling process of strip and plate The measurement data includes the roll speed and measurement time, and is based on the first measurement. The roll speed and measurement time of each measurement data point are used to calculate the strip's speed at the [number]th [time / item]. The strip length corresponding to each measurement data point; among which... It is a positive integer; According to the strip in the first Based on the strip length corresponding to each measurement data point, the number of sensor measurements within the time window, and the order of the measurement data, calculate the strip length direction of the [number of measurements]. The distance between the location of each measurement data point and the head of the conveyor belt is denoted as . ; In the direction of the strip length The measurement data at the location is used as the first in the time direction of the plate and strip. One measurement data; The method further includes: According to the number of sensor measurements within the time window, the data signals in the data signal set are sampled at intervals to reduce the frequency of the data signal set; And / or, based on the set of data signals after frequency reduction, the rolling quality of hot-rolled strip is evaluated using preset feature values; wherein, the preset feature values ​​include at least one of mean, hit rate and variance.

2. The hot rolling production line process data processing method according to claim 1, characterized in that, The method further includes: Data is stored according to a preset document structure, which includes at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment. Furthermore, a unified relational database table schema is adopted to store the feature values ​​calculated through data processing rules.

3. The hot rolling production line process data processing method according to claim 1, characterized in that, The method further includes: Receive and parse data subscription tasks to obtain the corresponding list of subscribed data; wherein, the data subscription task is generated based on the data items required by the data subscription activity initiated by the external system. According to the subscribed data list, the corresponding data is continuously pushed to a pre-generated or real-time generated message queue so that the external system can receive the data through the message queue.

4. The hot rolling production line process data processing method according to claim 1, characterized in that, The process of determining the time it takes for the head and tail of the strip to pass through a preset position based on the value of the bite signal includes: When the value of the steel bite signal changes from the first value to the second value, the strip head is marked as having passed the preset position, and the time at this moment is recorded as the time when the strip head has passed the preset position, which is also called the start time. When the value of the steel bite signal changes from the second value to the first value, the tail of the strip is marked as having passed the preset position, and the time at this moment is recorded as the time when the tail of the strip passes the preset position, which is also called the end time.

5. The hot rolling production line process data processing method according to claim 1, characterized in that, According to the The roll speed and measurement time of each measurement data point are used to calculate the strip's speed at the [number]th [time / item]. The strip lengths corresponding to the measured data are: In the formula, Indicates the length of the strip. Indicates the first The roll speed of the measured data Indicates the number of sensor measurements within the time window. Indicates the first One measurement data, Indicates the first One measurement data; And, calculate the length direction of the strip. The distance between the location of each measurement data point and the head of the conveyor belt is: In the formula, Indicates the length direction of the strip. The location of each measurement data point is the distance from the head of the strip.

6. A hot rolling production line process data processing system applying the hot rolling production line process data processing method according to any one of claims 1 to 5, characterized in that, The system includes: The signal definition module is used to group the sensors installed on the hot rolling production line of strip and sheet, including grouping sensors with the same installation position and measurement position into one group; and defining all data signals collected by each group of sensors according to the sensor grouping results to form a data signal set, and dividing the data signals in the data signal set into tracking signals and acquisition target signals; The data tracking module is used to determine the time when the strip head and strip tail pass through a preset position using the bite signal in the tracking signal, and to take the time when the strip head passes through the preset position as the start time and the time when the strip tail passes through the preset position as the end time; wherein, the time when the strip head and strip tail pass through the preset position is determined according to the value of the bite signal; The data acquisition module is used to form a time window based on the start time and the end time, and extract the identification code data segment, strip number signal data segment, and roll speed signal data segment from the time series database according to the time window and the storage location of the target signal in the time series database; and randomly select an acquired value from the strip number signal data segment as the strip number, and associate the strip number with the identification code data segment, the strip number signal data segment, and the roll speed signal data segment to obtain the rolling process data corresponding to the strip number.

7. The hot rolling production line process data processing system according to claim 6, characterized in that, The system also includes: The data processing module is used to evaluate the rolling quality of hot-rolled strip using preset feature values ​​based on the set of down-frequency data signals; wherein the preset feature values ​​include at least one of mean, hit rate and variance; The data storage module is used to store data according to a preset document structure, which includes at least one of the following: strip number, signal number, rolling pass number, signal name, mathematical unit, data acquisition start time, data acquisition end time, data position coordinates in the length direction, and process data segment; and, using a unified relational database table schema, stores feature values ​​calculated by data processing rules. The data sharing module is used to receive and parse data subscription tasks to obtain the corresponding subscription data list; wherein, the data subscription task is generated based on the data items required by the data subscription activity initiated by the external system; and, according to the subscription data list, the corresponding data is continuously pushed to a pre-generated or real-time generated message queue so that the external system can receive the data through the message queue.

8. A computer device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the hot rolling production line process data processing method according to any one of claims 1 to 5.

Images