Data processing method and device and readable storage medium

Abstract

The invention provides a data processing method and device and a readable storage medium, and the method comprises the steps: collecting and updating original data according to a corresponding preset frequency in a process that a roller extension carries out the roller separation of a mother roll to obtain child rolls, and submitting the original data to an edge device, and the edge device preprocesses the original data and submits the data to the cloud device at a second frequency, and the cloud device stores the to-be-processed data. The cloud equipment reads the data set from the database at a first frequency, divides the data set to obtain multiple pieces of batch data, and determines the thickness and meter number of the sub-volume according to each piece of batch data in the multiple pieces of batch data; a targeted data processing flow is provided for a roller dividing scene, a cloud device reads a database regularly to obtain a data set, the data set is divided to obtain batch data, the thickness and the meter number of a sub-roller are determined according to the batch data, and the purpose of improving the data processing accuracy is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lithium battery, and particularly relates to a data processing method, equipment and readable storage medium. BACKGROUND

[0002] A roll cutting machine, referred to as a roll cutting machine, is an important equipment in the lithium battery manufacturing industry. The core task of the roll cutting machine is to roll cut the mother roll after coating and drying to obtain multiple pole pieces, and to wind the pole pieces to obtain a sub-roll, which is a core material for preparing a lithium battery.

[0003] In the production process of a lithium battery, the thickness and the meter number of a sub-roll are key process parameters, which directly determine the performance, safety and cost of the lithium battery. In order to obtain the two key process parameters, a conventional scheme is to collect data by using sensors on the roll cutting machine, to pre-process the collected data and extract features, and to determine the thickness and the meter number of the sub-roll according to the extracted features. The pre-processing mode is a general pre-processing mode.

[0004] However, the accuracy of the thickness and the meter number of the sub-roll determined by using the general data pre-processing mode is poor. SUMMARY

[0005] The present application provides a data processing method, equipment and readable storage medium, which reads a database to obtain a data set, divides the data set to obtain batch data, and determines the thickness and the meter number of a sub-roll according to the batch data, so as to achieve the purpose of improving the accuracy of data processing.

[0006] In a first aspect, the present application provides a data processing method, comprising:

[0007] reading a data set from a database according to a first frequency, wherein the database stores to-be-processed data submitted by an edge device at a second frequency, the to-be-processed data is obtained by the edge device by pre-processing original data from a roll cutting machine, and the original data is data updated by each sub-device of the roll cutting machine according to a corresponding preset frequency in a process of roll cutting a mother roll to obtain a sub-roll;

[0008] dividing the data set to obtain a plurality of batch data, wherein each batch data contains to-be-processed data located between two adjacent discharge signals, different discharge signals correspond to different batch numbers, and different batch numbers are used to identify different sub-rolls, and the original data contains the discharge signals;

[0009] determining the thickness and the meter number of a sub-roll according to each batch data in the plurality of batch data.

[0010] In a second aspect, the present application provides a data processing device, comprising:

[0011] The reading module is configured to read a data set from a database according to a first frequency, wherein the database stores to-be-processed data submitted by an edge device at a second frequency, the to-be-processed data is obtained by the edge device by preprocessing raw data from a roll division machine, and the raw data is obtained by each sub-device of the roll division machine according to a corresponding preset frequency during a process in which the roll division machine divides a parent roll into sub-rolls.

[0012] The dividing module is configured to divide the data set to obtain a plurality of batch data, each batch data containing to-be-processed data located between two adjacent unloading signals, different unloading signals corresponding to different batch numbers, and different batch numbers being used to identify different sub-rolls, and the raw data containing the unloading signals.

[0013] The processing module is configured to determine a thickness and a meter number of a sub-roll according to each batch data in the plurality of batch data.

[0014] In a third aspect, the present application provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to enable the electronic device to implement the method in the first aspect or any possible implementation manner of the first aspect.

[0015] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer instructions, and the computer instructions are used to implement the method in the first aspect or any possible implementation manner of the first aspect when executed by a processor.

[0016] In a fifth aspect, the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the method in the first aspect or any possible implementation manner of the first aspect.

[0017] The data processing method, device and readable storage medium provided by the application, in the process of roll division machine dividing the mother roll to obtain the sub-roll, each sub-device of the roll division machine collects and updates the original data according to the corresponding preset frequency, and submits the original data to the edge device, the edge device submits the original data to the cloud device at a second frequency after pre-processing, and the cloud device saves the to-be-processed data. The cloud device reads the data set from the database at a first frequency, divides the data set to obtain a plurality of batch data, and determines the thickness and meter number of the sub-roll according to each batch data in the plurality of batch data, wherein each batch data contains to-be-processed data located between two adjacent unloading signals, different unloading signals correspond to different batch numbers, and different batch numbers are used to identify different sub-rolls, and the original data contains the unloading signal. By using the scheme, a targeted data processing flow is proposed for the roll division scene: the cloud device reads the database to obtain the data set at a time, divides the data set to obtain the batch data, determines the thickness and meter number of the sub-roll according to the batch data, and realizes the purpose of improving the accuracy of data processing. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0019] Figure 1A is a network architecture diagram applicable to the data processing method provided by the application;

[0020] Figure 1B is Figure 1A an example diagram;

[0021] Figure 2 is a flowchart of the data processing method provided by the application;

[0022] Figure 3A is a schematic diagram of the scanning track of the thickness gauge in the data processing method provided by the application;

[0023] Figure 3B is Figure 3A a blind area diagram of the sub-roll;

[0024] Figure 4 is a schematic diagram of the data processing device provided by the application;

[0025] Figure 5 is a structural schematic diagram of the electronic device provided by the application. DETAILED DESCRIPTION

[0026] In the production process of lithium batteries, a roll dividing machine is used to divide a mother roll to obtain a child roll, and the child roll is a core material for preparing lithium batteries. Process parameters such as the thickness and the meter number of the child roll are crucial and are key parameters affecting the performance, safety and cost of lithium batteries. In order to obtain these parameters, a conventional scheme is to use sensors on the roll dividing machine to collect data, to pre-process the collected data to extract features, and to determine the thickness and the meter number of the child roll according to the extracted features. The pre-processing scheme is a general data pre-processing scheme and is suitable for a scenario where data sources are synchronous, the measurement positions of the sensors are the same, and the collection frequencies are the same.

[0027] In the roll dividing scenario, the roll dividing machine includes a thickness gauge, a roll dividing device, a winding machine, a motor and other sub-devices. Various sensors such as a tension sensor, a displacement sensor and a speed sensor are also provided on the roll dividing machine, and these sensors are also referred to as sub-devices of the roll dividing machine for convenience. The positions of the sub-devices of the roll dividing machine are different, and the collection frequencies are different, resulting in time and space misalignment of the data collected by these sub-devices. Therefore, when the conventional pre-processing scheme is used in the roll dividing scenario, the accuracy of the determined data such as the thickness and the meter number is poor.

[0028] Based on this, the present application provides a data processing method, a device and a readable storage medium. The cloud device reads a database to obtain a data set at a fixed time, processes the data set in batches to obtain batch data, and determines the thickness and the meter number of the child roll according to the batch data, thereby achieving the purpose of improving the accuracy of data processing.

[0029] Figure 1A is a network architecture diagram applicable to the data processing method provided by the present application. Please refer to Figure 1A , the network architecture includes a roll dividing machine 11, an edge device 12 and a cloud device 13. A network connection is established between the roll dividing machine 11 and the edge device 12, and a network connection is established between the edge device 12 and the cloud device 13. The roll dividing machine 11 includes a plurality of sub-devices, including but not limited to a thickness gauge, a motor, various sensors and the like. These sub-devices are arranged at different positions of the roll dividing machine 11 and have different collection frequencies. For example, the sub-device a collects and updates data once every 2 seconds, and the sub-device b collects and updates data once every 1 second. The roll dividing machine 11 is provided with a controller, and the raw data collected by the sub-devices is transmitted to the controller, and the controller submits the raw data to the edge device at a fixed frequency. The fixed frequency is, for example, 1 time / second.

[0030] The edge device 12, also referred to as an edge server or a data acquisition Internet of Things platform, is located at the factory end and is usually deployed at a location such as a machine room of the factory. The edge device 12 pre-processes the raw data from the roll dividing machine 11 to obtain processed data. The pre-processing includes but is not limited to data filtering, data deduplication, unifying the units of the meter number and the thickness and the like. After the pre-processing, the edge device 12 submits the processed data obtained by the pre-processing to the cloud device 13 at a fixed frequency. The fixed frequency is, for example, 1 time / second.

[0031] The cloud device 13, also known as a cloud server or cloud data platform, can establish network connections with multiple edge devices 12. The cloud device 13 possesses significant storage and processing capabilities, used to store the data to be processed submitted by the edge devices 12. This data is stored sequentially according to timestamps. The cloud device 13 reads the stored data at a first-order frequency, with each read forming a data set. The cloud device 13 partitions the data set into batches, and then determines the thickness and length in meters of each sub-volume based on each batch.

[0032] Each time the cloud device 13 reads a data set, it performs time alignment, spatial alignment, and anomaly handling on the data to be processed in the data set. During the anomaly handling process, because the thickness gauge needs to be reset, sometimes the scanned thickness gauge data is inconsistent. It is necessary to delete and reassemble the abnormal data of the thickness gauge to ensure that the meter count of the sub-roll is in an increasing form.

[0033] Figure 1B yes Figure 1A An example diagram. Please refer to... Figure 1B The roller separator 11 includes multiple sub-devices 111 and a programmable logic controller (PLC) 112. Different sub-devices 111 have corresponding preset frequencies. Since the sub-devices 111 come from different manufacturers, their preset frequencies may be the same or different. Each sub-device 11 collects raw data according to its own preset frequency and submits the raw data to the PLC 112. The PLC 112 then submits the data to the edge device 12 at a second frequency.

[0034] Assume multiple sub-devices 111 include sub-device a and sub-device b. Sub-device a has a preset frequency of 1 time / second, and sub-device b has a preset frequency of 0.5 times / second (1 time / 2 seconds). A second frequency is also 1 time / second. Taking submission times t1, t2, t3, and t4 based on the second frequency as an example, sub-device a submits raw data at all four times. However, because the preset frequency of the sub-devices is 0.5 times / second, sub-device b only collects and updates data at times t2 and t4; no data is collected at times t1 and t3. When PLC 112 submits data, the data submitted by sub-device b at time t1 is either empty or an empirical value. At time t3, the original data from time t2 is resubmitted, and at time t5, the original data from time t4 is resubmitted.

[0035] A data acquisition and monitoring control system (Supervisory Control And Data Acquisition, SCADA) 121 is arranged on the edge device 12, and the SCADA 121 is responsible for pre-processing raw data from the roll splitter 11 to obtain to-be-processed data, and submitting the to-be-processed data to the cloud device 13.

[0036] A database 131 and an algorithm module 132 are arranged on the cloud device 13. The database 131 is, for example, an Intelligent Things Database (IOTDB), and the present application is not limited thereto. The to-be-processed data submitted by the edge device 12 at the second frequency is stored in the database 131. The algorithm module 132 reads a data set from the database 131 at the first frequency, processes the data set, obtains the thickness and the meterage of the sub-roll, writes the thickness and the meterage of the sub-roll into the database 131, and the thickness and the meterage of the sub-roll are different from the storage location of the to-be-processed data.

[0037] Next, based on the architecture shown in Figure 1A and Figure 1B , the data processing method described in the present application will be described in detail. For example, please refer to Figure 2 . Figure 2 is a flowchart of the data processing method provided by the present application. The execution subject of the present embodiment is a cloud device, and the present embodiment includes:

[0038] 201. Read a data set from a database according to a first frequency, wherein the database stores to-be-processed data submitted by an edge device at a second frequency, the to-be-processed data is obtained by pre-processing raw data from a roll splitter by the edge device, and the raw data is data updated by each sub-device of the roll splitter according to a corresponding preset frequency during the process of splitting a parent roll into a sub-roll.

[0039] The roll dividing process includes processes such as rolling, thickness measuring and slitting, and is a continuous process from "raw material input" to "finished product output". The unwinding at the head of the roll dividing machine is the starting point of production. The unwinding refers to placing the unrolled, to-be-divided parent roll on the unwinding machine at the head of the roll dividing machine. Then, the parent roll is gradually unwound through the transmission system and is sequentially sent to the rolling, thickness measuring, slitting and other processes. The rolling refers to adjusting the thickness of the parent roll to make the thickness and density of the parent roll meet the requirements. The thickness measuring instrument records the thickness and the meter number, which refers to the length and is measured in meters. The slitting refers to dividing the rolled parent roll into sub-rolls of a target width. Finally, the collection action is completed by the winding machine at the end of the production line, and the collection action is referred to as tail end unloading. Each time a sub-roll is collected, the pole piece is cut off, and the cutting is also referred to as material cutting. One material cutting triggers one unloading signal. Each sub-roll has its own batch number, which is generated when winding.

[0040] In this application, the first frequency is, for example, 3 hours / time, and the second frequency is, for example, 1 time / second, and the application is not limited. In the roll dividing process, the roll dividing machine rolls and slits the parent roll to obtain a sub-roll. After one parent roll is completely divided, a new parent roll is replaced, i.e., the parent roll is unwound again at the unwinding section.

[0041] Similarly, in the roll dividing process, when the winding machine completes the winding of one sub-roll, an unloading signal is generated to start the winding of the next sub-roll, until the winding is completed and the material is cut off, triggering a new unloading signal.

[0042] According to the above unwinding and winding, it can be seen that the roll dividing process continues, the parent roll is continuously consumed, and new sub-rolls are continuously generated. Generally, the parent roll is unwound from the head, rolled, thickness measured, and slit, and then a target number of winding machines simultaneously wind at the tail end, and finally a plurality of sub-rolls are obtained. When the parent roll is completely divided, the winding machine cuts off the material and generates an unloading signal to start the winding of the next sub-roll. The target number, for example, the ratio of the width of the parent roll to the width of the sub-roll, can be 2, 3, etc., and the application is not limited.

[0043] In addition, when there is a requirement for the length of the sub-roll, the length of the wound sub-roll is measured during winding. When the length of the sub-roll reaches the preset length, although the parent roll has not been completely divided at this time, the tail end of the production line will also cut off the material and generate an unloading signal to start the winding of the next sub-roll.

[0044] During the roll dividing process of the roll dividing machine, each sub-device collects data at its own preset frequency. For example, the preset frequency in the thickness measuring instrument scanning mode is 10 times / second, 20 times / second, etc. After the sub-device collects the original data, the original data is sent to the PLC.

[0045] The PLC receives the raw data collected and updated by each sub-device at its preset frequency, and submits the raw data to the edge device at a second frequency. When there is a submission time point determined according to the second frequency, and sub-device 1 has updated the raw data due to a higher preset frequency, and sub-device 2 has not updated the raw data due to a lower preset frequency, the updated raw data of sub-device 1 and the raw data of sub-device 2 updated at the last time are submitted at the submission time point. In this case, the raw data of sub-device 1 and the raw data of sub-device 2 are not synchronized in the time axis.

[0046] After the edge device receives the raw data from the PLC of the roll dividing machine, the raw data is preliminarily pre-processed to obtain to-be-processed data, the pre-processing includes filtering and deduplication, and all the units of length and thickness are unified. Then, the to-be-processed data is submitted to the cloud device at a second frequency.

[0047] After the cloud device receives the to-be-processed data, the to-be-processed data is stored in the database in chronological order according to the time stamp, and the to-be-processed data is read from the database at a first frequency. For example, the database is read once every 3 hours; for another example, the database is read once every 2 hours. The to-be-processed data read each time forms a data set.

[0048] 202, divide the data set to obtain a plurality of batch data, each batch data containing to-be-processed data located between two adjacent unloading signals, different unloading signals corresponding to different batch numbers, and different batch numbers being used to identify different sub-rolls, and the raw data containing the unloading signals.

[0049] The roll dividing process is a continuous process, in which the parent roll is continuously consumed, and new sub-rolls are continuously generated. Therefore, the to-be-processed data stored in the database of the cloud device is data in the process of generating a plurality of sub-rolls. In the roll dividing process, after each sub-roll is unloaded, i.e., after the cutting and winding of each sub-roll are completed, an unloading signal is generated, and the cloud device divides the to-be-processed data in the data set into a plurality of batch data according to the unloading signal, each batch data containing to-be-processed data located between two adjacent unloading signals.

[0050] 203, determine the thickness and length of the sub-roll according to each batch data in the plurality of batch data.

[0051] In this application, the data between two adjacent unloading signals includes the data collected and updated by each sub-device of the roll dividing machine from the start of the unwinding section to the roll pressing to the unloading position. After the cloud device divides the data set into batches, the thickness and length of the sub-roll are determined according to the to-be-processed data contained in each batch data.

[0052] The data processing method provided in the application, in the process of roll division of the mother roll by the roll division machine, each sub-device of the roll division machine collects and updates the original data according to the corresponding preset frequency, submits the original data to the edge device, the edge device submits the preprocessed original data to the cloud device at a second frequency, and the cloud device saves the to-be-processed data. The cloud device reads a data set from the database at a first frequency, divides the data set to obtain a plurality of batch data, and determines the thickness and meter number of the sub-roll according to each batch data in the plurality of batch data, wherein each batch data contains to-be-processed data located between two adjacent discharge signals, different discharge signals correspond to different batch numbers, and different batch numbers are used to identify different sub-rolls, and the original data contains the discharge signal. By using this scheme, a targeted data processing flow is proposed for the roll division scene: the cloud device reads the database to obtain a data set at a regular time, divides the data set to obtain batch data, determines the thickness and meter number of the sub-roll according to the batch data, and achieves the purpose of improving the accuracy of data processing.

[0053] In the above embodiment, when the data set is batched, in one way, the data set is evenly divided into a preset number of batch data according to the preset number, for example, 5, 6, etc. The application is not limited.

[0054] In another way, the cloud device determines a target queue according to the to-be-processed data contained in the data set, and the target queue contains a plurality of discharge signals with time stamps sequentially increasing. Then, the cloud device divides the data set according to each adjacent two discharge signals in the target queue to obtain a plurality of batch data.

[0055] For example, according to the roll division process described above, it can be known that: each time a sub-roll is collected, the pole piece is cut off, and each cutting triggers a discharge signal. After one discharge signal is triggered, the original data of the processes such as roll pressing, cutting, and thickness measurement from the mother roll unwinding section is continuously submitted to the edge device, and after the pre-processing of the edge device, it is submitted to the cloud device until the next discharge signal is triggered. After the next discharge signal is triggered, the original data of each process in the roll division process is continuously submitted to the edge device by the PLC of the roll division machine. It can be known that: the to-be-processed data between two discharge signals contains all the data of the sub-roll production, so the to-be-processed data between two adjacent discharge signals can be divided into a batch data.

[0056] The data set obtained by the cloud device reading the to-be-processed data from the database contains a plurality of discharge signals, the cloud device identifies each discharge signal, and arranges each discharge signal in the order of time stamp sequentially increasing to obtain a target queue. Then, the cloud device obtains all adjacent two discharge signals according to the target queue, divides the data set according to the adjacent two discharge signals, and obtains a plurality of batch data.

[0057] It can be understood that, since the data to be processed between two adjacent unloading signals contains all the data from the start of the rolling to the winding, and the object of the rolling is the parent roll, the last winding obtains the target number of sub-rolls. Therefore, based on one batch of data, the thickness and the meter number of the target number of sub-rolls can be determined.

[0058] With this scheme, the cloud device determines the target queue according to the unloading signals in the data set, and divides the data set according to the two adjacent unloading signals in the target queue, so as to accurately divide the data set, and further improve the meter number and the thickness of the sub-rolls.

[0059] Optionally, in the above embodiment, in the process of determining the thickness and the meter number of the sub-rolls by the cloud device according to each batch of data, for each batch of data, the thickness gauge data in the batch of data is split according to the target number of sub-rolls cut by the roll division machine, to obtain target number of sub-data. Then, the cloud device determines the thickness and the meter number of the corresponding sub-rolls according to each sub-data in the target number of sub-data, to obtain the thickness and the meter number of the target number of sub-rolls.

[0060] In this application, during the roll division process, each sub-device of the roll division machine continuously submits raw data to the edge device. The thickness gauge is a crucial sub-device of the roll division machine. The meter number encoder is arranged on the thickness gauge. The thickness gauge is used to provide thickness gauge data, which includes thickness and meter number, for example, the thickness of the 150th meter of the parent roll; for another example, the thickness of the 200th meter of the parent roll. During the roll division process, the thickness gauge continuously scans to obtain the thickness gauge data, and the data acquisition frequency is, for example, 20 times per second. Since the thickness gauge is located before the cutting, the data of the entire parent roll is scanned. Therefore, it is necessary to split the thickness gauge data in combination with the scanned thickness partition and the scanning direction. For example, please refer to Figure 3A .

[0061] Figure 3A is a schematic diagram of the scanning trajectory of the thickness gauge in the data processing method provided in this application. Please refer to Figure 3A , the thickness gauge is installed at a position after the production line roller and before the cutting, close to the tail unloading position. During the scanning process of the thickness gauge, the parent roll is continuously conveyed, so that the scanning trajectory of the thickness gauge during the thickness measurement stage is in the shape of "Z".

[0062] After the cutting stage, taking the parent roll being divided into two sub-rolls as an example, that is, taking the target number 2 as an example, the cloud device splits the thickness gauge data to obtain the thickness gauge data of each sub-roll. Figure 3AIn the figure, the dashed line represents the cutting of the parent roll into two child rolls, and at the same time, the dashed line divides the "Z" shaped track into two parts: the part above the dashed line and the part below the dashed line. The thickness gauge data above the dashed line is used to determine the thickness and meterage of child roll 1, and the thickness gauge data below the dashed line is used to determine the thickness and meterage of child roll 2.

[0063] With this scheme, by splitting the thickness gauge data according to the target number, obtaining the target number of sub-data and determining the thickness and meterage of the child roll, the speed is fast and the accuracy is high.

[0064] Optionally, in the above embodiment, before the cloud device determines the thickness and meterage of the corresponding child roll according to each of the target number of sub-data, when there is a blind area in the sub-data, the cloud device further interpolates the blind area according to the front and rear areas of the blind area in the sub-data.

[0065] Figure 3B is Figure 3A In the figure, the blind area of the child roll is shown. Please refer to Figure 3B The split sub-data has a blind area, which is caused by the continuous conveying of the parent roll during the scanning of the thickness gauge. These blind areas include the diagonal filled part in child roll 1 and the square filled part in child roll 2. On the other hand, the thickness gauge does not scan the parent roll when it is reset, resulting in a blind area, such as the dark gray filled part in the figure. When a blind area occurs, the cloud device determines the thickness and meterage of the child roll before interpolating the blind area according to the front and rear areas of the blind area.

[0066] In Figure 3B For example, the first blind area on the left side of child roll 2 has a front area 31 and a rear area 32, and the thickness gauge data of areas 31 and 32 is known. The cloud device interpolates the blind area according to the interpolation algorithm combined with the thickness gauge data of areas 31 and 32 to obtain the thickness gauge data of the blind area. The interpolation algorithm includes but is not limited to nearest neighbor difference value algorithm, polynomial interpolation algorithm, bilinear interpolation algorithm, etc.

[0067] With this scheme, by interpolating the blind area according to the thickness gauge data of the front and rear areas of the blind area, the purpose of improving the accuracy of the thickness and meterage of the child roll is achieved.

[0068] Optionally, in the above embodiment, before the cloud device divides the data set, it further determines a plurality of first time points and a plurality of second time points according to the data set, and performs spatial alignment on the data set according to the plurality of first time points and the plurality of second time points. The plurality of first time points are the time points triggered by each unloading signal in the data set, and the plurality of second time points are the time points at which each batch number is generated in the data set. The unloading signal and the batch number correspond one by one.

[0069] For example, the material feeding signal corresponds to the batch number one by one. Due to different operation habits of operators, a distance between the thickness gauge and the material feeding position, and other reasons, some thickness gauge data and batch numbers do not correspond. For example, the thickness gauge data obtained by scanning a region of the parent roll is used to determine the thickness and meter number of sub-roll 1 and sub-roll 2, which are two sub-rolls fed at the same time. However, due to the different update times of the material feeding signal and the batch number, the thickness gauge data of this region is used to calculate the thickness and meter number of sub-roll 3 and sub-roll 4, which is a spatial error. To avoid spatial errors, the cloud device determines the first time of each material feeding signal trigger and the second time of each batch number generation from the data set, and performs spatial alignment on the data set according to the first time and the second time, so that the thickness gauge data and the correct batch number are bound.

[0070] With this scheme, the cloud device performs spatial alignment on the data set according to the first time of each material feeding signal trigger and the second time of each batch number generation, achieving the purpose of improving data processing accuracy.

[0071] In this application, there is a certain distance between the thickness gauge and the material feeding position, so that the data processing method based on the finished production action, that is, the material feeding signal, needs to compensate for the spatial data deviation. At the same time, the various forms of manual operation make the time of batch number update and the time of material feeding signal trigger inconsistent. Therefore, different processing strategies need to be developed for different situations to compensate for the spatial deviation of the data.

[0072] Next, how to perform spatial alignment on the data set according to the plurality of first times and the plurality of second times will be described in detail in different cases.

[0073] Case one: the first time of the material feeding signal and the second time of the corresponding batch number are the same.

[0074] For each material feeding signal, when the first time of the material feeding signal and the second time of the corresponding batch number are the same, the thickness gauge data of the sheet area of the parent roll between the thickness gauge of the roller sub-machine and the material feeding position is bound to the next batch number to perform spatial alignment on the data set, and the material feeding position is the position of collecting the sub-roll.

[0075] Please refer to Figure 3AThe thickness gauge is arranged at a position after the roll and before the slitting. Compared with the unwinding position at the head and tail, the thickness gauge is closer to the winding position, i.e., the unloading position. The upper winding position is the starting end of the rolling stage, and the unloading position is the end of the slitting stage. There is a certain distance between the thickness gauge and the upper winding position, and there is also a certain distance between the thickness gauge and the unloading position. The batch number is used to mark the sub-roll, which is convenient for subsequent tracking, etc. The batch number of the sub-roll is obtained by modifying the batch number of the master roll. For example, the master roll is divided into two sub-rolls from the width direction, and the batch number of the master roll is H1MJID23A. The batch number of the sub-roll 1 is H1MJID23A1, and the batch number of the sub-roll 2 is H1MJID23A2.

[0076] Generally, the winding machine completes the winding of the sub-roll, triggers the unloading signal, and indicates the start of the next sub-roll. The number of winding machines is related to the target number. For example, the master roll is divided into two sub-rolls from the width direction, and the number of winding machines is two; for example, the master roll is divided into three sub-rolls from the width direction, and the number of winding machines is three.

[0077] After each winding of the winding machine is completed, the material cutting triggers the unloading signal, indicating the start of winding of the new sub-roll. That is, the unloading signal is before a sub-roll. After the unloading signal is triggered, it indicates that the previous sub-roll has completed production, and the production of the new sub-roll begins. The batch number of each sub-roll is often triggered before and after the unloading signal. For example, a display screen is provided on the production line, and the display screen displays an update button. The operator presses the update button to indicate the generation of a new batch number. If the operator presses the update button at the same time as the unloading signal is triggered, a new batch number is generated, indicating the start of the generation of a new sub-roll. Even if the time when the unloading signal is triggered and the time when the batch number is generated are the same, i.e., the first time and the second time are the same, since there is a certain distance between the thickness gauge and the unloading position, such as a distance of 10 meters, the thickness of the area corresponding to this distance in the master roll has been measured before the unloading signal is triggered. If the previous batch number is roll 1, i.e., the batch number of the sub-roll before the unloading signal is triggered is roll 1, then the thickness gauge data of the 10-meter-long area is used to measure the thickness and meter number of roll 1. However, in fact, the 10-meter-long area is used to produce roll 3, i.e., the sub-roll after roll 1 is roll 3, and the next batch number is roll 3. Therefore, the cloud device binds the thickness gauge data of the area of the master roll between the thickness gauge and the unloading position to the next batch number, i.e., the thickness gauge data of the 10-meter-long area is used to determine the thickness and meter number of roll 3.

[0078] In addition, the cloud device also deletes and re-splices the abnormal data of the thickness gauge, so as to ensure that the meter of the final obtained sub-roll is in an increasing form. For example, the meter is cleared after each update of the batch number. Assuming that the length of the sub-roll 1 is 990 meters. When the batch number is updated, there is a distance of 10 meters between the thickness gauge and the unloading position, and the 10 meters are the 991st meter, the 992nd meter, and so on. If no re-splicing is performed, the length of the next sub-roll, i.e., the roll 3, is marked as the 991st meter, the 992nd meter to the 1000th meter, and then the 1st meter, which is not in an increasing form. The cloud device converts the 991st meter, the 992nd meter to the 1000th meter into the 1st meter, the 2nd meter to the 10th meter, and the meter continues to increase.

[0079] Case two, the first time of the unloading signal is earlier than the second time of the corresponding batch number.

[0080] For each unloading signal, when the first time of the unloading signal is later than the second time of the corresponding batch number, the thickness gauge data of the piece area of the parent roll between the thickness gauge of the roller sub-machine at the first time and the unloading position, and the thickness gauge data measured by the thickness gauge between the first time and the second time are bound to the next batch number, so as to perform spatial alignment on the data set.

[0081] For example, the operation systems of different operators are different. Please refer to Figure 3A The thickness gauge is arranged at a position after the roller and before the slitting, and the thickness gauge has a first distance from the unloading position. After the unloading signal is triggered at the first time, a new batch number is generated by the operator at the second time after a period of time by clicking the screen or the like. Obviously, in addition to the thickness gauge data of the piece area of the parent roll between the thickness gauge and the unloading position being incorrectly used to determine the thickness and meter of the roll 1, the thickness gauge data of the thickness gauge between the first time and the second time is also incorrectly used to determine the thickness and meter of the roll 1. Therefore, the cloud device binds the thickness gauge data of the piece area of the parent roll between the thickness gauge and the unloading position to the next batch number, and binds the thickness gauge data measured by the thickness gauge between the first time and the second time to the next batch number. Continuing to take the distance of 10 meters between the thickness gauge and the unloading position as an example, the cloud device binds the thickness gauge data of the piece area corresponding to the 10 meters and the thickness gauge data of the piece area corresponding to the first time and the second time to the roll 3, which is used for measuring the thickness and meter of the roll 3, so as to perform spatial alignment on the data set.

[0082] Case three, for each unloading signal, when the first time of the unloading signal is earlier than the second time of the corresponding batch number, the thickness gauge data measured by the thickness gauge between the first time and the second time is bound to the previous batch number, so as to perform spatial alignment on the data set.

[0083] Please refer to Figure 3AThe thickness gauge is arranged at a position after the roll and before the slitting, and the thickness gauge has a first distance from the unloading position. An operator presses a button on the screen to update the batch number at a second time, at which time the winding machine has not completed winding. After a period of time, the time reaches the first time, the winding machine completes winding and triggers the unloading signal. If spatial alignment is not performed, the thickness gauge data from the second time to the first time and the current new batch number are used to determine the thickness and the number of meters of the sub-roll corresponding to the new batch number. In fact, the winding machine is winding the sub-roll corresponding to the previous batch number from the second time to the first time. Therefore, the cloud device binds the thickness gauge data measured by the thickness gauge between the first time and the second time to the previous batch number to perform spatial alignment on the data set

[0084] With this scheme, the cloud device performs spatial alignment on the data set according to the chronological relationship between the first time at which the unloading signal is triggered and the second time at which the new batch number is generated, and the distance between the thickness gauge and the unloading position, achieving the purpose of accuracy of spatial alignment.

[0085] Optionally, before the cloud device divides the data set in the above embodiment, the cloud device further determines first data and second data from the to-be-processed data included in the data set, and deletes the first data and the second data from the to-be-processed data. The first data and the second data are data submitted by the roll splitter to the edge device at the first frequency, and then submitted by the edge device to the cloud device at the first frequency. The first data is data repeatedly submitted by the roll splitter according to a preset frequency corresponding to a first sub-device, and the second data is independent data submitted by the roll splitter according to a preset frequency corresponding to a second sub-device. The preset frequency corresponding to the first sub-device is lower than the preset frequency corresponding to the second sub-device.

[0086] For example, the PLC of the roll splitter submits raw data to the edge device at a fixed second frequency. However, because the sub-devices of the roll splitter come from different manufacturers and have different acquisition frequencies, at some submission times, some sub-devices have the latest raw data and some sub-devices do not have the latest raw data. When such a submission time occurs, for the sub-devices that do not have the latest raw data, the PCL submits the raw data collected at the last time, thereby causing a situation of time dimension data misalignment. For example, refer to Table 1.

[0087] Table 1

[0088] Sub-device t1 t2 t3 t4 Sub-device a A1 A2 Sub-device b B1 B2 B3 B4

[0089] Please refer to Table 1, the frequency of the sub-device b is twice the frequency of the sub-device a, and the sub-device b collects original data at each of the t1-t4 time points, but the sub-device a only collects original data at the t2 and t4 time points. The PLC of the roll division machine determines that the t1-t4 time points are all the time points for submitting original data according to the second frequency. Therefore, at the t1 time point, B1 and the experience value A0 are submitted, at the t2 time point, A1 and B2 are submitted, at the t3 time point, A1 and B3 are submitted, and at the t4 time point, A2 and B4 are submitted. Among the four groups of data, B1 and A0 at the t1 time point are not original data collected at the same time, and A1 and B3 at the t3 time point are not original data collected at the same time. The cloud device deletes B1 and A0 at the t1 time point and A1 and B3 at the t3 time point, thereby time aligning the data set.

[0090] By adopting the scheme, the cloud device time aligns the data in the data set before dividing the data set, guarantees the event consistency of the data, and achieves the purpose of improving the data processing accuracy.

[0091] Optionally, in the above embodiment, in the process of reading the data set from the database by the cloud device according to the first frequency, whether the current time point is the time point for reading the data set is determined according to the second frequency. When the current time point is the time point for reading the data set, the cloud device determines a cutoff discharge signal, reads the to-be-processed data from the cutoff discharge signal until the nearest discharge signal to the current time point, and takes the sum of the to-be-processed data read from the cutoff discharge signal to the nearest discharge signal as the data in the data set. The cutoff discharge signal is the last discharge signal in the to-be-processed data contained in the last read historical set, and the discharge signal is used to indicate that a sub-roll has been collected.

[0092] In this application, since the PLC of the roll division machine submits original data to the edge device at the second frequency, the edge device submits to-be-processed data to the cloud device at the second frequency, the cloud device reads the data set from the database according to the second frequency for processing, and stores the thickness and meterage obtained after processing in the database. Since the first frequency is much smaller than the second frequency, and the triggering time point of the discharge signal and the generation time point of the batch number have uncertainty, the reading time point of the cloud device is not necessarily the triggering time point of the discharge signal, so as to ensure that the data set read this time can be connected with the data set read last time, and avoid missing data.

[0093] In the present application, the first frequency is, for example, 3 hours, 2 hours, etc. The cloud device monitors the current time in real time to determine whether it is a reading time. When the current time is not a reading time, the cloud device continues to monitor the current time. When the current time is a reading time, the cloud device determines the last unloading signal in the last data set read last time from the database, i.e., the cutoff unloading signal. For the sake of clarity, the last data set read last time is referred to as a history set. After determining the cutoff unloading signal, the cloud device reads the to-be-processed data from the cutoff unloading signal until the unloading signal closest to the current time is read. Between the unloading signal closest to the current time and the unloading signal closest to the current time, the cloud device reads a plurality of unloading signals. After reading the unloading signal closest to the current time, the cloud device marks the unloading signal closest to the current time as the cutoff unloading signal and caches it, so as to facilitate quick and accurate determination of the cutoff unloading signal when reading the data set next time.

[0094] With this scheme, the cloud device marks the unloading signal closest to the current time in the data set as the cutoff unloading signal after reading the data set each time, which facilitates reading next time and ensures the continuity of adjacent two readings and further ensures the continuity of data processing.

[0095] The following is an embodiment of the device of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the method embodiment of the present application.

[0096] Figure 4 An example of a data processing device provided by the present application is shown in the figure. The data processing device 400 comprises a reading module 41, a division module 42 and a processing module 43.

[0097] The reading module 41 is configured to read a data set from a database according to a first frequency, wherein the database stores to-be-processed data submitted by an edge device at a second frequency, the to-be-processed data is obtained by the edge device by preprocessing raw data from a roll division machine, and the raw data is data updated by each sub-device of the roll division machine according to a corresponding preset frequency during the process of dividing a parent roll into sub-rolls.

[0098] The division module 42 is configured to divide the data set to obtain a plurality of batch data, each batch data containing to-be-processed data located between two adjacent unloading signals, different unloading signals corresponding to different batch numbers, and different batch numbers being used to identify different sub-rolls, and the raw data containing the unloading signals.

[0099] The processing module 43 is configured to determine the thickness and the number of meters of a sub-roll according to each batch data in the plurality of batch data.

[0100] In an implementation, the dividing module 42 is configured to determine a target queue according to the data to be processed in the data set, the target queue comprising a plurality of unloading signals with time stamps in ascending order; and divide the data set according to each two adjacent unloading signals in the target queue to obtain a plurality of batch data.

[0101] In an implementation, before the dividing module 42 divides the data set, the processing module 43 is further configured to determine a plurality of first time points and a plurality of second time points according to the data set, the plurality of first time points being time points at which each unloading signal in the data set is triggered, and the plurality of second time points being time points at which each batch number in the data set is generated, each unloading signal corresponding to one batch number; and perform spatial alignment on the data set according to the plurality of first time points and the plurality of second time points.

[0102] In an implementation, when the processing module 43 performs spatial alignment on the data set according to the plurality of first time points and the plurality of second time points, for each unloading signal, when the first time point of the unloading signal is the same as the second time point of the corresponding batch number, the processing module 43 binds the thickness gauge data of the piece area of the parent roll between the thickness gauge of the roll dividing machine and the unloading position to the next batch number to perform spatial alignment on the data set, the unloading position being a position at which the sub-roll is collected; for each unloading signal, when the first time point of the unloading signal is earlier than the second time point of the corresponding batch number, the processing module 43 binds the thickness gauge data of the piece area of the parent roll between the thickness gauge of the roll dividing machine and the unloading position at the first time point, and the thickness gauge data measured by the thickness gauge between the first time point and the second time point to the next batch number to perform spatial alignment on the data set; for each unloading signal, when the first time point of the unloading signal is later than the second time point of the corresponding batch number, the processing module 43 binds the thickness gauge data measured by the thickness gauge between the first time point and the second time point to the previous batch number to perform spatial alignment on the data set.

[0103] In an implementation, the processing module 43 is configured to, for each batch data in the plurality of batch data, split the thickness gauge data in the batch data according to the target number of sub-rolls cut by the roll dividing machine to obtain a target number of sub-data; and determine the thickness and the meter number of the corresponding sub-roll according to each sub-data in the target number of sub-data to obtain the thickness and the meter number of a target number of sub-rolls.

[0104] In an implementation, before the processing module 43 determines the thickness and the meter number of the corresponding sub-roll according to each sub-data in the target number of sub-data, the processing module 43 is further configured to, when there is a blind area in the sub-data, interpolate the blind area according to the front and rear areas of the blind area in the sub-data.

[0105] In a possible implementation, before the division module 42 divides the data set, the processing module 43 is further configured to determine first data and second data from the to-be-processed data contained in the data set, the first data and the second data being data submitted by the roll machine to the edge device at the first frequency and submitted by the edge device to the cloud device at the first frequency, the first data being data repeatedly submitted by the roll machine according to a preset frequency corresponding to a first sub-device, the second data being independent data submitted by the roll machine according to a preset frequency corresponding to a second sub-device, the preset frequency corresponding to the first sub-device being lower than the preset frequency corresponding to the second sub-device; and the first data and the second data are deleted from the to-be-processed data.

[0106] In a possible implementation, when the reading module 41 reads the data set from the database according to the first frequency, the reading module 41 is configured to determine whether the current time is a time for reading the data set according to the second frequency; when the current time is the time for reading the data set, a last unloading signal in to-be-processed data contained in a historical set read last time is determined as a stop unloading signal, the unloading signal being used to indicate that a sub-volume has been collected; and to-be-processed data starting from the stop unloading signal is read until a nearest unloading signal to the current time is read, and a sum of to-be-processed data read in a time period from the stop unloading signal to the nearest unloading signal is taken as data in the data set.

[0107] The data processing apparatus provided in the application can perform the action of the cloud device in the above-described embodiments, and has similar implementation principles and technical effects, which will not be described here again.

[0108] Figure 5 A structural schematic diagram of an electronic device provided in the application is shown. The electronic device 500 includes:

[0109] a processor 51 and a memory 52;

[0110] The memory 52 stores computer instructions;

[0111] The processor 51 executes the computer instructions stored in the memory 52, so that the processor 51 performs the data processing method as described above.

[0112] The specific implementation process of the processor 51 can refer to the above-described method embodiments, and has similar implementation principles and technical effects, which will not be described here again in this embodiment.

[0113] Optionally, the electronic device 500 further includes a communication component 53. The processor 51, the memory 52, and the communication component 53 can be connected through a bus 54.

[0114] The application further provides a computer readable storage medium, wherein computer instructions are stored in the computer readable storage medium, and the computer instructions are used to implement the data processing method when executed by a processor.

[0115] The application further provides a computer program product, wherein the computer program product comprises a computer program, and the computer program is used to implement the data processing method when executed by a processor.

[0116] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0117] It should be understood that the application is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, Applied to cloud devices, the method includes: A data set is read from the database at a first frequency. The database stores data to be processed submitted by the edge device at a second frequency. The data to be processed is obtained by the edge device through preprocessing of the raw data from the roll separator. The raw data is the data updated by each sub-device of the roll separator at a corresponding preset frequency during the process of the roll separator separating the mother roll into sub-rolls. The data set is divided to obtain multiple batches of data. Each batch of data contains data to be processed located between two adjacent feeding signals. Different feeding signals correspond to different batch numbers. Different batch numbers are used to identify different sub-volumes. The original data includes the feeding signals. Based on each of the multiple batches of data, determine the thickness and length in meters of the sub-roll.

2. The method according to claim 1, characterized in that, The process of dividing the data set to obtain multiple batches of data includes: The target queue is determined based on the data to be processed contained in the data set, and the target queue contains multiple feeding signals with sequentially increasing timestamps; The data set is divided according to each pair of adjacent feeding signals in the target queue to obtain multiple batches of data.

3. The method according to claim 1, characterized in that, Before partitioning the data set, the method further includes: Multiple first moments and multiple second moments are determined based on the data set. The multiple first moments are the times when each feeding signal in the data set is triggered, and the multiple second moments are the times when each batch number in the data set is generated. The feeding signal corresponds one-to-one with the batch number. Spatial alignment is performed on the data set based on the plurality of first time points and the plurality of second time points.

4. The method according to claim 3, characterized in that, The step of performing spatial alignment on the data set based on the plurality of first time points and the plurality of second time points includes: For each feeding signal, when the first moment of the feeding signal is the same as the second moment of the corresponding batch number, the thickness gauge data of the area of ​​the mother roll between the thickness gauge of the roll separator and the feeding position is bound to the next batch number to perform spatial alignment on the data set, where the feeding position is the position where the sub-roll is collected; For each feeding signal, when the first moment of the feeding signal is earlier than the second moment of the corresponding batch number, the thickness gauge data of the area of ​​the master roll between the thickness gauge of the roll separator and the feeding position at the first moment, as well as the thickness gauge data measured by the thickness gauge between the first moment and the second moment, are bound to the next batch number to perform spatial alignment on the data set. For each feeding signal, when the first moment of the feeding signal is later than the second moment of the corresponding batch number, the thickness gauge data measured by the thickness gauge between the first moment and the second moment is bound to the previous batch number to perform spatial alignment on the data set.

5. The method according to any one of claims 1 to 4, characterized in that, The step of determining the thickness and length in meters of the sub-roll based on each batch of data from the plurality of batches includes: For each batch of data in the plurality of batch data, the thickness gauge data in the batch data is split according to the target number of sub-rolls cut out by the roll splitter to obtain the target number of sub-data. Based on each sub-data in the target number of sub-data, determine the thickness and length in meters of the corresponding sub-roll to obtain the thickness and length in meters of the target number of sub-rolls.

6. The method according to claim 5, characterized in that, Before determining the thickness and length in meters of the corresponding sub-roll based on each sub-data in the target quantity of sub-data, the method further includes: When a blind zone exists in the sub-data, the blind zone is interpolated based on the regions before and after the blind zone in the sub-data.

7. The method according to any one of claims 1 to 4, characterized in that, Before partitioning the data set, the method further includes: First data and second data are determined from the data to be processed contained in the data set. The first data and the second data are data submitted by the roller separator to the edge device at the first frequency and then submitted by the edge device to the cloud device at the first frequency. The first data is data repeatedly submitted by the roller separator according to the preset frequency corresponding to the first sub-device. The second data is independent data submitted by the roller separator according to the preset frequency corresponding to the second sub-device. The preset frequency corresponding to the first sub-device is lower than the preset frequency corresponding to the second sub-device. Delete the first and second data from the data to be processed.

8. The method according to any one of claims 1 to 4, characterized in that, The step of reading a data set from the database according to a first frequency includes: Determine whether the current time is the time to read the data set based on the second frequency; When the current time is the time to read the data set, a cutoff signal is determined. The cutoff signal is the last cutoff signal in the pending data contained in the last read historical set. The cutoff signal is used to indicate that a sub-volume has been collected. Starting from the cutoff feeding signal, data to be processed is read until the feeding signal closest to the current time is read. The sum of the data to be processed read from the cutoff feeding signal to the cutoff time period when the closest feeding signal is read is used as the data in the data set.

9. An electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it causes the electronic device to implement the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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