Real-time processing method, device and equipment for industrial processing process data and medium

Abstract

The invention provides a real-time processing method and device for industrial processing process data, equipment and a medium. The method comprises the following steps: configuring a filtering condition of a batch processing data pushing system; based on production task pushing of the batch processing data pushing system, operation starting data is pushed when industrial processing operation starts, and operation final state data is pushed when the operation ends; configuring a timed task based on the filtering condition, and collecting real-time data of charging and output according to a preset time interval; when the operation final state data is received, the collected real-time data of feeding and output are summarized, and the feeding amount and the output amount are calculated based on the initial parameter value and the termination parameter value; and the collected real-time data is stored in a historical database, and the real-time data, the feeding amount and the output amount are displayed in real time through a visual interface. According to the invention, feeding and output data can be fed back more efficiently and flexibly in real time, and the data processing efficiency and real-time performance of the industrial processing process are improved.

Description

Technical Field

[0001] The present application relates to the field of industrial automation technology, and in particular to a method, device, equipment and medium for real-time processing of industrial processing data. Background Art

[0002] Industrial processing data is used to display quantitative or qualitative data affected by time, working conditions and operating conditions during industrial manufacturing, testing and operation. These data include physical parameters such as processing temperature, humidity, pressure, flow, feeding and output that change over time, as well as information such as system monitoring, alarms, equipment maintenance and care. These real-time industrial data are crucial to the monitoring and optimization of the production process, and directly affect product quality and production efficiency.

[0003] In the prior art, SCADA, PLC, DCS and other hardware and software integrated systems are usually used to collect real-time data from industrial sites. The MOM (manufacturing operation management) system collects instantaneous data through data acquisition tools and compiles them into a real-time database. The data in the real-time library is regularly transferred to the historical library for long-term storage and analysis. These data are filtered and processed by real-time data to form feedback data on feeding and output, showing the real-time status of the industrial processing process. However, there are still problems in the prior art such as insufficient real-time data, high complexity of data processing, and poor flexibility. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a method, device, equipment and medium for real-time processing of industrial process data to solve the problems of insufficient data real-time performance, high data processing complexity and poor flexibility in the prior art.

[0005] According to a first aspect of an embodiment of the present application, a method for real-time processing of industrial processing data is provided, comprising: in an industrial processing control system, configuring filtering conditions for a batch data push system, wherein the filtering conditions include input point parameter names and output point parameter names; based on the production task push of the batch data push system, pushing operation start data at the start of the industrial processing operation, and pushing operation final state data at the end of the operation; configuring a scheduled task based on the filtering conditions, and starting the scheduled task after the start of the industrial processing operation, collecting real-time data of feeding and output at preset time intervals; when the final state data of the operation is received, stopping the scheduled task, summarizing the collected real-time data of feeding and output, and calculating the feeding amount and output amount based on the starting parameter value and the ending parameter value; storing the summarized real-time data in a historical database, and displaying the real-time data, feeding amount and output amount in real time through a visual interface.

[0006] According to a second aspect of an embodiment of the present application, there is provided a real-time processing device for industrial processing process data, comprising: a configuration module, configured to configure filtering conditions of a batch data push system in an industrial processing control system, wherein the filtering conditions include input point parameter names and output point parameter names; a push module, configured to push production tasks based on the batch data push system, push operation start data at the start of the industrial processing operation, and push operation final state data at the end of the operation; a collection module, configured to configure a scheduled task based on the filtering conditions, and start the scheduled task after the start of the industrial processing operation, and collect real-time data of feeding and output at preset time intervals; a summary module, configured to stop the scheduled task when receiving the final state data of the operation, summarize the collected real-time data of feeding and output, and calculate the feeding amount and output amount based on the starting parameter value and the ending parameter value; a display module, configured to store the summarized real-time data in a historical database, and display the real-time data, feeding amount and output amount in real time through a visual interface.

[0007] According to a third aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the processor executes the computer program.

[0008] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0009] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0010] By configuring the filtering conditions of the batch data push system in the industrial processing control system, wherein the filtering conditions include the input point parameter name and the output point parameter name; based on the production task push of the batch data push system, the operation start data is pushed at the beginning of the industrial processing operation, and the operation final state data is pushed at the end of the operation; the timing task is configured based on the filtering conditions, and the timing task is started after the industrial processing operation starts, and the real-time data of feeding and output are collected at preset time intervals; when the operation final state data is received, the timing task is stopped, the collected real-time data of feeding and output are summarized, and the feeding amount and output amount are calculated based on the starting parameter value and the ending parameter value; the summarized real-time data is stored in the historical database, and the real-time data, feeding amount and output amount are displayed in real time through a visual interface. The present application can more efficiently, flexibly and in real time feedback the feeding and output data, and improve the data processing efficiency and real-time performance of the industrial processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 It is a flow chart of a method for real-time processing of industrial process data provided by an embodiment of the present application;

[0013] Figure 2 is a schematic diagram of the structure of a real-time processing device for industrial processing data provided by an embodiment of the present application;

[0014] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0016] In industrial manufacturing, especially in the fine chemical industry, many physical parameters (such as temperature, humidity, pressure, flow, etc.) need to be monitored and controlled during industrial processing. These parameters directly affect the final processing quality and output efficiency. Therefore, in industrial scenarios, it is very important to collect and analyze these processing data. Specifically, industrial processing data mainly includes physical parameters (such as temperature, humidity, flow, etc.), system monitoring and alarms (to ensure normal equipment and operation), and equipment maintenance and maintenance data.

[0017] These data are usually collected through various automation systems at industrial sites (such as SCADA, PLC, DCS systems, etc.). These systems can collect data from various sensors and equipment in real time, and ensure the smooth progress of the processing through control and monitoring systems.

[0018] Current systems, such as MOM (Manufacturing Operations Management) systems, collect and process industrial real-time data by integrating different data collection tools. Although existing systems can provide real-time data collection and display functions, the following problems still exist:

[0019] Data update lag: Since the data processing process involves scheduled tasks and transfer steps, real-time performance will be delayed. Especially for the fine chemical industry that requires precise control, any data lag may affect product quality.

[0020] Lack of flexibility: The parameter rules in the current system need to be manually set in advance, and there is no automatic optimization function. If the production conditions or processes change, the system needs to be manually adjusted, which is inefficient.

[0021] High data processing complexity: The system relies on multi-level data filtering and processing. Although it can achieve the final data display, the entire process is relatively complicated, which may lead to increased operation and maintenance costs.

[0022] Therefore, there is still room for improvement in existing technologies in improving real-time data feedback in the fine chemical industry, especially in terms of how to improve the real-time performance of data processing, simplify operating procedures, and enhance the automation and intelligence of the system.

[0023] In view of the problems existing in the prior art, the present application proposes an improved method for industrial automation data collection and display. The present application can complete the collection and summary display of real-time data of industrial processing through simple operations. The main contents of the technical solution of the present application include control system parameter setting, Batch push data filtering, scheduled task data collection, data processing calculation and data display. Among them, the control system setting and Batch push data filtering can associate the data collection tag to a collection point with equipment. The data collection process, Batch push, and DCS mentioned in this application are only used as media and tools for collecting data and are not within the scope of discussion of this application.

[0024] Figure 1 Schematic diagram of the process flow of the real-time processing method of industrial process data provided by the embodiment of the present application. Figure 1 As shown, the real-time processing method of industrial processing data may specifically include:

[0025] S101, in the industrial process control system, configuring filtering conditions for the batch data push system, wherein the filtering conditions include input point parameter names and output point parameter names;

[0026] S102, pushing production tasks based on the batch processing data push system, pushing operation start data at the beginning of the industrial processing operation, and pushing operation final state data at the end of the operation;

[0027] S103, configuring a scheduled task based on the filtering conditions, and starting the scheduled task after the industrial processing operation starts, collecting real-time data of feeding and output at preset time intervals;

[0028] S104, when the final operation state data is received, the scheduled task is stopped, the collected real-time data of feeding and output are summarized, and the feeding amount and output amount are calculated based on the starting parameter value and the ending parameter value;

[0029] S105, storing the aggregated real-time data in a historical database, and displaying the real-time data, feed amount, and output amount in real time through a visual interface.

[0030] In some embodiments, in an industrial process control system, configuring control parameters for feeding and output includes:

[0031] In industrial process control systems, the control system settings are used to configure the input point parameter names in the feeding process and the output point parameter names in the output process. The input point parameter names are used to identify the key data points at the beginning of feeding, and the output point parameter names are used to identify the key data points at the beginning or end of output.

[0032] Specifically, in the industrial process control system, the parameters for the feeding process and the output process are configured through the control system setting entry of the MOM system. Specifically, the control parameters of the system include the input point parameter name and the output point parameter name.

[0033] Furthermore, the input point parameter name is used to identify the key data point at the start of feeding. Through the control interface of the MOM system, the user can enter or select the MACS point parameter name representing the start of feeding, which is associated with the specific collection point of the industrial processing equipment. For example, in the feeding operation, the system obtains the physical data (such as flow rate, pressure, etc.) at the start of feeding through the specific sensor of the monitoring equipment, and the data is transmitted to the control system through the corresponding input point parameter name for further processing and feedback.

[0034] Furthermore, the output point parameter name is used to identify the key data points of the output process, which usually represent the start or end status of the output operation. Similarly, through the control interface of the MOM system, users can configure or select the MACS point parameter names for the output process. These parameter names are used to monitor the status data of the output equipment, such as the weight or volume of the output material. Through these key points, the system can accurately identify the start and end of the output process.

[0035] Furthermore, while configuring the control parameters, the MOM system also allows users to set filtering conditions for Batch push data. Key constraints include the parameter names of input points and output points. These filtering conditions ensure that when the system receives the data pushed by Batch, it can automatically match the corresponding feeding and output operations and accurately obtain the required real-time data. For example, when the Batch system pushes information containing the start of the feeding operation, the system will automatically identify the start of the feeding process based on the previously configured input point parameter name and start the corresponding scheduled task for data collection.

[0036] Through the above configuration method, the industrial processing control system can accurately and flexibly configure the control parameters for feeding and output, and through the set filtering conditions, ensure that the MOM system can monitor and process key data from the Batch system in real time. This method simplifies data collection and management in the industrial processing process and improves the real-time nature and processing efficiency of data.

[0037] In some embodiments, configuring a scheduled task based on a filtering condition includes:

[0038] The industrial processing control system receives the operation start data pushed by the batch data push system, and matches the parameter names of feeding and output according to the filtering conditions;

[0039] After the parameter names are matched, determine whether the feeding parameters and output parameters meet the filtering conditions. If they meet the conditions, extract the corresponding collection label points from the feeding parameters and output parameters;

[0040] Add the collection tag points to the scheduled task queue and configure the scheduled task according to the preset time interval. The scheduled task is used to regularly collect real-time data of feeding and output.

[0041] Specifically, when the batch data push system (Batch system) pushes the production task to start, it will transmit the operation data related to feeding and output to the industrial process control system. The specific operation process is as follows:

[0042] First, when the batch data push system issues a production task for feeding or output, the Batch system will first push a message containing the operation start data, which carries the parameter names related to the processing process. These parameter names include the input point parameter names for the feeding process and the output point parameter names for the output process.

[0043] Furthermore, after receiving the operation start data, the industrial process control system will match the received parameter names according to the preset filtering conditions. The filtering conditions are pre-set and include specific feeding and output parameter names. The system compares the parameter names in the operation start data to determine whether these parameters meet the filtering conditions.

[0044] Furthermore, when the parameter name matches successfully and meets the filtering conditions, the system extracts the corresponding collection tag points from the feeding parameters and output parameters. These collection tag points correspond to key data points in the feeding and output processes, such as monitoring the flow rate and pressure during feeding and the weight or volume during output.

[0045] Furthermore, the extracted collection tag points will be automatically added to the scheduled task queue. The scheduled task queue pre-sets the frequency of data collection, usually at a fixed time interval (such as once every 5 minutes). These tasks will be executed regularly after the feeding and output processes start to ensure real-time data collection.

[0046] Furthermore, after the scheduled task is started, the system will periodically obtain the real-time data of feeding and output from the collection tag points according to the preset time interval. For example, the system will collect the real-time flow value of feeding every 5 minutes, or monitor the real-time weight during the output process. The collected data is stored in the real-time database for subsequent aggregation, calculation and analysis.

[0047] Furthermore, when the Batch system pushes the final state data of the operation (such as the completion, stop or abandonment of the production task), the industrial process control system will stop the scheduled tasks associated with the task and end the collection operation of the feeding and output data.

[0048] Through the above method of this embodiment, the industrial processing control system in the embodiment of this application can automatically configure the timing task and perform efficient feeding and output data collection based on the real-time data of the batch data push system and the preset filtering conditions. This method not only ensures the accuracy of data collection, but also improves the system's responsiveness to the industrial processing process and data processing efficiency.

[0049] In some embodiments, after the industrial processing operation begins, a timer task is started to collect real-time data of feeding and output at preset time intervals, including:

[0050] After the industrial processing operation begins, the timing task is started to obtain the real-time data of feeding and output from the collection tag point at a preset time interval, and the real-time data is stored in the real-time database;

[0051] At the end of the industrial processing operation, the scheduled task is stopped according to the final state data of the operation, and the real-time data collection operation of the collection tag points is ended.

[0052] Specifically, the present application proposes a method for starting a timed task after the start of an industrial processing operation to collect real-time data on feeding and output at preset time intervals, so as to ensure the real-time and accuracy of data collection during the industrial production process. This embodiment describes in detail how to obtain real-time data from a collection tag point through a timed task and stop the task after the operation is completed.

[0053] When an industrial processing operation starts, the batch data push system (Batch system) pushes information containing the operation start data. After receiving the information, the industrial processing control system starts the preset timer task. The timer task identifies the relevant parameters of feeding and output, especially the corresponding collection tag points, based on the data filtering conditions pushed by the Batch system. At this point, the timer task officially enters the execution state.

[0054] After the scheduled task is started, the system obtains real-time data of feeding and output from the specified collection tag points at a preset time interval (the default setting is once every 5 minutes). The collected data points may include flow, temperature, pressure, etc. during the feeding process, and physical parameters such as weight or output during the output process. For example, if the feeding operation starts, the system collects data from related sensors every 5 minutes to record the changes in the current feeding amount.

[0055] Each collected real-time data of feeding and output will be immediately stored in the real-time database of the industrial process control system. This process ensures that all key data points are recorded in a timely and accurate manner for subsequent data processing, analysis and display. For example, the system can gradually accumulate the data of each time point of feeding and output in the real-time database and calculate and process it.

[0056] When the industrial processing operation is completed, the Batch system will push the final state data of the operation, such as the operation is completed, abandoned or stopped. The industrial processing control system determines that the current task has been completed based on the final state data and then stops the scheduled task operation. At this time, the system will stop the real-time data collection operation of the collection tag points and end all data collection activities of the current task.

[0057] After the scheduled task stops, the system will summarize and store the real-time data of the entire feeding and output process to ensure that the complete feeding and output process data is included in the historical database for subsequent query and analysis.

[0058] For example, when the Batch system pushes data indicating that the feeding operation is completed, the MOM system will stop the scheduled task based on the last data collection result and end the real-time data collection of feeding and output. If the data pushed by Batch indicates that the operation is not completed or has been aborted, the system will adjust the data processing flow based on the actual status to ensure the accuracy of data collection.

[0059] Through the method of the above-mentioned embodiment, the present application can effectively realize the real-time collection and storage of feeding and output data in the industrial processing process, ensure the real-time, completeness and accuracy of data collection, and automatically stop the scheduled task after the operation is completed, avoiding unnecessary data collection operations.

[0060] In some embodiments, the method further comprises:

[0061] During the running of the scheduled task, when it is determined that the real-time data collected at two consecutive time points are the same, the storage operation of the real-time data at the current time point is skipped. When it is determined that no real-time data is obtained at any time point, the real-time data collected at the previous time point is used to complete the real-time data at the current time point.

[0062] Specifically, this embodiment also proposes a method for data optimization and fault-tolerant processing during the running of a scheduled task to improve the efficiency of data collection and ensure the integrity of the data. This method is suitable for real-time data collection in industrial processing, especially in the real-time data collection process of feeding and output, the system performs redundant control and fault-tolerant processing on the collected data.

[0063] During industrial processing operations, the timing task obtains real-time data of feeding and output from the collection tag point at a preset time interval (such as every 5 minutes). Real-time data includes key physical parameters such as feeding flow, pressure or output weight.

[0064] After each data collection of the scheduled task, the system will compare the data collected at the current time point with the data at the previous time point. If the real-time data collected at two consecutive time points are the same, the system will assume that the data has not changed, and skip the storage operation of the data at the current time point. For example, if the feed flow data collected at two time points is 450L / min, the system will skip the current storage operation to avoid redundant storage of duplicate data. This mechanism can effectively reduce the burden of data storage and prevent excessive expansion of the database.

[0065] During the running of scheduled tasks, there may be situations where real-time data cannot be successfully obtained at certain time points. In order to ensure the continuity and integrity of the data, when the system detects data missing, it will use the data successfully collected at the previous time point to fill the data at the current time point. For example, if the feed amount data cannot be obtained at a certain time point, the system will use the feed amount data collected at the previous time point to fill it, so as to ensure the integrity of data collection and the consistency of analysis.

[0066] For valid data that is not skipped, the system stores it in a real-time database to ensure that key feeding and output data can be accurately recorded and summarized. After the operation is completed, the system will further process and analyze the data of the entire feeding and output process. These data will be used for subsequent aggregation, calculation or historical query.

[0067] Through the method of the present embodiment described above, the system reduces the amount of invalid data stored, optimizes storage efficiency, and enhances the fault tolerance of the system while ensuring data integrity, especially when occasional failures occur during data collection, the reliability and continuity of the data can be ensured. The data optimization and fault-tolerant processing method in the above embodiment can effectively improve the efficiency of data collection in industrial processing and ensure that the collected feeding and output data have sufficient accuracy and continuity during analysis.

[0068] In some embodiments, the collected real-time data of feeding and output are summarized, and the feeding amount and output amount are calculated based on the starting parameter value and the ending parameter value, including:

[0069] According to the preset timed tasks, the real-time data of feeding and output are collected regularly, where the real-time data includes the starting parameter value and the ending parameter value during the feeding process;

[0070] When the feeding process and the output process are finished, the collected real-time data are grouped and summarized, and the real-time data of the feeding process and the output process are processed respectively;

[0071] For each set of real-time data, the feeding amount is calculated based on the starting parameter value and the ending parameter value of the feeding process, and the output amount is calculated based on the starting parameter value and the ending parameter value of the output process.

[0072] Specifically, this embodiment also proposes a method for summarizing the collected real-time data of feeding and output, and calculating the feeding amount and output amount based on the starting parameter value and the ending parameter value. This embodiment describes in detail how to collect data regularly through a scheduled task, and group, summarize and calculate the collected data to ensure accurate recording and feedback of feeding and output.

[0073] According to the preset timing task, the industrial processing control system regularly obtains real-time data from the collection tag points of feeding and output. The data collected each time includes the starting parameter value and the ending parameter value during the feeding process, as well as the intermediate parameter values ​​at the interval time point. For example, if the timing task is set to collect data every 5 minutes, the system will regularly record the real-time values ​​of the feeding operation. Assume that in a certain feeding operation, the real-time data collected is shown in Table 1 below.

[0074] Table 1 Real-time data table of feeding operation

[0075]

[0076] At the end of the feeding and output process, the industrial process control system determines that the operation is completed based on the final state data. At this time, the system groups the collected real-time data and summarizes the data of the feeding process and the output process respectively. For example, in the above feeding operation, the system summarizes the real-time data in chronological order and prepares to calculate the feeding amount.

[0077] For each set of feeding data, the system calculates the feeding amount based on the starting parameter value and the ending parameter value of the feeding process. The formula is: feeding amount = ending parameter value - starting parameter value. For example, in this embodiment, the feeding amount is calculated as: 975-0 = 975, that is, the total feeding amount of this feeding operation is 975 units (for example, 975 liters or kilograms).

[0078] Similar to the feeding process, the system also summarizes and calculates the data of the output process. Based on the starting parameter value and the ending parameter value of the output process, the output is calculated according to the formula. The calculation method of the output is the same as the feeding amount, and the final output is obtained by subtracting the starting value from the ending value.

[0079] After completing the calculation of the feeding amount and output, the system will store the summarized data in the historical database. These data can be displayed in real time through the visual interface. The operator can view the specific data of each feeding and output, as well as the calculated feeding amount and output, which is convenient for production monitoring and decision-making.

[0080] Through the method of the present embodiment described above, the system can accurately and efficiently collect and process real-time data during the feeding and output process, and calculate the specific feeding amount and output amount based on the start and end parameter values. This implementation method not only ensures the real-time and accuracy of the data, but also provides strong data support for subsequent production analysis.

[0081] In some embodiments, the aggregated real-time data is stored in a historical database, and the real-time data, feed amount, and output amount are displayed in real time through a visual interface, including:

[0082] The feeding amount and output amount are stored in the historical database respectively, and query operations with different conditions are set for the data in the historical database; the real-time data, feeding amount and output amount of the feeding and output process are visualized, and the visualized data are displayed in the interface of the industrial process control system.

[0083] Specifically, this embodiment also proposes a method for storing the aggregated feed amount and output amount in a historical database and displaying them in real time through a visual interface. This embodiment describes in detail how to store, query and display the feed and output data to ensure that operators can intuitively obtain key data in the industrial processing process.

[0084] When the industrial process control system completes the calculation of the feeding amount and output amount, the system will store these summarized real-time data in the historical database. The data storage includes the real-time data of each time point in the feeding process and the output process, as well as the final calculated feeding amount and output amount. For example, in a certain feeding operation, the system will store the feeding data collected at each time and the total feeding amount (such as 975 units) in the historical database.

[0085] Furthermore, in order to facilitate operators to query and analyze historical data, the system provides a variety of query conditions for the historical database. For example, users can search for data based on specific time periods, feed amounts, or output amounts. Operators can flexibly set query parameters through the query interface of the industrial process control system to retrieve feed and output records in any time period in the past. In this way, historical data can be conveniently used for production analysis, process optimization, or quality tracking.

[0086] Furthermore, the system will visualize the real-time data, feeding amount and output of the feeding and output process. The visualization methods include charts, curves or bar charts, and operators can use these visualization graphics to intuitively view the dynamic changes of the feeding and output process. For example, the system can generate a curve chart of the feeding amount over time, showing the real-time value and the final result value of the feeding process. The real-time data of the output process can also be displayed in a similar way to help operators monitor the entire production process.

[0087] Furthermore, as industrial processing operations are being performed, the system will display the current feeding and output data in real time through a visual interface. After each collection cycle, new data points will be added to the graph to reflect the current production progress in real time. For example, the operator can observe the change of feeding operations from 0 to 975 units through the interface, and can see the real-time feeding amount at each time point. The change process of output volume is also displayed in real time through the interface.

[0088] Furthermore, the system interface provides users with an intuitive and interactive operation experience. Operators can choose different data display methods (such as real-time curves, historical trend charts, etc.), and view the corresponding data changes by adjusting query conditions or selecting different production batches. The system also provides real-time feedback on key data of feeding and output, helping operators to adjust process parameters in a timely manner to optimize the production process.

[0089] Through the above method of this embodiment, this embodiment can ensure that the key data of feeding and output are collected, summarized and stored in real time, and intuitively presented to the operator in a graphical manner. This not only helps to monitor the production process in real time, but also provides historical data for subsequent analysis and optimization, effectively improving the transparency and management efficiency of industrial processing.

[0090] According to the technical solution provided in the embodiment of the present application, the present application provides a method for displaying real-time feedback and display of feeding and output data in industrial processing, which significantly improves the efficiency of data monitoring and analysis in industrial processing through effective collection, processing and display of real-time data. The technical solution of the present application has at least the following advantages:

[0091] 1. Through the combination of batch data push system and scheduled tasks, accurate real-time collection of feeding and output data can be achieved. Data push at the start and end of the operation ensures that the system can accurately obtain the real-time parameters of feeding and output at key nodes, and continuously collect data according to the preset time interval, which improves the real-time performance of data processing.

[0092] 2. The system automatically groups and summarizes the collected feeding and output data, and calculates the feeding amount and output amount through the starting parameter value and the ending parameter value. This automated calculation process reduces human intervention, improves the efficiency and accuracy of data processing, and ensures real-time tracking of key data in the production process.

[0093] 3. The aggregated feed amount and output data are stored in the historical database, and a multi-condition query function is provided, allowing users to flexibly retrieve historical data by time, feed amount, output, etc. This data management method enhances the system's traceability of historical data and provides basic support for subsequent production analysis and process optimization.

[0094] 4. Through the visual interface, the process data and calculation results of feeding and output are displayed in real time, and the operator can intuitively observe the real-time data points and their changing trends of each collection cycle. The dynamic display of feeding amount and output amount makes the changes in production status clear at a glance, which helps the operator to adjust the process parameters in time and optimize production efficiency.

[0095] 5. The system has redundant data processing and data missing compensation mechanisms, which can effectively avoid the storage of duplicate data and automatically fill in missing data when data collection is abnormal, ensuring data integrity and consistency. This fault-tolerant mechanism improves the stability and reliability of the system.

[0096] Therefore, in summary, this application enables the key data of feeding and output to be efficiently monitored and managed throughout the entire industrial processing process through interface display and real-time feedback, thereby maximizing the value of industrial processing data, improving the intelligence level of data collection and processing, and at the same time improving the accuracy and response speed of production management.

[0097] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0098] Figure 2 Schematic diagram of the structure of the real-time processing device for industrial processing data provided by the embodiment of the present application. Figure 2 As shown, the real-time processing device for industrial processing data includes:

[0099] The configuration module 201 is configured to configure the filtering conditions of the batch data push system in the industrial process control system, wherein the filtering conditions include the input point parameter name and the output point parameter name;

[0100] The push module 202 is configured to push production tasks based on the batch data push system, push operation start data when the industrial processing operation starts, and push operation final state data when the operation ends;

[0101] The collection module 203 is configured to configure a scheduled task based on the filtering conditions, and start the scheduled task after the industrial processing operation starts, and collect the real-time data of feeding and output at a preset time interval;

[0102] The summarization module 204 is configured to stop the scheduled task when receiving the final operation state data, summarize the collected real-time data of feeding and output, and calculate the feeding amount and output amount based on the starting parameter value and the ending parameter value;

[0103] The display module 205 is configured to store the aggregated real-time data in a historical database, and to display the real-time data, feed amount and output amount in real time through a visual interface.

[0104] In some embodiments, Figure 2 The configuration module 201 in the industrial process control system uses the control system settings to configure the input point parameter name in the feeding process and the output point parameter name in the output process, wherein the input point parameter name is used to identify the key data point at the beginning of feeding, and the output point parameter name is used to identify the key data point at the beginning or end of output.

[0105] In some embodiments, Figure 2The collection module 203 uses the industrial processing control system to receive the operation start data pushed by the batch data push system, and matches the parameter names of feeding and output according to the filtering conditions; after the parameter names are matched, it is determined whether the feeding parameters and the output parameters meet the filtering conditions. If they meet the conditions, the corresponding collection label points are extracted from the feeding parameters and the output parameters; the collection label points are added to the scheduled task queue, and the scheduled tasks are configured according to the preset time interval. The scheduled tasks are used to regularly collect real-time data of feeding and output.

[0106] In some embodiments, Figure 2 After the industrial processing operation starts, the collection module 203 starts the timing task, obtains the real-time data of material addition and output from the collection tag points at a preset time interval, and stores the real-time data in the real-time database; when the industrial processing operation ends, the timing task is stopped according to the final state data of the operation, and the real-time data collection operation of the collection tag points is ended.

[0107] In some embodiments, Figure 2 During the running of the scheduled task, when the acquisition module 203 determines that the real-time data collected at two consecutive time points are the same, the storage operation of the real-time data at the current time point is skipped; when it is determined that no real-time data is obtained at any time point, the real-time data collected at the previous time point is used to complete the real-time data at the current time point.

[0108] In some embodiments, Figure 2 The summary module 204 regularly collects the real-time data of feeding and output according to the preset timing task, wherein the real-time data includes the starting parameter value and the ending parameter value in the feeding process; when the feeding process and the output process are finished, the collected real-time data are grouped and summarized, and the real-time data of the feeding process and the output process are processed respectively; for each group of real-time data, the feeding amount is calculated based on the starting parameter value and the ending parameter value of the feeding process, and the output amount is calculated based on the starting parameter value and the ending parameter value of the output process.

[0109] In some embodiments, Figure 2 The display module 205 stores the feeding amount and the output amount in the historical database respectively, and sets query operations with different conditions for the data in the historical database; the real-time data, feeding amount and output amount of the feeding and output process are visualized, and the visualized data is displayed in the interface of the industrial process control system.

[0110] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0111] Figure 3 Schematic diagram of an electronic device 3 provided in an embodiment of the present application. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0112] The electronic device 3 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 3 The electronic device 3 is merely an example and does not limit the electronic device 3 , and may include more or less components than those shown in the figure, or different components.

[0113] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0114] The memory 302 may be an internal storage unit of the electronic device 3, for example, a hard disk or memory of the electronic device 3. The memory 302 may also be an external storage device of the electronic device 3, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. The memory 302 may also include both an internal storage unit of the electronic device 3 and an external storage device. The memory 302 is used to store computer programs and other programs and data required by the electronic device.

[0115] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0116] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium (e.g., a computer-readable storage medium). Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0117] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for real-time processing of industrial process data, characterized in that: include: In an industrial process control system, filter conditions of a batch data push system are configured, wherein the filter conditions include input point parameter names and output point parameter names; Based on the production task push of the batch processing data push system, the operation start data is pushed at the beginning of the industrial processing operation, and the operation final state data is pushed at the end of the operation; Configure a scheduled task based on the filtering conditions, and start the scheduled task after the industrial processing operation begins, and collect real-time data of feeding and output at preset time intervals; When the operation final state data is received, the timed task is stopped, the collected real-time data of feeding and output are summarized, and the feeding amount and output amount are calculated based on the starting parameter value and the ending parameter value; The aggregated real-time data is stored in a historical database, and the real-time data, the feed amount and the output amount are displayed in real time through a visual interface.

2. The method according to claim 1, characterized in that In the industrial process control system, the control parameters of feeding and output are configured, including: In the industrial process control system, the input point parameter name in the feeding process and the output point parameter name in the output process are configured using the control system settings, wherein the input point parameter name is used to identify the key data point at the beginning of feeding, and the output point parameter name is used to identify the key data point at the beginning or end of output.

3. The method according to claim 1, characterized in that The configuring of the scheduled task based on the filtering condition includes: Using the industrial processing control system to receive the operation start data pushed by the batch processing data push system, and matching the parameter names of feeding and output according to the filtering conditions; After the parameter names are matched, it is determined whether the feeding parameters and the output parameters meet the filtering conditions. If they meet the conditions, the corresponding collection label points are extracted from the feeding parameters and the output parameters; The collection tag point is added to the timed task queue, and the timed task is configured according to a preset time interval. The timed task is used to regularly collect real-time data of feeding and output.

4. The method according to claim 3, characterized in that The timing task is started after the industrial processing operation begins, and real-time data of feeding and output are collected at preset time intervals, including: After the industrial processing operation starts, the timing task is started to obtain the real-time data of feeding and output from the collection tag point at a preset time interval, and the real-time data is stored in the real-time database; When the industrial processing operation is finished, the scheduled task is stopped according to the final state data of the operation, and the real-time data collection operation of the collection tag points is ended.

5. The method according to claim 4, characterized in that The method further comprises: During the running of the scheduled task, when it is determined that the real-time data collected at two consecutive time points are the same, the storage operation of the real-time data at the current time point is skipped; when it is determined that no real-time data is obtained at any time point, the real-time data collected at the previous time point is used to complete the real-time data at the current time point.

6. The method according to claim 1, characterized in that The collected real-time data of feeding and output are summarized, and the feeding amount and output amount are calculated based on the starting parameter value and the ending parameter value, including: According to the preset timed tasks, the real-time data of feeding and output are collected regularly, wherein the real-time data includes the starting parameter value and the ending parameter value during the feeding process; When the feeding process and the output process are finished, the collected real-time data are grouped and summarized, and the real-time data of the feeding process and the output process are processed respectively; For each set of real-time data, the feeding amount is calculated based on the starting parameter value and the ending parameter value of the feeding process, and the output amount is calculated based on the starting parameter value and the ending parameter value of the output process.

7. The method according to claim 6, characterized in that The real-time data after aggregation is stored in a historical database, and the real-time data, the feed amount and the output amount are displayed in real time through a visual interface, including: The feeding amount and the output amount are stored in the historical database respectively, and query operations with different conditions are set for the data in the historical database; the real-time data, feeding amount and output amount of the feeding and output process are visualized, and the visualized data are displayed in the interface of the industrial process control system.

8. A real-time processing device for industrial process data, characterized in that: include: A configuration module is configured to configure filtering conditions of a batch data push system in an industrial process control system, wherein the filtering conditions include input point parameter names and output point parameter names; A push module, configured to push production tasks based on the batch data push system, push operation start data when an industrial processing operation starts, and push operation final state data when the operation ends; A collection module is configured to configure a timed task based on the filtering condition, and start the timed task after the industrial processing operation starts, and collect real-time data of feeding and output at preset time intervals; A summary module is configured to stop the timed task when receiving the final operation data, summarize the collected real-time data of feeding and output, and calculate the feeding amount and output amount based on the starting parameter value and the ending parameter value; The display module is configured to store the aggregated real-time data in a historical database, and to display the real-time data, the feed amount and the output amount in real time through a visual interface.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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