Monitoring method and monitoring system for steelmaking production process

Abstract

The invention relates to the technical field of monitoring, and discloses a monitoring method and a monitoring system for a steelmaking production process. The monitoring method comprises the following steps: collecting various production data and equipment real-time data under each of a plurality of processes involved in the steelmaking production process corresponding to the current heat number; storing each kind of production data in the various kinds of production data under each working procedure and the current heat number into a corresponding database table under each working procedure so as to obtain a plurality of database tables under each working procedure; according to the current furnace number and the plurality of database tables under each process, a production wide table under each process is constructed, and the production wide table comprises the plurality of production data; and monitoring the steelmaking production process according to the production width table under each process. According to the invention, the real-time monitoring of the production condition of the whole process can be realized, namely the real-time monitoring of the production line and the process can be realized, so that the monitoring efficiency can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of monitoring technology, and in particular to a monitoring method and a monitoring system for a steelmaking production process. Background Art

[0002] The steelmaking process of steel smelting includes converters, refining and continuous casting, which will generate a large amount of data in production. By monitoring, calculating and analyzing these data, the overall and local production conditions of the steelmaking production line can be monitored in real time, and alarms can be issued for production parameter indicators that exceed the upper threshold, so as to timely discover problems in production and the impact of production process parameters on product quality, and formulate targeted plans to improve the quality of steel billets.

[0003] Currently, real-time monitoring of steel plant production data is mainly completed in the steelmaking MES system. However, this method cannot achieve real-time monitoring of production processes in the entire plant, nor can it achieve real-time alarm for abnormal production index data. Summary of the invention

[0004] The purpose of the present invention is to provide a monitoring method and a monitoring system for a steelmaking production process, which can realize real-time monitoring of the production conditions of the entire process, that is, to realize real-time monitoring of the production line and the process, thereby greatly improving the monitoring efficiency.

[0005] In order to achieve the above-mentioned purpose, the first aspect of the present invention provides a monitoring method for a steelmaking production process, the monitoring method comprising: collecting a variety of production data and equipment real-time data under each process of a plurality of processes involved in the steelmaking production process corresponding to a current furnace number, wherein the plurality of production data include general data, production performance data, production event data, and the general data include the correspondence between material codes and material names, and the correspondence between event codes and event names; storing each of the plurality of production data under each process and the current furnace number in a corresponding database table under each process to obtain a plurality of database tables under each process; constructing a production wide table under each process according to the current furnace number and the plurality of database tables under each process, wherein the production wide table includes the plurality of production data; and monitoring the steelmaking production process according to the production wide table under each process.

[0006] Preferably, constructing the production width table under each process includes: using the current heat number as an index to obtain the multiple production data from multiple database tables under each process; and associating the obtained multiple production data with the steel type corresponding to the current heat number to form a production width table indexed by the current heat number.

[0007] Preferably, constructing the wide production table under each process also includes: when the production event data is feeding data, determining the consumption index of the target material under each process according to the sum of the input weights of the target materials in the feeding data under each process and the output molten steel in the corresponding production performance data; and adding the determined consumption index of the target material to the wide production table under each process.

[0008] Preferably, constructing the wide production table under each process also includes: determining the average operating index of the target equipment under each process according to the real-time operating data of the target equipment in the real-time equipment data under each process, the production start time and the production end time; and adding the determined average operating index of the target equipment to the wide production table under each process.

[0009] Preferably, the monitoring of the steelmaking production process includes: determining the production progress of each process according to whether the production start time and the production end time in the production performance data in the production wide table under each process are empty.

[0010] Preferably, each of the production performance data and the production event data includes a material code, an event code and corresponding record data, and the monitoring of the steelmaking production process includes: calling the production wide table corresponding to the furnace number to be monitored; obtaining the code corresponding to the name to be monitored according to the name to be monitored and the common data in the called production wide table, wherein the name to be monitored includes the name of the material to be monitored and / or the name of the event to be monitored; and obtaining the record data related to the obtained code from the called production wide table.

[0011] Preferably, the monitoring method also includes: calling corresponding alarm rules according to the target data in the production wide table, wherein the alarm rules include: process identification, equipment identification, indicator name, alarm threshold, judgment cycle, judgment type, and alarm level; and judging the target data according to the called alarm rules to form corresponding alarm records.

[0012] Preferably, the monitoring method further comprises: displaying a wide production table for each process on the same page.

[0013] Preferably, the various production data also include: production plan data and product inspection results.

[0014] Through the above technical scheme, the present invention creatively collects a variety of production data and equipment real-time data under each process of the multiple processes involved in the steelmaking production process corresponding to the current furnace number; each of the multiple production data under each process and the current furnace number are stored in the corresponding database table under each process to obtain multiple database tables under each process; according to the current furnace number and the multiple database tables under each process, a production wide table under each process is constructed, wherein the production wide table includes the multiple production data; and according to the production wide table under each process, the steelmaking production process is monitored. The present invention can realize real-time monitoring of the production situation of the entire process, that is, realize real-time monitoring of the production line and the process, thereby greatly improving the monitoring efficiency.

[0015] The second aspect of the present invention provides a monitoring system for a steelmaking production process, the monitoring system comprising: a collection device for collecting a variety of production data and equipment real-time data in each of a plurality of processes involved in the steelmaking production process corresponding to a current furnace number, wherein the plurality of production data include general data, production performance data, production event data, and the general data include the correspondence between material codes and material names, and the correspondence between event codes and event names; a storage device for storing each of the plurality of production data in each process and the current furnace number in a corresponding database table in each process to obtain a plurality of database tables in each process; a construction device for constructing a production wide table in each process according to the current furnace number and the plurality of database tables in each process, wherein the production wide table includes the plurality of production data; and a monitoring device for monitoring the steelmaking production process according to the production wide table in each process.

[0016] The specific details and benefits of the monitoring system for the steelmaking production process provided by the embodiment of the present invention can be found in the description of the monitoring method for the steelmaking production process mentioned above, which will not be repeated here.

[0017] A third aspect of the present invention provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for monitoring the steelmaking production process is implemented.

[0018] A fourth aspect of the present invention provides a computer program product, comprising a computer program, which implements the method for monitoring the steelmaking production process when executed by a processor.

[0019] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0021] Figure 1 It is a flow chart of a method for monitoring a steelmaking production process provided by one embodiment of the present invention;

[0022] Figure 2 It is a flow chart of a method for monitoring a steelmaking production process provided by one embodiment of the present invention;

[0023] Figure 3 is a screenshot of a monitoring system provided by an embodiment of the present invention; and

[0024] Figure 4 This is a screenshot of a monitoring system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0026] Figure 1 FIG. 1 is a flow chart of a method for monitoring a steelmaking production process provided by an embodiment of the present invention. Figure 1 As shown, the monitoring method includes: step S101, collecting a variety of production data and equipment real-time data under each process of the multiple processes involved in the steelmaking production process corresponding to the current furnace number, wherein the multiple production data include general data, production performance data, production event data, and the general data include the correspondence between material codes and material names, and the correspondence between event codes and event names; step S102, storing each of the multiple production data under each process and the current furnace number in the corresponding database table under each process to obtain multiple database tables under each process; step S103, constructing a production wide table under each process according to the current furnace number and the multiple database tables under each process, wherein the production wide table includes the multiple production data; and step S104, monitoring the steelmaking production process according to the production wide table under each process.

[0027] The above steps S101 - S104 are explained and illustrated below respectively.

[0028] Step S101, collecting various production data and equipment real-time data in each process of multiple processes involved in the steelmaking production process corresponding to the current furnace number.

[0029] The various production data include general data, production performance data, and production event data, and the general data include the correspondence between material codes and material names, and the correspondence between event codes and event names. For example, the general data include: material name (aluminum pellets): material code (01); event name (packaging debonding): event code (001). Of course, the general data may also include: the correspondence between equipment codes and equipment names.

[0030] In one embodiment, the various production data may also include: production plan data and product inspection results.

[0031] Among them, the multiple processes may include converter, refining, and continuous casting.

[0032] First, during the steelmaking production of the current furnace in the steelmaking plant, various data generated by each process are collected, including general data (for example, steel grade code, material code, event code, etc.), production plan data, production performance data (for example, process production result data), production event data (for example, temperature measurement, oxygen blowing, feeding, etc.), product inspection and testing results, equipment real-time data, etc. Figure 2 shown.

[0033] Step S102: storing each of the multiple production data under each process and the current furnace number into a corresponding database table under each process to obtain multiple database tables under each process.

[0034] The whole plant production data is collected and stored in the warehouse, including general data, production plan data, production performance data, production event data, product inspection results, equipment real-time data, etc. The above data and the corresponding furnace number are collected uniformly to the data center, and the database table corresponding to each process is designed in the data center to complete the storage.

[0035] Step S103, constructing a production wide table for each process according to the current furnace number and the multiple database tables for each process, wherein the production wide table includes the multiple production data.

[0036] For step S103, constructing the production width table under each process includes: using the current furnace number as an index to obtain the multiple production data from multiple database tables under each process; and associating the obtained multiple production data with the steel type corresponding to the current furnace number to form a production width table indexed by the current furnace number.

[0037] Since the heat number is stored in multiple database tables, various types of production data can be obtained from multiple database tables under one process based on the heat number, and various types of production data can be associated with corresponding steel grades to form a production width table corresponding to the current heat number, and the production width table can be obtained by indexing the current heat number. Therefore, the production width table and related information can also be queried, tracked and displayed by steel grade.

[0038] In one embodiment, constructing the wide production table for each process also includes: when the production event data is feeding data, determining the consumption index of the target material for each process according to the sum of the input weights of the target materials in the feeding data for each process and the output molten steel in the corresponding production performance data; and adding the determined consumption index of the target material to the wide production table for each process.

[0039] For example, for input materials (e.g., aluminum products), if there is a need to obtain material consumption indicators, it is necessary to calculate the unit consumption indicators of aluminum products under the converter process corresponding to a certain furnace number. The sum of the input weights of aluminum products (including aluminum particles, steel core aluminum, etc.) is obtained from the input data under the converter process corresponding to the furnace number, and the obtained input weight is divided by the output rigid water volume in the production performance data under the converter process corresponding to the same furnace number to determine the aluminum product consumption indicator under the converter process. Then, the determined aluminum product consumption indicator is added to the production wide table under the converter process, so that the indicators that cannot be directly obtained (such as material consumption indicators) can be directly monitored through the production wide table.

[0040] In another embodiment, constructing the wide production table under each process also includes: determining the average operating index of the target equipment under each process based on the real-time operating data of the target equipment in the real-time equipment data under each process, the production start time and the production end time; and adding the determined average operating index of the target equipment to the wide production table under each process.

[0041] For example, for real-time equipment data (e.g., casting speed), if there is a need to monitor the operation of the equipment, it is necessary to determine the average casting speed under the continuous casting process corresponding to a certain furnace number. Based on the actual production performance data under the continuous casting process corresponding to the furnace number, the start and end time of the continuous casting production of the furnace and the continuous casting equipment number are obtained, and the casting speed data of the continuous casting machine per second in the production start and end time period in the corresponding continuous casting equipment real-time data are obtained by association, and the average value is calculated to obtain the average casting speed of the equipment. Then, the determined average casting speed is added to the production wide table under the converter process, so that the average casting speed of the equipment can be directly monitored through the production wide table.

[0042] According to the actual production business logic of the steel plant (for example, the order of production processes), the above-mentioned collected data (except the real-time data of the equipment) are associated, organized and calculated, and the production indicators are calculated based on the collected original data. The above-mentioned associations and calculation results are used to construct a wide production table for each process, so as to directly query all the production data that need to be paid attention to in each process.

[0043] Among them, the production wide table can also include a production line wide table and a process wide table, which respectively store the production process parameters and quality inspection data related to the furnaces in the entire steelmaking production line and the converter, refining and continuous casting processes.

[0044] In this embodiment, as production proceeds in real time, efficient data aggregation and updating of the production wide table is realized in the data center. Taking the construction of the converter process wide table as an example, a temporary table is used to store the furnace numbers of all planned but unproduced, in production, and completed furnaces in the current converter process as a clue to associate all production data of the converter process.

[0045] Next, using the furnace number stored in the temporary table, the data in the database tables such as the converter production plan data, converter production performance data, material consumption records, inspection and test results, process standards, and public codes are associated (association is the connection of multiple database tables, using specific conditions to display the data distributed in different data tables in a unified manner according to the required logic) and calculated (for example: converter aluminum product consumption data should be obtained by calculating the total consumption of multiple aluminum products).

[0046] Therefore, through real-time automatic updating of wide tables, it is possible to store the real-time production status data of the entire production line in one table, avoiding the need to associate multiple data tables for each query, thereby improving query efficiency.

[0047] Step S104, monitoring the steelmaking production process according to the production width table of each process.

[0048] For step S104, the monitoring of the steelmaking production process includes: determining the production progress of each process according to whether the production start time and the production end time in the production performance data in the production wide table under each process are empty.

[0049] In one embodiment, the monitoring method further comprises: displaying a wide production table for each process on the same page.

[0050] For example, the real-time monitoring of the production line can be realized on the same page, and the production progress and basic information of each equipment in each process of converter, refining (LF), and continuous casting (CCM) can be tracked, so as to understand the overall production situation of the steelmaking production line. The data displayed by real-time monitoring comes from the constructed production wide table. Based on whether the production start and end time of each process in the wide table is empty, the production progress of the process at the current time of the furnace can be judged. According to different situations, it can be divided into: if the start and end time are both empty, the furnace has not started production; if the start time is not empty and the end time is empty, the furnace is in production; if the start and end time are both not empty, the furnace has completed production.

[0051] like Figure 3 As shown, for completed processes, the start and end time, shift, duration, and number of alarms are displayed; for processes that have not started, gray boxes are used as placeholders; for processes in production, the start time is displayed, and a progress bar is used to display the current production time. Based on the process path information in the wide table, it is determined whether the heat is a direct-up heat, thereby determining whether the heat refining data is displayed on the page.

[0052] The above is a description of real-time monitoring of the entire production line. In addition, real-time monitoring of processes can be achieved in the following ways. For each process in production, the data in the constructed wide table of each process can be used to further track the real-time events, key indicators, real-time alarm information and real-time indicator trends of the process (such as Figure 4 As shown), you can learn the latest production status in real time.

[0053] The furnace production event uses the production event data in the wide table to display various events and parameters in the furnace production process from new to old in the form of a timeline; the key indicator item part displays the indicator item data that needs to be paid attention to in production and is updated in real time in the wide table; the alarm information is displayed in the form of a timeline, using the data generated in step 2 using the production wide table. A line chart is used to display the change trend of the real-time data of the equipment sensor in the process, and the user can select the data items to be displayed in the line chart.

[0054] In addition, the system also provides a historical furnace query function, which can query the historical furnaces that have completed production and view the production details of each process. The content display is the same as the real-time process monitoring function.

[0055] Therefore, on the same page, real-time monitoring of single process events, indicator values, equipment real-time data curves, inspection and testing information, etc. can be achieved, while providing historical furnace production status inquiries in each process.

[0056] In one embodiment, each of the production performance data and the production event data includes a material code, an event code, and corresponding record data.

[0057] Correspondingly, the monitoring of the steelmaking production process includes: calling the production wide table corresponding to the furnace number to be monitored; obtaining the code corresponding to the name to be monitored according to the name to be monitored and the common data in the called production wide table, wherein the name to be monitored includes the name of the material to be monitored and / or the name of the event to be monitored; and obtaining the record data related to the obtained code from the called production wide table.

[0058] For example, in the tracking situation, the user enters the furnace number and aluminum particles (material name), and the platform calls the corresponding production wide table based on the furnace number, and obtains the material code corresponding to the aluminum particles from the general data therein (for example, 01); because the data included in the production wide table contains the material code, the record data related to the aluminum particles can be obtained through the material code 01.

[0059] For example, for tracking situations, the user inputs the furnace number and package debonding (event name), and the platform calls the corresponding production wide table based on the furnace number, and obtains the event code corresponding to the package debonding from the general data therein (for example, 001); since the data included in the production wide table contains event codes, the record data related to package debonding can be obtained through the event code 001.

[0060] For example, for tracking situations, the user inputs the furnace number and aluminum particles (material name) and package debonding (event name). The platform calls the corresponding production wide table based on the furnace number, and obtains the event codes corresponding to aluminum particles and package debonding from the general data therein (for example, 01, 001). Since the data included in the production wide table contain material and event codes, the record data related to aluminum particles and package debonding can be obtained through the material code 01 and the event code 001.

[0061] Based on any of the above embodiments, the monitoring method also includes: calling corresponding alarm rules according to the target data in the production wide table, wherein the alarm rules include: process identification, equipment identification, indicator name, alarm threshold, judgment cycle, judgment type, and alarm level; and judging the target data according to the called alarm rules to form a corresponding alarm record.

[0062] Configure indicator alarm rules for the collected data. Among them, the alarm coverage indicator data range includes: the aforementioned calculated production indicator data, as well as the product inspection and test results, equipment real-time data, etc. collected directly by the system. For data indicator items that require alarms, data alarm rules can be configured. The configuration content includes: production line (steel mill), process (including converter, refining, continuous casting), equipment (equipment options within the process are provided according to the selected process), indicator name (according to the selected process and equipment, the alternatives are all indicator items corresponding to the equipment), rule / alarm threshold, (alarm) judgment cycle, (alarm) judgment type, alarm level (red, yellow, etc.), and customizable alarm information. Among them, data indicator items that require alarms may include production performance data (such as converter steelmaking end temperature, continuous casting aluminum loss, etc.), equipment real-time data (real-time temperature, drawing speed, etc.), inspection and test results (test results of sample composition during production of each process). The system can provide an alarm configuration page, in which you can select production line, process, and equipment. After selection, the system will provide the indicator items contained in the selected equipment as alternatives. Users can select indicator items that require alarms and configure rule thresholds, alarm cycles, judgment types, etc.

[0063] Among them, the alarm judgment types include: out of range, number of violations, and violation rate. In particular, for some indicators with different alarm thresholds under different conditions (for example, for different execution standards, the upper and lower limits of the alarm threshold for the sulfur content of molten steel in the converter process are different), customized alarm judgment logic is implemented for this situation, so that the indicator can be alarmed according to the corresponding alarm threshold under different production parameter conditions.

[0064] For violation quantity types: for example, continuous casting-superheat, continuous casting-crystallizer water inlet temperature, this type of alarm can set upper and lower limits for the indicator, and set a violation quantity threshold. Every time the indicator exceeds the limit, a violation is recorded. When the number of consecutive violations exceeds the violation quantity threshold, an alarm is generated; for out-of-range types: for example, continuous casting-casting speed, converter-oxygen supply intensity, this type of alarm only sets upper and lower limits for the indicator, and an alarm is generated once the indicator value exceeds the limit.

[0065] For the alarm rules configured in the previous step, the system periodically monitors the corresponding indicator values ​​according to the alarm judgment cycle length of each alarm rule, and issues an alarm and generates an alarm result for the indicator items that exceed the alarm rules. The alarm results are uniformly displayed in the form of a detailed list, and the list display items include: process, equipment, alarm indicator name, furnace number, alarm level, judgment type, alarm information, and alarm generation time. Each line in the list is an alarm record, sorted from new to old by alarm time, and the most recently generated alarm record is displayed at the top of the list.

[0066] The system provides the definition of personnel positions for pushing alarm information, which is used to maintain the range of personnel included in each position and the range of alarm indicators that can be received. For each process, a furnace is assigned to different positions for information push according to the number of indicator alarms within a process cycle. When the number of alarms of the corresponding alarm indicator exceeds the threshold, the system pushes information based on the process where the furnace is located and the alarm indicator information combination, and pushes it to the corresponding user. The alarm push content consists of: "Furnace number: "+furnace number value+", "+team value+"-"+process value+"process-"+equipment value+"-"+alarm indicator name+", alarm level: "+alarm level value+"exceeds"+push threshold+", please handle in time".

[0067] The system will use the real-time collected production data to compare with the configured alarm rules, thereby generating alarm records and storing them in the database. For the alarm records generated by the system, the system provides an alarm result page, which displays the alarm results of the steel plant's entire plant indicators in a table. The alarm results are displayed in reverse order of generation time, and the latest alarm record is displayed at the top for real-time discovery and processing. The alarm push target users can be configured to push the indicator alarm results belonging to different processes to the corresponding users in real time. Real-time alarm of production data indicators: Provide custom configuration of alarm rules for indicators that require attention, and generate alarm results in real time according to the configuration of alarm rules, display them in the form of an alarm detail list, and push them to relevant personnel in real time.

[0068] By using the wide production tables of each process constructed above and the alarm records of each process indicator, real-time monitoring of the steelmaking production line can be achieved on a furnace basis. The converter, refining and continuous casting processes of each furnace are displayed in a result box respectively, which is used to monitor the overall production implementation of the steelmaking production line.

[0069] You can view detailed parameter information of each completed or in-production process on the details page of each process. The system will search for the production data of the process according to the furnace number, and display the furnace number, steel type and other basic information of the furnace on the details page, and display the latest event tracking, key indicators, alarm information, implementation indicator monitoring, real-time event tracking, inspection and testing information of the furnace in the form of charts.

[0070] Take the customized alarm for the steelmaking lime consumption as an example:

[0071] This indicator has different upper and lower limit thresholds under different conditions: 1. different steel grades; 2. whether the steel is over-refined.

[0072] The system provides a separate custom rule configuration page. The configuration content includes production line, process, equipment, indicator name, alarm judgment cycle, alarm judgment type, and alarm level. It also provides a table with a customizable number of rows for configuring alarm thresholds under different judgment conditions.

[0073] Specifically, after each alarm cycle, the system will make an alarm judgment, and the judgment steps are: 1. Obtain the steel type of the furnace and whether it is over-refined based on the furnace production performance data; 2. Obtain the upper and lower limits of the standard based on whether it is over-refined; 3. Perform rule matching to generate an alarm result.

[0074] The present invention is aimed at the application scenario of production monitoring of the entire production line of a steel plant. After collecting all the data to the data middle platform, the data is organized and associated based on the actual steelmaking production business, thereby realizing real-time production monitoring and real-time alarm of abnormal data, and realizing real-time monitoring of the converter, refining, and continuous casting processes in chronological order on the same page, as well as tracking and query of key indicators and alarm data in each process, which greatly improves the efficiency of discovering quality problems in the production process of the steel plant, and reduces the query time of important information such as key indicator items of process production and abnormal data alarm from tens of minutes to hours to minutes.

[0075] An embodiment of the present invention provides a monitoring system for a steelmaking production process, the monitoring system comprising: a collection device for collecting a variety of production data and equipment real-time data in each of a plurality of processes involved in the steelmaking production process corresponding to a current furnace number, wherein the plurality of production data comprises general data, production performance data, production event data, and the general data comprises a correspondence between a material code and a material name, and a correspondence between an event code and an event name; a storage device for storing each of the plurality of production data in each process and the current furnace number in a corresponding database table in each process to obtain a plurality of database tables in each process; a construction device for constructing a production wide table in each process according to the current furnace number and the plurality of database tables in each process, wherein the production wide table comprises the plurality of production data; and a monitoring device for monitoring the steelmaking production process according to the production wide table in each process.

[0076] The specific details and benefits of the monitoring system for the steelmaking production process provided by the embodiment of the present invention can be found in the description of the monitoring method for the steelmaking production process mentioned above, which will not be repeated here.

[0077] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for monitoring the steelmaking production process is implemented.

[0078] An embodiment of the present invention provides a computer program product, including a computer program, which implements the monitoring method of the steelmaking production process when executed by a processor.

[0079] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0080] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0081] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including a number of instructions to enable a single-chip microcomputer, a chip or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0082] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0083] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0084] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A method for monitoring a steelmaking production process, characterized in that: The monitoring method comprises: Collecting a variety of production data and equipment real-time data in each process of a plurality of processes involved in the steelmaking production process corresponding to the current furnace number, wherein the plurality of production data includes general data, production performance data, and production event data, and the general data includes a correspondence between a material code and a material name, and a correspondence between an event code and an event name; storing each of the multiple production data under each process and the current furnace number in a corresponding database table under each process to obtain multiple database tables under each process; According to the current furnace number and the multiple database tables under each process, construct a production wide table under each process, wherein the production wide table includes the multiple production data; and The steelmaking production process is monitored according to the production width table under each process.

2. The monitoring method according to claim 1, characterized in that: The construction of the production wide table under each process comprises: Using the current furnace number as an index to obtain the multiple production data from the multiple database tables under each process; and The acquired multiple production data and the steel type corresponding to the current heat number are associated to form a production width table indexed by the current heat number.

3. The monitoring method according to claim 2, characterized in that: The construction of the production wide table under each process also includes: In the case where the production event data is feeding data, determining the consumption index of the target material in each process according to the sum of the input weights of the target materials in the feeding data in each process and the output molten steel in the corresponding production performance data; and The determined consumption index of the target material is added to the production wide table under each process.

4. The monitoring method according to claim 2 or 3, characterized in that: The construction of the production wide table under each process also includes: Determine an average operation index of the target equipment in each process according to the real-time operation data of the target equipment in the real-time data of the equipment in each process, the production start time and the production end time; and The determined average operating index of the target equipment is added to the production wide table under each process.

5. The monitoring method according to claim 1, characterized in that: The monitoring of the steelmaking production process comprises: The production progress of each process is determined based on whether the production start time and the production end time in the production performance data in the production wide table under each process are empty.

6. The monitoring method according to claim 1, characterized in that: Each of the production performance data and the production event data includes a material code, an event code and corresponding record data. The monitoring of the steelmaking production process comprises: Call the production wide table corresponding to the furnace number to be monitored; According to the name to be monitored and the common data in the called production wide table, obtaining a code corresponding to the name to be monitored, wherein the name to be monitored includes a name of a material to be monitored and / or a name of an event to be monitored; and Obtain record data related to the acquired encoding from the called production wide table.

7. The monitoring method according to claim 1, characterized in that: The monitoring method further comprises: According to the target data in the production wide table, the corresponding alarm rules are called, wherein the alarm rules include: process identification, equipment identification, indicator name, alarm threshold, judgment cycle, judgment type, and alarm level; and The target data is judged according to the called alarm rule to form a corresponding alarm record.

8. The monitoring method according to any one of claims 1 to 3, characterized in that: The monitoring method further comprises: displaying a wide production table for each process on the same page.

9. The monitoring method according to any one of claims 1 to 3, characterized in that: The various production data also include: production plan data and product inspection results.

10. A monitoring system for a steelmaking production process, characterized in that: The monitoring system comprises: A collection device, used to collect a variety of production data and equipment real-time data in each process of a plurality of processes involved in the steelmaking production process corresponding to the current furnace number, wherein the plurality of production data includes general data, production performance data, and production event data, and the general data includes a correspondence between a material code and a material name, and a correspondence between an event code and an event name; A storage device, used for storing each of the multiple production data under each process and the current furnace number in a corresponding database table under each process, so as to obtain multiple database tables under each process; A construction device, configured to construct a production wide table for each process according to the current furnace number and the multiple database tables for each process, wherein the production wide table includes the multiple production data; and The monitoring device is used to monitor the steelmaking production process according to the production width table under each process.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for monitoring the steelmaking production process according to any one of claims 1 to 9.

12. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements a monitoring method for a steelmaking production process according to any one of claims 1-9.

Images