Material flow tracking method and device under industrial internet platform and electronic equipment
By using a material flow tracking method under the industrial internet platform, standardized operating data and preset rules are used to identify production equipment anomalies. Combined with material identification and energy consumption data, the standardization and automation of the entire material flow tracking is achieved. This solves the problem of the difficulty in standardizing and refining material flow tracking in existing technologies, improves the accuracy of process tracking, and reduces energy consumption.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-22
- Publication Date
- 2026-03-27
AI Technical Summary
Existing industrial platforms suffer from fragmented functions, complex equipment access, insufficient data processing efficiency, and limited alarm methods, making it difficult to achieve standardized and precise material flow tracking, which mainly relies on manual labor.
Through the industrial internet platform, abnormalities in production equipment are identified based on standardized operating data and preset anomaly rules. Combined with material identification and energy consumption data, the energy consumption of the production process is determined. Furthermore, preset process quality judgment rules are used to achieve graded alarms and complete the tracking of the entire material flow.
It has achieved standardized and fully automated tracking of the entire material flow, improved the precision of process tracking, reduced production energy consumption, increased production efficiency, and reduced labor costs.
Smart Images
Figure CN121745848A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of steel automated production technology, and in particular to a material flow tracking method, device and electronic equipment under an industrial internet platform. Background Technology
[0002] Currently, with the deepening and development of industrial automation and informatization, the scale of industrial data generated in the steel production process is growing rapidly, becoming an important foundation for promoting the digital transformation of enterprises.
[0003] However, existing industrial platforms generally suffer from problems such as fragmented functions, complex equipment access, insufficient data processing efficiency, and limited alarm methods. Furthermore, the tracking of the entire material flow mainly relies on manual labor, which makes it difficult to achieve standardization and precision in the tracking of material data throughout the entire process. Summary of the Invention
[0004] This application provides a material flow tracking method, device, and electronic device under an industrial internet platform. The embodiments provided by this application solve the problems of scattered functions, complex device access, insufficient data processing efficiency, and single alarm methods in the prior art. Moreover, the tracking of the entire material flow mainly relies on manual labor, which makes it difficult to achieve standardization and precision in the tracking of the entire material data. The embodiments provided by this application realize standardized tracking of the entire material flow of the target steel production, achieve fully automated tracking, and improve the precision of the entire material flow tracking.
[0005] In a first aspect, this application provides a material flow tracking method under an industrial internet platform, the material flow tracking method under the industrial internet platform comprising:
[0006] Based on standardized operating data and preset abnormal operating rules corresponding to at least one target production equipment in the target industrial production line, it is determined whether there is an abnormality in the target production equipment in the target industrial production line. The standardized operating data is used to characterize multi-source heterogeneous data under multiple target industrial protocols, and the preset abnormal operating rules include at least one rule for judging abnormal operation of the standardized operating data.
[0007] Based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process under the target industrial production line is determined.
[0008] Based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rules, the production quality of the target steel under the target industrial production line is determined.
[0009] If any of the target production equipment is found to be abnormal, or any of the production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, then a tiered alarm will be triggered based on preset alarm rules to complete the full material flow tracking of the target steel production.
[0010] In one feasible implementation, determining whether the target production equipment in the target industrial production line is abnormal, based on standardized operating data and preset abnormal operation rules corresponding to at least one target production equipment in the target industrial production line, includes:
[0011] When the standardized operating data corresponding to at least one of the target production equipment in the target industrial production line is greater than the preset threshold specified in the preset data abnormal operation rule, it is determined that each of the target production equipment in the target industrial production line is abnormal;
[0012] When the standardized operating data corresponding to at least one of the target production equipment in the target industrial production line is greater than or equal to the preset threshold specified in the preset data abnormal operation rules, it is determined that there is no abnormality in the target production equipment in the target industrial production line.
[0013] In one feasible implementation, determining the production process energy consumption data for each of the production processes under the target industrial production line based on material identification data for different production processes under the target industrial production line and material energy consumption data corresponding to each material includes:
[0014] Based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, the single coil energy consumption data, single billet energy consumption data and single process energy consumption data of each production process under the target industrial production line are determined. The material identification data includes: the coil number, billet number and furnace number of the target steel.
[0015] In one feasible implementation, determining the production quality of the target steel under the target industrial production line based on material process parameter data of different production processes under the target industrial production line and preset process quality judgment rules includes:
[0016] Material process parameter data for different production processes are determined from the standardized operating data, wherein the material process parameter data includes thickness, width, flatness, temperature, and surface defect detection signals;
[0017] The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rule to determine the production quality of the target steel under the target industrial production line.
[0018] In one feasible implementation, the step of comparing the material process parameter data with the corresponding process quality threshold in the preset process quality judgment rule to determine the production quality of the target steel under the target industrial production line includes:
[0019] The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rule to determine the quality deviation;
[0020] Based on the quality deviation, the quality grade of the target material in the target industrial production line is determined;
[0021] Based on the quality grade of the target material, the production quality of the target steel under the target industrial production line is determined.
[0022] In one feasible implementation, if it is determined that any of the target production equipment is abnormal, or any of the production process energy consumption data is abnormal, or the production quality of the target steel is abnormal, then a tiered alarm is triggered based on preset alarm rules to complete the full material flow tracking of the target steel production, including:
[0023] If any of the target production equipment is determined to be abnormal, an alarm for the abnormal production equipment will be triggered based on the first audible and visual alarm method in the preset alarm rules.
[0024] If any of the energy consumption data in the production process is found to be abnormal, an energy consumption anomaly alarm will be triggered based on the second audible and visual alarm method in the preset alarm rules.
[0025] If it is determined that the production quality of the target steel is abnormal, an alarm for abnormal production quality will be triggered based on the third audible and visual alarm method in the preset alarm rules.
[0026] In one feasible implementation, anomalies in any of the energy consumption data of the production process are determined by the following method:
[0027] The energy consumption data of each of the production processes are compared with the historical energy consumption benchmark curve to determine the energy consumption difference corresponding to each of the production processes.
[0028] When the energy consumption difference is greater than or equal to a preset energy consumption difference, the production process energy consumption data corresponding to the energy consumption difference that is greater than or equal to the preset energy consumption difference is determined to be abnormal.
[0029] In a second aspect, this application provides a material flow tracking device under the industrial internet platform, comprising:
[0030] The first determining module is used to determine whether there is an anomaly in the target production equipment in the target industrial production line based on the standardized operating data corresponding to at least one target production equipment in the target industrial production line and the preset data anomaly operating rules. The standardized operating data is used to characterize multi-source heterogeneous data under multiple target industrial protocols, and the preset data anomaly operating rules include at least one rule for judging the abnormal operation of the standardized operating data.
[0031] The second determining module is used to determine the production process energy consumption data of each production process under the target industrial production line based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material.
[0032] The third determining module is used to determine the production quality of the target steel under the target industrial production line based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rules.
[0033] The alarm module is used to issue a tiered alarm based on preset alarm rules if any of the target production equipment is found to be abnormal, any of the production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, so as to complete the full material process tracking of the production of the target steel.
[0034] In a third aspect, this application provides a material flow tracking device under an industrial internet platform, the material flow tracking device under the industrial internet platform comprising:
[0035] The determination module is used to determine whether there is an anomaly in the target production equipment in the target industrial production line based on the standardized operating data corresponding to at least one target production equipment in the target industrial production line and the preset data anomaly operating rules. The standardized operating data is used to characterize multi-source heterogeneous data under multiple target industrial protocols, and the preset data anomaly operating rules include at least one rule for judging the anomaly operation of the standardized operating data.
[0036] The second determining module is used to determine the production process energy consumption data of each production process under the target industrial production line based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material.
[0037] The third determining module is used to determine the production quality of the target steel under the target industrial production line based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rules.
[0038] The alarm module is used to issue a tiered alarm based on preset alarm rules if any of the target production equipment is found to be abnormal, any of the production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, so as to complete the full material process tracking of the production of the target steel.
[0039] In a third aspect, this application provides an electronic device, including a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus, and the machine-readable instructions are executed by the processor to perform the steps of the material flow tracking method under the industrial internet platform described above.
[0040] In a fourth aspect of this application, an embodiment of this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the material flow tracking method under the industrial internet platform described above.
[0041] Compared with the prior art, the material flow tracking method, device, and electronic equipment under the industrial internet platform provided in this application have the following advantages: Based on standardized operating data and preset abnormal operation rules corresponding to at least one target production equipment in the target industrial production line, the embodiments of this application determine whether there are any abnormalities in each target production equipment in the target industrial production line. Then, based on the material identification data of different production processes in the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process in the target industrial production line is determined. Furthermore, based on the material process parameter data of different production processes in the target industrial production line and preset process quality judgment rules, the production quality of the target steel in the target industrial production line is determined. If any target production equipment is found to be abnormal, or any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, a tiered alarm is triggered based on preset alarm rules to complete the full material flow tracking of the target steel production. The embodiments of this application achieve standardized tracking of the entire material flow of the target steel production, realize fully automated tracking, and improve the precision of the full material flow tracking. Attached Figure Description
[0042] Figure 1 A flowchart illustrating a material flow tracking method under an industrial internet platform provided in an embodiment of this application is shown.
[0043] Figure 2 This paper shows a structural block diagram of a material flow tracking device under an industrial internet platform provided in an embodiment of this application;
[0044] Figure 3A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown.
[0045] Figure 2 and Figure 3 The correspondence between the figure labels and figure titles in the accompanying drawings is as follows:
[0046] 200 Material flow tracking device under the industrial internet platform; 210 First determination module; 220 Second determination module; 230 Third determination module; 240 Alarm module; 300 Electronic device; 310 Processor; 320 Memory; 330 Bus. Detailed Implementation
[0047] To better understand the technical solutions provided in the embodiments of this specification, the technical solutions of the embodiments of this specification will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.
[0048] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element. The term "two or more" includes two or more cases.
[0049] First, the applicable application scenarios of this application will be introduced. The embodiments provided in this application are applicable to the field of steel automated production technology, and in particular, they relate to a material flow tracking method, device and electronic equipment under an industrial Internet platform.
[0050] Currently, existing industrial platforms generally suffer from problems such as fragmented functions, complex equipment access, insufficient data processing efficiency, and limited alarm methods. Furthermore, the tracking of the entire material flow mainly relies on manual labor, which makes it difficult to achieve standardization and precision in the tracking of material data throughout the entire process.
[0051] Based on this, the embodiments of this application provide a material flow tracking method, device, and electronic device under an industrial internet platform. The embodiments provided by this application solve the problems of dispersed functions, complex device access, insufficient data processing efficiency, and single alarm methods in the prior art. Moreover, the tracking of the entire material flow mainly relies on manual labor, which leads to the technical problem that it is difficult to achieve standardization and refinement of the entire material data tracking. The embodiments provided by this application realize standardized tracking of the entire material flow of the target steel production, achieve fully automated tracking, and improve the refinement of the entire material flow tracking.
[0052] The figure shows a flowchart of a method for determining a fault identification model provided in an embodiment of this application, as follows: Figure 1 As shown, the method for determining the fault identification model includes the following steps:
[0053] S101. Based on the standardized operating data and preset abnormal operating rules corresponding to at least one target production equipment in the target industrial production line, determine whether there is an abnormality in the target production equipment in the target industrial production line. The standardized operating data is used to characterize multi-source heterogeneous data under multiple target industrial protocols, and the preset abnormal operating rules include at least one rule for judging abnormal operation of the standardized operating data.
[0054] In this step, when the embodiments provided in this application need to track the standardized operating data corresponding to the target production equipment under the industrial internet platform, it is first necessary to deploy an industrial internet platform with a microservice architecture so that the disassembly and force ventilation of various types of data can support microservice deployment and run uniformly under the industrial internet platform.
[0055] For example, by using multiple industrial communication protocols to connect the industrial internet platform with the standardized operating data corresponding to at least one target production equipment, and after determining the data connection protocol, start collecting the standardized operating data corresponding to at least one target production equipment, and obtain the preset data anomaly operation rules for judging the anomalies of each type of standardized operating data, and then, based on the standardized operating data corresponding to the target production equipment and the preset data anomaly operation rules, determine whether there are any anomalies in the target production equipment in the target industrial production line.
[0056] The embodiments provided in this application, after determining the standardized operating data of different production processes under the target industrial production line, will display the above-mentioned standardized operating data in real time through a data display device, and will also display historical standardized operating data at the same time.
[0057] It is understood that the standardized operating data in the embodiments provided in this application are determined in the following ways:
[0058] Based on a unified data dictionary, the accessed multi-source heterogeneous basic operational data is standardized to generate standardized data.
[0059] Based on a unified data dictionary, the accessed multi-source heterogeneous basic operational data is standardized to generate standardized data, specifically:
[0060] Based on the variable identifiers, data units, and sampling frequencies of the target production equipment predefined in the unified data dictionary, the multi-source heterogeneous basic operation data is parsed and mapped. The parsed and mapped data is then unified in units and converted in format. The converted data is then aligned and stored according to time series to generate standardized operation data. This has enabled standardized modeling of the access data. Furthermore, the embodiments provided in this application support modeling methods such as single-point creation and Excel template import.
[0061] Here, the embodiments provided in this application require a unified data dictionary to specify a standardized data rule engine, and then link the standardized running data under the above data rule engine with the abnormal data calculation modules at different frequencies to determine the standardized running data calculation methods under triggered calculation frequency, high-frequency calculation, and low-frequency calculation.
[0062] The industrial communication protocol provided in this application can be selected and used according to different application scenarios and usage conditions. Specifically, the industrial communication protocol provided in this application can be set to at least one of OPCUA, Modbus and MQTT protocols.
[0063] The next at least one target production equipment under the target industrial production line in the embodiments provided in this application includes, but is not limited to: electricity meters, flow meters, fuel meters, gas meters, metering instruments, appliances, PLCs, sensors, vehicle positioning equipment, smoke sensors, sound and light sensors, thermometers, air compressors, charging piles, and level gauges, etc.
[0064] S102. Based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, determine the production process energy consumption data of each production process under the target industrial production line.
[0065] In this step, the embodiments provided in this application will also collect material identification data of different production processes under the target industrial production line, determine the material energy consumption data corresponding to each material, and then associate the material energy consumption data corresponding to each material with the material identification data to realize the calculation of single coil energy consumption, single billet energy consumption and single process energy consumption of plate and steel coil in each process, determine the production process energy consumption data of each production process under the target industrial production line, and associate the production process energy consumption data of each production process with the material identification data to realize energy consumption traceability.
[0066] In the embodiments provided in this application, the material identification data can be customized and used according to different application scenarios and usage conditions. The material identification data in the embodiments provided in this application can be specifically set as: the coil number of steel, the billet number of steel, or the furnace number of steel.
[0067] S103. Based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rules, determine the production quality of the target steel under the target industrial production line.
[0068] In this step, the embodiments provided in this application simultaneously collect material process parameter data of different production processes under the target industrial production line, and judge the production quality of the target steel under the target industrial production line by comparing the material process parameter data with the preset process quality judgment rules. Then, based on the judgment result of the production quality of the target steel, it is determined whether to issue an alarm reminder.
[0069] It is understood that the preset process quality judgment rules in the embodiments provided in this application specify process quality thresholds, and the setting of the above-mentioned process quality thresholds can be customized and used according to different application scenarios and usage conditions. The process quality thresholds in the embodiments provided in this application are set based on the enterprise's process standards.
[0070] S104. If it is determined that any target production equipment is abnormal, or any production process energy consumption data is abnormal, or the production quality of the target steel is abnormal, then a tiered alarm will be triggered based on preset alarm rules to complete the full material process tracking of the target steel production.
[0071] In this step, the embodiments provided in this application will trigger an alarm when it is determined that there is an abnormality in the target production equipment, an abnormality in the energy consumption data of the production process, or an abnormality in the production quality of the target steel. The alarm will be classified into different levels according to different types of abnormalities, so as to realize real-time alarm for the faults and abnormal status of the target production equipment.
[0072] It is understood that, in the embodiments provided in this application, the alarm level for abnormalities in the target production equipment is higher than the alarm level for abnormalities in production quality, and the alarm level for abnormalities in production quality is higher than the alarm level for abnormalities in production process energy consumption data.
[0073] It should be noted that, after performing graded alarms and real-time monitoring on the above-mentioned abnormal situations, the embodiments provided in this application will forward the above-mentioned graded alarms and real-time monitoring results to external systems, such as SCADA (Supervisory Control and Data Acquisition) and cloud platforms.
[0074] Compared with the prior art, the material flow tracking method under the industrial internet platform provided in this application determines whether there is an anomaly in each target production equipment in the target industrial production line based on standardized operating data and preset abnormal data operation rules corresponding to at least one target production equipment in the target industrial production line. Then, based on the material identification data of different production processes in the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process in the target industrial production line is determined. Based on the material process parameter data of different production processes in the target industrial production line and preset process quality judgment rules, the production quality of the target steel in the target industrial production line is determined. If any target production equipment is found to be abnormal, or any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, a graded alarm is set based on preset alarm rules to complete the full material flow tracking of the target steel production. The embodiment provided in this application realizes standardized tracking of the full material flow of the target steel production, achieves fully automated tracking, improves the precision of the full material flow tracking, and can realize full-process tracking of target materials between production line processes such as hot rolling and cold rolling.
[0075] For example, based on standardized operating data and preset abnormal operating rules corresponding to at least one target production equipment in the target industrial production line, it is determined whether there is an abnormality in the target production equipment in the target industrial production line, including:
[0076] When the standardized operating data of at least one target production equipment in the target industrial production line exceeds the preset threshold specified in the preset data anomaly operation rules, it is determined that each target production equipment in the target industrial production line is abnormal.
[0077] In the above-described embodiments, when it is determined that the standardized operating data corresponding to the target production equipment is greater than the preset threshold specified in the preset abnormal operation rules, it is determined that each target production equipment in the target industrial production line is abnormal.
[0078] Understandably, the preset threshold can be customized and used according to different application scenarios and usage conditions.
[0079] When the standardized operating data of at least one target production equipment in the target industrial production line is greater than or equal to the preset threshold specified in the preset data abnormal operation rules, it is determined that there is no abnormality in the target production equipment in the target industrial production line.
[0080] In the above-described embodiments, when the standardized operating data corresponding to the target production equipment is determined to be greater than or equal to a preset threshold, it indicates that the value of the standardized operating data is within the normal operating range, and at this time it is determined that there is no abnormality in the target production equipment in the target industrial production line.
[0081] For example, based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process under the target industrial production line is determined, including:
[0082] Based on the material identification data and the corresponding material energy consumption data of different production processes under the target industrial production line, the single coil energy consumption data, single billet energy consumption data and single process energy consumption data of each production process under the target industrial production line are determined. Among them, the material identification data includes: the coil number, billet number and furnace number of the target steel.
[0083] In the above-mentioned embodiments, the embodiments provided in this application can be associated with the energy consumption data of each material based on the coil number, billet number and furnace number of the target steel, and determine the single coil energy consumption data, single billet energy consumption data and single process energy consumption data of each production process under the target industrial production line, so as to realize energy consumption traceability.
[0084] For example, based on material process parameter data of different production processes under the target industrial production line and preset process quality judgment rules, the production quality of the target steel under the target industrial production line is determined, including:
[0085] Material process parameters for different production processes are determined from standardized operational data. These parameters include thickness, width, flatness, temperature, and surface defect detection signals. The material process parameters are then compared with the corresponding process quality thresholds in the preset process quality judgment rules to determine the production quality of the target steel on the target industrial production line.
[0086] It is understood that the embodiments provided in this application need to compare the material process parameter data of the standardized operating data with the corresponding process quality threshold in the preset process quality judgment rules, and determine the production quality of the target steel under the target industrial production line based on the above comparison results.
[0087] It should be noted that the process quality thresholds in the embodiments provided in this application can be customized and used according to different application scenarios and usage conditions.
[0088] This application first extracts material process parameter data generated throughout or in a specific process (such as cold rolling) from a standardized data pool based on the unique material identification data of the target material (e.g., a specific steel coil with coil number "A20231025001"). This data is collected online by a series of sensors deployed on the production line and processed through data access and a data dictionary. Key material process parameter data includes, but is not limited to: geometric dimensional parameters such as thickness (collected by a laser thickness gauge), width (collected by a width gauge), and flatness (collected by a shape gauge).
[0089] Thermal process parameters: rolling temperature, final rolling temperature and coiling temperature of each pass (collected by an infrared thermometer); Surface condition parameters: signals such as defect type, defect size and defect distribution density collected by a surface defect detector (such as a machine vision-based detection system).
[0090] Here, the defect types in the embodiments provided in this application include, but are not limited to, cracks, holes, and inclusions.
[0091] For example, comparing material process parameter data with the corresponding process quality threshold in the preset process quality judgment rules to determine the production quality of the target steel under the target industrial production line includes:
[0092] The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rules to determine the quality deviation.
[0093] In the above-described embodiments, the present application first determines the material process parameter data, and based on a galvanized steel coil with grade "DX54D+Z" and specifications of "1.0×1250mm", determines its process quality thresholds regarding thickness, width, zinc layer weight, and the number of surface defects. Then, it compares the aforementioned material process parameter data with the corresponding process quality thresholds in the preset process quality judgment rules to determine the quality deviation.
[0094] It is understood that the formula for determining the quality deviation in the embodiments provided in this application is specifically: Quality deviation = numerical value of material process parameter data - process quality threshold, and the absolute value is taken.
[0095] Based on quality deviations, determine the quality grade of the target material in the target industrial production line.
[0096] In the above-described embodiments, after determining the quality deviation, the embodiments provided in this application will divide the quality deviation within different numerical ranges to determine the quality grades of different target materials.
[0097] Here, the embodiments provided in this application can divide the quality grade of the target material into three grades: poor, normal, and excellent.
[0098] Based on the quality grade of the target material, determine the production quality of the target steel in the target industrial production line.
[0099] Here, after determining the quality grade of the target material, the embodiments provided in this application can further determine the production quality of the target steel based on the quality grade of the target material.
[0100] For example, if any target production equipment is found to be abnormal, or any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, then a tiered alarm will be triggered based on preset alarm rules to complete the full material flow tracking of the target steel production, including:
[0101] If any target production equipment is found to be abnormal, an alarm will be triggered based on the first audible and visual alarm method in the preset alarm rules; if any production process energy consumption data is found to be abnormal, an energy consumption abnormal alarm will be triggered based on the second audible and visual alarm method in the preset alarm rules; if the production quality of the target steel is found to be abnormal, a production quality abnormal alarm will be triggered based on the third audible and visual alarm method in the preset alarm rules.
[0102] In the above-described embodiments, the first audible and visual alarm will be triggered when there is an abnormality in the target production equipment; the second audible and visual alarm will be triggered when there is an abnormality in the energy consumption data of the production process; and the third audible and visual alarm will be triggered when there is an abnormality in the production quality.
[0103] It is understood that the third audible and visual alarm in the embodiments provided in this application is implemented based on the enterprise standard in the preset alarm rules.
[0104] For example, anomalies in energy consumption data for any production process can be identified using the following methods:
[0105] The energy consumption data of each production process is compared with the historical energy consumption baseline curve to determine the energy consumption difference corresponding to each production process. When the energy consumption difference is greater than or equal to the preset energy consumption difference, the energy consumption data of the production process corresponding to the energy consumption difference that is greater than or equal to the preset energy consumption difference is determined to be abnormal.
[0106] In the above context, the historical energy consumption baseline curve refers to a standard energy consumption reference curve established based on historical data for a specific production process, product specification, and production conditions. It represents the "normal" or "ideal" energy consumption level under that production scenario.
[0107] Understandably, the preset energy consumption difference can be customized and used according to different application scenarios and usage conditions.
[0108] The following describes the material flow tracking process under the industrial internet platform through different implementation examples:
[0109] Example 1: A system that deploys the material flow tracking method of this industrial internet platform across multiple production lines:
[0110] Deploy a data access module on the edge computing server to access the basic operating data of target production equipment such as single-machine 1200, single-machine 1500, pickling line, cold rolling line, continuous annealing line, galvanizing line and color coating line, as well as the data of ventilation, water and electricity.
[0111] Then, the equipment information table (Excel) is imported through a graphical configuration method, a data dictionary is automatically generated, and the industrial internet platform automatically loads the protocol to start reading the basic operating data, material energy consumption data, and material process parameter data on site, and saves the above data.
[0112] By configuring preset data anomaly operation rules and preset process quality judgment rules, and linking with the scenario, the relevant data of each roll is statistically analyzed based on the roll number and shearing signal, including abnormal data and normal data. The results are saved to the time series database to complete the full material flow tracking of the target steel production.
[0113] Multiple data points are compared together and displayed in formats such as line charts and step charts.
[0114] Real-time monitoring of the data acquisition link status and reconnection of the link are performed to ensure data integrity.
[0115] Example 2: A system for deploying the material flow tracking method of this industrial internet platform on a cold rolling production line:
[0116] A data access module is deployed on the edge computing server to access the basic operating data of target production equipment such as shape gauges, thickness gauges, infrared thermometers, and surface defect detectors, as well as data on ventilation, water, electricity, and gas systems.
[0117] Then, the equipment information table (Excel) is imported through a graphical configuration method, and a data dictionary is automatically generated. The data dictionary module also establishes preset rules for abnormal data operation, such as "thickness", "width", "temperature", "flatness" and "surface defects".
[0118] The system automatically aggregates relevant data such as quality based on roll number and process number, and performs real-time judgment on the collected data according to the set process parameters, using preset process quality judgment rules to identify cracks and defects.
[0119] The system monitors the results of real-time production quality assessments. When an anomaly is detected, a production quality anomaly alarm is triggered and pushed to relevant on-site operators and quality inspectors. Then, a data forwarding module pushes the statistical results to the MES system based on the user-configured interface address, port number, frequency, and mode for finished product grading and warehousing management.
[0120] The embodiments provided in this application reduce production energy consumption, improve production efficiency, reduce labor costs, and increase the traceability rate of materials throughout the entire process.
[0121] Figure 2 This diagram illustrates a structural block diagram of a material flow tracking device under an industrial internet platform, as provided in an embodiment of this application. Figure 2 As shown, the material flow tracking device 200 under the industrial internet platform includes:
[0122] The first determining module 210 is used to determine whether there is an anomaly in the target production equipment in the target industrial production line based on the standardized operating data corresponding to at least one target production equipment in the target industrial production line and the preset data anomaly operating rules. The standardized operating data is used to characterize multi-source heterogeneous data under multiple target industrial protocols, and the preset data anomaly operating rules include at least one rule for judging the anomaly of the standardized operating data.
[0123] The second determining module 220 is used to determine the production process energy consumption data of each production process under the target industrial production line based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material.
[0124] The third determining module 230 is used to determine the production quality of the target steel under the target industrial production line based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rules.
[0125] The alarm module 240 is used to issue a tiered alarm based on preset alarm rules if any target production equipment is found to be abnormal, any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, so as to complete the full material process tracking of the target steel production.
[0126] The embodiments provided in this application reduce production energy consumption, improve production efficiency, reduce labor costs, and increase the traceability rate of materials throughout the entire process.
[0127] For example, the first determining module 210 is used for:
[0128] When the standardized operating data of at least one target production equipment in the target industrial production line exceeds the preset threshold specified in the preset data anomaly operation rules, it is determined that each target production equipment in the target industrial production line is abnormal.
[0129] When the standardized operating data of at least one target production equipment in the target industrial production line is greater than or equal to the preset threshold specified in the preset data abnormal operation rules, it is determined that there is no abnormality in the target production equipment in the target industrial production line.
[0130] For example, the second determining module 220 is used for:
[0131] Based on the material identification data and the corresponding material energy consumption data of different production processes under the target industrial production line, the single coil energy consumption data, single billet energy consumption data and single process energy consumption data of each production process under the target industrial production line are determined. Among them, the material identification data includes: the coil number, billet number and furnace number of the target steel.
[0132] For example, the third determining module 230 is used for:
[0133] Material process parameters for different production processes are determined from standardized operational data. These parameters include thickness, width, flatness, temperature, and surface defect detection signals.
[0134] The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rules to determine the production quality of the target steel under the target industrial production line.
[0135] For example, the material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rules to determine the production quality of the target steel under the target industrial production line, including:
[0136] The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rules to determine the quality deviation.
[0137] Based on quality deviations, determine the quality grade of the target material in the target industrial production line.
[0138] Based on the quality grade of the target material, determine the production quality of the target steel in the target industrial production line.
[0139] For example, if any target production equipment is found to be abnormal, or any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, then a tiered alarm will be triggered based on preset alarm rules to complete the full material flow tracking of the target steel production, including:
[0140] If any target production equipment is found to be abnormal, an alarm will be triggered based on the first audible and visual alarm method in the preset alarm rules.
[0141] If any abnormality is found in the energy consumption data of any production process, an energy consumption abnormality alarm will be triggered based on the second audible and visual alarm method in the preset alarm rules.
[0142] If it is determined that there is an abnormality in the production quality of the target steel, an alarm for abnormal production quality will be triggered based on the third audible and visual alarm method in the preset alarm rules.
[0143] For example, anomalies in energy consumption data for any production process can be identified using the following methods:
[0144] The energy consumption data of each production process is compared with the historical energy consumption benchmark curve to determine the energy consumption difference corresponding to each production process.
[0145] When the energy consumption difference is greater than or equal to the preset energy consumption difference, the energy consumption data of the production process corresponding to the energy consumption difference that is greater than or equal to the preset energy consumption difference is determined to be abnormal.
[0146] Compared with the prior art, the material flow tracking method under the industrial internet platform provided in this application determines whether there is an anomaly in each target production equipment in the target industrial production line based on standardized operating data and preset abnormal data operation rules corresponding to at least one target production equipment in the target industrial production line. Then, based on the material identification data of different production processes in the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process in the target industrial production line is determined. Based on the material process parameter data of different production processes in the target industrial production line and preset process quality judgment rules, the production quality of the target steel in the target industrial production line is determined. If any target production equipment is found to be abnormal, or any production process energy consumption data is found to be abnormal, or the production quality of the target steel is found to be abnormal, a graded alarm is set based on preset alarm rules to complete the full material flow tracking of the target steel production. The embodiment provided in this application realizes standardized tracking of the full material flow of the target steel production, achieves fully automated tracking, improves the precision of the full material flow tracking, and can realize full-process tracking of target materials between production line processes such as hot rolling and cold rolling.
[0147] Please see Figure 3 , Figure 3 This application provides a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 3 As shown, the electronic device 300 includes a processor 310, a memory 320, and a bus 330.
[0148] Memory 320 stores machine-readable instructions executable by processor 310. When electronic device 300 is running, processor 310 and memory 320 communicate via bus 330. When the machine-readable instructions are executed by processor 310, they can perform the operations described above. Figure 1 The steps of the material flow tracking method under the industrial internet platform in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.
[0149] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 The steps of the material flow tracking method under the industrial internet platform in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.
[0150] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0151] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.
[0152] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-readable program code.
[0153] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0154] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0155] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0156] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to execute a process for determining a fault identification model.
[0157] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).
[0158] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0159] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.
[0160] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0161] Furthermore, the functional units in the various embodiments of this application 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 integrated unit can be implemented in hardware or as a software functional unit.
[0162] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0163] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
[0164] Although preferred embodiments have been described in this specification, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this specification.
[0165] Obviously, those skilled in the art can make various modifications and variations to this specification without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims and their equivalents, this specification is also intended to include such modifications and variations.
Claims
1. A material flow tracking method under an industrial internet platform, characterized in that, The material flow tracking method under the industrial internet platform comprises: Based on the standardized running data corresponding to at least one target production device under the target industrial production line and the preset data abnormal running rule, it is determined whether the target production device in the target industrial production line is abnormal, wherein the standardized running data is used to represent multi-source heterogeneous data under multiple target industrial protocols, and the preset data abnormal running rule includes at least one rule for abnormal running judgment of the standardized running data; Based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, the production process energy consumption data of each production process under the target industrial production line is determined; Based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rule, the production quality of the target steel material under the target industrial production line is determined; If it is determined that any of the target production devices is abnormal, or any of the production process energy consumption data is abnormal, or the production quality of the target steel material is abnormal, hierarchical alarm is performed based on the preset alarm rule to complete the full material flow tracking of the target steel production. 2.The material flow tracking method under the industrial internet platform of claim 1, wherein, The determination of whether the target production device in the target industrial production line is abnormal based on the standardized running data corresponding to at least one target production device under the target industrial production line and the preset data abnormal running rule comprises: When the standardized running data corresponding to at least one target production device under the target industrial production line is greater than the preset threshold value specified in the preset data abnormal running rule, it is determined that each target production device in the target industrial production line is abnormal; When the standardized running data corresponding to at least one target production device under the target industrial production line is greater than or equal to the preset threshold value specified in the preset data abnormal running rule, it is determined that the target production device in the target industrial production line is not abnormal. 3.The material flow tracking method under the industrial internet platform of claim 1, wherein, The determination of the production process energy consumption data of each production process under the target industrial production line based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material comprises: Based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each material, the single-roll energy consumption data, single-billet energy consumption data and single-process energy consumption data of each production process under the target industrial production line are determined, wherein the material identification data includes the roll number, billet number and furnace number of the target steel material. 4.The material flow tracking method under the industrial internet platform of claim 1, wherein, The determination of the production quality of the target steel material under the target industrial production line based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rule comprises: The material process parameter data of different production processes is determined from the standardized running data, wherein the material process parameter data includes thickness, width, flatness, temperature and surface defect detection signal; The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rule, and the production quality of the target steel material under the target industrial production line is determined. 5.The material flow tracking method under the industrial internet platform of claim 4, wherein, The comparison of the material process parameter data with the corresponding process quality threshold in the preset process quality judgment rule to determine the production quality of the target steel material under the target industrial production line comprises: The material process parameter data is compared with the corresponding process quality threshold in the preset process quality judgment rule to determine the quality deviation; Based on the quality deviation, the quality grade of the target material under the target industrial production line is determined; Based on the quality grade of the target material, the production quality of the target steel material under the target industrial production line is determined. 6.The material flow tracking method under the industrial internet platform of claim 1, wherein, If it is determined that any of the target production equipment has an abnormality, or any of the production process energy consumption data has an abnormality, or the production quality of the target steel material has an abnormality, hierarchical alarm is performed based on a preset alarm rule to complete the tracking of the whole material process of the target steel production, comprising: If it is determined that any of the target production equipment has an abnormality, production equipment abnormality alarm is performed based on a first audible and light alarm mode in the preset alarm rule; If it is determined that any of the production process energy consumption data has an abnormality, energy consumption abnormality alarm is performed based on a second audible and light alarm mode in the preset alarm rule; If it is determined that the production quality of the target steel material has an abnormality, production quality abnormality alarm is performed based on a third audible and light alarm mode in the preset alarm rule. 7.The material flow tracking method under the industrial internet platform of claim 1, wherein, The production process energy consumption data is determined to be abnormal in the following way: Each of the production process energy consumption data is compared with a historical energy consumption benchmark curve to determine the energy consumption difference value corresponding to each of the production processes; When the energy consumption difference value is greater than or equal to a preset energy consumption difference value, the production process energy consumption data corresponding to the energy consumption difference value greater than or equal to the preset energy consumption difference value is determined to be abnormal.
8. A material flow tracking device under an industrial internet platform, characterized in that, The material process tracking device under the industrial internet platform Comprise: The first determination module is used for determining whether the target production equipment in the target industrial production line has an abnormality based on the standardized running data corresponding to at least one target production equipment under the target industrial production line and the preset data abnormal running rule, wherein the standardized running data is used to represent multi-source heterogeneous data under multiple target industrial protocols, and the preset data abnormal running rule comprises at least one rule for abnormal running judgment of the standardized running data; The second determination module is used for determining the production process energy consumption data of each of the production processes under the target industrial production line based on the material identification data of different production processes under the target industrial production line and the material energy consumption data corresponding to each of the materials; The third determination module is used for determining the production quality of the target steel material under the target industrial production line based on the material process parameter data of different production processes under the target industrial production line and the preset process quality judgment rule; An alarm module is configured to perform hierarchical alarm based on preset alarm rules if it is determined that any of the target production equipment is abnormal, or any of the production process energy consumption data is abnormal, or the production quality of the target steel material is abnormal, so as to complete the full material process tracking of the target steel production.
9. An electronic device, comprising: The application further provides a computer readable storage medium having stored thereon a computer program, wherein the computer program is executed by a processor to perform the steps of the material process tracking method under the industrial internet platform as described in any one of claims 1-7. The application further provides a computer readable storage medium having stored thereon a computer program, wherein the computer program is executed by a processor to perform the steps of the material process tracking method under the industrial internet platform as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that,