Electric arc furnace smelting power supply and oxygen supply comprehensive monitoring method and system

Abstract

The invention discloses an electric arc furnace smelting power supply and oxygen supply comprehensive monitoring method and system, and belongs to the field of automatic control. Time sequence process data and heat actual performance data, related to power supply and oxygen supply monitoring analysis, of each furnace of steel are collected and stored in a real-time database and a relational database; carrying out furnace alignment processing on the time sequence process data, so that the time sequence process data is associated with the corresponding furnace number; an electric oxygen actual performance line with equal electric quantity interval points is automatically generated; calculating and generating an electro-oxygen guide line of each furnace of steel; comparing the electrooxygen actual performance line and the electrooxygen guide line of each furnace of steel, and judging whether the smelting power supply and oxygen supply process of each furnace of steel is abnormal or not; alarm prompts and evaluation reports are provided for abnormity in the smelting power supply and oxygen supply process, production personnel are reminded to adjust power supply and oxygen blowing parameters according to the range provided by the electro-oxygen guide line, and the smelting power supply and oxygen supply process is optimized. Power supply and oxygen supply process parameter control in the electric arc furnace smelting process can be guided and improved, the intelligent level of electric arc furnace steelmaking is improved, and energy conservation and consumption reduction are promoted.

Description

Technical Field

[0001] This invention belongs to the field of steelmaking process monitoring, and particularly relates to a method and system for integrated monitoring of power supply and oxygen supply in electric arc furnace smelting. Background Technology

[0002] As electric arc furnace steelmaking develops towards larger scale and ultra-high power both domestically and internationally, manufacturers of large and ultra-high power electric arc furnaces generally adopt a composite energy input method of electrode power supply + oxygen lance supply in the electric arc furnace smelting process in order to improve production efficiency and reduce power consumption.

[0003] In the electric arc furnace smelting process, the electrode power supply provides electrical energy, which generates heat through the arcing of the electrode to melt the steel material from the center of the electrode outwards; the oxygen lance provides chemical energy for oxygen blowing and combustion assistance. The oxygen lance burners arranged on the furnace wall of the electric arc furnace mix and burn the gas in proportion to form a concentrated jet. Relying on the reasonable distribution of electrical energy and chemical energy provided by the electrode and oxygen lance, the balanced melting of scrap steel and the high-efficiency and energy-saving steelmaking of the electric arc furnace are achieved.

[0004] The power supply and oxygen supply processes at different stages of the electric arc furnace smelting process have a significant impact on the energy consumption of electric arc furnace steelmaking.

[0005] Currently, most electric arc furnace steel plants still rely primarily on the manual experience of operators in each shift to track, monitor, set, and adjust the power and oxygen supply processes during the smelting process.

[0006] This monitoring method suffers from significant time lag, low analysis efficiency, difficulty in comparing different furnace batches, and excessive reliance on manual experience. It lacks systematic and comprehensive tracking, monitoring, analysis, and evaluation of the power and oxygen supply processes in electric arc furnace smelting. Consequently, unreasonable power and oxygen supply process parameters and operational behaviors during electric arc furnace smelting are difficult to detect and correct in a timely manner, resulting in significant differences in energy consumption between furnace batches and shifts. This directly affects the level of refined control over energy consumption in electric arc furnace smelting and hinders the achievement of the company's energy conservation and consumption reduction goals.

[0007] Patent application CN105241263A, published on January 13, 2016, discloses an electric furnace monitoring system. This system utilizes sensors and other components, along with wireless transmission and remote display equipment, to form a comprehensive monitoring system capable of monitoring parameters such as voltage, current, temperature, pressure, gas and liquid flow rates during furnace operation and taking appropriate actions based on this information to ensure safe production. However, the patent application primarily describes the system's composition and workflow, without providing specific, implementable technical solutions for monitoring specific parameters and implementing intelligent alarms.

[0008] Because sensors and other components are easily damaged during use at the smelting production site, resulting in the loss of their detection function, the lifespan of sensors and other components at the production site is relatively short, which seriously affects the normal and reliable functioning of the entire monitoring system.

[0009] If, without adding sensors, production data from the electric furnace smelting process can be used to monitor changes in power and oxygen consumption curves, and these curves can be compared with historical best furnace curves to optimize control parameters in real time, thereby guiding production and reducing energy consumption, then this would be a superior technical solution. Summary of the Invention

[0010] The technical problem to be solved by this invention is to provide a comprehensive monitoring method and system for power and oxygen supply in electric arc furnace (EAF) smelting. It utilizes production data from the EAF smelting process, monitors the changes in power and oxygen consumption curves during smelting, dynamically tracks and compares the trends and ranges of electricity and oxygen changes in each heat of steel during EAF smelting in real time, and automatically provides abnormal monitoring alarms and evaluations of the power and oxygen supply process by comparing it with the curves corresponding to the historical best heats. This guides improvements in the control of power and oxygen supply process parameters during EAF smelting, prevents significant deviations in smelting energy input, avoids unnecessary energy losses, reduces reliance on manual operation experience, enhances the intelligence level of EAF steelmaking, and promotes energy conservation and consumption reduction in steel plants.

[0011] The technical solution of this invention is: to provide a method for integrated monitoring of power supply and oxygen supply in electric arc furnace smelting, characterized by including the following steps:

[0012] 1) Collect time-series process data and actual data of each heat of steel related to power supply and oxygen supply monitoring and analysis, and store them in a real-time database and a relational database respectively;

[0013] 2) Perform furnace number alignment processing on the time sequence process data to associate the time sequence process data with the corresponding furnace number;

[0014] 3) Based on the time-series process data after each heat of steel is aligned and correlated, an electro-oxygen performance line with equal electrical energy intervals is automatically generated;

[0015] 4) Based on the automatically selected historical sample set of heats with the best energy consumption compared to the same period last year, calculate and generate the electric oxygen guideline for each heat of steel;

[0016] 5) Compare the actual and guide lines of the electric oxygen supply for each heat of steel to determine whether there are any abnormalities in the power supply and oxygen supply process of each heat of steel.

[0017] 6) Automatically provides alarm prompts and evaluation reports for abnormalities in the power and oxygen supply process of smelting, reminding production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the electric oxygen guideline, and optimize the power and oxygen supply process of smelting.

[0018] The integrated monitoring method for power and oxygen supply in electric arc furnace smelting described in this invention utilizes production data from the electric arc furnace smelting process. By monitoring the changes in power and oxygen consumption curves during the smelting process, it dynamically tracks and compares the trends and ranges of electricity and oxygen changes in each heat of steel during electric arc furnace smelting in real time. By comparing with the curves corresponding to the historical best heats, it automatically provides abnormal monitoring alarms and evaluations for the power and oxygen supply process of electric arc furnace smelting, guiding improvements in the control of power and oxygen supply process parameters during electric arc furnace smelting, preventing large deviations in smelting energy input, avoiding unnecessary energy losses, reducing reliance on manual operation experience, improving the intelligence level of electric arc furnace steelmaking, and promoting energy conservation and consumption reduction.

[0019] Specifically, in step 1), the time-series process data includes: the amount of electricity and oxygen supplied sampled according to a determined period, as well as the status of the smelting processing signal;

[0020] The aforementioned furnace performance data is data that is marked and statistically analyzed on a furnace-by-furnace basis, including: the smelting furnace number, steel grade mark, shift number, hot metal ratio, processing start time, processing end time, steel output, and energy consumption for each furnace of steel.

[0021] Specifically, in step 2), the time-series process data is aligned with the furnace number to associate the time-series process data with the corresponding smelting furnace number. This includes the following steps:

[0022] 2.1) Based on the processing start time in the actual data of each furnace and the preset synchronization time difference, locate the starting search point time of each furnace in the real-time database;

[0023] 2.2) Retrieve the smelting processing signal status of each furnace after the initial search point in the real-time database to determine the start and end points of the time sequence data for that furnace.

[0024] 2.3) Starting from the starting time of the furnace time sequence process data, each time sequence process data sampling point is read sequentially from the real-time database and saved to the data record associated with the furnace number in the relational database until the end of the furnace time sequence process data.

[0025] Furthermore, the starting search point time = furnace processing start time - synchronization time difference;

[0026] When retrieving the smelting processing signal status after the starting search point time for each furnace in the real-time database, if the smelting processing signal status changes from "processing ended" to "processing started", then that time point is determined as the starting point of the time sequence process data for that furnace; if the smelting processing signal status changes from "processing started" to "processing ended", then that time point is determined as the ending point of the time sequence process data for that furnace.

[0027] The endpoint of the heat sequence process data is limited by the maximum processing cycle, meaning that the time span of the time sequence process data for each heat of steel does not exceed the maximum processing cycle.

[0028] Specifically, in step 3), based on the time-series process data after alignment and correlation for each heat of steel, an electro-oxygen performance line with equal-electricity intervals is automatically generated, including:

[0029] 3.1) Based on the time-series process data after alignment and association of heats, with the power consumption of each heat as the abscissa and the oxygen consumption as the ordinate, the electro-oxygen curve of each heat is automatically generated according to the power consumption and oxygen consumption of each sampling point.

[0030] 3.2) Locate the sampling points on the left and right sides of the electric oxygen curve for each heat of steel that are closest to each isoelectric interval point on the x-axis. The coordinates of the left endpoint are (x... l y l ), the right endpoint coordinates are (x r y r );

[0031] 3.3) The coordinates of each isoelectric interval point are calculated using two-point interpolation (x...). t y t ), where y t The ordinate of the points at equal electrical intervals is... x t The x-coordinate of the points at equal electrical intervals;

[0032] 3.4) After calculating the coordinate data of all the isoelectric interval points, store them in the relational database to generate the electro-oxygen performance line of each heat of steel with isoelectric interval points.

[0033] Specifically, in step 4), the calculation of the electric oxygen guideline for each heat of steel based on the automatically selected historical sample set of heats with the best energy consumption compared to the same period last year includes:

[0034] 4.1) Automatically filter the sample set of furnaces with the best historical year-on-year energy consumption from the database;

[0035] 4.2) In the n-furnace sample with the best energy consumption in the same period in history, calculate the average oxygen flow rate and upper and lower boundary values ​​of each isoelectric interval point according to the data coordinates of the isoelectric interval points on the actual performance line of each furnace steel;

[0036] 4.3) Store the average oxygen flow rate and upper and lower boundary values ​​at each equal energy interval into a relational database to generate an electric oxygen guideline based on the best furnace sample of historical year-on-year energy consumption.

[0037] Furthermore, in step 4.1), the automatic selection of the sample set of furnaces with the best energy consumption in the same historical year includes: selecting historical furnaces that meet the same steel grade mark, a certain iron ratio and steel output range, and selecting the top n furnaces with the lowest energy consumption as the sample set of furnaces with the best energy consumption.

[0038] The specified range of molten iron ratio and tapping quantity is preset in the system, and the range of the same sample is set using relative values.

[0039] Furthermore, the iron-to-metal ratio is set to a range of ±5%, and the steel output is set to a range of ±10%.

[0040] Specifically, in step 4.2), the average oxygen flow rate at each isoelectric interval is: y i It is the oxygen flow rate of each heat of steel at a certain isoelectric interval point, and n is the number of heat samples selected.

[0041] The upper boundary value of oxygen flux at each isoelectric interval point is:

[0042] The lower boundary value of oxygen flux at each isoelectric interval point is:

[0043] Where δ is the deviation band and σ is the standard deviation.

[0044] Specifically, in step 5), the comparison between the actual and guideline electro-oxygenation performance lines for each heat of steel to determine whether there are any abnormalities in the power and oxygen supply process for each heat of steel includes:

[0045] 5.1) The power supply and oxygen supply process of electric arc furnace smelting is divided into different stages according to different power supply ranges;

[0046] 5.2) Determine whether the data coordinates on the electro-oxygenation performance line of each heat of steel at different stages exceed the upper and lower boundary lines of the electro-oxygenation guideline. If they do, it is determined that there is an abnormality in the smelting power supply and oxygen supply process of this heat of steel at that stage, and an abnormality mark is made in the record of the corresponding heat in the relational database.

[0047] Specifically, step 6) includes at least:

[0048] On the fixed or mobile monitoring terminal, the actual performance line and the guide line of the selected furnace are displayed;

[0049] Alarms are issued for abnormal coordinate points occurring at different stages of smelting, reminding production personnel to adjust power supply and oxygen blowing parameters according to the range provided by the electric oxygen guideline, and to optimize the power supply and oxygen supply process of smelting.

[0050] The system automatically generates anomaly statistics reports based on time, work group, and steel type, including the number and percentage of anomalies occurring in different time periods, work groups, and steel types, facilitating production process analysis and evaluation.

[0051] The technical solution of the present invention also provides a comprehensive monitoring system for power supply and oxygen supply in electric arc furnace smelting, characterized by comprising:

[0052] The data acquisition module, storage and analysis module, and report display module are connected in sequence.

[0053] The data acquisition module is used to collect time-series process data and actual heat data from different sources for each heat of steel, and send them to the storage and analysis module.

[0054] The storage and analysis module is connected to the data acquisition module;

[0055] The report display module is used to query and display the actual performance line and guide line of each heat, alarm the abnormal coordinate points of the power supply and oxygen supply process of each heat of steel, remind production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the guide line, optimize the power supply and oxygen supply process of smelting, and display abnormal statistical reports by time, shift and steel type.

[0056] The aforementioned integrated monitoring system for power and oxygen supply in electric arc furnace smelting tracks and analyzes oxygen levels using electricity as the independent variable. It observes the energy balance and changes at each stage of each heat of steel, analyzes the smelting energy control mode for each heat, and compares and analyzes the differences in energy consumption between different heats. By observing and analyzing the changes in the electric-oxygen curves of historical sample heats of the same steel grade, it adjusts the set values ​​of factors including current, voltage, and oxygen flow rate for the current heat in a timely manner to ensure that the furnace's smelting energy input does not deviate significantly, avoids unnecessary energy losses caused by improper control of the smelting process, and identifies areas for energy-saving optimization.

[0057] Specifically, the data acquisition module includes a time-series data acquisition module and a furnace-time data acquisition module;

[0058] The time-series data acquisition module is connected to the process detection instrument and is used to periodically acquire signals such as the power supply, oxygen supply, and smelting status of each heat of steel.

[0059] The furnace data acquisition module is connected to the process control system and is used to collect the furnace number, steel grade mark, iron-to-water ratio, processing start time, processing end time, steel output, and energy consumption for each furnace.

[0060] The timing data acquisition module is a programmable logic controller (PLC) connected to the basic automation network; the furnace data acquisition module is a process control server connected to the production information network.

[0061] Specifically, the storage and analysis module includes: a data storage module, a data alignment module, an electro-oxygen performance line determination module, an electro-oxygen guidance line determination module, and an anomaly detection module;

[0062] The data storage module, with the furnace as the recording unit, is used to record and save the time-series process data and furnace performance data sent by the data acquisition module;

[0063] The data storage module records and saves the coordinate points of the electro-oxidation performance line calculated by the electro-oxidation performance line determination module and the coordinate points of the electro-oxidation guidance line calculated by the electro-oxidation guidance line determination module for each heat of steel.

[0064] The data storage module includes a real-time database and a relational database;

[0065] The data alignment module is used to align the time-series process data and smelting furnace number in the real-time database of the data storage module, determine the start and end points of the time-series process data for each heat of steel, associate the time-series process data with the smelting furnace number, and store it in the relational database of the data storage module.

[0066] The electro-oxygenation performance line determination module is used to automatically generate the coordinates of the electro-oxygenation performance line with equal electrical energy intervals based on the time sequence process data after alignment and association of each heat of steel, and transmit it to the data storage module and display it through the report display module;

[0067] The aforementioned electric oxygen guideline determination module is used to determine the coordinates of each data point of the electric oxygen guideline for each heat of steel based on the automatically filtered historical sample set of heats with the best energy consumption compared to the same period last year, and transmit it to the data storage module and display it through the report display module;

[0068] The aforementioned anomaly determination module is used to compare the electric oxygen performance line and electric oxygen guidance line calculated by the electric oxygen performance line determination module and the electric oxygen guidance line determination module for each heat of steel, determine whether there are any anomalies in the power supply and oxygen supply process of each heat of steel at different stages, and record the anomaly determination results in the relational database of the data storage module.

[0069] Furthermore, the real-time database adopts a table structure with timestamp as the main index field, which is used to store the time-series process data periodically collected in real time by the time-series data acquisition module.

[0070] The relational database adopts a table structure with the furnace number as the main index field, which is used to store the data related to the furnace number collected by the furnace number data acquisition module.

[0071] Specifically, the storage and analysis module adopts a workshop edge server, which has a central processing unit, memory, hard disk storage and network interface, and is connected to the basic automation and production information network via Ethernet;

[0072] The report display module includes a fixed or mobile monitoring terminal.

[0073] Compared with the prior art, the advantages of the present invention are:

[0074] 1. The technical solution of the present invention, without adding sensors, generates an electro-oxygen performance line for each heat of steel and establishes an oxygen change curve with electricity as the independent variable. The change of a single curve can reflect the electro-oxygen matching relationship during the electric arc furnace smelting process. Since the electric arc furnace smelting process usually reflects different smelting stages and enters different oxygen blowing modes by the amount of electricity supplied, the electro-oxygen curve can reflect the overall power supply and oxygen supply mode of each heat of steel, making it more convenient to compare the electro-oxygen matching process of smelting stages between different heats.

[0075] 2. The technical solution of the present invention, by establishing an electric oxygen guideline based on the historical best energy consumption furnace sample, can provide a benchmark reference for the power supply and oxygen supply mode of furnaces of different steel grades. Once the electric oxygen curve generated by the power supply and oxygen supply mode adopted by the current furnace deviates from the range of the electric oxygen guideline, an abnormal alarm will be issued in time to prompt production personnel to adjust the power supply and oxygen supply parameters, prevent large deviations in smelting energy input, reduce the difference from the best energy consumption furnace sample, and avoid unnecessary energy loss.

[0076] 3. By adopting the technical solution of this invention, the demonstration and guidance of the electric oxygen guideline during the production of various steel grades, as well as the real-time comparative monitoring, avoids the blindness and arbitrariness of production process parameter adjustments caused by differences in the operating skills of production operators. It reduces the reliance on manual operating experience and makes the smelting process better tend towards the electric oxygen combination process of the heat with optimal energy consumption. This reduces the differences between different heats of the same type of steel, promotes energy conservation and consumption reduction in steel plants, and improves the intelligent level of electric arc furnace steelmaking. Attached Figure Description

[0077] Figure 1 This is a flowchart of the integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to the present invention;

[0078] Figure 2 This is a flowchart of the timing process data alignment by furnace number in this invention;

[0079] Figure 3 This is a flowchart of the electro-oxygen performance curve determination method of the present invention;

[0080] Figure 4This is a flowchart of the process for determining the electro-oxygen guideline of the present invention;

[0081] Figure 5 This is a flowchart for determining abnormalities in the smelting power supply and oxygen supply process of the present invention.

[0082] Figure 6 This is a structural diagram of the integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to the present invention.

[0083] In the diagram, 1 is the data acquisition module, 11 is the time-series data acquisition module, 12 is the furnace-by-furnace data acquisition module, 2 is the storage and analysis module, 21 is the data storage module, 22 is the data alignment module, 23 is the electro-oxygen performance line determination module, 24 is the electro-oxygen guideline determination module, 25 is the anomaly detection module, 3 is the report display module, 4 is the process monitoring instrument, and 5 is the process control system. Detailed Implementation

[0084] The invention will now be further described with reference to the accompanying drawings.

[0085] like Figure 1 As shown, in a first aspect, the present invention provides a method for integrated monitoring of power supply and oxygen supply in electric arc furnace smelting, comprising the following steps:

[0086] 1) Collect time-series process data and actual data of each heat of steel related to power supply and oxygen supply monitoring and analysis, and store them in a real-time database and a relational database respectively.

[0087] The time-series process data includes: the amount of electricity and oxygen supplied, as well as the smelting processing signal status, sampled according to a defined period; in this application example, the sampling period for the time-series process data is set to 1 minute.

[0088] The aforementioned furnace performance data is data that is marked and statistically analyzed on a furnace-by-furnace basis, including: the smelting furnace number, steel grade mark, shift number, hot metal ratio, processing start time, processing end time, steel output, and energy consumption for each furnace of steel.

[0089] 2) Perform furnace number alignment processing on the time sequence process data to associate the time sequence process data with the corresponding furnace number.

[0090] like Figure 2 As shown, the time-series process data is aligned with the furnace number to associate the time-series process data with the corresponding smelting furnace number, including:

[0091] 2.1) Based on the processing start time in the actual performance data of each furnace and the preset synchronization time difference, locate the starting search point of each furnace in the real-time database; the starting search point time = furnace processing start time - synchronization time difference; the synchronization time difference in this application example is set to 3 minutes;

[0092] 2.2) Retrieve the smelting processing signal status after the starting search point time for each furnace point in the real-time database. If the smelting processing signal status changes from "processing ended" to "processing started", then determine that time point as the starting point of the time sequence process data for that furnace. If the smelting processing signal status changes from "processing started" to "processing ended", then determine that time point as the ending point of the time sequence process data for that furnace.

[0093] 2.3) Starting from the starting time of the furnace time sequence process data, each time sequence process data sampling point is read sequentially from the real-time database and saved to the data record associated with the furnace number in the relational database until the end of the furnace time sequence process data.

[0094] Furthermore, the endpoint of the heat sequence process data is limited by the maximum processing cycle, that is, the time span of the time sequence process data for each heat of steel does not exceed the maximum processing cycle; in this application example, the maximum processing cycle is set to 80 minutes.

[0095] 3) Based on the time-series process data after each heat of steel is aligned and correlated, an electro-oxygen performance line with equal electrical energy intervals is automatically generated;

[0096] Furthermore, such as Figure 3 As shown, based on the time-series process data after alignment and correlation for each heat of steel, an electro-oxygen performance line with equal-electricity intervals is automatically generated, including:

[0097] 3.1) Based on the time-series process data after alignment and association of heats, with the power consumption of each heat as the abscissa and the oxygen consumption as the ordinate, the electro-oxygen curve of each heat is automatically generated according to the power consumption and oxygen consumption of each sampling point.

[0098] 3.2) Locate the sampling points on the left and right sides of the electric oxygen curve for each heat of steel that are closest to each isoelectric interval point on the x-axis. The coordinates of the left endpoint are (x... l y l ), the right endpoint coordinates are (x r y r );

[0099] 3.3) The coordinates of each isoelectric interval point are calculated using two-point interpolation (x...). t y t ), where y t The ordinate of the points at equal electrical intervals is... x t The x-coordinate of the points at equal electrical intervals;

[0100] This example uses an equal power interval of 500 kWh to calculate the oxygen flow rate corresponding to 500, 1000, 1500, and so on. To calculate the oxygen flow rate corresponding to a furnace power interval of 500 kWh, first find the sampling points on the left and right sides closest to 500 kWh on the x-axis of that furnace. The coordinate of the left endpoint is (x... l y l ), the right endpoint coordinates are (x r y r Then, using two-point interpolation, the coordinates of the isoelectric interval points are calculated as (500, y). t ),in,

[0101] 3.4) After calculating the coordinate data of all the isoelectric interval points, store them in the relational database to generate the electro-oxygen performance line of each heat of steel with isoelectric interval points.

[0102] 4) Based on the automatically selected historical sample set of heats with the best energy consumption compared to the same period last year, calculate and generate the electric oxygen guideline for each heat of steel;

[0103] Furthermore, such as Figure 4 As shown, the step of calculating and generating the electric oxygen guideline for each heat of steel based on an automatically selected historical sample set of heats with the best energy consumption compared to the same period last year includes:

[0104] 4.1) Automatically filter the sample set of furnaces with the best historical year-on-year energy consumption from the database;

[0105] The automatic selection of the sample set of furnaces with the best energy consumption in the same period of the previous year includes: selecting historical furnaces that meet the same steel grade mark, a certain iron ratio and steel output range, and selecting the top n furnaces with the lowest energy consumption as the sample set of furnaces with the best energy consumption.

[0106] The specified range of molten iron ratio and tapping amount is preset in the system, and the range of the same sample is set by relative values; in this example, the range of the same sample of molten iron ratio is set to ±5%, and the range of the same sample of tapping amount is set to ±10%.

[0107] 4.2) In the n-furnace sample with the best energy consumption in the same period in history, calculate the average oxygen flow rate and upper and lower boundary values ​​of each equal energy interval point according to the data coordinates of the equal energy interval points on the actual performance line of each furnace's steel-oxygen conversion.

[0108] Among them, the average oxygen flux at each isoelectric interval point y i It is the oxygen flow rate of each heat of steel at a certain isoelectric interval point, and n is the number of heat samples selected.

[0109] upper boundary value lower boundary value

[0110] Where δ is the deviation band, and in this example, it is taken as ±3σ, where σ is the standard deviation.

[0111] 4.3) Store the average oxygen flow rate and upper and lower boundary values ​​at each equal energy interval into a relational database to generate an electric oxygen guideline based on the best furnace sample of historical year-on-year energy consumption.

[0112] 5) Compare the actual and guide lines of the electric oxygen supply for each heat of steel to determine whether there are any abnormalities in the power supply and oxygen supply process of each heat of steel.

[0113] like Figure 5 As shown, the step of comparing the actual electro-oxygen performance line and the electro-oxygen guidance line for each heat of steel to determine whether there are any abnormalities in the power supply and oxygen supply process of each heat of steel includes:

[0114] 5.1) The power supply and oxygen supply process of electric arc furnace smelting is divided into different stages according to different power supply ranges;

[0115] 5.2) Determine whether the data coordinates on the electro-oxygenation performance line of each heat of steel at different stages exceed the upper and lower boundary lines of the electro-oxygenation guideline. If they do, it is determined that there is an abnormality in the smelting power supply and oxygen supply process of this heat of steel at that stage, and an abnormality mark is made in the record of the corresponding heat in the relational database.

[0116] 6) Automatically provides alarm prompts and evaluation reports for abnormalities in the power and oxygen supply process of smelting, reminding production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the power and oxygen guideline, and optimize the power and oxygen supply process of smelting;

[0117] Furthermore, the automatic system provides alarm prompts and evaluation reports for abnormalities in the smelting power and oxygen supply process, reminding production personnel to adjust power supply and oxygen blowing parameters according to the range provided by the power and oxygen guidelines, thereby optimizing the smelting power and oxygen supply process, including:

[0118] On the fixed or mobile monitoring terminal, the actual performance line and the guide line of the selected furnace are displayed;

[0119] Alarms are issued for abnormal coordinate points occurring at different stages of smelting, reminding production personnel to adjust power supply and oxygen blowing parameters according to the range provided by the electric oxygen guideline, and to optimize the power supply and oxygen supply process of smelting.

[0120] The system automatically generates anomaly statistics reports based on time, work group, and steel type, including the number and percentage of anomalies occurring in different time periods, work groups, and steel types, facilitating production process analysis and evaluation.

[0121] The technical solution of this invention, without adding sensors, generates an electro-oxygen performance line for each heat of steel and establishes an oxygen change curve with electricity as the independent variable. The change of a single curve can reflect the electro-oxygen matching relationship during the electric arc furnace smelting process. Since the electric arc furnace smelting process usually reflects different smelting stages and enters different oxygen blowing modes by the amount of electricity supplied, the electro-oxygen curve can reflect the overall power supply and oxygen supply mode of each heat of steel, making it easier to compare the electro-oxygen matching process of smelting stages between different heats.

[0122] The energy input for electric arc furnace smelting mainly consists of electrical energy generated by the power supply and chemical energy generated by oxygen blowing. If too much oxygen is blown, the oxygen content of the molten steel will be too high, affecting the quality of the molten steel and the overall energy consumption, while also increasing the consumption of deoxidizer. If the oxygen blowing is insufficient, it will affect the fluxing effect, resulting in a longer melting period and increased smelting power consumption.

[0123] The integrated monitoring method for power and oxygen supply in electric arc furnace smelting described in this invention provides a benchmark reference for power and oxygen supply modes for different steel grades by establishing an electric oxygen guideline based on historical best-energy-consumption furnace samples. Once the electric oxygen curve generated by the power and oxygen supply mode used in the current furnace deviates from the range of the electric oxygen guideline, an abnormal alarm will be issued in a timely manner, prompting production personnel to adjust the power and oxygen supply parameters to prevent large deviations in smelting energy input, reduce the difference from the best-energy-consumption furnace samples, and avoid unnecessary energy losses.

[0124] Because various steel grades are guided by demonstration lines for electric oxygen production and monitored in real time, the blind and arbitrary adjustment of production process parameters caused by differences in the skill level of production operators is avoided. This reduces the reliance on manual operating experience and makes the smelting process more closely follow the electric oxygen combination process of the heat with optimal energy consumption. As a result, the differences between different heats of the same type of steel are reduced, promoting energy conservation and consumption reduction in steel plants and improving the level of intelligence in electric arc furnace steelmaking.

[0125] Secondly, such as Figure 6 As shown, the technical solution of the present invention also provides a comprehensive monitoring system for power supply and oxygen supply in electric arc furnace smelting, including: a data acquisition module 1, a storage and analysis module 2, and a report display module 3.

[0126] The data acquisition module 1 includes a time-series data acquisition module 11 and a heat-time data acquisition module 12. It is used to collect time-series process data and heat-time performance data from different sources for each heat of steel and send them to the storage and analysis module 2.

[0127] The timing data acquisition module 11 is connected to the process detection instrument 4 and is used to periodically acquire signals such as the power supply, oxygen supply, and smelting status of each furnace of steel.

[0128] In this example, the timing data acquisition module 11 is a programmable logic controller (PLC) connected to the basic automation network;

[0129] The furnace data acquisition module 12 is connected to the process control system 5 and is used to collect the furnace number, steel grade mark, molten iron ratio, processing start time, processing end time, steel output, and energy consumption of each furnace of steel.

[0130] In this example, the furnace data acquisition module 12 is a process control server connected to the production information network;

[0131] The storage analysis module 2, such as Figure 6 As shown, connected to the data acquisition module 1, it includes: a data storage module 21, a data alignment module 22, an electro-oxygen performance line determination module 23, an electro-oxygen guidance line determination module 24, and an anomaly determination module 25.

[0132] The storage analysis module 2 in this example uses a workshop edge server, which has a central processing unit, memory, hard disk storage and network interface, and is connected to the basic automation and production information network via Ethernet.

[0133] The data storage module 21, with the furnace as the recording unit, is used to record and save the time-series process data and furnace performance data sent by the data acquisition module 1;

[0134] The data storage module 21 records and saves the coordinate points of the electric oxygen performance line calculated by the electric oxygen performance line determination module 23 and the coordinate points of the electric oxygen guide line calculated by the electric oxygen guide line determination module 24 for each heat of steel.

[0135] The data storage module 21 includes a real-time database and a relational database. The real-time database uses a table structure with timestamps as the primary index field to store time-series process data periodically collected in real-time by the time-series data acquisition module 11. The relational database uses a table structure with furnace number as the primary index field to store data associated with furnaces collected by the furnace number acquisition module 12. This embodiment uses a DB2 relational database.

[0136] The data alignment module 22 is used to align the time-series process data and smelting furnace number in the real-time database of the data storage module 21, determine the start and end points of the time-series process data for each heat of steel, associate the time-series process data with the smelting furnace number, and store it in the relational database of the data storage module 21.

[0137] The electro-oxygenation performance line determination module 23 is used to automatically generate the coordinates of the electro-oxygenation performance line with equal electrical intervals based on the time sequence process data after each heat of steel is aligned and associated, and transmit it to the data storage module 21 and display it through the report display module 5;

[0138] The electric oxygen guideline determination module 24 is used to determine the coordinates of each data point of the electric oxygen guideline for each heat of steel based on the automatically selected historical sample set of the best energy consumption of the same year, and transmit it to the data storage module 21 and display it through the report display module 3;

[0139] The anomaly determination module 25 is used to compare the electric oxygen performance line and electric oxygen guidance line of each heat of steel calculated by the electric oxygen performance line determination module 23 and the electric oxygen guidance line determination module 24, determine whether there is an anomaly in the power supply and oxygen supply process of each heat of steel at different stages, and record the anomaly determination result in the relational database of the data storage module 21.

[0140] The report display module 3 includes a fixed or mobile monitoring terminal, which is used to query and display the actual electric oxygen supply line and the electric oxygen supply guide line for each heat, alarm the abnormal coordinate points of the power supply and oxygen supply process for each heat of steel, remind production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the electric oxygen supply guide line, optimize the power supply and oxygen supply process of smelting, and display abnormal statistical reports by time, shift and steel type.

[0141] After this invention was applied to a 150t DC electric arc furnace, the differences in smelting energy consumption between different work groups were significantly improved. The average annual electricity consumption per ton of steel decreased from 213kWh before implementation to 208kWh, a reduction of 5kWh per ton of steel, which played a good role in promoting energy conservation and consumption reduction for enterprises.

[0142] In summary, this invention fully leverages the value of historical operational data from the electric arc furnace smelting process. By using electricity as the independent variable to track and analyze oxygen levels, it allows for better observation of the energy balance and changes at each stage of each heat, facilitating the analysis of smelting energy control modes for each heat and enabling comparative analysis of energy consumption differences between different heats. Based on this, a monitoring system is established. By observing and analyzing the changes in the electricity-oxygen curves of historical sample heats of the same steel grade, analysts can promptly adjust the setpoints of current, voltage, oxygen flow, and other factors for the current heat. This ensures that the furnace's smelting energy input does not deviate significantly, avoiding unnecessary energy losses due to improper smelting process control, and thus identifying areas for energy-saving optimization.

[0143] This invention can be widely used in the field of integrated monitoring of power and oxygen supply during electric arc furnace smelting processes.

Claims

1. A method for integrated monitoring of power supply and oxygen supply in electric arc furnace smelting, characterized in that: Includes the following steps: 1) Collect time-series process data and actual data of each heat of steel related to power supply and oxygen supply monitoring and analysis, and store them in a real-time database and a relational database respectively; 2) Perform furnace number alignment processing on the time sequence process data to associate the time sequence process data with the corresponding furnace number; 3) Based on the time-series process data after each heat of steel is aligned and correlated, an electro-oxygen performance line with equal electrical energy intervals is automatically generated; 4) Based on the automatically selected historical sample set of heats with the best energy consumption compared to the same period last year, calculate and generate the electric oxygen guideline for each heat of steel; 5) Compare the actual and guide lines of the electric oxygen supply for each heat of steel to determine whether there are any abnormalities in the power supply and oxygen supply process of each heat of steel. 6) Automatically provides alarm prompts and evaluation reports for abnormalities in the power and oxygen supply process of smelting, reminding production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the electric oxygen guideline, and optimize the power and oxygen supply process of smelting.

2. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that: The aforementioned integrated monitoring method for power and oxygen supply in electric arc furnace smelting utilizes production data from the electric arc furnace smelting process. By monitoring the changes in power and oxygen consumption curves during the smelting process, it dynamically tracks and compares the trends and ranges of electricity and oxygen changes in each heat of steel during electric arc furnace smelting in real time. Through comparison with the curves corresponding to the historical best heats, it automatically provides abnormal monitoring alarms and evaluations for the power and oxygen supply process of electric arc furnace smelting. This guides improvements in the control of power and oxygen supply process parameters during electric arc furnace smelting, prevents significant deviations in smelting energy input, avoids unnecessary energy losses, reduces reliance on manual operation experience, enhances the intelligence level of electric arc furnace steelmaking, and promotes energy conservation and consumption reduction.

3. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that... In step 1), the time-series process data includes: the amount of electricity and oxygen supplied sampled according to a determined period, as well as the status of the smelting processing signal. The aforementioned furnace performance data is data that is marked and statistically analyzed on a furnace-by-furnace basis, including: the smelting furnace number, steel grade mark, shift number, hot metal ratio, processing start time, processing end time, steel output, and energy consumption for each furnace of steel.

4. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that... In step 2), the time-series process data is aligned with the furnace number to associate the time-series process data with the corresponding smelting furnace number. This specifically includes the following steps: 2.1) Based on the processing start time in the actual data of each furnace and the preset synchronization time difference, locate the starting search point time of each furnace in the real-time database; 2.2) Retrieve the smelting processing signal status of each furnace after the initial search point in the real-time database to determine the start and end points of the time sequence data for that furnace. 2.3) Starting from the starting time of the furnace time sequence process data, each time sequence process data sampling point is read sequentially from the real-time database and saved to the data record associated with the furnace number in the relational database until the end of the furnace time sequence process data.

5. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 4, characterized in that: The starting search point time = furnace processing start time - synchronization time difference; When retrieving the smelting processing signal status after the start search point of each furnace in the real-time database, if the smelting processing signal status changes from "processing ended" to "processing started", then that moment is determined as the starting point of the timing process data for that furnace. If the smelting processing signal status changes from "processing start" to "processing end", then that point in time is determined to be the end point of the timing process data for that furnace. The endpoint of the heat sequence process data is limited by the maximum processing cycle, meaning that the time span of the time sequence process data for each heat of steel does not exceed the maximum processing cycle.

6. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that... In step 3), based on the time-series process data after alignment and correlation for each heat of steel, an electro-oxygen performance line with equal-electricity intervals is automatically generated, specifically including: 3.1) Based on the time-series process data after alignment and association of heats, with the power consumption of each heat as the abscissa and the oxygen consumption as the ordinate, the electro-oxygen curve of each heat is automatically generated according to the power consumption and oxygen consumption of each sampling point. 3.2) Locate the sampling points on the left and right sides of the electric oxygen curve for each heat of steel that are closest to each isoelectric interval point on the x-axis. The coordinates of the left endpoint are (x... l y l ), the right endpoint coordinates are (x r y r ); 3.3) The coordinates of each isoelectric interval point are calculated using two-point interpolation (x...). t y t ), where y t The ordinate of the points with equal electrical quantities is y. x t The x-coordinate of the points at equal electrical intervals; 3.4) After calculating the coordinate data of all the isoelectric interval points, store them in the relational database to generate the electro-oxygen performance line of each heat of steel with isoelectric interval points.

7. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that... In step 4), the step of calculating and generating the electrical oxygen guideline for each heat of steel based on the automatically selected historical sample set of heats with the best energy consumption compared to the same period last year specifically includes: 4.1) Automatically filter the sample set of furnaces with the best historical year-on-year energy consumption from the database; 4.2) In the n-furnace sample with the best energy consumption in the same period in history, calculate the average oxygen flow rate and upper and lower boundary values ​​of each isoelectric interval point according to the data coordinates of the isoelectric interval points on the actual performance line of each furnace steel; 4.3) Store the average oxygen flow rate and upper and lower boundary values ​​at each equal-electricity interval into a relational database to generate an electric oxygen guideline based on the best furnace sample of historical year-on-year energy consumption.

8. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 7, characterized in that... In step 4.1), the automatic selection of the sample set of furnaces with the best energy consumption in the same historical year includes: selecting historical furnaces that meet the same steel grade mark, a certain iron ratio and steel output range, and selecting the top n furnaces with the lowest energy consumption as the sample set of furnaces with the best energy consumption. The specified range of molten iron ratio and tapping quantity is preset in the system, and the range of comparable samples is set using relative values.

9. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 8, characterized in that: The iron-to-metal ratio is set to a range of ±5%, and the tapping rate is set to a range of ±10%.

10. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 7, characterized in that... In step 4.2), the average oxygen flow rate at each isoelectric interval is: y i It is the oxygen flow rate of each heat of steel at a certain isoelectric interval point, and n is the number of heat samples selected. The upper boundary value of oxygen flux at each isoelectric interval point is: The lower boundary value of oxygen flux at each isoelectric interval point is: Where δ is the deviation band and σ is the standard deviation.

11. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that... Step 5), which involves comparing the actual electro-oxygen performance line and the electro-oxygen guideline for each heat of steel to determine whether there are any abnormalities in the power supply and oxygen supply process for each heat of steel, specifically includes: 5.1) The power supply and oxygen supply process of electric arc furnace smelting is divided into different stages according to different power supply ranges; 5.2) Determine whether the data coordinates on the electro-oxygenation performance line of each heat of steel at different stages exceed the upper and lower boundary lines of the electro-oxygenation guideline. If they do, it is determined that there is an abnormality in the smelting power supply and oxygen supply process of this heat of steel at that stage, and an abnormality mark is made in the record of the corresponding heat in the relational database.

12. The integrated monitoring method for power supply and oxygen supply in electric arc furnace smelting according to claim 1, characterized in that: Step 6) includes at least: On the fixed or mobile monitoring terminal, the actual line and guide line of the selected furnace are displayed; Alarms are issued for abnormal coordinate points occurring at different stages of smelting, reminding production personnel to adjust power supply and oxygen blowing parameters according to the range provided by the electric oxygen guideline, and to optimize the power supply and oxygen supply process of smelting. The system automatically generates anomaly statistics reports based on time, work group, and steel type, including the number and percentage of anomalies occurring in different time periods, work groups, and steel types, facilitating production process analysis and evaluation.

13. A comprehensive monitoring system for power and oxygen supply in electric arc furnace smelting, characterized in that: include: The data acquisition module, storage and analysis module, and report display module are connected in sequence. The data acquisition module is used to collect time-series process data and actual heat data from different sources for each heat of steel, and send them to the storage and analysis module. The storage and analysis module is connected to the data acquisition module; The report display module is used to query and display the actual performance line and guide line of each heat, alarm the abnormal coordinate points of the power supply and oxygen supply process of each heat of steel, remind production personnel to adjust the power supply and oxygen blowing parameters according to the range provided by the guide line, optimize the power supply and oxygen supply process of smelting, and display abnormal statistical reports by time, shift and steel type. The aforementioned integrated monitoring system for power and oxygen supply in electric arc furnace smelting tracks and analyzes oxygen levels using electricity as the independent variable. It observes the energy balance and changes at each stage of each heat of steel, analyzes the smelting energy control mode for each heat, and compares and analyzes the differences in energy consumption between different heats. By observing and analyzing the changes in the electric-oxygen curves of historical sample heats of the same steel grade, it adjusts the set values ​​of factors including current, voltage, and oxygen flow rate for the current heat in a timely manner to ensure that the furnace's smelting energy input does not deviate significantly, avoids unnecessary energy losses caused by improper control of the smelting process, and identifies areas for energy-saving optimization.

14. The integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to claim 13, characterized in that: The data acquisition module includes a time-series data acquisition module and a furnace-time data acquisition module; The time-series data acquisition module is connected to the process detection instrument and is used to periodically acquire signals such as the power supply, oxygen supply, and smelting status of each heat of steel. The furnace data acquisition module is connected to the process control system and is used to collect the furnace number, steel grade mark, iron-to-water ratio, processing start time, processing end time, steel output, and energy consumption for each furnace.

15. The integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to claim 14, characterized in that: The timing data acquisition module is a programmable logic controller (PLC) connected to the basic automation network. The furnace data acquisition module is a process control server connected to the production information network.

16. The integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to claim 13, characterized in that: The storage and analysis module includes: a data storage module, a data alignment module, an electro-oxygen performance line determination module, an electro-oxygen guidance line determination module, and an anomaly detection module; The data storage module, with the furnace as the recording unit, is used to record and save the time-series process data and furnace performance data sent by the data acquisition module; The data storage module records and saves the coordinate points of the electro-oxidation performance line calculated by the electro-oxidation performance line determination module and the coordinate points of the electro-oxidation guidance line calculated by the electro-oxidation guidance line determination module for each heat of steel. The data storage module includes a real-time database and a relational database; The data alignment module is used to align the time-series process data and smelting furnace number in the real-time database of the data storage module, determine the start and end points of the time-series process data for each heat of steel, associate the time-series process data with the smelting furnace number, and store it in the relational database of the data storage module. The electro-oxygenation performance line determination module is used to automatically generate the coordinates of the electro-oxygenation performance line with equal electrical energy intervals based on the time sequence process data after alignment and association of each heat of steel, and transmit it to the data storage module and display it through the report display module; The aforementioned electric oxygen guideline determination module is used to determine the coordinates of each data point of the electric oxygen guideline for each heat of steel based on the automatically filtered historical sample set of heats with the best energy consumption compared to the same period last year, and transmit it to the data storage module and display it through the report display module; The aforementioned anomaly determination module is used to compare the electric oxygen performance line and electric oxygen guidance line calculated by the electric oxygen performance line determination module and the electric oxygen guidance line determination module for each heat of steel, determine whether there are any anomalies in the power supply and oxygen supply process of each heat of steel at different stages, and record the anomaly determination results in the relational database of the data storage module.

17. The integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to claim 16, characterized in that: The real-time database adopts a table structure with timestamp as the main index field, which is used to store the time-series process data collected periodically in real time by the time-series data acquisition module. The relational database uses a table structure with the furnace number as the main index field to store the data associated with the furnace number collected by the furnace number data acquisition module.

18. The integrated monitoring system for power supply and oxygen supply in electric arc furnace smelting according to claim 13, characterized in that: The storage and analysis module uses a workshop edge server, which has a central processing unit, memory, hard disk storage and network interface, and is connected to the basic automation and production information network via Ethernet; The report display module includes a fixed or mobile monitoring terminal.

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