A method, system, device and medium for identifying the collapse and sliding materials of a blast furnace

Abstract

The present application provides a method, system, device and medium for identifying collapse and landslide materials in a blast furnace. The method includes: determining the stockline values corresponding to the last two times of lifting the sounding rod according to the sounding rod signal; determining the fitting production value corresponding to the production process parameters between the last two times of lifting the sounding rod according to the mapping relationship between the preset theoretical fitting production and the production process parameters; determining the material volume and the average burden thickness between the last two times of lifting the sounding rod according to the charging information and the under-bunker material information; determining the height of the burden surface drop between the last two times of lifting the sounding rod according to the fitting production value and the material volume; determining the collapse height of the burden between the last two times of lifting the sounding rod according to the height of the burden surface drop, the stockline value and the average burden thickness; and determining the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset abnormal interval of the burden.

Description

Technical Field

[0001] The present invention relates to the field of intelligent smelting, and particularly to a method, system, device and medium for identifying charging collapse and slip in a blast furnace. Background Art

[0002] During the production process of a blast furnace, due to the imbalance between the descent of the burden column and the rise of the gas in the furnace, charging collapse or slip occurs. Charging collapse or slip will disrupt the layered burden, cause mixing of the burden layer, deteriorate the permeability of the burden column, and in severe cases, even cause a cold furnace. Therefore, during production, technicians will always pay attention to the phenomena of charging collapse and slip, and when large charging collapses or continuous charging collapses and slips occur, measures such as reducing the blast volume, reducing the oxygen content, or adding net coke will be taken to prevent further deterioration of the furnace condition.

[0003] In order to grasp the changes in the furnace condition in real time, during production, the number of charging collapses and slips will be manually counted and used as an index to evaluate the quality of the furnace condition. At present, technicians mainly identify charging collapse or slip based on the change of the mechanical sounding line. When the sounding line suddenly drops, manually according to the difference before and after the sudden change of the sounding line, when the difference is within the slip determination interval, it is called slip, and when it is within the charging collapse determination interval, it is called charging collapse. This manual judgment method has strong subjectivity, poor timeliness, and no quantification. Summary of the Invention

[0004] In view of the above problems existing in the prior art, the present invention proposes a method, system, device and medium for identifying charging collapse and slip in a blast furnace, mainly solving the problems that the existing method for identifying charging collapse and slip abnormally relies on manual collection of information for evaluation and decision-making, and has poor reliability and timeliness.

[0005] In order to achieve the above object and other objects, the technical solution adopted by the present invention is as follows.

[0006] The present application provides a method for identifying charging collapse and slip in a blast furnace, including:

[0007] Obtaining sounding signals, charging information, material information under the bin, and production process parameters;

[0008] Determining the burden line values corresponding to the most recent two times of lifting the sounding based on the sounding signals;

[0009] Determining the fitting output value corresponding to the production process parameters between the most recent two times of lifting the sounding based on the mapping relationship between the preset theoretical fitting output and the production process parameters;

[0010] Determining the material volume and average burden thickness between the most recent two times of lifting the sounding based on the charging information and the material information under the bin;

[0011] Determining the height of the burden surface drop between the most recent two times of lifting the sounding based on the fitting output value and the material volume;

[0012] Determine the collapse height of the burden between the most recent two lifting of the sounding rod according to the height of the burden surface drop, the stockline value, and the average burden thickness;

[0013] Determine the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset abnormal interval of the burden.

[0014] In an embodiment of the present application, after determining the abnormal type of the current burden collapse height, it further includes:

[0015] Determine the abnormal level corresponding to the abnormal type according to the abnormal type, the frequency of occurrence of the abnormality, or the change rate of the preset blast furnace index when the abnormality occurs;

[0016] Generate an alarm message according to the abnormal type and the corresponding abnormal level;

[0017] Call the corresponding adjustment suggestion in the preset adjustment suggestion library according to the alarm message and output it to the target terminal for display.

[0018] In an embodiment of the present application, determining the stockline values corresponding to the most recent two lifting of the sounding rod according to the sounding rod signal includes:

[0019] When it is determined according to the sounding rod signal that the state of the sounding rod changes to lifting the sounding rod, read the stockline value of the sounding rod to generate a stockline record when lifting the sounding rod;

[0020] Obtain the stockline values corresponding to the two most recent lifting of the sounding rod in the stockline record when lifting the sounding rod that are closest to the current time node.

[0021] In an embodiment of the present application, before determining the fitting output value corresponding to the production process parameters between the most recent two lifting of the sounding rod according to the mapping relationship between the preset theoretical fitting output and the production process parameters, it includes:

[0022] Obtain the historical production process parameters of the blast furnace within a preset time period, where the historical production process parameters include blast volume, oxygen content, blast temperature, carbon monoxide utilization rate, and total furnace heat load;

[0023] Perform multiple linear fitting according to the historical production process parameters to obtain the mapping relationship between the theoretical fitting output and the production process parameters.

[0024] In an embodiment of the present application, determining the material volume and the average burden thickness between the most recent two lifting of the sounding rod according to the charging information and the material information under the bin includes:

[0025] Determine the charging batches and material numbers between the most recent two lifting of the sounding rod according to the charging information;

[0026] Call the bulk specific gravity of the corresponding material in the preset material library according to the material number;

[0027] Determine the weight and bulk density of the material under the chute in the charging batches between the two most recent sounding operations according to the material information under the chute, where the material under the chute includes sinter, lump ore, pellet, coke, and flux;

[0028] Determine the total volume of the corresponding charging batch as the material volume between the two most recent sounding operations according to the bulk specific gravity, weight, and bulk weight ratio;

[0029] Determine the average burden thickness according to the material volume and the cross-sectional area of the blast furnace throat.

[0030] In an embodiment of the present application, determining the height of the material surface drop between the two most recent sounding operations according to the fitted output value and the material volume includes:

[0031] Determine the total volume of the latest single batch of burden between the two most recent sounding operations according to the charging information and the material information under the chute;

[0032] Calculate the total volume of the material corresponding to the fitted output value according to the total volume of the single batch of burden and the preset iron amount per batch;

[0033] Determine the height of the material surface drop between the two most recent sounding operations according to the ratio of the fitted output value to the cross-sectional area of the blast furnace throat.

[0034] In an embodiment of the present application, determining the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset abnormal burden interval includes:

[0035] The abnormal burden interval includes a preset slipping interval and a slippage interval; if the burden collapse height is within the slipping interval, it is determined that the abnormal type is a slipping abnormality; if the burden collapse height is within the slippage interval, it is determined that the abnormal type is a slippage abnormality.

[0036] The present application also provides a blast furnace slippage and collapse identification system, including:

[0037] A data acquisition module for acquiring sounding signals, charging information, material information under the chute, and production process parameters;

[0038] A burden line value acquisition module for determining the burden line values corresponding to the two most recent sounding operations according to the sounding signals;

[0039] A fitted output acquisition module for determining the fitted output value corresponding to the production process parameters between the two most recent sounding operations according to the mapping relationship between the preset theoretical fitted output and the production process parameters;

[0040] A material information calculation module, configured to determine the material volume and the average burden thickness between the two most recent sounding operations according to the charging information and the under-bunker material information;

[0041] A descent height calculation module, configured to determine the burden surface descent height between the two most recent sounding operations according to the fitted production value and the material volume;

[0042] A height acquisition module, configured to determine the burden collapse height between the two most recent sounding operations according to the burden surface descent height, the stock line value, and the average burden thickness;

[0043] An abnormality identification module, configured to determine the abnormality type of the current burden collapse height according to the comparison result between the burden collapse height and a preset burden abnormality range.

[0044] The present application further provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the blast furnace collapse and slide material identification method are implemented.

[0045] The present application further provides a computer-readable storage medium, on which a computer program is stored. The computer program, when executed by a processor, implements the steps of the blast furnace collapse and slide material identification method.

[0046] As described above, the present application provides a blast furnace collapse and slide material identification method, system, device, and medium, having the following beneficial effects.

[0047] The present application automatically calculates the burden collapse height between two sounding operations for collapse and slide material identification by collecting sounding signals, charging information, under-bunker material information, and production process parameters, facilitating operators to perform corresponding maintenance and repair according to the identification results, reducing dependence on manual labor, and improving the identification stability and the timeliness of problem handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic flow chart of the blast furnace collapse and slide material identification method in an embodiment of the present application.

[0049] Figure 2 It is a schematic diagram of the burden surface collapse height calculation in an embodiment of the present application.

[0050] Figure 3 It is a schematic architecture diagram of the blast furnace collapse and slide material identification system in an embodiment of the present application.

[0051] Figure 4 It is a module diagram of the blast furnace collapse and slide material identification system in an embodiment of the present application.

[0052] Figure 5This is a schematic structural diagram of the device in an embodiment of the present application. Detailed implementation manners

[0053] The following uses specific specific examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0054] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Therefore, only the components related to the present invention are shown in the diagrams, rather than being drawn according to the number, shape, and size of the components in actual implementation. The types, quantities, and proportions of the components in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0055] Please refer to Figure 1 , the present application provides a method for identifying the collapse and sliding materials in a blast furnace, and the method includes the following steps.

[0056] Step S01, obtain the sounding rod signal, charging information, under-bunker material information, and production process parameters.

[0057] In one embodiment, the sounding rod signal may include the sounding rod rising signal, the sounding rod falling signal, the sounding rod following signal, and the stockline value of the sounding rod, etc.; the charging information may include the numbers and batch numbers of coke, ore, etc.; the under-bunker material information may include the weights and bulk densities of sinter, lump ore, pellet ore, coke, and solvent, etc.; the production process parameters may include information such as air volume, oxygen enrichment flow rate, blast temperature, gas utilization rate, reheating load, and theoretical output. The above information can be collected from the preset data acquisition and storage module and the automatic control system. For blast furnaces of different specifications, the production process parameters can be differentially selected, which should not be regarded as a limitation to the embodiments of the present application.

[0058] In one embodiment, the collected data can be cleaned to remove abnormal interference signals, wind reduction records, and other peripheral condition records to avoid the interference of dirty data.

[0059] Step S02, determine the stockline values corresponding to the last two times of lifting the sounding rod according to the sounding rod signal.

[0060] In one embodiment, determining the stockline values corresponding to the last two times of lifting the sounding rod according to the sounding rod signal includes:

[0061] When it is determined according to the sounding rod signal that the state of the sounding rod changes to lifting the sounding rod, read the stockline value of the sounding rod to generate a stockline record when lifting the sounding rod;

[0062] Obtain the stockline values corresponding to the two most recent times of lifting the sounding rod in the stockline record when lifting the sounding rod, respectively, that are closest to the current time node.

[0063] In one embodiment, according to the collected sounding rod signal, when the sounding rod signal changes from "following" to "lifting the rod", the system reads the stockline value of the sounding rod at this time. The following embodiment takes a blast furnace of 2500m 3 as an example. Record the stockline value when lifting the sounding rod this time as L2 = 2.53m, the time t2 is 12:42:24, the stockline value when lifting the sounding rod last time is L1 = 1.48, and the time t1 is 12:38:48, and thus obtain the stockline values of the two most recent times of lifting the sounding rod that are closest to the current time node.

[0064] Step S03, according to the mapping relationship between the preset theoretical fitted output and the production process parameters, determine the fitted output value corresponding to the production process parameters between the two most recent times of lifting the sounding rod.

[0065] In one embodiment, before determining the fitted output value corresponding to the production process parameters between the two most recent times of lifting the sounding rod according to the mapping relationship between the preset theoretical fitted output and the production process parameters, it includes:

[0066] Obtain the historical production process parameters of the blast furnace within a preset time period, where the historical production process parameters include blast volume, oxygen volume, blast temperature, carbon monoxide utilization rate, and total furnace heat load;

[0067] Perform multiple linear fitting based on the historical production process parameters to obtain the mapping relationship between the theoretical fitted output and the production process parameters.

[0068] Specifically, based on the historical data of the blast furnace in the past 30 days, select the parameters that have a greater impact on the output according to the smelting principle, perform multiple linear fitting on the theoretical output, and the independent variables include blast volume, oxygen volume, blast temperature, CO utilization rate, and total furnace heat load data, to obtain a functional relationship of the daily theoretical output OP with respect to the independent variables. This functional relationship is denoted as the mapping relationship between the production process parameters and the fitted output value, and this functional relationship can be expressed as:

[0069] OP = f(BV, O2, BT, ηCO, Q)

[0070] where BV is the cold air flow rate, O2 is the oxygen enrichment flow rate, BT is the blast temperature, ηCO is the CO utilization rate of the top gas of the furnace, and Q is the total furnace heat load.

[0071] For a 2500m 3Taking a blast furnace as an example, through collecting the historical data of the blast furnace and performing multiple linear fitting, a functional relationship of the theoretical daily output OP with respect to the independent variables can be expressed as:

[0072] OP = 699.9965 + 1.277332BV + 0.117566O2 - 4.0164BT

[0073] + 73.45829ηCO - 0.00368Q (R2 = 0.93)

[0074] Wherein, BV is the cold air flow rate, O2 is the oxygen enrichment flow rate, BT is the blast temperature, ηCO is the utilization rate of CO in the top gas of the furnace, and Q is the total heat load of the whole furnace.

[0075] In one embodiment, according to the time between the last two times of lifting the sounding rod and the mapping relationship between the production process parameters and the output, the fitted output value between the last two times of lifting the sounding rod can be calculated.

[0076] Specifically, according to data such as the air volume, oxygen content, blast temperature, CO utilization rate, and total heat load of the whole furnace, the average value of the corresponding independent variable parameters between the two times of lifting the sounding rod is obtained and substituted into the theoretical output fitting equation to obtain the theoretical fitted output OP' between the two times of lifting the sounding rod. Its calculation formula is as follows:

[0077]

[0078] Wherein, △t is the duration between the two times of lifting the sounding rod, 86400 is the total number of seconds in a day, and BV', O2', BT', ηCO', and Q' are the average values of the air volume, oxygen content, blast temperature, CO utilization rate, and total heat load of the whole furnace between the two times of lifting the sounding rod, respectively.

[0079] Step S04, determining the material volume and the average burden thickness between the last two times of lifting the sounding rod according to the charging information and the under-bunker material information.

[0080] In one embodiment, determining the material volume and the average burden thickness between the last two times of lifting the sounding rod according to the charging information and the under-bunker material information includes:

[0081] Determining the charging batches and the material numbers between the last two times of lifting the sounding rod according to the charging information;

[0082] Calling the bulk specific gravity of the corresponding material in the preset material library according to the material number;

[0083] Determining the weight and bulk density of the under-bunker materials of the charging batches between the last two times of lifting the sounding rod according to the under-bunker material information, wherein the under-bunker materials include sinter, lump ore, pellet, coke, and solvent;

[0084] Determine the total volume corresponding to the charging batch as the material volume between the last two times of lifting the sounding rod according to the bulk specific gravity, weight, and bulk weight ratio;

[0085] Determine the average burden thickness according to the material volume and the cross-sectional area of the blast furnace throat.

[0086] In one embodiment, calculate the thickness of the burden during the period between two times of lifting the sounding rod according to the burden material information between the two times of lifting the sounding rod;

[0087] According to the weight of the material during weighing under the bin and the corresponding material name, read the bulk specific gravity of the corresponding material in the database according to the material name, and then calculate the volume V_material of this batch of materials. The calculation formula is as follows:

[0088]

[0089] where m_i is the mass of the i-th material and ρ_i is the bulk specific gravity of the i-th material.

[0090] The average burden thickness d between two times of lifting the sounding rod is calculated as follows:

[0091] d = V 料 / S 喉

[0092] where S_throat is the cross-sectional area of the blast furnace throat.

[0093] Step S05, determine the height of the burden surface drop between the last two times of lifting the sounding rod according to the fitted output value and the material volume.

[0094] In one embodiment, determining the height of the burden surface drop between the last two times of lifting the sounding rod according to the fitted output value and the material volume includes:

[0095] Determine the total volume of the latest single batch of burden (including ore and coke) between the last two times of lifting the sounding rod according to the charging information and the material information under the bin;

[0096] Calculate the total volume of the material corresponding to the fitted output value according to the total volume of the single batch of burden (including ore and coke) and the preset single batch of iron amount;

[0097] Determine the height of the burden surface drop between the last two times of lifting the sounding rod according to the ratio of the fitted output value to the cross-sectional area of the blast furnace throat.

[0098] In one embodiment, since blast furnace charging is performed each time the sounding rod is lifted, the total volume of a single batch of burden (including ore and coke) in the calculation result of the latest burden change can be calculated according to the collected information. According to the total volume of a single batch of burden (including ore and coke) in the calculation result of the latest burden change and the theoretical batch of iron amount, calculate the total volume V_material' of the material corresponding to the fitted output OP' between the two times of lifting the sounding rod. The calculation formula is as follows:

[0099]

[0100] Among them, V is calculated as the total volume of the burden in the latest result, and P_iron is the theoretical batch iron amount in the latest result.

[0101] Calculate the normal descent height h of the burden surface between two consecutive raising of the sounding rod. The calculation formula is as follows:

[0102]

[0103] Step S06, determine the collapse height of the burden between the two most recent raising of the sounding rod according to the descent height of the burden surface, the stock line value, and the average burden thickness.

[0104] Please refer to Figure 2 , Figure 2 , which is a schematic diagram of calculating the collapse height of the burden surface in an embodiment of the present application. Combining the stock line values at the two times of raising the sounding rod, calculate the collapse height of the burden between the two times of raising the sounding rod:

[0105] H = L2 - (L1 - d + h)

[0106] Among them, L1 is the stock line value at the previous raising of the sounding rod, and L2 is the stock line value at the current raising of the sounding rod.

[0107] Step S07, determine the abnormal type of the current collapse height of the burden according to the comparison result between the collapse height of the burden and the preset abnormal interval of the burden.

[0108] In one embodiment, determining the abnormal type of the current collapse height of the burden according to the comparison result between the collapse height of the burden and the preset abnormal interval of the burden includes:

[0109] The abnormal interval of the burden includes a preset slipping interval and a caving interval; if the collapse height of the burden is within the slipping interval, it is determined that the abnormal type is slipping abnormality; if the collapse height of the burden is within the caving interval, it is determined that the abnormal type is caving abnormality.

[0110] In one embodiment, different caving and slipping judgment thresholds can be set according to different blast furnace volumes. When the collapse height of the burden between two consecutive raising of the sounding rod is within the slipping interval, it is determined as slipping, and when it is within the caving interval, it is determined as caving.

[0111] In one embodiment, the judgment rules for caving and slipping are shown in Table 1.

[0112] Table 1

[0113]

[0114] In one embodiment, after determining the abnormal type of the current collapse height of the burden, it further includes:

[0115] Determine the abnormal level corresponding to the abnormal type according to the abnormal type, the frequency of occurrence of the abnormality, or the change rate of the preset blast furnace index when the abnormality occurs;

[0116] Generate an alarm message according to the abnormal type and the corresponding abnormal level;

[0117] Call the corresponding adjustment suggestion in the preset adjustment suggestion library according to the alarm message and output it to the target terminal for display.

[0118] Conduct different types of alarms according to the height of the material surface collapse when the collapse and sliding material occur, and output adjustment suggestions;

[0119] Conduct different types of alarms according to the frequency of occurrence of the collapse and sliding material within a period of time, and output adjustment suggestions;

[0120] Conduct different types of alarms according to the changes in blast furnace indexes such as differential pressure and gas utilization rate after the collapse and sliding material occur, and output adjustment suggestions.

[0121] Table 2

[0122]

[0123] Since the above embodiments take the blast furnace volume of 2500 m 3 as an example, the judgment interval for sliding material is 0.3 - 0.8 m, the judgment interval for collapsing material is greater than 0.8 m, and the calculated height H of the material surface collapse in this case is 1.38 m, so it is a collapsing material event.

[0124] The alarm rules include:

[0125] Conduct an alarm according to the height of the material surface collapse when the collapse and sliding material occur;

[0126] Conduct an alarm according to the frequency of occurrence of the collapse and sliding material within a period of time;

[0127] Conduct an alarm according to the changes in blast furnace indexes such as differential pressure and gas utilization rate after the collapse and sliding material occur.

[0128] Display the situation of the collapse and sliding material and the alarm information through the client for real-time online alarm, and support historical record query, statistical analysis, and trend display.

[0129] Please refer to Figure 3 , Figure 3 which is the schematic diagram of the architecture of the blast furnace collapse and sliding material identification system in an embodiment of the present application.

[0130] The data acquisition and storage module collects and stores in real time the sounding signals and charging information of the primary automation control system, as well as the under-bunker material information and production data associated with the charging information, etc.;

[0131] The data processing module cleans the collected data, removes abnormal interference signals, blast reduction records, and other peripheral condition records, and performs fitting calculations on the processed data.

[0132] The identification and judgment module calculates the collapse height of the burden between two consecutive probe lifts, and automatically and online identifies and determines abnormal furnace conditions such as caving and sliding materials according to the set rule library for judging caving and sliding materials.

[0133] The alarm display module gives real-time online alarms for the identified caving and sliding materials according to the alarm rules, and supports querying of historical records, statistical analysis, and trend display.

[0134] Please refer to Figure 4 , this embodiment provides a blast furnace caving and sliding material identification system for implementing the blast furnace caving and sliding material identification method described in the foregoing method embodiment. Since the technical principle of the system embodiment is similar to that of the foregoing method embodiment, the same technical details will not be repeated.

[0135] In one embodiment, a blast furnace caving and sliding material identification system includes: a data acquisition module 10 for acquiring probe signals, charging information, under-bunker material information, and production process parameters; a stockline value acquisition module 11 for determining the stockline values corresponding to the two most recent probe lifts according to the probe signals; a fitted output acquisition module 12 for determining the fitted output value corresponding to the production process parameters between the two most recent probe lifts according to the mapping relationship between the preset theoretical fitted output and the production process parameters; a material information calculation module 13 for determining the material volume and average burden thickness between the two most recent probe lifts according to the charging information and the under-bunker material information; a descent height calculation module 14 for determining the burden surface descent height between the two most recent probe lifts according to the fitted output value and the material volume; a height acquisition module 15 for determining the burden collapse height between the two most recent probe lifts according to the burden surface descent height, the stockline value, and the average burden thickness; and an abnormality identification module 16 for determining the abnormality type of the current burden collapse height according to the comparison result between the burden collapse height and the preset burden abnormality interval.

[0136] The embodiment of the present application also provides a blast furnace caving and sliding material identification device, which may include: one or more processors; and one or more machine-readable media storing instructions thereon, which when executed by the one or more processors cause the device to execute Figure 1The method described above. In practical applications, this device can be used as a terminal device or a server. Examples of terminal devices may include: smart phones, tablet computers, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, in-vehicle computers, desktop computers, set-top boxes, smart TVs, wearable devices, etc. The embodiments of the present application do not limit specific devices.

[0137] The embodiments of the present application also provide a computer-readable storage medium. One or more modules (programs) are stored in this medium. When the one or more modules are applied to a device, they can cause the device to execute the Figure 1 instructions included in the blast furnace collapse and sliding material identification method in the present application. The machine-readable medium can be any available medium that a computer can store or a data storage device such as a server or a data center that integrates one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0138] Refer to Figure 5 , this embodiment provides a device 80. The device 80 can be a desktop computer, a portable computer, a smart phone, or other devices. Specifically, the device 80 at least includes: a memory 82 and a processor 83 connected through a bus 81. The memory 82 is used to store computer programs, and the processor 83 is used to execute the computer programs stored in the memory 82 to perform all or part of the steps in the foregoing method embodiments.

[0139] The aforementioned system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience in representation, only a thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The communication interface is used to implement communication between the database access device and other devices (such as clients, read-write libraries, and read-only libraries). The memory may include Random Access Memory (RAM), and may also include non-volatile memory, such as at least one disk memory.

[0140] The aforementioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0141] The above embodiments are only illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A method for identifying the collapse and sliding materials in a blast furnace, characterized in that, Including: Obtaining sounding rod signals, charging information, under-bunker material information, and production process parameters; Determining the burden line values corresponding to the two most recent sounding rod lifts according to the sounding rod signals; Determining the burden line values corresponding to the two most recent sounding rod lifts according to the sounding rod signals, including: when it is determined according to the sounding rod signals that the state of the sounding rod changes to lifting the sounding rod, reading the burden line value of the sounding rod to generate a burden line record at the time of lifting the sounding rod; obtaining the burden line values corresponding to the two most recent sounding rod lifts closest to the current time node in the burden line record at the time of lifting the sounding rod; Determining the fitting output value corresponding to the production process parameters between the two most recent sounding rod lifts according to the mapping relationship between the preset theoretical fitting output and the production process parameters; before determining the fitting output value corresponding to the production process parameters between the two most recent sounding rod lifts according to the mapping relationship between the preset theoretical fitting output and the production process parameters, including: obtaining the historical production process parameters of the blast furnace within a preset time period, where the historical production process parameters include blast volume, oxygen content, blast temperature, carbon monoxide utilization rate, and full furnace heat load; performing multiple linear fitting according to the historical production process parameters to obtain the mapping relationship between the theoretical fitting output and the production process parameters; Determine the material volume and average burden thickness between the two most recent lifting of the sounding rod according to the charging information and the under-bunker material information; determining the material volume and average burden thickness between the two most recent lifting of the sounding rod according to the charging information and the under-bunker material information includes: determining the charging batches and material numbers between the two most recent lifting of the sounding rod according to the charging information; calling the bulk specific gravity of the corresponding material in the preset material library according to the material number; determining the mass and bulk density of the under-bunker material of the charging batches between the two most recent lifting of the sounding rod according to the under-bunker material information, where the under-bunker material includes sinter, lump ore, pellet, coke and solvent; determining the total volume of the corresponding charging batches as the material volume between the two most recent lifting of the sounding rod according to the mass and bulk specific gravity; determining the average burden thickness according to the material volume and the cross-sectional area of the blast furnace throat; material volume V 料 The calculation formula is as follows: where m i is the mass of the i-th material, and ρ i is the bulk specific gravity of the i-th material; The average burden thickness d between two sounding rod lifts, and the calculation formula is as follows: d = V 料 / S 喉 Among them, S 喉 is the cross-sectional area of the blast furnace throat; Determining the burden surface descent height between the two most recent sounding rod lifts according to the fitting output value and the material volume; determining the burden surface descent height between the two most recent sounding rod lifts according to the fitting output value and the material volume, including: determining the total volume of the latest single batch of furnace charge between the two most recent sounding rod lifts according to the charging information and the under-bunker material information; calculating the total material volume corresponding to the fitting output value according to the total volume of the single batch of furnace charge and the preset single batch of iron amount; determining the burden surface descent height between the two most recent sounding rod lifts according to the ratio of the fitting output value to the cross-sectional area of the blast furnace throat; Determining the burden collapse height between the two most recent sounding rod lifts according to the burden surface descent height, the burden line value, and the average burden thickness; the formula for calculating the burden collapse height H between two sounding rod lifts is as follows: H = L2-(L1-d+h) where L1 is the burden line value at the previous sounding rod lift, L2 is the burden line value at the current sounding rod lift, and h is the normal burden surface descent height between two sounding rod lifts; Determining the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset burden abnormal interval.

2. The blast furnace collapse and landslide material identification method according to claim 1, characterized in that After determining the abnormal type of the current burden collapse height, it further includes: Determining the abnormal level corresponding to the abnormal type according to the abnormal type, the abnormal occurrence frequency, or the change rate of the preset blast furnace index when the abnormality occurs; Generating an alarm message according to the abnormal type and the corresponding abnormal level; Invoking the corresponding adjustment suggestion in the preset adjustment suggestion library according to the alarm message and outputting it to the target terminal for display.

3. The blast furnace collapse and landslide material identification method according to claim 1, wherein, Determining the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset burden abnormal interval, including: The abnormal burden interval includes a preset slippage interval and a stock collapse interval; if the collapse height of the burden is within the slippage interval, the abnormal type is determined as slippage abnormality; if the collapse height of the burden is within the stock collapse interval, the abnormal type is determined as stock collapse abnormality.

4. A blast furnace collapse and landslide material identification system for implementing the blast furnace collapse and landslide material identification method according to any one of claims 1-3, characterized in that, Comprising: A data acquisition module, configured to obtain sounding rod signals, charging information, under-bunker material information, and production process parameters; A burden line value acquisition module, configured to determine the burden line values corresponding to the last two sounding rod lifts according to the sounding rod signals; A fitted output acquisition module, configured to determine the fitted output value corresponding to the production process parameters between the last two sounding rod lifts according to the mapping relationship between the preset theoretical fitted output and the production process parameters; A material information calculation module, configured to determine the material volume and the average burden thickness between the last two sounding rod lifts according to the charging information and the under-bunker material information; A descent height calculation module, configured to determine the burden surface descent height between the last two sounding rod lifts according to the fitted output value and the material volume; A height acquisition module, configured to determine the burden collapse height between the last two sounding rod lifts according to the burden surface descent height, the burden line value, and the average burden thickness; An abnormality identification module, configured to determine the abnormal type of the current burden collapse height according to the comparison result between the burden collapse height and the preset abnormal burden interval.

5. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the blast furnace slippage and stock collapse identification method according to any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the blast furnace slippage and stock collapse identification method according to any one of claims 1 to 3 are implemented.

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