Method and device for determining thickness of slag crust

Abstract

The embodiment of the invention provides a slag crust thickness determination method and device, and belongs to the technical field of blast furnaces. The method comprises the steps that off-line data and on-line data are obtained; determining slag crust property data based on the ore data, and determining a slag adhering grid model based on the designed furnace profile data and the slag crust property data; carrying out slag adhering numerical simulation on the basis of the slag adhering grid model, and determining a slag adhering numerical simulation model; determining offline slag crust numerical simulation data based on the slag adhering numerical simulation model and the working condition data; and constructing a slag crust thickness online calculation model based on the offline slag crust numerical simulation data, and determining the slag crust thickness based on the constructed slag crust thickness online calculation model. On the basis of actual blast furnace data, the calculation process is closely combined with the site, the calculation result is accurate, the calculation efficiency is high, the real-time performance is high, the method is suitable for blast furnaces with different coolers, the popularization capacity is high, the slag crust thickness is calculated in real time according to the method, operators can be effectively assisted in controlling the blast furnace, and it is guaranteed that the blast furnace stably and smoothly runs.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of blast furnace technology, and in particular to a method for determining slag skin thickness. Background Art

[0002] The thickness of the slag skin of the blast furnace is the focus of the operator. The thickness of the slag skin can characterize the working state of the internal surface of the blast furnace. With the fluctuation of the furnace condition and the cooling system, the thickness of the slag skin is in a dynamic change process. The change of the slag skin thickness can also reflect the state of the blast furnace. When the slag layer has abnormal phenomena such as large-scale shedding or thickening, this will lead to a drop in furnace temperature, uneven distribution of gas flow, and even accidents such as furnace body burning through. Especially in the middle and late stages of the furnace campaign, the furnace lining is almost non-existent, and the blast furnace mainly relies on the slag layer to protect the furnace body. Therefore, maintaining a reasonable slag layer thickness and real-time monitoring of the slag skin thickness are important means to ensure the stable and smooth operation of the blast furnace. However, since the internal state of the blast furnace cannot be directly observed during operation, in actual production, the slag skin thickness of the blast furnace is indirectly judged based on experience based on data such as cooling water temperature difference and thermocouple temperature. However, the judgment of the furnace state under different furnace conditions and different operating conditions based on experience often has errors and is difficult to quantify.

[0003] In the existing slag skin thickness calculation method, the thermal conductivity of the slag layer and the slag hanging temperature are generally set values, which are not closely combined with the actual blast furnace charge. However, for the blast furnace slag skin thickness, the heat transfer process design of the one-dimensional and two-dimensional heat transfer models is unreasonable, and the results cannot represent the slag skin thickness distribution of the entire cooler. The general empirical judgment method cannot directly quantify the slag skin thickness. The three-dimensional heat transfer model of the cooler is more in line with the actual situation, but the calculation cost is high and the consumption time is long. Therefore, a better solution is urgently needed. Summary of the invention

[0004] In view of this, the embodiments of this specification provide a method for determining slag thickness. One or more embodiments of this specification also relate to a slag thickness determination device, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0005] According to a first aspect of an embodiment of this specification, a method for determining slag skin thickness is provided, comprising: Obtain offline data and online data; offline data includes design furnace data, and online data includes operating data and ore data; Determine the slag skin property data based on the ore data, and determine the slag grid model based on the designed furnace data and the slag skin property data; Perform slag numerical simulation based on the slag grid model and determine the slag numerical simulation model; Determine the offline slag skin numerical simulation data based on the slag hanging numerical simulation model and working condition data; An online calculation model for slag skin thickness is constructed based on offline slag skin numerical simulation data, and the slag skin thickness is determined based on the constructed online calculation model for slag skin thickness.

[0006] In a possible implementation, determining slag crust property data based on ore data includes: Determine the ore to be charged into the blast furnace based on the ore data; High temperature experiments are carried out based on the ore charged into the blast furnace and the actual proportion to determine the thermal conductivity and slag temperature.

[0007] In a possible implementation, determining the slag grid model based on the designed furnace type data and the slag skin property data includes: Determine the design structure of furnace shell, refractory material and cooler based on the design furnace type data; Construct a three-dimensional physical model of cooler slag based on the design mechanism; Based on the three-dimensional physical model of cooler slag, the meshing technology is used to mesh the model and construct a three-dimensional cooler slag mesh model.

[0008] In a possible implementation, performing dross numerical simulation based on the dross grid model and determining the dross numerical simulation model includes: Determine the iterative calculation method of slag skin, and construct a slag numerical simulation model based on the slag grid model and the iterative calculation method of slag skin.

[0009] In a possible implementation, determining offline slag skin numerical simulation data based on the slag hanging numerical simulation model and operating condition data includes: Based on the slag hanging numerical simulation model, the thickness distribution of the three-dimensional slag skin of the cooler under different working conditions is simulated, and the offline slag skin numerical simulation case library is determined; Determine the slag skin thickness and thermocouple temperature data based on the operating condition data and the offline slag skin numerical simulation case library; The offline slag skin numerical simulation data is determined based on the slag skin thickness and thermocouple temperature data.

[0010] In a possible implementation, an online calculation model for slag skin thickness is constructed based on offline slag skin numerical simulation data, including: The operating condition data and thermocouple temperature data are taken as input, the slag skin thickness is taken as output, and an online calculation model for slag skin thickness is constructed based on supervised machine learning.

[0011] In a possible implementation, the slag skin thickness is determined based on building an online calculation model for the slag skin thickness, including: Get current working condition data and current thermocouple temperature data; The current operating condition data and the current thermocouple temperature data are input into the online calculation model of the slag skin thickness to determine the slag skin thickness.

[0012] According to a second aspect of an embodiment of this specification, a device for determining slag skin thickness is provided, comprising: A data acquisition module is configured to acquire offline data and online data; wherein the offline data includes the designed furnace type data, and the online data includes the operating condition data and the ore data; A model determination module is configured to determine slag skin property data based on ore data, and determine a slag grid model based on designed furnace data and slag skin property data; A numerical simulation module is configured to perform slag numerical simulation based on the slag grid model and determine a slag numerical simulation model; A simulation data module is configured to determine offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the working condition data; The slag skin thickness determination module is configured to construct an online calculation model for slag skin thickness based on offline slag skin numerical simulation data, and determine the slag skin thickness based on the constructed online calculation model for slag skin thickness.

[0013] According to a third aspect of an embodiment of this specification, a computing device is provided, including: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above-mentioned slag skin thickness determination method are implemented.

[0014] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned slag skin thickness determination method are implemented.

[0015] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned slag skin thickness determination method.

[0016] The embodiments of this specification provide a method and device for determining slag skin thickness, wherein the method includes: obtaining offline data and online data; determining slag skin property data based on ore data, and determining a slag grid model based on the designed furnace type data and slag skin property data; performing slag numerical simulation based on the slag grid model, and determining a slag numerical simulation model; determining offline slag skin numerical simulation data based on the slag numerical simulation model and operating condition data; constructing an online calculation model for slag skin thickness based on the offline slag skin numerical simulation data, and determining the slag skin thickness based on the constructed online calculation model for slag skin thickness. By taking actual blast furnace data as a basis, the calculation process is closely integrated with the site, the calculation results are accurate, the calculation efficiency is high, and the real-time performance is strong. It is applicable to blast furnaces with different coolers and has strong promotion capabilities. The slag skin thickness calculated in real time according to this method can effectively assist operators in controlling the blast furnace and ensure the stable and smooth operation of the blast furnace. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of a method for determining slag skin thickness provided by an embodiment of this specification; Figure 2 is a schematic diagram of a method for determining slag skin thickness provided in one embodiment of this specification; Figure 3 It is a structural schematic diagram of a slag skin thickness determination device provided by an embodiment of this specification; Figure 4 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0018] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0019] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0021] In this specification, a method for determining slag skin thickness is provided. This specification also relates to a slag skin thickness determination device, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0022] See also Figure 1 , Figure 1 A flow chart of a method for determining slag skin thickness provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0023] Step 101: Obtain offline data and online data; wherein the offline data includes designed furnace data, and the online data includes operating condition data and ore data.

[0024] In a possible implementation, slag skin property data is determined based on ore data, including: determining ore charged into a blast furnace based on the ore data; and conducting high temperature experiments based on the ore charged into the blast furnace and actual proportions to determine thermal conductivity and slag temperature.

[0025] In practical applications, see Figure 2 The collected blast furnace design data include furnace structure, applied materials and physical parameters of materials. The real-time collected blast furnace operating data include gas temperature data, cooling water data, thermocouple temperature data, etc. The collected blast furnace input ore includes sintered ore, pellets, lump ore, coke and solvent ore for actual production. Based on the actual batching structure of the blast furnace, the ore is proportioned. In the specific example, a melting drop experiment is carried out to collect dripping slag to simulate the slag skin below the soft melting zone of the blast furnace. In the specific example, the temperature at which the slag skin undergoes drastic deformation with increasing temperature is detected, which is defined as the slag hanging temperature. The thermal conductivity of the slag skin at different temperatures is detected in the range from room temperature to slag hanging temperature.

[0026] The embodiments of this specification use actual blast furnace charges and high-temperature experiments as the core to simulate the blast furnace slag skin, obtain the slag skin slagging temperature and thermal conductivity, and the slag skin properties are more in line with reality.

[0027] Step 102: Determine slag crust property data based on ore data, and determine a slag grid model based on designed furnace data and slag crust property data.

[0028] In one possible implementation, a slag mesh model is determined based on the design furnace type data and the slag skin property data, including: determining the design structure of the furnace shell, refractory materials and cooler based on the design furnace type data; constructing a three-dimensional physical model of the cooler slag based on the design structure; and meshing the model based on the three-dimensional physical model of the cooler slag using meshing technology to construct a three-dimensional slag mesh model of the cooler.

[0029] In practical applications, based on the blast furnace design data, according to the design structure of materials such as furnace shell, refractory materials and cooler, the physical properties of materials such as furnace shell, refractory materials, cooler and slag skin are given to construct a three-dimensional physical model of cooler slag. Based on the three-dimensional physical model of cooler slag, the meshing technology is used to mesh the model and construct a three-dimensional cooler slag mesh model. In the specific example, the mesh density is distinguished according to the importance of heat transfer. The slag skin and cooler are the main heat transfer structures, and the mesh division is relatively tight. The heat transfer efficiency of the furnace shell and refractory materials is low, and the mesh division is appropriately sparse.

[0030] Step 103: Perform dross numerical simulation based on the dross grid model to determine the dross numerical simulation model.

[0031] In a possible implementation, dross numerical simulation is performed based on the dross grid model to determine the dross numerical simulation model, including: determining a slag skin iterative calculation method, and constructing a dross numerical simulation model based on the dross grid model and the slag skin iterative calculation method.

[0032] In practical applications, a slag skin iterative calculation method is designed, which can be applied to the three-dimensional slag mesh model of the cooler. The numerical simulation technology is used to build a three-dimensional slag numerical simulation model of the cooler, and the thickness distribution of the three-dimensional slag skin of the cooler under steady-state conditions is simulated in the simulation software.

[0033] Specifically, a slag skin iterative calculation method is designed. When the temperature of the slag skin grid is greater than the slag hanging temperature, the slag skin grid is considered to disappear; when it is less than the slag hanging temperature, the slag skin grid is considered to exist; this process is iterated, and when all slag skin grids are less than the slag hanging temperature, the iterative process ends. This process is applied to the three-dimensional slag hanging grid model of the cooler. Numerical simulation technology is used to construct a three-dimensional slag hanging numerical simulation model of the cooler, and the thickness distribution of the three-dimensional slag skin of the cooler under steady-state conditions is simulated in the simulation software.

[0034] The embodiment of this specification applies a three-dimensional heat transfer method and a slag skin iterative calculation method in a three-dimensional slag hanging numerical simulation model of a cooler, which can simulate the thickness of the slag skin at different positions, and the slag skin simulation result is more accurate and has strong interpretability.

[0035] Step 104: Determine offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the operating condition data.

[0036] In a possible implementation, offline slag skin numerical simulation data is determined based on the slag numerical simulation model and operating condition data, including: simulating the thickness distribution of the three-dimensional slag skin of the cooler under different operating conditions based on the slag numerical simulation model, and determining an offline slag skin numerical simulation case library; determining slag skin thickness and thermocouple temperature data based on the operating condition data and the offline slag skin numerical simulation case library; and determining offline slag skin numerical simulation data based on the slag skin thickness and thermocouple temperature data.

[0037] In practical applications, based on the three-dimensional slag numerical simulation model of the cooler, different working conditions are set, including gas temperature, cooling water speed and cooling water temperature, to simulate the thickness distribution of the three-dimensional slag skin of the cooler under different working conditions, and form an offline slag skin numerical simulation case library. Based on the offline slag skin data simulation case library, the slag skin thickness and thermocouple temperature data corresponding to the working condition data are extracted, and these offline data are used to construct a data set.

[0038] Step 105: constructing an online calculation model for slag skin thickness based on the offline slag skin numerical simulation data, and determining the slag skin thickness based on the constructed online calculation model for slag skin thickness.

[0039] In a possible implementation, an online calculation model for slag skin thickness is constructed based on offline slag skin numerical simulation data, including: taking operating condition data and thermocouple temperature data as input, taking slag skin thickness as output, and constructing an online calculation model for slag skin thickness based on supervised machine learning.

[0040] In practical applications, based on offline data sets, with operating condition data and thermocouple temperature data as input and slag thickness as output, supervised machine learning is used to analyze the nonlinear relationship between input and output data to construct an online calculation model for slag thickness.

[0041] The real-time calculation method of slag skin thickness in the embodiment of this specification is based on actual on-site data, and is calculated using numerical simulation and machine learning technology. The information source is accurate, the application cost is low, the analysis method has strong generalization ability and real-time performance, and can be extended to blast furnaces with different coolers. The online calculation model of slag skin thickness is constructed based on offline data and machine learning, which realizes offline data value mining and online application, covers a wide range of working conditions, and has accurate calculation results and strong real-time performance.

[0042] In a possible implementation, the slag skin thickness is determined based on building an online calculation model for the slag skin thickness, including: obtaining current operating condition data and current thermocouple temperature data; inputting the current operating condition data and the current thermocouple temperature data into the online calculation model for the slag skin thickness to determine the slag skin thickness.

[0043] In practical applications, based on the real-time collected blast furnace operating data and thermocouple temperature data, the slag skin thickness online calculation model is input, and the real-time slag skin thickness data is obtained and pushed to the human-computer interaction interface to realize real-time monitoring of the slag skin thickness.

[0044] It should be noted that, since there are multiple groups of blast furnace operating data and thermocouple temperature data, the slag skin thickness data finally obtained includes slag skin thickness data at multiple heights and multiple angles of the cooler.

[0045] The embodiments of this specification provide a method and device for determining slag skin thickness, wherein the method includes: obtaining offline data and online data; determining slag skin property data based on ore data, and determining a slag grid model based on the designed furnace type data and slag skin property data; performing slag numerical simulation based on the slag grid model, and determining a slag numerical simulation model; determining offline slag skin numerical simulation data based on the slag numerical simulation model and operating condition data; constructing an online calculation model for slag skin thickness based on the offline slag skin numerical simulation data, and determining the slag skin thickness based on the constructed online calculation model for slag skin thickness. By taking actual blast furnace data as a basis, the calculation process is closely integrated with the site, the calculation results are accurate, the calculation efficiency is high, and the real-time performance is strong. It is applicable to blast furnaces with different coolers and has strong promotion capabilities. The slag skin thickness calculated in real time according to this method can effectively assist operators in controlling the blast furnace and ensure the stable and smooth operation of the blast furnace.

[0046] Corresponding to the above method embodiment, this specification also provides an embodiment of a device for determining slag skin thickness. Figure 3 FIG. 2 shows a schematic diagram of a slag skin thickness determination device provided in one embodiment of the present specification. Figure 3 As shown, the device comprises: The data acquisition module 301 is configured to acquire offline data and online data; wherein the offline data includes the designed furnace type data, and the online data includes the operating condition data and the ore data; The model determination module 302 is configured to determine the slag crust property data based on the ore data, and determine the slag grid model based on the designed furnace data and the slag crust property data; The numerical simulation module 303 is configured to perform dross numerical simulation based on the dross grid model and determine a dross numerical simulation model; A simulation data module 304 is configured to determine offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the operating condition data; The slag skin thickness determination module 305 is configured to construct an online calculation model for slag skin thickness based on the offline slag skin numerical simulation data, and determine the slag skin thickness based on the constructed online calculation model for slag skin thickness.

[0047] In a possible implementation, determining slag crust property data based on ore data includes: Determine the ore to be charged into the blast furnace based on the ore data; High temperature experiments are carried out based on the ore charged into the blast furnace and the actual proportion to determine the thermal conductivity and slag temperature.

[0048] In a possible implementation, determining the slag grid model based on the designed furnace type data and the slag skin property data includes: Determine the design structure of furnace shell, refractory material and cooler based on the design furnace type data; Construct a three-dimensional physical model of cooler slag based on the design mechanism; Based on the three-dimensional physical model of cooler slag, the meshing technology is used to mesh the model and construct a three-dimensional cooler slag mesh model.

[0049] In a possible implementation, performing dross numerical simulation based on the dross grid model and determining the dross numerical simulation model includes: Determine the iterative calculation method of slag skin, and construct a slag numerical simulation model based on the slag grid model and the iterative calculation method of slag skin.

[0050] In a possible implementation, determining offline slag skin numerical simulation data based on the slag hanging numerical simulation model and operating condition data includes: Based on the slag hanging numerical simulation model, the thickness distribution of the three-dimensional slag skin of the cooler under different working conditions is simulated, and the offline slag skin numerical simulation case library is determined; Determine the slag skin thickness and thermocouple temperature data based on the operating condition data and the offline slag skin numerical simulation case library; The offline slag skin numerical simulation data is determined based on the slag skin thickness and thermocouple temperature data.

[0051] In a possible implementation, an online calculation model for slag skin thickness is constructed based on offline slag skin numerical simulation data, including: The operating condition data and thermocouple temperature data are taken as input, the slag skin thickness is taken as output, and an online calculation model for slag skin thickness is constructed based on supervised machine learning.

[0052] In a possible implementation, the slag skin thickness is determined based on building an online calculation model for the slag skin thickness, including: Get current working condition data and current thermocouple temperature data; The current operating condition data and the current thermocouple temperature data are input into the online calculation model of the slag skin thickness to determine the slag skin thickness.

[0053] The above is a schematic scheme of a slag skin thickness determination device of this embodiment. It should be noted that the technical scheme of the slag skin thickness determination device and the technical scheme of the slag skin thickness determination method described above belong to the same concept, and the details not described in detail in the technical scheme of the slag skin thickness determination device can be referred to the description of the technical scheme of the slag skin thickness determination method described above.

[0054] Figure 4 The block diagram of a computing device 400 according to one embodiment of the present specification is shown. The components of the computing device 400 include but are not limited to a memory 410 and a processor 420. The processor 420 is connected to the memory 410 via a bus 430, and the database 450 is used to store data.

[0055] The computing device 400 also includes an access device 440 that enables the computing device 400 to communicate via one or more networks 460. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 440 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0056] In one embodiment of the present specification, the above components of the computing device 400 and Figure 4 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 4 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0057] The computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 400 may also be a mobile or stationary server.

[0058] The processor 420 is used to execute the following computer executable instructions, which implement the steps of the above-mentioned slag skin thickness determination method when executed by the processor. The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above-mentioned slag skin thickness determination method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above-mentioned slag skin thickness determination method.

[0059] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the above-mentioned method for determining slag skin thickness.

[0060] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above-mentioned method for determining the thickness of the slag crust belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above-mentioned method for determining the thickness of the slag crust.

[0061] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned method for determining the thickness of the slag skin.

[0062] The above is a schematic scheme of a computer program of this embodiment. It should be noted that the technical scheme of the computer program and the technical scheme of the above-mentioned method for determining the thickness of the slag crust are of the same concept, and the details not described in detail in the technical scheme of the computer program can be referred to the description of the technical scheme of the above-mentioned method for determining the thickness of the slag crust.

[0063] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0064] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0065] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0066] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0067] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for determining the thickness of slag skin, It is characterized in that include: Obtaining offline data and online data; wherein the offline data includes design furnace data, and the online data includes operating condition data and ore data; Determine slag crust property data based on the ore data, and determine a slag grid model based on the designed furnace type data and the slag crust property data; Perform dross numerical simulation based on the dross grid model to determine a dross numerical simulation model; Determining offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the operating condition data; An online calculation model for slag skin thickness is constructed based on the offline slag skin numerical simulation data, and the slag skin thickness is determined based on the constructed online calculation model for slag skin thickness.

2. The method according to claim 1, It is characterized in that Determining slag skin property data based on the ore data includes: Determining ore to be charged into a blast furnace based on the ore data; Based on the ore charged into the blast furnace and the actual proportion, a high temperature experiment is carried out to determine the thermal conductivity and the slag temperature.

3. The method according to claim 1, It is characterized in that Determining a slag grid model based on the designed furnace type data and the slag skin property data includes: Determining the design structure of the furnace shell, refractory materials and cooler based on the designed furnace type data; Constructing a three-dimensional physical model of cooler slag based on the design mechanism; Based on the three-dimensional physical model of the cooler slag, a meshing technology is applied to mesh the model to construct a three-dimensional cooler slag mesh model.

4. The method according to claim 1, It is characterized in that Performing dross numerical simulation based on the dross grid model and determining the dross numerical simulation model includes: A slag skin iterative calculation method is determined, and a slag skin numerical simulation model is constructed based on the slag skin grid model and the slag skin iterative calculation method.

5. The method according to claim 1, It is characterized in that Determining offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the operating condition data includes: Based on the slag hanging numerical simulation model, the thickness distribution of the three-dimensional slag skin of the cooler under different working conditions is simulated to determine the offline slag skin numerical simulation case library; Determining slag skin thickness and thermocouple temperature data based on the operating condition data and the offline slag skin numerical simulation case library; The offline slag skin numerical simulation data is determined based on the slag skin thickness and thermocouple temperature data.

6. The method according to claim 5, It is characterized in that An online calculation model for slag skin thickness is constructed based on the offline slag skin numerical simulation data, including: The operating condition data and the thermocouple temperature data are taken as input, the slag skin thickness is taken as output, and an online calculation model for slag skin thickness is constructed based on supervised machine learning.

7. The method according to claim 1, It is characterized in that Based on the online calculation model of slag skin thickness, the slag skin thickness at different cooler elevations and different angles is determined, including: Get current working condition data and current thermocouple temperature data; The current operating condition data and the current thermocouple temperature data are input into the slag skin thickness online calculation model to determine the slag skin thickness.

8. A device for determining the thickness of slag skin, It is characterized in that include: A data acquisition module is configured to acquire offline data and online data; wherein the offline data includes designed furnace type data, and the online data includes operating condition data and ore data; A model determination module is configured to determine slag crust property data based on the ore data, and determine a slag grid model based on the designed furnace type data and the slag crust property data; A numerical simulation module is configured to perform dross numerical simulation based on the dross grid model and determine a dross numerical simulation model; A simulation data module is configured to determine offline slag skin numerical simulation data based on the slag hanging numerical simulation model and the operating condition data; The slag skin thickness determination module is configured to construct an online calculation model for slag skin thickness based on the offline slag skin numerical simulation data, and determine the slag skin thickness based on the constructed online calculation model for slag skin thickness.

9. A computing device, It is characterized in that include: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for determining the slag skin thickness according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the method for determining slag skin thickness according to any one of claims 1 to 7.

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