Method and device for determining remaining thickness of blast furnace lining and state of slag skin

Abstract

The embodiments of this specification provide a method and device for determining the remaining thickness of the blast furnace lining and the slag skin state. The method includes: determining a numerical simulation model based on the designed furnace type data and physical property parameters; determining an offline database without slag skin based on the numerical simulation model, and determining an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the offline database without slag skin; constructing a slag skin state judgment model based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the working condition data; obtaining the current working condition data, and determining the slag skin state based on the current working condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model. Based on the actual data of the blast furnace, integrating a variety of theoretical technologies, accurately calculating the remaining thickness of the lining and scientifically evaluating the slag skin state, with fast response speed, strong real-time performance, low cost, and strong promotion and application capabilities, which helps to assist on-site operators in controlling the blast furnace type, stabilizing the blast furnace condition, and reducing the ironmaking cost.

Description

Technical Field

[0001] The embodiments of this specification relate to the technical field of blast furnaces, and particularly to a method for determining the remaining thickness of a blast furnace lining and the state of slag crusts. Background Art

[0002] The high heat load area is a limiting factor affecting the life of a blast furnace. The high heat load area of a blast furnace mainly relies on lining protection, cooler cooling protection, and furnace wall condensed slag crust protection, which helps prevent the high-temperature edge gas in the furnace from eroding the furnace body, and this is a conventional means to extend the life of a blast furnace. During the actual production process, the remaining thickness of the blast furnace lining cannot be directly monitored, and the state of the slag crust cannot be directly judged whether it is abnormal. On-site operators can only rely on blast furnace operation data combined with their own experience for analysis. This method has weak generalization ability, inconsistent rules, slow response speed, long analysis cycle, and high labor intensity of personnel, seriously affecting the stable production of blast furnaces by on-site personnel and making it difficult to real-time control the blast furnace condition.

[0003] Therefore, there is an urgent need for a better solution. Summary of the Invention

[0004] In view of this, the embodiments of this specification provide a method for determining the remaining thickness of a blast furnace lining and the state of slag crusts. One or more embodiments of this specification simultaneously relate to a device for determining the remaining thickness of a blast furnace lining and the state of slag crusts, 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 the first aspect of the embodiments of this specification, a method for determining the remaining thickness of a blast furnace lining and the state of slag crusts is provided, including:

[0006] Obtain the designed furnace type data, physical property parameters, and working condition data;

[0007] Based on the designed furnace type data and physical property parameters, determine a numerical simulation model;

[0008] Based on the numerical simulation model, determine an offline database without slag crusts, and based on the offline database without slag crusts, determine an intelligent real-time calculation model for the remaining thickness of the blast furnace lining;

[0009] Based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the working condition data, construct a slag crust state judgment model;

[0010] Obtain the current working condition data, and based on the current working condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag crust state judgment model, determine the state of the slag crust.

[0011] In a possible implementation manner, the designed furnace type data includes the blast furnace CAD structure diagram, the blast furnace cooler, the three-dimensional dimension diagram of refractory materials, and the distribution structure diagram;

[0012] The physical property parameters include the thermal conductivity, mass density, and specific heat capacity;

[0013] The operating condition data includes cooling data, temperature data, and air volume data.

[0014] In a possible implementation manner, based on the designed furnace type data and physical property parameters, a numerical simulation model is determined, including:

[0015] Based on the designed furnace type data and physical property parameters, a numerical simulation model is constructed through three-dimensional heat transfer theory.

[0016] In a possible implementation manner, based on the numerical simulation model, a slag-free skin offline database is determined, including:

[0017] Based on the numerical simulation model, operating condition parameters, set thickness of the furnace lining, thermocouple temperature, and maximum operating temperature of the cooler are extracted and collected to construct a slag-free skin offline database.

[0018] In a possible implementation manner, based on the slag-free skin offline database, an intelligent real-time calculation model for the remaining thickness of the blast furnace lining is determined, including:

[0019] Based on the slag-free skin offline database, the set thickness of the furnace lining and operating condition parameters are determined;

[0020] Taking the set thickness of the furnace lining as output data and the operating condition parameters as input data, an intelligent real-time calculation model for the remaining thickness of the blast furnace lining is constructed through supervised machine learning.

[0021] In a possible implementation manner, based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the operating condition data, a slag skin state judgment model is constructed, including:

[0022] Based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, the remaining thickness of the furnace lining at the current moment is determined;

[0023] Based on the remaining thickness of the furnace lining, the operating condition data, and the slag-free skin offline database, a slag skin state judgment model is constructed; among them, the slag skin state judgment model includes a slag skin shedding judgment model, a slag skin too thin judgment model, a slag skin no abnormality judgment model, and a slag skin thickening judgment model.

[0024] In a possible implementation manner, the current operating condition data is obtained, and based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model, the slag skin state is determined, including:

[0025] The current operating condition data is obtained, and the current operating condition data is input into the intelligent real-time calculation model for the remaining thickness of the blast furnace lining to determine the current remaining thickness of the furnace lining;

[0026] Determine the slag skin state based on the current remaining thickness of the furnace lining and the slag skin state judgment model.

[0027] According to the second aspect of the embodiments of the present specification, there is provided a device for determining the state of the blast furnace slag skin, including:

[0028] A data acquisition module configured to acquire designed furnace profile data, physical property parameters, and operating condition data;

[0029] A numerical simulation module configured to determine a numerical simulation model based on the designed furnace profile data and physical property parameters;

[0030] A thickness calculation module configured to determine a slag-skin-free offline database based on the numerical simulation model, and determine an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the slag-skin-free offline database;

[0031] A state judgment module configured to construct a slag skin state judgment model based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the operating condition data;

[0032] A state determination module configured to acquire the current operating condition data, and determine the slag skin state based on the current operating condition data, the real-time calculation model for the blast furnace slag skin thickness, and the slag skin state judgment model.

[0033] According to the third aspect of the embodiments of the present specification, there is provided a computing device, including:

[0034] A memory and a processor;

[0035] 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state are implemented.

[0036] According to the fourth aspect of the embodiments of the present specification, there is provided a computer-readable storage medium storing computer-executable instructions, and when the instructions are executed by a processor, the steps of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state are implemented.

[0037] According to the fifth aspect of the embodiments of the present specification, there is provided a computer program, wherein when the computer program is executed on a computer, the computer is made to execute the steps of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0038] The embodiments of this specification provide a method and device for determining the remaining thickness of a blast furnace lining and the condition of the slag skin. The method includes: obtaining design furnace type data, physical property parameters, and operating condition data; determining a numerical simulation model based on the design furnace type data and physical property parameters; determining an offline database without slag skin based on the numerical simulation model, and determining an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the offline database without slag skin; constructing a slag skin condition judgment model based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the operating condition data; obtaining the current operating condition data, and determining the slag skin condition based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin condition judgment model. Based on the actual data of the blast furnace, integrating various theoretical technologies, accurately calculating the remaining thickness of the lining and scientifically evaluating the condition of the slag skin, with fast response speed, strong real-time performance, low cost, and strong promotion and application capabilities, which helps assist on-site operators in controlling the blast furnace type, stabilizing the blast furnace condition, and reducing the ironmaking cost. Description of the Drawings

[0039] Figure 1 is a flowchart of a method for determining the remaining thickness of a blast furnace lining and the condition of the slag skin provided by an embodiment of this specification;

[0040] Figure 2 is a schematic diagram of the principle of a method for determining the remaining thickness of a blast furnace lining and the condition of the slag skin provided by an embodiment of this specification;

[0041] Figure 3 is a schematic structural diagram of a device for determining the remaining thickness of a blast furnace lining and the condition of the slag skin provided by an embodiment of this specification;

[0042] Figure 4 is a structural block diagram of a computing device provided by an embodiment of this specification. Detailed Embodiments

[0043] Many specific details are set forth in the following description in order to provide a thorough understanding of this specification. However, this specification can be implemented in many other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of this specification. Therefore, this specification is not limited by the specific embodiments disclosed below.

[0044] The terms used in one or more embodiments of this specification are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of this specification. The singular forms "a" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. 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 of the associated listed items.

[0045] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type 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 "when" or "while" or "in response to determining".

[0046] In this specification, a method for determining the remaining thickness of the blast furnace lining and the state of the slag skin is provided. This specification also relates to a device for determining the state of the blast furnace slag skin, a computing device, and a computer-readable storage medium, which will be described in detail one by one in the following embodiments.

[0047] See Figure 1 , Figure 1 shows a flowchart of a method for determining the remaining thickness of the blast furnace lining and the state of the slag skin according to an embodiment of this specification, which specifically includes the following steps.

[0048] Step 101: Obtain the designed furnace type data, physical property parameters, and operating condition data.

[0049] In a possible implementation, the designed furnace type data includes the blast furnace CAD structure diagram, blast furnace cooler, three-dimensional dimension diagram of refractory materials, and distribution structure diagram; the physical property parameters include thermal conductivity, mass density, and specific heat capacity; the operating condition data includes cooling data, temperature data, and air volume data.

[0050] In practical applications, the designed furnace type data in the high heat load area of the blast furnace includes the blast furnace CAD structure diagram, blast furnace cooler, three-dimensional dimension diagram of refractory materials, and distribution structure diagram. The blast furnace materials include cooler materials, refractory materials, furnace shell materials, and filling materials. The physical property parameters include thermal conductivity, mass density, and specific heat capacity. The operating condition data includes cooling data, temperature data, air volume data, etc. Collect the designed furnace type data in the high heat load area of the blast furnace and the physical property parameters of the blast furnace materials, and collect the blast furnace operating condition data in real time. Perform time series frequency unification and integration for the blast furnace operating condition data. Among them, for data problems such as inconsistent frequencies and outlier identification of the operating condition data, the operating condition data is cleaned and integrated by methods such as oversampling, resampling, and isolation forest identification.

[0051] Step 102: Determine a numerical simulation model based on the designed furnace type data and physical property parameters.

[0052] In a possible implementation manner, based on the designed furnace type data and physical property parameters, a numerical simulation model is determined, including: constructing a numerical simulation model based on the designed furnace type data and physical property parameters through three-dimensional heat transfer theory.

[0053] In practical applications, refer to Figure 2 , and based on the designed furnace type data of the high heat load area of the blast furnace and the material physical parameters, a three-dimensional temperature field numerical simulation model of the cooler with different lining thickness settings and working condition parameters in a slag-free state is constructed.

[0054] Specifically, a three-dimensional physical model of the cooler in a slag-free state in the high heat load area is designed based on the designed furnace type data and material physical parameters, and then a three-dimensional heat transfer mathematical model, a three-dimensional grid model of the cooler are constructed respectively, and boundary conditions are applied. Finally, the offline working condition parameters are input to calculate the three-dimensional temperature field of the cooler in the slag skin state by using numerical simulation technology.

[0055] Step 103: Determine a slag-free offline database based on the numerical simulation model, and determine an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the slag-free offline database.

[0056] In a possible implementation manner, determining a slag-free offline database based on the numerical simulation model includes: based on the numerical simulation model, extracting and collecting working condition parameters, lining thickness settings, thermocouple temperatures, and the highest working temperature of the cooler, and constructing a slag-free offline database.

[0057] In practical applications, a large number of slag-free cases are simulated to obtain the working condition data, lining thickness settings, thermocouple temperatures, the highest working temperature of the cooler, and the highest working temperature of the refractory material of different numerical simulation models, and form a slag-free offline database.

[0058] Specifically, according to different working condition parameters, a large number of cases of the three-dimensional temperature field numerical simulation model of the cooler in the slag-free state are calculated, and the working condition data, lining thickness settings, thermocouple temperatures, the highest working temperature of the cooler, and the highest working temperature of the refractory material in the cases are extracted to form a slag-free offline database.

[0059] In a possible implementation manner, determining an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the slag-free offline database includes: determining the lining thickness setting and working condition parameters based on the slag-free offline database; using the lining thickness setting as the output data and the working condition parameters as the input data, and constructing an intelligent real-time calculation model for the remaining thickness of the blast furnace lining through supervised machine learning.

[0060] In practical applications, based on the thermocouple temperature and working condition data in the slag-free offline database as input parameters, and the set thickness of the furnace lining as output data, a supervised machine learning method is applied to construct an intelligent real-time calculation model for the remaining thickness of the furnace lining to complete the online application of offline data. By inputting the working condition data collected in real time, the remaining thickness of the furnace lining in the high-load area of the blast furnace is output in real time.

[0061] Step 104: Based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the working condition data, construct a slag skin state judgment model.

[0062] In a possible implementation, based on the real-time calculation model of the remaining thickness of the blast furnace lining and the working condition data, construct a slag skin state judgment model, including: determining the remaining thickness of the furnace lining at the current moment based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining; constructing a slag skin state judgment model based on the remaining thickness of the furnace lining, the working condition data, and the slag-free offline database; where the slag skin state judgment model includes a slag skin shedding judgment model, a slag skin too thin judgment model, a slag skin no abnormality judgment model, and a slag skin thickening judgment model.

[0063] In practical applications, based on the real-time calculated remaining thickness of the furnace lining and the real-time collected working condition data. Extract the real-time calculated remaining thickness H of the furnace lining from the slag-free offline database L The corresponding thermocouple temperature T R 、The maximum working temperature T of the cooler L 、The maximum working temperature T of the refractory material N . Extract the actual working temperature T of the thermocouple at this moment from the real-time collected working condition data R ’, The actual maximum working temperature T of the cooler L ’, The actual maximum working temperature T of the refractory material N ’. Extract the safe working temperature T of the cooler material according to expert experience A1 、The safe working temperature T of the refractory material A2 .

[0064] Slag skin shedding real-time identification and dynamic judgment model: When T R ’ is greater than T R or T L ’ is greater than T L or T N ’ is greater than T N , According to the temperature, it is identified that the slag skin at this position has completely fallen off, and it is judged that this position is in the state of slag skin shedding. In a specific example, as the remaining thickness of the furnace lining and the working condition data are updated, the identification method remains unchanged, but with the data update, the specific identification rules are dynamically updated.

[0065] Slag skin too thin real-time identification and dynamic judgment model: When T L ’ is less than T L and TL ’ greater than T A 、T L ’ less than T L and T N ’ greater than T N According to the temperature, it is recognized that the slag skin at this position condenses in the furnace wall, but the slag skin cannot ensure the safe operation of the cooler and refractory materials, and it is judged that this position is in a state of too thin slag skin. In a specific example, as the remaining thickness of the furnace lining and the working condition data are updated, the recognition method remains unchanged, but with the data update, the specific recognition rules are dynamically updated accordingly.

[0066] Real-time identification and dynamic judgment model for abnormal-free slag skin: T R ’ less than T R and T L ’ less than T A1 and T N ’ less than T A2 According to the temperature, it is recognized that the slag skin at this position condenses in the furnace wall, and the slag skin can ensure the safe operation of the cooler and refractory materials, and it is judged that this position is in a state of abnormal-free slag skin. In a specific example, as the remaining thickness of the furnace lining and the working condition data are updated, the recognition method remains unchanged, but with the data update, the specific recognition rules are dynamically updated accordingly.

[0067] Real-time identification and dynamic judgment model for thick slag skin: Extract the air volume data F, water temperature difference data 、the inlet water temperature T of the cooling water S . According to expert experience, for a blast furnace operating under constant blast pressure, when it is recognized that F is less than the average air volume within one month minus 500 m 3 / h, it is judged that there is a state of thick slag skin in the furnace at this time. For a blast furnace operating under constant air volume, when it is recognized that is less than 0.2 °C, at this time the slag skin is too thick and the water temperature difference hardly changes, and it is judged that this position is in a state of thick slag skin. For all types of blast furnaces, when it is recognized that TR’ is less than T within a period of time S , at this time the cooling water cannot play the role of taking away heat, and it is dynamically judged that there is a state of thick slag skin in the furnace at this time.

[0068] Step 105: Obtain the current working condition data, and determine the slag skin state based on the current working condition data, the intelligent real-time calculation model of the remaining thickness of the blast furnace lining, and the slag skin state judgment model.

[0069] In a possible implementation manner, obtaining the current working condition data and determining the slag skin state based on the current working condition data, the real-time calculation model of the remaining thickness of the blast furnace lining, and the slag skin state judgment model includes: obtaining the current working condition data, inputting the current working condition data into the intelligent real-time calculation model of the remaining thickness of the blast furnace lining to determine the current remaining thickness of the furnace lining; based on the current remaining thickness of the furnace lining and the slag skin state judgment model, determining the slag skin state.

[0070] In practical applications, the working condition data collected in real time is input into the intelligent real-time calculation model of the remaining thickness of the furnace lining and the real-time recognition model of the slag skin state, and the remaining thickness of the furnace lining and the slag skin state at different positions in the high-heat load area are obtained online. As the working condition data is continuously input, the remaining thickness of the furnace lining and the slag skin state are dynamically updated.

[0071] The embodiments of this specification provide a method and device for determining the remaining thickness of the blast furnace lining and the slag skin state. The method includes: obtaining the designed furnace type data, physical property parameters, and working condition data; determining a numerical simulation model based on the designed furnace type data and physical property parameters; determining an offline database without slag skin based on the numerical simulation model, and determining an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the offline database without slag skin and supervised machine learning; constructing a slag skin state judgment model based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the working condition data; obtaining the current working condition data, and determining the slag skin state based on the current working condition data, the intelligent real-time calculation model of the remaining thickness of the blast furnace lining, and the slag skin state judgment model. Based on the actual data of the blast furnace, integrating a variety of theoretical technologies, accurately calculating the remaining thickness of the furnace lining and scientifically evaluating the slag skin state, with a fast response speed, strong real-time performance, low cost, and strong promotion and application ability, which helps to assist on-site operators in controlling the blast furnace type, stabilizing the blast furnace condition, and reducing the ironmaking cost.

[0072] Corresponding to the above method embodiments, this specification also provides embodiments of a device for determining the slag skin state of a blast furnace. Figure 3 The structure diagram of a device for determining the slag skin state of a blast furnace provided by an embodiment of this specification is shown. As Figure 3 shown, the device includes:

[0073] A data acquisition module 301, configured to obtain the designed furnace type data, physical property parameters, and working condition data;

[0074] A numerical simulation module 302, configured to determine a numerical simulation model based on the designed furnace type data and physical property parameters;

[0075] A thickness calculation module 303, configured to determine an offline database without slag skin based on the numerical simulation model, and determine an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the offline database without slag skin;

[0076] A state judgment module 304, configured to construct a slag skin state judgment model based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the working condition data;

[0077] A state determination module 305, configured to obtain the current working condition data, and determine the slag skin state based on the current working condition data, the intelligent real-time calculation model of the remaining thickness of the blast furnace lining, and the slag skin state judgment model.

[0078] In a possible implementation, the designed furnace type data includes the blast furnace CAD structure diagram, the blast furnace cooler, the three-dimensional dimension diagram of refractories, and the distribution structure diagram;

[0079] The physical property parameters include the thermal conductivity, mass density, and specific heat capacity;

[0080] The operating condition data includes cooling data, temperature data, and air volume data.

[0081] In a possible implementation, based on the designed furnace type data and physical property parameters, a numerical simulation model is determined, including:

[0082] Based on the designed furnace type data and physical property parameters, a numerical simulation model is constructed through the three-dimensional heat transfer theory.

[0083] In a possible implementation, based on the numerical simulation model, a slag-free skin offline database is determined, including:

[0084] Based on the numerical simulation model, operating condition parameters, the set thickness of the furnace lining, thermocouple temperature, and the maximum operating temperature of the cooler are extracted and collected to construct a slag-free skin offline database.

[0085] In a possible implementation, based on the slag-free skin offline database, an intelligent real-time calculation model for the remaining thickness of the blast furnace lining is determined, including:

[0086] Based on the slag-free skin offline database, the set thickness of the furnace lining and operating condition parameters are determined;

[0087] Taking the set thickness of the furnace lining as the output data and the operating condition parameters as the input data, an intelligent real-time calculation model for the remaining thickness of the blast furnace lining is constructed through supervised machine learning.

[0088] In a possible implementation, based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the operating condition data, a slag skin state judgment model is constructed, including:

[0089] Based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, the remaining thickness of the furnace lining at the current moment is determined;

[0090] Based on the remaining thickness of the furnace lining, the operating condition data, and the slag-free skin offline database, a slag skin state judgment model is constructed; among them, the slag skin state judgment model includes a slag skin shedding judgment model, a slag skin too thin judgment model, a slag skin no abnormality judgment model, and a slag skin thick and solid judgment model.

[0091] In a possible implementation, the current operating condition data is obtained, and based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model, the slag skin state is determined, including:

[0092] Obtain the current operating condition data, and input the current operating condition data into the intelligent real-time calculation model for the remaining thickness of the blast furnace lining to determine the current remaining thickness of the lining;

[0093] Based on the remaining thickness of the current furnace lining and the slag skin state judgment model, determine the slag skin state.

[0094] The embodiments of this specification provide a method and device for determining the remaining thickness of the blast furnace lining and the slag skin state. The device includes: obtaining the designed furnace type data, physical property parameters, and operating condition data; determining a numerical simulation model based on the designed furnace type data and physical property parameters; determining an offline database without slag skin based on the numerical simulation model, and determining an intelligent real-time calculation model for the remaining thickness of the blast furnace lining based on the offline database without slag skin; constructing a slag skin state judgment model based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the operating condition data; obtaining the current operating condition data, and determining the slag skin state based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model. Based on the actual data of the blast furnace, integrating various theoretical technologies, accurately calculating the remaining thickness of the lining and scientifically evaluating the slag skin state, with fast response speed, strong real-time performance, low cost, and strong promotion and application capabilities, which helps assist on-site operators in controlling the blast furnace type and stabilizing the blast furnace condition to reduce the ironmaking cost.

[0095] The above is a schematic solution of a device for determining the slag skin state of a blast furnace in this embodiment. It should be noted that the technical solution of the device for determining the slag skin state of the blast furnace belongs to the same concept as the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state. For the details not described in the technical solution of the device for determining the slag skin state of the blast furnace, reference can be made to the description of the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0096] Figure 4 The structural block diagram of a computing device 400 provided according to an embodiment of this 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 through a bus 430, and a database 450 is used to store data.

[0097] 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 such networks include the Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), 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 wired or wireless network interface (e.g., a network interface controller (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0098] In one embodiment of the present specification, the above components of the computing device 400, as well as Figure 4 other components not shown, may also be connected to each other, for example, via a bus. It should be understood that Figure 4 the block diagram of the computing device shown is merely for illustrative purposes and is not a limitation on the scope of the present specification. Those skilled in the art may add or replace other components as needed.

[0099] The computing device 400 can 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 smartphone), a wearable computing device (e.g., a smartwatch, 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 can also be a mobile or stationary server.

[0100] Among them, the processor 420 is used to execute the following computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state are implemented. The above is a schematic solution of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state belong to the same concept. For the details not described in detail in the technical solution of the computing device, reference can be made to the description of the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0101] An embodiment of this specification also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the steps of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state are implemented.

[0102] The above is a schematic solution of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state belong to the same concept. For the details not described in detail in the technical solution of the storage medium, reference can be made to the description of the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0103] An embodiment of this specification also provides a computer program. When the computer program is executed on a computer, the computer is made to execute the steps of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0104] The above is a schematic solution of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state belong to the same concept. For the details not described in detail in the technical solution of the computer program, reference can be made to the description of the technical solution of the above method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0105] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] The computer instructions include computer program code, which may be in the form of source code, object code, 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), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0107] It should be noted that for the foregoing method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of this specification are not limited by the described action sequence, because according to the embodiments of this specification, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments of this specification.

[0108] In the above embodiments, the descriptions of the various embodiments have their own focuses. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0109] 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 the specific embodiments 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 to better explain the principles and practical applications of the embodiments of this specification, so that those skilled in the art can understand and utilize this specification well. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for determining the remaining thickness of a blast furnace lining and the state of slag skin, characterized in that: include: Obtain design furnace data, physical performance parameters and operating condition data; Determining a numerical simulation model based on the designed furnace data and physical performance parameters; Determine a slag-free offline database based on the numerical simulation model, and determine an intelligent real-time calculation model for the remaining thickness of a blast furnace lining based on the slag-free offline database and supervised machine learning; Based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating condition data, a slag skin state judgment model is constructed; Acquire current operating condition data, and determine the slag skin state based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model; Based on the designed furnace data and physical performance parameters, a numerical simulation model is determined, including: Based on the designed furnace data and physical performance parameters, a numerical simulation model is constructed by three-dimensional heat transfer theory; the numerical simulation model includes a three-dimensional physical model of a cooler in a slag-free state; Based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating condition data, a slag skin state judgment model is constructed, including: Determine the remaining thickness of the blast furnace lining based on the intelligent real-time calculation model for the remaining thickness of the blast furnace lining; Based on the remaining thickness of the furnace lining, the operating condition data and the slag skin-free offline database, a slag skin state judgment model is constructed; wherein the slag skin state judgment model includes a slag skin shedding judgment model, a slag skin too thin judgment model, a slag skin normal judgment model and a slag skin thick judgment model; Real-time calculation of the remaining thickness H of the furnace lining extracted from the slag-free offline database L The corresponding thermocouple temperature T R , Cooler maximum operating temperature T L , Maximum working temperature of refractory materials T N , extract the actual working temperature T of the thermocouple at this moment from the real-time collected working condition data R ', the actual maximum operating temperature of the cooler T L '、The actual maximum working temperature of refractory materials T N ', extract the safe working temperature T of the cooler material based on expert experience A1 , Refractory material safe working temperature T A2 ; The slag skin shedding judgment model includes: when T R 'Greater than T R or T L 'Greater than T L or T N 'Greater than T N , according to the temperature, it is identified that the slag skin at this position has completely fallen off, and it is judged that this position is in the slag skin falling state; The slag skin is too thin judgment model includes: when T L ' is less than T L And T L 'Greater than T A 、T L ' is less than T L And T N 'Greater than T N According to the temperature, the slag skin at this position is condensed in the furnace wall, but the slag skin cannot ensure that the cooler and refractory materials are in a safe working state, and it is judged that the slag skin at this position is too thin; The slag skin no abnormality judgment model includes: R ' is less than T R And T L ' is less than T A1 And T N ' is less than T A2 , according to the temperature, it is identified that the slag skin at this position is condensed in the furnace wall, and the slag skin can ensure that the cooler and refractory materials are in a safe working state, and it is judged that the slag skin at this position is in a normal state; The slag crust thickness judgment model includes: extracting air volume data F, water temperature difference data , Cooling water inlet temperature T S For a blast furnace operated at a constant wind pressure, identify the case where F is less than the average wind volume in one month minus 500 m 3 / h, it is judged that the slag crust is thick in the furnace at this time, and the blast furnace is operated with constant air volume to identify Less than 0.2℃, at this time the slag skin is too thick, the water temperature difference is almost unchanged, it is judged that this position is in the state of thick slag skin, for all types of blast furnaces, it is identified that TR' is less than T within a period of time S At this time, the cooling water cannot take away the heat, and it is dynamically judged that the slag skin is thick in the furnace.

2. The method according to claim 1, characterized in that The designed furnace type data includes a blast furnace CAD structure diagram, a blast furnace cooler, a 3D dimension diagram of refractory materials and a distribution structure diagram; The physical performance parameters include thermal conductivity, mass density and specific heat capacity; The operating condition data includes cooling data, temperature data and air volume data.

3. The method according to claim 1, characterized in that Determining a slag-free offline database based on the numerical simulation model includes: Based on the numerical simulation model, the operating parameters, furnace lining setting thickness, thermocouple temperature and maximum operating temperature of the cooler are extracted and collected to construct a slag-free offline database.

4. The method according to claim 1, characterized in that: The intelligent real-time calculation model for determining the remaining thickness of the blast furnace lining based on the slag-free offline database includes: Determine the furnace lining setting thickness and operating parameters based on the slag-free offline database; The furnace lining setting thickness is used as output data, and the operating condition parameters are used as input data, and an intelligent real-time calculation model for the remaining thickness of the blast furnace lining is constructed through supervised machine learning.

5. The method according to claim 1, characterized in that Acquiring current operating condition data, and determining the slag skin state based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining, and the slag skin state judgment model, including: Acquire current operating condition data, and input the current operating condition data into the intelligent real-time calculation model for the remaining thickness of the blast furnace lining to determine the current remaining thickness of the blast furnace lining; The slag skin state is determined based on the current furnace lining remaining thickness and the slag skin state judgment model.

6. A device for determining the state of slag skin of a blast furnace, used to implement the steps of the method for determining the remaining thickness of the blast furnace lining and the state of slag skin of a blast furnace as claimed in any one of claims 1 to 5, characterized in that: include: A data acquisition module is configured to acquire design furnace data, physical performance parameters and operating condition data; A numerical simulation module is configured to determine a numerical simulation model based on the designed furnace data and physical performance parameters; A thickness calculation module is configured to determine a slag-free offline database based on the numerical simulation model, and determine an intelligent real-time calculation model for the remaining thickness of a blast furnace lining based on the slag-free offline database; A state judgment module is configured to construct a slag skin state judgment model based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating condition data; The state determination module is configured to obtain current operating condition data and determine the slag skin state based on the current operating condition data, the intelligent real-time calculation model for the remaining thickness of the blast furnace lining and the slag skin state judgment model.

7. A computing device, 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 remaining thickness of the blast furnace lining and the slag skin state as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for determining the remaining thickness of a blast furnace lining and the slag skin state as described in any one of claims 1 to 5.

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