Method and device for determining residual thickness of blast furnace lining and slag crust state

Abstract

The embodiment of the invention provides a blast furnace lining residual thickness and slag crust state determination method and device, and the method comprises the steps that a numerical simulation model is determined based on design furnace profile data and physical performance parameters; determining a slag-skin-free off-line database based on the numerical simulation model, and determining a blast furnace lining residual thickness intelligent real-time calculation model based on the slag-skin-free off-line database; based on the intelligent real-time calculation model of the residual thickness of the blast furnace lining and the working condition data, constructing a slag crust state judgment model; and acquiring current working condition data, and determining the slag crust state based on the current working condition data, the intelligent real-time calculation model of the residual thickness of the blast furnace lining and the slag crust state judgment model. On the basis of actual data of the blast furnace, multiple theoretical technologies are fused, the residual thickness of the furnace lining is accurately calculated, the slag crust state is scientifically evaluated, the response speed is high, the real-time performance is high, the cost is low, the high popularization and application capacity is achieved, and field operators can be helped to control the blast furnace type, stabilize the blast furnace condition and reduce the ironmaking cost.

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 the remaining thickness of a blast furnace lining and the state of a slag crust. Background Art

[0002] The high heat load area is a restrictive link that affects the life of the blast furnace. The high heat load area of ​​the blast furnace mainly relies on lining protection, cooler cooling protection and furnace wall condensation slag skin protection, which helps prevent the high-temperature edge gas in the furnace from eroding the furnace body. This is a conventional means to extend the life of the blast furnace. In the actual production process, the remaining thickness of the blast furnace lining cannot be directly monitored, and the slag skin cannot directly determine whether there is an abnormality in the state. 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. It seriously affects the stable production of blast furnaces by on-site personnel and makes it difficult to control the blast furnace conditions in real time.

[0003] 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 the remaining thickness of a blast furnace lining and the state of a slag crust. One or more embodiments of this specification also relate to a device for determining the remaining thickness of a blast furnace lining and the state of a slag crust, 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 a blast furnace lining remaining thickness and a slag skin state is provided, comprising: Obtain design furnace data, physical performance parameters and operating condition data; Determine the numerical simulation model based on the designed furnace data and physical performance parameters; Determine the slag-free offline database based on the numerical simulation model, and determine the intelligent real-time calculation model of the remaining thickness of the blast furnace lining based on the slag-free offline database; Based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating data, a slag skin state judgment model is constructed; The current operating condition data is obtained, and the slag skin state is determined based on the current operating condition data, the intelligent real-time calculation model of the remaining thickness of the blast furnace lining, and the slag skin state judgment model.

[0006] In a possible implementation, the design 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; 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.

[0007] In a possible implementation, a numerical simulation model is determined based on the design furnace data and physical performance parameters, including: Based on the designed furnace data and physical performance parameters, a numerical simulation model is constructed using three-dimensional heat transfer theory.

[0008] In a possible implementation, determining a slag-free offline database based on a 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 build a slag-free offline database.

[0009] In a possible implementation, an intelligent real-time calculation model for determining the remaining thickness of a blast furnace lining based on a slag-free offline database includes: Determine the lining thickness and operating parameters based on the slag-free offline database; The set thickness of the lining is used as the output data, and the operating parameters are used 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.

[0010] In a possible implementation, a slag skin state judgment model is constructed based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating data, including: Determine the remaining thickness of the blast furnace lining at the current moment based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining; Based on the remaining thickness of the furnace lining, operating condition data and the offline database without slag skin, a slag skin status judgment model is constructed; among them, the slag skin status judgment model includes a slag skin falling judgment model, a slag skin too thin judgment model, a slag skin normal judgment model and a slag skin thick judgment model.

[0011] In a possible implementation, current operating condition data is obtained, and the slag skin state is determined based on the current operating condition data, an intelligent real-time calculation model for the remaining thickness of a blast furnace lining, and a slag skin state judgment model, including: Obtain current operating condition data, and input the current operating 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 lining; The slag skin state is determined based on the current lining remaining thickness and slag skin state judgment model.

[0012] According to a second aspect of an embodiment of this specification, a device for determining a blast furnace slag skin state is provided, comprising: 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 a numerical simulation model, and to 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 an intelligent real-time calculation model of the remaining thickness of a blast furnace lining and 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, a real-time calculation model for blast furnace slag skin thickness and a slag skin state judgment model.

[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 method for determining the remaining thickness of the blast furnace lining and the slag skin state 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, which, when executed by a processor, implement the steps of the above-mentioned method for determining the remaining thickness of a blast furnace lining and the slag skin state.

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

[0016] The present specification provides a method and device for determining the remaining thickness and slag skin state of a blast furnace lining, wherein the method includes: obtaining design furnace type data, physical performance parameters and operating condition data; determining a numerical simulation model based on the design furnace type data and physical performance parameters; determining a slag skin-free offline database 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 slag skin-free offline database; 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 operating condition data; obtaining 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, a variety of theoretical technologies are integrated to accurately calculate the remaining thickness of the lining and scientifically evaluate 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 blast furnace types, stabilizing blast furnace conditions and reducing ironmaking costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a method for determining the remaining thickness of a blast furnace lining and the slag skin state provided by an embodiment of this specification; Figure 2 It is a schematic diagram of a method for determining the remaining thickness of a blast furnace lining and the state of a slag skin provided in one embodiment of this specification; Figure 3 It is a structural schematic diagram of a device for determining the remaining thickness of a blast furnace lining and the slag skin state 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 the remaining thickness of a blast furnace lining and the state of a slag crust is provided. This specification also relates to a device for determining the state of a blast furnace slag crust, 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 the remaining thickness of a blast furnace lining and the state of a slag crust provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0023] Step 101: Obtain design furnace data, physical performance parameters and operating condition data.

[0024] In one possible implementation, the design furnace data includes a blast furnace CAD structure diagram, a blast furnace cooler, a refractory material three-dimensional dimension diagram, and a distribution structure diagram; the physical performance parameters include thermal conductivity, mass density, and specific heat capacity; and the operating condition data includes cooling data, temperature data, and air volume data.

[0025] In actual applications, the design data of the high heat load area of ​​the blast furnace includes the blast furnace CAD structure diagram, blast furnace cooler, refractory material three-dimensional size diagram and distribution structure diagram. Blast furnace materials include cooler materials, refractory materials, furnace shell materials and filling materials, and the physical performance parameters include thermal conductivity, mass density and specific heat capacity. Operating condition data cooling data, temperature data and air volume data, etc. Collect the design data of the blast furnace high heat load area and the physical performance parameters of the blast furnace materials, collect the blast furnace operating data in real time, and unify and integrate the time series frequency of the blast furnace operating data. Among them, in order to solve the data problems such as the inconsistent frequency of the operating condition data and the identification of outliers, the operating condition data is cleaned and integrated through oversampling, resampling, isolated forest recognition and other methods.

[0026] Step 102: Determine a numerical simulation model based on the designed furnace data and physical performance parameters.

[0027] In a possible implementation, a numerical simulation model is determined based on the design furnace data and physical performance parameters, including: constructing a numerical simulation model through three-dimensional heat transfer theory based on the design furnace data and physical performance parameters.

[0028] In practical applications, see Figure 2 Based on the design data of the furnace type and the physical parameters of the materials in the high heat load zone of the blast furnace, a three-dimensional temperature field numerical simulation model of the cooler with no slag, different lining setting thickness and operating parameters is constructed.

[0029] Specifically, a three-dimensional physical model of the cooler in the high heat load zone in the slag-free state is designed based on the design furnace data and material physical parameters, and then the three-dimensional heat transfer mathematical model and three-dimensional grid model of the cooler are constructed, and boundary conditions are applied. Finally, the offline operating parameters are input and the numerical simulation technology is used to calculate the three-dimensional temperature field of the cooler in the slag-free state.

[0030] 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 a blast furnace lining based on the slag-free offline database.

[0031] In a possible implementation, a slag-free offline database is determined based on a numerical simulation model, including: based on the numerical simulation model, extracting and collecting operating parameters, furnace lining setting thickness, thermocouple temperature and cooler maximum operating temperature to construct a slag-free offline database.

[0032] In practical applications, a large number of slag-free cases are simulated to obtain the operating data of different numerical simulation models, furnace lining setting thickness, thermocouple temperature, maximum operating temperature of the cooler and maximum operating temperature of the refractory material to form a slag-free offline database.

[0033] Specifically, a large number of numerical simulation model cases of the three-dimensional temperature field of the cooler in the slag-free state are calculated according to different operating parameters, and the operating data, lining setting thickness, thermocouple temperature, maximum operating temperature of the cooler and maximum operating temperature of the refractory material in the cases are extracted to form a slag-free offline database.

[0034] In one possible implementation, an intelligent real-time calculation model for the remaining thickness of a blast furnace lining is determined based on a slag-free offline database, including: determining the lining setting thickness and operating parameters based on the slag-free offline database; taking the lining setting thickness as output data and the operating parameters as input data, and constructing an intelligent real-time calculation model for the remaining thickness of a blast furnace lining through supervised machine learning.

[0035] In actual applications, based on the thermocouple temperature and operating data in the slag-free offline database as input parameters and the lining setting thickness as output data, supervised machine learning is used to build an intelligent real-time calculation model for the remaining thickness of the lining to complete the online application of offline data. By inputting the operating data collected in real time, the remaining thickness of the lining in the high-load area of ​​the blast furnace is output in real time.

[0036] Step 104: construct a slag skin state judgment model based on the intelligent real-time calculation model of the blast furnace lining remaining thickness and the operating condition data.

[0037] In a possible implementation, a slag skin status judgment model is constructed based on a real-time calculation model of the remaining thickness of the blast furnace lining and operating data, including: determining the remaining thickness of the lining at the current moment based on an intelligent real-time calculation model of the remaining thickness of the blast furnace lining; constructing a slag skin status judgment model based on the remaining thickness of the lining, operating data and a slag skin-free offline database; wherein the slag skin status judgment model includes a slag skin falling off judgment model, a slag skin too thin judgment model, a slag skin normal judgment model and a slag skin thick judgment model.

[0038] In practical applications, the real-time calculation of the remaining thickness of the furnace lining and the real-time collected working condition data are used to extract the real-time calculation of the remaining thickness of the furnace lining H 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 operating temperature T of the cooler material based on expert experience A1 , Refractory material safe working temperature T A2 .

[0039] Real-time identification and dynamic judgment model of slag peeling: 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, the slag skin at this position has completely fallen off, and it is judged that this position is in the state of slag skin falling off. In the specific example, as the remaining thickness of the furnace lining and the working condition data are updated, the identification method remains unchanged, but the data is updated, and the specific identification rules are dynamically updated accordingly.

[0040] Real-time identification and dynamic judgment model of thin slag skin: 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. In the specific example, as the remaining thickness of the furnace lining and the operating condition data are updated, the identification method remains unchanged, but the data is updated, and the specific identification rules are dynamically updated.

[0041] Real-time recognition and dynamic judgment model of no abnormality in slag skin: T 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, 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. In the specific example, as the remaining thickness of the furnace lining and the working condition data are updated, the identification method remains unchanged, but the data is updated, and the specific identification rules are dynamically updated.

[0042] Real-time identification and dynamic judgment model of slag crust thickness: extract air volume data F, water temperature difference data , Cooling water inlet temperature T S According to expert experience, for a blast furnace operating at a constant wind pressure, the identification 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. For the blast furnace operated with constant air volume, identify Less than 0.2℃, the slag skin is too thick, and the water temperature difference is almost unchanged, so 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 for 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.

[0043] Step 105: obtaining 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.

[0044] In one possible implementation, current operating condition data is obtained, and the slag skin state is determined based on the current operating condition data, a real-time calculation model for the remaining lining thickness of a blast furnace, and a slag skin state judgment model, including: obtaining current operating condition data, inputting the current operating condition data into an intelligent real-time calculation model for the remaining thickness of a blast furnace lining to determine the current remaining thickness of the lining; and determining the slag skin state based on the current remaining thickness of the lining and the slag skin state judgment model.

[0045] In practical applications, the real-time collected working condition data is input into the intelligent real-time calculation model of the remaining thickness of the furnace lining and the real-time identification 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. With the continuous input of working condition data, the remaining thickness of the furnace lining and the slag skin state are dynamically updated.

[0046] The present specification embodiment provides a method and device for determining the remaining thickness and slag skin state of a blast furnace lining, wherein the method includes: obtaining design furnace type data, physical performance parameters and operating condition data; determining a numerical simulation model based on the design furnace type data and physical performance parameters; determining a slag skin-free offline database 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 slag skin-free offline database and supervised machine learning; 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 operating condition data; obtaining 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, a variety of theoretical technologies are integrated to accurately calculate the remaining thickness of the lining and scientifically evaluate 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 blast furnace types, stabilizing blast furnace conditions and reducing ironmaking costs.

[0047] Corresponding to the above method embodiment, this specification also provides a blast furnace slag skin state determination device embodiment, Figure 3 FIG. 2 shows a schematic diagram of a blast furnace slag skin state determination device provided by an embodiment of the present specification. Figure 3 As shown, the device comprises: The data acquisition module 301 is configured to acquire the designed furnace data, physical performance parameters and operating condition data; The numerical simulation module 302 is configured to determine a numerical simulation model based on the designed furnace data and physical performance parameters; The thickness calculation module 303 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 the blast furnace lining based on the slag-free offline database; The state judgment module 304 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 305 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 of the remaining thickness of the blast furnace lining, and the slag skin state judgment model.

[0048] In a possible implementation, the design 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; 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.

[0049] In a possible implementation, a numerical simulation model is determined based on the design furnace data and physical performance parameters, including: Based on the designed furnace data and physical performance parameters, a numerical simulation model is constructed using three-dimensional heat transfer theory.

[0050] In a possible implementation, determining a slag-free offline database based on a 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 build a slag-free offline database.

[0051] In a possible implementation, an intelligent real-time calculation model for determining the remaining thickness of a blast furnace lining based on a slag-free offline database includes: Determine the lining thickness and operating parameters based on the slag-free offline database; The set thickness of the lining is used as the output data, and the operating parameters are used 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.

[0052] In a possible implementation, a slag skin state judgment model is constructed based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining and the operating data, including: Determine the remaining thickness of the blast furnace lining at the current moment based on the intelligent real-time calculation model of the remaining thickness of the blast furnace lining; Based on the remaining thickness of the furnace lining, operating condition data and the offline database without slag skin, a slag skin status judgment model is constructed; among them, the slag skin status judgment model includes a slag skin falling judgment model, a slag skin too thin judgment model, a slag skin normal judgment model and a slag skin thick judgment model.

[0053] In a possible implementation, current operating condition data is obtained, and the slag skin state is determined based on the current operating condition data, an intelligent real-time calculation model for the remaining thickness of a blast furnace lining, and a slag skin state judgment model, including: Obtain current operating condition data, and input the current operating 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 lining; The slag skin state is determined based on the current furnace remaining lining thickness and slag skin state judgment model.

[0054] The embodiment of this specification provides a method and device for determining the remaining thickness and slag skin state of a blast furnace lining, wherein the device includes: obtaining design furnace type data, physical performance parameters and operating condition data; determining a numerical simulation model based on the design furnace type data and physical performance parameters; determining a slag skin-free offline database 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 slag skin-free offline database; 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 operating condition data; obtaining 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, a variety of theoretical technologies are integrated to accurately calculate the remaining thickness of the lining and scientifically evaluate 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 blast furnace types, stabilizing blast furnace conditions and reducing ironmaking costs.

[0055] The above is a schematic scheme of a blast furnace slag skin state determination device of this embodiment. It should be noted that the technical scheme of the blast furnace slag skin state determination device and the technical scheme of the above-mentioned blast furnace lining remaining thickness and slag skin state determination method belong to the same concept, and the details not described in detail in the technical scheme of the blast furnace slag skin state determination device can all be referred to the description of the technical scheme of the above-mentioned blast furnace lining remaining thickness and slag skin state determination method.

[0056] Figure 4 The block diagram of a computing device 400 according to an 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.

[0057] 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).

[0058] 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.

[0059] 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.

[0060] The processor 420 is used to execute the following computer executable instructions, which, when executed by the processor, implement the steps of the above-mentioned method for determining the remaining thickness of the blast furnace lining and the slag skin state. 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state belong to the same concept. For details not described in detail in the technical scheme of the computing device, please refer to the description of the technical scheme of the above-mentioned method for determining the remaining thickness of the blast furnace lining and the slag skin state.

[0061] An embodiment of the present specification also 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 the remaining thickness of a blast furnace lining and the slag skin state.

[0062] 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state described above 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state described above.

[0063] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to execute the steps of the above-mentioned method for determining the remaining thickness of a blast furnace lining and the slag skin state.

[0064] 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state described above belong to 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 method for determining the remaining thickness of the blast furnace lining and the slag skin state described above.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] 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.

[0069] 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 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; The current operating condition data is obtained, and the slag skin state is determined 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.

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 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 using three-dimensional heat transfer theory.

4. 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.

5. 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.

6. The method according to claim 1, characterized in that 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 status judgment model is constructed; wherein the slag skin status 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.

7. 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.

8. A device for determining the state of blast furnace slag skin, 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.

9. 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 7 are implemented.

10. 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 7.

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