Blast furnace pulverized coal combustion rate detection and prediction method based on extreme temperature rise state

Abstract

The invention discloses a blast furnace pulverized coal combustion rate detection and prediction method based on an extreme temperature rise state, and the method comprises the following steps: S1, carrying out grinding, screening and particle size determination on raw materials to obtain a first coal sample; s2, drying the first coal sample to obtain a second coal sample, weighing the second coal sample with a set weight, and placing the second coal sample in a crucible; s3, carrying out an extreme temperature rise pulverized coal combustion experiment, and collecting data of the pulverized coal combustion rate to form a pulverized coal combustion rate data set; s4, integrating the pulverized coal combustion rate data set at 1200 DEG C and the pulverized coal industry composition data set to construct a comprehensive database; s5, constructing a combustion rate prediction model of the pulverized coal at 1200 DEG C; s6, fitting a relational expression between the pulverized coal combustion rate at 1200 DEG C and the pulverized coal combustion rate at 2000 DEG C; and obtaining pulverized coal combustion rate data under the condition of 2000 DEG C through a fitted relational expression. According to the method for detecting and predicting the pulverized coal combustion rate of the blast furnace, the authenticity and reliability of pulverized coal combustion simulation are greatly improved, the complex combustion behavior of the pulverized coal in the blast furnace can be deeply understood, and the prediction accuracy of the pulverized coal combustion efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of blast furnace ironmaking technology. Specifically, this invention relates to a method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions. Background Technology

[0002] In steel production, coke is an important reducing agent and fuel in the blast furnace. However, the coking process is energy-intensive, polluting, and its price fluctuates greatly. Therefore, reducing the coke ratio has become an important way for steel companies to reduce production costs and improve market competitiveness. Blast furnace pulverized coal injection technology is one of the effective means to achieve the goal of reducing coke. Blast furnace pulverized coal injection technology replaces part of the coke by injecting finely ground coal powder at the blast furnace tuyere, achieving multiple benefits such as reducing coke, reducing energy consumption, reducing environmental pollution, and improving production efficiency. However, the in-depth application and optimization of this technology faces a series of technical challenges. First, the combustion process of pulverized coal in the blast furnace is a complex thermochemical process. In actual production, the pulverized coal tuyere combustion rate is affected by a variety of factors, such as the particle size of the pulverized coal, the design of the tuyere, and the injection parameters. The difference in the combustion rate of different pulverized coal tuyeres has a significant impact on the heat distribution, reducing atmosphere, and gas utilization rate in the blast furnace. Second, while achieving a reduced coke ratio can significantly reduce production costs, it also brings about more precise control requirements for blast furnace operating parameters. The combustion characteristics of pulverized coal differ from those of coke, resulting in a more complex dynamic impact on the atmosphere and temperature field within the blast furnace. This necessitates precise adjustments to blast furnace operation. Furthermore, real-time monitoring and accurate control of the pulverized coal tuyere combustion rate are crucial for optimizing blast furnace pulverized coal injection technology. Currently, methods for detecting the pulverized coal tuyere combustion rate are complex and require costly equipment. Therefore, real-time monitoring and control of the pulverized coal tuyere combustion rate remains a challenge in actual production.

[0003] Chinese Patent Application No. 200720190577.9 discloses a blast furnace pulverized coal injection simulation experimental device. This device simulates the air supply system of a blast furnace hot blast stove, enabling pulverized coal to undergo combustion at 1500℃. The device measures the content of CO, CO2, O2, and H2 in the flue gas, combined with parameters such as the pressure in the high-pressure and low-pressure sections during the experiment, and the elemental content of C, H, and O in the pulverized coal, to obtain the combustion rate of pulverized coal under different oxygen-to-carbon ratios. However, the morphological changes and temperature distribution of pulverized coal during combustion are complex and dynamic. Current equipment often requires auxiliary equipment such as high-speed cameras to roughly record the state and temperature changes of the pulverized coal during the reaction process, which is lacking in accuracy and real-time performance.

[0004] Chinese patent application number 202311420638.6 discloses a method for simulating and testing the pulverized coal combustion rate at the tuyeres of a hydrogen-rich blast furnace. This method, by comprehensively considering the process parameters of the hydrogen-rich blast furnace, accurately determines the amount of hydrogen-rich gas, pulverized coal, oxygen enrichment, and carrier gas injected at a single tuyer. By calculating the molar amount of carbon atoms, the molar amount of oxygen atoms, the oxygen-to-carbon ratio, and the volume ratio of oxygen to hydrogen-rich gas, the amount of pulverized coal injected, the amount of hydrogen-rich gas, and the volume fraction of oxygen and nitrogen in the carrier gas under experimental conditions can be deduced. This method, combined with the pipeline design of a novel blast furnace composite injection simulation experiment, achieves accurate measurement of the pulverized coal combustion rate. Although numerical simulation methods play an important role in the study of blast furnace pulverized coal injection technology, this method also has certain drawbacks. The numerical simulation process is lengthy, has extremely high parameter requirements, a long construction cycle, and its accuracy depends on the precision of the model and the accuracy of the parameters. In practical applications, due to the complexity and variability of the pulverized coal combustion process, the results of numerical simulations often deviate from actual operations, and their accuracy needs to be further improved.

[0005] Thermogravimetric analysis (TGA) is an important experimental method widely used in the study of pulverized coal combustion characteristics. However, existing TGA methods have some limitations, which restrict their practical application in the study of pulverized coal combustion characteristics in blast furnaces. TGA typically employs a constant-rate heating method, where pulverized coal samples are heated to the target combustion temperature within the furnace at a constant heating rate (5-20℃ / min). In this mode, most thermal analyzers can only reach a maximum temperature of 1200℃, while the actual temperature inside a blast furnace is often much higher. Furthermore, the constant-rate heating rate is relatively slow and cannot simulate the rapid combustion of pulverized coal during actual blast furnace pulverized coal injection. In actual blast furnace pulverized coal injection operations, the injection rate can reach 10ms, an extremely high speed that ordinary thermal analyzers cannot achieve. Although drip furnaces and novel injection simulation devices can achieve rapid heating in a short time, thus more closely resembling the actual pulverized coal injection process, these devices still have shortcomings in characterizing the pulverized coal combustion process. The morphological changes and temperature distribution of pulverized coal during combustion are complex and dynamic. Current equipment often requires auxiliary devices such as high-speed cameras to roughly record the state and temperature changes of pulverized coal during the reaction process, which is lacking in accuracy and real-time performance. Furthermore, numerical simulation methods play an important role in the study of blast furnace pulverized coal injection technology, but this method also has certain drawbacks. Numerical simulation processes are lengthy, have extremely high parameter requirements, and long construction cycles; their accuracy depends on the precision of the model and the accuracy of the parameters. In practical applications, due to the complexity and variability of the pulverized coal combustion process, the results of numerical simulations often deviate from actual operations, and their accuracy needs further improvement.

[0006] Therefore, existing thermogravimetric analysis, drip furnace and injection simulation test devices, and numerical simulation methods all have certain limitations in studying blast furnace pulverized coal injection technology. These techniques are unable to comprehensively and accurately simulate and characterize the pulverized coal combustion characteristics during the blast furnace pulverized coal injection process. If accurate data can be obtained through laboratory experiments, and numerical simulation predictions can be performed based on this data, the prediction accuracy of the model will be greatly improved, and the model construction cycle will be effectively shortened.

[0007] The aim is to provide a method for detecting and predicting the combustion rate of pulverized coal in blast furnaces under extreme heating conditions, particularly regarding how to improve the accuracy of the prediction. Summary of the Invention

[0008] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention provides a method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions, with the aim of improving prediction accuracy.

[0009] To achieve the above objectives, the technical solution adopted by this invention is as follows: a method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions, comprising the following steps:

[0010] S1. After grinding, screening and particle size determination of the raw materials, the first coal sample is obtained;

[0011] S2. After drying the first coal sample, a second coal sample is obtained. Then, a predetermined weight of the second coal sample is weighed and placed in a crucible.

[0012] S3. The second coal sample was heated using an extreme temperature synchronous thermal analyzer to conduct an extreme temperature coal powder combustion experiment, and data on coal powder combustion rate under different temperature conditions were collected to form a coal powder combustion rate dataset.

[0013] S4. Integrate the coal powder combustion rate dataset at 1200℃ and the coal powder industrial composition dataset into a comprehensive database;

[0014] S5. Construct a prediction model for the combustion rate of pulverized coal at 1200℃;

[0015] S6. Based on the data of pulverized coal combustion rate under different temperature conditions, fit the relationship between the pulverized coal combustion rate at 1200℃ and the pulverized coal combustion rate at 2000℃; finally, the pulverized coal combustion rate data under 2000℃ can be obtained through the fitted relationship.

[0016] The extreme heating synchronous thermal analyzer includes a heating furnace and a lifting device for controlling the heating furnace to rise and fall. A sample center heating zone for accommodating the second sample is set at the center of the heating furnace.

[0017] Step S3 includes:

[0018] S301. Control the heating furnace to rise to the first set height;

[0019] S302. Control the heating furnace to uniformly heat up from the initial temperature to the preset target temperature at a set heating rate;

[0020] S303. When the heating furnace reaches the preset target temperature, the heating furnace is controlled to descend to the second preset height, and the heating furnace heats the second sample located in the central heating zone of the sample.

[0021] The set heating rate is 20℃ / min.

[0022] In step S303, the second sample enters the central heating zone of the sample and begins to synchronously record TG and DSC curves to monitor the thermal decomposition and combustion process of pulverized coal in real time.

[0023] The steps S301 to S303 are executed multiple times, with different preset target temperatures each time, in order to collect data on the pulverized coal combustion rate under different temperature conditions.

[0024] The lifting device includes a drive motor and a power transmission mechanism connected to the drive motor, and the power transmission mechanism is connected to the heating furnace.

[0025] In step S2, the drying time for the first coal sample is 11 to 13 hours, and the drying temperature is 95 to 115°C.

[0026] Step S1 includes:

[0027] S101. Grind the bituminous coal;

[0028] S102. Use 115-mesh and 200-mesh standard sieves to screen coal powder on a standard vibrating screen.

[0029] S103. Continue to feed coal powder larger than 125μm into the crusher for grinding;

[0030] S104. Use 115-mesh and 200-mesh standard sieves to screen the coal powder again on a standard vibrating screen.

[0031] S105. The experimental coal sample obtained after sieving is subjected to particle size analysis in a laser particle size analyzer to confirm that the sieved particle size is consistent with the particle size tested by the instrument.

[0032] The method for detecting and predicting the combustion rate of pulverized coal in blast furnaces under extreme heating conditions, as proposed in this invention, not only greatly improves the realism and reliability of pulverized coal combustion simulation, but also helps to understand the complex combustion behavior of pulverized coal in blast furnaces more deeply. Through mathematical modeling of the combustion rate, it is possible not only to predict the combustion efficiency of pulverized coal under specific temperature conditions, but also to assess the influence of different pulverized coal characteristics on the combustion process, thereby improving the accuracy of pulverized coal combustion efficiency prediction. Attached Figure Description

[0033] This manual includes the following figures, which illustrate the following:

[0034] Figure 1 This is a flowchart of the method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions, as described in this invention.

[0035] Figure 2 This is a schematic diagram of the structure of the extreme temperature rise synchronous thermal analyzer;

[0036] Figure 3 This is a schematic diagram of the process for constructing a pulverized coal combustion rate prediction model;

[0037] The diagram is marked as follows:

[0038] 1. Heating furnace; 2. Motor drive control; 3. External furnace temperature signal; 4. Computer; 5. Gas flow control; 6. Flow meter; 7. Gas flow unit; 8. Internal furnace temperature signal; 9. Mass signal; 10. Furnace body descends to the sample center heating zone; 11. Furnace body rises. Detailed Implementation

[0039] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, in order to help those skilled in the art to have a more complete, accurate and in-depth understanding of the concept and technical solutions of the present invention, and to facilitate its implementation.

[0040] like Figure 1 As shown, a method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions includes the following steps:

[0041] S1. After grinding, screening and particle size determination of the raw materials, the first coal sample is obtained;

[0042] S2. After drying the first coal sample, a second coal sample is obtained. Then, a predetermined weight of the second coal sample is weighed and placed in a crucible.

[0043] S3. The second coal sample was heated using an extreme temperature synchronous thermal analyzer to conduct an extreme temperature coal powder combustion experiment, and data on coal powder combustion rate under different temperature conditions were collected to form a coal powder combustion rate dataset, which includes a coal powder combustion rate dataset at 1200℃.

[0044] S4. Integrate the coal powder combustion rate dataset at 1200℃ and the coal powder industrial composition dataset into a comprehensive database;

[0045] S5. Based on the coal powder industrial composition dataset and the coal powder combustion rate dataset at 1200℃, a coal powder combustion rate prediction model at 1200℃ is constructed using machine learning and a linear regression algorithm.

[0046] S6. Based on the data of pulverized coal combustion rate under different temperature conditions, fit the relationship between the pulverized coal combustion rate at 1200℃ and the pulverized coal combustion rate at 2000℃; finally, the pulverized coal combustion rate data under 2000℃ can be obtained through the fitted relationship.

[0047] Specifically, the objective of this invention is to first predict the coal powder combustion rate data at 1200℃, and then, based on the relationship between the combustion rates at 1200℃ and 2000℃, predict the coal powder combustion rate under the actual theoretical combustion temperature (2000℃) of the blast furnace.

[0048] This invention addresses the shortcomings of conventional thermogravimetric analysis (TGA) with its constant-rate heating test conditions and the inability of some experimental devices to detect the coal powder reaction process in real time. It proposes an innovative coal powder combustion method—the extreme-heating coal powder combustion method—and employs an extreme-heating synchronous thermal analyzer for conducting extreme-heating coal powder combustion experiments.

[0049] This invention aims to simulate the actual combustion process of pulverized coal in front of the tuyeres of a blast furnace by precisely controlling experimental conditions. The invention establishes an extreme heating condition where the furnace body is first heated to a preset target temperature and held stable. The furnace body is then moved to the central heating zone of the pulverized coal sample. In this zone, the pulverized coal sample rapidly absorbs heat, rapidly heating from room temperature to the target temperature, thus completing the combustion reaction. This process simulates the dynamic scenario where pulverized coal in a blast furnace encounters high temperatures and burns rapidly after being quickly injected into the tuyeres. This experimental method allows for a more accurate capture and description of the combustion characteristics of pulverized coal within the blast furnace, thereby revealing its thermal behavior and reaction mechanisms under extreme conditions.

[0050] Meanwhile, this invention addresses the lack of experimental data for current mathematical models. Based on coal pulverized coal combustion rate data obtained from experiments at different temperatures, a mathematical model is constructed to predict the coal pulverized coal combustion rate at actual theoretical temperatures, thus providing a powerful quantitative tool for a deeper understanding and precise control of the combustion process.

[0051] The application of a novel method for extreme-temperature pulverized coal combustion not only significantly improves the realism and reliability of pulverized coal combustion simulation but also contributes to a deeper understanding of the complex combustion behavior of pulverized coal in blast furnaces. Through mathematical modeling of the combustion rate, it is possible not only to predict the combustion efficiency of pulverized coal under specific temperature conditions but also to assess the impact of different pulverized coal characteristics on the combustion process. More importantly, this research provides a solid theoretical basis and crucial technical support for optimizing blast furnace pulverized coal injection processes, and has significant practical implications for promoting energy conservation, emission reduction, and process upgrading in the steel industry.

[0052] Step S1 above includes:

[0053] S101. Grind the bituminous coal;

[0054] S102. Coal powder was screened on a standard vibrating screen using standard sieves of 115 mesh (125μm) and 200 mesh (75μm) respectively.

[0055] S103. Continue to feed coal powder larger than 125μm into the crusher for grinding;

[0056] S104. Use 115-mesh and 200-mesh standard sieves to screen the coal powder again on a standard vibrating screen.

[0057] S105. The experimental coal sample obtained after sieving is subjected to particle size analysis in a laser particle size analyzer to confirm that the sieved particle size is consistent with the particle size tested by the instrument.

[0058] In step S102 above, raw material preparation is carried out. The raw material is dried bituminous coal, anthracite, or mixed coal (mixed coal refers to a coal product made by mixing two or more different types of coal in a certain proportion), and the grinding time is 15-20 seconds.

[0059] In step S2 above, the first coal sample is dried for 11–13 hours at a temperature of 95–115°C. After drying, the second coal sample is weighed and its weight is set to 10 ± 0.2 mg.

[0060] like Figure 2 As shown, the extreme temperature simultaneous thermal analyzer includes a balance, a heating furnace, and a lifting device for controlling the raising and lowering of the heating furnace. The heating furnace is a tubular heating furnace, with a central heating zone at the center to accommodate a second sample. A sample stage is mounted on the balance, and a crucible is placed on the stage. The weighed second sample is spread evenly in the crucible, and the balance is used for weighing.

[0061] In this invention, the lifting device mainly includes a drive motor and a power transmission mechanism connected to the drive motor. The power transmission mechanism is connected to the heating furnace and is used to convert the rotational force generated by the drive motor into linear motion that moves the heating furnace vertically. The power transmission mechanism can be a lead screw and nut mechanism. The drive motor is electrically connected to the control system, which includes a computer and a data acquisition system. The data acquisition system includes a temperature sensor and a flow meter, etc. The temperature sensor is used to collect the temperature of the heating furnace, and the flow meter is used to collect the flow rate of air and protective gas supplied to the balance. The data acquisition system transmits the collected data to the computer.

[0062] Step S3 above includes:

[0063] S301, Control the heating furnace to rise to the first set height;

[0064] S302. Control the heating furnace to uniformly heat up from the initial temperature to the preset target temperature at a set heating rate;

[0065] S303. When the heating furnace reaches the preset target temperature, control the heating furnace to descend to the second set height, and the heating furnace heats the second sample located in the sample center heating zone.

[0066] Before the experiment, the instruments need to be preheated. The flow meter, the extreme-temperature simultaneous thermal analyzer, and the computer should be turned on and preheated for 30 minutes. Then, during the instrument calibration phase, the extreme-temperature thermal analyzer undergoes mass calibration and temperature calibration. Next, coal samples are prepared by spreading the second sample in a crucible and placing it on the balance sample stage. Then, the gas supply is opened, and protective gas and air are supplied to the balance. The protective gas is nitrogen, the air inlet flow rate is 100 mL / min, and the protective gas inlet flow rate is 30 mL / min.

[0067] In step S301 above, the drive motor operates, causing the heating furnace to rise to a first set height, the heating furnace is away from the balance, and the balance is located below the heating furnace.

[0068] In step S302 above, the heating rate is set to 20℃ / min. By setting the heating program, the furnace is heated at a rate of 20℃ / min from an initial temperature of 30℃ to a preset target temperature at a uniform rate, and the temperature is kept stable.

[0069] In step S303 above, after the heating furnace reaches the preset target temperature, the drive motor starts running, controlling the heating furnace to rapidly descend to a second set height, which is less than the first set height. The second sample enters the sample center heating zone of the heating furnace. In this zone, the second sample can rapidly absorb the heat from the heating furnace, and the second sample rapidly heats up from room temperature to the target temperature, thereby completing the combustion reaction. At this time, the TG curve (i.e., thermogravimetric curve) and DSC curve (i.e., differential scanning calorimetry curve) are simultaneously recorded to monitor the thermal decomposition and combustion process of the pulverized coal in real time.

[0070] In step S3 above, steps S301 to S303 are executed multiple times, with a different preset target temperature each time steps S301 to S303 are executed. This allows for the collection of coal pulverized coal combustion rate data under different temperature conditions, forming a coal pulverized coal combustion rate dataset. In one execution of steps S301 to S303, the preset target temperature is 1200℃.

[0071] In step S3 above, the coal pulverized coal combustion rate dataset at 1200℃ refers to the coal pulverized coal combustion rate data under the preset target temperature of 1200℃.

[0072] In step S3 above, the extreme heating coal combustion experiment method was adopted, which caused the coal powder to experience a rapid temperature rise in the central heating zone, simulating the dynamic environment of actual pulverized coal injection in a blast furnace.

[0073] In step S4 above, by conducting in-depth analysis of the industrial composition of different pulverized coal samples, pulverized coal industrial composition data is obtained, forming a pulverized coal industrial composition dataset; the pulverized coal industrial composition includes volatile matter (V... ad ) and fixed carbon (FC) ad Key indicators such as ) were selected. Finally, the coal pulverized coal combustion rate dataset and the coal pulverized coal industrial composition dataset were integrated to construct a comprehensive database.

[0074] In step S5 above, data processing is performed first. Python software and its data processing libraries NumPy and Pandas are used to preprocess the data in the comprehensive database. This includes data processing of data such as coal pulverization rate for different industrial analyses, outlier detection, removal of invalid data, and ensuring data quality.

[0075] In step S6 above, a linear regression algorithm is used to construct a 1200℃ pulverized coal combustion rate prediction model. The prediction model is trained based on the existing database. Based on pulverized coal combustion rate data at different temperatures, the relationship between pulverized coal combustion rates at 1200℃ and 2000℃ is fitted using least squares regression analysis. When using a new type of pulverized coal, the combustion rate at 1200℃ can be obtained using the prediction model, and the combustion rate data at 2000℃ can be obtained by fitting the relationship.

[0076] By analyzing the prediction results, the pulverized coal combustion process can be optimized to improve combustion efficiency. This method not only improves the accuracy of predictions but also provides strong data support for optimizing the pulverized coal combustion process.

[0077] Example 1

[0078] In this embodiment, the raw material was bituminous coal A. Extreme temperature-increasing pulverized coal combustion tests were conducted at 1200℃, 1100℃, 1000℃, 900℃, 800℃, 700℃, and 600℃. Table 1 shows that the combustion rates of bituminous coal A at extreme temperature-increasing temperatures were 57.07% at 1200℃, 51.16% at 1100℃, 47.32% at 1000℃, 41.89% at 900℃, 35.894% at 800℃, 26.08% at 700℃, and 20.75% at 600℃.

[0079] Table 1 Database of Pulverized Coal Combustion under Different Temperatures and Extreme Temperature Increase of Bituminous Coal A

[0080]

[0081] Based on the linear regression equation, y = 53.138ln(x) - 320.07, and the goodness of fit R of this equation... 2 =0.9937. The combustion rate of bituminous coal A at 2000℃ with extreme heating is 83.83%.

[0082] Example 2

[0083] In this embodiment, anthracite B was used as the raw material. Extreme heating combustion tests were conducted on the pulverized coal at 1200℃, 1100℃, 1000℃, 900℃, 800℃, 700℃, and 600℃. Table 2 shows that the combustion rates of anthracite B at extreme heating were 43.98% at 1200℃, 37.67% at 1100℃, 33.23% at 1000℃, 29.96% at 900℃, 24.03% at 800℃, 17.73% at 700℃, and 10.09% at 600℃.

[0084] Table 2 Database of Anthracite B Pulverized Coal Combustion under Different Temperatures

[0085]

[0086] Based on the linear regression equation, the predicted value is y = 46.96ln(x) - 290.13, and the goodness of fit R of this equation is... 2 =0.995. The combustion rate of anthracite B at 2000℃ with extreme heating is 66.81%.

[0087] Example 3

[0088] In this embodiment, the raw material was mixed coal C, and extreme temperature rise pulverized coal combustion tests were conducted at 1200℃, 1100℃, 1000℃, 900℃, 800℃, 700℃, and 600℃. Table 3 shows that the combustion rates of mixed coal C under extreme temperature rise were 49.57% at 1200℃, 43.28% at 1100℃, 36.12% at 1000℃, 32.76% at 900℃, 26.48% at 800℃, 19.19% at 700℃, and 12.68% at 600℃.

[0089] Table 3 Database of Pulverized Coal Combustion at Different Temperatures and Extreme Temperature Rise of Blended Coal (C)

[0090]

[0091] Based on the linear regression equation, y = 52.182ln(x) - 322.18, and the goodness of fit R of this equation... 2 =0.991. The combustion rate of anthracite B at 2000℃ with extreme heating is 74.45%.

[0092] Example 4

[0093] In this embodiment, the raw material is pulverized coal D, and the industrial analysis of pulverized coal D is A. ad V ad FC ad The rates were 10.11%, 14.33%, and 75.56%, respectively. Based on the prediction model, the combustion rate at 1200℃ was predicted to be 45.39%. According to the relationship between the pulverized coal combustion rate at 1200℃ and 2000℃, y = 1.6742x - 9.0159, the combustion rate of pulverized coal D at the extreme temperature of 2000℃ was calculated to be 66.98% ± 3%.

[0094] Pulverized coal combustion rate data

[0095]

[0096] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution; or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions, characterized in that, Including the following steps: S1. After grinding, screening and particle size determination of the raw materials, the first coal sample is obtained; S2. After drying the first coal sample, a second coal sample is obtained. Then, a predetermined weight of the second coal sample is weighed and placed in a crucible. S3. The second coal sample was heated using an extreme temperature synchronous thermal analyzer to conduct an extreme temperature coal powder combustion experiment, and data on coal powder combustion rate under different temperature conditions were collected to form a coal powder combustion rate dataset. S4. Integrate the coal powder combustion rate dataset at 1200℃ and the coal powder industrial composition dataset into a comprehensive database; S5. Construct a prediction model for the combustion rate of pulverized coal at 1200℃; S6. Based on the data of pulverized coal combustion rate under different temperature conditions, fit the relationship between the pulverized coal combustion rate at 1200℃ and the pulverized coal combustion rate at 2000℃; finally, the pulverized coal combustion rate data under 2000℃ can be obtained through the fitted relationship.

2. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions as described in claim 1, characterized in that, The extreme heating synchronous thermal analyzer includes a heating furnace and a lifting device for controlling the heating furnace to rise and fall. A sample center heating zone for accommodating the second sample is set at the center of the heating furnace.

3. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to claim 2, characterized in that, Step S3 includes: S301. Control the heating furnace to rise to the first set height; S302. Control the heating furnace to uniformly heat up from the initial temperature to the preset target temperature at a set heating rate; S303. When the heating furnace reaches the preset target temperature, the heating furnace is controlled to descend to the second preset height, and the heating furnace heats the second sample located in the central heating zone of the sample.

4. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to claim 3, characterized in that, The set heating rate is 20℃ / min.

5. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to claim 3, characterized in that, In step S303, the second sample enters the central heating zone of the sample and begins to synchronously record TG and DSC curves to monitor the thermal decomposition and combustion process of pulverized coal in real time.

6. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to any one of claims 3 to 5, characterized in that, The steps S301 to S303 are executed multiple times, with different preset target temperatures each time, in order to collect data on the pulverized coal combustion rate under different temperature conditions.

7. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to any one of claims 2 to 6, characterized in that, The lifting device includes a drive motor and a power transmission mechanism connected to the drive motor, and the power transmission mechanism is connected to the heating furnace.

8. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to any one of claims 1 to 7, characterized in that, In step S2, the drying time for the first coal sample is 11 to 13 hours, and the drying temperature is 95 to 115°C.

9. The method for detecting and predicting the combustion rate of pulverized coal in a blast furnace under extreme heating conditions according to any one of claims 1 to 7, characterized in that, Step S1 includes: S101. Grind the bituminous coal; S102. Use 115-mesh and 200-mesh standard sieves to screen coal powder on a standard vibrating screen. S103. Continue to feed coal powder larger than 125μm into the crusher for grinding; S104. Use 115-mesh and 200-mesh standard sieves to screen the coal powder again on a standard vibrating screen. S105. The experimental coal sample obtained after sieving is subjected to particle size analysis in a laser particle size analyzer to confirm that the sieved particle size is consistent with the particle size tested by the instrument.

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