Dynamic regulation and control method for blast furnace operation

Abstract

The invention relates to a blast furnace operation dynamic regulation and control method, and belongs to the technical field of blast furnace smelting methods. According to the technical scheme, the method comprises the steps that an ore granularity index and a coke granularity index are defined, dynamic correlation between the granularity indexes and cold air flow is monitored in real time, and a regulation and control strategy is triggered in combination with a preset early warning value; and when the index exceeds the limit, the opening degree of a throttle valve, the number of material distribution turns and the cold air flow are dynamically adjusted, and the raw material supply end is synchronously linked to optimize the screening process. The method has the beneficial effects that the purpose of precise regulation and control is achieved, the material suspension risk is remarkably reduced, the coal gas utilization rate is synchronously increased, and smooth furnace conditions and optimization of the blast furnace smelting cost are achieved.

Description

Technical Field

[0001] The invention relates to a blast furnace operation dynamic control method, belonging to the technical field of blast furnace smelting methods. Background Art

[0002] In blast furnace smelting, charge particle size (especially the fines content of ore and coke) directly affects the permeability of the charge column and gas flow distribution. Traditional methods rely on manual sampling to detect particle size (for example, patent publication CN114814154B analyzes coke degradation by sampling inside the blast furnace). However, this method is time-consuming and cannot provide real-time guidance for optimizing blast furnace operations.

[0003] Existing particle size evaluation is mostly based on laboratory static testing (such as patent announcement No. CN113640173B simulating blast furnace dynamic reactions to evaluate coke quality), which is difficult to directly correlate with real-time operating parameters (such as γ angle and air volume).

[0004] Currently, blast furnace operators rely on experience to respond to changes in particle size and lack quantitative indicators. Dynamic changes in particle size can easily lead to fluctuations in furnace conditions (such as hanging materials and excessive edge airflow).

[0005] Patent publication number CN119120811A proposes a method for regulating the transition period of full coke smelting, but does not involve refined control of dynamic particle size monitoring and operational linkage. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for dynamic control of blast furnace operation, which combines the γ angle with the batch weight, and indirectly reflects the particle size fluctuations fed back by the change in the specific gravity of the raw fuel pile through the throttle valve opening, thereby avoiding the lag of the particle size fluctuations fed back by traditional sampling; multi-parameter coordinated control, linking the cold air flow, distribution angle and raw material management, to achieve a "monitoring-adjustment-feedback" closed loop; early warning dynamic calibration, combining historical data with AI algorithm to optimize the threshold, and adapt to different furnace capacities and raw material structures; to achieve the purpose of precise control, significantly reduce the risk of suspended materials, and simultaneously improve the gas utilization rate, achieve the optimization of furnace conditions and blast furnace smelting costs, and effectively solve the above-mentioned problems existing in the background technology.

[0007] The technical solution of the present invention is: a method for dynamically controlling blast furnace operation, comprising the following steps:

[0008] (1) Define the particle size index and early warning mechanism. The particle size index includes the ore particle size index and the coke particle size index. An increase in the index indicates that the particle size is getting finer or the powder is increasing, which requires triggering operational adjustments;

[0009] (2) Real-time monitoring of the particle size index and the cold air flow data, displaying the particle size index trend chart on the operation interface, superimposing the warning line and the cold air flow curve, when the ore particle size index or coke particle size index exceeds the limit, the system prompts and associates the historical data;

[0010] (3) Triggering control strategies in combination with preset warning values;

[0011] (4) Synchronize and optimize the screening process at the raw material supply end.

[0012] In the step (1), the ore particle size index: Iore = Wore / γ, unit kg / °, where Wore is the ore batch weight, γ is the throttle valve opening, and an early warning value is set; the coke particle size index: Icoke = Wcoke / γ, unit kg / °, where Wcoke is the marginal coke batch weight, and an early warning value is set.

[0013] In the step (2), the horizontal axis of the particle size index trend graph is time.

[0014] In the step (3), when the ore particle size index exceeds the limit, the γ angle is reduced to reduce the feeding speed, the number of feeding circles is extended to 8 to 16 circles, the powder segregation is reduced, and the cold air flow rate is simultaneously reduced to match the air permeability of the material column;

[0015] When the coke particle size index exceeds the limit, adjust the α angle to increase the edge coke ratio and compensate for the coke skeleton effect; combine the coke optical structure detection data to optimize the coal blending plan.

[0016] The step In (4), the abnormal data of particle size index are pushed to the supply side, requiring the improvement of raw material screening process; based on the machine learning model, the warning threshold is dynamically calibrated to adapt to different blast furnace operating conditions.

[0017] The beneficial effects of the present invention are: by combining the γ angle with the batch weight, the particle size fluctuations fed back by the change in the specific gravity of the raw fuel pile are indirectly reflected through the throttle valve opening, thereby avoiding the lag of the particle size fluctuations fed back by traditional sampling; multi-parameter coordinated control, linking the cold air flow, distribution angle and raw material management, to achieve a "monitoring-adjustment-feedback" closed loop; early warning dynamic calibration, combining historical data with AI algorithm to optimize the threshold, adapt to different furnace capacities and raw material structures; achieve the purpose of precise control, significantly reduce the risk of suspended materials, and simultaneously improve the gas utilization rate, to achieve the optimization of furnace conditions and blast furnace smelting costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the method of the present invention;

[0019] Figure 2 This is a correlation diagram between the particle size index and the cold air flow rate trend of the present invention;

[0020] Figure 3 It is a schematic diagram of the interface of the particle size index early warning system of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the invention implementation cases clearer, the technical solutions in the invention implementation cases will be clearly and completely described below in conjunction with the drawings in the implementation cases. Obviously, the implementation cases described are only a small part of the implementation cases of the present invention, rather than all the implementation cases. Based on the implementation cases in the present invention, all other implementation cases obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] A method for dynamically controlling blast furnace operation comprises the following steps:

[0023] (1) Define the particle size index and early warning mechanism. The particle size index includes the ore particle size index and the coke particle size index. An increase in the index indicates that the particle size is getting finer or the powder is increasing, which requires triggering operational adjustments;

[0024] (2) Real-time monitoring of the particle size index and the cold air flow data, displaying the particle size index trend chart on the operation interface, superimposing the warning line and the cold air flow curve, when the ore particle size index or coke particle size index exceeds the limit, the system prompts and associates the historical data;

[0025] (3) Triggering control strategies in combination with preset warning values;

[0026] (4) Synchronize and optimize the screening process at the raw material supply end.

[0027] In the step (1), the ore particle size index: Iore = Wore / γ, unit kg / °, where Wore is the ore batch weight, γ is the throttle valve opening, and an early warning value is set; the coke particle size index: Icoke = Wcoke / γ, unit kg / °, where Wcoke is the marginal coke batch weight, and an early warning value is set.

[0028] In the step (2), the horizontal axis of the particle size index trend graph is time.

[0029] In the step (3), when the ore particle size index exceeds the limit, the γ angle is reduced to reduce the feeding speed, the number of feeding circles is extended to 8 to 16 circles, the powder segregation is reduced, and the cold air flow rate is simultaneously reduced to match the air permeability of the material column;

[0030] When the coke particle size index exceeds the limit, adjust the α angle to increase the edge coke ratio and compensate for the coke skeleton effect; combine the coke optical structure detection data to optimize the coal blending plan.

[0031] The step In (4), the abnormal data of particle size index are pushed to the supply side, requiring the improvement of raw material screening process; based on the machine learning model, the warning threshold is dynamically calibrated to adapt to different blast furnace operating conditions.

[0032] In practical application, the specific implementation steps of the present invention are as follows:

[0033] Step 1: Define granularity index and early warning mechanism

[0034] Ore particle size index: (Unit: kg / °), where Wore is the ore batch weight, γ is the throttle valve opening (e.g. 0-75°), for example, the warning value is set to 2055 kg / °;

[0035] Coke particle size index: (Unit: kg / °), for example, the warning value is set to 435kg / °;

[0036] An increase in the index indicates that the particle size is getting finer or the powder is increasing, which requires triggering operational adjustments.

[0037] Step 2: Real-time monitoring and data correlation

[0038] The particle size index trend graph is displayed on the operation interface (the horizontal axis is time), and the warning line and the cold air flow curve are superimposed (for example, the cold air flow ≥ 5000m 3 / min, the correlation was significant);

[0039] When Iore or Icoke exceeds the limit, the system automatically prompts and associates historical data (such as patent publication number CN109918702A optimizes ingredients and operations through neural network modeling).

[0040] Step 3: Dynamically control the strategy

[0041] Ore index exceeds limit:

[0042] Reduce the γ angle (reduce the feeding speed), extend the number of feeding circles to 8 to 16 circles, and reduce powder segregation;

[0043] Simultaneously reduce the cold air flow (e.g. reduce 100-500m 3 / min), matching the permeability of the material column (e.g., patent publication No. CN118792066A verifies the coal blending effect through temperature detection);

[0044] Coke index exceeds the limit:

[0045] Increase the edge coke ratio (adjust the α angle) to compensate for the coke skeleton effect;

[0046] The coal blending plan is optimized by combining the coke optical structure detection data (refer to patent announcement number CN113834810B for automated detection of coke quality).

[0047] Step 4: Feedback and Optimization

[0048] Push abnormal particle size index data to the supply side, requiring improvements to the raw material screening process (e.g., evaluating sintered ore particle size by porosity in patent publication number CN113159562B);

[0049] Dynamically calibrate the warning threshold based on machine learning models (such as NSGA-Ⅱ algorithm) to adapt to different blast furnace operating conditions.

[0050] Example

[0051] 2500m 3 Take the blast furnace as an example:

[0052] 1. When Iore rises to 2200kg / ° (exceeding the warning value of 2055kg / °), the system prompts "ore powder increases";

[0053] 2. Automatically adjust the γ angle from 37.2° to 36.2° and increase the number of fabric turns from 12 to 13;

[0054] 3. Cold air flow from 5350m 3 / min down to 5200m 3 / min, the pressure difference is stable at 180kPa;

[0055] 4. Simultaneously push data to suppliers, requiring the sinter ore screening efficiency to be increased to above 95%.

[0056] Technical effects of the present invention:

[0057] 1. The response time to abnormal particle size is shortened by more than 60%, and the incidence of suspended particles is reduced by 30%;

[0058] 2. The cold air flow control accuracy is improved, and the gas utilization rate is increased by 1.5% to 2.0%;

[0059] 3. Raw material quality data is traceable, driving process improvements on the supply side (screening efficiency increased by 10% to 15%).

Claims

1. A method for dynamic control of blast furnace operation, characterized in that The following steps are involved: (1) Define the particle size index and early warning mechanism. The particle size index includes the ore particle size index and the coke particle size index. An increase in the index indicates that the particle size is getting finer or the powder is increasing, which requires triggering operational adjustments; (2) Real-time monitoring of the particle size index and the cold air flow data are associated, and the particle size index trend chart is displayed on the operation interface, with the warning line and the cold air flow curve superimposed. When the ore particle size index or the coke particle size index exceeds the limit, the system prompts and associates the historical data; (3) Triggering control strategies based on preset warning values; (4) Synchronize and link the raw material supply side to optimize the screening process.

2. A blast furnace operation dynamic control method according to claim 1, characterized in that: In the step (1), the ore particle size index is: Iore = Wore / γ, in kg / °, where Wore is the ore batch weight, γ is the throttle valve opening, and an early warning value is set; the coke particle size index is: Icoke = Wcoke / γ, in kg / °, where Wcoke is the marginal coke batch weight, and an early warning value is set.

3. A method for dynamic control of blast furnace operation according to claim 1, characterized in that: In the step (2), the horizontal axis of the particle size index trend graph is time.

4. A method for dynamic control of blast furnace operation according to claim 1, characterized in that: In step (3), when the ore particle size index exceeds the limit, the γ angle is reduced to reduce the feeding speed, the number of feeding circles is extended to 8 to 16 circles, the powder segregation is reduced, and the cold air flow rate is simultaneously reduced to match the permeability of the material column; When the coke particle size index exceeds the limit, adjust the α angle to increase the edge coke ratio and compensate for the coke skeleton effect; combine the coke optical structure detection data to optimize the coal blending plan.

5. The method for dynamic control of blast furnace operation according to claim 1, characterized in that: In the step (4), the abnormal data of the particle size index is pushed to the supply side, requiring improvement of the raw material screening process; based on the machine learning model, the warning threshold is dynamically calibrated to adapt to different blast furnace operating conditions.

Images