Dynamic pouring control method for hot-metal bottle

Abstract

The invention discloses a dynamic pouring control method for a hot-metal bottle, which belongs to the technical field of metallurgical industry automation control, and comprises the following steps: carrying out high-precision dynamic weighing and vibration compensation on the hot-metal bottle; performing multi-source sensing and safety monitoring on the hot-metal bottle; self-adaptive dumping speed control is realized based on the flow speed of molten iron in the molten iron tank; parameter optimization is carried out, and optimal control parameters are output; and setting a security protection strategy. The problems that an existing molten iron tank is insufficient in control metering precision, extensive in control mode and weak in safety protection can be solved, and blast furnace molten iron can be transferred and poured through the molten iron tank more efficiently, intelligently and safely.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic control in metallurgical industry, and particularly relates to a molten iron ladle dynamic pouring control method. BACKGROUND

[0002] In a modern steel production process, the accurate transfer of molten iron from a blast furnace to a converter through a molten iron ladle is a core technical link for realizing the advanced process of "one ladle to the end". The process requires that the molten iron is not replaced in the whole process from tapping in the blast furnace to smelting in the converter, and puts forward unprecedented strict requirements for the control accuracy and safety guarantee of the transfer process. However, the current commonly used transfer technology system has systematic defects, which has become a key bottleneck restricting the intelligent upgrading of steel production.

[0003] The traditional metering method relies on a static rail scale device, and it is difficult to overcome the interference of mechanical vibration and ladle shaking during the molten iron pouring process, resulting in that the dynamic weighing error is maintained at a high level for a long time. Such metering deviation not only causes the calculation error of the converter burdening, affects the stability of the final molten steel composition control, but also makes it difficult to realize the accurate evaluation of the single-ladle molten iron transfer efficiency. The control strategy of the tilting mechanism is particularly extensive, and the fixed angular velocity operation mode completely ignores the physical characteristics that the molten iron flow rate dynamically decays with the liquid level drop, and also fails to consider the significant influence of the molten iron temperature change on the fluidity. Such rigid control mode directly leads to two vicious working conditions: the molten iron is splashed due to the too fast flow rate at the initial pouring stage, which not only causes the molten iron loss but also threatens the operation safety; the residual molten iron forms an overload impact on the ladle at the end of the pouring stage, which greatly shortens the service life of the equipment. At the same time, the transfer operation time is irregularly fluctuated, which seriously affects the stability of the production rhythm.

[0004] There is a serious original defect that the safety monitoring link relies on manual experience. The single-band infrared detection device has weak anti-interference ability in the harsh working conditions of high temperature and high dust, and the false report rate is high. More seriously, the existing system lacks the monitoring ability of the real-time posture of the ladle, and cannot give early warning when the inclination angle deviation accumulates to the dangerous threshold, which has a major hidden danger of overturning. The problem of slow response of the emergency braking mechanism has not been solved for a long time, and the action delay is far beyond the basic requirements of the modern metallurgical safety specification. The subsystems are in isolated operation state, the data acquisition period of the weighing, temperature monitoring and posture detection units is seriously out of step, and the fault disposal completely relies on manual identification and intervention, and the response time cannot match the millisecond-level cooperation standard required by the "one ladle to the end" process.

[0005] The prior art technical improvement scheme of the industry is mainly focused on local optimization. Some weighing devices attempt to introduce static filtering algorithm but fail to touch the core of dynamic compensation; some speed control devices use conventional PID regulation but have not established a closed-loop control model of flow rate-inclination; the upgrade of safety system is limited to the increase of single-point sensors and ignores multi-source information fusion. These improvements have not systematically solved the fundamental contradictions of insufficient dynamic weighing precision, lack of self-adaptation in pouring process, weak panoramic safety protection and low system coordination efficiency, and there is still a significant gap from the high-precision measurement, zero spatter operation, full-automatic operation and intrinsic safety targets pursued by modern steel production. SUMMARY

[0006] The technical problem to be solved by the present application is to provide a molten iron tank dynamic pouring control method. The problems of insufficient control measurement precision, extensive control mode and weak safety protection of the existing molten iron tank control are solved, and the high-efficiency intelligent safety is realized to realize the transfer and pouring of molten iron from the blast furnace through the molten iron tank.

[0007] To solve the above technical problems, the technical scheme adopted by the present application is as follows:

[0008] Step 1: high-precision dynamic weighing and vibration compensation of the molten iron tank;

[0009] Step 2: multi-source sensing and safety monitoring of the molten iron tank;

[0010] Step 3: adaptive pouring speed control based on the flow rate of molten iron in the molten iron tank;

[0011] Step 4: parameter optimization and output of optimal control parameters;

[0012] Step 5: setting safety protection strategy.

[0013] The further improvement of the technical scheme of the present application is that the specific steps of step 1 are as follows:

[0014] Step 1.1: installing a high-precision dynamic track scale under the molten iron transportation track, the range is 200-400 tons, and the sampling frequency is greater than or equal to 10 Hz;

[0015] Step 1.2: real-time acquisition of the weight signal W_m(t) of the molten iron tank, and calculation of the compensated weight through a dynamic compensation model:

[0016] W_c(t)=W_m(t)+k·d 2 W / dt 2

[0017] Wherein, W_c is the compensated weight, W_m is the measured weight, and k is the dynamic compensation coefficient;

[0018] Step 1.3: Send the compensated weight data to the edge computing node for real-time calibration.

[0019] Further improvement of the technical scheme of the present application is that step 2 has the following specific steps:

[0020] Step 2.1: Install double-waveband infrared thermal imagers on both sides of the turnover mechanism: the middle wave channel (3-5 μm) detects the molten iron liquid level height h(t) in real time; the long wave channel (8-12 μm) monitors the surface temperature distribution of the tank body;

[0021] Step 2.2: Install a multi-axis inertial measurement unit at the molten iron tank lug, with an accuracy of ±0.1°, to monitor the tank body inclination angle θ and vibration acceleration in real time;

[0022] Step 2.3: Fuse the weighing data, liquid level height and tank body attitude data to construct a three-dimensional model of the molten iron state.

[0023] Further improvement of the technical scheme of the present application is that step 3 has the following specific steps:

[0024] Step 3.1: Calculate the real-time molten iron flow rate according to steps 1 and 2:

[0025] Step 3.2: Dynamically adjust the turnover plate angular velocity through the servo hydraulic turnover plate mechanism according to the real-time flow rate:

[0026] ω(t) = ω_0 + α·(v_d-v(t))

[0027] Where: ω_0 is the reference speed (2-3° / s), α is the adjustment coefficient (0.5-1.2), v_d is the target flow rate (3-5 kg / s), and v(t) is the real-time flow rate.

[0028] Further improvement of the technical scheme of the present application is that step 4 has the following specific steps:

[0029] Step 4.1: Deploy an LSTM neural network model on the edge computing node, inputting the molten iron tank parameters;

[0030] Step 4.2: The neural network outputs the optimized control parameters: initial turnover plate speed ω_0 and expected transfer time T_p;

[0031] Step 4.3: Inject the optimized control parameters into the servo hydraulic turnover plate mechanism speed control loop of step 3.

[0032] Further improvement of the technical scheme of the present application is that step 5 has the following specific steps:

[0033] 5.1: Double stop judging mechanism: when the following conditions are met simultaneously:

[0034] W_c(t) ≤ 5% W_max and h(t) ≤ h_min

[0035] Time triggered multi-stage hydraulic locking device (braking time ≤ 50 ms);

[0036] 5.2: Set real-time running fault self-diagnosis program: when the sensor data deviates from the normal value range, automatically switch to the backup detection channel; when the thermal imager temperature abnormal gradient is detected, start the tank cooling emergency protocol;

[0037] 5.3: In the double-side tank dumping system, based on Kalman filtering algorithm, the double-track scale data are fused, and when the master-slave system deviation exceeds 0.5%, the redundancy switching of ≤1s is performed.

[0038] By adopting the above technical scheme, the technical progress achieved by the application is: by deploying high-precision dynamic track scales and vibration compensation algorithms, the molten iron weighing accuracy is fundamentally improved, and the measurement deviation caused by vibration interference is completely overcome; by establishing a flow rate-inclination angle closed-loop control model and configuring a servo hydraulic actuator, adaptive optimization of the dumping speed is realized, effectively eliminating the molten iron splashing and tank impact problems; by integrating double-waveband infrared monitoring, multi-axis attitude sensing and double-judgment shutdown mechanism, a panoramic safety protection system is constructed, significantly reducing the risk of manual intervention. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction will be given below to the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings;

[0040] Figure 1 is a flowchart of the present application; DETAILED DESCRIPTION

[0041] The present application will be further described in detail below in combination with embodiments:

[0042] As shown in the flowchart of the dynamic dumping control method of the molten iron tank, the specific steps are as follows: Figure 1

[0043] Step 1: High-precision dynamic weighing and vibration compensation of the molten iron tank;

[0044] Step 1.1: Install high-precision dynamic track scales under the molten iron transportation track, with a range of 200-400 tons and a sampling frequency of ≥10Hz;

[0045] Step 1.2: Real-time acquisition of the molten iron tank weight signal W_m(t), and calculation of the compensated weight through the dynamic compensation model:

[0046] ​W_c(t) = W_m(t) + k · d 2 W / dt 2

[0047] Wherein, W_c is the compensated weight, W_m is the measured weight, k is the dynamic compensation coefficient;

[0048] Step 1.3: Send the compensated weight data to the edge computing node for real-time calibration.

[0049] Step 2: Multi-source sensing and safety monitoring of the molten iron tank;

[0050] Step 2.1: Install dual-band infrared thermal imager on both sides of the turnover mechanism: the middle wave channel (3-5 μm) detects the molten iron liquid level height h(t) in real time; the long wave channel (8-12 μm) monitors the surface temperature distribution of the tank body;

[0051] Step 2.2: Install multi-axis inertial measurement unit at the molten iron tank lug, with accuracy ±0.1°, to monitor the tank body inclination angle θ and vibration acceleration in real time;

[0052] Step 2.3: Fuse weighing data, liquid level height and tank body attitude data to build a three-dimensional model of the molten iron state.

[0053] Step 3: Realize adaptive pouring speed control based on the flow rate of molten iron in the molten iron tank;

[0054] Step 3.1: Calculate the real-time molten iron flow rate according to steps 1 and 2:

[0055] Step 3.2: Dynamically adjust the turnover plate angular velocity according to the real-time flow rate through the servo hydraulic turnover plate mechanism:

[0056] ω(t) = ω_0 + α · (v_d - v(t))

[0057] Where: ω_0 is the reference speed (2-3° / s), α is the adjustment coefficient (0.5-1.2), v_d is the target flow rate (3-5 kg / s), and v(t) is the real-time flow rate.

[0058] Step 4: Perform parameter optimization and output optimal control parameters;

[0059] Step 4.1: Deploy LSTM neural network model on edge computing node, input molten iron tank parameters; input parameters include: molten iron temperature (1350-1500℃) composition (C, Si, Mn content) environmental temperature (-20-50℃).

[0060] Step 4.2: Neural network outputs optimal control parameters: initial turnover plate speed ω_0 and expected transfer time T_p;

[0061] Step 4.3: Inject the optimized control parameters into the servo hydraulic flipper mechanism speed control loop of step 3.

[0062] Step 5: Set up safety protection strategy.

[0063] 5.1: Double judgment stop mechanism: when the following conditions are met simultaneously:

[0064] W_c(t)≤5%W_max and h(t)≤h_min

[0065] trigger the multi-stage hydraulic locking device (braking time ≤50ms);

[0066] 5.2: Set up real-time operation fault self-diagnosis program: when the sensor data deviates from the normal value range, automatically switch to the backup detection channel; when the thermal imager temperature abnormal gradient is detected, start the tank cooling emergency protocol;

[0067] 5.3: In the double-sided tank dumping system, based on the Kalman filter algorithm, fuse the double-track scale data, when the master-slave system deviation exceeds 0.5%, execute ≤1s redundant switching.

[0068] The above-described embodiments are merely descriptions of the preferred embodiments of the present application and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those of ordinary skill in the art shall fall within the protection scope determined by the claims of the present application.

Claims

1. A method for controlling the dynamic tilting of molten iron ladles, characterized in that: The steps include the following: Step 1: Perform high-precision dynamic weighing and vibration compensation on the molten iron ladle; Step 2: Conduct multi-source sensing and safety monitoring of the molten iron ladle; Step 3: Implement adaptive pouring speed control based on the molten iron flow rate in the ladle; Step 4: Optimize parameters and output optimal control parameters; Step 5: Set up security protection policies.

2. The method for controlling the dynamic tilting of a molten iron ladle according to claim 1, characterized in that: Step 1: The specific steps are as follows: Step 1.1: Install a high-precision dynamic rail scale under the molten iron transport rail, with a measuring range of 200-400 tons and a sampling frequency of ≥10Hz; Step 1.2: Real-time acquisition of the molten iron ladle weight signal W_m(t), and calculation of the compensated weight using a dynamic compensation model: W_c(t)=W_m(t)+k·d 2 W / dt 2 Where W_c is the compensated weight, W_m is the measured weight, and k is the dynamic compensation coefficient; Step 1.3: Send the compensated weight data to the edge computing node for real-time calibration.

3. The method for controlling the dynamic tilting of a molten iron ladle according to claim 1, characterized in that: Step 2 is detailed below: Step 2.1: Install dual-band infrared thermal imagers on both sides of the flip-plate mechanism: the medium-wave channel (3-5μm) is used to detect the molten iron level height h(t) in real time; the long-wave channel (8-12μm) is used to monitor the temperature distribution on the surface of the tank. Step 2.2: Install a multi-axis inertial measurement unit at the lifting lug of the molten iron ladle, with an accuracy of ±0.1°, to monitor the ladle's tilt angle θ and vibration acceleration in real time; Step 2.3: Integrate weighing data, liquid level height and tank posture data to construct a three-dimensional model of the molten iron state.

4. The method for controlling the dynamic tilting of a molten iron ladle according to claim 1, characterized in that: Step 3 is detailed below: Step 3.1: Calculate the real-time molten iron flow rate based on Step 1 and Step 2: Step 3.2: The angular velocity of the tilting plate is dynamically adjusted according to the real-time flow rate via the servo hydraulic tilting mechanism. ω(t)=ω_0+α·(v_d-v(t)) Where: ω_0 is the reference velocity (2-3° / s), α is the adjustment coefficient (0.5-1.2), v_d is the target flow velocity (3-5 kg / s), and v(t) is the real-time flow velocity.

5. The method for controlling the dynamic tilting of a molten iron ladle according to claim 1, characterized in that: Step 4 is detailed below: Step 4.1: Deploy the LSTM neural network model on the edge computing node and input the parameters of the molten iron ladle; Step 4.2: The neural network outputs optimized control parameters: initial flipping speed ω_0 and expected transfer time T_p; Step 4.3: Inject the optimized control parameters into the speed control loop of the servo hydraulic tilting mechanism in Step 3.

6. The method for controlling the dynamic tilting of a molten iron ladle according to claim 1, characterized in that: Step 5 is detailed below: 5.1: Dual Stop Mechanism: When the following conditions are met simultaneously: W_c(t)≤5%W_max and h(t)≤h_min The multi-stage hydraulic locking device is triggered at any time (braking time ≤ 50ms); 5.2: Set up a real-time fault self-diagnosis program: When sensor data deviates from the normal range, automatically switch to the backup detection channel; when an abnormal temperature gradient is detected by the thermal imager, activate the tank cooling emergency protocol. 5.3: In the double-sided tank transfer system, the dual-track balance data are fused based on the Kalman filter algorithm, and a redundancy switch of ≤1s is performed when the master-slave system deviation exceeds 0.5%.

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