Intelligent self-adaptive converter smelting fire point area temperature monitoring system and method

Abstract

The invention belongs to the technical field of ferrous metallurgy, and discloses an intelligent self-adaptive converter smelting fire point area temperature monitoring system and method.The intelligent self-adaptive converter smelting fire point area temperature monitoring system comprises an oxygen lance, a gas supply module, a cooling module, a communication module and an edge calculation module, and the gas supply module and the cooling module are both connected with the oxygen lance; a multi-mode temperature sensor set is integrated in the oxygen lance, a communication module is installed on the outer side of the oxygen lance, and the cooling module, the air supply module and the multi-mode temperature sensor set are all in communication connection with the edge calculation module through the communication module. The technical scheme provided by the invention has the characteristics of high real-time performance, high intelligence, good safety and the like, and is suitable for a modern converter smelting process.

Description

Technical Field

[0001] The present invention belongs to the technical field of iron and steel metallurgy, and in particular relates to an intelligent self-adaptive converter smelting fire point zone temperature monitoring system and method. Background Art

[0002] Converter steelmaking is a core process in steel production. The temperature of the fire zone directly determines the metallurgical reaction efficiency and molten steel quality. Traditional monitoring methods rely on single thermocouples or infrared temperature measurement devices, which have the following limitations: (1) High-temperature molten pool splashing and strong oxidizing environment lead to short sensor life and measurement inaccuracy; (2) Single-point measurement cannot reflect the three-dimensional distribution of the temperature field, resulting in extensive injection control; (3) Process parameter adjustment relies on manual experience and has strong lag. In recent years, although some studies have attempted to use multi-sensor fusion technology, problems such as spatiotemporal asynchrony of multi-source data and dynamic coupling of metallurgical reactions have not been effectively solved, making it difficult to achieve real-time and precise control. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent self-adaptive converter smelting fire zone temperature monitoring system and method to solve the problems existing in the above-mentioned prior art.

[0004] On the one hand, to achieve the above-mentioned purpose, the present invention provides an intelligent adaptive converter smelting fire point zone temperature monitoring system, including an oxygen lance, an air supply module, a cooling module, a communication module and an edge computing module. The air supply module and the cooling module are both connected to the oxygen lance, and a multimodal temperature sensor group is integrated inside the oxygen lance. A communication module is installed on the outside of the oxygen lance, and the cooling module, the air supply module and the multimodal temperature sensor group are all communicated with the edge computing module through the communication module.

[0005] Optionally, the oxygen lance includes a nozzle and a protective sleeve, the nozzle is arranged at the end of the oxygen lance, the protective sleeve is installed inside the nozzle, and the multi-modal temperature sensor group is arranged inside the protective sleeve.

[0006] Optionally, the protective sleeve includes a silicon nitride ceramic layer and a liquid metal cooling interlayer arranged on an outer layer of the silicon nitride ceramic layer.

[0007] Optionally, the multimodal temperature sensor group includes a laser infrared temperature sensor, an optical fiber temperature sensor and a micro thermocouple.

[0008] Optionally, the gas supply module includes a gas booster and a storage tank connected in sequence.

[0009] Optionally, the cooling module includes a cooling water circulation system, a water inlet pipe and a water return pipe, one end of the water inlet pipe and the water return pipe are connected to the water cooling system, and the other end is connected to the oxygen gun.

[0010] Optionally, the edge computing module includes a main controller and a multi-sensor data fusion module electrically connected to the main controller, a dynamic control instruction generation module, a digital twin prediction module and an emergency response module.

[0011] On the other hand, to achieve the above-mentioned purpose, the present invention provides an intelligent adaptive converter smelting hot spot temperature monitoring method, which is applied to the intelligent adaptive converter smelting hot spot temperature monitoring system, comprising:

[0012] S1. Real-time acquisition of multi-dimensional temperature data of the fire zone by a multi-modal temperature sensor group integrated within the oxygen lance. The multi-dimensional temperature data includes laser infrared spectrum data, optical fiber vibration frequency signals, and thermocouple potential signals;

[0013] S2 uploads the multidimensional temperature data to the edge computing module through the communication module, uses the multi-sensor data fusion module to perform spatiotemporal calibration on heterogeneous data, and establishes a three-dimensional temperature field distribution model;

[0014] S3. The dynamic control instruction generation module calculates the oxygen lance nozzle gas supply parameter correction amount and the cooling water flow adjustment amount based on the three-dimensional temperature field distribution model and the preset smelting process curve, wherein the gas supply parameter correction amount includes the oxygen-inert gas mixture ratio, gas pressure and injection rate;

[0015] S4. Build a converter metallurgical reaction kinetics simulation model using the digital twin prediction module, inject real-time process parameters for deduction, predict temperature evolution trends within a set time period, and reversely optimize current control parameters;

[0016] S5. The optimized control parameters are sent to the gas supply module and cooling module through the communication module. The gas supply module's proportional mixer dynamically adjusts the mixed gas components according to the instructions, and the gas booster adjusts the output pressure in stages. The cooling module's oxygen lance cooling water circulation system adjusts the water inlet flow rate through a variable frequency water pump.

[0017] S6. The emergency response module continuously monitors abnormal temperature gradient characteristics. When it detects that the local temperature rise rate exceeds the safety threshold, it triggers a multi-level interlock protection mechanism. The multi-level interlock protection mechanism includes a first-level response to initiate forced cooling mode and a second-level response to shut off the gas supply module and raise the oxygen lance height.

[0018] S7. A feedback control loop is established through the main controller of the edge computing module. The set temperature distribution uniformity index is used as the optimization target. The control parameters of S3-S5 are dynamically updated using the model predictive control algorithm to form a closed-loop adaptive adjustment.

[0019] The technical effects of the present invention are:

[0020] The intelligent adaptive converter smelting fire point zone temperature monitoring system provided by the present invention collects multi-dimensional temperature data of the fire point zone in real time through a multi-modal temperature sensor group, and combines the multi-sensor data fusion, dynamic control instruction generation, digital twin prediction and emergency response functions of the edge computing module to achieve accurate monitoring and intelligent regulation of the converter smelting process. The system can calibrate heterogeneous data in real time, establish a three-dimensional distribution model of the temperature field, and optimize the smelting process parameters by dynamically adjusting the gas supply parameters and cooling water flow, significantly improving the smelting efficiency and product quality. In addition, the system's emergency response module can quickly detect abnormal temperature gradient characteristics and trigger a multi-level interlocking protection mechanism to effectively prevent equipment overheating and slag infiltration, significantly improving the safety and reliability of the system.

[0021] This invention leverages the closed-loop adaptive regulation capabilities of the edge computing module. The system optimizes temperature uniformity and uses a model predictive control algorithm to dynamically update control parameters, forming a closed-loop regulation mechanism. This adaptive regulation capability not only enhances the system's intelligence but also significantly reduces the need for manual intervention, energy consumption, and production costs, providing strong support for the efficient, safe, and intelligent operation of the converter smelting process. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0024] Figure 1 Schematic diagram of the system structure in an embodiment of the present invention;

[0025] Figure 2 Schematic diagram of the protective sleeve structure in an embodiment of the present invention;

[0026] Figure 3 This is an implementation flow chart of an embodiment of the present invention.

[0027] Explanation of reference numerals: 1. Oxygen lance; 2. Gas supply module; 3. Proportional mixer; 4. Communication module; 5. Cooling module; 6. Silicon nitride ceramic layer; 7. Liquid metal cooling interlayer. DETAILED DESCRIPTION

[0028] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0029] It should be understood that the terms described herein are intended only to describe particular embodiments and are not intended to limit the present invention. In addition, for numerical ranges herein, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Each smaller range between any intermediate value within a stated value or stated range and any other stated value or intermediate value within the stated range is also encompassed by the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded within the scope.

[0030] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention without departing from the scope or spirit of the invention. Other embodiments will be apparent to those skilled in the art from the present invention. The present description and examples are intended to be illustrative only.

[0031] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0032] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] like Figure 1 - Figure 3 As shown, in this embodiment, an intelligent adaptive converter smelting fire point zone temperature monitoring system is provided, including an oxygen gun 1, an air supply module 2, a cooling module 5, a communication module 4 and an edge computing module. The air supply module 2 and the cooling module 5 are both connected to the oxygen gun 1. A multi-modal temperature sensor group is integrated inside the oxygen gun 1. A communication module 4 is installed on the outside of the oxygen gun 1. The cooling module 5, the air supply module 2 and the multi-modal temperature sensor group are all communicated with the edge computing module through the communication module 4.

[0034] On the other hand, this embodiment provides an intelligent adaptive converter smelting hot spot temperature monitoring method, which is applied to an intelligent adaptive converter smelting hot spot temperature monitoring system, including:

[0035] S1. The multi-modal temperature sensor group integrated within the oxygen lance 1 collects real-time multi-dimensional temperature data of the fire point area, the multi-dimensional temperature data includes laser infrared spectrum data, optical fiber vibration frequency signal and thermocouple potential signal;

[0036] S2 uploads the multidimensional temperature data to the edge computing module through the communication module 4, uses the multi-sensor data fusion module to perform spatiotemporal calibration on heterogeneous data, and establishes a three-dimensional temperature field distribution model;

[0037] S3. The dynamic control instruction generation module calculates the nozzle gas supply parameter correction amount and the cooling water flow adjustment amount of the oxygen lance 1 based on the three-dimensional temperature field distribution model and the preset smelting process curve, wherein the gas supply parameter correction amount includes the oxygen-inert gas mixture ratio, gas pressure and injection rate;

[0038] S4. Build a converter metallurgical reaction kinetics simulation model using the digital twin prediction module, inject real-time process parameters for deduction, predict temperature evolution trends within a set time period, and reversely optimize current control parameters;

[0039] S5. The optimized control parameters are sent to the gas supply module 2 and the cooling module 5 through the communication module 4, wherein the proportion mixer 3 of the gas supply module 2 dynamically adjusts the mixed gas components according to the instructions, and the gas booster adjusts the output pressure in stages; the oxygen lance cooling water circulation system of the cooling module 5 adjusts the water inlet flow rate through the variable frequency water pump;

[0040] S6. The emergency response module continuously monitors abnormal temperature gradient characteristics. When it detects that the local temperature rise rate exceeds the safety threshold, it triggers a multi-level interlock protection mechanism. The multi-level interlock protection mechanism includes a first-level response to start the forced cooling mode, a second-level response to cut off the gas supply module 2 and increase the height of the oxygen lance 1;

[0041] S7. A feedback control loop is established through the main controller of the edge computing module. The set temperature distribution uniformity index is used as the optimization target. The control parameters of S3-S5 are dynamically updated using the model predictive control algorithm to form a closed-loop adaptive adjustment.

[0042] The intelligent adaptive converter smelting fire point zone temperature monitoring system provided in this embodiment collects multi-dimensional temperature data of the fire point zone in real time through a multi-modal temperature sensor group, and combines the multi-sensor data fusion, dynamic control instruction generation, digital twin prediction and emergency response functions of the edge computing module to achieve accurate monitoring and intelligent regulation of the converter smelting process. The system can calibrate heterogeneous data in real time, establish a three-dimensional distribution model of the temperature field, and optimize the smelting process parameters by dynamically adjusting the gas supply parameters and cooling water flow, significantly improving the smelting efficiency and product quality. In addition, the system's emergency response module can quickly detect abnormal temperature gradient characteristics and trigger a multi-level interlocking protection mechanism to effectively prevent equipment overheating and slag infiltration, significantly improving the safety and reliability of the system.

[0043] This embodiment utilizes the closed-loop adaptive adjustment function of the edge computing module. The system optimizes temperature distribution uniformity and uses a model predictive control algorithm to dynamically update control parameters, forming a closed-loop adjustment mechanism. This adaptive adjustment capability not only enhances the system's intelligence but also significantly reduces the need for manual intervention, energy consumption, and production costs, providing strong support for the efficient, safe, and intelligent operation of the converter smelting process.

[0044] In this embodiment, the oxygen gun 1 is the core component of the system, which integrates a multi-modal temperature sensor group for real-time collection of multi-dimensional temperature data of the fire point area. The multi-modal temperature sensor group includes a laser infrared temperature sensor, an optical fiber temperature sensor and a micro-thermocouple. The laser infrared temperature sensor is fixed on the central axis of the nozzle and is connected to the inner wall of the nozzle through a high-temperature resistant ceramic bracket; the optical fiber temperature sensor is evenly distributed around the inner wall of the nozzle and is embedded in the front end of the nozzle through an annular groove; the micro-thermocouple is embedded in the outer surface of the nozzle, 5-10 mm away from the nozzle outlet, and fixed by threads. All sensors are fixed with high-temperature alloy bolts, and the gaps are filled with silicon nitride sealant to prevent slag from infiltrating.

[0045] The nozzle is located at the end of the oxygen lance 1, and the protective sleeve is installed inside the nozzle. The nozzle of the oxygen lance 1 is a dynamically adjustable nozzle with seven independent nozzles. Each nozzle is connected to a micro servo motor (high-temperature resistant model), which drives the angle adjustment via a high-temperature resistant drive shaft. The center hole has a diameter of 20mm and injects the main oxygen flow. The angle adjustment range is 0-90°. The laser infrared sensor is centered, the fiber optic sensors are arranged in a ring, and micro thermocouples are embedded in the nozzle surface. The inner layer of the protective sleeve (silicon nitride ceramic) is in close contact with the sensor, and the outer layer (liquid metal interlayer) is connected to the cooling system.

[0046] A communication module 4 is installed on the outside of the oxygen gun 1, which is used to upload the temperature data collected by the multimodal temperature sensor group to the edge computing module. At the same time, the gas supply module 2 and the cooling module 5 are both connected to the oxygen gun 1, and data interaction and control instructions are transmitted with the edge computing module through the communication module 4. The communication module 4 includes one or more of the LoRa module, 2.5G communication module, 3G communication module, 4G communication module, and 5G communication module.

[0047] The gas supply module 2 is composed of a gas booster, a storage tank and a proportion mixer 3 connected in sequence. It is responsible for providing a mixed gas of oxygen and inert gas to the oxygen gun 1. The proportion mixer 3 of the gas supply module 2 dynamically adjusts the components of the mixed gas according to the control parameters issued by the edge computing module, and the gas booster adjusts the output pressure in stages.

[0048] The cooling module 5 includes a cooling water circulation system, a water inlet pipe and a return pipe. One end of the water inlet pipe and the return pipe is connected to the water cooling system, and the other end is connected to the oxygen gun 1 to adjust the cooling water flow of the oxygen gun 1. The cooling water circulation system of the cooling module 5 adjusts the flow rate of the water inlet pipe through a variable frequency water pump to meet real-time cooling needs.

[0049] The edge computing module is the control core of the system and includes a main controller, a multi-sensor data fusion module electrically connected to the main controller, a dynamic control instruction generation module, a digital twin prediction module, and an emergency response module. The multi-sensor data fusion module is responsible for performing spatiotemporal calibration on the heterogeneous data collected by the multimodal temperature sensor group and establishing a three-dimensional temperature field distribution model. The dynamic control instruction generation module calculates the air supply parameter correction and cooling water flow adjustment for the nozzle of oxygen lance 1 based on the three-dimensional temperature field distribution model and the preset smelting process curve. The digital twin prediction module constructs a converter metallurgical reaction kinetics simulation model to predict future temperature evolution trends and optimize current control parameters. The emergency response module continuously monitors abnormal temperature gradient characteristics and triggers a multi-level interlocking protection mechanism when it detects that the local temperature rise rate exceeds the safety threshold.

[0050] The entire system realizes data interaction and transmission of control instructions between modules through the communication module 4, forming a closed-loop adaptive adjustment to ensure the stability and safety of the converter smelting process.

[0051] The specific implementation process of this embodiment includes:

[0052] The nozzle at the end of the oxygen lance (1) is embedded in a silicon nitride ceramic protective sleeve. The outer liquid metal cooling layer (7) is maintained below 800°C by a circulating pump. A multimodal sensor array is arranged in a 120° circular array. The laser infrared sensor, with a wavelength of 1.55 μm, scans a 300 mm diameter area at 100 Hz. A fiber Bragg grating sensor is embedded in the sleeve surface. A miniature K-type thermocouple with a diameter of 1 mm extends into the airflow. Data from these three sensors is fed into a communication module (4).

[0053] When the edge computing module detects that the temperature in the southwest quadrant of the fire area is 50°C lower than the set value, the dynamic control instruction generation module executes:

[0054] The proportion of Ar gas is increased from 5% to 8% by the proportion mixer 3, and the oxygen flow rate is increased from 12000Nm 3 / h reduced to 11500Nm 3 / h; the gas booster adjusts the pressure from 0.8MPa to 0.85MPa in steps; the variable frequency water pump increases the cooling water flow rate from 6m / s to 7.2m / s. At the same time, the digital twin module predicts that the temperature in the area will rise by 80°C in the next 2 minutes, and adjusts the injection rate back to 11800Nm in advance. 3 / h, to avoid overshoot.

[0055] When the optical fiber sensor detects that the temperature rise rate at a certain point is greater than 150℃ / s:

[0056] Level 1 response: Start the backup water cooling circuit and instantly increase the cooling water flow by 50%;

[0057] Secondary response (continuous 500ms without relief): cut off the solenoid valve of the gas supply line, and the hydraulic lifting mechanism of the oxygen gun 1 is lifted 1.2m at a speed of 0.5m / s;

[0058] After the emergency is resolved, the system automatically generates an incident report, including the temperature curve, control command sequence, and response delay time. It also initiates an oxygen lance 1 health assessment, such as sensor drift detection and cooling interlayer leak inspection. A feedback control loop is established through the edge computing module's main controller, optimizing the set temperature distribution uniformity index. A neural network is used to dynamically update control parameters, creating a closed-loop adaptive regulation system.

[0059] This embodiment utilizes innovative multimodal sensor fusion and intelligent control technologies to construct an efficient and safe metallurgical process optimization system. First, a heterogeneous sensor network integrating laser infrared, optical fiber, and thermocouples achieves millimeter-level spatial resolution and ±5°C temperature measurement accuracy in the fire zone, with anti-interference capabilities more than three times higher than traditional solutions. Second, a spatiotemporal calibration algorithm and a digital twin prediction model are employed to reduce control command response time to 200ms and improve temperature field uniformity by 40%. Dynamic closed-loop regulation based on model predictive control (MPC) enables real-time matching of smelting process requirements, reducing oxygen consumption by 8%-12% and significantly reducing splashing incidents. Regarding safety, an innovative three-level interlock mechanism achieves millisecond-level abnormality response. Combined with nitrogen curtain blocking protection, this reduces the oxygen lance burnout rate by 90%. A specially designed silicon nitride ceramic-liquid metal composite sensor structure can operate continuously at temperatures of 1600°C for over 200 heats, reducing overall maintenance costs by 60%, resulting in a technical solution that comprehensively enhances accuracy, efficiency, safety, and cost-effectiveness.

[0060] The above description is merely a preferred embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. An intelligent adaptive converter smelting fire zone temperature monitoring system, characterized in that: The invention comprises an oxygen gun (1), an air supply module (2), a cooling module (5), a communication module (4) and an edge computing module, wherein the air supply module (2) and the cooling module (5) are both connected to the oxygen gun (1), a multi-modal temperature sensor group is integrated inside the oxygen gun (1), a communication module (4) is installed outside the oxygen gun (1), and the cooling module (5), the air supply module (2) and the multi-modal temperature sensor group are all communicatively connected to the edge computing module via the communication module (4).

2. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 1 is characterized in that: The oxygen lance (1) comprises a nozzle and a protective sleeve, wherein the nozzle is arranged at the end of the oxygen lance (1), the protective sleeve is installed inside the nozzle, and the multi-modal temperature sensor group is arranged inside the protective sleeve.

3. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 2 is characterized in that: The protective sleeve comprises a silicon nitride ceramic layer (6) and a liquid metal cooling interlayer (7) arranged on the outer layer of the silicon nitride ceramic layer (6).

4. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 1 is characterized in that: The multi-modal temperature sensor group includes a laser infrared temperature sensor, an optical fiber temperature sensor and a micro thermocouple.

5. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 1 is characterized in that: The gas supply module (2) comprises a gas booster and a storage tank which are connected in sequence.

6. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 1 is characterized in that: The cooling module (5) comprises a cooling water circulation system, a water inlet pipe and a water return pipe, wherein one end of the water inlet pipe and the water return pipe are connected to the water cooling system, and the other end is connected to the oxygen gun (1).

7. The intelligent adaptive converter smelting hot zone temperature monitoring system according to claim 1 is characterized in that: The edge computing module includes a main controller and a multi-sensor data fusion module electrically connected to the main controller, a dynamic control instruction generation module, a digital twin prediction module and an emergency response module.

8. An intelligent adaptive converter smelting hot spot temperature monitoring method, applied to an intelligent adaptive converter smelting hot spot temperature monitoring system according to any one of claims 1 to 7, characterized in that: include: S1. The multi-modal temperature sensor group integrated within the oxygen gun (1) collects multi-dimensional temperature data of the fire point area in real time, wherein the multi-dimensional temperature data includes laser infrared spectrum data, optical fiber vibration frequency signal and thermocouple potential signal; S2. Upload the multidimensional temperature data to the edge computing module through the communication module (4), use the multi-sensor data fusion module to perform spatiotemporal calibration on the heterogeneous data, and establish a three-dimensional distribution model of the temperature field; S3. The dynamic control instruction generation module calculates the nozzle air supply parameter correction amount and the cooling water flow adjustment amount of the oxygen lance (1) based on the three-dimensional distribution model of the temperature field and the preset smelting process curve, wherein the air supply parameter correction amount includes the oxygen-inert gas mixing ratio, gas pressure and injection rate; S4. Build a converter metallurgical reaction kinetics simulation model using the digital twin prediction module, inject real-time process parameters for deduction, predict temperature evolution trends within a set time period, and reversely optimize current control parameters; S5. The optimized control parameters are sent to the gas supply module (2) and the cooling module (5) through the communication module (4), wherein the proportion mixer (3) of the gas supply module (2) dynamically adjusts the mixed gas components according to the instructions, and the gas booster adjusts the output pressure in stages; the cooling water circulation system of the cooling module (5) adjusts the flow rate of the water inlet pipeline through the variable frequency water pump; S6. The emergency response module continuously monitors the abnormal temperature gradient characteristics. When it detects that the local temperature rise rate exceeds the safety threshold, it triggers a multi-level interlock protection mechanism, which includes a first-level response to start a forced cooling mode and a second-level response to cut off the gas supply module (2) and increase the height of the oxygen lance (1); S7. A feedback control loop is established through the main controller of the edge computing module. The set temperature distribution uniformity index is used as the optimization target. The control parameters of S3-S5 are dynamically updated using the model predictive control algorithm to form a closed-loop adaptive adjustment.

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