Oxygen lance jet flow detection system and method based on intelligent control

Abstract

The invention belongs to the technical field of ferrous metallurgy, and discloses an oxygen lance jet flow detection system and method based on intelligent control, and the system comprises a central control module, a gas supply module, a dynamic gas mixing module, an injection module and a non-contact measurement module. The central control system comprises a main controller, and an intelligent data processing module, a gas supply module and a dynamic gas mixing module which are electrically connected with the main controller, the dynamic gas mixing module is further connected with an injection module, a mechanical control module is arranged on the side surface of the injection module, and the non-contact measurement module is matched with a jet flow area of the injection module. The gas supply module, the dynamic gas mixing module, the injection module and the mechanical control module are all electrically connected with the main controller, and the non-contact measurement module is in communication connection with the main controller. According to the invention, the efficiency and reliability of oxygen lance jet flow detection are obviously improved, and powerful support is provided for intelligent upgrading of a steel 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 oxygen lance jet detection system and method based on intelligent control. Background Art

[0002] The oxygen lance is a critical process equipment in the steelmaking process. Its jet characteristics directly impact smelting efficiency, oxygen utilization, and product quality. Traditional oxygen lance jet detection methods rely primarily on contact measurement tools (such as pressure sensors and temperature probes) and manual parameter adjustment. These methods suffer from low measurement accuracy, slow response, and an inability to optimize in real time. The advancement of industrial automation and intelligent technologies has placed higher demands on oxygen lance jet detection systems, including high-precision measurement, real-time data processing, intelligent optimization, and closed-loop control.

[0003] Existing jet detection technology faces many challenges: First, traditional contact measurement methods are easily affected by environmental interference and it is difficult to accurately capture the velocity field, temperature field and turbulence characteristics of high-speed jets, resulting in insufficient measurement accuracy; second, the gas mixing device lacks dynamic flow adjustment capabilities, and cannot achieve real-time and precise control of the gas ratio, resulting in unstable fluctuations in jet parameters; at the same time, the system lacks real-time data analysis and feedback mechanisms, and cannot dynamically optimize the oxygen lance parameters based on jet characteristics. Over-reliance on manual experience leads to delayed and inefficient control; in addition, the safety monitoring system has obvious shortcomings, and its warning and emergency response capabilities for abnormal working conditions such as gas leakage and robotic arm collision are weak, posing a safety hazard; finally, the overall intelligence level is low, and there is a lack of data-driven intelligent analysis and prediction capabilities, making it difficult to achieve autonomous optimization of oxygen lance operating parameters and iterative performance improvement. Summary of the Invention

[0004] The purpose of the present invention is to provide an oxygen lance jet flow detection system and method based on intelligent control to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above-mentioned objectives, the present invention provides an oxygen lance jet detection system based on intelligent control, comprising a central control module, an air supply module, a dynamic gas mixing module, an injection module and a non-contact measurement module, wherein the central control system comprises a main controller and an intelligent data processing module electrically connected to the main controller, the air supply module is connected to the dynamic gas mixing module, and the dynamic gas mixing module is also connected to the injection module, a mechanical control module is provided on the side of the injection module, the non-contact measurement module is arranged in coordination with the jet area of ​​the injection module, the air supply module, the dynamic gas mixing module, the injection module and the mechanical control module are all electrically connected to the main controller, and the non-contact measurement module is communicatively connected to the main controller.

[0006] Optionally, the gas supply module includes a gas booster and a storage tank connected in sequence.

[0007] Optionally, the dynamic gas mixing module adopts a mass flow controller.

[0008] Optionally, the injection module includes a test nozzle, a main gas pipeline, and an auxiliary gas pipeline. The air inlet ends of the main gas pipeline and the auxiliary gas pipeline are both connected to the dynamic gas mixing module, and the air outlet end of the main gas pipeline is connected to the test nozzle, and the test nozzle sprays gas onto the test pressure row.

[0009] Optionally, the non-contact measurement module includes a laser Doppler velocimeter, a particle image velocimeter, a high-speed camera and an infrared thermal imager, the laser Doppler velocimeter and the particle image velocimeter are aligned with the jet area, the high-speed camera is installed above the injection module, and the infrared thermal imager is installed on the side of the injection module.

[0010] Optionally, the mechanical control module includes a six-axis robotic arm and a displacement sensor installed at the end of the six-axis robotic arm, and the six-axis robotic arm is installed above or on the side of the jet area.

[0011] Optionally, the intelligent data processing module includes a digital twin pre-simulation module, a gas proportioning and pressurization module, a jet detection data processing module, an oxygen gun optimization module and a robotic arm path planning module.

[0012] An oxygen lance jet flow detection method based on intelligent control, the oxygen lance jet flow detection system based on intelligent control, comprising

[0013] Step S1: Input oxygen lance design parameters, including the number of nozzles, Mach number, gas type, and mixing ratio; generate an initial jet flow field prediction model through computational fluid dynamics simulation; set the main / auxiliary gas flow range, and the horizontal and vertical scanning paths for test compression and exhaust;

[0014] Step S2: pressurizing one or more gases among O2, CO2, and Ar to a target pressure through a gas booster, dynamically adjusting the main / auxiliary gas flow rate according to a preset ratio using a mass flow controller, and delivering the mixed gas to the injection module;

[0015] Step S3: Control the six-axis robotic arm to move the test pressure row to the initial detection position, start the main / auxiliary gas injection, and generate a high-speed jet through the test nozzle;

[0016] Step S4: using a laser Doppler velocimeter and a particle image velocimeter to synchronously collect jet velocity field data at a frequency of ≥10 kHz, recording the flow state image with a high-speed camera, and obtaining the jet temperature distribution with an infrared thermal imager to obtain non-contact measurement data;

[0017] The non-contact measurement data is transmitted to the intelligent data processing module in real time. If the diffusion angle in the core area of ​​the jet exceeds the threshold or the temperature gradient is abnormal, the main / auxiliary gas flow ratio or the position of the robotic arm is dynamically adjusted through closed-loop control to optimize the flow field stability.

[0018] Step S6: generating a jet core velocity attenuation curve, a turbulence intensity distribution diagram, and a three-dimensional energy thermodynamic diagram based on the non-contact measurement data to obtain jet characteristic data;

[0019] Step S7: inputting the jet characteristic data into an oxygen lance optimization model for prediction, and outputting oxygen lance optimization parameters; wherein the oxygen lance optimization parameters include increase or decrease in the number of nozzles, adjustment of Mach number, correction of gas mixing ratio, oxygen utilization rate improvement rate, and smelting time reduction ratio; the oxygen lance optimization model is constructed based on a convolutional neural network model;

[0020] Step S8: Generate a jet detection report, which includes flow field distribution, optimization suggestions and abnormal alarm records; if gas leakage or robot arm collision risk is detected, immediately trigger the emergency shut-off valve and interrupt the test process.

[0021] The technical effects of the present invention are:

[0022] Through intelligent control, non-contact measurement and closed-loop optimization technology, this invention solves the shortcomings of traditional oxygen lance jet detection systems in measurement accuracy, dynamic adjustment, real-time optimization and safety, significantly improves the efficiency and reliability of oxygen lance jet detection, and provides strong support for the intelligent upgrade of steel smelting processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] 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.

[0024] 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:

[0025] Figure 1 Schematic diagram of the structure of an embodiment of the present invention;

[0026] Figure 2 This is an implementation flow chart of an embodiment of the present invention.

[0027] Explanation of reference numerals: 1. Gas supply module; 2. Dynamic gas mixing module; 3. Injection module; 4. Non-contact measurement module; 5. Central control module. 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 2 As shown, this embodiment provides an oxygen lance jet detection system based on intelligent control, including a central control module 5, a gas supply module 1, a dynamic gas mixing module 2, an injection module 3 and a non-contact measurement module 4, the central control system includes a main controller and an intelligent data processing module electrically connected to the main controller, the gas supply module 1 and the dynamic gas mixing module 2 are connected, the dynamic gas mixing module 2 is also connected to the injection module 3, a mechanical control module is provided on the side of the injection module 3, the non-contact measurement module 4 is arranged in coordination with the jet area of ​​the injection module 3, the gas supply module 1, the dynamic gas mixing module 2, the injection module 3 and the mechanical control module are all electrically connected to the main controller, and the non-contact measurement module 4 is communicatively connected to the main controller.

[0034] This embodiment solves the shortcomings of traditional oxygen lance jet detection systems in measurement accuracy, dynamic adjustment, real-time optimization and safety through intelligent control, non-contact measurement and closed-loop optimization technology, significantly improves the efficiency and reliability of oxygen lance jet detection, and provides strong support for the intelligent upgrade of steel smelting processes.

[0035] In this embodiment, the central control module 5 is the core of the entire system, which consists of a main controller and an intelligent data processing module. The main controller is connected to the intelligent data processing module through an electrical connection and is responsible for coordinating and controlling the overall operation of the system. The gas supply module 1, the dynamic gas mixing module 2, the injection module 3 and the mechanical control module are all electrically connected to the main controller, and the non-contact measurement module 4 exchanges data with the main controller through a communication connection.

[0036] The gas supply module 1 includes a gas booster and a storage tank, which are connected in sequence to provide a gas source for the system. The output end of the gas supply module 1 is connected to the dynamic gas mixing module 2. The dynamic gas mixing module 2 adopts a mass flow controller for dynamically adjusting the gas flow according to a preset ratio. The output end of the dynamic gas mixing module 2 is connected to the injection module 3 to deliver the mixed gas to the injection module 3. The injection module 3 is composed of a test nozzle, a main gas pipeline and an auxiliary gas pipeline. The air inlet ends of the main gas pipeline and the auxiliary gas pipeline are both connected to the dynamic gas mixing module 2, and the air outlet end of the main gas pipeline is connected to the test nozzle. The test nozzle sprays the gas onto the test pressure plate. A mechanical control module is provided on the side of the injection module 3. The mechanical control module includes a six-axis robotic arm and a displacement sensor installed at its end. The six-axis robotic arm is installed above or on the side of the jet area to control the position of the test pressure plate. The six-axis robotic arm combined with the displacement sensor can achieve high-precision positioning of the test pressure plate and reduce manual intervention.

[0037] The non-contact measurement module 4 includes a laser Doppler velocimeter, a particle image velocimeter, a high-speed camera, and an infrared thermal imager. The laser Doppler velocimeter and particle image velocimeter are aimed at the jet flow area, while the high-speed camera is mounted above the injection module 3 and the infrared thermal imager is mounted to the side of the injection module 3. These sensors collect velocity field data, flow pattern images, and temperature distribution in the jet flow area.

[0038] The intelligent data processing module includes a digital twin pre-simulation module, a gas proportioning and pressurization module, a jet detection data processing module, an oxygen gun optimization module, and a robotic arm path planning module. These modules work together to process non-contact measurement data, generate jet characteristic data, and output optimization parameters through the oxygen gun optimization model.

[0039] The entire system is coordinated by the main controller to achieve closed-loop control of gas supply, mixing, injection, measurement and optimization, ensuring the stability and optimization effect of the oxygen lance jet.

[0040] This embodiment is also provided with safety protection devices, including an emergency shut-off valve, a gas leakage sensor and an audible and visual alarm. The emergency shut-off valve is installed at the entrance of the main gas line, close to the storage tank or booster of the gas supply system. The gas leakage sensor is installed around the injection system and the gas supply system to ensure that any gas leakage can be monitored. The audible and visual alarm is installed in the operating area of ​​the system to facilitate operators to detect abnormalities in time.

[0041] The system configuration and parameters in this embodiment are:

[0042] The gas booster has a boost ratio of 50:1 and a maximum output pressure of 10.0 MPa. The storage tank has a capacity of 100 Nm 3 , design pressure 12.0MPa, storage gas is O2 and CO2 (mixing ratio 9:1).

[0043] The main gas flow range of the mass flow controller (MFC) is 1-50000Nm 3 / h, auxiliary gas flow range 1-25000Nm 3 / h, mixing accuracy ±0.5%.

[0044] The test nozzle has an outer diameter of 300mm, 6 nozzles, and a Mach number of 2.2. The main gas pipeline is made of stainless steel with an inner diameter of 200mm, and the annular seam area of ​​the auxiliary gas pipeline is 50,000mm. 2 .

[0045] The sampling frequency of the laser Doppler velocimeter (LDV) is 10 kHz, and the velocity resolution is 0.1 m / s; the frame rate of the high-speed camera is 10,000 fps, and the resolution is 1920 × 1080; the temperature measurement range of the infrared thermal imager is 0-2000°C, with an accuracy of ±1°C and a spatial resolution of 0.5 mm.

[0046] The six-axis robotic arm has a load capacity of 50kg and a repeatability accuracy of ±0.1mm; the linear error of the displacement sensor is ±0.05mm and the measuring range is ±1500mm.

[0047] Digital twin pre-simulation: Build a CFD model based on ANSYS Fluent, with a mesh size of 5 million and a simulation error of ≤2%;

[0048] Oxygen lance optimization model, the convolutional neural network (CNN) training dataset contains 500 sets of historical jet data, and the prediction accuracy is ≥95%.

[0049] The specific implementation steps of this embodiment include:

[0050] Step S1: Digital twin pre-simulation and parameter initialization

[0051] Input oxygen lance parameters: 6 nozzles, Mach number 2.2, gas O2 and CO2 (9:1 mixture). Generate an initial flow field model through CFD simulation, and predict the jet core velocity to be 52m / s, the diffusion angle to be 14°, and the impact depth to be 1200mm. Set the main gas flow rate to 45000Nm 3 / h, auxiliary gas flow rate 2250Nm 3 / h (main gas 5%), the horizontal scanning path of the test compression discharge is 1500-3000mm (interval 500mm), and the vertical height is ±1000mm (interval 300mm).

[0052] Step S2: Start the gas booster to pressurize the O2 and CO2 mixed gas to 8.5MPa, and stabilize the tank pressure to 9.0MPa. Adjust the main gas flow rate to 45000Nm through MFC. 3 / h, auxiliary gas flow rate up to 2250Nm 3 / h, mixing ratio error ≤0.3%.

[0053] Step S3: The six-axis robot moves the test press to the initial position (horizontally 1500 mm, vertically 0 mm). The main / auxiliary air injection is turned on, and the test nozzle generates a high-speed jet for 40 seconds.

[0054] Step S4: LDV / PIV synchronously collect the jet velocity field, detecting the core velocity as 50.8 m / s (error -2.3%) and the diffusion angle as 15.5°; a high-speed camera records the jet morphology; and an infrared thermal imager measures the maximum temperature in the jet impact area as 680°C.

[0055] Step S5: The intelligent data processing module detects that the diffusion angle exceeds the threshold (>15°) and automatically increases the auxiliary gas flow rate to 2475Nm 3 / h (main gas 5.5%), and at the same time controlled the robotic arm to move the test pressure exhaust 100mm toward the nozzle. After re-collecting the data, the diffusion angle dropped to 13.8° and the core speed stabilized to 51.2m / s.

[0056] Step S6: Generate a jet core velocity attenuation curve, a turbulence intensity distribution map, and a three-dimensional energy thermodynamic map; input the jet characteristic data into the CNN model, and output optimization suggestions: adjust the nozzle angle from 12° to 14°; adjust the gas mixture ratio to O2:CO2 = 8.5:1.5; predict that the oxygen utilization rate will increase by 6.8% and the smelting time will be shortened by 9.2%.

[0057] Step S8: Generate a PDF test report containing the flow field distribution, optimized parameters, and temperature anomaly records. During the test, if the gas leak sensor detects that the CO2 concentration exceeds the limit (>1000ppm), it will trigger the emergency shut-off valve (response time 30ms), interrupt the test, and issue an alarm.

[0058] This embodiment uses advanced equipment such as a laser Doppler velocimeter and a particle image velocimeter, combined with a high-speed camera and an infrared thermal imager, to achieve non-contact, high-precision measurement of the jet velocity field, temperature field, and flow state. This ensures the real-time stability of the jet parameters and solves the problems of traditional contact measurement being susceptible to interference and flow regulation lag.

[0059] This embodiment integrates an intelligent data processing module to analyze jet characteristic data in real time, and dynamically adjusts the gas flow ratio or robotic arm position through a closed-loop control algorithm, thereby optimizing the jet flow field stability, significantly improving oxygen utilization and smelting efficiency, and breaking through the inefficient mode of traditional systems that rely on manual experience.

[0060] The system configured in this embodiment is equipped with gas leak sensors and emergency shut-off valves, enabling millisecond-level response and safe handling of abnormal operating conditions. Furthermore, by generating jet core velocity decay curves, turbulence intensity distribution maps, and three-dimensional energy thermodynamic maps, it visually demonstrates the dynamic characteristics of the jet flow, providing data support for parameter adjustments and addressing the shortcomings of traditional systems in safety monitoring and visual analysis.

[0061] In summary, this embodiment solves the shortcomings of traditional oxygen lance jet detection systems in measurement accuracy, dynamic adjustment, real-time optimization, and safety through intelligent control, non-contact measurement, and closed-loop optimization technologies, significantly improves the efficiency and reliability of oxygen lance jet detection, and provides strong support for the intelligent upgrade of steel smelting processes.

[0062] 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 oxygen lance jet flow detection system based on intelligent control, characterized in that: The invention comprises a central control module (5), an air supply module (1), a dynamic gas mixing module (2), an injection module (3) and a non-contact measurement module (4), wherein the central control system comprises a main controller and an intelligent data processing module electrically connected to the main controller, the air supply module (1) is connected to the dynamic gas mixing module (2), the dynamic gas mixing module (2) is also connected to the injection module (3), a mechanical control module is provided on the side of the injection module (3), the non-contact measurement module (4) is arranged in coordination with the jet region of the injection module (3), the air supply module (1), the dynamic gas mixing module (2), the injection module (3) and the mechanical control module are all electrically connected to the main controller, and the non-contact measurement module (4) is communicatively connected to the main controller.

2. The oxygen lance jet flow detection system based on intelligent control according to claim 1 is characterized in that: The gas supply module (1) comprises a gas booster and a storage tank which are connected in sequence.

3. The oxygen lance jet flow detection system based on intelligent control according to claim 1 is characterized in that: The dynamic gas mixing module (2) adopts a mass flow controller.

4. The oxygen lance jet flow detection system based on intelligent control according to claim 1, characterized in that: The injection module (3) comprises a test nozzle, a main gas pipeline, and an auxiliary gas pipeline. The air inlet ends of the main gas pipeline and the auxiliary gas pipeline are both connected to the dynamic gas mixing module (2). The air outlet end of the main gas pipeline is connected to the test nozzle, and the test nozzle sprays gas onto the test pressure plate.

5. The oxygen lance jet flow detection system based on intelligent control according to claim 1 is characterized in that: The non-contact measurement module (4) comprises a laser Doppler velocimeter, a particle image velocimeter, a high-speed camera and an infrared thermal imager, the laser Doppler velocimeter and the particle image velocimeter are aligned with the jet region, the high-speed camera is installed above the injection module (3), and the infrared thermal imager is installed on the side of the injection module (3).

6. The oxygen lance jet flow detection system based on intelligent control according to claim 1, characterized in that: The mechanical control module includes a six-axis robotic arm and a displacement sensor installed at the end of the six-axis robotic arm. The six-axis robotic arm is installed above or on the side of the jet area.

7. The oxygen lance jet flow detection system based on intelligent control according to claim 1 is characterized in that: The intelligent data processing module includes a digital twin pre-simulation module, a gas proportioning and pressurization module, a jet detection data processing module, an oxygen gun optimization module and a robotic arm path planning module.

8. An oxygen lance jet flow detection method based on intelligent control, applied to an oxygen lance jet flow detection system based on intelligent control according to any one of claims 1 to 7, characterized in that: include Step S1: Input oxygen lance design parameters, including the number of nozzles, Mach number, gas type, and mixing ratio; generate an initial jet flow field prediction model through computational fluid dynamics simulation; set the main / auxiliary gas flow range, and the horizontal and vertical scanning paths for test compression and exhaust; Step S2: pressurizing one or more gases among O2, CO2, and Ar to a target pressure using a gas booster, dynamically adjusting the main / auxiliary gas flow rate according to a preset ratio using a mass flow controller, and delivering the mixed gas to the injection module (3); Step S3: Control the six-axis robotic arm to move the test pressure row to the initial detection position, start the main / auxiliary gas injection, and generate a high-speed jet through the test nozzle; Step S4: using a laser Doppler velocimeter and a particle image velocimeter to synchronously collect jet velocity field data at a frequency of ≥10 kHz, recording the flow state image with a high-speed camera, and obtaining the jet temperature distribution with an infrared thermal imager to obtain non-contact measurement data; The non-contact measurement data is transmitted to the intelligent data processing module in real time. If the diffusion angle in the core area of ​​the jet exceeds the threshold or the temperature gradient is abnormal, the main / auxiliary gas flow ratio or the position of the robotic arm is dynamically adjusted through closed-loop control to optimize the flow field stability. Step S6: generating a jet core velocity attenuation curve, a turbulence intensity distribution diagram, and a three-dimensional energy thermodynamic diagram based on the non-contact measurement data to obtain jet characteristic data; Step S7: inputting the jet characteristic data into an oxygen lance optimization model for prediction, and outputting oxygen lance optimization parameters; wherein the oxygen lance optimization parameters include increase or decrease in the number of nozzles, adjustment of Mach number, correction of gas mixing ratio, oxygen utilization rate improvement rate, and smelting time reduction ratio; the oxygen lance optimization model is constructed based on a convolutional neural network model; Step S8: Generate a jet detection report, which includes flow field distribution, optimization suggestions and abnormal alarm records; if gas leakage or robot arm collision risk is detected, immediately trigger the emergency shut-off valve and interrupt the test process.

Images