Visualization system for hearth of aluminum electrolysis cell
By designing the aluminum electrolytic tank furnace visualization system, real-time monitoring and visualization of furnace status is achieved using hardware equipment and modular software architecture, the problems of strong subjectivity and poor real-time performance of traditional monitoring methods are solved, production efficiency and product quality are improved, and industrial intelligence development is promoted.
Patent Information
- Application Number
- CN202411653287.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-19
- Publication Date
- 2025-02-28
AI Technical Summary
The traditional aluminum electrolytic tank furnace monitoring method has problems such as strong subjectivity, poor real-time performance, and difficulty in fully reflecting the furnace state, which affects production efficiency and product quality.
Aluminum electrolytic tank furnace visualization system is designed, using hardware equipment such as temperature distribution, current distribution, magnetic field distribution, and flow field distribution testing instruments, combined with a modular and layered design software architecture to realize real-time monitoring and visual display of furnace status.
It realizes accurate monitoring and visual display of furnace condition, improves production efficiency and product quality, reduces production costs, and promotes the intelligent development of the aluminum electrolytic industry.
Smart Images
Figure CN119530889A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to a visualization system, in particular to a furnace visualization system for an aluminum electrolysis cell. Background Art
[0002] The furnace rib in aluminum electrolysis production refers to the solidified electrolyte protective layer formed by the liquid electrolyte in the electrolytic cell and the inner side of the electrolytic cell side structure. The furnace rib is mainly composed of a mixture of solid inorganic salts such as cryolite, alumina, and calcium fluoride. The furnace rib is the basis of the electrolytic cell chamber, which is the molten pool of the electrolytic cell reaction. The main functions of the furnace rib are as follows: (1) The furnace side has a heat-insulating effect, which can protect the side structure of the electrolytic cell and prevent the side blocks from being corroded by the electrolyte, which may cause the risk of furnace leakage; (2) The furnace sidewall is an insulating layer that can prevent current from passing through the side wall and has the effect of reducing horizontal current; (3) Seal the connection between the cathode carbon block and the surrounding paste in the electrolytic cell to prevent electrolyte leakage at the connection gap; (4) The furnace side is an important part of the electrolytic cell's thermal balance self-regulating system, and has the function of regulating the electrolytic cell's thermal balance and material balance. When the electrolytic cell is running cold, the furnace side becomes thicker, the tank chamber shrinks, and the electrolytic cell's heat dissipation decreases, preventing the electrolytic cell from further cooling and forming a new thermal balance; on the contrary, when the electrolytic cell is in an overheated state, the furnace chamber melts appropriately to enhance the side heat dissipation.
[0003] The voltage stability of the electrolytic cell with irregular inner sidewall is poor. When the voltage is unstable, the mirror surface of the aluminum liquid in the cell fluctuates greatly, which aggravates the secondary reaction of the aluminum liquid and reduces the current efficiency. A more regular inner sidewall can reduce the energy consumption caused by the horizontal current on the side, and can also play a role in heat preservation, thereby reducing the energy loss of the electrolytic cell. Therefore, the quality of the electrolytic cell furnace sidewall directly affects the economic indicators of electrolytic production. In the actual aluminum electrolytic production process, follow the management idea of "focusing on furnace control" and adjust the production parameters around the changes in the furnace to ensure the smooth operation of the electrolytic cell.
[0004] With the development of industrial automation and intelligence, the aluminum electrolysis industry has put forward higher requirements for the monitoring and management of the production process. However, the traditional aluminum electrolysis furnace monitoring method mainly relies on the daily single-point measurement, experience judgment and daily production data analysis of process personnel. This method has the problems of strong subjectivity, poor real-time performance and difficulty in fully reflecting the furnace status. Summary of the invention
[0005] The purpose of the present invention is to provide an aluminum electrolysis cell furnace visualization system. The realization of accurate monitoring, visualization and prediction of furnace status is of great significance for improving production efficiency and optimizing production decisions, and is also an important way to promote the intelligent development of the aluminum electrolysis industry.
[0006] The technical solution of the present invention is: a furnace visualization system for an aluminum electrolytic cell, which includes hardware equipment and software architecture; the hardware equipment includes test instruments related to the temperature distribution, current distribution, magnetic field distribution, and flow field distribution of the electrolytic cell; the software architecture adopts a modular design and a layered design, and the real-time monitoring and visualization functions of the furnace of the aluminum electrolytic cell are jointly realized by the hardware system and the software system.
[0007] In the aforementioned aluminum electrolytic cell furnace visualization system, the hardware equipment is divided into temporary detection equipment and real-time monitoring equipment; the temporary detection equipment includes magnetic field, flow field test, and current distribution test equipment, and the test data is stored in the basic database of the aluminum electrolytic cell magnetic fluid parameter input port; the real-time monitoring equipment includes real-time temperature test equipment, which is fixed at the key position on the side of the electrolytic cell, and the test data is stored in the dynamic database of the aluminum electrolytic furnace change trend input port.
[0008] In the aforementioned aluminum electrolytic cell furnace visualization system, the software architecture modularly designs the system database according to the furnace visualization system function analysis, and divides it into real-time monitoring parameter module, temporary test parameter module, production parameter module, and design parameter module; the layered design will carry out data acquisition layer, data storage layer, data analysis and calculation layer, application layer, and user human-computer interaction interface design.
[0009] In the aforementioned aluminum electrolytic cell furnace visualization system, the real-time monitoring data module is used to store real-time temperature data of key parts on the side of the electrolytic cell; the temporary detection data module is used to store single test data related to the magnetic field, electric field and flow field of the electrolytic cell; the production parameter data module is used to store aluminum electrolysis production process parameters, mainly including electrolyte level, aluminum level, electrolyte composition, cell voltage and related production process parameters; the design parameter module is used to store basic design parameters of the electrolytic cell, mainly including current intensity, number of anode groups, anode size, electrolytic cell furnace design size, and lining structure basic parameters related design parameters.
[0010] In the aforementioned aluminum electrolytic cell furnace visualization system, the data acquisition layer is used to clean, denoise, and standardize the collected data to ensure the accuracy and reliability of the data; the data storage layer is used to store and manage the collected real-time data; the data analysis and calculation layer is applied to furnace state monitoring, and based on the preprocessed data, the furnace state is monitored in real time in combination with three-dimensional models, simulation calculations, machine learning or deep learning algorithms, and a furnace state recognition model is constructed to realize automatic recognition of various states such as furnace hot tank, cold tank, anode long bag, precipitation, and leg extension; the application layer is used to realize visualization display, and visualization technology is used to intuitively display the furnace state to production management personnel in the form of charts and images; through the visualization interface, users can view the changing trend of the furnace state in real time and understand the abnormal situation in the production process; the user human-computer interaction interface is used for management personnel to realize data filtering, zooming, and dragging related operations in the interactive interface.
[0011] In the aforementioned aluminum electrolytic cell furnace visualization system, the user-computer interaction interface also has prediction and decision support functions. It combines historical data and real-time data and uses the LSTM deep learning model to predict the future state of the furnace.
[0012] Beneficial effects of the present invention: Compared with the prior art, after adopting the above technical solution, the present invention has the following advantages: (1) Realize real-time monitoring and visualization of furnace status: By building an aluminum electrolytic cell furnace visualization system, real-time monitoring and visualization of furnace status can be achieved, providing intuitive and accurate information support for production management personnel.
[0013] (2) Improve production efficiency and product quality: Through real-time monitoring and prediction of furnace status, abnormal situations in the production process can be discovered and handled in a timely manner, production plans and production parameters can be optimized, and production efficiency and product quality can be improved.
[0014] (3) Reduce production costs: By accurately monitoring and predicting furnace status, we can reduce resource waste and cost increases caused by production abnormalities, thereby reducing production costs.
[0015] (4) Promoting the intelligent development of the aluminum electrolysis industry: The present invention will promote the intelligent development of the aluminum electrolysis industry and provide technical support and demonstration guidance for the transformation and upgrading of the aluminum electrolysis industry. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 is a flow chart of the overall method of the present invention; Figure 2 This is a schematic diagram of data modularization of the present invention. DETAILED DESCRIPTION
[0017] The present invention is further described below in conjunction with the accompanying drawings and embodiments, but they are not intended to limit the present invention.
[0018] The embodiment of the present invention is a furnace visualization system for aluminum electrolytic cells, which includes hardware equipment and software architecture. The hardware equipment includes relevant test instruments for the temperature distribution, current distribution, magnetic field distribution, flow field distribution, etc. of the electrolytic cell. The software architecture adopts modular design and layered design, and the real-time monitoring and visualization functions of the furnace of the aluminum electrolytic cell are realized through the hardware system and the software system.
[0019] The hardware equipment is mainly divided into temporary detection equipment and real-time monitoring equipment. Temporary detection equipment mainly includes magnetic field, flow field test, and current distribution test equipment. The test data is stored in the basic database of the magnetic fluid parameter input port of the aluminum electrolysis cell. The real-time monitoring equipment mainly includes real-time temperature test equipment. This equipment needs to be fixed at the key part of the side of the electrolysis cell. The test data is stored in the dynamic database of the aluminum electrolysis furnace change trend input port.
[0020] The software architecture includes modular design and hierarchical design. According to the functional analysis of the furnace visualization system, the system database is modularly designed and divided into real-time monitoring parameter module, temporary test parameter module, production parameter module, and design parameter module. The hierarchical design will carry out the design of data acquisition layer, data storage layer, data analysis and calculation layer, application layer, and user human-computer interaction interface.
[0021] The real-time monitoring data module is used to store the real-time temperature data of key parts on the side of the electrolytic cell.
[0022] The temporary detection data module is used to store single test data related to the electrolytic cell magnetic field, electric field, flow field, etc.
[0023] The production parameter data module is used to store aluminum electrolysis production process parameters, mainly including electrolyte level, aluminum level, electrolyte composition, cell voltage and other related production process parameters.
[0024] The design parameter module is used to store the basic design parameters of the electrolytic cell, mainly including current intensity, number of anode groups, anode size, electrolytic cell furnace design size, basic parameters of the lining structure and other related design parameters.
[0025] The functions of the data acquisition layer, data storage layer, data analysis and calculation layer, application layer, and user human-computer interaction interface are as follows: After the database is established, the relevant data is preprocessed, and the furnace state is monitored in real time by combining three-dimensional models, simulation calculations, machine learning or deep learning algorithms. By building a furnace state recognition model, the furnace hot tank, cold tank, anode long bag, precipitation, leg extension and other states can be automatically recognized. At the same time, the furnace state is intuitively displayed to production managers in the form of charts, images, etc. Managers can implement data filtering, zooming, dragging and other related operations in the interactive interface, which can help users better understand the data, find problems and make decisions. In addition, historical data and real-time data are combined to use deep learning models such as LSTM to predict the future state of the furnace.
[0026] The functions of each layer are as follows: The data collection layer is used to clean, denoise, and standardize the collected data to ensure the accuracy and reliability of the data.
[0027] The data storage layer is used to store and manage the collected real-time data. Different from the traditional relational database, the real-time database in the data storage layer has higher data throughput and faster response time, which can meet the requirements of real-time data in the electrolysis production process.
[0028] The data analysis and computing layer is mainly used for furnace status monitoring. Based on the preprocessed data, it combines three-dimensional models, simulation calculations, machine learning or deep learning algorithms to monitor the furnace status in real time. By building a furnace status recognition model, it can realize automatic recognition of various states of the furnace, such as hot tank, cold tank, anode long bag, precipitation, and leg extension.
[0029] The application layer is used to achieve visual display. It uses visualization technology to intuitively display the furnace status to production managers in the form of charts and images. Through the visualization interface, users can view the changing trend of the furnace status in real time and understand abnormal situations in the production process.
[0030] The user-computer interaction interface is used by managers to perform data filtering, zooming, dragging and other operations in the interactive interface, which can help users better understand data, identify problems and make decisions.
[0031] The user-computer interaction interface also has prediction and decision support functions. It combines historical data and real-time data and uses the LSTM deep learning model to predict the future state of the furnace. It provides production decision support based on the prediction results, helping production managers optimize production plans, adjust production parameters, and improve production efficiency and product quality.
[0032] Taking the 500kA electrolytic cell as an example, the magnetic field, flow field and electric field of the 500kA electrolytic cell are first tested and stored in the temporary test parameter module. A real-time temperature monitoring device is installed on the side of the 500kA electrolytic cell, and the real-time temperature data is stored in the real-time monitoring data module. In the production parameter data module, relevant production process parameters such as electrolyte level, aluminum level, electrolyte composition, and cell voltage are input. In the design parameter module, the basic design parameters of the electrolytic cell are input, mainly including current intensity, number of anode groups, anode size, electrolytic cell furnace design size, lining structure basic parameters and other related design parameters. Combined with three-dimensional models, simulation calculations, machine learning or deep learning algorithms, a furnace state recognition model is constructed to monitor the 500kA furnace state in real time. Using visualization technology, the furnace state is output in the form of charts, images, etc. to form a furnace visualization interface. At the same time, deep learning models such as LSTM are used to predict the future state of the furnace. Production decision support is provided based on the prediction results to help production managers optimize production plans, adjust production parameters, and improve production efficiency and product quality.
Claims
1. An aluminum electrolytic cell furnace visualization system, characterized in that: This system includes hardware equipment and software architecture; the hardware equipment includes relevant test instruments for the temperature distribution, current distribution, magnetic field distribution, and flow field distribution of the electrolytic cell; the software architecture adopts modular design and layered design, and realizes the real-time monitoring and visualization functions of the aluminum electrolytic cell furnace through the hardware system and software system.
2. The aluminum electrolysis cell furnace visualization system according to claim 1, characterized in that: The hardware equipment is divided into temporary detection equipment and real-time monitoring equipment; the temporary detection equipment includes magnetic field, flow field test, and current distribution test equipment, and the test data is stored in the basic database of the magnetic fluid parameter input port of the aluminum electrolysis cell; the real-time monitoring equipment includes real-time temperature test equipment, which is fixed at the key position on the side of the electrolysis cell, and the test data is stored in the dynamic database of the aluminum electrolysis furnace change trend input port.
3. The aluminum electrolysis cell furnace visualization system according to claim 1, characterized in that: The software framework conducts modular design of the system database according to the function analysis of the furnace visualization system, and divides it into real-time monitoring parameter module, temporary test parameter module, production parameter module and design parameter module; The layered design will include data collection layer, data storage layer, data analysis and computing layer, application layer, and user-computer interaction interface design.
4. A furnace visualization system for aluminum electrolysis cell according to claim 3, characterized in that: The real-time monitoring data module is used to store real-time temperature data of key parts on the side of the electrolytic cell; the temporary detection data module is used to store single test data related to the magnetic field, electric field and flow field of the electrolytic cell; the production parameter data module is used to store aluminum electrolysis production process parameters, mainly including electrolyte level, aluminum level, electrolyte composition, cell voltage and related production process parameters; the design parameter module is used to store the basic design parameters of the electrolytic cell, mainly including current intensity, number of anode groups, anode size, electrolytic cell furnace design size, and lining structure basic parameters related design parameters.
5. A furnace visualization system for aluminum electrolysis cell according to claim 3, characterized in that: The data collection layer is used to clean, denoise and standardize the collected data to ensure the accuracy and reliability of the data; The data storage layer is used to store and manage the collected real-time data; the data analysis and calculation layer is applied to furnace status monitoring. Based on the preprocessed data, it combines three-dimensional models, simulation calculations, machine learning or deep learning algorithms to monitor the furnace status in real time. By building a furnace status recognition model, it can realize automatic recognition of various states such as furnace hot tank, cold tank, anode long bag, precipitation, leg extension, etc.; the application layer is used to realize visual display, and uses visualization technology to intuitively display the furnace status to production managers in the form of charts and images; through the visualization interface, users can view the changing trend of the furnace status in real time and understand abnormal situations in the production process; the user human-computer interaction interface is used for managers to implement data filtering, zooming, and dragging related operations in the interactive interface.
6. The aluminum electrolysis cell furnace visualization system according to claim 5, characterized in that: The user-computer interaction interface also has prediction and decision-making support functions. It combines historical data and real-time data and uses the LSTM deep learning model to predict the future state of the furnace.