A method for dynamic heat preservation of aluminum electrolytic cell body

Abstract

The present invention proposes a method for dynamic heat preservation of an aluminum electrolytic cell body, which relates to the technical field of aluminum electrolysis, and includes: S1 installing a dynamic heat preservation device outside the aluminum electrolytic cell body, the dynamic heat preservation device including: a support structure fixed to the outer wall of the cell body; a movable heat preservation unit installed on the support structure, wherein the movable heat preservation unit contains a heat preservation material whose thermal conductivity increases with increasing temperature; a driving mechanism for adjusting the position of the movable heat preservation unit; S2 arranging multiple sensors on the aluminum electrolytic cell for real-time collection of cell body operation parameters; S3 establishing a cold and hot analysis model of the electrolytic cell, and judging the cold and hot state of the electrolytic cell according to the operating parameters; S4 based on the cold and hot state, operating the driving mechanism through the control system, adjusting the distance between the movable heat preservation unit and the outer wall of the cell body, and realizing dynamic heat preservation. The present invention strikes a balance between improving energy utilization efficiency and ensuring safe operation of the electrolytic cell, and ultimately achieves the dual goals of energy saving and consumption reduction and safe production.

Description

Technical Field

[0001] The invention relates to the technical field of aluminum electrolysis, and in particular to a method for dynamically insulating an aluminum electrolysis cell body. Background Art

[0002] The aluminum electrolysis industry is a large power consumer. Every ton of raw aluminum produced consumes 13,000 kWh of electricity, of which only 6,400 kWh is used to heat raw materials and electrolysis reactions, and the rest of the electricity is lost to the environment in the form of heat. Optimizing the design of the electrolytic cell and adopting aluminum electrolysis energy-saving technology is an effective way to achieve energy conservation in the aluminum electrolysis process. However, this method requires an overhaul of the electrolytic cell, which is relatively costly; and the inevitable overheating during the initial start-up of the electrolytic cell and during production requires the electrolytic cell to be designed to be relatively heat-dissipating.

[0003] At present, some enterprises adhere insulation materials to the outer wall of the electrolytic cell to reduce the heat dissipation of the electrolytic cell, increase the heat dissipation thermal resistance of the electrolytic cell and improve the energy utilization efficiency. However, the operation of the electrolytic cell is a dynamic process. When the electrolytic cell is running cool, increasing the insulation can indeed reduce heat loss and improve the energy utilization efficiency; but when the electrolytic cell tends to heat up or even overheats and needs to dissipate heat, it will cause the electrolytic cell to be over-insulated. When the temperature of the electrolytic cell shell is too high and exceeds the maximum tolerance temperature of the steel, the shell strength drops sharply, which brings huge risks to electrolytic production.

[0004] In the prior art, some methods attempt to reduce heat loss by installing fixed insulation materials on the outer wall of the electrolytic cell. However, these methods often cannot adapt to the dynamic changes during the operation of the electrolytic cell and it is difficult to strike a balance between insulation effect and safety.

[0005] In summary, the prior art lacks a method that can dynamically adjust the insulation effect according to the operating status of the electrolytic cell while ensuring safe production. Summary of the invention

[0006] In view of this, the present invention proposes a method for dynamic heat preservation of the body of an aluminum electrolytic cell, which realizes intelligent dynamic adjustment of the heat preservation effect of the electrolytic cell by installing an adjustable dynamic heat preservation device on the outside of the electrolytic cell body, combining the real-time collected operating parameters and the cold and hot analysis model. This method aims to reduce the heat dissipation and energy consumption of the electrolytic cell while avoiding the risk of excessive temperature of the outer wall of the cell body due to excessive heat preservation, thereby achieving a balance between improving energy utilization efficiency and ensuring the safe operation of the electrolytic cell, and ultimately achieving the dual goals of energy saving and consumption reduction and safe production.

[0007] The technical solution of the present invention is implemented as follows: The present invention provides a method for dynamic heat preservation of an aluminum electrolytic cell body, comprising:

[0008] S1 A dynamic heat preservation device is installed outside the aluminum electrolysis cell body. The dynamic heat preservation device includes:

[0009] A support structure fixed to the outer wall of the tank;

[0010] a movable insulation unit mounted on the support structure, wherein the movable insulation unit comprises an insulation material having a thermal conductivity that increases with increasing temperature;

[0011] A drive mechanism for adjusting the position of the movable heat preservation unit;

[0012] S2 sets multiple sensors on the aluminum electrolytic cell to collect the cell operation parameters in real time;

[0013] S3 establishes a hot and cold analysis model for the electrolytic cell and determines the hot and cold state of the electrolytic cell according to the operating parameters;

[0014] Based on the hot and cold states, S4 operates the driving mechanism through the control system to adjust the distance between the movable insulation unit and the outer wall of the tank body to achieve dynamic insulation.

[0015] On the basis of the above scheme, preferably, the operating parameters include tank temperature, set voltage, working voltage, average voltage, alumina consumption, current efficiency, DC power consumption, number and duration of anode effects.

[0016] On the basis of the above solution, preferably, the supporting structure includes four vertical pillars, which are respectively fixed on the outer walls of the four sides of the tank body, and each pillar is fixedly connected to the outer wall of the tank body by at least two expansion bolts.

[0017] On the basis of the above scheme, preferably, the movable insulation unit includes multiple independent insulation modules, the multiple insulation modules are evenly distributed along the circumference of the trough body, and gaps are left between adjacent insulation modules. Each insulation module is connected to the supporting structure through at least two driving mechanisms, and the driving mechanisms are electric push rods or cylinders.

[0018] On the basis of the above scheme, preferably, the thermal insulation material is a multilayer composite material with double-sided coating, and the thermal conductivity λ and the temperature T satisfy the relationship: λ=λ0+k(T-T0) 2 , where λ0 is the initial thermal conductivity, k is the thermal conductivity temperature coefficient, and T0 is the reference temperature.

[0019] Based on the above scheme, preferably, the mathematical expression of the electrolytic cell thermal analysis model is as follows:

[0020]

[0021] In the formula, is the thermal state index, is the operating voltage, To set the voltage, is the slot current, is the average voltage, is the current efficiency, is the DC power consumption, is the number of anode effects, is the total duration of the anode effect, is the alumina consumption, is the rate of change of the tank temperature, is the rate of change of alumina consumption, T is the tank temperature, is the current time, to The model coefficients to be determined are determined through statistical analysis of historical data and regression methods.

[0022] On the basis of the above scheme, preferably, the specific judgment logic for judging the hot and cold state of the electrolytic cell according to the operating parameters is:

[0023] Calculate the comprehensive evaluation value of the thermal state index S :

[0024]

[0025] In the formula, to is the evaluation coefficient, is the integration time constant, is the current time;

[0026] Defining a composite threshold function :

[0027]

[0028] In the formula, , is the weight coefficient, , is the magnification factor, The function is used to convert the comprehensive evaluation value S Map to the interval [-1,1];

[0029] according to The value of determines the hot and cold state:

[0030] when When , it is judged as extremely strong thermotaxis operation;

[0031] when When , it is judged as strong thermotaxis operation;

[0032] when When , it is judged as weak thermotaxis operation;

[0033] when When , it is judged to be stable operation;

[0034] when When , it is judged as weak cooling operation;

[0035] when When , it is judged as strong cooling operation;

[0036] when When , it is judged as extremely strong cooling operation;

[0037] in, , , , , and is the preset threshold and satisfies .

[0038] Based on the above solution, preferably, step S4 includes:

[0039] S41 sets the maximum distance between the movable heat preservation unit and the outer wall of the tank body, takes the movable heat preservation unit and the outer wall of the tank body to be in contact as the minimum distance, takes the midpoint between the maximum distance and the minimum distance as the middle position, takes the midpoint between the maximum distance and the middle position as the larger distance, and takes the midpoint between the minimum distance and the middle position as the smaller distance;

[0040] S42 operates the drive mechanism for dynamic insulation based on the hot and cold states through the control system:

[0041] When it is determined to be an extremely strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the maximum distance and start auxiliary cooling measures;

[0042] When it is determined to be a strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to a greater distance;

[0043] When it is determined to be a weak heat-tending operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the middle position;

[0044] When it is determined to be in stable operation, the control system maintains the current position of the movable heat preservation unit;

[0045] When it is determined to be a weak cooling operation, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to the middle position;

[0046] When it is determined that the operation is in a strong cooling trend, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to a smaller distance;

[0047] When it is determined that the operation is extremely cold, the control system sends a signal to the drive mechanism to move the movable insulation unit to the minimum distance and start the auxiliary heating measure.

[0048] Based on the above solution, preferably, the control system includes:

[0049] A data acquisition module, used for receiving sensor data;

[0050] A data processing unit for processing sensor data and executing a thermal analysis model;

[0051] The decision module is used to determine the value of the comprehensive evaluation value S and the composite threshold function. Generate control instructions;

[0052] The execution control module is used to convert the control instructions into operating signals of the drive mechanism and auxiliary measures.

[0053] On the basis of the above solution, preferably, the control system is connected with the driving mechanism and the auxiliary measures via an industrial field bus, and uses Modbus RTU or Profibus DP protocol for communication.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] (1) The present invention realizes intelligent dynamic adjustment of the electrolytic cell's thermal insulation effect by installing an adjustable dynamic thermal insulation device on the outside of the electrolytic cell, combined with real-time collected operating parameters and hot and cold analysis models. This method can not only provide effective thermal insulation when the electrolytic cell tends to cool down and reduce energy consumption, but also reduce thermal insulation in time when the electrolytic cell tends to heat up to avoid the risk of overheating of the cell body, thereby achieving a good balance between improving energy utilization efficiency and ensuring the safe operation of the electrolytic cell;

[0056] (2) The present invention uses an insulation material whose thermal conductivity increases with increasing temperature, which can automatically increase heat dissipation when the temperature of the electrolytic cell rises, forming a passive protection mechanism. This characteristic, combined with dynamic regulation, further enhances the safety and reliability of the system and effectively prevents potential dangers caused by overheating of the cell;

[0057] (3) The electrolytic cell hot and cold analysis model proposed in the present invention comprehensively considers multiple key operating parameters, including voltage deviation, temperature change rate, current efficiency, anode effect and other factors. This comprehensive analysis method improves the accuracy of hot and cold state judgment and provides a reliable decision-making basis for dynamic insulation control;

[0058] (4) The present invention introduces a composite threshold function to judge the hot and cold state, taking into account factors such as the instantaneous value, rate of change and cumulative effect of the thermal state index. This multi-dimensional judgment method improves the system's sensitivity and response speed to changes in the electrolytic cell state, making dynamic insulation control more accurate and timely;

[0059] (5) The present invention designs a multi-level adjustable heat preservation unit position and adopts corresponding control strategies according to different degrees of hot and cold states. This refined control method enables the system to respond to various operating conditions more flexibly, achieving precise adjustment of the heat preservation effect and optimization of energy utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0061] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] like Figure 1 As shown, the present invention provides a method for dynamically keeping the body of an aluminum electrolytic cell warm, comprising:

[0064] S1 A dynamic heat preservation device is installed outside the aluminum electrolysis cell body. The dynamic heat preservation device includes:

[0065] A support structure fixed to the outer wall of the tank;

[0066] a movable insulation unit mounted on the support structure, wherein the movable insulation unit comprises an insulation material having a thermal conductivity that increases with increasing temperature;

[0067] A drive mechanism for adjusting the position of the movable heat preservation unit;

[0068] S2 sets multiple sensors on the aluminum electrolytic cell to collect the cell operation parameters in real time;

[0069] S3 establishes a hot and cold analysis model for the electrolytic cell and determines the hot and cold state of the electrolytic cell according to the operating parameters;

[0070] Based on the hot and cold states, S4 operates the driving mechanism through the control system to adjust the distance between the movable insulation unit and the outer wall of the tank body to achieve dynamic insulation.

[0071] Specifically, in one embodiment of the present invention, the installation process of the dynamic thermal insulation device is as follows:

[0072] 1. Installation of the support structure: a) Prepare four vertical pillars, using high-temperature resistant, high-strength alloy steel. b) Select appropriate installation locations on the outer walls of the four sides of the electrolytic cell, and drill at least two expansion bolt holes at each location. c) Use expansion bolts to fix the pillars to the outer wall of the cell, ensuring that each pillar has at least two fixing points. d) Check the verticality and stability of the pillars and make adjustments if necessary.

[0073] 2. Fabrication and installation of movable insulation units: a) Select insulation materials whose thermal conductivity increases with increasing temperature, such as multi-layer composite materials with double-sided coatings, whose thermal conductivity λ and temperature T satisfy the relationship: λ=λ0+k(T-T0) 2 , where λ0 is the initial thermal conductivity, k is the temperature coefficient of thermal conductivity, and T0 is the reference temperature. b) Cut the insulation material into appropriate sizes and make multiple independent insulation modules. c) Install a lightweight but sturdy frame outside the insulation module for connecting the drive mechanism. d) Distribute the insulation modules evenly on the support structure, ensuring that there is an appropriate gap between adjacent insulation modules.

[0074] 3. Installation of drive mechanism: a) Select a suitable drive mechanism, such as electric push rod or air cylinder. b) Install at least two drive mechanisms for each insulation module to ensure stability and precise control. c) Fix one end of the drive mechanism to the support structure and connect the other end to the insulation module frame. d) Debug the drive mechanism to ensure that it can smoothly and accurately control the position of the insulation module.

[0075] Specifically, in one embodiment of the present invention, the installation process of the sensor system is as follows:

[0076] 1. Selection and arrangement of sensors: a) Select temperature sensors suitable for high temperature environments, such as thermocouples or infrared thermometers. b) Install temperature sensors at key locations of the tank, including but not limited to: the outer wall of the cathode area, the outer wall of the insulation area, the outer wall of the furnace bottom area, and the electrolyte area. c) Install voltage sensors to monitor the operating voltage, set voltage, and average voltage. d) Install current sensors to monitor the tank current. e) Install an alumina consumption monitoring device.

[0077] 2. Building a data acquisition system: a) Select data acquisition equipment suitable for industrial environments, such as PLC or industrial computers. b) Connect all sensors to the data acquisition equipment through appropriate interfaces. c) Configure the data acquisition software and set appropriate sampling frequency and data storage method. d) Establish a data transmission network to ensure that the collected data can be transmitted to the control system in real time.

[0078] 3. Calibration and testing of sensor systems: a) Perform initial calibration of all installed sensors to ensure measurement accuracy. b) Perform system integration testing to verify that all sensor data can be correctly collected and transmitted. c) Simulate different operating conditions to test the response speed and stability of the sensor system. d) Establish a regular calibration and maintenance plan to ensure long-term operational reliability.

[0079] Specifically, the operating parameters collected by the sensor system include: tank temperature, set voltage, operating voltage, average voltage, alumina consumption, current efficiency, DC power consumption, number and duration of anode effects.

[0080] Specifically, in one embodiment of the present invention, the main purpose of step S3 is to establish a thermal analysis model of the electrolytic cell and determine the thermal state of the electrolytic cell according to the operating parameters.

[0081] Specifically, the mathematical expression of the electrolytic cell thermal analysis model is as follows:

[0082]

[0083] In the formula, is the thermal state index, is the operating voltage, To set the voltage, is the slot current, is the average voltage, is the current efficiency, is the DC power consumption, is the number of anode effects, is the total duration of the anode effect, is the alumina consumption, is the rate of change of the tank temperature, is the rate of change of alumina consumption, T is the tank temperature, is the current time, to The model coefficients to be determined are determined through statistical analysis of historical data and regression methods.

[0084] Specifically, in the mathematical expression of the model, the first term It indicates the extra heat generated by the deviation between the actual working voltage and the set voltage. It reflects the degree to which the operating state of the electrolytic cell deviates from the set value. If the voltage deviation is larger, the extra heat generated is more, indicating that the electrolytic cell may be in a heat-trending state. The second item The heat generated by the deviation of the working voltage from the average voltage reflects the change of the current operating state of the electrolyzer relative to the historical average level. If the current working voltage is higher than the average voltage, it may indicate that the electrolyzer is in a state of heating. Indicates the rate of change of the tank temperature, which directly reflects the changing trend of the electrolytic tank temperature. A positive value indicates a temperature increase, and a negative value indicates a temperature decrease, which helps to capture temperature changes in a timely manner; the fourth item It indicates the additional heat generated due to the loss of current efficiency, reflecting the efficiency of the electrolysis process. The lower the current efficiency, the more energy is converted into heat, and the possibility of electrolytic cell heating increases. The fifth item and the sixth item Indicates the influence of anode effect. Anode effect will cause voltage to increase and generate additional heat. Frequent or continuous anode effect will make the electrolytic cell hotter. Item 7 Indicates the change of alumina consumption rate, reflecting the stability of the electrolysis process. Abnormal changes in alumina consumption rate may indicate that the electrolysis process is unstable and affects the thermal balance; is a bias term used to correct the baseline level of the model.

[0085] The model combines the electrical parameters, thermodynamic parameters and chemical reaction parameters of the electrolytic cell to comprehensively evaluate the thermal state of the cell; by considering the rate of change of temperature and alumina consumption, the model can sensitively reflect the dynamic changes of operating parameters and make timely judgments on abnormal situations; the current efficiency and anode effect are included in the model as independent items, highlighting the significant impact of process efficiency and abnormal events on thermal balance; the deviations of the working voltage from the set voltage and the average voltage are considered separately, reflecting both long-term deviations and capturing short-term fluctuations.

[0086] in, to The determination process is as follows:

[0087] Data collection: Collect a large amount of historical operating data, including all relevant parameters. Data preprocessing: Clean the data, remove outliers and missing values, and perform standardization. Feature engineering: Construct the features required for the model, such as voltage difference, temperature change rate, etc. Model training: Use multiple linear regression or advanced regression methods (such as ridge regression, LASSO) to fit the coefficients. Model evaluation: Use cross-validation methods to evaluate the generalization ability of the model. Coefficient determination: Based on the regression results, get to Model validation: Use a dataset that was not used in the training to validate the model’s predictions. Regular updates: Establish a regular update mechanism to ensure that the model adapts to long-term changes in the electrolyzer.

[0088] Specifically, the specific judgment logic for judging the hot and cold state of the electrolytic cell according to the operating parameters is:

[0089] Calculate the comprehensive evaluation value of the thermal state index S :

[0090]

[0091] In the formula, to is the evaluation coefficient, is the integration time constant, The first item considers the current thermal state index value, the second item reflects the change rate of the thermal state index, the third item considers the cumulative effect of the thermal state index over a period of time, the fourth item reflects the acceleration of the change of the thermal state index, and the fifth item considers the change rate of the thermal state index change rate. By comprehensively considering multiple aspects of the thermal state index, the accuracy and sensitivity of the judgment are improved.

[0092] Defining a composite threshold function :

[0093]

[0094] In the formula, , is the weight coefficient, which is used to adjust the relative importance of the two tanh functions. , is the amplification factor, which is used to adjust the sensitivity of the function. The function is used to convert the comprehensive evaluation value S Mapping to the [-1,1] interval makes the judgment result smoother. By using nonlinear functions, the model's ability to distinguish between different degrees of hot and cold states is improved. This embodiment uses a dual tanh function structure. Each tanh function has an amplification factor and a weight factor. The amplification factor can control the slope of the tanh function and affect the function's comprehensive evaluation value for the input. S sensitivity. , For rapid response to extreme conditions (extreme heating / cooling), Used for smooth response to other states.

[0095] in , The determination process is as follows:

[0096] Data preparation: Collect historical operation data, classify the data by hot and cold states, and establish a standard data set. Initial value estimation: Analyze the distribution range of the comprehensive evaluation value S and determine , , , , and The value of , Parameter optimization: Minimizing judgment error is the optimization goal, using historical data for simulation and adjusting , value, It can distinguish different hot and cold states and perform iterative optimization until the optimization target is met. , value.

[0097] according to The value of determines the hot and cold state:

[0098] when When , it is judged as extremely strong thermotaxis operation;

[0099] when When , it is judged as strong thermotaxis operation;

[0100] when When , it is judged as weak thermotaxis operation;

[0101] when When , it is judged to be stable operation;

[0102] when When , it is judged as weak cooling operation;

[0103] when When , it is judged as strong cooling operation;

[0104] when When , it is judged as extremely strong cooling operation;

[0105] in, , , , , and is the preset threshold and satisfies By setting multiple thresholds, a refined classification of the hot and cold states of the electrolytic cell is achieved, providing a detailed decision-making basis for subsequent dynamic insulation control.

[0106] In actual operation, the model parameters and preset thresholds can be adjusted regularly according to the operating results to adapt to the long-term changes of the electrolyzer.

[0107] Specifically, in one embodiment of the present invention, step S4 includes:

[0108] S41 sets the maximum distance between the movable heat preservation unit and the outer wall of the tank body, takes the movable heat preservation unit and the outer wall of the tank body to be in contact as the minimum distance, takes the midpoint between the maximum distance and the minimum distance as the middle position, takes the midpoint between the maximum distance and the middle position as the larger distance, and takes the midpoint between the minimum distance and the middle position as the smaller distance;

[0109] S42 operates the drive mechanism for dynamic insulation based on the hot and cold states through the control system:

[0110] When it is determined to be an extremely strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the maximum distance and start auxiliary cooling measures;

[0111] When it is determined to be a strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to a greater distance;

[0112] When it is determined to be a weak heat-tending operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the middle position;

[0113] When it is determined to be in stable operation, the control system maintains the current position of the movable heat preservation unit;

[0114] When it is determined to be a weak cooling operation, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to the middle position;

[0115] When it is determined that the operation is in a strong cooling trend, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to a smaller distance;

[0116] When it is determined that the operation is extremely cold, the control system sends a signal to the drive mechanism to move the movable insulation unit to the minimum distance and start the auxiliary heating measure.

[0117] Among them, the maximum distance is the maximum heat dissipation state, the larger distance is the transition position under the strong heat tendency state, the middle position is the buffer transition area, the smaller distance is the transition position under the strong cooling state, and the minimum distance is the maximum heat preservation state.

[0118] In this embodiment, the target positions of the weak heating trend and the weak cooling trend are both set to the middle position, so as to facilitate rapid response in two directions.

[0119] According to the judgment process of the composite threshold function, stable operation is a state between weak heating and weak cooling, that is, in actual control, the current position is also an intermediate position.

[0120] If the operation is changed from stable operation to weak heating operation, the movable heat preservation unit is always kept in the middle position. Similarly, if the operation is changed from stable operation to weak cooling operation, the movable heat preservation unit is also kept in the middle position.

[0121] The control system determines the current position of the tank body according to the current operating state of the tank body and the previous operating state, and generates a control signal according to the changing trend of the operating state to control the movable insulation unit to move away from or close to the tank body to dissipate heat or keep the tank body warm.

[0122] In this embodiment, the threshold range is The state within the range is used as a buffer state. At this time, the movable insulation unit is not adjusted frequently and drastically to avoid accelerating the wear of the equipment. However, it is still necessary to set multiple threshold ranges to determine multiple operating states. This is to achieve an early warning purpose and to detect the trend of heating or cooling in time. In the actual operation process, if necessary, a lower intensity auxiliary cooling can be started, or monitoring can be strengthened to take preventive measures.

[0123] Specifically, the auxiliary heating measure may be to increase air cooling or electric heating.

[0124] In this embodiment, the control system includes the following modules:

[0125] The data acquisition module receives real-time data from the sensor and uses a high-speed data acquisition card with a sampling frequency of no less than 1 Hz.

[0126] The data processing unit processes the sensor data and executes the thermal analysis model, using an industrial-grade computer to run the optimized algorithm.

[0127] The decision module is based on the comprehensive evaluation value S and the composite threshold function Generate control instructions and output discrete control instructions based on preset judgment logic.

[0128] The execution control module converts the control instructions into operating signals for the drive mechanism and auxiliary measures, and uses a PLC or a dedicated controller to output the control signals through the industrial field bus.

[0129] The control system communicates with the drive mechanism and auxiliary measures using industrial fieldbus:

[0130] Using Modbus RTU or Profibus DP protocol, the communication rate is not less than 9600bps to ensure the real-time and reliability of communication.

[0131] In another embodiment of the present invention, software and hardware limits are set to prevent the movable insulation unit from exceeding a safe range; a manual operation mode of the drive mechanism is implemented for emergency situations and maintenance; fault diagnosis and alarm functions are added to the control system; and sensors and drive mechanisms are regularly calibrated to ensure the long-term reliability of the system.

[0132] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for dynamic heat preservation of an aluminum electrolytic cell, characterized in that: include: S1 A dynamic heat preservation device is installed outside the aluminum electrolysis cell body. The dynamic heat preservation device includes: A support structure fixed to the outer wall of the tank; a movable insulation unit mounted on the support structure, wherein the movable insulation unit comprises an insulation material having a thermal conductivity that increases with increasing temperature; A drive mechanism for adjusting the position of the movable heat-insulating unit; S2 sets multiple sensors on the aluminum electrolytic cell to collect the cell operation parameters in real time; The operating parameters include tank temperature, set voltage, working voltage, average voltage, alumina consumption, current efficiency, DC power consumption, number and duration of anode effects; S3 establishes a hot and cold analysis model for the electrolytic cell and determines the hot and cold state of the electrolytic cell according to the operating parameters; The mathematical expression of the electrolytic cell thermal analysis model is as follows: Where H is the thermal state index, V w is the operating voltage, V s is the set voltage, I is the slot current, V avg is the average voltage, η is the current efficiency, P DC is the DC power consumption, N AE is the number of anode effects, t AE is the total duration of the anode effect, is the alumina consumption, is the rate of change of the tank temperature, is the rate of change of alumina consumption, T is the tank temperature, t is the current time, w1 to w8 are model coefficients to be determined, which are determined by statistical analysis of historical data and regression method; The specific judgment logic for judging the hot and cold state of the electrolytic cell according to the operating parameters is: Calculate the comprehensive evaluation value S of the thermal state index: In the formula, β1 to β5 are evaluation coefficients, τ is the integration time constant, and t is the current time; Define the composite threshold function Ψ(S): Ψ(S)=γ1·tanh(κ1·S)+γ2·tanh(κ2·S) In the formula, γ1 and γ2 are weight coefficients, κ1 and κ2 are magnification coefficients, and the tanh function is used to map the comprehensive evaluation value S to the interval [-1,1]; According to the value of Ψ(S), judge the hot and cold state: When Ψ(S)>Φ1, it is judged as extremely strong thermotaxis operation; When Φ1≥Ψ(S)>Φ2, it is determined to be a strong thermotaxis operation; When Φ2≥Ψ(S)>Φ3, it is judged as weak thermotropism operation; When Φ3≥Ψ(S)>Φ4, it is judged to be stable operation; When Φ4≥Ψ(S)>Φ5, it is judged as weak cooling operation; When φ5≥Ψ(S)>Φ6, it is determined to be a strong cooling operation; When Ψ(S)≤Φ6, it is judged as extremely strong cooling operation; Among them, Φ1, Φ2, Φ3, Φ4, Φ5 and Φ6 are preset thresholds, and satisfy Φ1>Φ2>Φ3>Φ4>Φ5>Φ6; S4 operates the driving mechanism through the control system based on the hot and cold state to adjust the distance between the movable insulation unit and the outer wall of the tank to achieve dynamic insulation; Step S4 includes: S41 sets the maximum distance between the movable heat preservation unit and the outer wall of the tank body, takes the movable heat preservation unit and the outer wall of the tank body to be in contact as the minimum distance, takes the midpoint between the maximum distance and the minimum distance as the middle position, takes the midpoint between the maximum distance and the middle position as the larger distance, and takes the midpoint between the minimum distance and the middle position as the smaller distance; S42 operates the drive mechanism for dynamic insulation based on the hot and cold states through the control system: When it is determined to be an extremely strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the maximum distance and start auxiliary cooling measures; When it is determined to be a strong heat-seeking operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to a greater distance; When it is determined to be a weak heat-tending operation, the control system sends a signal to the drive mechanism to move the movable heat-insulating unit to the middle position; When it is determined to be in stable operation, the control system maintains the current position of the movable heat preservation unit; When it is determined to be a weak cooling operation, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to the middle position; When it is determined that the operation is in a strong cooling trend, the control system sends a signal to the drive mechanism to move the movable heat preservation unit to a smaller distance; When it is determined that the operation is extremely cold, the control system sends a signal to the drive mechanism to move the movable insulation unit to the minimum distance and start the auxiliary heating measure.

2. A method for dynamic heat preservation of an aluminum electrolysis cell according to claim 1, characterized in that: The supporting structure comprises four vertical pillars which are respectively fixed on the outer walls of the four sides of the tank body, and each pillar is fixedly connected to the outer wall of the tank body by at least two expansion bolts.

3. A method for dynamic heat preservation of an aluminum electrolysis cell according to claim 1, characterized in that: The movable insulation unit includes multiple independent insulation modules, which are evenly distributed along the circumference of the tank body, with gaps between adjacent insulation modules. Each insulation module is connected to the supporting structure through at least two driving mechanisms, which are electric push rods or cylinders.

4. A method for dynamic heat preservation of an aluminum electrolytic cell according to claim 1, characterized in that: The insulation material is a multilayer composite material with double-sided coating, and the relationship between its thermal conductivity λ and temperature T satisfies: λ=λ0+k(T-T0) 2 , where λ0 is the initial thermal conductivity, k is the thermal conductivity temperature coefficient, and T0 is the reference temperature.

5. A method for dynamic heat preservation of an aluminum electrolysis cell according to claim 1, characterized in that: The control system includes: A data acquisition module, used for receiving sensor data; A data processing unit for processing sensor data and executing a thermal analysis model; A decision module, used for generating a control instruction according to a comprehensive evaluation value S and a composite threshold function Ψ(S); The execution control module is used to convert the control instructions into operating signals of the drive mechanism and auxiliary measures.

6. A method for dynamic heat preservation of an aluminum electrolysis cell as claimed in claim 5, characterized in that: The control system is connected to the drive mechanism and auxiliary measures through the industrial field bus and uses Modbus RTU or Profibus DP protocol for communication.

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