Electrolytic bath health degree evaluation method and electrolytic bath age prediction method

Abstract

The invention belongs to the technical field of electrolytic cells, and particularly relates to an electrolytic cell health degree evaluation method and an electrolytic cell age prediction method.The method comprises the steps that full life cycle data of a plurality of electrolytic cells are collected, and an electrolytic cell health management database is established; establishing an electrolytic bath health degree evaluation model according to the electrolytic bath health management database; and collecting active-service electrolytic cell data, and predicting the health degree of the active-service electrolytic cell according to the electrolytic cell health degree evaluation model. The method comprises the following steps: acquiring key data parameters of the electrolytic cell in different life stages, covering equipment, energy, chemical examination, materials, measurement and other data influencing the operation of the electrolytic cell, establishing an electrolytic cell health management database, and comparing and analyzing key influence factors influencing the service life of the electrolytic cell in combination with historical data and expert experience; judgment of cell health degree, cell life prediction, cell risk and problem early warning are realized, and improvement of electrolysis production management is guided.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrolytic cells, and particularly relates to a method for evaluating the health of an electrolytic cell and a method for predicting the age of an electrolytic cell. Background Art

[0002] In the field of electrolytic industry, as the core production equipment, the operation efficiency of electrolytic cells is directly related to the production efficiency, energy consumption, and product quality. However, during the continuous operation of electrolytic cells, they are affected by multiple factors such as raw material quality fluctuations, operating condition changes, and natural equipment aging. These factors together lead to differences in the health status of electrolytic cells. Electrolytic cells in a sub-healthy or non-optimal state will not only significantly increase energy consumption and reduce the output of aluminum products, but also are very likely to trigger a series of fault problems, thus posing a severe challenge to the overall production efficiency and the economic benefits of enterprises. Therefore, it is necessary to evaluate the health of electrolytic cells. Traditionally, the evaluation of the health of electrolytic cells mainly relies on the subjective experience and intuitive judgment of technicians. This method not only has a strong subjective color, but also often only touches the surface of the problem and is difficult to comprehensively and accurately reveal the actual operating conditions of electrolytic cells.

[0003] As the service time of electrolytic cells accumulates, their performance will gradually degrade, and the cell age has thus become a key factor that cannot be ignored in measuring the health of electrolytic cells. However, currently, the industry lacks effective technical means for predicting the age of electrolytic cells, which directly leads to the passivity and lag in formulating maintenance and replacement strategies for electrolytic cells, further exacerbating the problem of managing the health status of electrolytic cells. Summary of the Invention

[0004] Aiming at the problems existing in the prior art, the present invention provides a method for evaluating the health of an electrolytic cell and a method for evaluating the age of an electrolytic cell. The purpose is to collect key data parameters of electrolytic cells at different life stages, covering several categories of data that affect the operation of electrolytic cells, such as equipment, energy, laboratory tests, materials, and measurements, establish a health management database for electrolytic cells, and combine historical data and expert experience to compare and analyze the key influencing factors affecting the cell life, so as to achieve the determination of cell health, cell life prediction, cell risk and problem warning, and guide the improvement of electrolytic production management. The present invention specifically includes the following content:

[0005] In the first aspect, the present invention protects a method for evaluating the health of an electrolytic cell, including:

[0006] Collect the full-life cycle data of multiple electrolytic cells and establish a health management database for electrolytic cells; in this step, it is preferably to collect data from a sufficient number of electrolytic cells to ensure the universality and integrity of the data in the database;

[0007] Based on the electrolytic cell health management database, an electrolytic cell health assessment model is established;

[0008] Collect data of active electrolytic cells, and predict the health of the active electrolytic cells according to the electrolytic cell health assessment model.

[0009] Furthermore, the full life cycle data of the electrolytic cell includes data in the furnace building stage, baking stage, and production operation stage.

[0010] Furthermore, the data in the furnace building stage includes cell shell cleanliness, thickness of anti-seepage material, type of anti-seepage material, and / or cathode type. Specifically, the data in the furnace building stage can be manually scored based on a set of scoring rules.

[0011] Furthermore, the data in the baking stage includes baking duration, baking current distribution, baking temperature uniformity, baking heating rate, baking voltage change situation, and / or baking quality.

[0012] Furthermore, the data in the production operation stage includes voltage, aluminum level, electrolyte parameters, molecular ratio, cell temperature, and / or operation time.

[0013] Furthermore, the electrolytic cell health assessment model includes a furnace building stage scoring model, a baking stage scoring model, a production operation stage data scoring model, and a total scoring model.

[0014] Furthermore, the method for evaluating the health of the active electrolytic cell according to the electrolytic cell health assessment model is as follows:

[0015] Collect data in the furnace building stage of the active electrolytic cell, and score the active electrolytic cell in the furnace building stage according to the furnace building stage scoring model;

[0016] Collect data in the baking stage of the active electrolytic cell, and score the active electrolytic cell in the baking stage according to the baking stage scoring model;

[0017] Collect data in the production operation stage of the active electrolytic cell, and score the active electrolytic cell in the production operation stage according to the production operation stage scoring model;

[0018] Calculate the total score of the active electrolytic cell according to the scores in the furnace building stage, baking stage, and production operation stage of the active electrolytic cell, and then evaluate the health of the active electrolytic cell according to the total score.

[0019] The second aspect of the present invention protects an electrolytic cell age prediction method, and predicts the age of the electrolytic cell according to the electrolytic cell health assessment result obtained by the method of the present invention.

[0020] Advantages of the present invention:

[0021] (1) The method of the present invention can comprehensively and systematically evaluate the health status of an electrolytic cell by collecting the full-life cycle data of the electrolytic cell (including data in the furnace building stage, baking stage, and production operation stage). Such comprehensive data collection and analysis make the evaluation results more accurate and reliable. Based on the established evaluation model for the health degree of the electrolytic cell, this method can accurately predict the health degree of the in-service electrolytic cell. This not only helps to timely detect potential problems but also provides a scientific basis for the maintenance and management of the electrolytic cell. Through the health degree evaluation, the maintenance plan and overhaul cycle of the electrolytic cell can be arranged more effectively, avoiding unnecessary downtime and maintenance costs. At the same time, it also helps to optimize the production process and improve the overall operation efficiency. Based on data and through model evaluation, the health status of the electrolytic cell is obtained, providing an objective and quantitative basis for decision-makers. This helps to reduce the errors caused by subjective judgment and improve the accuracy and scientific nature of decision-making. Since enough electrolytic cell data is collected to establish a health management database, this method has high universality and integrity and is applicable to different types of electrolytic cells and different production environments. With the continuous accumulation of data, the electrolytic cell health management database and evaluation model can be continuously optimized and improved to adapt to new production conditions and requirements and improve the accuracy and reliability of the evaluation.

[0022] (2) By predicting the cell age of the electrolytic cell through the method of the present invention, the aging signs of the electrolytic cell can be timely detected, and corresponding maintenance and management measures can be taken, thereby prolonging the service life of the electrolytic cell. Accurate cell age prediction helps to reasonably arrange the renewal and replacement plan of the electrolytic cell, avoiding waste of resources and unnecessary investment. At the same time, it can also provide a time reference for the maintenance and overhaul of the electrolytic cell and optimize the resource allocation. Through cell age prediction, the problems of the electrolytic cell that may affect production efficiency can be timely detected and processed, avoiding production interruption and losses caused by electrolytic cell failures. Moreover, through cell age prediction, potential safety problems can be timely detected and processed, reducing safety risks. Specific embodiments

[0023] The present invention will be described in detail below in conjunction with specific embodiments. The embodiments shown below do not limit the content of the invention recorded in the claims in any way. In addition, all the contents of the constitution shown in the following embodiments are not limited to those necessary for the solution of the invention recorded in the claims.

[0024] A method for evaluating the health degree of an electrolytic cell, comprising:

[0025] Collect full life cycle data such as the data in the furnace building stage, baking stage, and production operation stage of multiple electrolytic cells, and establish a health management database for electrolytic cells; in this step, it is preferable that the number of electrolytic cells for data collection is large enough to ensure the universality and integrity of the data in the database; the furnace building stage data includes cell shell cleanliness, thickness of the anti-seepage material, type of anti-seepage material, and / or cathode type; the baking stage data includes baking duration, baking current distribution, baking temperature uniformity, baking heating rate, baking voltage change situation, and / or baking quality; the production operation stage data includes voltage, aluminum level, electrolyte parameters, molecular ratio, cell temperature, and / or operation time;

[0026] Establish a furnace building stage scoring model, a baking stage scoring model, a production operation stage data scoring model, and a total scoring model according to the electrolytic cell health management database;

[0027] Collect the furnace building stage data of the existing electrolytic cells, and score the existing electrolytic cells in the furnace building stage according to the furnace building stage scoring model;

[0028] Collect the baking stage data of the existing electrolytic cells, and score the existing electrolytic cells in the baking stage according to the baking stage scoring model;

[0029] Collect the production operation stage data of the existing electrolytic cells, and score the existing electrolytic cells in the production operation stage according to the production operation stage scoring model;

[0030] Calculate the total score of the existing electrolytic cells according to the scores in the furnace building stage, baking stage, and production operation stage of the existing electrolytic cells, and then evaluate the health degree of the existing electrolytic cells according to the total score.

[0031] The evaluation result of the health degree of the electrolytic cell obtained by the method according to the present invention can accurately predict the cell age of the electrolytic cell, and provide management and operation references for actual production.

[0032] Embodiment 1

[0033] A method for evaluating the health degree of an electrolytic cell, comprising:

[0034] (1) Collect full life cycle data such as the data in the furnace building stage, baking stage, and production operation stage of multiple electrolytic cells, and establish a health management database for electrolytic cells; the furnace building stage data includes cell shell cleanliness, thickness of the anti-seepage material, type of anti-seepage material, and / or cathode type; the baking stage data includes baking duration, baking current distribution, baking temperature uniformity, baking heating rate, baking voltage change situation, baking quality; the production operation stage data includes voltage, aluminum level, electrolyte parameters, molecular ratio, cell temperature, operation time;

[0035] (2) Establish a scoring model for the furnace building stage, a scoring model for the baking stage, a data scoring model for the production operation stage, and an overall scoring model based on the electrolytic cell health management database; in each scoring model, scoring rules such as the proportion of each data situation in the scoring can be specified according to actual needs.

[0036] (3) Collect the furnace building stage data of the in-service electrolytic cells, and score the in-service electrolytic cells in the furnace building stage according to the scoring model for the furnace building stage.

[0037] (4) Collect the baking stage data of the in-service electrolytic cells, and score the in-service electrolytic cells in the baking stage according to the scoring model for the baking stage.

[0038] (5) Collect the production operation stage data of the in-service electrolytic cells, and score the in-service electrolytic cells in the production operation stage according to the scoring model for the production operation stage.

[0039] (6) Calculate the overall score of the in-service electrolytic cells based on the scores of the furnace building stage, baking stage, and production operation stage of the in-service electrolytic cells. Then, evaluate the health of the in-service electrolytic cells according to the overall score, and accurately predict the cell age of the electrolytic cells according to the health, providing management and operation references for actual production.

[0040] Example 2

[0041] An electrolytic cell health evaluation method includes:

[0042] 1. Data collection and database establishment

[0043] Step 1.1: Select a sufficient number of electrolytic cells as samples to ensure that electrolytic cells in different life stages, different operating conditions, and different maintenance histories are covered to ensure the universality and integrity of the data.

[0044] Step 1.2: For each electrolytic cell, starting from the furnace building stage, record the following data in detail:

[0045] Furnace building stage data: including but not limited to the cleanliness of the cell shell (scored on a 0 - 10 scale, 10 points for clean without impurities), the thickness of the anti-seepage material (unit: mm), the type of anti-seepage material (such as ceramic anti-seepage material, refractory bricks, etc.), the type of cathode (such as pre-baked anode cathode, inert cathode, etc.).

[0046] Baking stage data: record the baking duration (unit: hours), the baking current distribution map, the baking temperature uniformity (measured at multiple points by temperature sensors), the baking heating rate (unit: °C / h), the change of baking voltage (record the voltage values at key time points), and the baking quality evaluation (based on the preliminary inspection of the electrolytic cell after baking).

[0047] Data in the production operation stage: Regularly collect voltage (unit: V), aluminum level (unit: cm), electrolyte parameters (such as electrolyte temperature, density, molecular ratio), cell temperature (unit: °C), and cumulative operation time (unit: days).

[0048] Step 1.3: Integrate the above data to establish an electrolytic cell health management database, and store it using a relational database management system (such as MySQL) to ensure data security and accessibility.

[0049] 2. Establish an electrolytic cell health assessment model

[0050] Step 2.1: Based on historical data and expert experience, establish scoring models for the furnace building stage, baking stage, and production operation stage respectively. For example, the scoring model for the furnace building stage can comprehensively calculate the score according to the weights and scoring rules of parameters such as cell shell cleanliness and thickness of the anti-seepage material; similar methods are used for the baking stage and production operation stage, but the weights and scoring criteria need to be adjusted according to the characteristics of each stage.

[0051] Step 2.2: Establish a total scoring model, and add the scores of the three stages according to a certain weight (such as 30% for the furnace building stage, 30% for the baking stage, and 40% for the production operation stage) to obtain the total score of the electrolytic cell.

[0052] Step 2.3: Divide the health level according to the total score, such as excellent (above 90 points), good (75 - 89 points), average (60 - 74 points), poor (below 60 points).

[0053] 3. Assessment of the health of existing electrolytic cells

[0054] Step 3.1: For existing electrolytic cells, collect data for the furnace building stage, baking stage, and production operation stage respectively according to the above data collection method.

[0055] Step 3.2: Input the collected data into the corresponding scoring model to obtain the score of each stage.

[0056] Step 3.3: Calculate the total score according to the total scoring model, and evaluate the health of existing electrolytic cells based on the health level classification standard.

[0057] 4. Implementation of the electrolytic cell age prediction method

[0058] Step 4.1: Based on the established electrolytic cell health assessment model, conduct a health assessment on a batch of existing electrolytic cells to obtain their respective health levels and total scores.

[0059] Step 4.2: Collect the actual age data of these electrolytic cells, that is, the time span from their commissioning to the current assessment moment.

[0060] Step 4.3: Establish a relationship model between the health score and the cell age using statistical methods (such as regression analysis, machine learning algorithms, etc.). For example, a linear regression model can be used, with the total score as the independent variable and the cell age as the dependent variable, to obtain a prediction formula by fitting.

[0061] Step 4.4: For the newly evaluated electrolytic cell, based on its health score, use the above relationship model to predict its possible cell age, or reverse-infer its remaining service life based on the predicted cell age, providing decision support for electrolytic production management.

[0062] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the health of an electrolytic cell, characterized in that, include: Collect the full life cycle data of multiple electrolyzers and establish an electrolyzer health management database; Establishing an electrolytic cell health assessment model based on the electrolytic cell health management database; The data of the electrolytic cells in service are collected, and the health of the electrolytic cells in service is predicted according to the electrolytic cell health assessment model.

2. The method for evaluating the health degree of an electrolytic cell according to claim 1, wherein The full life cycle data of the electrolytic cell includes furnace building stage data, roasting stage data, and production operation stage data.

3. The method for evaluating the health of an electrolytic cell according to claim 2, characterized in that, The furnace construction stage data include tank shell cleanliness, barrier material thickness, barrier material type, and / or cathode type.

4. The method for evaluating the health degree of an electrolytic cell according to claim 2, wherein, The roasting stage data include roasting time, roasting current distribution, roasting temperature uniformity, roasting temperature rise rate, roasting voltage change, and / or roasting quality.

5. The method for evaluating the health of an electrolytic cell according to claim 2, wherein, The production run stage data includes voltage, aluminum level, electrolyte parameters, molecular ratio, bath temperature, and / or run time.

6. The method for evaluating the health of an electrolytic cell according to claim 2, wherein The electrolytic cell health evaluation model includes a furnace building stage scoring model, a roasting stage scoring model, a production operation stage data scoring model, and a total scoring model.

7. The method for evaluating the health degree of an electrolytic cell according to claim 6, characterized in that, The method for evaluating the health of the active electrolytic cell according to the electrolytic cell health evaluation model is: Collecting furnace-building stage data of the active electrolytic cells, and scoring the furnace-building stage of the active electrolytic cells according to the furnace-building stage scoring model; Collecting roasting stage data of the active electrolytic cells, and scoring the roasting stage of the active electrolytic cells according to the roasting stage scoring model; Collecting production and operation stage data of the active electrolytic cells, and scoring the production and operation stage of the active electrolytic cells according to the production and operation stage scoring model; The total score of the active electrolytic cell is calculated based on the furnace building stage score, roasting stage score, and production operation stage score of the active electrolytic cell, and the health of the active electrolytic cell is evaluated based on the total score.

8. A method for predicting the cell age of an electrolytic cell, characterized in that, The electrolytic cell health assessment result obtained according to the method described in any one of claims 1 to 7 predicts the cell age of the electrolytic cell.