Rare earth production control method and system

Abstract

The invention belongs to the technical field of rare earth production, and relates to a rare earth production control method and system. The method comprises the following steps: acquiring control parameter data of a rare earth production process and corresponding rare earth product quality data; optimal rare earth product quality data are screened out, and control parameter data corresponding to the group of rare earth product quality data are obtained and preprocessed to obtain a first control parameter; taking each control parameter in the first control parameters as a control reference parameter of the current production cycle, outputting a plurality of groups of feeding amounts at the next moment through a PID (Proportion Integration Differentiation) control algorithm, and averaging the plurality of groups of feeding amounts at the next moment obtained based on different characteristic quantities of the same control parameter to obtain an average feeding amount; and carrying out weighted average on the average feeding amount corresponding to different control parameters to obtain the final feeding amount at the next moment. According to the method, the feeding amount control parameters are obtained, the rare earth production quality can be effectively improved, and the carbon content and the iron content in the rare earth product are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of rare earth production, and specifically discloses a rare earth production control method and system. Background Art

[0002] Rare earth elements are all lanthanides; however, the atomic radius and chemical properties of the 15 lanthanide elements (atomic numbers 57-71) are extremely similar, with ionic radii varying by only 0.01-0.02 nm. This results in nearly identical solubility and coordination abilities in solvents, making separation difficult via traditional chemical precipitation or simple extraction. Currently, rare earth separation relies primarily on solvent extraction to obtain high-purity rare earth compounds, such as rare earth oxides. With the exception of rare earth elements with high vapor pressures, most rare earth metals and alloys, such as praseodymium and neodymium, require electrolysis of rare earth oxides.

[0003] At present, the production parameters, product process technical indicators and manual experience parameters of traditional rare earth electrolysis plants cannot be organically integrated, and a large amount of production data has not been effectively utilized. The relevant parameters in the production process are still almost controlled based on manual experience. This method that relies on manual experience is not only inefficient, but also has accuracy that needs to be considered.

[0004] How to make good use of existing production data to further improve product quality is an important research direction in rare earth production. Summary of the Invention

[0005] The purpose of the present invention is to provide a rare earth production control method and system to solve the problem that the traditional method relies on manual experience to adjust and improve product quality, which is low in efficiency and unsatisfactory in effect. The specific scheme is as follows:

[0006] In a first aspect, a rare earth production control method is provided, comprising the following steps:

[0007] Obtain control parameter data of the rare earth production process and corresponding rare earth product quality data;

[0008] Filtering out the best rare earth product quality data, and obtaining control parameter data corresponding to the set of rare earth product quality data for preprocessing to obtain a first control parameter;

[0009] Using one of the first control parameters as a control reference parameter for the current production cycle, and outputting the feeding amount at the next moment through a PID control algorithm, repeating the process until a set of feeding amount data at the next moment is obtained based on each of the first control parameters;

[0010] The average feeding amount is obtained by averaging multiple groups of next moment feeding amounts obtained based on different characteristic quantities of the same control parameter; and the weighted average of the average feeding amounts corresponding to different control parameters is then used to obtain the final next moment feeding amount.

[0011] Furthermore, the control parameter data includes current data, temperature data and feeding amount data; wherein the current data, temperature data and feeding amount data are all time series data representing parameter changes during the production process;

[0012] The rare earth product quality data includes but is not limited to elemental carbon content data and iron content data.

[0013] Furthermore, the above-mentioned screening out of the best rare earth product quality data is specifically as follows:

[0014] Determine the optimal quality data of rare earth products based on the elemental carbon content data and iron content data of rare earth products; including:

[0015] Taking the element carbon content data less than a first threshold and the iron content data less than a second threshold as constraint conditions, obtaining rare earth product quality data that meets the constraint conditions;

[0016] If there is only one set of rare earth product quality data that meets the constraint condition, then this set of rare earth product quality data is used as the optimal rare earth product quality data;

[0017] If there is no rare earth product quality data that meets the constraint conditions or there are multiple sets of rare earth product quality data that meet the constraint conditions, the quality evaluation coefficient is obtained based on the preset weight, and the rare earth product quality data corresponding to the quality evaluation coefficient with the smallest value is used as the optimal rare earth product quality data.

[0018] Furthermore, the quality evaluation coefficient is obtained based on the preset weight, specifically as follows:

[0019] q=αcon C +βcon Fe

[0020] Among them, q represents the quality evaluation coefficient, α represents the weight of element carbon, and con C represents the carbon content, β represents the weight of iron, and con Fe represents the iron content; and α+β=1, α>β.

[0021] Furthermore, the control parameter data corresponding to the set of rare earth product quality data is obtained and preprocessed, specifically:

[0022] Based on the current time series data corresponding to the optimal rare earth product quality data, the peak current, valley current, average current and mean current are obtained;

[0023] Based on the temperature time series data corresponding to the optimal rare earth product quality data, the peak temperature, valley temperature, average temperature and mean temperature are obtained;

[0024] Based on the time series data of the feeding amount corresponding to the optimal rare earth product quality data, the peak feeding amount, the valley feeding amount, the average feeding amount and the average feeding amount are obtained;

[0025] The first control parameters include peak current, valley current, average current, average current, peak temperature, valley temperature, average temperature, average temperature, peak feeding amount, valley feeding amount, average feeding amount and average feeding amount.

[0026] Furthermore, one of the first control parameters is used as the control reference parameter of the current production cycle, and the feeding amount at the next moment is output through the PID control algorithm, specifically:

[0027] When the control reference parameter is current or temperature data, the control amount of the reference parameter is obtained through the PID control method; the control amount of the reference parameter is then converted into the feeding control amount through linear mapping conversion, and the feeding amount at the next moment is obtained based on the planned feeding amount at the next moment and the feeding control amount;

[0028] When the control reference parameter is the feeding amount data, the control amount of the reference parameter is obtained by the PID control method; and then the feeding amount at the next moment is obtained based on the control reference parameter and the control amount of the reference parameter.

[0029] Furthermore, the average feeding amount is obtained by averaging multiple groups of feeding amounts at the next moment obtained based on different characteristic quantities of the same control parameter, specifically:

[0030] Obtaining a first average feeding amount based on four sets of feeding amounts at the next moment obtained when the peak current, the valley current, the average current, and the average current are used as control reference parameters respectively;

[0031] Obtaining a second average feeding amount based on four sets of feeding amounts at the next moment obtained when the peak temperature, the valley temperature, the average temperature, and the mean temperature are used as control reference parameters respectively;

[0032] A third average feeding amount is obtained based on four groups of feeding amounts at the next moment obtained when the peak feeding amount, the valley feeding amount, the average feeding amount and the average feeding amount are respectively used as control reference parameters.

[0033] Furthermore, the weighted average of the average feeding amounts corresponding to different control parameters is used to obtain the final feeding amount at the next moment, which is specifically as follows:

[0034] Q t+1 =w1Q I +w2Q T+w3Q Q

[0035] Among them, Q t+1 represents the final feed rate at the next moment, w1 represents the weight of the first average feed rate Q I of, w2 represents the weight of the second average feed rate Q T of, and w3 represents the weight of the third average feed rate Q Q of; and w1 + w2 + w3 = 1.

[0036] Furthermore, when the purity of rare earth products is taken as the control target, w1 < w2; when the production efficiency or morphology control of rare earth products is taken as the control target, w1 > w2.

[0037] In a second aspect, a rare earth production control system is provided, including a data storage server and a control center, and the data storage server is communicatively connected to the control center;

[0038] The data storage server is used to collect and store the production data of each production unit in the rare earth electrolysis plant;

[0039] The control center is used to obtain the production data in the data storage server and execute the rare earth production control method as described above.

[0040] The beneficial effects of the present invention are as follows:

[0041] Based on the existing production data records, the present invention screens out the production process control data with the best rare earth quality; then uses the screened production process control data as the reference parameters to output the parameter control at the next moment by adopting the PID control method; and converts all the parameter controls at the next moment into the feed rate control parameters through the mapping relationship, and then obtains the final feed rate at the next moment through the processing of multiple groups of feed rate control parameters; this method obtains the feed rate control parameters, which can effectively improve the quality of rare earth production and reduce the carbon content and iron content in rare earth products. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic flow chart of the rare earth production control method provided by the present invention. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown here can be arranged and designed in various different configurations.

[0044] At present, the production parameters, product process technical indicators and manual experience parameters of traditional rare earth electrolysis plants cannot be organically integrated, and a large amount of production data has not been effectively utilized. The relevant parameters in the production process are still almost controlled based on manual experience. This method that relies on manual experience is not only inefficient, but also has accuracy that needs to be considered.

[0045] Based on the problems existing in the above-mentioned traditional rare earth production process, the present invention hopes to provide the following solutions to solve some of the problems.

[0046] Example 1

[0047] This embodiment describes a rare earth production control system comprising a data storage server and a control center in communication with each other. The data storage server is used to collect and store production data from each production unit in a rare earth electrolysis plant; the control center is used to obtain the production data from the data storage server and, based on the obtained production data, to control the parameters of the current rare earth production process, thereby improving the quality of rare earth production and reducing the carbon and iron content of the rare earth products.

[0048] Since the production data of each production unit in the current traditional rare earth electrolysis plant are independent, there are data islands in the production and manufacturing, and the equipment monitoring methods are backward; it is difficult to integrate and use the relevant production data to maximize its value. In this embodiment, by adopting the design of the industrial Internet of Things, the sensor installation of each production unit is unified to realize the Internet of Things and data collection of each production unit equipment; specifically, the data collected by the sensor can be transmitted to the data storage server through communication protocols such as Modbus-TCP or Modbus-ASCII, and the data storage server can adopt OPC (OLE for Process Control, OLE for process control) server. OPC server is a standard interface software based on the field of industrial automation, which is used to realize data interaction and sharing between equipment and systems of different manufacturers. It is a key component for realizing data intercommunication in the field of industrial automation, and solves the problem of equipment integration through standardized interfaces.

[0049] The control center integrates a method for filtering data from the data storage server. Using a PID algorithm, the filtered data provides a basis for determining control parameters for current production, thereby improving the quality of rare earth production. For details on the specific data processing and control methods integrated into the control center, please refer to the solution in Example 2. It should be further explained that the control center is composed of one or more computers, and its operation primarily relies on software systems that can run on the computer hardware.

[0050] Example 2

[0051] This embodiment provides a rare earth production control method, such as Figure 1 As shown; including the following steps:

[0052] Obtain control parameter data for the rare earth production process and corresponding rare earth product quality data. In this embodiment, the control parameter data includes current data, temperature data, and feed rate data; these data are all time-series data representing parameter changes during the production process. It should be noted that the control parameter data may also include voltage data. Because current and voltage data are strongly correlated in steady state, this embodiment only includes current data to save subsequent processing workload. If voltage data is added, the processing flow is the same as the data processing described later in this embodiment. Regarding time-series data, the relevant parameters in this embodiment are composed of data continuously collected by the corresponding sensors in each production unit according to a certain data collection cycle. The collection cycle can be once per second, or different collection cycles can be set according to different stages of rare earth electrolysis. For example, in the early stages of electrolysis, when changes are relatively rapid, data collection can be set to every 100-500 ms, while in the stage where electrolysis tends to stabilize, data collection can be set to every 1-5 seconds. The specific setting method can be determined based on the actual conditions of the electrolysis site.

[0053] Rare earth product quality data includes data on elemental carbon content, iron content, calcium content, and magnesium content. Since elemental carbon and iron impurities in rare earth products are the two most important indicators of product quality, in this embodiment, rare earth product quality data is represented by carbon content and iron content. For example, the national standard for praseodymium-neodymium metal products is that the elemental carbon content is less than or equal to 300ppm, and the iron content is less than or equal to 3000ppm, which is considered a Class I qualified product. In production, as long as other impurity elements meet the national standards, the lower the elemental carbon and iron content, the higher the quality of the rare earth product.

[0054] The aforementioned control parameter data is collected by corresponding sensors and stored in a data storage server. Rare earth product quality data is acquired through quality testing of a batch of finished products within a production cycle. In other words, each set of rare earth product quality data corresponds to a period of continuous control parameter data. It will be appreciated that the acquired rare earth product quality data is also stored in the data storage server. In the method disclosed in this embodiment, the control center acquires the aforementioned data from the data storage server.

[0055] The control center obtains control parameter data and rare earth product quality data from multiple production cycles and selects the optimal rare earth product quality data. Specifically, the optimal rare earth product quality data is determined based on the elemental carbon content data and iron content data of the rare earth product. This includes:

[0056] Evaluate multiple sets of rare earth product quality data; obtain rare earth product quality data that meets the constraints, with the elemental carbon content data being less than a first threshold and the iron content data being less than a second threshold. As previously mentioned, the national standard defines a Class I product as one with an elemental carbon content of 300 ppm or less and an iron content of 3000 ppm or less. Based on production requirements, the first threshold is generally set at 200 ppm, and the second threshold at 1500 ppm. It should be noted that the first and second thresholds can be set lower depending on the quality requirements for rare earth products.

[0057] If there is only one set of rare earth product quality data that meets the above constraints (i.e., the rare earth product quality data obtained in only one production cycle meets the constraints), then this set of rare earth product quality data will be used as the optimal rare earth product quality data.

[0058] If there is no rare earth product quality data that meets the constraint conditions or there are multiple sets of rare earth product quality data that meet the constraint conditions, the quality evaluation coefficient is obtained based on the preset weight, because the higher the quality of the rare earth product, the lower the elemental carbon content and iron content; therefore, the rare earth product quality data corresponding to the quality evaluation coefficient with the smallest value is used as the optimal rare earth product quality data.

[0059] The quality evaluation coefficient is obtained as follows:

[0060] q=αcon C +βcon Fe

[0061] Among them, q represents the quality evaluation coefficient, α represents the weight of element carbon, and con C represents the carbon content, β represents the weight of iron, and con Fe represents the iron content; and α+β=1, α>β.

[0062] Normally, the value range of α is 0.51-0.99, and the value range of β is 0.01-0.49. Regarding the weight setting of elemental carbon and iron, it is mainly because the hard and brittle phase formed by carbon and praseodymium-neodymium metal is difficult to eliminate through subsequent processes, and the damage to magnetic properties and processing performance is irreversible; and iron, as a metallic impurity, can be further effectively controlled through purification processes, and its effect on material properties is relatively mild; therefore, α>β.

[0063] After the optimal rare earth product quality data is selected through the above steps, the control parameter data corresponding to the group of rare earth product quality data is obtained and preprocessed to obtain the first control parameter.

[0064] Based on the current time series data corresponding to the optimal rare earth product quality data, the peak current, valley current, average current and mean current are obtained; based on the temperature time series data corresponding to the optimal rare earth product quality data, the peak temperature, valley temperature, average temperature and mean temperature are obtained; based on the feeding amount time series data corresponding to the optimal rare earth product quality data, the peak feeding amount, valley feeding amount, average feeding amount and mean feeding amount are obtained. It can be understood that the above-mentioned peak data is the data with the largest median value in the corresponding time series data; the valley data is the data with the smallest median value in the corresponding time series data; the mean data refers to the average value of all data values ​​in the corresponding time series data; and the average data refers to the value corresponding to the median of all data values ​​in the corresponding time series data. It should be noted that the feeding amount refers to the feeding amount per unit time, such as the mass of feeding per second.

[0065] The first control parameter includes the above-mentioned peak current, valley current, average current, average current, peak temperature, valley temperature, average temperature, average temperature, peak feeding amount, valley feeding amount, average feeding amount and average feeding amount.

[0066] Then, one of the first control parameters is used as the control reference parameter of the current production cycle, and the feeding amount at the next moment is output through the PID control algorithm. Specifically:

[0067] When the control reference parameter is current or temperature data, the PID control method is used to obtain the control variable of the reference parameter. This control variable is then converted to the feed control variable through linear mapping, such as: Q(t) = Q0 + k·u(t), where Q0 is the reference feed quantity, k is the conversion factor (which needs to be adjusted according to the equipment range), and u(t) is the control variable output by the PID algorithm when the current or temperature data is used as the reference parameter. The feed quantity at the next moment is then determined based on the planned feed quantity and the feed control variable. This conversion into control of the feed quantity facilitates subsequent data processing.

[0068] When the control reference parameter is the feeding amount data, the control amount of the reference parameter is obtained by the PID control method; and then the feeding amount at the next moment is obtained based on the control reference parameter and the control amount of the reference parameter.

[0069] It should be noted that the above-mentioned PID control algorithm is relatively mature. For details, please refer to the description of the PID control algorithm process in Chinese invention patent ZL202110968477.9. The difference here mainly lies in the difference in the benchmark parameters.

[0070] Repeat the above method of obtaining the feeding amount at the next moment until a set of feeding amount data at the next moment is obtained based on each control parameter in the first control parameter; that is, the peak current, valley current, average current, average current, peak temperature, valley temperature, average temperature, average temperature, peak feeding amount, valley feeding amount, average feeding amount and average feeding amount in the first control parameter are all obtained through the above method to obtain a set of feeding amount data at the next moment.

[0071] Then, the average feeding amount is obtained by averaging multiple groups of feeding amounts at the next moment obtained based on different characteristic quantities of the same control parameter, specifically:

[0072] The first average feeding amount is obtained based on the four sets of feeding amounts at the next moment obtained when the peak current, valley current, flat current and average current are used as control reference parameters respectively; that is, the first average feeding amount is obtained based on current-related data.

[0073] The second average feeding amount is obtained based on the four sets of feeding amounts at the next moment obtained when the peak temperature, valley temperature, average temperature and mean temperature are used as control reference parameters; that is, the second average feeding amount is obtained based on temperature-related data.

[0074] The third average feeding amount is obtained based on the four sets of feeding amounts at the next moment obtained when the peak feeding amount, the valley feeding amount, the average feeding amount, and the average feeding amount are used as control reference parameters. That is, the third average feeding amount is obtained based on the data related to the feeding amount.

[0075] Finally, the weighted average of the average feeding amount corresponding to different control parameters is used to obtain the final feeding amount at the next moment. The specific formula is as follows:

[0076] Q t+1 =w1Q I +w2Q T +w3Q Q

[0077] Among them, Q t+1 Indicates the final feeding amount at the next moment, w1 indicates the first average feeding amount Q I The weight of w2 represents the second average feeding amount Q t The weight of w3 represents the third average feeding amount Q Q weight; and w1+w2+w3=1.

[0078] When the purity of rare earth products is taken as the control target, temperature control is more critical because the volatilization loss and impurity introduction caused by high temperature are difficult to eliminate through subsequent processing. Therefore, in this case, w1 < w2; in this case, w1 takes the value of 0.3, w2 takes the value of 0.4, and w3 takes the value of 0.3. When the production efficiency or morphology control of rare earth products is taken as the control target, the precise regulation of current is more important, which can effectively avoid crystallization defects or side reactions caused by improper current. Therefore, in this case, w1 > w2; in this case, w1 takes the value of 0.4, w2 takes the value of 0.3, and w3 takes the value of 0.3.

[0079] Based on the above embodiments, it can be seen that based on the existing production data records, the production process control data with the best rare earth quality is screened out; then, the screened production process control data is used as the reference parameters to output the parameter control for the next moment by adopting the PID control method; and all the parameter controls for the next moment are converted into the feed rate control parameters through the mapping relationship, and then through the processing of multiple groups of feed rate control parameters, the final feed rate for the next moment is obtained. This method can effectively improve the quality of rare earth production and reduce the carbon and iron contents in rare earth products.

[0080] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A rare earth production control method, characterized in that: The following steps are involved: Obtain control parameter data of the rare earth production process and corresponding rare earth product quality data; Filtering out the best rare earth product quality data, and obtaining control parameter data corresponding to the set of rare earth product quality data for preprocessing to obtain a first control parameter; Using one of the first control parameters as a control reference parameter for the current production cycle, and outputting the feeding amount at the next moment through a PID control algorithm, repeating the process until a set of feeding amount data at the next moment is obtained based on each of the first control parameters; The average feeding amount is obtained by averaging multiple groups of next moment feeding amounts obtained based on different characteristic quantities of the same control parameter; and the weighted average of the average feeding amounts corresponding to different control parameters is then used to obtain the final next moment feeding amount.

2. The rare earth production control method according to claim 1, characterized in that: The control parameter data includes current data, temperature data and feeding amount data; wherein the current data, temperature data and feeding amount data are all time series data representing parameter changes during the production process; The rare earth product quality data includes but is not limited to elemental carbon content data and iron content data.

3. The rare earth production control method according to claim 2, characterized in that: The above-mentioned screening out of the best rare earth product quality data is specifically as follows: Determine the optimal quality data of rare earth products based on the elemental carbon content data and iron content data of rare earth products; including: Taking the element carbon content data less than a first threshold and the iron content data less than a second threshold as constraint conditions, obtaining rare earth product quality data that meets the constraint conditions; If there is only one set of rare earth product quality data that meets the constraint condition, then this set of rare earth product quality data is used as the optimal rare earth product quality data; If there is no rare earth product quality data that meets the constraint conditions or there are multiple sets of rare earth product quality data that meet the constraint conditions, the quality evaluation coefficient is obtained based on the preset weight, and the rare earth product quality data corresponding to the quality evaluation coefficient with the smallest value is used as the optimal rare earth product quality data.

4. The rare earth production control method according to claim 3, wherein: The quality evaluation coefficient is obtained based on the preset weight, specifically as follows: q=αcon C +βcon Fe Among them, q represents the quality evaluation coefficient, α represents the weight of element carbon, and con C represents the carbon content, β represents the weight of iron, and con Fe represents the iron content; and α+β=1, α>β.

5. The rare earth production control method according to claim 2, wherein: The obtaining of the control parameter data corresponding to the set of rare earth product quality data and preprocessing is specifically as follows: Based on the current time series data corresponding to the optimal rare earth product quality data, the peak current, valley current, average current and mean current are obtained; Based on the temperature time series data corresponding to the optimal rare earth product quality data, the peak temperature, valley temperature, average temperature and mean temperature are obtained; Based on the time series data of the feeding amount corresponding to the optimal rare earth product quality data, the peak feeding amount, the valley feeding amount, the average feeding amount and the average feeding amount are obtained; The first control parameters include peak current, valley current, average current, average current, peak temperature, valley temperature, average temperature, average temperature, peak feeding amount, valley feeding amount, average feeding amount and average feeding amount.

6. The rare earth production control method according to claim 5, characterized in that: The method uses one of the first control parameters as the control reference parameter of the current production cycle, and outputs the feeding amount at the next moment through the PID control algorithm, specifically: When the control reference parameter is current or temperature data, the control quantity of the reference parameter is obtained by the PID control method; then the control quantity of the reference parameter is converted into the feeding control quantity through linear mapping conversion, and the feeding quantity at the next moment is obtained based on the planned feeding quantity and the feeding control quantity at the next moment. When the control reference parameter is the feeding quantity data, the control quantity of the reference parameter is obtained by the PID control method; then the feeding quantity at the next moment is obtained based on the control reference parameter and the control quantity of the reference parameter.

7. The rare earth production control method according to claim 6, characterized in that: The average feeding quantity is obtained by averaging multiple groups of feeding quantities at the next moment obtained from different characteristic quantities based on the same control parameter. Specifically: Based on four groups of feeding quantities at the next moment obtained when the peak current, valley current, flat current, and average current are used as the control reference parameter respectively, the first average feeding quantity is obtained. Based on four groups of feeding quantities at the next moment obtained when the peak temperature, valley temperature, flat temperature, and average temperature are used as the control reference parameter respectively, the second average feeding quantity is obtained. Based on four groups of feeding quantities at the next moment obtained when the peak feeding quantity, valley feeding quantity, flat feeding quantity, and average feeding quantity are used as the control reference parameter respectively, the third average feeding quantity is obtained.

8. The rare earth production control method according to claim 7, characterized in that: The weighted average of the average feeding quantities corresponding to different control parameters is performed to obtain the final feeding quantity at the next moment, as shown in the following formula: Q t+1 =w1Q I +w2Q T +w3Q Q Among them, Q t+1 Indicates the final feeding amount at the next moment, w1 indicates the first average feeding amount Q I The weight of w2 represents the second average feeding amount Q T The weight of w3 represents the third average feeding amount Q Q weight; and w1+w2+w3=1.

9. The rare earth production control method according to claim 8, characterized in that: When the purity of rare earth products is the control target, w1 < w2; when the production efficiency or morphology control of rare earth products is the control target, w1 > w2.

10. A rare earth production control system, characterized in that: It includes a data storage server and a control center, and the data storage server is communicatively connected to the control center; The data storage server is used to collect and store the production data of each production unit in the rare earth electrolysis plant; The control center is used to obtain the production data in the data storage server and execute the rare earth production control method according to any one of claims 1-9.

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