Automatic phosphine production method and device based on parallel reaction kettles

Abstract

The invention provides a phosphine automatic production method and device based on parallel reaction kettles, and relates to the technical field of phosphine preparation, and the phosphine automatic production method comprises the following steps: obtaining feeding proportions of different materials for producing phosphine and production plans of different reaction kettles; aiming at any reaction kettle, determining the feeding amount of each material in the reaction kettle according to the feeding proportion of different materials and the total feeding amount of the reaction kettle; controlling a feeding assembly to feed the materials into the reaction kettle and controlling a stirring assembly to stir the materials in the reaction kettle according to the feeding amount, feeding control parameters and operation control parameters of the materials in the reaction kettle, so that different materials react to generate hydrogen phosphide; monitoring real-time environment data in the reaction kettle; and according to the real-time environment data, adjusting the feeding control parameters and the operation control parameters to control the reaction of different materials until the reaction of the different materials is completed. According to the invention, the production process of phosphine can be automatically and intelligently controlled, and accurate control of feeding and operation in the reaction kettle is realized.

Description

Technical Field

[0001] This application relates to the technical field of phosphine preparation, and more specifically, to an automated method and apparatus for phosphine production based on parallel reactors. Background Technology

[0002] Phosphine is a colorless, flammable, and highly toxic gaseous compound. It is an important N-type dopant source in semiconductor device manufacturing and is also used in polycrystalline silicon chemical vapor deposition, epitaxial GaP materials, ion implantation processes, and MOCVD processes. Current phosphine production typically employs manual or semi-automatic control methods, making fully automated phosphine production impossible. Furthermore, temperature and pressure control is unstable, resulting in low production efficiency. Summary of the Invention

[0003] The purpose of this application is to provide an automated phosphine production method and apparatus based on parallel reactors, which solves the above-mentioned problems existing in the prior art, and can automatically and intelligently control the phosphine production process, and realize precise control of feeding and operation in the reactor.

[0004] Firstly, an automated phosphine production method based on parallel reactors is provided, applied to the controller of a parallel reactor control system. The parallel reactor control system further includes: multiple reactors connected in parallel, and a feeding assembly and a stirring assembly installed on each reactor. The method may include: Obtain the feeding ratios of different materials used in the production of phosphine, as well as the production plans for different reactors; wherein, the production plans for different reactors include: the total feed amount, feed control parameters, and operating control parameters for different reactors; For any given reactor, the amount of each material to be added to the reactor is determined based on the proportion of the different materials added and the total amount of material added to the reactor. Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, the feeding component is controlled to add materials to the reactor, and the stirring component is controlled to stir the materials in the reactor so that different materials react to generate phosphine; and real-time environmental data in the reactor is monitored. Based on the real-time environmental data, the feeding control parameters and the operation control parameters are adjusted to control the reaction of different materials until the reaction of different materials is completed.

[0005] In an optional implementation, the feeding ratio of different materials is obtained by inputting the chemical parameters of different materials into a pre-trained feeding ratio prediction model; The different materials include: liquid yellow phosphorus, lime milk, and sodium hydroxide solution; The chemical parameter of the lime slurry is the lime slurry dispersion; the chemical parameter of the sodium hydroxide solution is the sodium hydroxide concentration.

[0006] In an optional implementation, the feeding ratio prediction model includes: an input layer, a feature extraction layer, a first hidden layer, a second hidden layer, and an output layer; The input layer is used to standardize the input lime milk dispersion and sodium hydroxide concentration; The feature extraction layer is used to perform feature cross processing on the standardized lime milk dispersion and sodium hydroxide concentration to obtain a multi-dimensional feature vector. The first hidden layer is used to learn the low-order nonlinear relationship between multidimensional feature vectors and obtain low-order feature vectors. The second hidden layer is used to learn the higher-order coupling relationship of the lower-order feature vectors to obtain higher-order feature vectors; The output layer is used to map high-order feature vectors to the range of feeding parameters to obtain the feeding ratio of lime slurry and sodium hydroxide solution.

[0007] In an optional implementation, the method for obtaining the production plans of the different reactors includes: To obtain the target production capacity of phosphine, the chemical parameters of different materials, and the initial environmental data in different reactors; The target production volume, the proportion of different materials added, and the initial environmental data in different reactors are input into a pre-constructed dynamic model of parallel reactors to obtain the production plan for each reactor.

[0008] In an optional implementation, the parallel reactor control system further includes: a feeding metering component, an environmental monitoring component, and a temperature control component installed on each reactor; Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, the feeding component is controlled to add materials to the reactor, and the stirring component is controlled to stir the materials in the reactor, including: Based on the amount of each material added to the reactor and the feeding control parameters, the feeding component is controlled to add materials to the reactor, and the feeding metering component is controlled to monitor the amount of materials added, and the environmental monitoring component is controlled to monitor the real-time environmental data inside the reactor. According to the operation control parameters, the stirring assembly is controlled to stir the materials in the reactor, and the temperature control assembly is controlled to adjust the temperature in the reactor.

[0009] In an optional implementation, adjusting the feeding control parameters and the operation control parameters based on the real-time environmental data includes: Calculate the risk index based on the real-time environmental data; Based on the risk index, adjust the feeding control parameters and the operation control parameters to obtain new feeding control parameters and new operation control parameters, and return to the execution steps: based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, control the feeding component to add materials to the reactor and control the stirring component to stir the materials in the reactor until the different materials have reacted completely.

[0010] In an optional implementation, adjusting the feeding control parameters and the operation control parameters according to the risk index includes: Obtain risk thresholds for different stages of phosphine production; Based on the comparison between the risk index and the risk threshold, the risk level of the current phosphine production stage is determined; Based on the different adjustment rules corresponding to different production stages and different risk levels, determine the target adjustment rule corresponding to the risk level of the current phosphine production stage; According to the target adjustment rules, the feeding control parameters and operation control parameters are adjusted to allow different materials to continue reacting.

[0011] Secondly, an automated phosphine production device based on parallel reactors is provided, applied to the controller of a parallel reactor control system. The parallel reactor control system further includes: multiple reactors connected in parallel, and a feeding assembly and a stirring assembly installed on each reactor. The device may include: The acquisition unit is used to acquire the feeding ratio of different materials used in the production of phosphine, as well as the production plans of different reactors; wherein, the production plans of different reactors include: the total feeding amount of different reactors, feeding control parameters and operating control parameters; A determining unit is used to determine the amount of each material in any reactor based on the proportion of different materials added and the total amount of material added to the reactor. The control unit is used to control the feeding component to feed materials into the reactor and control the stirring component to stir the materials in the reactor according to the amount of each material fed into the reactor, the feeding control parameters and the operation control parameters, so that different materials react to generate phosphine; and to monitor the real-time environmental data in the reactor. The adjustment unit is used to adjust the feeding control parameters and the operation control parameters according to the real-time environmental data, so as to control the reaction of different materials until the reaction of different materials is completed.

[0012] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.

[0013] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.

[0014] This application solves the pain points of traditional processes, such as high human error, unstable reaction conditions, significant safety hazards, and substantial resource waste, through automated interlocking control, phased feeding and operation adjustment, and precise material management, thereby achieving efficient, safe, and environmentally friendly continuous production. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A parallel reactor control system is provided as an embodiment of this application; Figure 2 A schematic diagram of a phosphine automated production method based on parallel reactors provided in this application embodiment; Figure 3 A schematic diagram of the structure of an automated phosphine production device based on parallel reactors provided in this application embodiment; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by those skilled in the art. The words "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are only used to distinguish different components. The words "comprising" or "including," etc., mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but do not exclude other elements or objects. The words "connected," "coupled," or "connected," etc., are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] The automated phosphine production based on parallel reactors provided in this application embodiment can be applied to... Figure 1 In the system architecture shown, such as Figure 1 As shown, the parallel reactor control system may include: a controller, multiple reactors connected in parallel, and an environmental monitoring component, a feeding component, and a stirring component installed on each reactor; the controller is connected to the environmental monitoring component, the feeding component, and the stirring component respectively; The controller is used to execute the automated phosphine production method based on parallel reactors provided in the embodiments of this application, and to issue corresponding control parameters to the environmental monitoring component, the feeding component and the stirring component; The environmental monitoring components include: a temperature sensor, a pressure sensor, an oxygen content sensor, an exhaust gas sensor, and a laser Doppler velocimeter; used to monitor environmental data within the corresponding reactor; the environmental data includes: temperature, pressure, oxygen content, exhaust gas, and flow field uniformity; the temperature and pressure sensors can employ a high-temperature, high-pressure sensor array based on sapphire fiber (withstanding temperatures ≥150℃ and pressures ≥1.0MPa) to achieve distributed synchronous monitoring (sampling frequency ≥2kHz) of temperature (error ±0.05℃) and pressure (error ±0.005MPa) in different regions within the reactor (top gas phase / middle mixed phase / bottom precipitate phase); The feeding components include: a first feeding component, a second feeding component, a third feeding component, and a fourth feeding component; the first feeding component, the second feeding component, the third feeding component, and the fourth feeding component are respectively used to feed lime milk, pure water, liquid yellow phosphorus, and sodium hydroxide solution into the reactor according to the received feeding control parameters; The stirring assembly is used to stir the temperature inside the reactor according to the operation control parameters received from the controller; specifically, the stirring assembly is a double helix stirring assembly; its stirring shaft speed (50-500 rpm) and impeller tilt angle (30°-60°) can be adjusted independently; In another embodiment of this application, the system may further include: a feeding and metering component connected to a controller, the feeding and metering component being used to monitor the amount of material added into the reactor; when the feeding and metering component detects that the amount of any material added has met the amount of the corresponding material in the feeding control parameters, it sends a feeding completion signal to the controller, and the controller controls the feeding component of the corresponding material to shut down after receiving the feeding completion signal; or, each feeding component corresponds to a feeding control component, used to control the rate and amount of material added by the corresponding feeding component; a third feeding component. The feeding control component can be an electromagnetic reversing valve; the electromagnetic reversing valve controls the intermittent opening or closing frequency (unit: times / minute) of the third feeding component, and controls the total feeding amount per unit time (total feeding amount = pulse frequency × single feeding amount) by controlling the configured single feeding amount (fixed to a preset value, such as 5g / time); when the feeding metering component detects that the feeding amount of any material has met the feeding amount of the corresponding material in the feeding control parameters, it directly sends a feeding completion signal to the feeding control component of the corresponding material, so that the feeding control component of the corresponding material will no longer feed the corresponding material into the reactor.

[0019] In another embodiment of this application, the reactor is encased in a coil or jacket. The system may further include a temperature control component and an inert gas purging component. The temperature control component includes a heating component and a cooling component. The heating component and the cooling component are respectively connected to a controller and are used to receive temperature control parameters issued by the controller and control the temperature inside the reactor according to the received temperature control parameters. Specifically, the heating component may include a steam chamber, a steam control valve, and a steam channel communicating with the coil or jacket. The steam control valve is used to introduce steam from the steam chamber into the coil or jacket through the steam channel based on the received operating control parameters issued by the controller, so as to raise the temperature inside the reactor. The cooling component may include a cooling water control valve and a cooling water channel communicating with the coil or jacket. The cooling water control valve is used to introduce cooling water into the coil or jacket through the cooling water channel based on the received operating control parameters issued by the controller, so as to lower the temperature inside the reactor. The inert gas purging component is used to introduce an inert gas (e.g., nitrogen) into the reactor to create a vacuum environment inside the reactor.

[0020] In other embodiments of this application, a microchannel heat exchange component is provided outside the medium-temperature zone and the low-temperature zone of the reactor; the microchannel heat exchange component is used to heat the medium-temperature zone and the low-temperature zone of the reactor according to the operation control parameters sent by the controller, so as to make the temperature inside the reactor uniform; the medium-temperature zone and the low-temperature zone are determined based on human experience.

[0021] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0022] Figure 2 This is a schematic flow diagram of an automated phosphine production method based on parallel reactors, provided as an embodiment of this application. Figure 2 As shown, the method may include: Step S210: Obtain the proportions of different materials used in the production of phosphine, as well as the production plans for different reactors.

[0023] The feeding ratios of different materials were obtained by inputting their chemical parameters into a pre-trained feeding ratio prediction model. These materials included liquid yellow phosphorus, lime slurry, and sodium hydroxide solution. The chemical parameters of lime slurry included density, specific heat capacity, reactivity, and dispersibility. Dispersibility was measured using an online ultrasonic dispersibility monitor. The chemical parameters of sodium hydroxide solution included density, specific heat capacity, reactivity, and sodium hydroxide concentration, which was detected using a density sensor. Liquid yellow phosphorus, due to its stable industrial state (small fluctuations in purity and temperature), was treated as a fixed process constant by default. No input is required; the training data for the feed ratio prediction model comes from actual production processes or related experiments, requiring at least 500 hours of multi-condition operation data; the training data includes the chemical parameters of each material under different operating conditions, as well as the corresponding reaction result data (such as the yield and purity of phosphine) and the final feed ratio, etc.; through this data, the feed ratio prediction model learns the mapping relationship between "dispersion degree - alkali concentration" and their correlation with the ideal feed ratio, so that it can output appropriate feed control parameters based on the real-time input parameters in actual operation to achieve stable control of the reaction process.

[0024] Specifically, the feed ratio prediction model includes: an input layer, a feature extraction layer, a first hidden layer, a second hidden layer, and an output layer. The input layer is used to standardize the chemical parameters of different input materials. Specifically, the standardization process includes mapping the chemical parameters of different input materials to the [0,1] interval (e.g., lime milk dispersion D∈[50,200μm]→[0,1], sodium hydroxide concentration C∈[5,15mol / L]→[0,1]). The feature extraction layer is used to perform feature cross-processing on the standardized chemical parameters to obtain a multi-dimensional feature vector. The feature vector includes: a first feature vector reflecting the synergistic effect of material dispersion uniformity and alkali concentration, which is the product of sodium hydroxide concentration and lime milk dispersion; a second feature vector reflecting the effect of nonlinear changes in one parameter on another, which is the product of the square of sodium hydroxide concentration and lime milk dispersion; and a second feature vector representing the square of the phosphorus pulse frequency and the product of hydrogen and oxygen. The product of sodium hydroxide concentrations; a third feature vector reflecting the matching degree between contact efficiency and reactivity, the third feature vector being the ratio of lime slurry dispersion to sodium hydroxide concentration; a fourth feature vector reflecting the ability of quantitative dispersion to inhibit side reactions at low concentrations, the fourth feature vector being the ratio of the reciprocal of lime slurry dispersion to sodium hydroxide concentration; a first hidden layer, used to learn the low-order nonlinear relationship of multidimensional feature vectors through the ReLU activation function to obtain a 24-dimensional low-order feature vector; a second hidden layer, used to learn the high-order coupling relationship of the 24-dimensional low-order feature vectors through the LeakyReLU activation function (to avoid gradient vanishing), to obtain a 12-dimensional high-order feature vector; an output layer, used to map the 12-dimensional high-order feature vector to the actual process parameter range through a linear activation function (because the feed ratio is a continuous positive value), to obtain the feed ratio of lime slurry, liquid yellow phosphorus, and sodium hydroxide (the sum is 1, which can be directly used for feed metering, such as when the total feed is 100kg, 52kg, 31kg, and 17kg are fed respectively).

[0025] The production plan for different reactors is obtained by acquiring the target production volume of phosphine, the chemical parameters of different materials, and the initial environmental data within different reactors; the target production volume, the proportion of different materials added, and the initial environmental data within different reactors are then input into a pre-constructed dynamic model of parallel reactors.

[0026] In one embodiment of this application, the method for constructing a dynamic model of a parallel reactor may include: First, obtain the chemical parameters of the materials, the configured production rules, the reaction mechanism and cost accounting data for phosphine production, as well as the historical production records, physical parameters, equipment aging parameters, energy consumption baseline, and maintenance cycle of each reactor. The production rules include: upper limit of reactor volume (total feed ≤ 80% of volume), prohibited material feeding order (e.g., A must be fed before B), safe range of operating parameters (heating power ≤ 90% of rated power), and upper limit of production cycle (e.g., single reactor single reaction ≤ 8 hours). The reaction mechanism includes: stoichiometric formulas of the main and side reactions, enthalpy change (endothermic / exothermic and numerical values), reaction order (e.g., second-order reaction of A and B), and theoretical activation energy (which can be inferred from similar reaction systems or obtained from a database). Physical parameters include: thermal conductivity of the reactor material, volume and inner wall roughness, geometric characteristics of the stirring device, power curve, and heat loss coefficient (relationship between ambient temperature and reactor body heat transfer). Equipment aging parameters reflect the aging degree of the corresponding reactor. The energy consumption baseline reflects the energy consumption of the corresponding reactor and can be based on this. The historical material input parameters, control parameters, and output results of the reactors should be determined. Cost accounting data includes: raw material costs, energy consumption costs, the relationship between equipment maintenance costs and operating time (e.g., the maintenance cost amortization of 20 yuan per hour of operation for the first reactor) and product selling prices (e.g., 1000 yuan / kg for qualified products, with a 5% discount for every 1% decrease in purity). Raw material cost = Σ (the amount of different materials input in each reactor × the corresponding unit price of the material) + Σ (the amount of different materials lost in each reactor × the corresponding unit price of the material); Energy consumption cost = Σ (the reaction cycle of each reactor × the energy consumption per unit time). × Electricity cost), where the reaction cycle varies with the total feed amount; historical production records include: the time interval (e.g., A is added at t=0, B is added at t=30min) and the addition rate of different materials in different reactors under different total feed amounts (i.e., the feed amount and value of all materials in the reactor), the corresponding operating parameters (stirring speed, heating temperature, heating power, heating time, cooling power and cooling time at each stage), and the actual results under these parameters (reaction efficiency, reaction cycle, product purity, material loss, energy consumption records). Then, a reaction mechanism model was constructed based on the chemical parameters of the materials, the reaction mechanism for producing phosphine, and the historical production records of each reactor; a reactor state model was constructed based on physical parameters, equipment aging parameters, energy consumption baseline, and maintenance cycle; and a production constraint model was constructed based on the configured production rules and cost accounting data. The reaction mechanism model is as follows: ; ; ; in, represents the concentration of the nth material in the i-th reactor at time t; m represents the total number of material types. This represents the feeding rate of the nth material in the i-th reactor at time t; This represents the initial concentration of the nth material (derived from the chemical parameters of the corresponding material). This represents the reaction consumption rate of material n with the m-th material; This represents the effective volume of the i-th reactor; the loss rate is determined based on a correlation model of feed rate, stirring speed, and loss constructed from historical production records. , Indicates the loss coefficient; Indicates the stirring speed; This indicates the maximum stirring speed; The reaction rate constant is derived from historical production records; α and β represent the reaction order, derived from chemical parameters. Indicates the rate of phosphine formation; The activation energy originates from chemical parameters; This is the real-time temperature, which is related to heating or cooling parameters. The stirring enhancement coefficient, The higher the value, the greater the stirring enhancement coefficient, which is based on historical production records; The initial temperature; and Heating / cooling power; and For thermal efficiency, , The aging coefficient; The reaction is exothermic. , It represents the enthalpy change of a reaction, derived from chemical parameters; This refers to the total amount of material fed into the machine. Specific heat capacity (chemical parameter); The heating time is used; the reactor state model includes: a maximum total feed rate limiting model and an energy consumption model; the maximum total feed rate limiting model is as follows: ;in, (The density of the mixed materials can be derived from chemical parameters). Remaining maintenance time, maintenance cycle parameters: ; The single-batch reaction cycle is based on historical production records. The maximum feed rate per batch can be obtained based on physical parameters; the energy consumption model is as follows: ;in, (Heating energy consumption); (Stirring energy consumption, (This represents the stirring power coefficient, which can be obtained from physical parameters). (Cooling energy consumption); This is the energy consumption increase factor (equipment aging parameter, which can be obtained based on historical energy consumption baseline); the production constraint model includes production rule constraints and a cost accounting model; among them, production rule constraints include: a method to characterize the feeding interval between any two materials, for example... (The minimum interval between feeding material A and feeding material B is derived from production rules); Heating / Cooling: , The temperature resistance of the vessel body can be determined based on its physical parameters. , Indicates product crystallization time; Safety: Oxygen content is 0; Cost accounting model includes: ;in, Indicates raw material cost; Indicates energy consumption cost; Indicates maintenance costs; Indicates loss cost; Finally, based on the reaction mechanism model, the reactor state model, and the production constraint model, a dynamic model of the parallel reactor based on digital twins is obtained.

[0027] Specifically, the target production volume, the proportion of different materials added, and the initial environmental data within different reactors are input into a pre-constructed dynamic model of parallel reactors to obtain the production plan for each reactor, including: Initialize the total feed rate, feed rate, feed interval, and operating control parameters for each reactor; among which, the operating control parameters include: target stirring speed, target heating rate, target heating temperature, target heating time, target cooling rate, target cooling temperature, target depressurization rate, and target cooling time; the target heating time includes: start heating time and heating duration; the target cooling time includes: start cooling time and cooling duration. Based on the types of parameters included in the production plan of the configured reactors, multiple alternative production plans are determined; these multiple alternative production plans are randomly generated within the constraints of the parallel reactor dynamic model. Multiple candidate production plans are input into a parallel reactor dynamic model for phosphine automated production simulation, yielding simulation results for different candidate plans. Specifically, the parallel reactor dynamic model calculates the temperature change over time within the reactor based on the total feed rate, feed interval, and operating control parameters in the candidate production plans. Combined with the reaction mechanism model, the model simulates the chemical reaction process of materials under temperature changes (e.g., changes in material concentration and product formation rate). Simultaneously, it checks whether production constraints are met (e.g., maximum reactor pressure does not exceed the upper limit, cooling time is not less than the safety threshold, etc.). If constraints are violated, the combination is directly marked as an invalid candidate production plan. For each valid alternative production plan, key indicators (such as product yield, energy consumption, and production time) are extracted from the simulation results and substituted into the preset objective function to calculate the objective function value for each alternative production plan. The parallel reactor dynamic model aims to optimize the following: lowest total cost, lowest material loss rate (the proportion of reaction byproducts or residues to the feed amount), highest output value per unit time (product output × unit price), and shortest reaction cycle. The total feed amount, feed control parameters, and operation control parameters of each reactor are used as optimization variables. The production constraint model and production rules of the parallel reactor dynamic model serve as constraints. The objective function is as follows: ;in, ;k represents the total number of reactors; ; Indicates the unit price of electricity; , Indicates basic maintenance costs; Indicates the aging-related additional maintenance factor; This indicates the degree of aging of the i-th reactor; This represents the total batch cycle of the i-th reactor; This represents the maintenance cycle of the i-th reactor; loss cost. , This represents the loss rate of the nth material in the i-th reactor; ; This represents the feeding rate of the nth material; This is the maximum stirring speed; This is the theoretical optimal heating temperature for the nth material, i.e., the target heating temperature. , and This is the loss coefficient; By comparing the objective function values ​​of all effective combinations, the combination of variables with the optimal objective function value (such as maximum or minimum) is selected as the optimal solution to obtain the production plan for each reactor. If there are multiple solutions with similar objective function values, a secondary screening can be performed by combining secondary indicators (such as production stability).

[0028] Step S220: For any reactor, determine the amount of each material to be added to the reactor based on the proportion of different materials added and the total amount of material added to the reactor.

[0029] Specifically, for any given material, the amount of that material added to the reactor can be determined based on its proportion and the total amount of material added to the reactor.

[0030] Step S230: Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, control the feeding component to add materials to the reactor and control the stirring component to stir the materials in the reactor so that different materials react to generate phosphine; and monitor the real-time environmental data in the reactor.

[0031] Specifically, based on the amount of each material added to the reactor and the feeding control parameters, the feeding component is controlled to add materials to the reactor, and the feeding metering component is controlled to monitor the amount of materials added, and the environmental monitoring component is controlled to monitor the real-time environmental data inside the reactor; based on the operation control parameters, the stirring component is controlled to stir the materials inside the reactor, and the temperature control component is controlled to adjust the temperature inside the reactor.

[0032] Step S240: Adjust the feeding control parameters and operation control parameters according to real-time environmental data to control the reaction of different materials until the reaction of different materials is completed.

[0033] Specifically, the phosphine production process can be divided into the lime slurry feeding stage, the first heating stage, the liquid yellow phosphorus feeding stage, the second heating stage, the sodium hydroxide feeding stage, and the cooling stage. Based on real-time environmental data, the risk index is calculated. Based on the risk index, the feeding control parameters and the operation control parameters are adjusted to obtain new feeding control parameters and new operation control parameters, and the process returns to step S230.

[0034] Specifically, the formula for calculating the risk index includes: The system acquires historical environmental data within a preset time period, as well as the current stage of the real-time environmental data. The preset time period is configurable by the user according to their needs; for example, it could be the past 5 minutes or the past 10 minutes. The current stage of the real-time environmental data refers to which stage the reactor is in when the data is measured: lime slurry feeding stage, first heating stage, liquid yellow phosphorus feeding stage, second heating stage, sodium hydroxide feeding stage, or cooling stage. Based on the historical environmental data and the safety thresholds corresponding to different stages, the system calculates the risk index of the real-time environmental data. The environmental data includes four categories: temperature, pressure, exhaust gas, and flow field uniformity. The exhaust gas concentration is defined as the concentration of phosphine in the exhaust gas. Safety thresholds for different types of environmental data at different stages are also defined. The safety thresholds for any type of environmental data differ; they include: safe range, critical threshold, safe rate, and dangerous rate. For example, the safe range for temperature during the lime slurry feeding stage is 25±5℃, and the critical threshold is 40℃; the safe range for pressure during the lime slurry feeding stage is 0.1±0.02MPa, and the critical threshold is 0.2MPa; the safe range for exhaust gas during the lime slurry feeding stage is 0.1%, the critical threshold is 0.5%, the safe rate is 0.05% / min, and the dangerous rate is 0.2% / min; the safe range for flow field uniformity during the lime slurry feeding stage is 70%, and the critical threshold is 50%; the safe range for temperature during the first heating stage is 50±3℃, the critical threshold is 60℃, and the safe rate... The safe range for pressure during the first heating stage is 0.2 ± 0.03 MPa, the critical critical value is 0.3 MPa, the safe rate is 0.02 MPa / min, and the critical rate is 0.05 MPa / min. The safe range for exhaust gas during the first heating stage is 0.2%, and the critical critical value is 0.6%. The safe range for flow field uniformity during the first heating stage is 80%, and the critical critical value is 60%. The safe range for temperature during the liquid yellow phosphorus feeding stage is 50 ± 2℃, the critical critical value is 60℃, the safe rate is 1℃ / min, and the critical rate is 3℃ / min. The safe range for pressure during the liquid yellow phosphorus feeding stage is 0.2 ± 0.02 MPa. The critical value for danger is 0.25 MPa; the safe range for tail gas during the liquid yellow phosphorus feeding stage is 0.3%, and the critical value for danger is 0.8%; the safe range for flow field uniformity during the liquid yellow phosphorus feeding stage is 85%, and the critical value for danger is 70%; the safe rate is a change in stirring speed ≤ 5 rpm / min; the dangerous rate is a change in stirring speed ≥ 10 rpm / min; the safe range for temperature during the second heating stage is 65±5℃, the critical value for danger is 80℃, the safe rate is 4℃ / min, and the dangerous rate is 9℃ / min; the safe range for pressure during the second heating stage is 0.25±0.03 MPa, the critical value for danger is 0.35 MPa, the safe rate is 0.03 MPa / min, and the dangerous rate is 0.0.07 MPa / min; the safe range for the exhaust gas in the second heating stage is 0.5%, and the critical value is 1.0%; the safe range for the flow field uniformity in the second heating stage is 80%, and the critical value is 60%; the safe range for the temperature in the sodium hydroxide feeding stage is 65±5℃, the critical value is 85℃, the safe rate is 2℃ / min, and the critical rate is 5℃ / min; the safe range for the pressure in the sodium hydroxide feeding stage is 0.3±0.04 MPa, the critical value is 0.4 MPa, the safe rate is 0.03 MPa / min, and the critical rate is 0.08 MPa / min; the safe range for the exhaust gas in the sodium hydroxide feeding stage is 2.0%, the critical value is 5.0%, the safe rate is 0.5% / min, and the critical rate is 1.5% / min; the sodium hydroxide feeding stage The safe range for flow field uniformity is 85%, and the critical value is 65%; the safe rate is a change in stirring speed ≤ 3 rpm / min; the critical rate is a change in stirring speed ≥ 8 rpm / min; the safe range for temperature during the cooling stage is 40℃, the critical value is 50℃, the safe rate is 3℃ / min, and the critical rate is 7℃ / min; the safe range for pressure during the cooling stage is 0.15 MPa, the critical value is 0.2 MPa, the safe rate is 0.02 MPa / min, and the critical rate is 0.05 MPa / min; the safe range for exhaust gas during the cooling stage is 0.5%, the critical value is 1.0%, the safe rate is 0.03% / min, and the critical rate is 0.1% / min; the safe range for flow field uniformity during the cooling stage is 75%, and the critical value is 55%. The formula for calculating the Risk Index (RI) is as follows:

[0035] in, This represents the current risk factor for the z-th type of environmental data. The current risk factor for any type of environmental data is calculated based on the deviation between the real-time environmental data for that type and the configured safety threshold. The rate risk factor represents the rate of change risk factor for the z-th type of environmental data. The rate risk factor is determined based on the deviation between the measured rate of change and the safe and dangerous rates. The weights of the z-th type of environmental data are represented by the weights of temperature, pressure, exhaust gas, and flow field uniformity, which can be 0.25, 0.25, 0.3, and 0.2, respectively, based on the risk characteristics of phosphine production. Represents the coupling coefficient; This indicates the rate coupling risk of temperature and pressure (sudden increases in temperature and pressure exacerbate equipment leakage). This indicates the risk of velocity coupling between exhaust gas concentration and flow field (a sudden increase in concentration and a sudden change in flow field can easily lead to local combustion and explosion).

[0036] Based on the risk index, adjust the feeding control parameters and operating control parameters, including: Risk thresholds were determined for different stages, including low-risk, medium-risk, and high-risk thresholds. For the lime slurry feeding stage, the low-risk threshold was ≤40, medium-risk was 41-70, and high-risk was ≥71. For the first heating stage, the low-risk threshold was ≤35, medium-risk was 36-65, and high-risk was ≥66. For the liquid yellow phosphorus feeding stage, the low-risk threshold was ≤30, medium-risk was 31-60, and high-risk was ≥61. For the second heating stage, the low-risk threshold was ≤45, medium-risk was 46-75, and high-risk was ≥76. For the sodium hydroxide feeding stage, the low-risk threshold was ≤50, medium-risk was 51-80, and high-risk was ≥81. For the cooling stage, the low-risk threshold was ≤40, medium-risk was 51-80, and high-risk was ≥81. Risk levels are 41-70, with high risk ≥71. Based on the comparison between the risk index and risk threshold, the risk level of the current phosphine production stage is determined. Specifically, when the risk index is less than or equal to the low-risk threshold, the risk level is low; when the risk index is within the medium-risk threshold, the risk level is medium; and when the risk index is greater than or equal to the high-risk threshold, the risk level is high. Based on the different adjustment rules corresponding to different production stages and risk levels, the target adjustment rules corresponding to the risk level of the current phosphine production stage are determined. According to the target adjustment rules, the feed control parameters and operating control parameters are adjusted to ensure that different materials continue to react.

[0037] Specifically, each time, the first adjustment rule is executed first. After the first adjustment rule is executed, real-time environmental data must be acquired again and the risk index must be recalculated. If the risk index does not decrease (or the risk level does not change), the second adjustment rule is executed. After the second adjustment rule is executed, real-time environmental data must be acquired again and the risk index must be recalculated. If the risk index does not decrease (or the risk level does not change), the third adjustment rule is executed. When all three adjustment rules have been executed and the risk index has not decreased, a real-time warning is generated, pre-configured safety enforcement measures (such as interrupting the reaction) are adopted, and the corresponding data is stored. The stored corresponding data is input into the parallel reactor dynamic model to analyze the fault.

[0038] The adjustment rules for the lime slurry feeding stage include: When the risk level is low, maintain real-time feeding control parameters and operation control parameters; When the risk level is medium risk, the first adjustment rule is: if the flow field uniformity in the real-time environmental data is less than 70%, then increase the stirring speed in the operation control parameters to 10%-15% of the real-time stirring speed; the second adjustment rule is: if the flow field uniformity in the newly acquired real-time environmental data is still less than 65%, then reduce the feeding rate in the feeding control parameters to 90%-95% of the real-time feeding rate, and extend the feeding interval by 10% of the real-time feeding interval; the third adjustment rule is: if the temperature in the newly acquired real-time environmental data is less than 20℃, then start heating, with a target heating temperature of 25℃ and a target heating rate less than or equal to the configured real-time maximum possible safe rate × 0.8; if the temperature in the real-time environmental data is greater than or equal to 30℃, then do not heat up; When the risk level is high, the first adjustment rule is: increase the stirring speed in the operation control parameters by 20%-30% of the real-time stirring speed; the second adjustment rule is: if the risk index calculated from the newly acquired real-time environmental data is still high after adjustment, then reduce the feeding rate in the feeding control parameters to 70%-80% of the real-time feeding rate, extend the feeding interval by 20%-30% of the real-time feeding interval, and check the flow field uniformity after each batch of feeding (only continue if the flow field uniformity is ≥60%); the third adjustment rule is: if the temperature of the newly acquired real-time environmental data is >35℃ after adjustment, then start cooling, with a target cooling temperature of 30℃ and a target cooling rate not greater than the maximum possible safe rate in real time × 0.7; The adjustment rules for the first warming phase include: When the risk level is low, maintain real-time feeding control parameters and operation control parameters; When the risk level is medium risk, the first adjustment rule is: if the heating rate exceeds 5℃ / min, reduce the heating rate in the operation control parameters to 70%-80% of the real-time value, while keeping the target heating temperature at 50℃ (unchanged); the second adjustment rule is: if the local temperature difference in the real-time environmental data is >3℃, increase the stirring speed in the operation control parameters by 5%-10% of the real-time stirring speed; the third adjustment rule is: if the material quantity is insufficient, the replenishment rate should be ≤5% of the real-time value. When the risk level is high, the first adjustment rule is: prioritize temperature adjustment: suspend heating; if the temperature in the real-time environmental data exceeds 55℃, start cooling (target cooling rate ≤ configured real-time maximum possible safe rate × 0.6), with a target cooling temperature of 48℃; the second adjustment rule is: increase the rotation speed in the operation control parameters by 15%-20% of the real-time value; the third adjustment rule is: suspend supplementary heating, wait until the temperature stabilizes at 48-50℃ and the danger index ≤ 65, then increase the rotation speed by 50% of the real-time value. v 0×0.5) additional investment to maintain the total amount.

[0039] The adjustment rules for the liquid yellow phosphorus feeding stage include: No adjustment is made when the risk level is low. When the risk level is medium risk, the first adjustment rule is: reduce the feeding rate in the feeding control parameters to 80%-90% of the real-time feeding rate, and extend the feeding interval by 20% of the real-time feeding interval; the second adjustment rule is: if the temperature in the real-time environmental data is <45℃, start heating (heating rate ≤ configured current maximum possible safe rate × 0.6), with a target heating temperature of 48℃; if the temperature is >50℃, pause heating and allow it to cool down naturally; the third adjustment rule is: if the mixing is uneven, increase the stirring speed in the operation control parameters by 10% of the current value, and use inert gas purging. When the risk level is high, the first adjustment rule is: reduce the feeding rate in the feeding control parameters to 50%-60% of the current feeding rate, and switch to intermittent feeding (stop for 3 minutes after feeding 10L), and check the concentration during the pause; the second adjustment rule is: start cooling (cooling rate ≤ the configured current maximum possible safe rate × 0.5), target 45℃ (away from the auto-ignition point); the third adjustment rule is: increase the stirring speed by 20% of the current stirring speed, but not exceed the equipment limit; The adjustment rules for the second warming phase include: No adjustment is made when the risk level is low. When the risk level is medium risk, the first adjustment rule is: if the heating rate exceeds 4℃ / min, the heating rate is reduced to 60%-70% of the current heating rate, while the target heating temperature remains at 65℃; the second adjustment rule is: if the exhaust gas concentration exceeds 1%, the stirring speed is increased by 10%-15% of the current stirring speed to promote gas escape; the third adjustment rule is: if the pressure exceeds 0.2MPa, the pressure relief rate is adjusted to 50% of the current pressure relief rate to slowly reduce the pressure. When the risk level is high, the first adjustment rule is: stop heating and start cooling (cooling rate ≤ current maximum possible safe rate × 0.6), with a target cooling temperature of 60℃; the second adjustment rule is: increase the rotation speed by 20% of the current value to enhance heat transfer and avoid local overheating; the third adjustment rule is: if the pressure exceeds 0.25MPa, adjust the pressure relief rate to 80% of the current pressure relief rate to control pressure in conjunction with cooling. The adjustment rules for the sodium hydroxide feeding stage include: No adjustment is made when the risk level is low. When the risk level is medium risk, the first adjustment rule is: reduce the feeding rate to 80%-90% of the current feeding rate and extend the feeding interval by 10% of the current feeding interval; the second adjustment rule is: if the neutralization exothermic temperature exceeds 65℃, increase the cooling rate by 30% of the current value, and the target cooling temperature is 63℃. When the risk level is high, the first adjustment rule is: pause feeding, and after 3 minutes, add feed dropwise at 40%-50% of the current feeding rate, pausing for 5 minutes after every 10L of feed added; the second adjustment rule is: increase the cooling rate by 50% of the current cooling rate, with a target cooling temperature of 60℃; the third adjustment rule is: increase the stirring speed by 20% of the current stirring speed to ensure rapid dispersion of NaOH. The adjustment rules for the cooling phase include: No adjustment is made when the risk level is low. When the risk level is medium risk, the first adjustment rule is: if the cooling rate exceeds 6℃ / min (viscosity increases rapidly), the cooling rate should be reduced to 70%-80% of the current cooling rate; When the risk level is high, the first adjustment rule is: stop cooling, and if the temperature is <45℃, slightly increase the temperature (heating rate ≤ the current maximum possible safe rate × 0.3) to 45℃; the second adjustment rule is: increase the stirring speed by 20%-30% of the current stirring speed, and force stirring to prevent solidification.

[0040] The automated phosphine production method based on parallel reactors adopted in this application embodiment further includes: When obtaining the feeding ratios of different materials used in the production of phosphine, and the production plans of different reactors; wherein the production plans of different reactors include: the total feed amount of different reactors, the feed control parameters, and the operation control parameters; for any reactor, the feed amount of each material in the reactor is determined according to the feeding ratios of the different materials and the total feed amount of the reactor; firstly, lime slurry is added to the reactor according to the lime slurry feed amount and the feed control parameters using a metering pump, and the lime slurry is metered using a flow meter. After addition, the stirring assembly is turned on and stirred according to the stirring speed in the operation control parameters. After rinsing the lime slurry pipeline with a measured amount of purified water, the lime slurry is added to the reactor. The amount of purified water added is measured by a flow meter (automatically controlled, with the cumulative flow value of the purified water flow meter interlocking with the purified water feed valve). In the first heating stage, the heating element heats the reactor to 50°C, then the heating element is turned off. Liquid yellow phosphorus is fed into the reactor according to the corresponding dosage and feeding control parameters via a flow meter. Steam is introduced into the reactor to raise the temperature to 65°C, then the steam is turned off. A measured amount of sodium hydroxide solution is slowly added via a flow meter, and the sodium hydroxide solution is added dropwise after 1-2 hours. As the reaction proceeds, the exothermic reaction causes the temperature inside the reactor to gradually rise. The cooling element cools the reactor, controlling the temperature to 80-110°C. After 3-5 hours, the reaction stage ends. Throughout the above stages, real-time environmental data inside the reactor is continuously monitored, and the feeding control parameters and the aforementioned operating control parameters are adjusted to control the reaction of different materials until the reaction of different materials is complete.

[0041] Corresponding to the above method, this application also provides an automated phosphine production device based on parallel reactors, applied to the controller of a parallel reactor control system. The parallel reactor control system further includes: multiple reactors connected in parallel, and feeding and stirring components installed on each reactor, such as... Figure 3 As shown, the device includes: The acquisition unit 310 is used to acquire the feeding ratio of different materials used in the production of phosphine, as well as the production plans of different reactors; wherein, the production plans of different reactors include: the total feeding amount of different reactors, feeding control parameters and operating control parameters; The determining unit 320 is used to determine the amount of each material in the reactor based on the feeding ratio of different materials and the total feeding amount of the reactor for any given reactor. The control unit 330 is used to control the feeding component to feed materials into the reactor and control the stirring component to stir the materials in the reactor according to the amount of each material fed into the reactor, the feeding control parameters and the operation control parameters, so that different materials react to generate phosphine; and to monitor the real-time environmental data in the reactor. The adjustment unit 340 is used to adjust the feeding control parameters and operation control parameters according to real-time environmental data in order to control the reaction of different materials until the reaction of different materials is completed.

[0042] The functions of each functional unit in the phosphine automated production device based on parallel reactors provided in the above embodiments of this application can be realized through the above methods and steps. Therefore, the specific working process and beneficial effects of each unit in the phosphine automated production device based on parallel reactors provided in the embodiments of this application will not be repeated here.

[0043] This application also provides an electronic device, such as... Figure 4 As shown, it includes a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440.

[0044] Memory 430 is used to store computer programs; When the processor 410 executes the program stored in the memory 430, it performs the following steps: Obtain the feeding ratios of different materials used in the production of phosphine, as well as the production plans for different reactors; wherein, the production plans for different reactors include: the total feed amount, feed control parameters, and operating control parameters for different reactors; For any given reactor, determine the amount of each material to be added to the reactor based on the proportion of different materials added and the total amount of material added to the reactor. Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, the feeding component is controlled to add materials to the reactor, and the stirring component is controlled to stir the materials in the reactor so that different materials react to generate phosphine; and the real-time environmental data in the reactor is monitored. Based on real-time environmental data, adjust the feeding control parameters and operation control parameters to control the reaction of different materials until the reaction of different materials is completed.

[0045] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0046] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0047] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0048] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0049] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 2 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.

[0050] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform any of the above embodiments of an automated phosphine production method based on a parallel reactor.

[0051] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the above embodiments of the automated phosphine production method based on parallel reactors.

[0052] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0054] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0055] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0056] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0057] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims in this application and their equivalents, then this application also intends to include these modifications and variations.

Claims

1. An automated phosphine production method based on parallel reactors, characterized in that, The method is applied to a controller in a parallel reactor control system, the parallel reactor control system further comprising: multiple reactors connected in parallel, and a feeding assembly and a stirring assembly installed on each reactor, the method comprising: Obtain the feeding ratios of different materials used in the production of phosphine, as well as the production plans for different reactors; wherein, the production plans for different reactors include: the total feed amount, feed control parameters, and operating control parameters for different reactors; For any given reactor, the amount of each material to be added to the reactor is determined based on the proportion of the different materials added and the total amount of material added to the reactor. Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, the feeding component is controlled to add materials to the reactor, and the stirring component is controlled to stir the materials in the reactor so that different materials react to generate phosphine; and real-time environmental data in the reactor is monitored. Based on the real-time environmental data, the feeding control parameters and the operation control parameters are adjusted to control the reaction of different materials until the reaction of different materials is completed.

2. The method as described in claim 1, characterized in that, The feeding ratio of different materials is obtained by inputting the chemical parameters of different materials into a pre-trained feeding ratio prediction model; The different materials include: liquid yellow phosphorus, lime milk, and sodium hydroxide solution; The chemical parameter of the lime slurry is the lime slurry dispersion; the chemical parameter of the sodium hydroxide solution is the sodium hydroxide concentration.

3. The method as described in claim 2, characterized in that, The feeding ratio prediction model includes: an input layer, a feature extraction layer, a first hidden layer, a second hidden layer, and an output layer; The input layer is used to standardize the input lime slurry dispersion and sodium hydroxide concentration; The feature extraction layer is used to perform feature cross processing on the standardized lime milk dispersion and sodium hydroxide concentration to obtain a multi-dimensional feature vector. The first hidden layer is used to learn the low-order nonlinear relationship between multidimensional feature vectors and obtain low-order feature vectors. The second hidden layer is used to learn the higher-order coupling relationship of the lower-order feature vectors to obtain higher-order feature vectors; The output layer is used to map high-order feature vectors to the range of feeding parameters to obtain the feeding ratio of lime slurry and sodium hydroxide solution.

4. The method as described in claim 1, characterized in that, The method for obtaining the production plans for the different reactors includes: To obtain the target production capacity of phosphine, the chemical parameters of different materials, and the initial environmental data in different reactors; The target production volume, the proportion of different materials added, and the initial environmental data in different reactors are input into a pre-constructed dynamic model of parallel reactors to obtain the production plan for each reactor.

5. The method as described in claim 1, characterized in that, The parallel reactor control system also includes: a feeding metering component, an environmental monitoring component, and a temperature control component installed on each reactor; Based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, the feeding component is controlled to add materials to the reactor, and the stirring component is controlled to stir the materials in the reactor, including: Based on the amount of each material added to the reactor and the feeding control parameters, the feeding component is controlled to add materials to the reactor, and the feeding metering component is controlled to monitor the amount of materials added, and the environmental monitoring component is controlled to monitor the real-time environmental data inside the reactor. According to the operation control parameters, the stirring assembly is controlled to stir the materials in the reactor, and the temperature control assembly is controlled to adjust the temperature in the reactor.

6. The method as described in claim 1, characterized in that, Based on the real-time environmental data, adjust the feeding control parameters and the operation control parameters, including: Calculate the risk index based on the real-time environmental data; Based on the risk index, adjust the feeding control parameters and the operation control parameters to obtain new feeding control parameters and new operation control parameters, and return to the execution steps: based on the amount of each material added to the reactor, the feeding control parameters, and the operation control parameters, control the feeding component to add materials to the reactor and control the stirring component to stir the materials in the reactor until the different materials have reacted completely.

7. The method as described in claim 6, characterized in that, Based on the risk index, adjust the feeding control parameters and the operation control parameters, including: Obtain risk thresholds for different stages of phosphine production; Based on the comparison between the risk index and the risk threshold, the risk level of the current phosphine production stage is determined; Based on the different adjustment rules corresponding to different production stages and different risk levels, determine the target adjustment rule corresponding to the risk level of the current phosphine production stage; According to the target adjustment rules, the feeding control parameters and operation control parameters are adjusted to allow different materials to continue reacting.

8. An automated phosphine production device based on parallel reactors, characterized in that, The controller is applied to a parallel reactor control system, which further includes: multiple reactors connected in parallel, and a feeding assembly and a stirring assembly installed on each reactor. The device includes: The acquisition unit is used to acquire the feeding ratio of different materials used in the production of phosphine, as well as the production plans of different reactors; wherein, the production plans of different reactors include: the total feeding amount of different reactors, feeding control parameters and operating control parameters; A determining unit is used to determine the amount of each material in any reactor based on the proportion of different materials added and the total amount of material added to the reactor. The control unit is used to control the feeding component to feed materials into the reactor and control the stirring component to stir the materials in the reactor according to the amount of each material fed into the reactor, the feeding control parameters and the operation control parameters, so that different materials react to generate phosphine; and to monitor the real-time environmental data in the reactor. The adjustment unit is used to adjust the feeding control parameters and the operation control parameters according to the real-time environmental data, so as to control the reaction of different materials until the reaction of different materials is completed.

9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

Images