An online control system and method for powder production equipment

Abstract

The invention discloses an online control system and method for powder production equipment, belonging to the technical field of production equipment control. The method specifically comprises: using sensors to collect key parameters in a powder production process in real time, including humidity, temperature, density, particle size and composition, and preprocessing the collected key parameters in the powder production process; establishing a mathematical model of the powder production process according to the collected key parameters in the powder production process; analyzing changes in key parameters of the powder in the production process; collecting key parameters of finished products at a powder finished product outlet in real time; evaluating the quality of the powder finished products; and according to the powder finished product quality analysis results, using an adaptive control strategy to feedback and adjust key parameters of the powder production equipment in the production process, and optimizing the production process and improving the quality of the powder product through real-time monitoring and automatic control.

Description

Technical Field

[0001] The invention belongs to the technical field of production equipment control, in particular to an online control system and method for powder production equipment. Background Art

[0002] Powder production equipment has been widely used in the fields of pharmaceuticals, food, and chemicals. The main functions of these equipment are to crush, mix, and dry raw materials, and finally form powder products that meet the requirements. However, traditional powder production equipment usually relies on manual operation and offline detection, and has the following problems:

[0003] 1) Low production efficiency: Due to reliance on manual operation, there are many human factors in the production process, resulting in low production efficiency; 2) Difficulty in quality control: Offline testing is usually carried out after the end of production, and it is impossible to detect and correct quality problems in the production process in time, which can easily lead to unstable product quality; 3) Poor real-time data: Traditional methods lack real-time monitoring and data collection of the production process, making it difficult to perform effective process optimization and control; 4) Waste of resources: Due to the inability to monitor the production process in real time, it is easy to lead to waste of resources, such as excessive feeding, excessive energy consumption, etc.

[0004] For example, a Chinese patent application with publication number CN1 17724417A discloses a production equipment control method based on the Internet of Things, which relates to the technical field of the Internet of Things and solves the technical problem in the prior art that the production equipment is not reasonably regulated in a timely manner, resulting in the production equipment not reaching its own maximum output value, thereby reducing the overall output; the method comprises: an equipment management module obtains the completed output at a monitoring time node; a data processing module processes the data sent by the equipment management module, and analyzes whether the completed output reaches the corresponding predicted output. If not, the speed regulation module adjusts the production speed of the equipment; at the same time, the data processing module also monitors the equipment temperature, and adjusts the production speed to keep the equipment temperature normal; this method reasonably regulates the production speed of the production equipment in a timely manner, so that each production equipment reaches its own maximum output value, thereby improving the overall output of the factory.

[0005] For example, a Chinese patent application with publication number CN1 17076849A discloses a method and system for intelligent control of production equipment, which compresses and derives the screened data blocks to obtain cluster data with data importance levels for each data block, and then controls the designated importance levels of the data blocks through the cluster data, thereby controlling the designated importance levels of the data collected by the production equipment and obtaining control results of the data collected by the production equipment. In the screening process, while ensuring that the error range in the data collected by the production equipment is not missed, the screening of the normal range in the data collected by the production equipment can be reduced, so that more attention is paid to the error range in the data collected by the production equipment during the derivation process, reducing the difference in subsequent error control, making the controlled data importance level more accurate, and being able to more accurately control the designated importance levels of the data blocks, thereby improving the accuracy of the designated importance levels of the data collected by the production equipment and obtaining more accurate control results.

[0006] The defects of the above patent are: 1) It is not directly applied to the production control of animal health powder; 2) It fails to improve the production efficiency of animal health powder while controlling the quality of the produced animal health powder. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention proposes an online control system and method for powder production equipment, which optimizes the powder production process and improves the quality of powder products through real-time monitoring and automatic control.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] An online control method for powder production equipment comprises the following specific steps:

[0010] Use sensors to collect key parameters in the powder production process in real time, including humidity, temperature, density, particle size and composition, and pre-process the collected key parameters in the powder production process;

[0011] According to the key parameters collected in the powder production process, a mathematical model of the powder production process is established to analyze the changes in the key parameters of the powder production process;

[0012] Real-time collection of key parameters of finished powder products at the export site to evaluate the quality of finished powder products;

[0013] According to the quality analysis results of powder finished products, adaptive control strategy is used to feedback and adjust the key parameters of powder production equipment in the production process.

[0014] Specifically, the mathematical model for establishing the powder production process includes:

[0015] a first equilibrium model, a second equilibrium model, and a third equilibrium model;

[0016] In the production process of powders, a first balance model is established according to the feed of powder raw materials, the discharge of powders and the mass of substances produced or consumed in the reaction process to obtain the feed flow rate of powder production, the discharge flow rate of powder production and the production or consumption of powder production reaction. The rate of change of the total amount of powder raw materials in powder production with the powder production time is the sum of the feed flow rate of powder production, the discharge flow rate of powder production and the production or consumption of powder production reaction;

[0017] According to the input, output, generation and consumption of energy in the powder production equipment, a second balance model is established to obtain the heat input into the powder production equipment, the heat output of the powder production equipment and the working energy of the powder production equipment. The total energy in the powder production equipment is the sum of the heat input into the powder production equipment, the heat output of the powder production equipment and the working energy of the powder production equipment.

[0018] According to the diffusion, convection and reaction factors in the powder production process, a third equilibrium model is established to express the balance between the concentration of components in the powder production process and the convection term of the components moving with the fluid in the powder production process, and the diffusion term of the components in the powder production process and the production or consumption rate of the components in the powder production reaction.

[0019] Specifically, the specific formula for the production or consumption rate of the components in the powder production reaction is:

[0020]

[0021] Among them, R i represents the production or consumption rate of the component in the i-th powder production reaction, K i represents the rate constant of the i-th powder production reaction, C q represents the concentration of the qth component in the powder production process, represents the reaction order of the qth component in the i-th powder production reaction, and G represents the total number of reaction components in the i-th powder production reaction.

[0022] Specifically, the quality assessment of the powder finished product includes:

[0023] The average particle size of the finished powder, the moisture content of the finished powder, the color difference of the finished powder, the density of the finished powder and the fluidity of the finished powder are weightedly summed.

[0024] Specifically, the adaptive control strategy includes:

[0025] A qualified threshold value for the quality of the powder finished product is set. When the quality of the powder finished product is lower than the qualified threshold value for the quality of the powder finished product, the powder finished product is judged to be unqualified. Otherwise, the powder finished product is judged to be qualified.

[0026] When the powder product is unqualified, the state at time g in the powder production process is estimated. The specific formula is:

[0027]

[0028] in, represents the estimated value of the state at time g in the powder production process, represents the estimated value of the state at time g-1 in the powder production process, G g represents the Kalman gain, y g represents the observed value at time g in the powder production process, and H represents the observation matrix;

[0029] The error parameters at time g in the powder production process are identified, and the specific formula is:

[0030]

[0031] Among them, θ g represents the parameter estimation vector at time g in the powder production process, θ g-1 represents the parameter estimation vector at time g-1 in the powder production process, Zy g represents the gain matrix, φ g represents the regression vector at time g in the powder production process;

[0032] According to the state estimation and parameter identification at time g in the powder production process, the key parameters of the powder production equipment are dynamically adjusted. The specific formula for the control input of the powder production equipment is:

[0033]

[0034] Among them, u g represents the control input of the powder production equipment at time g, and ζ represents the adaptive control gain matrix.

[0035] Specifically, the preprocessing includes: removing noise and outliers.

[0036] An online control system for powder production equipment, used to implement the online control method for powder production equipment, comprising: a data acquisition module, a model building module, a quality assessment module and a control adjustment module;

[0037] The data acquisition module is used to use sensors to collect key parameters in the powder production process in real time, including humidity, temperature, density, particle size and composition, and pre-process the collected key parameters in the powder production process;

[0038] The model building module is used to build a mathematical model of the powder production process based on the key parameters collected during the powder production process, and analyze changes in the key parameters of the powder during the production process;

[0039] The quality assessment module is used to collect key parameters of finished powder products at the outlet in real time and assess the quality of the finished powder products;

[0040] The control adjustment module is used to feedback and adjust key parameters of the powder production equipment during the production process based on the powder finished product quality analysis results and using an adaptive control strategy.

[0041] Specifically, the control adjustment module includes: a state estimation unit, an error parameter identification unit and a control input unit;

[0042] The state estimation unit is used to estimate the state at time g during the powder production process;

[0043] The error parameter identification unit is used to identify the error parameter at time g during the powder production process;

[0044] The control input unit is used to calculate the control input of the powder production equipment according to the state estimation and parameter identification at time g in the powder production process.

[0045] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of an online control method for powder production equipment when executing the computer program.

[0046] A storage medium stores computer instructions, which, when executed, execute the steps of an online control method for powder production equipment.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention proposes an online control method for powder production equipment. The online control can monitor various parameters in the production process in real time, detect and adjust abnormal situations in time, and ensure the stability and consistency of product quality.

[0049] 2. The present invention proposes an online control method for powder production equipment, which avoids excessive consumption of resources and reduces production costs by accurately controlling various production parameters, while reducing human intervention and improving production efficiency.

[0050] 3. The present invention proposes an online control method for powder production equipment, which can collect and analyze data in the production process in real time through sensors and control systems, and provide data support for powder production process optimization and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A flow chart of an online control method for powder production equipment provided by the present invention;

[0052] Figure 2 A schematic diagram of key parameter processing in the powder production process provided by the present invention;

[0053] Figure 3 An architecture diagram of an online control system for powder production equipment provided by the present invention;

[0054] Figure 4 A schematic diagram of an electronic device provided by the present invention;

[0055] Figure 5 This is a schematic diagram of the storage medium structure provided by the present invention. DETAILED DESCRIPTION

[0056] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, in the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate the orientation or position relationship based on the orientation or position relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "No. 1", "No. 2" and "No. 3" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. The present invention is further explained below in conjunction with specific embodiments.

[0057] Example 1

[0058] See also Figure 1-Figure 2 , an embodiment provided by the present invention: an online control method for powder production equipment, comprising the following specific steps:

[0059] Step S1: using sensors to collect key parameters in the powder production process in real time, including but not limited to humidity, temperature, density, particle size and composition, and preprocessing the collected key parameters in the powder production process, including removing noise and outliers, to ensure the accuracy and reliability of the data;

[0060] In the production process of feed powder, due to the need for specific production humidity and the fact that the powder is spread throughout the entire production space during the production process, the existing sensors have low detection accuracy and cannot be used directly. The collected data needs to be processed.

[0061] During a T period of time in the powder production process, key parameters in the powder production process are alternately collected through a first data collection window and a second data collection window; wherein the time length of the first data collection window is greater than the time length of the second data collection window;

[0062] Determine the real-time data in a time period T during the powder production process according to the real-time data segments correspondingly collected by the first data collection window and the second data collection window;

[0063] The production parameters of the powder production process are controlled according to the real-time data.

[0064] Determining the real-time data in a time period T during the powder production process according to the real-time data segments corresponding to the first data acquisition window and the second data acquisition window includes:

[0065] Averaging the data collected by the first data collection window to obtain first average data;

[0066] Averaging the data collected by the second data collection window to obtain second average data;

[0067] The first average data is alternately corrected using the second average data to complete the processing of key parameters in the powder production process.

[0068] In this embodiment, the first data acquisition window (longer time window) is used to obtain key parameters within a longer time range to provide a stable data basis, and the second data acquisition window (shorter time window) is used to obtain key parameters within a shorter time range to provide faster response data. By alternately using two data acquisition windows of different lengths to obtain and process key parameters in the powder production process, more accurate real-time monitoring and production control can be achieved, which significantly improves the accuracy and stability of the data.

[0069] The real-time correction mechanism ensures that the system can respond to changes in the production process in a timely manner, quickly adjust production parameters, and avoid fluctuations and anomalies in the production process. The flexible data acquisition window setting and correction adjustment can be customized according to different production processes and needs, and has good adaptability and versatility.

[0070] Step S2: establishing a mathematical model of the powder production process based on the collected key parameters in the powder production process, and analyzing changes in the key parameters of the powder in the production process;

[0071] The specific steps of step S2 are:

[0072] Step S201: establishing a mathematical model of the powder production process according to the key parameters collected in the powder production process, including: a material balance model, an energy balance model and a mass transfer model;

[0073] Step S202: In the production process of powders, material balance is the key to ensure the stable operation of the powder production system. A material balance model is established based on the amount of powder raw material feed, powder discharge and substances produced or consumed during the reaction process. The specific formula is:

[0074]

[0075] Where M represents the total amount of powder raw materials in powder production, t represents the powder production time, Indicates the rate of change of the total amount of powder raw materials in powder production with the powder production time, F in Indicates the feed flow rate of powder production, F out Indicates the powder production discharge flow rate, R i represents the production or consumption rate of the ith powder production reaction, and N is the total number of powder production reactions;

[0076] The production rate here refers to the rate at which the powder is produced, and the consumption rate refers to the rate at which the powder raw materials are consumed;

[0077] Powder production reactions include: crushing and drying;

[0078] Step S203: Heat and working energy are particularly important in the powder production process. An energy balance model is established based on the input, output, generation and consumption of energy in the powder production equipment. The specific formula is:

[0079]

[0080] Where E represents the total energy in the powder production equipment, It represents the rate of change of total energy in the powder production equipment over time, Q in Indicates the heat input into the powder production equipment, Q out Indicates the heat output of the powder production equipment, W j represents the jth working energy, and P represents the total amount of working energy;

[0081] Here, the total energy in the powder production equipment is the sum of all forms of energy in the system, including but not limited to the following main forms: internal energy: the sum of the molecular kinetic energy and molecular potential energy of all substances in the system; kinetic energy: the energy possessed by the macroscopic movement of substances in the system; potential energy: the energy possessed by the position of substances in the system, usually including gravitational potential energy; chemical energy: the energy that can be released or absorbed by substances in the system during chemical reactions; working energy is the energy generated or consumed in the powder production equipment due to external work or internal conversion, including: mechanical work, thermal work and electrical work;

[0082] Step S204: A mass transfer model is established based on diffusion, convection and reaction factors in the powder production process. The mass transfer model describes the transfer and diffusion process between different components in the powder production process. The specific formula of the mass transfer model is:

[0083]

[0084] Among them, C k represents the concentration of the kth component in the powder production process, It represents the rate of change of the concentration of the kth component in the powder production process over time, represents partial derivative, represents the gradient operator, v represents the powder fluid velocity vector, It represents the convection term of the kth component moving with the fluid during the powder production process, and the unit is kg / m 3 ×s,D k represents the diffusion coefficient of the kth component in the powder production process, It represents the diffusion term of the kth component in the powder production process, and the unit is kg / m 3 ×s,R k It represents the production or consumption rate of the kth component in the powder production reaction;

[0085] Step S205: Analyze the changes of key parameters of the powder during the production process according to the material balance model, energy balance model and mass transfer model.

[0086] The production or consumption rate R of the i-th powder production reaction i The specific formula is:

[0087]

[0088] Among them, K i represents the rate constant of the i-th powder production reaction, C q represents the concentration of the qth component in the powder production process, represents the reaction order of the qth component in the i-th powder production reaction, and G represents the total number of reaction components in the i-th powder production reaction.

[0089] The powder fluid is a granular powder fluid formed by crushing and drying solid raw materials.

[0090] Step S3: collecting key parameters of finished powder products at the outlet in real time to evaluate the quality of the finished powder products;

[0091] The specific formula for evaluating the quality of the powder product in step S3 is:

[0092] Zl=ι1×d wd+ι2×Sd+ι3×ΔE+ι4×ρ cp +ι5×Ld,

[0093] Wherein, Z1 represents the quality evaluation value of the powder finished product, ι1, ι2, ι3, ι4 and ι5 all represent weight coefficients, and d wd represents the average particle size of the powder product, Sd represents the humidity of the powder product, ΔE represents the color difference of the powder product, ρ cp It indicates the density of the finished powder product, and Ld indicates the fluidity of the finished powder product.

[0094] The specific formula for the average particle size dwd of the finished powder is: Where B represents the total number of powder finished particles, wc represents the dimension parameter, d e It represents the diameter of the e-th particle in the finished powder;

[0095] The specific formula of the humidity Sd of the powder product is: Sd = the mass of water in the powder product / the total mass of the powder product × 100%;

[0096] The specific formula for the color difference ΔE of the finished powder product is: Among them, L cp Indicates the brightness of the finished powder, a cp Indicates the a component of the powder product, b cp Indicates the b component of the powder product, L bz Indicates the standard brightness of the finished powder, a bz Indicates the standard a weight of the finished powder, b bz Indicates the standard b weight of the powder product;

[0097] The Lab color space consists of three components: brightness (L), a component, and b component. The a component represents the range from red to green, and the b component represents the range from blue to yellow.

[0098] The data used in the formula for evaluating the quality of the finished powder product in step S3 needs to be collected by several sensors, including: a particle size distribution sensor, a humidity sensor, a color sensor, a density sensor, and a fluidity sensor;

[0099] The weight coefficients ι1, ι2, ι3, ι4 and ι5 are obtained through a large number of experiments by personnel in this field and can be slightly adjusted according to actual conditions.

[0100] Step S4: Based on the powder finished product quality analysis results, an adaptive control strategy is used to feedback and adjust key parameters of the powder production equipment during the production process.

[0101] The specific steps of step S4 are:

[0102] Step S401: setting a qualified threshold value for the quality of the powder finished product. When the quality of the powder finished product is lower than the qualified threshold value, the powder finished product is judged to be unqualified. Otherwise, the powder finished product is judged to be qualified.

[0103] Step S402: When the powder product is unqualified, the state at time g in the powder production process is estimated. The specific formula is:

[0104]

[0105] in, represents the estimated value of the state at time g in the powder production process, represents the estimated value of the state at time g-1 in the powder production process, G g represents the Kalman gain, y g represents the observed value at time g in the powder production process, and H represents the observation matrix;

[0106] Kalman gain G g The specific formula is: g =O g H T ×(HO g H T +Rs) -1 , where O g represents the prediction error covariance matrix at time g in the powder production process, T represents the transpose operation, and Rs represents the observation noise covariance matrix at time g in the powder production process;

[0107] The specific formula of the prediction error covariance matrix 0g at time g in the powder production process is: g =AO g-1 A T +Qs, where O g-1 represents the prediction error covariance matrix at time g-1 in the powder production process, A represents the state transfer matrix, and Qs represents the noise covariance matrix in the powder production process;

[0108] Step S403: Identify the error parameters in the powder production process. The specific formula is:

[0109]

[0110] Among them, θ g represents the parameter estimation vector at time g in the powder production process, θ g-1 represents the parameter estimation vector at time g-1 in the powder production process, Zy g represents the gain matrix, φ g represents the regression vector at time g in the powder production process;

[0111] Gain matrix Zy g The specific formula is: Among them, P′ g-1 represents the parameter estimation error covariance matrix at time g-1, and λ represents the forgetting factor;

[0112] The specific formula of the parameter estimation error covariance matrix at time g is:

[0113] Among them, P′ g Represents the parameter estimation error covariance matrix at time g;

[0114] Step S404: According to the state estimation and parameter identification at time g in the powder production process, the key parameters of the powder production equipment are dynamically adjusted. The specific formula for the control input of the powder production equipment is:

[0115]

[0116] Among them, u g represents the control input of the powder production equipment at time g, and ζ represents the adaptive control gain matrix.

[0117] The adaptive control gain matrix ζ can be dynamically adjusted through Lyapunov stability theory.

[0118] Example 2

[0119] See also Figure 3 , another embodiment provided by the present invention: an online control system for powder production equipment, comprising: a data acquisition module, a model building module, a quality assessment module and a control adjustment module;

[0120] The data acquisition module is used to use sensors to collect key parameters in the powder production process in real time, including humidity, temperature, density, particle size and composition, and pre-process the collected key parameters in the powder production process;

[0121] The model building module is used to build a mathematical model of the powder production process based on the key parameters collected during the powder production process, and analyze changes in the key parameters of the powder during the production process;

[0122] The quality assessment module is used to collect key parameters of finished powder products at the outlet in real time and assess the quality of the finished powder products;

[0123] The control adjustment module is used to feedback and adjust key parameters of the powder production equipment during the production process based on the powder finished product quality analysis results and using an adaptive control strategy.

[0124] The control adjustment module includes: a state estimation unit, an error parameter identification unit and a control input unit;

[0125] The state estimation unit is used to estimate the state at time g during the powder production process;

[0126] The error parameter identification unit is used to identify the error parameter at time g during the powder production process;

[0127] The control input unit is used to calculate the control input of the powder production equipment according to the state estimation and parameter identification at time g in the powder production process.

[0128] Example 3

[0129] Figure 4 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 4 As shown, according to another aspect of the present application, an electronic device 500 is also provided. The electronic device 500 may include one or more processors and one or more memories. The memories store computer readable codes, and when the computer readable codes are run by one or more processors, an online control method for a powder production device can be executed.

[0130] The method or system according to the embodiment of the present application can also be used by Figure 4 The electronic device architecture shown in FIG. Figure 4 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, ROM 503, RAM 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, and the like. The storage device in the electronic device 500, such as ROM 503 or hard disk 507, may store an online control method for a powder production device provided in the present application. An online control method for a powder production device may, for example, include: using sensors to collect key parameters in the powder production process in real time, including humidity, temperature, density, particle size, and composition, and preprocessing the collected key parameters in the powder production process, establishing a mathematical model of the powder production process based on the collected key parameters in the powder production process, analyzing the changes in the key parameters of the powder in the production process, collecting the key parameters of the finished powder at the outlet of the finished powder in real time, evaluating the quality of the finished powder, and using an adaptive control strategy to feedback and adjust the key parameters of the powder production equipment in the production process based on the quality analysis results of the finished powder. Further, the electronic device 500 may also include a user interface 508. Of course, Figure 4 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 4 One or more components of an electronic device are shown.

[0131] Example 4

[0132] Figure 5 Schematic diagram of a storage medium structure provided by an embodiment of the present application. Figure 5 As shown, a storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the storage medium 600. When the computer-readable instructions are executed by the processor, an online control method for a powder production device according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0133] It should be understood that the methods, apparatuses, and devices of the present application can be implemented in many ways. For example, the methods, apparatuses, and devices of the present application can be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present application are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present application can also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers a recording medium storing a program for executing the method according to the present application.

[0134] In addition, the parts of the above-mentioned technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive redundancy.

[0135] The specific implementation modes as described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation mode of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An online control method for powder production equipment, characterized in that: include: Use sensors to collect key parameters in the powder production process in real time, and pre-process the collected key parameters in the powder production process; According to the key parameters collected in the powder production process, a mathematical model of the powder production process is established to analyze the changes in the key parameters of the powder production process; Real-time collection of key parameters of finished powder products at the export site to evaluate the quality of finished powder products; According to the quality analysis results of powder finished products, adaptive control strategy is used to feedback and adjust the key parameters of powder production equipment in the production process; During a T period of time in the powder production process, key parameters in the powder production process are alternately collected through a first data collection window and a second data collection window; wherein the time length of the first data collection window is greater than the time length of the second data collection window; Determine the real-time data in a time period T during the powder production process according to the real-time data segments correspondingly collected by the first data collection window and the second data collection window; Controlling production parameters of the powder production process according to the real-time data; Determining the real-time data in a time period T during the powder production process according to the real-time data segments corresponding to the first data acquisition window and the second data acquisition window includes: Averaging the data collected by the first data collection window to obtain first average data; Averaging the data collected by the second data collection window to obtain second average data; The first average data is alternately corrected using the second average data to complete the processing of key parameters in the powder production process; The adaptive control strategy includes: A qualified threshold value for the quality of the powder finished product is set. When the quality of the powder finished product is lower than the qualified threshold value for the quality of the powder finished product, the powder finished product is judged to be unqualified. Otherwise, the powder finished product is judged to be qualified. When the powder product is unqualified, the state at time g in the powder production process is estimated. The specific formula is: in, represents the estimated value of the state at time g in the powder production process, represents the estimated value of the state at time g-1 in the powder production process, G g represents the Kalman gain, y g represents the observed value at time g in the powder production process, and H represents the observation matrix; The error parameters at time g in the powder production process are identified, and the specific formula is: Among them, θ g represents the parameter estimation vector at time g in the powder production process, θ g-1 represents the parameter estimation vector at time g-1 in the powder production process, Zy g represents the gain matrix, φ g represents the regression vector at time g in the powder production process; According to the state estimation and parameter identification at time g in the powder production process, the key parameters of the powder production equipment are dynamically adjusted. The specific formula for the control input of the powder production equipment is: Among them, u g represents the control input of the powder production equipment at time g, and ζ represents the adaptive control gain matrix.

2. An online control method for powder production equipment according to claim 1, characterized in that: The mathematical model for establishing the powder production process comprises: a first equilibrium model, a second equilibrium model, and a third equilibrium model; In the production process of powders, a first balance model is established according to the feed of powder raw materials, the discharge of powders and the mass of substances produced or consumed in the reaction process to obtain the feed flow rate of powder production, the discharge flow rate of powder production and the production or consumption of powder production reaction. The rate of change of the total amount of powder raw materials in powder production with the powder production time is the sum of the feed flow rate of powder production, the discharge flow rate of powder production and the production or consumption of powder production reaction; According to the input, output, generation and consumption of energy in the powder production equipment, a second balance model is established to obtain the heat input into the powder production equipment, the heat output of the powder production equipment and the working energy of the powder production equipment. The total energy in the powder production equipment is the sum of the heat input into the powder production equipment, the heat output of the powder production equipment and the working energy of the powder production equipment. According to the diffusion, convection and reaction factors in the powder production process, a third equilibrium model is established to express the balance between the concentration of components in the powder production process and the convection term of the components moving with the fluid in the powder production process, and the diffusion term of the components in the powder production process and the production or consumption rate of the components in the powder production reaction.

3. An online control method for powder production equipment according to claim 2, characterized in that: The specific formula for the production or consumption rate of the components in the powder production reaction is: Among them, R i represents the production or consumption rate of the component in the i-th powder production reaction, K i represents the rate constant of the i-th powder production reaction, C q represents the concentration of the qth component in the powder production process, represents the reaction order of the qth component in the i-th powder production reaction, and G represents the total number of reaction components in the i-th powder production reaction.

4. An online control method for powder production equipment according to claim 3, characterized in that: The quality assessment of the powder finished product includes: The average particle size of the finished powder, the moisture content of the finished powder, the color difference of the finished powder, the density of the finished powder and the fluidity of the finished powder are weightedly summed.

5. An online control system for powder production equipment, used to implement an online control method for powder production equipment according to any one of claims 1 to 4, characterized in that: include: Data acquisition module, model building module, quality assessment module and control adjustment module; The data acquisition module is used to use sensors to collect key parameters in the powder production process in real time, including humidity, temperature, density, particle size and composition, and pre-process the collected key parameters in the powder production process; The model building module is used to build a mathematical model of the powder production process based on the key parameters collected during the powder production process, and analyze changes in the key parameters of the powder during the production process; The quality assessment module is used to collect key parameters of finished powder products at the outlet in real time and assess the quality of the finished powder products; The control adjustment module is used to feedback and adjust key parameters of the powder production equipment during the production process based on the powder finished product quality analysis results and using an adaptive control strategy.

6. An online control system for powder production equipment according to claim 5, characterized in that: The control adjustment module includes: a state estimation unit, an error parameter identification unit and a control input unit; The state estimation unit is used to estimate the state at time g during the powder production process; The error parameter identification unit is used to identify the error parameter at time g during the powder production process; The control input unit is used to calculate the control input of the powder production equipment according to the state estimation and parameter identification at time g in the powder production process.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of an online control method for powder production equipment according to any one of claims 1 to 4 are implemented.

8. A storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, the steps of an online control method for powder production equipment described in any one of claims 1-4 are executed.

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