Operating control system of double-roller extrusion flour mill based on Internet of Things

Abstract

The invention discloses a double-roller extrusion flour mill operation control system based on the Internet of Things, and particularly relates to the field of the Internet of Things, and the system comprises a monitoring area determination module, a parameter setting module, a data acquisition module, a data preprocessing module, a data analysis module, a data comprehensive analysis module, a judgment early warning module and a man-machine interaction module. And the monitoring area determination module is used for determining the monitoring range of the flour mill. Parameters of the dryer are set through the parameter setting module. A first grinding and drying key information value is acquired through a data acquisition module. A second grinding and drying key information value is obtained through the data preprocessing module, and a third grinding key information value is obtained through the data analysis module. And a fourth grinding key information value is obtained through a data comprehensive analysis module. Whether the working quality of the flour mill reaches the standard or not is judged through the judgment early warning module, a visual interface is provided through the man-machine interaction module, and the performance of the flour mill is comprehensively and effectively fed back.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology, and more specifically, to an IoT-based operating control system for a double-roller extrusion mill. Background Technology

[0002] Early grinding mills relied primarily on traditional heating methods and simple control systems, lacking intelligent and automated capabilities. Manual monitoring and adjustments were required during operation, resulting in low production efficiency and inconsistent product quality. As people's living standards improve, the demand for ground products continues to grow. Traditional sun-drying methods are heavily influenced by weather and are inefficient, failing to meet market demand for dried ground products. The development of IoT technology has made intelligent grinding mills possible. Through IoT, remote monitoring, data collection, and intelligent analysis of dryers can be achieved, improving production efficiency and product quality. With the continuous development of IoT, AI, and big data technologies, IoT-based double-roller extrusion grinding mill operation control systems will usher in even broader development prospects.

[0003] Traditional grinding mill operation control systems include a user management module, a parameter setting module, an operation control module, a data monitoring module, a fault alarm module, and a remote communication and monitoring module. The user management module manages user accounts and permissions; the parameter setting module allows users to set dryer parameters; the operation control module provides functions for starting, stopping, and pausing dryer operation; the data monitoring module monitors and displays the dryer's operating status and key parameters in real time; the fault alarm module issues relevant alarm information; and the remote communication and monitoring module uses IoT technology to achieve real-time communication and data transmission between the dryer and a remote monitoring center. Through the collaborative work of these multiple modules, the traditional grinding mill operation control system achieves comprehensive machine monitoring, intelligent operation and maintenance, and efficient management.

[0004] However, in actual use, it still has some shortcomings, such as the data collection is not comprehensive enough. The parameters collected by the traditional mill operation control system are not comprehensive enough and cannot accurately reflect the actual situation of milling and drying, resulting in inaccurate subsequent parameter setting adjustments. It does not evaluate the comprehensive ability of the mill to dry and grind, and cannot provide timely feedback on the milling and drying status and whether the milling and drying meets the standards. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an Internet of Things-based operation control system for a double-roller extrusion mill, which solves the problems mentioned in the background art through the following solutions.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an Internet of Things-based operation control system for a double-roller extrusion mill, comprising a system operation database, a system central manager, and a user information terminal, and further comprising: a monitoring area determination module, a parameter setting module, a data acquisition module, a data preprocessing module, a data analysis module, a data comprehensive analysis module, a judgment and early warning module, and a human-machine interaction module; The system operation database includes all data information of the grinding mill operation control system and collects data information output by each module in real time; the system central processor is used to centrally control the text instructions output by each module; the user information terminal is a device for receiving information output from the grinding mill operation control system. The monitoring area determination module is used to determine the monitoring range of the grinding mill and divide it into individual sub-area monitoring areas in an equal area manner, which are sequentially marked as 1, 2, ..., i, ..., n; The parameter setting module is used to set the parameters of the dryer according to different grinding characteristics and drying requirements; The data acquisition module includes a parameter acquisition unit, which is used to acquire key information values ​​of the first grinding and drying process, including environmental parameters and equipment parameters, and transmit the acquired information to the data preprocessing module. The data preprocessing module includes an environmental parameter preprocessing unit and an equipment parameter preprocessing unit, which are used to preprocess the first key information value of grinding and drying to obtain the second key information value of grinding and drying, and then transmit it to the data analysis module. The data analysis module includes an environmental parameter analysis unit and an equipment parameter analysis unit. It further analyzes the key information values ​​of the second grinding and drying process to obtain the key information values ​​of the third grinding process, and then transmits them to the data comprehensive analysis module. The data comprehensive analysis module is used to construct a data comprehensive analysis model, perform comprehensive data analysis on the third key information value of grinding, obtain the fourth key information value of grinding, namely the comprehensive evaluation index of grinding and drying, and transmit it to the judgment and early warning module. The judgment and early warning module is used to construct a comprehensive evaluation standard value for grinding and drying, compare the comprehensive evaluation index for grinding and drying with the comprehensive evaluation standard value for grinding and drying, judge whether the working quality of the grinding mill meets the standard, and transmit relevant alarm information to the parameter setting module and the human-machine interaction module. The human-computer interaction module is used to provide a visual interface, display various parameter information of the grinding mill in real time, and send it to the user information terminal simultaneously.

[0007] Preferably, the environmental parameters include dryer temperature and humidity parameters and drying process parameters. The dryer temperature and humidity parameters specifically include drying chamber temperature, drying chamber humidity, set temperature, and set humidity, which are respectively labeled as T, RH, T1, and RH1. The drying process parameters include wind speed, drying time, pressure, grinding powder loading amount, and grinding powder loading density, which are respectively labeled as v, t, F, G, and ρ.

[0008] Preferably, the equipment parameters include equipment operating parameters and equipment performance parameters. The equipment operating parameters include the drying chamber volume, heating power, temperature sensor accuracy, and humidity sensor accuracy, which are respectively labeled as V, P, η1, and η2. The equipment performance parameters include power consumption, noise intensity, and maintenance frequency, which are respectively labeled as E, I, and η3.

[0009] Preferably, the environmental parameter preprocessing unit is used to establish an environmental parameter preprocessing model, import the first key information value of grinding and drying collected by the data acquisition module into the environmental parameter preprocessing model, and calculate the dryer temperature and humidity assessment value and the drying process assessment value. The dryer temperature and humidity assessment value is specifically expressed as follows: , y1 represents the temperature and humidity assessment value of the dryer of the target monitoring mill, T i RH represents the drying chamber temperature of the target monitoring mill in the i-th sub-area monitoring region. i Let T represent the drying chamber humidity of the target monitoring mill in the i-th sub-area monitoring region, T represent the drying chamber temperature of the target monitoring mill, RH represent the drying chamber humidity of the target monitoring mill, T1 represent the set temperature of the target monitoring mill, RH1 represent the set humidity of the target monitoring mill, α1, α2, α3, and α4 represent the influence coefficients of drying chamber temperature, drying chamber humidity, set temperature, and set humidity on the temperature and humidity evaluation value of the dryer, respectively, and b1 and b2 are known constants; the specific evaluation value of the drying process is expressed as follows: , y2 represents the evaluation value of the drying process of the target monitoring mill, v represents the wind speed of the target monitoring mill, t represents the drying time of the target monitoring mill, and F i Let G represent the pressure of the target monitoring mill in the i-th sub-area monitoring region, G represent the milling load of the target monitoring mill, ρ represent the milling load density of the target monitoring mill, β1, β2, β3, β4 and β5 represent the influence coefficients of wind speed, drying time, pressure, milling load and milling load density on the evaluation value of the drying process, respectively, and b3, b4, b5 and b6 are known constants.

[0010] Preferably, the equipment parameter preprocessing unit is used to establish an equipment parameter preprocessing model, import the first grinding and drying key information value collected by the data acquisition module into the equipment parameter preprocessing model, and calculate the equipment operation evaluation value and the equipment performance evaluation value. The equipment operation evaluation value is specifically expressed as follows: , y3 represents the equipment operation evaluation value of the target monitoring grinding mill, V represents the drying chamber volume of the target monitoring grinding mill, P represents the heating power of the target monitoring grinding mill, η1 represents the temperature sensor accuracy of the target monitoring grinding mill, η2 represents the humidity sensor accuracy of the target monitoring grinding mill, ε1, ε2, ε3 and ε4 represent the influence coefficients of drying chamber volume, heating power, temperature sensor accuracy and humidity sensor accuracy on the equipment operation evaluation value, respectively, and c1 is a known constant; the equipment performance evaluation value is expressed as: , y4 represents the equipment performance evaluation value of the target monitoring grinding mill, E represents the power consumption of the target monitoring grinding mill, I represents the noise intensity of the target monitoring grinding mill, η3 represents the maintenance frequency of the target monitoring grinding mill, γ1, γ2 and γ3 represent the influence coefficients of power consumption, noise intensity and maintenance frequency on the equipment performance evaluation value, respectively, and c2 is a known constant.

[0011] Preferably, the environmental parameter analysis unit is used to construct an environmental parameter analysis model, importing the dryer temperature and humidity assessment values ​​and the drying process assessment values ​​into the environmental parameter analysis model to calculate the environmental parameter assessment values, specifically expressed as follows: , y e y1 represents the environmental parameter assessment value of the target monitoring mill, y2 represents the dryer temperature and humidity assessment value of the target monitoring mill, and λ1 and λ2 represent the influence coefficients of the dryer temperature and humidity assessment value and the drying process assessment value on the environmental parameter assessment value, respectively.

[0012] Preferably, the equipment parameter analysis unit is used to establish an equipment parameter analysis model, import the equipment operation evaluation value and the equipment performance evaluation value into the equipment parameter analysis model, and calculate the equipment parameter evaluation value, specifically expressed as follows: , y d y3 represents the equipment parameter evaluation value of the target monitoring grinding mill, y4 represents the equipment operation evaluation value of the target monitoring grinding mill, and λ3 and λ4 represent the influence coefficients of the equipment operation evaluation value and the equipment performance evaluation value on the equipment parameter evaluation value, respectively.

[0013] Preferably, the acquisition of the fourth key information value for grinding involves importing environmental parameter assessment values ​​and equipment parameter assessment values ​​into a comprehensive data analysis model to calculate the fourth key information value for grinding, namely the comprehensive evaluation index for grinding and drying, specifically expressed as follows: , φ represents the comprehensive evaluation index of grinding and drying of the target monitoring grinding mill, y e y represents the environmental parameter assessment value of the target monitoring grinding mill. d y represents the equipment parameter evaluation value of the target monitoring grinding mill. e标 This represents the environmental parameter evaluation standard value of the target monitoring grinding mill, y d标 This indicates the standard values ​​for evaluating the equipment parameters of the target monitoring grinding mill.

[0014] Preferably, the comprehensive evaluation standard value for grinding and drying is marked as φ. 标 When φ>φ 标 When φ < φ, it indicates that the comprehensive evaluation index for grinding and drying is greater than the standard value for comprehensive evaluation of grinding and drying, and the grinding and drying quality meets the standard; when φ < φ 标 When the comprehensive evaluation index of grinding and drying is less than the comprehensive evaluation standard value of grinding and drying, the grinding and drying quality does not meet the standard. The information is transmitted to the parameter setting module, and the parameters of the target monitoring grinding mill are adjusted according to the monitoring and judgment results.

[0015] The technical effects and advantages of this invention are as follows: 1. This invention collects key information values ​​for the first grinding and drying process through the parameter acquisition unit of the data acquisition module, including the temperature and humidity parameters of the dryer, the drying process parameters, the equipment operating parameters, and the equipment performance parameters. It also divides the unit sub-area monitoring area through the monitoring area determination module, which improves the accuracy of data acquisition and collects the parameters affecting the performance of the grinding mill more comprehensively, providing effective data support for subsequent analysis and processing. 2. This invention calculates the dryer temperature and humidity assessment value, drying process assessment value, equipment operation assessment value, equipment performance assessment value, environmental parameter assessment value, equipment parameter assessment value, and grinding drying comprehensive assessment index through the data preprocessing module, data analysis module, and data comprehensive analysis module. It accurately reflects the real-time status of the grinding mill and determines whether the drying of the grinding mill meets the standards through the judgment and early warning module, and adjusts the parameter settings of the grinding mill according to the judgment results. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system structure of the present invention.

[0017] Figure 2 This is a schematic diagram of the method steps of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] As attached Figure 1 The control system for a double-roll extrusion mill based on the Internet of Things includes a system operation database, a system central manager, and a user information terminal. It also includes a monitoring area determination module, a parameter setting module, a data acquisition module, a data preprocessing module, a data analysis module, a data comprehensive analysis module, a judgment and early warning module, and a human-machine interaction module.

[0020] The output of the monitoring area determination module is connected to the input of the parameter setting module via telecommunications. The output of the parameter setting module is connected to the input of the data acquisition module via telecommunications. The output of the data acquisition module is connected to the input of the data preprocessing module via telecommunications. The output of the data preprocessing module is connected to the input of the data analysis module via telecommunications. The output of the data analysis module is connected to the input of the data comprehensive analysis module via telecommunications. The output of the data comprehensive analysis module is connected to the input of the judgment and early warning module via telecommunications. The output of the judgment and early warning module is connected to the inputs of the parameter setting module and the human-computer interaction module via telecommunications. The output of the system central processing unit is connected to the inputs of each module via telecommunications. The output of each module is connected to the input of the system operating database via telecommunications.

[0021] The system's operating database contains all data information from the grinding mill's operation and control system, and collects data output from each module in real time; the system's central processing unit is used to centrally control the text commands output by each module; and the user information terminal is a device for receiving information output from the grinding mill's operation and control system. Monitoring area determination module: used to determine the monitoring range of the grinding mill and divide it into individual sub-area monitoring areas in an equal area manner, which are sequentially marked as 1, 2, ..., i, ..., n.

[0022] Parameter setting module: Used to set the parameters of the dryer according to different grinding characteristics and drying requirements.

[0023] This embodiment requires specific explanation of setting the parameters of the dryer. First, it's essential to understand the characteristics of the powder. Differences in the composition, structure, and moisture content of different powders lead to different requirements for drying temperatures. A drying temperature between 50℃ and 70℃ is generally suitable for the product. Powders with higher moisture content require lower drying temperatures to avoid excessive dehydration and spoilage. Different drying equipment has varying degrees of precision in controlling the drying temperature. Selecting appropriate drying equipment ensures stable and accurate drying temperatures. By selecting suitable temperature, humidity, airflow direction, drying time, and loading capacity and arrangement, a scientifically sound and reasonable setting can achieve an efficient, high-quality, and energy-saving drying process, providing the market with dried powder products that are delicious, nutritious, and have a long shelf life.

[0024] Data acquisition module: includes parameter acquisition unit, used to collect key information values ​​of the first grinding and drying process, including environmental parameters and equipment parameters, and transmit the collected information to data preprocessing module.

[0025] Furthermore, the environmental parameters include dryer temperature and humidity parameters and drying process parameters. The dryer temperature and humidity parameters specifically include drying chamber temperature, drying chamber humidity, set temperature, and set humidity, which are labeled as T, RH, T1, and RH1, respectively. The drying process parameters include wind speed, drying time, pressure, grinding mill loading, and grinding mill loading density, which are labeled as v, t, F, G, and ρ, respectively.

[0026] This embodiment specifically illustrates that by inserting a thermocouple into the drying chamber and connecting it to a thermometer or data logger, real-time monitoring and recording of the drying chamber temperature can be achieved; installing a humidity sensor in the drying chamber of the grinding mill allows for real-time monitoring and recording of humidity changes; a suitable location can be selected to install or handheld an anemometer in the drying chamber of the grinding mill to monitor and record real-time wind speed changes; and an airflow and air pressure monitoring device can be installed in the drying chamber to monitor real-time changes in airflow and air pressure.

[0027] Furthermore, the equipment parameters include equipment operating parameters and equipment performance parameters. The equipment operating parameters include the drying chamber volume, heating power, temperature sensor accuracy, and humidity sensor accuracy, which are marked as V, P, η1, and η2, respectively. The equipment performance parameters include power consumption, noise intensity, and maintenance frequency, which are marked as E, I, and η3, respectively.

[0028] Data preprocessing module: includes an environmental parameter preprocessing unit and an equipment parameter preprocessing unit, used to preprocess the first key information value of grinding and drying to obtain the second key information value of grinding and drying, and then transmit it to the data analysis module.

[0029] Furthermore, the environmental parameter preprocessing unit is used to establish an environmental parameter preprocessing model. It imports the first key information values ​​for grinding and drying collected by the data acquisition module into the environmental parameter preprocessing model to calculate the dryer temperature and humidity assessment values ​​and the drying process assessment values. The dryer temperature and humidity assessment values ​​are specifically expressed as follows: , y1 represents the temperature and humidity assessment value of the dryer of the target monitoring mill, T i RH represents the drying chamber temperature of the target monitoring mill in the i-th sub-area monitoring region. i Let T represent the drying chamber humidity of the target monitoring mill in the i-th sub-area monitoring region, T represent the drying chamber temperature of the target monitoring mill, RH represent the drying chamber humidity of the target monitoring mill, T1 represent the set temperature of the target monitoring mill, RH1 represent the set humidity of the target monitoring mill, α1, α2, α3, and α4 represent the influence coefficients of drying chamber temperature, drying chamber humidity, set temperature, and set humidity on the temperature and humidity evaluation value of the dryer, respectively, and b1 and b2 are known constants; the specific evaluation value of the drying process is expressed as follows: , y2 represents the evaluation value of the drying process of the target monitoring mill, v represents the wind speed of the target monitoring mill, t represents the drying time of the target monitoring mill, and F i Let G represent the pressure of the target monitoring mill in the i-th sub-area monitoring region, G represent the milling load of the target monitoring mill, ρ represent the milling load density of the target monitoring mill, β1, β2, β3, β4 and β5 represent the influence coefficients of wind speed, drying time, pressure, milling load and milling load density on the evaluation value of the drying process, respectively, and b3, b4, b5 and b6 are known constants.

[0030] Furthermore, the equipment parameter preprocessing unit is used to establish an equipment parameter preprocessing model. It imports the first key information values ​​for grinding and drying collected by the data acquisition module into the equipment parameter preprocessing model to calculate the equipment operation evaluation value and the equipment performance evaluation value. The equipment operation evaluation value is specifically expressed as follows: , y3 represents the equipment operation evaluation value of the target monitoring grinding mill, V represents the drying chamber volume of the target monitoring grinding mill, P represents the heating power of the target monitoring grinding mill, η1 represents the temperature sensor accuracy of the target monitoring grinding mill, η2 represents the humidity sensor accuracy of the target monitoring grinding mill, ε1, ε2, ε3 and ε4 represent the influence coefficients of drying chamber volume, heating power, temperature sensor accuracy and humidity sensor accuracy on the equipment operation evaluation value, respectively, and c1 is a known constant; the equipment performance evaluation value is expressed as: , y4 represents the equipment performance evaluation value of the target monitoring grinding mill, E represents the power consumption of the target monitoring grinding mill, I represents the noise intensity of the target monitoring grinding mill, η3 represents the maintenance frequency of the target monitoring grinding mill, γ1, γ2 and γ3 represent the influence coefficients of power consumption, noise intensity and maintenance frequency on the equipment performance evaluation value, respectively, and c2 is a known constant.

[0031] Data analysis module: including environmental parameter analysis unit and equipment parameter analysis unit, further analyzes the key information values ​​of the second grinding and drying process to obtain the key information values ​​of the third grinding process, and transmits them to the data comprehensive analysis module.

[0032] Furthermore, the environmental parameter analysis unit is used to construct an environmental parameter analysis model. The dryer's temperature and humidity assessment values ​​and the drying process assessment values ​​are imported into the environmental parameter analysis model to calculate the environmental parameter assessment values, specifically expressed as follows: , y e y1 represents the environmental parameter assessment value of the target monitoring mill, y2 represents the dryer temperature and humidity assessment value of the target monitoring mill, and λ1 and λ2 represent the influence coefficients of the dryer temperature and humidity assessment value and the drying process assessment value on the environmental parameter assessment value, respectively.

[0033] Furthermore, the equipment parameter analysis unit is used to establish an equipment parameter analysis model. It imports equipment operation evaluation values ​​and equipment performance evaluation values ​​into the model to calculate the equipment parameter evaluation values, specifically expressed as follows: , y d y3 represents the equipment parameter evaluation value of the target monitoring grinding mill, y4 represents the equipment operation evaluation value of the target monitoring grinding mill, and λ3 and λ4 represent the influence coefficients of the equipment operation evaluation value and the equipment performance evaluation value on the equipment parameter evaluation value, respectively.

[0034] Data Comprehensive Analysis Module: Used to build a data comprehensive analysis model, perform comprehensive data analysis on the third key information value of grinding, obtain the fourth key information value of grinding, namely the comprehensive evaluation index of grinding and drying, and transmit it to the judgment and early warning module.

[0035] Furthermore, the acquisition of the fourth key information value for grinding involves importing environmental parameter assessment values ​​and equipment parameter assessment values ​​into a comprehensive data analysis model to calculate the fourth key information value for grinding, namely the comprehensive evaluation index for grinding and drying, specifically expressed as follows: , φ represents the comprehensive evaluation index of grinding and drying of the target monitoring grinding mill, y ey represents the environmental parameter assessment value of the target monitoring grinding mill. d y represents the equipment parameter evaluation value of the target monitoring grinding mill. e标 This represents the environmental parameter evaluation standard value of the target monitoring grinding mill, y d标 This indicates the standard values ​​for evaluating the equipment parameters of the target monitoring grinding mill.

[0036] Judgment and early warning module: It is used to construct the comprehensive evaluation standard value of grinding and drying, compare the comprehensive evaluation index of grinding and drying with the comprehensive evaluation standard value of grinding and drying, judge whether the working quality of the grinding mill meets the standard, and transmit relevant alarm information to the parameter setting module and the human-machine interaction module.

[0037] Furthermore, the comprehensive evaluation standard value for grinding and drying is marked as φ. 标 When φ>φ 标 When φ < φ, it indicates that the comprehensive evaluation index for grinding and drying is greater than the standard value for comprehensive evaluation of grinding and drying, and the grinding and drying quality meets the standard; when φ < φ 标 When the comprehensive evaluation index of grinding and drying is less than the comprehensive evaluation standard value of grinding and drying, the grinding and drying quality does not meet the standard. The information is transmitted to the parameter setting module, and the parameters of the target monitoring grinding mill are adjusted according to the monitoring and judgment results.

[0038] Human-computer interaction module: This module provides a visual interface to display various parameter information of the grinding mill in real time and sends it to the user information terminal simultaneously.

[0039] In this embodiment, it is important to note that the menu bar of the visual interface provides user navigation and setting options, including file operations, view control, and file import and export. The toolbar includes commonly used tool buttons to facilitate user interaction with the interface and displays the parameters and working status of the target monitoring mill in real time, including dryer temperature and humidity parameters, drying process parameters, equipment operating parameters, equipment performance parameters, dryer temperature and humidity assessment values, drying process assessment values, equipment operating assessment values, equipment performance assessment values, environmental parameter assessment values, equipment parameter assessment values, and a comprehensive grinding and drying assessment index.

[0040] like Figure 2 As shown, this invention provides a method for controlling the operation of a grinding mill based on the Internet of Things, the steps of which are as follows: S1: Determine the monitoring range of the grinding mill and divide it into individual sub-area monitoring areas in an equal area manner, and label them sequentially as 1, 2, ..., i, ..., n; S2: Set the parameters of the dryer according to different grinding characteristics and drying requirements; S3: Collect key information values ​​for the first grinding and drying process, including environmental parameters and equipment parameters; S4: Perform data preprocessing on the first key information value for grinding and drying to obtain the second key information value for grinding and drying; S5: Further analysis of the second key information value for grinding and drying is conducted to obtain the third key information value for grinding; S6: Construct a comprehensive data analysis model to conduct a comprehensive data analysis on the third key information value of grinding and obtain the fourth key information value of grinding, namely the comprehensive evaluation index of grinding and drying. S7: Construct a comprehensive evaluation standard value for grinding and drying, compare the comprehensive evaluation index for grinding and drying with the comprehensive evaluation standard value for grinding and drying, determine whether the working quality of the grinding mill meets the standard, and transmit relevant alarm information; S8: Provides a visual interface that displays various parameter information of the grinding mill in real time and sends it to the user information terminal simultaneously.

[0041] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An Internet of Things-based operation control system for a pair-roller extrusion flour mill, comprising a system operation database, a system central manager, and a user information terminal, characterized in that, Also include: Monitoring area determination module, parameter setting module, data acquisition module, data preprocessing module, data analysis module, data comprehensive analysis module, judgment warning module and man-machine interaction module; The system operation database is all data information of the flour mill operation control system, and real-time collection of data information output by each module; The central processor of the system is used for controlling the information text instructions output by each module; the user information terminal is an information output device receiving the flour mill operation control system; The monitoring area determination module is used for determining the monitoring range of the flour mill, and dividing it into single sub-area monitoring areas in an equal area manner, and sequentially marking them as 1, 2, …, i, …, n; The parameter setting module is used for setting the parameters of the dryer according to different grinding characteristics and drying requirements; The data acquisition module includes a parameter acquisition unit, which is used for acquiring first flour drying key information values, including environmental parameters and equipment parameters, and transmitting the acquired information to the data preprocessing module; The data preprocessing module includes an environmental parameter preprocessing unit and an equipment parameter preprocessing unit, which are used for data preprocessing of the first flour drying key information values to obtain second flour drying key information values, and transmitting them to the data analysis module; The data analysis module includes an environmental parameter analysis unit and an equipment parameter analysis unit, which are used for further analyzing the second flour drying key information values to obtain third flour key information values, and transmitting them to the data comprehensive analysis module; The data comprehensive analysis module is used for constructing a data comprehensive analysis model, performing comprehensive data analysis on the third flour key information values to obtain fourth flour key information values, i.e. flour drying comprehensive evaluation index, and transmitting them to the judgment warning module; The judgment warning module is used for constructing a flour drying comprehensive evaluation standard value, comparing the flour drying comprehensive evaluation index with the flour drying comprehensive evaluation standard value, judging whether the working quality of the flour mill meets the standard, and transmitting related warning information to the parameter setting module and the man-machine interaction module; The man-machine interaction module is used for providing a visual interface, displaying various parameter information of the flour mill in real time, and synchronously sending them to the user information terminal.

2. The running control system of the pair-roller extruding flour mill based on the Internet of Things according to claim 1, characterized in that: The environmental parameters include dryer temperature and humidity parameters and drying process parameters, and the dryer temperature and humidity parameters specifically include drying chamber temperature, drying chamber humidity, set temperature and set humidity, which are marked as T, RH, T1 and RH1 respectively; the drying process parameters include wind speed, drying time, pressure, flour loading and flour loading density, which are marked as v, t, F, G and p respectively.

3. The running control system of the pair-roller extruding flour mill based on the internet of things according to claim 1, characterized in that: The equipment parameters include equipment operation parameters and equipment performance parameters, and the equipment operation parameters include drying chamber volume, heating power, temperature sensor accuracy and humidity sensor accuracy, which are marked as V, P, η1 and η2 respectively; the equipment performance parameters include consumed electric energy, noise intensity and maintenance frequency, which are marked as E, I and η3 respectively.

4. The running control system of the pair-roller extruding flour mill based on the internet of things according to claim 1, characterized in that: The environment parameter preprocessing unit is used to establish an environment parameter preprocessing model, and the first flour milling and drying key information value collected by the data collection module is introduced into the environment parameter preprocessing model to calculate a dryer temperature and humidity evaluation value and a drying process evaluation value. The dryer temperature and humidity evaluation value is specifically represented as: ， y1 represents the drying oven temperature and humidity evaluation value of the target monitoring mill, T i represents the drying chamber temperature of the target monitoring mill in the i-th sub-area monitoring region, RH i represents the drying chamber humidity of the target monitoring mill in the i-th sub-area monitoring region, T represents the drying chamber temperature of the target monitoring mill, RH represents the drying chamber humidity of the target monitoring mill, T1 represents the set temperature of the target monitoring mill, RH1 represents the set humidity of the target monitoring mill, α1, α2, α3 and α4 respectively represent the influence coefficients of the drying chamber temperature, the drying chamber humidity, the set temperature and the set humidity on the drying oven temperature and humidity evaluation value, b1 and b2 are known constants; the drying process evaluation value is specifically represented as: ， y2 represents the drying process evaluation value of the target monitored mill, v represents the air speed of the target monitored mill, t represents the drying time of the target monitored mill, F i represents the pressure of the target monitored mill in the i-th sub-area monitoring region, G represents the mill load of the target monitored mill, p represents the mill load density of the target monitored mill, b1, b2, b3, b4, and b5 respectively represent the influence coefficients of the air speed, the drying time, the pressure, the mill load, and the mill load density on the drying process evaluation value, and b3, b4, b5, and b6 are known constants.

5. The operation control system of the roll press pulverizing mill based on the Internet of Things according to claim 1, characterized in that: The device parameter preprocessing unit is used to establish a device parameter preprocessing model, and the first flour milling and drying key information value collected by the data collection module is introduced into the device parameter preprocessing model to calculate a device operation evaluation value and a device performance evaluation value. The device operation evaluation value is specifically represented as: ， y3 represents the device operation evaluation value of the target monitored flour mill, V represents the volume of the drying chamber of the target monitored flour mill, P represents the heating power of the target monitored flour mill, η1 represents the temperature sensor accuracy of the target monitored flour mill, η2 represents the humidity sensor accuracy of the target monitored flour mill, ε1, ε2, ε3 and ε4 respectively represent the influence coefficients of the volume of the drying chamber, the heating power, the temperature sensor accuracy and the humidity sensor accuracy on the device operation evaluation value, and c1 is a known constant; the device performance evaluation value is represented as: ， y4 represents the device performance evaluation value of the target monitored flour mill, E represents the consumed power of the target monitored flour mill, I represents the noise intensity of the target monitored flour mill, η3 represents the maintenance frequency of the target monitored flour mill, γ1, γ2 and γ3 respectively represent the influence coefficients of the consumed power, the noise intensity and the maintenance frequency on the device performance evaluation value, and c2 is a known constant.

6. The operation control system of a pair-roller extruding mill based on the Internet of Things according to claim 1, characterized in that: The environment parameter analysis unit is used to construct an environment parameter analysis model, and the dryer temperature and humidity evaluation value and the drying process evaluation value are introduced into the environment parameter analysis model to calculate an environment parameter evaluation value, which is specifically represented as: ， y e y represents the evaluation value of the environmental parameter of the target monitored mill, y1 represents the evaluation value of the dryer temperature and humidity of the target monitored mill, y2 represents the evaluation value of the drying process of the target monitored mill, and λ1 and λ2 represent the influence coefficients of the evaluation value of the dryer temperature and humidity and the evaluation value of the drying process on the evaluation value of the environmental parameter, respectively.

7. The running control system of the pair-roller extruding flour mill based on the internet of things according to claim 1, characterized in that: The device parameter analysis unit is used to establish a device parameter analysis model, and the device operation evaluation value and the device performance evaluation value are introduced into the device parameter analysis model to calculate a device parameter evaluation value, which is specifically represented as: ， y d y3 represents the equipment operation evaluation value of the target monitored mill, y4 represents the equipment performance evaluation value of the target monitored mill, and λ3 and λ4 represent the influence coefficients of the equipment operation evaluation value and the equipment performance evaluation value on the equipment parameter evaluation value, respectively.

8. The operation control system of a pair-roller extruding mill based on the Internet of Things according to claim 1, characterized in that: The fourth flour milling key information value is obtained, the environment parameter evaluation value and the device parameter evaluation value are introduced into the data comprehensive analysis model, and the fourth flour milling key information value, i.e. the flour milling and drying comprehensive evaluation index, is calculated, which is specifically represented as: ， φ represents the comprehensive evaluation index of the grinding and drying of the target monitored mill, y e represents the environmental parameter evaluation value of the target monitored mill, y d represents the equipment parameter evaluation value of the target monitored mill, y e标 represents the environmental parameter evaluation standard value of the target monitored mill, y d标 represents the equipment parameter evaluation standard value of the target monitored mill.

9. The running control system of the pair-roller extrusion flour mill based on the Internet of Things according to claim 1, characterized in that: The flour milling and drying comprehensive evaluation standard value is marked as φ 标 When φ>φ 标 , it indicates that the flour milling and drying comprehensive evaluation index is greater than the flour milling and drying comprehensive evaluation standard value, and the flour milling and drying quality meets the standard; when φ<φ 标 , it indicates that the flour milling and drying comprehensive evaluation index is less than the flour milling and drying comprehensive evaluation standard value, and the flour milling and drying quality does not meet the standard, and the information is transmitted to the parameter setting module to adjust the parameters of the target monitoring flour mill according to the monitoring judgment result.

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