A control system for a winnowing machine of konjac refined powder

Abstract

The present invention relates to a pneumatic separator control system, and discloses a control system for a konjac refined powder pneumatic separator. The system includes a wind pressure data acquisition module, a wind pressure fluctuation characteristic analysis module, a wind speed adjustment strategy matching module, and a wind speed control module. By monitoring the minute fluctuations of the wind pressure at the discharge port, the system can infer the distribution state of the material in the air flow in real time, and accurately regulate the wind speed according to the fluctuation characteristics, avoiding the limitation that traditional material sensors are vulnerable to environmental interference. Through the indirect sensing strategy based on the principle of fluid mechanics, the present invention significantly reduces the system complexity and maintenance cost, and improves the sensitivity and dynamic optimization ability of the pneumatic separation process, thereby effectively improving the separation accuracy and adaptability, solving the problems of low pneumatic separation accuracy, easy interference of sensors and response lag in the prior art, and providing a more efficient and stable separation solution for different batches of raw materials.

Description

Technical Field

[0001] The present invention relates to a control system for a pneumatic separator of konjac flour, belonging to the sorting control technology field of pneumatic separation equipment. Background Art

[0002] The pneumatic separator of konjac flour is a device used for sorting granular materials such as konjac flour. Its working principle is to separate the materials in the pneumatic separator by adjusting the air flow, so as to achieve the effect of fine sorting. Usually, the working process of this kind of pneumatic separator involves the dynamic interaction between the air flow and the materials. The materials will be driven by the air flow and separated according to their forms, densities and other characteristics. In the traditional sorting system, the visual sensing or weight sensing of the materials is usually adopted to monitor the state and position of the materials, and the sorting is realized by adjusting the wind speed of the fan. However, these existing technologies have certain limitations and problems.

[0003] In the prior art, most traditional pneumatic separators of konjac flour rely on direct material sensors for real-time detection, such as visual sensors or weight sensors. These sensors judge the characteristics of the materials by directly contacting the materials or monitoring the appearance of the materials, and then control the wind speed adjustment. However, this method has some problems: 1. Greatly affected by the environment: Material sensors are often easily affected by environmental factors, such as climate change, light change, etc. These interferences will affect the accuracy and stability of the sensors. 2. Difficult to capture the dynamic characteristics of materials in real time: Existing sensors are difficult to accurately and timely reflect the real-time changes of materials in the air flow field. Especially under high flow rate and complex air flow conditions, the state of materials changes rapidly, and sensors are often difficult to accurately track. 3. Limited sensor accuracy: Traditional sensors often perform static perception on the appearance or weight of materials. During the process of dynamically adjusting the wind speed, their response time and sensitivity often cannot meet the requirements of efficient sorting.

[0004] In order to overcome these problems, attempts have been made in the industry to optimize the sorting process through the principle of fluid mechanics. For example, some solutions have begun to try to indirectly infer the state of materials by monitoring the wind pressure changes in the air flow. However, the perception method based on wind pressure fluctuations can theoretically avoid the way of directly contacting the materials, thus reducing the influence of environmental interference. But these technologies often rely too much on large-scale air flow control, resulting in insufficiently sensitive wind speed adjustment. Summary of the Invention

[0005] The present invention provides a control system for a pneumatic separator of konjac flour. Its main purpose is to solve the problems that the traditional pneumatic separator of konjac flour relies on weight sensors or visual sensors to detect the material state, is easily affected by the environment and difficult to accurately perceive the dynamic characteristics of materials in real time, resulting in low sorting accuracy, high system complexity and high maintenance cost.

[0006] To achieve the above object, a control system of a konjac refined powder air classifier provided by the present invention includes:

[0007] A wind pressure data acquisition module for real-time acquisition of wind pressure data at the discharge port of the konjac refined powder air classifier;

[0008] A wind pressure fluctuation characteristic analysis module, communicatively connected to the wind pressure data acquisition module, for receiving the wind pressure data and calculating a fluctuation standard deviation characterizing the dynamic change of the wind pressure and a frequency characteristic characterizing the speed of wind pressure fluctuation, wherein the fluctuation standard deviation:

[0009] ,

[0010] In the formula, represents the th wind pressure data collected within a preset time window, represents the average wind pressure within the preset time window, represents the total number of wind pressure data collected within the preset time window;

[0011] A wind speed adjustment strategy matching module, communicatively connected to the wind pressure fluctuation characteristic analysis module, for receiving the fluctuation standard deviation and the frequency characteristic, and according to the material distribution state characterized by the fluctuation standard deviation and the frequency characteristic, matching a corresponding wind speed adjustment strategy according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy, so as to maintain or adjust the self-organizing dynamic balance of the airflow field and the material distribution during the air classification process;

[0012] A wind speed control module, communicatively connected to the wind speed adjustment strategy matching module and the fan actuator of the air classifier, for receiving the wind speed adjustment strategy and controlling the fan actuator to adjust the wind speed of the air classifier.

[0013] Preferably, the method for the wind pressure fluctuation characteristic analysis module to calculate the wind pressure fluctuation frequency characteristic is: by analyzing the number of times that the wind pressure value exceeds or is lower than its average value continuously twice within a preset time window, the fluctuation frequency is obtained.

[0014] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation is less than or equal to a preset threshold, it is determined that the material state is in a steady state, and the wind speed adjustment strategy is to maintain the current wind speed.

[0015] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation is greater than the preset threshold, according to the frequency characteristic and the fluctuation standard deviation of the wind pressure The combination matches the corresponding wind speed adjustment strategy.

[0016] Preferably, in the wind speed adjustment strategy matching module, it is preset that when the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, the matched wind speed adjustment strategy is to finely adjust the current wind speed.

[0017] Preferably, in the wind speed adjustment strategy matching module, it is preset that when the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, the matched wind speed adjustment strategy is to perform stepwise adjustment on the current wind speed.

[0018] Preferably, the response delay of the wind speed control module to control the fan actuator to adjust the wind speed is less than or equal to 0.5 seconds.

[0019] Compared with the problems described in the background art, the beneficial effects of the present invention are:

[0020] 1. Aiming at the limitation that traditional konjac refined powder air separators rely on direct material sensing (such as vision or weight analysis), which is vulnerable to environmental interference and difficult to capture the dynamic characteristics of materials in real time, the present invention adopts an indirect sensing strategy based on the principle of fluid mechanics. By monitoring the minute fluctuations of the wind pressure at the discharge port, it can infer the distribution state of materials in the airflow field in real time, and based on this, accurately control the wind speed. Avoiding the way of directly contacting the materials not only reduces the system complexity and maintenance cost, but also realizes more sensitive and efficient dynamic optimization of the sorting process. While simplifying the physical structure and avoiding internal detection, it significantly improves the sorting accuracy and adaptability to different batches of raw materials.

[0021] 2. By avoiding the way of directly sensing the material state in the traditional technology, the influence of environmental interference on the material sensor is avoided. Through the data analysis of the wind pressure fluctuation based on the principle of fluid mechanics, the system not only reduces the system complexity and maintenance cost, but also improves the sensitivity and dynamic optimization ability of the sorting process. It not only reduces the sensitivity of the sensor to environmental changes, reduces the complexity and maintenance cost of the equipment, but also enhances the stability and anti-interference ability of the equipment. Brief Description of the Drawings

[0022] Figure 1 The wind speed adjustment flowchart of the konjac refined powder air separator control system of the present invention;

[0023] Figure 2 The fluctuation characteristic calculation flowchart of the konjac refined powder air separator control system of the present invention;

[0024] Figure 3 The module communication schematic diagram of the konjac refined powder air separator control system of the present invention;

[0025] Figure 4Schematic diagram of wind speed adjustment decision-making for the control system of konjac flour air classifier of the present invention;

[0026] Figure 5 Schematic diagram of the functional module structure of the control system of konjac flour air classifier of the present invention;

[0027] Figure 6 Schematic diagram of the composition of sensors in the traditional solution;

[0028] Figure 7 Schematic diagram of the composition of sensors in the solution of the present invention.

[0029] The realization of the object, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0030] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0031] The embodiment of the present application provides a control system for a konjac flour air classifier, including: a wind pressure data acquisition module for real-time acquisition of the wind pressure data at the discharge port of the konjac flour air classifier;

[0032] A wind pressure fluctuation characteristic analysis module, communicatively connected to the wind pressure data acquisition module, for receiving the wind pressure data and calculating the fluctuation standard deviation characterizing the dynamic change of the wind pressure and the frequency characteristic characterizing the speed of the wind pressure fluctuation, wherein the fluctuation standard deviation:

[0033] ,

[0034] In the formula, represents the th wind pressure data collected within a preset time window, represents the average wind pressure within the preset time window, represents the total number of wind pressure data collected within the preset time window;

[0035] A wind speed adjustment strategy matching module, communicatively connected to the wind pressure fluctuation characteristic analysis module, for receiving the fluctuation standard deviation and the frequency characteristic, and according to the material distribution state characterized by the fluctuation standard deviation and the frequency characteristic, matching the corresponding wind speed adjustment strategy according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy to maintain or adjust the self-organizing dynamic balance of the airflow field and the material distribution in the air classification process;

[0036] The wind speed control module is communicatively connected to the wind speed adjustment strategy matching module and the fan actuator of the air separator, and is configured to receive the wind speed adjustment strategy and control the fan actuator to adjust the wind speed of the air separator.

[0037] Preferably, the method for the air pressure fluctuation characteristic analysis module to calculate the air pressure fluctuation frequency characteristic is: by analyzing the number of times that the air pressure value exceeds or is lower than its average value twice continuously within a preset time window, the fluctuation frequency is obtained. to obtain the fluctuation frequency.

[0038] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation is less than or equal to a preset threshold, it is determined that the material state is in a steady state, and the wind speed adjustment strategy is to maintain the current wind speed.

[0039] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation is greater than the preset threshold, according to the combination of the frequency characteristic and the fluctuation standard deviation of the air pressure fluctuation corresponding wind speed adjustment strategy is matched.

[0040] Preferably, in the wind speed adjustment strategy matching module, it is preset that when the air pressure fluctuation shows high-frequency and small-amplitude fluctuations, the matched wind speed adjustment strategy is to fine-tune the current wind speed.

[0041] Preferably, in the wind speed adjustment strategy matching module, it is preset that when the air pressure fluctuation shows low-frequency and large-amplitude fluctuations, the matched wind speed adjustment strategy is to perform a stepped adjustment on the current wind speed.

[0042] Preferably, the response delay of the wind speed control module to control the fan actuator to adjust the wind speed is less than or equal to 0.5 seconds.

[0043] Example 1: In this example, the system consists of the following key modules: the air pressure data acquisition module: continuously acquires the air pressure data at the discharge port of the air separator in real time; the air pressure fluctuation characteristic analysis module: receives and analyzes the air pressure data, and calculates the standard deviation and frequency characteristic of the air pressure fluctuation. The standard deviation calculation formula is as follows:

[0044] ,

[0045] where, is the th air pressure data collected within the preset time window, is the average air pressure of this window, is the total number of data points. Through this formula, the air pressure fluctuation standard deviation It can reflect the dynamic change degree of the wind pressure, and then infer the stability of the material distribution; Wind speed adjustment strategy matching module: Based on the analyzed standard deviation of fluctuations and frequency characteristics, match appropriate wind speed adjustment strategies, aiming to maintain or adjust the dynamic balance between the air flow field and the material distribution during the air separation process; Wind speed control module: This module accurately controls the wind speed of the air separator through the fan actuator according to the matched wind speed adjustment strategy.

[0046] In implementation, the system first continuously monitors the wind pressure change at the discharge port through the wind pressure data acquisition module. Each set of collected data will be transmitted to the wind pressure fluctuation characteristic analysis module; The wind pressure fluctuation characteristic analysis module calculates the standard deviation of fluctuations of the current time window according to the formula and further analyzes the frequency characteristics of the wind pressure fluctuation. The frequency characteristic is obtained by calculating the number of times the wind pressure value exceeds or is lower than the average value twice within a preset time window; If the calculated standard deviation of wind pressure fluctuations is less than or equal to the preset threshold, the system will determine that the material is in a steady state, and at this time the wind speed remains unchanged; If is greater than the threshold, the system further analyzes the dynamic characteristics of the material distribution according to the frequency characteristics. For example, when the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, the system will choose to finely adjust the wind speed to avoid uneven material distribution caused by excessive wind speed. On the contrary, when the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, the system adopts a stepped wind speed adjustment strategy to more effectively adapt to the rapid change of the material distribution.

[0047] The wind speed adjustment strategy accurately controls the fan actuator through the wind speed control module, ensuring that the reaction delay of the wind speed adjustment does not exceed 0.5 seconds to ensure an immediate response to the operation of the air separator. Through this control strategy, the system can maintain the stability of the material distribution and the sorting accuracy under real-time monitoring and adjustment, thereby significantly improving the overall sorting effect, enabling the control system of this embodiment to effectively avoid the direct perception of the material state in the traditional technology and avoiding the influence of environmental interference on the material sensor. Through the analysis of the wind pressure fluctuation data based on the principle of fluid mechanics, the system not only reduces the system complexity and maintenance cost, but also improves the sensitivity and dynamic optimization ability of the sorting process. Compared with the prior art, this system can more accurately control the wind speed of the air separator, ensure the adaptability and stability of different batches of raw materials, and thus improve the production efficiency and product quality.

[0048] Example 2: This example demonstrates its specific implementation steps. Step 1: Wind pressure data collection. The system collects the wind pressure data at the outlet of the konjac flour air classifier in real time through the wind pressure data collection module. The collected data is used to analyze the characteristics of wind pressure fluctuations, so as to infer the dynamic relationship between the airflow field and the material distribution in real time. Step 2: Analysis of wind pressure fluctuation characteristics. The wind pressure fluctuation characteristic analysis module receives the data from the wind pressure data collection module, and calculates and analyzes the standard deviation and frequency characteristics. The standard deviation is calculated as follows:

[0049] ,

[0050] where is the th wind pressure data point collected, is the average wind pressure of this time window, is the total number of data. The standard deviation is used to characterize the fluctuation amplitude of the wind pressure, thus indirectly reflecting the distribution stability of the material.

[0051] At the same time, the frequency characteristics are obtained by calculating the number of times the wind pressure value exceeds or is lower than the average value within a preset time window, and further analyzing the speed of the fluctuation. The frequency characteristics reflect the instantaneous change of the airflow and help the wind speed adjustment strategy to respond more precisely to the dynamic changes of the material.

[0052] Step 3: Matching of wind speed adjustment strategy. The wind speed adjustment strategy matching module matches the most suitable wind speed adjustment strategy according to the standard deviation and frequency characteristics of the wind pressure fluctuation. The specific strategy is as follows: when is less than or equal to the preset threshold, the system considers that the material state is in a steady state. At this time, the wind speed adjustment strategy is to maintain the current wind speed to ensure the stable operation of the system. When is greater than the preset threshold, further analyze the frequency characteristics of the wind pressure fluctuation and match the corresponding wind speed adjustment strategy. If the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, select to fine-tune the wind speed; if the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, then select to adjust the wind speed in a stepwise manner.

[0053] Step 4: Response of the wind speed control module. The wind speed control module receives the wind speed adjustment strategy and executes the specific wind speed adjustment. To ensure an immediate response to the operation of the air classifier, the wind speed control module requires that the response delay does not exceed 0.5 seconds. In this way, by precisely controlling the fan actuator, the wind speed can be adjusted in real time to maintain the dynamic balance between the airflow field and the material distribution.

[0054] Example 3: This example combines Appendix Figure 1 to Appendix Figure 7, the technical solution of the present invention will be further described. As Figure 1 shown, the system first collects the wind pressure data at the discharge port through the wind pressure data acquisition module. Then, the system calculates the standard deviation of wind pressure fluctuations and frequency characteristics in the calculation of the fluctuation dynamic standard deviation and frequency characteristics module. According to the calculation results, the system judges whether it is less than or equal to the preset threshold. When is less than or equal to the threshold, the system selects to maintain the current wind speed strategy; if is greater than the threshold, the system enters the wind pressure fluctuation frequency analysis stage. If the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, the system selects the fine-tuning wind speed strategy; if the fluctuation shows low-frequency and large-amplitude fluctuations, the stepped wind speed adjustment strategy is selected. Finally, the system generates a fan control command according to the selected strategy to adjust the wind speed of the air separator.

[0055] As Figure 2 shown, in the process of calculating the wind pressure fluctuation characteristics, the system first obtains the time window data, then calculates the average wind pressure within the window, and calculates the standard deviation of wind pressure fluctuations and frequency characteristics according to this value. Through these characteristics, the system can effectively identify the distribution state of materials and provide data support for subsequent wind speed adjustment. As Figure 3 shown, the modules of the system interact through data streams. First, the wind pressure data acquisition module obtains the wind pressure data and transmits it to the analysis module for fluctuation characteristic analysis. The analysis results are further transmitted to the matching module to select an appropriate wind speed adjustment strategy and achieve wind speed adjustment through the control module. The system ensures the stability and optimization of the air separation process through a closed-loop feedback mechanism. As Figure 4 shown, after the system judges whether the standard deviation of fluctuations is greater than the threshold, it enters the frequency characteristic analysis stage. According to the analysis results, the system will select different wind speed adjustment strategies, such as fine-tuning the wind speed or stepped adjustment of the wind speed. If the standard deviation of fluctuations is not greater than the threshold, the current wind speed is maintained to ensure the system operates in a stable state.

[0056] As Figure 5 shown, the comparison between the control system of the present invention and the traditional solution reflects its advantages. The traditional solution relies on weight sensors and vision sensors, while the present invention uses a wind pressure sensor to indirectly sense the material state through the principle of fluid mechanics, avoiding the limitations of direct contact with materials, reducing environmental interference, and improving the stability and accuracy of the system. As Figure 6As shown, the sensors in the traditional solution include a weight sensor and a vision sensor. These sensors are vulnerable to environmental interference and cannot accurately reflect the dynamic state of the material in real time. In contrast, the present invention indirectly senses the state of the material from the perspective of fluid mechanics through a wind pressure sensor in combination with an analysis algorithm, improving the accuracy of the air separation process. As Figure 7 shown, the present invention indirectly senses the distribution state of the material in the air flow through a wind pressure sensor and an analysis algorithm, avoiding the limitations of traditional sensors, reducing the influence of environmental factors, and providing a more stable and accurate control solution.

[0057] Example 4: In the wind pressure fluctuation characteristic analysis module of this example, the standard deviation of wind pressure fluctuation is calculated by the formula: ,

[0058] where represents the th wind pressure data collected within a preset time window, represents the average wind pressure within this time window, represents the total number of wind pressure data collected within this time window; the duration of this preset time window is usually set to 2 to 5 seconds, and the specific value is determined according to the discharge rhythm of the actual air separator and the change speed of the material distribution. In practical applications, the dynamic changes of the air flow and the material during the air separation process are usually at the second level. Therefore, choosing 2 to 5 seconds as the window length can balance real-time performance and data stability. Secondly, in the calculation method of frequency characteristics, within each time window , the system counts the number of times the wind pressure value crosses its average value , that is, the total number of crossing events formed by exceeding or falling below the average value continuously twice, and then calculates the fluctuation frequency characteristic :

[0059] ,

[0060] where represents the crossing frequency of wind pressure fluctuation, with the unit of Hertz (Hz); represents the total number of crossing events; is the time window duration (seconds), and this frequency characteristic is used to quantify the speed of wind pressure fluctuation. When the material distribution state is unstable, the crossing frequency of wind pressure fluctuation usually shows an abnormal increase or decrease, and the system judges the dynamic change trend during the air separation process based on this frequency characteristic. In addition, to ensure the accuracy of the wind speed adjustment strategy, this example supplements the setting principle of preset thresholds: the standard deviation threshold of wind pressure fluctuation and the crossing frequency threshold are set according to the following principles: It is usually taken as 1.2 to 1.5 times the standard deviation of the wind pressure fluctuation during the historical stable operation process, and the specific value is determined through the empirical data in the sorting process of multiple batches of materials, aiming to distinguish the steady state and the dynamic fluctuation state; The value is set comprehensively according to the discharge rhythm of the air separator and the sampling frequency of the wind pressure sensor. It is usually set in the range of ±20% of the crossing frequency under normal operation conditions, and is used to identify abnormal frequency fluctuations.

[0061] To avoid deviations in the above threshold setting due to different material batches, the system allows dynamic adjustment through the parameter configuration interface and of the specific values to adapt to different production conditions. The specific logical chains of the three types of strategies, namely the steady state, fine adjustment and step-by-step adjustment strategies, in the wind speed adjustment strategy matching module of this embodiment are as follows: when and are within the normal range, the system determines that the material distribution state is steady and maintains the current wind speed; when and , the system identifies it as a high-frequency small-amplitude fluctuation and executes the fine adjustment strategy, specifically that the wind speed is adjusted by no more than ±2% of the current wind speed each time; when and , the system identifies it as a low-frequency large-amplitude fluctuation and executes the step-by-step adjustment strategy, specifically that the wind speed increases or decreases by 5% to 10% in each adjustment cycle until the fluctuation characteristics return to the threshold range.

[0062] Embodiment 5: This embodiment includes a wind pressure data acquisition module, a wind pressure fluctuation characteristic analysis module, a wind speed adjustment strategy matching module and a wind speed control module, and the modules are linked through data communication. However, in the implementation process, key parameters, formula meanings and implementation steps are specifically supplemented and refined as follows:

[0063] During the operation of the system, the wind pressure data acquisition module continuously obtains the wind pressure data at the discharge port of the air separator, and the data sampling frequency is set to 10 times per second to ensure the real-time and accuracy of the data. Before all the collected wind pressure data enter the wind pressure fluctuation characteristic analysis module, they will first undergo filtering processing to exclude abnormal data caused by external mechanical vibrations or transient air flow fluctuations.

[0064] In the wind pressure fluctuation characteristic analysis module, the system uses two core parameters, the fluctuation standard deviation and the crossing frequency , to characterize the dynamic characteristics of the wind pressure. Among them, the calculation method of the fluctuation standard deviation is uniformly adopted as the following formula:

[0065] ,

[0066] where: represents the th wind pressure data collected within a preset time window, with the unit of Pascal (Pa); represents the average value of the wind pressure data within this time window, with the unit of Pascal (Pa); represents the total number of sampling points of the wind pressure data within the time window. The duration of the time window is set according to the discharging rhythm of the air separator, usually 3 seconds, and the number of sampling points is fixed at 30. In the calculation of the crossing frequency f, the system counts within the time window the total number of crossing events formed by the wind pressure data sequence exceeding or falling below the average value continuously twice, and calculates the crossing frequency according to the following formula:

[0067] ,

[0068] where: with the unit of Hertz (Hz), represents the number of times the wind pressure fluctuates across the average value per unit time; is the number of crossing events obtained through statistics; is the duration of the time window, with the unit of second (s).

[0069] Meanwhile, in this embodiment, the setting principles of the fluctuation standard deviation threshold and the crossing frequency threshold are further described. is set to 1.3 times the standard deviation of the wind pressure fluctuation under the historical stable operation state of the system, and the specific value is determined through the measured data during multiple batches of production operations. For example, if the average value is 4.5 Pa in the stable state, then can be set to 5.85 Pa.

[0070] is set within the range of ±20% of the crossing frequency under the normal operation state. For example, if the average value is 0.8 Hz during normal operation, then the range is from 0.64 Hz to 0.96 Hz.

[0071] In the wind speed adjustment strategy matching module, the system adjusts the wind speed according to the following strategy based on the real-time analysis results of and : When and is within the range of , the system determines that the material distribution is in a steady state and keeps the current wind speed unchanged. When And When, the system determines that the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, and executes a fine-tuning strategy with an adjustment amplitude of ±2% of the current wind speed. When And When, the system determines that the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, and executes a stepped adjustment strategy with a single adjustment amplitude of ±10% of the current wind speed. All of these belong to the extended implementation methods known to those of ordinary skill in the art.

[0072] Example 6: In the wind pressure fluctuation characteristic analysis module, the calculation method of the standard deviation of wind pressure fluctuation Adopts the following formula:

[0073] ,

[0074] Wherein: Represents the th wind pressure data collected within the preset time window, with the unit of Pascal (Pa); Represents the average value of all wind pressure data within this time window, with the unit of Pascal (Pa); Represents the total number of wind pressure data collected within this time window, which is a positive integer.

[0075] The duration of the preset time window is usually set to 2 to 5 seconds, and the specific value is determined according to the discharge rhythm of the air separator and the change speed of the material distribution. This interval setting aims to balance the system real-time performance and data fluctuation stability to ensure accurate reflection of dynamic characteristics. The system counts the total number of crossing events formed by the wind pressure value exceeding or falling below the average value twice continuously in the wind pressure data sequence within each time window. . Based on this, the crossing frequency characteristic is calculated:

[0076] ,

[0077] Wherein: Is the total number of crossing events statistically obtained within the time window; Is the time window duration, with the unit of second (s); Is the crossing frequency of the wind pressure fluctuation, with the unit of Hertz (Hz). This frequency characteristic is used to characterize the speed of the wind pressure fluctuation and is directly related to the dynamic change of the material distribution state.

[0078] To improve the accuracy of system decision-making, the system presets the standard deviation threshold of the wind pressure fluctuation and the crossing frequency threshold in the parameter configuration interface. The specific setting principles are as follows: It is set to 1.2 to 1.5 times the standard deviation of the wind pressure fluctuation under the historical stable operation state of the system. The specific value is determined according to the statistical data in the actual production process and is used to distinguish the steady state from the dynamic fluctuation state. It is set to the ±20% interval of the crossover frequency under the normal operation state. The specific value is determined comprehensively based on the discharge rhythm of the air classifier and the sampling frequency. This setting method aims to ensure that the system has good adaptability and operability for different material batches and production conditions.

[0079] In this embodiment, the wind speed adjustment strategy matching module is based on the standard deviation and the crossover frequency of the real-time calculation results, and adopts the following decision-making process: when and falls within the normal range, it is determined that the material distribution state is steady, and the system maintains the current wind speed unchanged; when and , it is determined that the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, and the system adopts a fine-tuning wind speed strategy, with each adjustment amplitude not exceeding ±2% of the current wind speed; when and , it is determined that the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, and the system adopts a stepped adjustment strategy, and the wind speed increases or decreases by 5% to 10% of the current wind speed in each adjustment cycle until the fluctuation characteristics return to the threshold range. Through the above strategy, the system can dynamically and accurately adjust the wind speed according to the real-time wind pressure fluctuation characteristics, realize the stable control of the air separation process, and all belong to the extended implementation methods known to those of ordinary skill in the art.

[0080] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A control system for a winnowing machine of konjac refined powder, characterized in that, Including: A wind pressure data acquisition module for real-time acquisition of wind pressure data at the discharge port of the konjac flour pneumatic separator; The wind pressure fluctuation characteristic analysis module, which is communicatively connected to the wind pressure data acquisition module, is configured to receive the wind pressure data and calculate the fluctuation standard deviation characterizing the dynamic change of the wind pressure and the frequency characteristic characterizing the speed of the wind pressure fluctuation, wherein the fluctuation standard deviation is as follows ， In the formula, represents the th wind pressure data collected within a preset time window, represents the average wind pressure within the preset time window, represents the total number of wind pressure data collected within the preset time window; The wind speed adjustment strategy matching module, which is communicatively connected to the wind pressure fluctuation characteristic analysis module, is configured to receive the fluctuation standard deviation and the frequency characteristics, and according to the material distribution state characterized by the fluctuation standard deviation and the frequency characteristics, match corresponding wind speed adjustment strategies according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy, so as to maintain or adjust the self-organizing dynamic balance between the airflow field and the material distribution in the air separation process; A wind speed control module, which is communicatively connected to the wind speed adjustment strategy matching module and the fan actuator of the pneumatic separator, for receiving the wind speed adjustment strategy and controlling the fan actuator to adjust the wind speed of the pneumatic separator; The mapping relationship between the preset fluctuation pattern and the wind speed adjustment strategy includes: when the fluctuation standard deviation is greater than a preset threshold, according to the combination of the frequency characteristics and the fluctuation standard deviation of the wind pressure fluctuation , a corresponding wind speed adjustment strategy is matched; in the wind speed adjustment strategy matching module, it is preset that: when the wind pressure fluctuation shows high-frequency and small-amplitude fluctuations, the matched wind speed adjustment strategy is to finely adjust the current wind speed; in the wind speed adjustment strategy matching module, it is preset that: when the wind pressure fluctuation shows low-frequency and large-amplitude fluctuations, the matched wind speed adjustment strategy is to perform a stepped adjustment on the current wind speed; the method for the wind pressure fluctuation feature analysis module to calculate the frequency characteristics of the wind pressure fluctuation is: by analyzing the number of times that the wind pressure value exceeds or is lower than its average value continuously twice within a preset time window, the fluctuation frequency is obtained.

2. The control system of the air classifier for konjac flour according to claim 1, characterized in that, The mapping relationship between the preset fluctuation pattern and the wind speed adjustment strategy includes: when the fluctuation standard deviation is less than or equal to a preset threshold, it is determined that the material state is in a steady state, and the wind speed adjustment strategy is to maintain the current wind speed.

3. The control system of the konjac flour pneumatic separator according to claim 1, characterized in that, The response delay of the wind speed control module to control the fan actuator to adjust the wind speed is less than or equal to 0.5 seconds.

Images