Control system of konjac powder winnowing machine

Abstract

The invention relates to a control system of a winnowing machine, and discloses a control system of a konjac powder winnowing machine. The system comprises 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. The system can deduce the distribution state of the material in the airflow in real time by monitoring the tiny fluctuation of the air pressure of the discharge port, and accurately regulate and control the air speed according to the fluctuation characteristics, so that the limitation that a traditional material sensor is easily interfered by the environment is avoided. Through an indirect sensing strategy based on the fluid mechanics principle, the system complexity and the maintenance cost are remarkably reduced, the sensitivity and the dynamic optimization capacity of the winnowing process are improved, and therefore the sorting precision and adaptability are effectively improved, and the problems that in the prior art, the sorting precision is low, a sensor is prone to being interfered, and response lags are solved; and a more efficient and stable sorting scheme is provided for different batches of raw materials.

Description

Technical Field

[0001] The invention relates to a control system of a konjac flour air separator, belonging to the technical field of separation control of air separators. Background Art

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

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

[0004] In order to overcome these problems, attempts have been made in the industry to optimize the sorting process through the principles of fluid mechanics. For example, some solutions have begun to try to indirectly infer the state of the material by monitoring the changes in wind pressure in the airflow. However, the perception method based on wind pressure fluctuations can theoretically avoid direct contact with the material, thereby reducing the impact of environmental interference, but these technologies often rely too much on large-scale airflow control, resulting in insufficient sensitivity in wind speed adjustment. Summary of the invention

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

[0006] To achieve the above object, the present invention provides a control system for a konjak flour winnowing machine, comprising: The wind pressure data collection module is used to collect the wind pressure data at the discharge port of the konjac flour air separator in real time; The wind pressure fluctuation characteristic analysis module is connected to the wind pressure data acquisition module for receiving the wind pressure data and calculating the standard deviation of the fluctuation that characterizes the dynamic change of wind pressure. And the frequency characteristics that characterize the speed of wind pressure fluctuation, wherein the standard deviation of the fluctuation is: , In the formula, Indicates the first Wind pressure data, represents the average wind pressure within the preset time window, Indicates the total number of wind pressure data collected within the preset time window; The wind speed adjustment strategy matching module is connected to the wind pressure fluctuation characteristic analysis module for receiving the fluctuation standard deviation. and frequency characteristics, and according to the standard deviation of the fluctuation According to the material distribution state represented by the frequency characteristics, the corresponding wind speed adjustment strategy is matched according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy to maintain or adjust the self-organized dynamic balance of the airflow field and material distribution during the air selection process; The wind speed control module is communicatively connected with the wind speed adjustment strategy matching module and the fan actuator of the air separator, and is used for receiving the wind speed adjustment strategy and controlling the fan actuator to adjust the wind speed of the air separator.

[0007] Preferably, the wind pressure fluctuation characteristic analysis module calculates the wind pressure fluctuation frequency characteristic by analyzing whether the wind pressure value exceeds or falls below its average value twice in a row within a preset time window. The number of times we get the fluctuation frequency.

[0008] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it 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.

[0009] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it is greater than a preset threshold, a corresponding wind speed adjustment strategy is matched according to a combination of the frequency characteristics and the amplitude characteristics of the wind pressure fluctuation.

[0010] Preferably, the wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation is characterized by high frequency and small amplitude fluctuation, the matched wind speed adjustment strategy is to fine-tune the current wind speed.

[0011] Preferably, the wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation exhibits low frequency and large amplitude fluctuation, the matched wind speed adjustment strategy is to perform step-by-step adjustment on the current wind speed.

[0012] Preferably, the wind speed control module controls the response delay of the fan actuator to adjust the wind speed to be less than or equal to 0.5 seconds.

[0013] Compared with the problems described in the background technology, the beneficial effects of the present invention are: 1. In view of the limitations of traditional konjac flour air sorting machines that rely on direct material sensing (such as visual or weight analysis), which is easily disturbed by the environment 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 slight fluctuations in the wind pressure at the discharge port, the distribution state of the material in the airflow field can be inferred in real time, and the wind speed can be accurately controlled based on this, avoiding direct contact with the material. This not only reduces the system complexity and maintenance costs, but also achieves a more sensitive and efficient dynamic optimization of the sorting process. While simplifying the physical structure and avoiding internal detection, the sorting accuracy and adaptability to different batches of raw materials are significantly improved.

[0014] 2. By avoiding the direct perception of material status in traditional technologies, the impact of environmental interference on material sensors is avoided. Through the analysis of wind pressure fluctuation data based on fluid mechanics principles, the system not only reduces system complexity and maintenance costs, but also improves the sensitivity and dynamic optimization capabilities of the sorting process. It not only reduces the sensitivity of sensors to environmental changes, reduces the complexity and maintenance costs of equipment, but also enhances the stability and anti-interference ability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Wind speed adjustment flow chart of konjac flour air separator control system of the present invention; Figure 2 The fluctuation characteristic calculation flow chart of the konjac flour winnowing machine control system of the present invention; Figure 3 Module communication schematic diagram of konjac flour winnowing machine control system of the present invention; Figure 4 Schematic diagram of wind speed adjustment decision of konjac flour winnowing machine control system of the present invention; Figure 5 The functional module structure diagram of the konjac flour winnowing machine control system of the present invention; Figure 6 Schematic diagram of the sensor composition of the traditional solution; Figure 7 Schematic diagram of the sensor structure of the present invention.

[0016] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] 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.

[0018] The embodiment of the present application provides a control system of a konjac flour air separator, comprising: a wind pressure data acquisition module, for real-time acquisition of wind pressure data at a discharge port of the konjac flour air separator; The wind pressure fluctuation characteristic analysis module is connected to the wind pressure data acquisition module for receiving the wind pressure data and calculating the standard deviation of the fluctuation that characterizes the dynamic change of wind pressure. And the frequency characteristics that characterize the speed of wind pressure fluctuation, wherein the standard deviation of the fluctuation is: , In the formula, Indicates the first Wind pressure data, represents the average wind pressure within the preset time window, Indicates the total number of wind pressure data collected within the preset time window; The wind speed adjustment strategy matching module is connected to the wind pressure fluctuation characteristic analysis module for receiving the fluctuation standard deviation. and frequency characteristics, and according to the standard deviation of the fluctuation According to the material distribution state represented by the frequency characteristics, the corresponding wind speed adjustment strategy is matched according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy to maintain or adjust the self-organized dynamic balance of the airflow field and material distribution during the air selection process; The wind speed control module is communicatively connected with the wind speed adjustment strategy matching module and the fan actuator of the air separator, and is used for receiving the wind speed adjustment strategy and controlling the fan actuator to adjust the wind speed of the air separator.

[0019] Preferably, the wind pressure fluctuation characteristic analysis module calculates the wind pressure fluctuation frequency characteristic by analyzing whether the wind pressure value exceeds or falls below its average value twice in a row within a preset time window. The number of times we get the fluctuation frequency.

[0020] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it 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.

[0021] Preferably, the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it is greater than a preset threshold, a corresponding wind speed adjustment strategy is matched according to a combination of the frequency characteristics and the amplitude characteristics of the wind pressure fluctuation.

[0022] Preferably, the wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation is characterized by high frequency and small amplitude fluctuation, the matched wind speed adjustment strategy is to fine-tune the current wind speed.

[0023] Preferably, the wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation exhibits low frequency and large amplitude fluctuation, the matched wind speed adjustment strategy is to perform step-by-step adjustment on the current wind speed.

[0024] Preferably, the wind speed control module controls the response delay of the fan actuator to adjust the wind speed to be less than or equal to 0.5 seconds.

[0025] Embodiment 1: In this embodiment, the system is composed of the following key modules: wind pressure data acquisition module: real-time collection of wind pressure data at the outlet of the wind separator; wind pressure fluctuation characteristic analysis module: receiving and analyzing wind pressure data, calculating the standard deviation of wind pressure fluctuation and frequency characteristics. The standard deviation is calculated as follows: , in, The first Wind pressure data, is the average wind pressure of the window, is the total number of data points. Through this formula, the standard deviation of wind pressure fluctuation It can reflect the dynamic change degree of wind pressure and further infer the stability of material distribution; wind speed adjustment strategy matching module: based on the analyzed fluctuation standard deviation and frequency characteristics, it matches the appropriate wind speed adjustment strategy to maintain or adjust the dynamic balance of airflow field and 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.

[0026] In the implementation, the system first continuously monitors the wind pressure changes at the discharge port through the wind pressure data acquisition module. Each set of data collected It will be passed to the wind pressure fluctuation characteristic analysis module; the wind pressure fluctuation characteristic analysis module calculates the fluctuation standard deviation of the current time window according to the formula , and further analyze the frequency characteristics of wind pressure fluctuations. The frequency characteristics are calculated by calculating the number of times the wind pressure value exceeds or falls below the average value twice within a preset time window. The number of times is obtained; if the calculated wind pressure fluctuation standard deviation If the wind speed is less than or equal to the preset threshold, the system will determine that the material is in a steady state and the wind speed remains unchanged. If the wind pressure fluctuation is greater than the threshold, the system further analyzes the dynamic characteristics of material distribution according to the frequency characteristics. For example, when the wind pressure fluctuation is characterized by high-frequency and small-amplitude fluctuations, the system will choose to fine-tune the wind speed to avoid uneven material distribution caused by excessive wind speed. On the contrary, when the wind pressure fluctuation is characterized by low-frequency and large-amplitude fluctuations, the system will adopt a step-by-step wind speed adjustment strategy to more effectively adapt to the rapid changes in material distribution.

[0027] The wind speed adjustment strategy accurately controls the fan actuator through the wind speed control module to ensure that the wind speed adjustment reaction delay does not exceed 0.5 seconds to ensure immediate response to the operation of the air separator. Through this control strategy, the system can maintain the stability of material distribution and sorting accuracy under real-time monitoring and adjustment, thereby significantly improving the overall sorting effect, so that the control system of this embodiment can effectively avoid the direct perception of material status in traditional technology and avoid the impact of environmental interference on material sensors. Through the analysis of wind pressure fluctuation data based on the principles of fluid mechanics, the system not only reduces the system complexity and maintenance costs, but also improves the sensitivity and dynamic optimization capabilities of the sorting process. Compared with the prior art, the 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 production efficiency and product quality.

[0028] Example 2: This example shows its specific implementation steps. Step 1: Wind pressure data collection. The system collects wind pressure data at the outlet of the konjac flour air separator in real time through the wind pressure data collection module. The collected data is used to analyze the wind pressure fluctuation characteristics in order to infer the dynamic relationship between the airflow field and the material distribution in real time. Step 2: Wind pressure fluctuation characteristics analysis. The wind pressure fluctuation characteristics analysis module receives data from the wind pressure data collection module, calculates and analyzes the standard deviation of the wind pressure fluctuation. and frequency characteristics. Standard deviation The calculation formula is as follows: , in, For the collection of wind pressure data points, is the average wind pressure in the time window, is the total number of data. Standard deviation It is used to characterize the fluctuation amplitude of wind pressure, thereby indirectly reflecting the distribution stability of materials.

[0029] At the same time, the frequency characteristic is calculated by calculating the wind pressure value exceeding or falling below the average value within the preset time window. The frequency characteristics reflect the instantaneous changes of airflow and help the wind speed adjustment strategy respond to the dynamic changes of materials more accurately.

[0030] Step 3: Wind speed adjustment strategy matching. The wind speed adjustment strategy matching module is based on the standard deviation of wind pressure fluctuations. and frequency characteristics, and match the most appropriate wind speed adjustment strategy. The specific strategy is as follows: When it 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 stable operation of the system. When it is greater than the preset threshold, the frequency characteristics of wind pressure fluctuations are further analyzed and the corresponding wind speed adjustment strategy is matched. If the wind pressure fluctuation is characterized by high frequency and small fluctuations, fine-tuning the wind speed is selected; if the wind pressure fluctuation is characterized by low frequency and large fluctuations, step-by-step wind speed adjustment is selected.

[0031] Step 4: The wind speed control module responds. The wind speed control module receives the wind speed adjustment strategy and performs specific wind speed adjustment. In order to ensure immediate response to the operation of the winnowing machine, the wind speed control module requires a response delay of no more than 0.5 seconds. In this way, by precisely controlling the fan actuator, the wind speed can be adjusted in real time to maintain a dynamic balance between the airflow field and the material distribution.

[0032] Embodiment 3: This embodiment is combined with the attached Figure 1 To Attachment Figure 7 , the technical solution of the present invention is further described. Figure 1 As shown in the figure, the system first collects the wind pressure data at the discharge port through the wind pressure data acquisition module. Then, the system calculates the dynamic standard deviation of the fluctuation In the frequency characteristic module, the standard deviation of wind pressure fluctuation is calculated and frequency characteristics. Based on the calculation results, the system determines Is it less than or equal to the preset threshold? When it is less than or equal to the threshold, the system chooses to maintain the current wind speed strategy; if If the wind pressure fluctuation is greater than the threshold, the system enters the wind pressure fluctuation frequency analysis stage. If the wind pressure fluctuation is characterized by high-frequency and small-amplitude fluctuation, the system selects the fine-tuning wind speed strategy; if the fluctuation is characterized by low-frequency and large-amplitude fluctuation, the system selects the step-by-step wind speed adjustment strategy. Finally, the system generates fan control instructions based on the selected strategy to adjust the wind speed of the air separator.

[0033] like Figure 2 As shown in the figure, in the process of calculating the wind pressure fluctuation characteristics, the system first obtains the time window data, then calculates the average wind pressure in the window, and calculates the standard deviation of wind pressure fluctuation based on this value. And frequency characteristics. Through these characteristics, the system can effectively identify the distribution status of the material and provide data support for subsequent wind speed adjustment. Figure 3 As shown in the figure, the modules of the system interact with each other through data flow. First, the wind pressure data acquisition module obtains 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 the appropriate wind speed adjustment strategy, and the wind speed adjustment is implemented through the control module. The system ensures the stability and optimization of the wind selection process through a closed-loop feedback mechanism. Figure 4 As shown, the system is in determining the standard deviation of fluctuations If the value is greater than the threshold, the system will enter the frequency characteristic analysis phase. Based on the analysis results, the system will select different wind speed adjustment strategies, such as fine-tuning the wind speed or step-by-step adjustment of the wind speed. If the wind speed is not greater than the threshold, the current wind speed is maintained to ensure that the system operates in a stable state.

[0034] like Figure 5 As shown in the figure, the control system of the present invention is superior to the traditional solution. The traditional solution relies on weight sensors and visual sensors, while the present invention uses wind pressure sensors to indirectly sense the material state through the principle of fluid mechanics, avoiding the limitation of direct contact with the material, reducing environmental interference, and improving the stability and accuracy of the system. Figure 6 As shown in the figure, the sensors of the traditional scheme include weight sensors and visual sensors, which are easily disturbed by the environment and cannot accurately reflect the dynamic state of the material in real time. However, the present invention uses wind pressure sensors and combines analysis algorithms to indirectly perceive the material state from the perspective of fluid mechanics, thereby improving the accuracy of the wind selection process. Figure 7 As shown, the present invention indirectly senses the distribution state of materials in the airflow through wind pressure sensors and analysis algorithms, avoids the limitations of traditional sensors, reduces the influence of environmental factors, and provides a more stable and accurate control solution.

[0035] Embodiment 4: In this embodiment, in the wind pressure fluctuation characteristic analysis module, the wind pressure fluctuation standard deviation The calculation formula is: , in, Indicates the first Wind pressure data, represents the average wind pressure in the time window, Indicates the total number of wind pressure data collected within the time window; the length of the preset time window It is usually set to 2 to 5 seconds. The specific value is determined by the actual discharge rhythm of the air separator and the speed of material distribution change. In actual applications, the dynamic changes of airflow and materials during air separation are usually in 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, in each time window The system statistics wind pressure value Crossing its mean The number of , that is, the total number of crossing events consisting of two consecutive times exceeding or falling below the average value, and then calculating the fluctuation frequency characteristics : , in, It represents the crossover frequency of wind pressure fluctuations in Hertz (Hz); represents the total number of crossing events; is the time window duration (seconds). This frequency feature is used to quantify the speed of wind pressure fluctuations. When the material distribution state is unstable, the crossing frequency of wind pressure fluctuations will usually increase or decrease abnormally. The system judges the dynamic change trend in the wind selection process based on this frequency feature. In addition, to ensure the accuracy of the wind speed adjustment strategy, this embodiment supplements the setting principle of the preset threshold: wind pressure fluctuation standard deviation threshold and crossing frequency threshold Set according to the following principles: It is usually taken as 1.2 to 1.5 times the standard deviation of wind pressure fluctuations during historical stable operation. The specific value is determined by empirical data from multiple batches of material sorting, aiming to distinguish between steady state and dynamic fluctuation state; The value is set based on the discharge rhythm of the air separator and the sampling frequency of the wind pressure sensor. It is usually set to the ±20% range of the crossover frequency under normal operating conditions to identify abnormal frequency fluctuations.

[0036] In order to avoid deviations in the above threshold settings due to different material batches, the system allows dynamic adjustment through the parameter configuration interface and The specific value of to adapt to different production conditions. The specific logic chain of the three types of strategies of steady state, fine adjustment and step-by-step adjustment in the wind speed adjustment strategy matching module of this embodiment is as follows: and Within the normal range, the system determines that the material distribution state is stable and maintains the current wind speed; and , the system identifies it as a high-frequency small-amplitude fluctuation and executes a fine-tuning strategy, specifically adjusting the wind speed each time to no more than ±2% of the current wind speed; when and The system identifies it as a low-frequency and large-amplitude fluctuation and implements a step-by-step adjustment strategy. Specifically, the wind speed increases or decreases by 5% to 10% in each adjustment cycle until the fluctuation characteristics return to the threshold range.

[0037] 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, the key parameters, formula meanings and implementation steps are specifically supplemented and refined, as follows: During the operation of the system, the wind pressure data acquisition module obtains the wind pressure data of the outlet of the air separator in real time. The data sampling frequency is set to 10 times per second to ensure the real-time and accuracy of the data. All the collected wind pressure data will first be filtered before entering the wind pressure fluctuation characteristic analysis module to exclude abnormal data caused by external mechanical vibration or transient airflow fluctuations.

[0038] In the wind pressure fluctuation characteristic analysis module, the system uses the fluctuation standard deviation and crossover frequency Two core parameters characterize the dynamic characteristics of wind pressure. Among them, the standard deviation of fluctuation The calculation method uniformly adopts the following formula: , in: Indicates the first Wind pressure data, in Pascal (Pa); Represents the average value of wind pressure data in the time window, in Pascal (Pa); Indicates the total number of sampling points of wind pressure data in the time window. Time window length According to the wind separator discharging beat setting, usually 3 seconds, sampling points Fixed to 30. In the calculation of the crossover frequency f, the system counts the Internal wind pressure data series Over or under the average twice in a row The total number of crossing events , and calculate the crossover frequency according to the following formula: , in: The unit is Hertz (Hz), which indicates the number of times the wind pressure fluctuation crosses the average value per unit time; The number of crossing events obtained by statistics; The time window duration is in seconds (s).

[0039] At the same time, this embodiment sets the fluctuation standard deviation threshold and crossing frequency threshold The setting principle of It is set to 1.3 times the standard deviation of wind pressure fluctuation under the system's historical stable operation state. The specific value is determined by the measured data during multiple batches of production operations. The average value is 4.5Pa, then Can be set to 5.85 Pa.

[0040] Set to ±20% of the crossover frequency under normal operation. The mean value is 0.8 Hz, then The range is 0.64 Hz to 0.96 Hz.

[0041] In the wind speed adjustment strategy matching module, the system is based on and Based on the real-time analysis results, the wind speed is adjusted according to the following strategy: and In When the wind speed is within the range, the system determines that the material distribution is in a steady state and keeps the current wind speed unchanged. and When , the system determines that the wind pressure fluctuation is a high-frequency small-amplitude fluctuation, and executes a fine-tuning strategy with an adjustment range of ±2% of the current wind speed. and When the system determines that the wind pressure fluctuation is manifested as low-frequency and large-amplitude fluctuation, a step-by-step adjustment strategy is implemented, and a single adjustment range is ±10% of the current wind speed, which are all extended implementation methods known to ordinary technicians in this field.

[0042] Example 6: In the wind pressure fluctuation characteristic analysis module, the wind pressure fluctuation standard deviation The calculation method uses the following formula: , in: Indicates the first Wind pressure data, in Pascal (Pa); Represents the average value of all wind pressure data in the time window, in Pascal (Pa); Represents the total number of wind pressure data collected within the time window, which is a positive integer.

[0043] The duration of the preset time window It is usually set to 2 to 5 seconds, and the specific value is determined by the discharge rhythm of the wind separator and the speed of material distribution change. This interval setting is intended to take into account the real-time performance of the system and the stability of data fluctuations to ensure accurate reflection of dynamic characteristics. The system counts the wind pressure data sequence in each time window. The wind pressure value exceeds or falls below the average value twice in a row. The total number of crossing events . Based on this, the crossover frequency characteristics are calculated : , in: is the total number of crossing events obtained within the time window; is the time window length, in seconds (s); is the crossover frequency of wind pressure fluctuations, in Hertz (Hz). This frequency feature is used to characterize the speed of wind pressure fluctuations and is directly related to the dynamic changes in the material distribution state.

[0044] In order to improve the accuracy of system decision-making, the system presets the wind pressure fluctuation standard deviation threshold in the parameter configuration interface and crossing frequency threshold , the specific setting principles are as follows: It is set to 1.2 to 1.5 times the standard deviation of wind pressure fluctuation under the historical stable operation state of the system. The specific value is determined based on historical data statistics in the actual production process and is used to distinguish between steady state and dynamic fluctuation state. It is set to ±20% of the crossover frequency under normal operation. The specific value is determined based on the discharge beat of the air separator and the sampling frequency. This setting method is intended to ensure that the system has good adaptability and operability for different material batches and production conditions.

[0045] In this embodiment, the wind speed adjustment strategy matching module is based on the standard deviation and crossover frequency The real-time calculation results are as follows: and Falling Within the normal range, the material distribution state is determined to be steady, and the system maintains the current wind speed unchanged; and , it is determined that the wind pressure fluctuation is characterized by 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 is manifested as low-frequency and large-amplitude fluctuation. The system adopts a step-by-step 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, and achieve stable control of the wind selection process, which are all extended implementation methods known to ordinary technicians in this field.

[0046] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A control system for a konjac flour winnowing machine, characterized in that: include: The wind pressure data collection module is used to collect the wind pressure data at the discharge port of the konjac flour air separator in real time; The wind pressure fluctuation characteristic analysis module is connected to the wind pressure data acquisition module for receiving the wind pressure data and calculating the standard deviation of the fluctuation that characterizes the dynamic change of wind pressure. And the frequency characteristics that characterize the speed of wind pressure fluctuation, wherein the standard deviation of the fluctuation is: ， In the formula, Indicates the first Wind pressure data, represents the average wind pressure within the preset time window, Indicates the total number of wind pressure data collected within the preset time window; The wind speed adjustment strategy matching module is connected to the wind pressure fluctuation characteristic analysis module for receiving the fluctuation standard deviation. and frequency characteristics, and according to the standard deviation of the fluctuation According to the material distribution state represented by the frequency characteristics, the corresponding wind speed adjustment strategy is matched according to the mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy to maintain or adjust the self-organized dynamic balance of the airflow field and material distribution during the air selection process; The wind speed control module is communicatively connected with the wind speed adjustment strategy matching module and the fan actuator of the air separator, and is used for receiving the wind speed adjustment strategy and controlling the fan actuator to adjust the wind speed of the air separator.

2. The control system of the konjak flour winnowing machine according to claim 1, wherein The wind pressure fluctuation characteristic analysis module calculates the wind pressure fluctuation frequency characteristic by analyzing whether the wind pressure value exceeds or falls below its average value twice in a row within a preset time window. The number of times we get the fluctuation frequency.

3. The control system of the konjak flour winnowing machine according to claim 1, wherein The mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it 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.

4. The control system of the konjak flour winnowing machine according to claim 1, wherein The mapping relationship between the preset fluctuation mode and the wind speed adjustment strategy includes: when the fluctuation standard deviation When it is greater than a preset threshold, a corresponding wind speed adjustment strategy is matched according to a combination of the frequency characteristics and the amplitude characteristics of the wind pressure fluctuation.

5. The control system of the konjak flour winnowing machine according to claim 4, wherein The wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation is characterized by high frequency and small amplitude fluctuation, the matched wind speed adjustment strategy is to fine-tune the current wind speed.

6. The control system of the konjak flour winnowing machine according to claim 4, wherein The wind speed adjustment strategy matching module is preset with the following: when the wind pressure fluctuation is characterized by low frequency and large fluctuation, the matched wind speed adjustment strategy is to perform step-by-step adjustment on the current wind speed.

7. The control system of the konjak flour winnowing machine according to claim 1, wherein The wind speed control module controls the fan actuator to adjust the wind speed so that the response delay is less than or equal to 0.5 seconds.

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