Intelligent adjustment system and method for paddle drying device

Abstract

The application relates to an intelligent adjusting system and method of a paddle drying device, which comprises a sensing unit and an adjusting unit. The sensing unit comprises a viscosity sensor, a temperature sensor and a fluidity sensor, the adjusting unit is in communication connection with the sensing unit, the viscosity parameter, the temperature parameter and the fluidity parameter are used to calculate a distiller's grains drying state index and a change trend thereof in real time, the change trend of the operating parameters of the paddle drying device is monitored in real time, and when the distiller's grains drying state index reaches a preset adjusting threshold, an instruction of increasing or reducing the stirring frequency is sent to a control module. According to the application, the drying state of the distiller's grains can be more accurately evaluated. The accurate evaluation avoids the low drying efficiency problem caused by single parameter or inaccurate evaluation in the traditional method. The dynamic adjusting mode of the adjusting unit can optimize the stirring frequency according to the real-time drying state, and over-drying or under-drying is avoided, so that the drying efficiency is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of distillers' grains drying technology, and in particular to an intelligent adjustment system and method for paddle drying. Background Technology

[0002] Paddle dryers, as an indirect heating drying device, are widely used for drying materials with high moisture content. Their core structure consists of a hollow shell, wedge-shaped paddle shafts, and a jacketed heating system. Heat transfer and moisture evaporation are achieved through full contact between the rotating paddles and the material. However, in the drying process of highly viscous materials such as distiller's grains, this equipment has significant technical defects, leading to poor drying effects and high moisture content in the finished product.

[0003] When drying distiller's grains in a paddle dryer, the distinctive characteristics of the distiller's grains lie primarily in their high moisture content and high viscosity. Distiller's grains are a byproduct of the brewing process, containing a large amount of water and organic matter, which makes them highly adhesive and poorly fluid during drying. This high moisture content and viscosity cause the distiller's grains to easily clump together during drying, making it difficult to disperse evenly within the dryer and thus affecting drying efficiency. Furthermore, the organic matter in the distiller's grains is prone to chemical changes at high temperatures, producing volatile organic compounds (VOCs). These substances may not only affect the operational stability of the dryer but also potentially pollute the environment.

[0004] Currently, there is a lack of intelligent control systems for paddle drying specifically designed for the drying of distiller's grains.

[0005] For example, CN116874160A discloses a paddle-type drying device that uses steam to indirectly heat sludge, including a dryer shell and a hollow paddle shaft. The hollow paddle shaft is coaxially arranged inside the dryer shell, which is inclined. The hollow paddle shaft is a hollow structure, and several hollow paddles are arranged axially inside the dryer shell. One end of the hollow paddle shaft is sealed and connected to a motor, and the other end is provided with a hot steam inlet and a condensate outlet. The hollow paddles include stationary blades and moving blades, which are interlaced in the gaps between other blades. The stationary blades are fixedly arranged on the inner wall of the dryer shell, and the moving blades and the hollow paddle shaft have interconnected steam spaces and condensate channels. In this invention, the paddle shaft, moving and stationary blades, and the walls continuously squeeze, roll, stir, and rub the sludge during operation, achieving dynamic self-cleaning and efficient heat transfer during relative rotation, reducing the thermal resistance of steam between the structural components and the sludge, and completely eliminating the dead zone in sludge drying.

[0006] This paddle-type dryer is unsuitable for drying distiller's grains. Firstly, the physical characteristics of distiller's grains include high moisture content, high viscosity, and a tendency to clump during drying. These characteristics cause the distiller's grains to easily adhere to the heat transfer surfaces of the paddle-type dryer, forming clumps and hindering heat and mass transfer. Therefore, the aforementioned paddle-type dryer cannot completely solve the adhesion problem for such a highly viscous material as distiller's grains.

[0007] Secondly, the lees undergo different drying stages during the drying process, from a fluid state to a viscous state, and then to a solid state. In the viscous state, the lees have poor flowability and are prone to forming dead zones within the dryer, leading to uneven drying. Although the aforementioned paddle dryer reduces the formation of dead zones through the inclined arrangement of the dryer shell and the relative rotation of the moving and stationary blades, uneven drying still exists for materials like lees that have poor flowability in the viscous state.

[0008] Furthermore, the aforementioned paddle dryer employs indirect condensation heating with low-pressure steam. While this method may be effective in treating sludge, its high water content and viscosity can negatively impact the heat transfer efficiency of the steam, particularly for distiller's grains. Determining precisely when to increase and decrease the stirring frequency is difficult, causing the control system to frequently miss effective drying timing, resulting in poor drying of the distiller's grains.

[0009] Therefore, due to the special physical properties of the lees, the above-mentioned paddle-type drying device may have technical defects such as adhesion, uneven drying, low heat transfer efficiency, and poor drainage of condensate when processing lees.

[0010] In summary, existing paddle dryers have failed to adequately adapt to the physical characteristics of distiller's grains in terms of structural design and control strategies, resulting in problems such as low drying efficiency, high energy consumption, and unstable product quality.

[0011] The present invention aims to provide a paddle drying device and its adjustment system suitable for the physical properties of distiller's grains, thereby improving the drying efficiency of distiller's grains.

[0012] Furthermore, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making this invention, but due to space limitations, not all details and contents were listed in detail. However, this does not mean that the present invention does not possess the features of these prior art. On the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art. Summary of the Invention

[0013] Currently available paddle dryers are not suitable for drying distiller's grains. Firstly, distiller's grains have a high moisture content, strong viscosity, and a tendency to clump during drying. These physical properties cause the distiller's grains to easily adhere to the heat transfer surfaces of the paddle dryer, forming lumps that affect heat and mass transfer efficiency. This type of equipment struggles to effectively address the adhesion problem caused by highly viscous materials like distiller's grains.

[0014] Secondly, the lees undergo several stages of change during the drying process, gradually transitioning from an initial fluid state to a viscous state, and finally becoming a solid. During the viscous stage, the lees' fluidity decreases significantly, easily creating stagnant areas within the dryer and causing uneven drying. Although this paddle dryer, through its inclined design and the relative rotation between the moving and stationary blades, reduces the formation of stagnant areas to some extent, it is still difficult to achieve uniform drying for lees with poor fluidity in the viscous state.

[0015] To address the shortcomings of existing technologies, this invention provides an intelligent adjustment system for a paddle dryer, comprising a sensing unit and an adjustment unit. The sensing unit includes a viscosity sensor, a temperature sensor, and a flowability sensor. The adjustment unit is communicatively connected to the sensing unit. Based on the viscosity parameters collected by the viscosity sensor, the temperature parameters collected by the temperature sensor, and the flowability parameters collected by the flowability sensor, the system calculates the lees drying state index and its changing trend in real time. It also monitors the changing trends of the operating parameters of the paddle dryer in real time. When the lees drying state index reaches a preset adjustment threshold, the system sends a command to the control module to increase or decrease the stirring frequency.

[0016] This invention integrates viscosity, temperature, and flowability sensors, combined with real-time dynamic adjustment, to accurately identify adhesion risks caused by the high viscosity and tendency to agglomerate during the drying process of distiller's grains. When an increased adhesion trend is detected, the system adjusts the stirring frequency (e.g., increasing stirring intensity) to disrupt the adhesion between the material and the heat transfer surface, thereby effectively inhibiting the formation of lumps, improving heat and mass transfer efficiency, and solving the shortcomings of traditional paddle dryers in dealing with the adhesion problem of highly viscous materials.

[0017] According to a preferred embodiment, the system further includes a feedback unit. The feedback unit establishes a communication connection with the operation monitoring module and the adjustment unit of the paddle drying device, and calculates the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft based on the operation monitoring data of the paddle. The feedback unit judges the accuracy of the command based on the changing trends of the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft. In the case of an incorrect command, the feedback unit sends a readjustment command to the adjustment unit.

[0018] The feedback unit dynamically verifies the execution effect of commands by monitoring the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft. For example, if the current or vibration data does not improve synchronously after the system issues a command to increase the stirring frequency, the feedback unit determines that the command has failed and triggers a readjustment mechanism to avoid abnormal equipment operation caused by adhesion or agglomeration. This design solves the defects of poor fluidity due to viscous state and the difficulty of achieving uniform drying in traditional equipment during the drying process of distiller's grains, ensuring that the stirring parameters match the actual drying state.

[0019] According to a preferred embodiment, the step of the adjustment unit calculating the lees drying state index in real time based on viscosity parameters, temperature parameters, and flowability parameters includes: calculating the dynamic weights of various parameters based on dynamic scoring functions, and calculating the lees drying state index using a nonlinear weighting method based on the dynamic weights of various parameters.

[0020] This invention presents a method for calculating the drying state index based on dynamic weighting and a nonlinear weighted algorithm. This method integrates multidimensional parameters such as viscosity, temperature, and flowability to dynamically adapt to the changing characteristics of distiller's grains at different drying stages (e.g., from fluid to viscous to solid). This algorithm can more accurately reflect the real-time drying state of the distiller's grains, avoiding misjudgments caused by a single parameter, thereby optimizing the stirring frequency adjustment strategy and alleviating the problem of uneven drying caused by poor flowability in the viscous state.

[0021] According to a preferred embodiment, the adjustment unit predicts the predicted values ​​and dynamic trends of the smoothing coefficients of the viscosity, temperature, and flowability parameters. Based on these predicted values, the adjustment unit calculates a lees drying state prediction index. When both the lees drying state index and the lees drying state prediction index are greater than a first adjustment threshold, the adjustment unit sends a command to the control module to increase the stirring frequency. When both the lees drying state index and the lees drying state prediction index are less than a second adjustment threshold, the adjustment unit sends a command to the control module to decrease the stirring frequency.

[0022] By predicting the dynamic change trend of parameters through the smoothing coefficient, the system can predict the evolution direction of the drying state of the lees in advance (such as a sudden increase in viscosity or a sudden decrease in fluidity), and combine the prediction index and the current index dual threshold judgment to realize the forward-looking adjustment of the stirring frequency.

[0023] According to a preferred embodiment, the feedback unit calculates the operating resistance index of the paddle dryer based on the motor current change rate and the stirring shaft vibration frequency change rate. The operating resistance index is used to reflect the resistance encountered during the mixing of the lees in real time, and the resistance is related to the drying state of the lees.

[0024] The introduction of the operating resistance index, through quantitative analysis of motor current and vibration frequency, directly reflects the resistance changes caused by adhesion or agglomeration during the mixing of distiller's grains. The correlation analysis between the operating resistance index and the drying state index (e.g., increased resistance corresponds to enhanced adhesion) helps the system more accurately assess the adhesion risk of the distiller's grains, thereby dynamically adjusting mixing parameters to avoid a decrease in heat and mass transfer efficiency due to adhesion problems, and compensating for the shortcomings of traditional equipment in handling viscous materials.

[0025] According to a preferred embodiment, when the adjustment unit determines that the lees drying state index has reached a preset adjustment threshold, the adjustment unit generates a confirmation instruction and sends it to the feedback unit; in response to the confirmation instruction, the feedback unit sends an instruction confirmation result to the adjustment unit; when the operating resistance index and the lees drying state index show opposite trends, the feedback unit determines that the current blade operating resistance matches the drying state and instructs the adjustment unit to adjust the confirmation instruction to a confirmed instruction; when the operating resistance index and the lees drying state index show non-inverse trends, the feedback unit determines that the current blade operating resistance does not match the drying state and that the confirmation instruction is incorrect, and sends a readjustment instruction to the adjustment unit; thereby, the adjustment unit recalculates the lees drying state index to confirm the true drying state of the lees.

[0026] The collaborative mechanism between the pending confirmation command and the feedback unit can identify whether the command meets the actual needs by comparing the changing trends of the operating resistance index and the drying state index. For example, when the command requires an increase in stirring frequency but the resistance index does not decrease synchronously, the system determines that the command is incorrect and triggers a recalculation, thereby avoiding over- or under-stirring due to incorrect adjustment and solving the problem of uneven drying of the lees caused by poor fluidity during the viscous stage.

[0027] According to a preferred embodiment, when the feedback unit determines that the operating state of the paddle drying device cannot increase the stirring frequency based on the rate of change of motor current and the rate of change of stirring shaft vibration frequency, in response to the pending confirmation command sent by the regulating unit, the feedback unit sends a negative command to the regulating unit so that the regulating unit cancels the pending confirmation command.

[0028] The negative instruction function can proactively terminate the execution of erroneous instructions when the feedback unit detects that the equipment's operating status cannot meet the adjustment requirements (such as motor overload or abnormal vibration). For example, when the system attempts to increase the stirring frequency but the motor current is already close to its limit, triggering the negative instruction can prevent equipment damage and avoid grain clumping or expansion of the stirring dead zone caused by forced adjustment, thereby ensuring the stability and uniformity of the drying process.

[0029] The present invention provides a second aspect of an intelligent adjustment method for a paddle drying device. The method includes: collecting viscosity parameters, temperature parameters, and flowability parameters of the lees; calculating the lees drying state index and its changing trend in real time based on the viscosity parameters, temperature parameters, and flowability parameters, and monitoring the changing trend of the operating parameters of the paddle drying device in real time; and sending an instruction to the control module to increase or decrease the stirring frequency when the lees drying state index reaches a preset adjustment threshold.

[0030] This method significantly improves the accuracy of calculating the distillers' grains drying state index by real-time acquisition and comprehensive calculation of multi-dimensional parameters (viscosity, temperature, and flowability) combined with dynamic monitoring of operating parameters. Compared with traditional methods that adjust single parameters or static thresholds, this method can more accurately capture the characteristic changes of distillers' grains at different drying stages (such as the viscous state), avoiding adjustment delays caused by parameter lag or misjudgment. Simultaneously, the real-time monitoring and command triggering mechanism optimizes equipment operating efficiency, quickly adjusting the stirring frequency when there is a risk of grain adhesion or decreased flowability, reducing agglomeration and dead zones on the heat transfer surface, thereby reducing energy consumption and improving drying uniformity.

[0031] According to a preferred embodiment, the method further includes: calculating the rate of change of motor current and the rate of change of vibration frequency of stirring shaft based on the operating monitoring data of the impeller; the feedback unit judges the accuracy of the command based on the changing trends of the rate of change of motor current and the rate of change of vibration frequency of stirring shaft; and in the case of an incorrect command, the feedback unit sends a readjustment command to the adjustment unit.

[0032] By introducing feedback verification of the motor current change rate and the agitator shaft vibration frequency change rate, this method further verifies the accuracy of the adjustment strategy after the command is executed, significantly reducing erroneous operations caused by parameter misjudgment or external interference. For example, when the system issues a command to increase the agitation frequency, if the current or vibration data does not improve synchronously, the feedback mechanism can promptly correct the erroneous command, avoiding the negative impact of ineffective operations on equipment operating efficiency. This design not only improves the reliability of calculation results but also reduces energy waste and equipment wear caused by incorrect adjustments, thereby improving overall operating efficiency and system stability.

[0033] According to a preferred embodiment, the method further includes: calculating a lees drying state prediction index based on the predicted values ​​and dynamic trends of smoothing coefficient prediction parameters for viscosity, temperature, and flowability parameters; sending an instruction to increase the stirring frequency when both the lees drying state index and the lees drying state prediction index are greater than a first adjustment threshold; and sending an instruction to decrease the stirring frequency when both the lees drying state index and the lees drying state prediction index are less than a second adjustment threshold.

[0034] Based on a smoothing coefficient-based parameter prediction algorithm, this method can predict the evolution trend of the drying state of distiller's grains (such as a sudden increase in viscosity or a sudden decrease in fluidity) in advance, and achieve proactive adjustment through dual threshold judgment of the predicted index and the current index. Compared with traditional adjustment methods that rely on real-time status, the predictive strategy significantly improves the forward accuracy of the calculation results and avoids over- or under-stirring due to hysteresis response. In addition, the dynamic prediction algorithm reduces the formation of dead zones caused by poor fluidity in the equipment during the viscous stage, optimizes the timing of stirring parameter adjustment, thereby reducing energy consumption and improving drying efficiency and uniformity. Attached Figure Description

[0035] Figure 1 This is a simplified schematic diagram of the module connection relationship of the intelligent adjustment system of the paddle drying device provided by the present invention;

[0036] Figure 2 This is a schematic diagram of the intelligent adjustment system of the paddle drying device provided by the present invention;

[0037] Figure 3 This is a flowchart illustrating the intelligent adjustment method for the paddle drying device provided by the present invention.

[0038] List of reference numerals

[0039] 100: Paddle drying device; 110: Operation monitoring module; 120: Control module; 200: Intelligent adjustment system; 210: Sensing unit; 211: Viscosity sensor; 212: Temperature sensor; 213: Flowability sensor; 220: Adjustment unit; 221: First calculation module; 222: Second calculation module; 223: Instruction generation module; 230: Feedback unit; 231: Judgment module; 232: Third calculation module; 240: Storage unit. Detailed Implementation

[0040] The following is a detailed explanation with reference to the accompanying drawings.

[0041] In existing paddle dryers 100, the drying process is typically regulated by a single parameter (such as temperature or viscosity) or by a simple linear adjustment strategy. These methods have significant technical drawbacks: First, existing technologies usually rely on a single parameter to determine the drying state, ignoring the influence of other key parameters (such as flowability), resulting in an incomplete assessment of the drying state and potential misjudgments. Second, existing technologies typically employ fixed adjustment strategies, failing to dynamically adjust the stirring frequency based on real-time data, making it difficult for the drying process to adapt to different drying states, leading to low drying efficiency or over-drying. Furthermore, existing technologies typically focus only on current operating parameters, ignoring trends in parameter changes, making it impossible for the system to predict changes in the drying state in advance and thus unable to adjust the stirring frequency in a timely manner. Finally, existing technologies typically rely on human experience or simple logical judgment, lacking intelligence and adaptive capabilities, making it difficult for the system to cope with complex drying processes and achieve efficient and stable drying.

[0042] Therefore, how to change the stirring frequency of the paddle at the appropriate time to maximize drying efficiency and extend equipment life is a technical problem that current technology has not yet solved.

[0043] This application provides an intelligent adjustment system 200 and method for a paddle drying device 100. The present invention can also provide an intelligent paddle drying device 100 including the intelligent adjustment system 200 of the present invention. The present invention can also provide a processor or server applicable to paddle drying devices 100 of various specifications, used to control the timing of changes in the stirring frequency of the paddle drying device 100.

[0044] The intelligent adjustment system 200 of the blade drying device 100 of this application is used to execute the intelligent adjustment method of the blade drying device 100.

[0045] like Figure 3 As shown, the intelligent adjustment method is as follows: collecting the viscosity, temperature and fluidity parameters of the lees; calculating the lees drying state index and its changing trend in real time based on the viscosity, temperature and fluidity parameters, and monitoring the changing trend of the operating parameters of the paddle dryer 100 in real time; when the lees drying state index reaches the preset adjustment threshold, sending a command to the control module 120 to increase or decrease the stirring frequency.

[0046] The specific steps of this intelligent adjustment method are described together with the structure of the intelligent adjustment system 200. In this application, it is assumed that each unit is equipped with a wired and / or wireless communication interface.

[0047] like Figure 1As shown, the operation monitoring module 110 of the paddle drying device 100 establishes a communication connection with the intelligent control system 200 via wired or wireless means. The physical hardware of the operation monitoring module 110 may include operation sensors, a data acquisition unit, a microprocessor, and a communication module. The operation sensors are used to collect real-time operating parameters of the paddle drying device, such as the vibration frequency of the stirring shaft and the motor current. The data acquisition unit is used to perform preliminary processing and storage of the data collected by the operation sensors. The microprocessor is used to further analyze and calculate the collected data to generate monitoring results of the operating status. The communication module is used to transmit these monitoring results to the intelligent control system 200 via wired or wireless means, so that the intelligent control system 200 can make corresponding adjustments and controls based on the real-time data. These hardware components together constitute the operation monitoring module 110, ensuring the efficient and stable operation of the paddle drying device 100.

[0048] like Figure 1 and Figure 2 As shown, the intelligent control system 200 includes a sensing unit 210 and a control unit 220. The control unit 220 and the sensing unit 210 are connected in a wired or wireless manner.

[0049] like Figure 1 and Figure 2 As shown, the sensing unit 210 includes a viscosity sensor 211, a temperature sensor 212, and a flowability sensor 213. The sensing unit 210 is used to collect the viscosity parameters, temperature parameters, and flowability parameters of the distiller's grains, and transmit them to the regulating unit 220 through a communication interface.

[0050] Preferably, the viscosity sensor 211 is typically a vibration sensor or a rotation sensor, which calculates the viscosity of the distiller's grains by measuring the resistance of the fluid to vibration or rotation. The viscosity sensor 211 is usually installed near the inlet or outlet of the paddle dryer 100, as changes in the viscosity of the distiller's grains at these locations directly affect drying efficiency and product quality. During installation, the viscosity sensor 211 can be installed using an immersion type or a surface contact type to ensure accurate detection of changes in fluid viscosity.

[0051] Preferably, at least two viscosity sensors 211 are located in the pipes or channels at the material inlet and outlet, respectively. These two viscosity sensors 211 are arranged one after the other along the material flow direction, and their relative positions should ensure that the viscosity changes of the material during the drying process can be monitored. The installation angle of the viscosity sensors 211 should be consistent with the material flow direction to reduce measurement errors.

[0052] Temperature sensor 212 typically employs a thermocouple or thermistor, generating a corresponding electrical signal based on changes in fluid temperature. It is installed in the heat exchange area of ​​the paddle dryer 100, such as near the heating jacket or hot air duct, to monitor temperature changes during the drying process in real time. Temperature sensor 212 is usually surface-mounted or embedded to ensure good thermal contact with the heating surface, thereby improving the accuracy of temperature measurement.

[0053] At least two temperature sensors 212 are present, located at the upper and lower parts of the heat exchange area, respectively, to monitor the temperature distribution at different heights. These two temperature sensors 212 are arranged vertically, and their relative positions should ensure a comprehensive reflection of temperature changes within the heat exchange area. The installation angle of the temperature sensors 212 is perpendicular to the heat exchange surface to improve the accuracy of temperature measurements.

[0054] The flow sensor 213 can be an ultrasonic sensor or a photoelectric sensor, which assesses flowability by detecting the movement of particles in the fluid or the flow velocity of the fluid. The flow sensor 213 communicates with the regulating unit 220 via wired or wireless means to jointly achieve intelligent regulation of fluid characteristics. The flow sensor 213 is installed inside the paddle dryer 100, especially in the paddle stirring area, to monitor changes in the flowability of the distiller's grains during the drying process.

[0055] For example, the flowability sensor 213 can be installed on the side or top of the impeller blades, close to the surface where the material flows. This allows for real-time monitoring of changes in the flowability of the material during the mixing process, especially the flow state of the material under the action of the impeller blades.

[0056] The flowability sensor 213 can also be installed on the inner wall of the drying chamber, near the periphery of the paddle stirring area. This allows monitoring of the flowability of the material near the inner wall of the drying chamber, especially the flow characteristics between the material and the chamber wall under the action of the paddle stirring.

[0057] The flowability sensor 213 can also be installed inside the material layer, i.e., in the area where the material accumulates within the drying chamber. This allows for more direct monitoring of changes in the flowability of the material during the drying process, especially when there are changes in the thickness of the material layer or movement of material particles.

[0058] The flow sensor 213 can be installed in a non-contact manner, such as an ultrasonic sensor or a photoelectric sensor, to avoid interference with the drying process while ensuring accurate capture of the fluid's flow characteristics.

[0059] At least two flowability sensors 213 are used, located at the upper and lower parts of the stirring zone, respectively, to monitor changes in the flowability of the material at different heights. These two flowability sensors 213 should be arranged front-to-back along the stirring axis, and their relative positions should ensure comprehensive capture of the material's flowability characteristics. The installation angle of the flowability sensors 213 should be consistent with the stirring axis to reduce measurement errors.

[0060] The adjustment unit 220 calculates the lees drying state index and its changing trend in real time based on viscosity, temperature, and flowability parameters, and monitors the changing trends of the operating parameters of the paddle dryer 100 in real time. When the lees drying state index reaches a preset adjustment threshold, the adjustment unit 220 generates a corresponding instruction and sends an instruction to the control module 120 to increase or decrease the stirring frequency through the communication interface.

[0061] The control module 120 is used to control the operating status of the paddle drying device 100. Specifically, the control module 120 receives instructions from the adjustment unit 220 and performs an adjustment operation on the stirring frequency.

[0062] According to a preferred embodiment, the system further includes a feedback unit 230. The feedback unit 230 establishes a communication connection with the operation monitoring module 110 and the adjustment unit 220 of the paddle drying device 100. Preferably, the adjustment unit 220 and the feedback unit 230 can be configured as independent processors, or they can be integrated into a central processing unit, logic processor, or dedicated integrated chip.

[0063] The rate of change of motor current reflects the change in motor load. During the mixing process, changes in the viscosity, temperature, and flowability of the material directly affect the mixing resistance, thus affecting the motor load and current. The rate of change of the vibration frequency of the mixing shaft reflects the change in mechanical vibration conditions. Abnormal changes in the vibration frequency of the mixing shaft usually correspond to changes in mechanical load, changes in material flow pattern, or equipment failure.

[0064] Feedback unit 230 calculates the rate of change of motor current and the rate of change of vibration frequency of the agitator shaft based on the operating monitoring data of the impeller. Feedback unit 230 judges the accuracy of the command based on the changing trends of the rate of change of motor current and the rate of change of vibration frequency of the agitator shaft. In the event of an incorrect command, feedback unit 230 sends a readjustment command to adjustment unit 220. In response to receiving the readjustment command, adjustment unit 220 recalculates the lees drying state index to avoid issuing erroneous commands.

[0065] In this embodiment, the readjustment command refers to a corrective control signal actively sent by the feedback unit 230 to the adjustment unit 220 when the feedback unit 230 identifies a deviation between the current execution command and the actual state of the system by real-time monitoring of the motor current change rate and the stirring shaft vibration frequency change rate.

[0066] As the lees gradually dry, the stirring resistance increases, the motor load increases, and the motor current rises, with a positive rate of change (upward trend). Due to the increased stirring load, mechanical vibration may intensify, and the rate of change of the stirring shaft vibration frequency also shows an upward trend.

[0067] As the fluidity of the distiller's grains deteriorates (material flowability decreases), the stirring load increases, the motor current rises, and the rate of change of the motor current is positive. Mechanical vibration intensifies, and the rate of change of the vibration frequency of the stirring shaft increases.

[0068] If the command to increase the stirring frequency issued by the regulating unit 220 is correct, the trends of the motor current change rate and the stirring shaft vibration frequency change rate should change from an upward trend to a downward trend after the command is executed. This is because increasing the stirring frequency will increase the rotational speed of the stirring paddle, enhance the stirring intensity, make the material more evenly stressed, and make it easier to break up or disperse the high-viscosity lees. After the lees are broken up, the overall flow pattern improves, the apparent viscosity decreases, and the fluidity increases, thereby reducing the stirring resistance and lowering the motor load.

[0069] Specifically, when the viscosity has increased and the regulating unit 220 has just issued a command to increase the stirring frequency, the motor current and the vibration frequency of the stirring shaft may continue to rise briefly (inertia effect). Immediately afterwards, due to the material crushing effect brought about by the increase in stirring frequency, the motor current and the vibration frequency of the stirring shaft should show a clear turning point and begin to decrease, indicating that the load has been reduced and the command has taken effect.

[0070] Preferably, the manifestation of an incorrect instruction is that the changing trends of the motor current and the vibration frequency of the stirring shaft do not conform to the expected direction of the instruction, and there is no obvious turning point, continuous increase or continuous decrease.

[0071] For example, if the motor current and vibration frequency continue to rise for an extended period after the regulating unit 220 issues the command to "increase the stirring frequency" without any downward trend, it indicates that the material has not been effectively crushed, the load has not been reduced, the command execution effect is poor, or the equipment is malfunctioning. If the motor current and stirring shaft vibration frequency do not decrease but instead increase after the regulating unit 220 issues the command to "decrease the stirring frequency," this is also considered a command error.

[0072] Preferably, the feedback unit 230's judgment time window for the changing trend is 10-30 seconds. After the instruction from the adjustment unit 220 is issued, the feedback unit 230 monitors the trends of the motor current change rate and the stirring shaft vibration frequency change rate. If no obvious reversal from rising to falling (or from falling to rising) occurs within 10-30 seconds, it can be determined that the instruction execution effect is not ideal and is considered an instruction error.

[0073] More preferably, the feedback unit 230's judgment time window for the changing trend is preferably 10s, 15s, 20s, 25s, and 30s. For example, if there is no change in 10s, the feedback unit 230 sends a warning message to the adjustment unit 220; if there is still no change in 30s, the feedback unit 230 finally determines that the instruction is wrong and triggers the corresponding action.

[0074] More preferably, to avoid signal noise interference, the turning point of the change trend should meet a certain amplitude change threshold, and the change trend needs to last for at least several seconds. This amplitude change threshold is preferably 5% to 10%.

[0075] According to a preferred embodiment, the system further includes a storage unit 240. The storage unit 240 is communicatively connected to the sensing unit 210, the adjustment unit 220, and the feedback unit 230 via wired or wireless means, for storing data from each unit and allowing each unit to access historical data. The storage unit 240 also stores pre-set encoding programs for various data tables or calculation models, allowing each unit to access them. Preferably, the storage unit 240 can be a memory chip.

[0076] This application significantly improves production efficiency. The sensing unit 210 collects the viscosity, temperature, and flowability parameters of the distiller's grains in real time through a viscosity sensor 211, a temperature sensor 212, and a flowability sensor 213. The adjustment unit 220 calculates the dryness index of the distiller's grains and its changing trend based on these parameters. This multi-parameter integrated monitoring can more comprehensively and accurately reflect the dryness state of the distiller's grains, avoiding misjudgments that may occur with single-parameter monitoring, thereby improving the stability and efficiency of the production process. When the dryness index of the distiller's grains reaches a preset adjustment threshold, the adjustment unit 220 generates instructions to increase or decrease the stirring frequency. This dynamic adjustment strategy can optimize the stirring frequency according to the real-time drying state, avoiding over-drying or under-drying, thereby improving production efficiency.

[0077] In terms of equipment maintenance, the operation monitoring module 110 monitors the operating parameters of the paddle dryer 100 in real time (such as motor current, stirring shaft vibration frequency, etc.), and calculates the rate of change of motor current and the rate of change of stirring shaft vibration frequency through the feedback unit 230. This data is used not only for instruction judgment but also for real-time monitoring of equipment operating status. When abnormal monitoring data occurs, the system can issue an early warning, helping maintenance personnel to promptly identify and handle potential faults, reducing the risk of equipment downtime and improving maintenance convenience. The feedback unit 230 can determine the accuracy of instructions based on the operation monitoring data. If the instruction is incorrect, the feedback unit 230 will send a readjustment instruction to the adjustment unit 220, avoiding equipment damage or decreased production efficiency due to incorrect instructions, further improving equipment reliability and maintenance convenience.

[0078] In terms of response speed, the regulating unit 220 quickly calculates the lees drying state index and its changing trend based on real-time data from the sensing unit 210, and generates instructions. This real-time data acquisition and processing mechanism significantly improves the system's regulating response speed. The feedback unit 230 can quickly determine the accuracy of the instructions based on operational monitoring data, and send a readjustment instruction to the regulating unit 220 in case of an error. This rapid correction mechanism further shortens the regulating response time, ensuring the continuity and stability of the drying process.

[0079] like Figure 1 and Figure 2 As shown, the adjustment unit 220 includes a first calculation module 221, a second calculation module 222, and an instruction generation module 223. The first calculation module 221 and the second calculation module 222 are respectively communicatively connected to the instruction generation module 223.

[0080] The first calculation module 221 is used to calculate the lees drying state index in real time based on viscosity parameters, temperature parameters, and flowability parameters, and send it to the instruction generation module 223, such as... Figure 2 As shown.

[0081] Specifically, the first calculation module 221 calculates the dynamic weights based on a dynamic scoring function of viscosity parameters, temperature parameters, and flowability parameters.

[0082] Preferably, the dynamic weight of the viscosity parameter is set to W. V (t), the dynamic weight of the temperature parameter is W. T (t), where the dynamic weight of the liquidity parameter is W. L (t). The first calculation module 221 uses recursive least squares (RLS) or a Kalman filter to dynamically adjust the weights so that they can better adapt to real-time changes in parameters.

[0083]

[0084] In the above formula, f V (V(t)) represents the dynamic scoring function of the viscosity parameter, f T (T(t)) represents the dynamic scoring function of the temperature parameter, f L (L(t)) represents the dynamic scoring function of the liquidity parameter.

[0085]

[0086] In the above formula, V opt T represents the optimal value of the viscosity parameter. opt L represents the optimal value of the temperature parameter. opt This represents the optimal value of the liquidity parameter.

[0087] The first calculation module 221 calculates the lees drying state index using a nonlinear weighting method based on the dynamic weights of viscosity parameters, temperature parameters, and flowability parameters.

[0088] The formula for calculating the dry state index of distiller's grains in the first calculation module 221 is as follows:

[0089]

[0090] In the above formula, V norm (t) represents the standardized viscosity parameter value, T norm (t) represents the standardized temperature parameter value, L norm (t) represents the standardized value of the flowability parameter. α represents the nonlinear adjustment parameter for the viscosity parameter, β represents the nonlinear adjustment parameter for the temperature parameter, and γ represents the nonlinear adjustment parameter for the flowability parameter.

[0091] The second calculation module 222 is used to calculate the prediction index of the drying state of the distiller's grains and send it to the instruction generation module 223, such as... Figure 2 As shown.

[0092] Specifically, the second calculation module 222 in the adjustment unit 220 predicts the predicted values ​​and dynamic trends of parameters based on the smoothing coefficients of viscosity parameters, temperature parameters, and flowability parameters.

[0093] The second calculation module 222 calculates the predicted index of the drying state of distiller's grains based on the predicted values ​​of viscosity parameters, temperature parameters, and flowability parameters.

[0094] Preferably, in order to capture the dynamic changing trend of the parameters, the second calculation module 222 uses exponential smoothing to predict the parameters:

[0095] V pred (t+1)=α V ·V(t)+(1-α V )·Vpred (t);

[0096] T pred (t+1)=α T ·T(t)+(1-α T )·T pred (t);

[0097] V pred (t+1)=α L ·L(t)+(1-α L )·V pred (t).

[0098] In the above formula, α V α represents the smoothing coefficient of the viscosity parameter. T α represents the smoothing coefficient of the temperature parameter. L This represents the smoothing coefficient for the fluidity parameter. Using the same formula, the predictive index for the drying state of the distiller's grains can be calculated.

[0099] When I(t)>I inc And I pred (t+1)>I inc At that time, that is, when both the lees drying state index and the lees drying state prediction index are greater than the first adjustment threshold I. inc In this case, the instruction generation module 223 in the adjustment unit 220 generates and sends an instruction to the control module 120 to increase the stirring frequency, such as... Figure 2 As shown.

[0100] When I(t)<I dec And I pred (t+1)<I dec At that time, that is, when both the lees drying state index and the lees drying state prediction index are less than the second adjustment threshold I. dec In this case, the instruction generation module 223 in the adjustment unit 220 generates and sends an instruction to the control module 120 to reduce the stirring frequency, such as... Figure 2 As shown.

[0101] This application enables a more precise assessment of the drying state of the distiller's grains. This precise assessment avoids the low drying efficiency problems caused by single parameters or inaccurate assessments in traditional methods. The dynamic adjustment mode of the adjustment unit 220 can optimize the stirring frequency according to the real-time drying state, avoiding over-drying or under-drying, thereby significantly improving drying efficiency.

[0102] For example, at time t, the viscosity parameter is 1.2 Pa·s, the temperature parameter is 65℃, and the flowability parameter is 0.8 m / s.

[0103] The standardized parameter values ​​are:

[0104] V norm (t) = 0.7; T norm (t) = 0.6; L norm (t) = 0.8.

[0105] The scoring function for dynamic weights is:

[0106]

[0107] The dynamic weights are:

[0108]

[0109] Therefore, the dryness index of the distiller's grains is:

[0110]

[0111] When the first adjustment threshold I inc If I(t) = 0.7, then I(t) = 0.62 < 0.7. In this case, the instruction generation module 223 in the adjustment unit 220 generates and sends an instruction to the control module 120 to reduce the stirring frequency.

[0112] According to a preferred embodiment, the feedback unit 230 includes a judgment module 231 and a third calculation module 232.

[0113] The third calculation module 232 is used to calculate the rate of change of motor current, the rate of change of vibration frequency of the stirring shaft, and the working resistance index. The working resistance index is used to reflect the resistance encountered during the mixing of the distiller's grains in real time, and the resistance is related to the drying state of the distiller's grains. The judgment module 231 is used to determine whether the instruction to be confirmed is erroneous, and sends the instruction confirmation result to the instruction generation module 223, such as... Figure 2 As shown.

[0114] A pending confirmation instruction refers to a preliminary control instruction (such as increasing or decreasing the stirring frequency) generated by the regulating unit 220 based on parameters such as viscosity, temperature, and flowability provided by the sensing unit 210 in the intelligent regulating system of the paddle dryer. However, this instruction is not yet verified by the feedback unit 230 through real-time monitoring based on the rate of change of motor current and the rate of change of stirring shaft vibration frequency. The pending confirmation instruction requires the feedback unit to assess whether the current operating state meets the execution conditions. If the feedback unit 230 determines that the pending confirmation instruction matches the actual operating conditions, it confirms execution; if there is an anomaly (such as equipment overload risk or parameter deviation), it sends a negative instruction to cancel the operation. The core function of the pending confirmation instruction is to provide preliminary decision support for the regulating unit 220, while the verification mechanism of the feedback unit 230 ensures the safety and effectiveness of the instruction, avoiding equipment failure or process loss due to blind execution.

[0115] like Figure 2 As shown, the third calculation module 232 receives motor current and stirring shaft vibration frequency from the operation monitoring module 110 through the communication interface of the feedback unit 230. Preferably, the third calculation module 232 can also receive other types of operating parameters from the operation monitoring module 110.

[0116] The process by which the third calculation module 232 calculates the motor current change rate, the stirring shaft vibration frequency change rate, and the working resistance index of the blade drying device 100 is shown below.

[0117] Specifically, the motor current change rate is set to I. Δ The unit is A / s; the rate of change of the vibration frequency of the stirring shaft is set to f. Δ , Hz / s.

[0118]

[0119] In the above formula, ΔI represents the change in motor current within the time interval Δt, in amperes (A); Δt represents the change in time, in seconds (s); and Δf represents the change in vibration frequency of the stirring shaft within the time interval Δt, in hertz (Hz).

[0120] The nonlinear function is:

[0121]

[0122] In the above formula, γ1 and γ2 represent nonlinear coefficients, which are determined through testing.

[0123] To eliminate the dimensional differences, the third calculation module 232 normalizes the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft:

[0124]

[0125] In the above formula, I Δ,min I represents the minimum rate of change of motor current. Δ,max This represents the maximum rate of change of the motor current. f Δ,min f represents the minimum rate of change of the vibration frequency of the stirring shaft. Δ,max This represents the maximum rate of change of the vibration frequency of the stirring shaft.

[0126] The formula for calculating the operating resistance index in the third calculation module 232 is as follows:

[0127] R index =A·g(I Δ,min )+B·h(f Δ,min ).

[0128] In the above formula, g(I) Δ,minh(f) represents a nonlinear function of the normalized rate of change of motor current. Δ,min R represents a nonlinear function of the normalized rate of change of the stirring shaft vibration frequency. index This represents the operating resistance index. A represents the dynamic weighting coefficient of the motor current change rate, and B represents the dynamic weighting coefficient of the agitator shaft vibration frequency change rate.

[0129] The weighting coefficients A and B can be dynamically adjusted based on real-time data. For example, using fuzzy logic methods:

[0130] If the rate of change of motor current I Δ A relatively large value indicates that the resistance mainly comes from the motor current, so in this case, increase A.

[0131] If the rate of change of the vibration frequency of the stirring shaft is f Δ A relatively large value indicates that the resistance mainly comes from the vibration of the stirring shaft; in this case, increase B.

[0132] By using real-time data and optimization algorithms (such as gradient descent), the weighting coefficients A and B are dynamically adjusted to minimize the error of the resistance index.

[0133]

[0134] In the above formula, R index,i I represents the actual operating resistance index during the i-th test. Δ,i and f Δ,i Let represent the rate of change of motor current and the rate of change of vibration frequency of stirring shaft in the i-th test, and n represent the number of experiments.

[0135] For example, when the rate of change of motor current Set the vibration frequency change rate of the stirring shaft to f. Δ =0.2Hz / s, γ1=0.1, γ2=0.05, A=0.7, B=0.3, A+B=1. I Δ,min =0, I Δ,max =1,f Δ,min =0,f Δ,max =1.

[0136] So,

[0137] g(I Δ，norm )=(0.5) 2 +0.1·0.5=0.25+0.05=0.3;

[0138] h(f Δ，norm )=(0.2) 2 +0.05·0.2=0.04+0.01=0.05.

[0139] Rindex =0.7·0.3+0.3·0.05=0.21+0.015=0.225.

[0140] The operating resistance index is 0.225.

[0141] According to a preferred embodiment, when the adjustment unit 220 determines that the lees drying state index has reached a preset adjustment threshold, the instruction generation module 223 in the adjustment unit 220 generates a confirmation instruction and sends it to the feedback unit 230, such as... Figure 2 As shown. In response to the pending confirmation command, the feedback unit 230 sends the command confirmation result to the adjustment unit 220, such as... Figure 2 As shown.

[0142] Specifically, such as Figure 2 As shown, the third calculation module 232 sends the operating resistance index to the judgment module 231. The judgment module 231 sends an interaction command to the instruction generation module 223. Preferably, the interaction command includes time information (time period information) to retrieve the lees drying state index within the same time period corresponding to the operating resistance index. In response to the interaction command, the instruction generation module 223 sends the lees drying state index within the specified time period to the judgment module 231. The judgment module 231 receives the operating resistance index from the third calculation module 232 and compares the changing trends of the operating resistance index and the lees drying state index.

[0143] When the operating resistance index and the lees drying state index show opposite trends, the feedback unit 230 determines that the current impeller operating resistance matches the drying state. The judgment module 231 of the feedback unit 230 sends positive instructions such as "adjust the pending instruction to a confirmed instruction" or "instruction correct" to the instruction generation module 223 of the adjustment unit 220. The instruction generation module 223 then adjusts the pending instruction to a confirmed instruction.

[0144] A confirmed command is a final control signal that can be safely executed. The core function of a confirmed command is to ensure the rationality and safety of the adjustment operation through the mutual verification of two indicators (drying state index and operating resistance index), thereby improving drying efficiency and avoiding equipment risks caused by abnormal operating conditions.

[0145] When the operating resistance index and the lees drying state index do not change in opposite directions, the feedback unit 230 determines that the current blade operating resistance does not match the drying state and that the instruction to be confirmed is incorrect. The confirmation result of the instruction sent by the judgment module 231 of the feedback unit 230 to the instruction generation module 223 of the adjustment unit 220 is a readjustment instruction. In response to the receipt of the readjustment instruction, the instruction generation module 223 recalculates the lees drying state index and reconfirms the actual drying state of the lees.

[0146] The degree of dryness of the lees essentially determines its physical properties, especially the amount of resistance that hinders the movement of the paddle.

[0147] In theory, when the dryness index of the lees increases (indicating that the lees are gradually drying), the moisture content of the material decreases, the material becomes relatively loose, the viscosity decreases, and the running resistance of the paddle should decrease. Therefore, the working resistance index should decrease, and the two show opposite trends (when the dryness index of the lees increases, the working resistance index should decrease).

[0148] The two indicators, the lees drying state index and the operating resistance index, are obtained independently by different sensors and calculation modules. If their trends are opposite, it indicates that the feedback data from the sensors and calculation modules are mutually verifying each other, reflecting the true system state. At this point, the instruction generation module 223 can confirm that the current drying state judgment is accurate, and the instruction can be changed from "pending confirmation" to "confirmed," meaning that the system recognizes the rationality of the current adjustment operation.

[0149] If the lees drying state index and the operating resistance index do not show the expected inverse relationship (e.g., rising or falling simultaneously), the possible problems are: abnormal or biased sensor data leading to inaccurate calculated drying indices; equipment malfunctions or mechanical abnormalities, such as impeller jamming or abnormal resistance measurement; or complex material conditions, such as agglomeration or stratification, resulting in inconsistencies between resistance and drying state. In this case, the regulating unit 220 cannot simply rely on the current lees drying state index to make adjustment decisions. Therefore, the regulating unit 220 determines that the instruction to be confirmed is incorrect and needs to recalculate the lees drying state index to eliminate the abnormality, confirm the true drying state of the lees, and ensure the accuracy and safety of the drying process.

[0150] Therefore, the calculation of the operating resistance index of the feedback unit 230 can help the adjustment unit 220 more accurately determine the matching between the drying state and the operating resistance, further optimize the adjustment of the stirring frequency, and improve the drying efficiency.

[0151] According to a preferred embodiment, when the judgment unit in the feedback unit 230 determines that the operating state of the paddle dryer 100 cannot increase the stirring frequency based on the motor current change rate and the stirring shaft vibration frequency change rate, the feedback unit 230 sends a negative instruction to the adjustment unit 220 in response to the pending confirmation instruction sent by the adjustment unit 220, so that the adjustment unit 220 cancels the pending confirmation instruction.

[0152] In other words, the feedback unit 230 determines whether the current operating state of the paddle dryer 100 is suitable for increasing the stirring frequency based on the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft. It then responds to the pending confirmation command sent by the adjustment unit 220, and if necessary, sends a negative command to the adjustment unit 220 to cancel the adjustment operation. That is, the confirmation result of the command sent by the judgment module 231 to the command generation module 223 is a negative command.

[0153] A rejection command is a rejection signal actively sent by the feedback unit 230 to the adjustment unit 220. The core function of the rejection command is to promptly cancel unreasonable adjustment operations that may cause overload, failure, or efficiency reduction by monitoring the equipment load and mechanical status in real time, thereby ensuring the safety and stability of system operation.

[0154] The primary purpose of this design is to ensure the safe and stable operation of the equipment. Motor current and stirring shaft vibration frequency are crucial parameters reflecting the equipment's load and mechanical condition. When the system detects that the current state cannot withstand a higher stirring frequency, blindly executing commands to increase the frequency may lead to motor overload, mechanical failure, or even equipment damage. Therefore, the feedback unit 230 promptly cancels unreasonable adjustment requests through negative commands, avoiding potential risks. Furthermore, this mechanism enhances the intelligence level of the control system. Real-time feedback judgment forms a closed-loop control, ensuring the scientific validity and effectiveness of commands and preventing increased energy consumption and decreased production efficiency due to blind operation. The feedback unit 230 can also treat multiple negative commands as abnormal signals, assisting the system in fault warning and adaptive adjustment, thereby further improving the equipment's operational reliability and process stability. This invention, through dynamic monitoring and feedback control, effectively achieves the matching of equipment status and commands, contributing to the safe, efficient, and intelligent operation of the drying unit.

[0155] It should be noted that the specific embodiments described above are exemplary. Those skilled in the art can devise various solutions inspired by the disclosure of this invention, and these solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and not intended to limit the scope of the claims. The scope of protection of this invention is defined by the claims and their equivalents. This specification contains multiple inventive concepts; phrases such as "preferredly" or "according to a preferred embodiment" indicate that the corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications based on each inventive concept.

Claims

1. An intelligent adjustment system for a paddle drying device, characterized in that, The system includes: The sensing unit (210) includes a viscosity sensor (211), a temperature sensor (212), and a flowability sensor (213). The adjustment unit (220) is communicatively connected to the sensing unit (210). Based on the viscosity parameters collected by the viscosity sensor (211), the temperature parameters collected by the temperature sensor (212), and the flowability parameters collected by the flowability sensor (213), it calculates the lees drying state index and its changing trend in real time. It also monitors the changing trend of the operating parameters of the paddle drying device (100) in real time. When the lees drying state index reaches the preset adjustment threshold, it sends an instruction to the control module (120) to increase or decrease the stirring frequency. The feedback unit (230) establishes a communication connection with the operation monitoring module (110) of the blade drying device (100) and the adjustment unit (220), and calculates the motor current change rate and the stirring shaft vibration frequency change rate based on the blade operation monitoring data; the feedback unit (230) judges the accuracy of the command based on the change trend of the motor current change rate and the stirring shaft vibration frequency change rate, and in the case of an incorrect command, the feedback unit (230) sends a readjustment command to the adjustment unit (220).

2. The system according to claim 1, characterized in that, The steps of the adjustment unit (220) in calculating the lees drying state index in real time based on viscosity parameters, temperature parameters, and flowability parameters include: The dynamic weights are calculated based on a dynamic scoring function that uses various parameters. The lees drying state index is calculated using a nonlinear weighting method based on the dynamic weights of various parameters.

3. The system according to claim 2, characterized in that, The adjustment unit (220) predicts the predicted values ​​and dynamic trends of parameters based on the smoothing coefficients of viscosity parameters, temperature parameters, and flowability parameters. The adjustment unit (220) calculates the predicted index of the drying state of the lees based on the predicted values ​​of viscosity parameters, temperature parameters and fluidity parameters; When both the lees drying state index and the lees drying state prediction index are greater than the first adjustment threshold, the adjustment unit (220) sends an instruction to the control module (120) to increase the stirring frequency. When both the lees drying state index and the lees drying state prediction index are less than the second adjustment threshold, the adjustment unit (220) sends an instruction to the control module (120) to reduce the stirring frequency.

4. The system according to claim 1, characterized in that, The feedback unit (230) calculates the operating resistance index of the impeller drying device (100) based on the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft. The operating resistance index is used to reflect the resistance encountered during the mixing of distiller's grains in real time. The resistance is related to the drying state of the distiller's grains.

5. The system according to claim 4, characterized in that, When the adjustment unit (220) determines that the lees drying state index has reached the preset adjustment threshold, the adjustment unit (220) generates a confirmation instruction and sends it to the feedback unit (230). In response to the pending confirmation command, the feedback unit (230) sends the command confirmation result to the adjustment unit (220); When the operating resistance index and the lees drying state index change in opposite directions, the feedback unit (230) determines that the current blade operating resistance matches the drying state and instructs the adjustment unit (220) to adjust the pending confirmation command to the confirmed command. When the operating resistance index and the lees drying state index do not change in opposite directions, the feedback unit (230) determines that the current blade operating resistance does not match the drying state and that the confirmation command is incorrect, and sends a readjustment command to the adjustment unit (220); thereby the adjustment unit (220) recalculates the lees drying state index to confirm the true drying state of the lees.

6. The system according to claim 5, characterized in that, If the feedback unit (230) determines that the operating state of the paddle drying device (100) cannot be increased based on the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft, In response to the pending confirmation instruction sent by the adjustment unit (220), the feedback unit (230) sends a negative instruction to the adjustment unit (220) so that the adjustment unit (220) cancels the pending confirmation instruction.

7. A smart adjustment method for a paddle drying device, characterized in that the method... include: Collect viscosity, temperature, and flowability parameters of the distiller's grains; The distillers' grains drying state index and its changing trend are calculated in real time based on viscosity parameters, temperature parameters and flowability parameters, and the changing trend of the operating parameters of the paddle dryer (100) is monitored in real time. When the lees dryness index reaches the preset adjustment threshold, an instruction to increase or decrease the stirring frequency is sent to the control module (120). The rate of change of motor current and the rate of change of vibration frequency of the stirring shaft are calculated based on the operating monitoring data of the impeller; the accuracy of the command is judged based on the changing trends of the rate of change of motor current and the rate of change of vibration frequency of the stirring shaft, and a readjustment command is sent in case of an error in the command.

8. The method according to claim 7, characterized in that, The method also includes: The predicted values ​​and dynamic trends of the smoothing coefficient based on viscosity, temperature and flow parameters. The predicted index of the drying state of distiller's grains is calculated based on the predicted values ​​of viscosity parameters, temperature parameters, and flowability parameters. If both the lees dryness index and the lees dryness prediction index are greater than the first adjustment threshold, a command to increase the stirring frequency is sent. If both the lees dryness index and the lees dryness prediction index are less than the second adjustment threshold, a command to reduce the stirring frequency is sent.

Images