Anti-dusting grain conveying device for drying tower

Abstract

The present application belongs to the technical field of dust suppression and transportation, and particularly relates to a dust-suppression grain conveying device for a drying tower, which comprises: a conveying belt for carrying and conveying grains; a dust control cover arranged above the conveying belt and internally divided into a humid dust suppression section, a pre-drying section and an exhaust suction section in sequence along the grain conveying direction; a grain turning and pre-drying assembly arranged in the pre-drying section and comprising a heater, a circulating fan and a grain turning rake continuously rotating across the grain surface; a suction and separation assembly arranged in the exhaust suction section and comprising a suction fan connected to the dust control cover and a gas-solid separator connected to the exhaust end of the suction fan for gas-solid separation to obtain clean humid exhaust gas; and an exhaust gas recycling pipeline connecting the exhaust end of the gas-solid separator and the humid dust suppression section as the only gas injection port of the section.

Description

Technical Field

[0001] This invention belongs to the field of dust suppression and conveying technology, specifically a dust suppression and grain conveying device for drying towers. Background Technology

[0002] In grain storage and processing systems, grain typically undergoes long-distance belt conveying before entering the main drying tower. To reduce the dehydration load on the main drying tower and improve overall processing efficiency, pre-drying is carried out simultaneously during the dust-proof and dust-suppressing grain conveying process. This has become an important technological means for improving the quality and efficiency of modern grain conveying. Pre-drying not only preheats cold grain and evaporates some of the surface free water, but also improves the fluidity of the grain. It is an indispensable pre-process for achieving efficient and continuous grain drying.

[0003] The usual method to prevent dust from escaping is to install a dust collection hood above the conveyor belt and connect it to a high-power dust removal fan. At the same time, a hot air fan is installed independently inside the hood for pre-drying treatment. However, with the increase in pre-drying intensity, mechanical turning parts have been widely introduced in order to allow the hot air to penetrate to the bottom of the grain layer. The dry fine dust will be stripped off in large quantities and suspended in the airflow under mechanical turning. In order to prevent these high-concentration dusts from escaping, the traditional solution can only rely on continuously increasing the suction negative pressure of the tail exhaust fan, and finally the high-temperature exhaust gas carrying water vapor and dust will be directly discharged outdoors as waste gas.

[0004] Specifically, when the bottom layer of grain is violently turned up by the mechanical rake teeth, the hidden dry dust will burst out instantly. At this time, the strong negative pressure suction at the top will directly short-circuit and suck away the hot air that has just been blown towards the grain surface, causing the hot air to be forcibly discharged before it can exchange heat with the lower layer of grain, which seriously damages the uniformity of heat penetration. On the other hand, the existing system treats the high-humidity, high-heat and dusty exhaust gas as simple pollutant waste. During the emission treatment process, it is very easy to generate severe condensation and dust adhesion at the cold wall of the pipe, which will eventually lead to pipe narrowing and blockage. The existing technology completely ignores the physical adhesion characteristics of the moisture in the exhaust gas when it undergoes phase change condensation at a specific temperature difference, and fails to transform it into an endogenous means to solve the problem of dust caused by mechanical turning.

[0005] Therefore, the present invention provides a dust-prevention and dust-suppressing grain conveying device for a drying tower. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0007] The technical solution adopted by this invention to solve its technical problem is: a dust-prevention and dust-suppressing grain conveying device for a drying tower, comprising: Conveyor belts are used to carry and transport grain. A dust control hood is installed above the conveyor belt, and its interior is divided into a wet dust suppression section, a pre-drying section and an exhaust gas extraction section along the grain walking direction. The grain turning and pre-drying assembly is located in the pre-drying section and includes a heater, a circulating fan, and a grain turning rake that rotates continuously across the grain surface. The suction and separation assembly is located in the exhaust gas suction section and includes a suction fan connected to the dust control hood and a gas-solid separator connected to its exhaust end, used for gas-solid separation to obtain clean, humid, and hot exhaust gas. The exhaust gas reuse pipeline connects the exhaust end of the gas-solid separator to the wet dust suppression section, serving as the only air injection port for this section. Clean, hot, and humid exhaust gas is blown onto the surface of the cold grain to condense a micro-water film and agglomerate micro-dust. A diversion regulating valve is also provided on the pipeline. The sensor array includes differential pressure transmitters located at the inlet and outlet of the dust control hood, infrared thermometers in the humid dust suppression section, temperature and humidity meters and wall temperature probes in the exhaust gas reuse pipeline, micro-pressure gauges above the grain turning rake, array temperature probes at the outlet of the pre-drying section, moisture activity meters and mass flow meters. The controller is communicatively connected to the aforementioned components, pipelines, and sensor array; it is configured to perform real-time calculations based on sensor data to extract the micro-water film phase change window index, air curtain anti-interference blockade stiffness, and thermal-mass penetration synergistic performance; calculate the multi-modal phase change dust suppression synergistic fidelity and dustproof stiffness safety margin; and output the target servo diversion ratio for adjusting the opening of the diversion regulating valve using a pure algebraic operator.

[0008] The beneficial effects of this invention are as follows: 1. This invention introduces the hot and humid exhaust gas, which was originally discharged as waste gas, into the humid dust suppression section by setting up an exhaust gas recycling pipeline. The temperature difference between the cold grain surface and the hot and humid exhaust gas causes water vapor to condense into a micro water film, which actively agglomerates the micro dust generated by turning the grain, thus suppressing dust from the source. This solves the drawbacks of mechanical grain turning causing instantaneous dust explosions and passive dust removal that relies solely on increasing the negative pressure of suction.

[0009] 2. This invention incorporates a suction separation component and a tail gas recycling pipeline to recycle the sensible and latent heat in the humid and hot tail gas discharged from the pre-drying section into the humid dust suppression section. This process forms a dust-suppressing micro-water film while preheating the cold grain, preventing the hot air from being short-circuited away by the suction fan. This significantly improves the synergistic effect of heat and mass penetration, reduces the dehydration load of the main drying tower, and achieves the ultimate recovery and utilization of the heat and moisture resources of the waste gas.

[0010] 3. This invention sets up a sensor array and controller, and performs real-time calculations based on multimodal characteristics (micro-water film phase change window index, air curtain anti-disturbance blocking stiffness, thermal mass penetration synergistic efficiency, etc.). It outputs a target servo split ratio with an algebraic operator driven by stiffness safety taking priority over fidelity, and dynamically adjusts the amount of recycled exhaust gas. This not only prevents condensation and blockage on the pipe wall, but also ensures that the air curtain is stable under grain turning disturbance, thus achieving adaptive and precise dust suppression. Attached Figure Description

[0011] The invention will now be further described with reference to the accompanying drawings.

[0012] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a schematic diagram of the installation of the circulating fan in this invention; Figure 3 This is a schematic diagram of the grain turning rake in this invention; Figure 4 This is the overall control flowchart of the present invention; Figure 5 This is a flowchart of the multimodal feature extraction and collaborative operation of the controller in this invention; Figure 6 This is the optimization mapping logic diagram of the micro-water film phase change window index in this invention; Figure 7 This is a dual-target drive limiting output diagram of the target servo split ratio in this invention.

[0013] In the diagram: 1. Conveyor belt; 2. Exhaust gas recycling pipeline; 3. Pre-drying section; 4. Gas-solid separator; 5. Suction fan; 6. Exhaust gas suction section; 7. Turning motor; 8. Circulating fan; 9. Wet dust suppression section; 10. Grain turning rake. Detailed Implementation

[0014] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0015] like Figures 1 to 3 As shown, the present invention provides a dust suppression grain conveying device for a drying tower, comprising a conveyor belt 1 for carrying and conveying grain. The conveyor belt 1 can be made of various materials and structures, and can be a flat belt made of materials such as rubber or polyvinyl chloride (PVC). The grain is continuously conveyed by rollers and a motor drive.

[0016] The dust control hood is installed above the conveyor belt 1. Its interior is divided into a wet dust suppression section 9, a pre-drying section 3 and an exhaust gas extraction section 6 along the grain conveying direction. The dust control hood is constructed of metal plates to form a semi-enclosed channel. A partition is installed between the wet dust suppression section 9 and the pre-drying section 3, and the pre-drying section 3 and the exhaust gas extraction section 6 can be directly connected.

[0017] The grain turning and pre-drying assembly is located inside the pre-drying section 3. It includes a heater, a circulating fan 8, and a grain turning rake 10 that rotates across the grain surface. The heater uses an electric heating tube and is located at the top of the dust control hood to provide a heat source for the pre-drying section 3. The circulating fan 8 is located outside the dust control hood, and its input and output ends are connected to the inner cavity of the dust control hood. It is used to drive hot air to circulate within the pre-drying section 3 to improve heat exchange efficiency. The grain turning rake 10 is rotatably mounted on the inner wall of the dust control hood. A turning motor 7 is located outside the dust control hood to control the rotation of the grain turning rake 10. The output shaft of the turning motor 7 is fixedly connected to the axial end of the grain turning rake 10. The grain turning rake 10 turns the grain in the pre-drying section 3 through mechanical movement, ensuring that the grain is heated evenly and promoting moisture evaporation.

[0018] The suction and separation assembly is located in the exhaust gas suction section 6. It includes a suction fan 5 connected to the dust control hood and a gas-solid separator 4 connected to its exhaust end. The suction fan 5 can be a medium-pressure or high-pressure fan, used to draw humid and hot gas from the dust control hood. The gas-solid separator 4 can be a cyclone separator, gravity settling chamber or inertial separator, etc., used to separate dust particles in the drawn gas, thereby obtaining clean humid and hot exhaust gas.

[0019] The exhaust gas reuse pipeline 2 connects the exhaust end of the gas-solid separator 4 to the humidification dust suppression section 9, serving as the air injection port for this section. This air injection port is a single configuration. This pipeline is used to blow clean, hot, and humid exhaust gas onto the grain surface, causing water vapor to condense and form a micro-water film to agglomerate fine dust. The pipeline is equipped with a flow diversion regulating valve. The exhaust gas reuse pipeline 2 can be constructed of galvanized steel pipe or stainless steel pipe to ensure the airtightness of the gas transmission. The flow diversion regulating valve can be an electric proportional regulating valve or a pneumatic diaphragm regulating valve, which can receive servo control commands. By changing the valve opening, the flow rate of the reused exhaust gas can be automatically adjusted. In addition, to solve the problem of insufficient usable moisture in the system during the initial operation phase, the humidification dust suppression section 9 is also equipped with a set of external atomizing nozzles, configured to spray water mist into the hood during the cold start phase of the equipment to help form the initial micro-water film.

[0020] The sensor array includes differential pressure transmitters located at the inlet and outlet of the dust control hood, an infrared thermometer in the humidification and dust suppression section 9, a temperature and humidity meter and wall temperature probe in the exhaust gas reuse pipeline 2, a micro-pressure gauge above the grain turning rake 10, an array temperature probe at the outlet of the pre-drying section 3, a moisture activity meter, and a mass flow meter. These sensors can be commercially available industrial-grade sensors. The differential pressure transmitters can be Pitot tube or diaphragm sensors to monitor the pressure balance inside and outside the dust control hood. The infrared thermometers use point or line scanning sensors to measure the temperature of the grain surface. The temperature and humidity meters use... Capacitive or resistive sensors are used to monitor the state of the recycled exhaust gas. The wall temperature probe uses thermocouples or resistance thermometers to monitor the pipe wall temperature. The micro-pressure gauge uses a high-sensitivity differential pressure sensor to monitor airflow disturbances near the grain turning rake 10. The array temperature probe can be composed of multiple thermocouples or resistance thermometers to obtain the temperature distribution of the grain at the outlet of the pre-drying section 3. The moisture activity meter uses a capacitive or resistive sensor to measure the moisture activity of the grain. The mass flow meter uses a thermal or Coriolis sensor to measure the gas mass flow rate in the exhaust gas recycling pipeline 2.

[0021] As a preferred extension of this embodiment, in order to obtain a more intuitive physical field state, the sensing array can also be equipped with an industrial vision sensor. Specifically, an explosion-proof multispectral industrial camera or high-speed vision sensor is set at the inlet and outlet of the dust control hood and above the interior of the wet dust suppression section 9. The vision sensor is configured to acquire morphological images of the grain flow surface on the conveyor belt 1 and microscopic dust scattering images of the edge of the dust control hood in real time, and extract the reflectivity features of the grain surface and the motion trajectory features of the dust particles through the embedded image processing module, so as to provide multimodal auxiliary verification of the visual dimension for subsequent algorithms.

[0022] like Figure 4-7 As shown, the controller communicates with the aforementioned components, pipelines, and sensor array. The controller is configured to perform real-time calculations based on sensor data, extracting the micro-water film phase change window index, air curtain anti-interference blockade stiffness, and thermal-mass penetration synergistic efficiency. It calculates the multi-modal phase change dust suppression synergistic fidelity and dustproof stiffness safety margin, and outputs the servo diversion ratio in the form of an algebraic operator. This servo diversion ratio is a target value used to adjust the opening of the diversion regulating valve. The controller is implemented using hardware platforms such as programmable logic controllers (PLCs), distributed control systems (DCS), or industrial personal computers (IPCs).

[0023] Its software logic can be constructed based on preset empirical rules, simple proportional-integral-derivative (PID) control algorithms, or fuzzy control algorithms. For example, the controller can determine whether the condensation conditions are met based on the grain surface temperature measured by the infrared thermometer in the wet dust suppression section 9 and the exhaust gas temperature measured by the thermometer and hygrometer in the exhaust gas reuse pipeline 2, through a preset temperature difference threshold, and adjust the opening of the diversion regulating valve accordingly. Alternatively, the controller can maintain the air pressure balance inside the dust control hood through simple logic judgment based on the pressure difference change measured by the differential pressure transmitter at the inlet and outlet of the dust control hood to prevent dust from overflowing. In addition, the controller can also evaluate the uniformity of heat penetration based on the temperature distribution measured by the array temperature probe at the outlet of the pre-drying section 3 through simple average or maximum value judgment, and make rough adjustments to the operating parameters of the grain turning and pre-drying components.

[0024] During the conveying process, the grain material first enters the wet dust suppression section 9 of the dust control hood. At this time, the suction fan 5 inside the dust control hood starts to work, drawing away the gas inside the dust control hood. This gas is processed by the gas-solid separator 4, and the dust is separated and collected. The clean, hot, and humid exhaust gas is then transported back to the wet dust suppression section 9 through the exhaust gas reuse pipeline 2. Because the surface temperature of the grain material entering the wet dust suppression section 9 is low, the water vapor in the reused hot and humid exhaust gas condenses on the surface of the grain material, forming a layer of micro water film. This layer of micro water film can effectively adhere to the micro dust that may be generated during the subsequent turning of the grain material, agglomerating it on the surface of the grain material, thereby suppressing the spread of dust from the source.

[0025] Subsequently, the grain material enters the pre-drying section 3. The heater in the grain turning and pre-drying component provides heat, and the circulating fan 8 blows hot air evenly onto the grain material layer. At the same time, the grain turning rake 10 continues to rotate, turning the grain material to ensure that each grain material can fully contact the hot air and achieve uniform pre-drying. During this process, some of the moisture in the grain material is evaporated, forming hot and humid gas.

[0026] Throughout the operation, the sensor array continuously collects various key data. The differential pressure transmitters at the inlet and outlet of the dust control hood monitor the pressure balance inside the hood to ensure that dust does not overflow. The infrared thermometer in the humidification and dust suppression section 9 monitors the surface temperature of the grain material to assess the conditions for the formation of micro-water film. The thermometer and hygrometer and the wall temperature probe in the exhaust gas reuse pipeline 2 monitor the status of the reused exhaust gas and the risk of condensation in the pipeline. The micro-pressure gauge above the turning rake 10 monitors the airflow disturbance during the turning process. The array temperature probe, moisture activity meter and mass flow meter at the outlet of the pre-drying section 3 monitor the drying effect and the state of the grain.

[0027] The controller receives these real-time sensor data and performs calculations. It extracts the micro-water film phase change window index to quantify the dust suppression effect of condensation, extracts the air curtain anti-interference blockade stiffness to evaluate the stability of airflow organization within the dust control hood, and extracts the thermal-mass penetration synergy efficiency to evaluate the efficiency and uniformity of pre-drying. Based on these indicators, the controller further calculates the multi-modal phase change dust suppression synergy fidelity and dustproof stiffness safety margin, comprehensively evaluating the dust suppression performance and operational safety of the system. Finally, the controller outputs a servo split ratio, which is the target value, to precisely adjust the opening of the split regulating valve on the exhaust gas reuse pipeline 2. For example, when the controller detects a decrease in dust suppression effect or an increase in dust concentration, it calculates a new servo split ratio, which is the target value, and instructs the split regulating valve to increase the amount of reused exhaust gas to enhance the formation of the micro-water film, thereby improving the dust suppression effect. Conversely, when the dust suppression effect is good and the pre-drying efficiency needs to be improved, the controller may adjust the split ratio to optimize energy distribution.

[0028] Thus, the wet and hot exhaust gas, which was originally considered waste, is transformed into a dust suppression medium, realizing the technological transformation from passive exhaust and dust removal to active phase change dust suppression. At the same time, through intelligent control, the uniformity of heat and mass penetration in the pre-drying process is ensured, and the heat and mass potential of the exhaust gas is maximized, effectively solving the problems of dust generation from mechanical turning of grain, heat waste, and pipeline blockage during the pre-drying process of grain transportation.

[0029] Before extracting multimodal features, the controller is configured to obtain the total enthalpy heat of the recycled tail gas based on thermodynamic theory. The method for obtaining the total enthalpy heat of the recycled tail gas is as follows: based on the mass of recycled dry gas obtained by the mass flow meter, combined with the sensible heat change determined by the constant pressure specific heat capacity and temperature difference of the recycled tail gas, and the latent heat change determined by the absolute moisture content and latent heat of vaporization of water vapor in the recycled tail gas, the two are summed and multiplied with the mass of recycled dry gas to obtain the total enthalpy heat.

[0030] Before performing multimodal model calculations, the controller first calculates the total enthalpy and heat of the recycled exhaust gas based on the laws of thermodynamics. The unit is The specific calculation formula is as follows: ; In the formula, The cumulative dry gas mass for exhaust gas reuse pipeline 2 is [unit:] ; The specific heat capacity of dry gas at constant pressure is expressed in units of . ; To reuse the temperature of the hot, humid exhaust gas; The ambient room temperature is used as the reference. The mass fraction of water vapor in the recycled exhaust gas; The latent heat of vaporization of water vapor, in units of .

[0031] The controller is responsible for receiving real-time data from the sensor array, performing complex calculations and logical judgments, and then outputting control commands. It integrates a processing unit, a storage unit, and a communication interface, enabling automated management and precise control of the entire dust suppression grain conveying device. Multimodal model calculation refers to a series of complex algorithm processing performed by the controller to achieve dust suppression control, including calculations of multiple dimensions such as micro-water film phase change window index, air curtain anti-disturbance blockade stiffness, thermal mass penetration synergistic efficiency, multimodal phase change dust suppression synergistic fidelity, and dust suppression stiffness safety margin. These calculations aim to comprehensively evaluate and optimize the dust suppression effect and ultimately determine the opening degree of the diversion regulating valve. Thermodynamic laws refer to the basic physical laws describing the conversion and transfer of energy between different forms.

[0032] In this embodiment, the total energy carried by the recycled exhaust gas, i.e., the total enthalpy, is mainly quantified based on the first law of thermodynamics (the law of conservation of energy). It represents the total energy contained in the recycled exhaust gas, including sensible heat and latent heat. Sensible heat is the energy carried by the gas because its temperature is higher than the ambient temperature, while latent heat is the energy released by the phase change (condensation) of water vapor.

[0033] The cumulative dry gas mass of exhaust gas reuse pipeline 2 refers to the cumulative mass of dry air in the gas passing through exhaust gas reuse pipeline 2 within a certain period of time after removing the water vapor portion. This parameter is measured or estimated in real time by a mass flow meter installed in exhaust gas reuse pipeline 2, such as a Coriolis mass flow meter or a thermal mass flow meter.

[0034] The constant-pressure specific heat capacity of dry air refers to the amount of heat required to raise the temperature of a unit mass of dry air by a unit temperature under constant pressure. It is a physical constant related to the gas composition and can usually be obtained from tables or determined experimentally. The temperature of the recycled wet and hot exhaust gas refers to the actual temperature of the wet and hot exhaust gas discharged from the gas-solid separator 4 and entering the exhaust gas recycling pipeline 2. This temperature is monitored in real time by a thermometer or hygrometer or wall temperature probe installed in the exhaust gas recycling pipeline 2.

[0035] The ambient room temperature reference refers to the reference ambient temperature used to calculate the energy difference. It can be set to the average room temperature of the environment where the device is located, or it can be obtained in real time through an ambient temperature sensor. The water vapor mass fraction in the recycled exhaust gas refers to the proportion of water vapor mass in the total gas mass. This parameter can be measured in real time using a temperature and humidity meter installed in the exhaust gas recycling pipeline 2, for example, a capacitive humidity sensor. The latent heat of vaporization of water vapor refers to the energy absorbed or released by a unit mass of water when it changes from a liquid state to a gaseous state (vaporization) or from a gaseous state to a liquid state (condensation) under constant temperature and pressure. It is a physical constant related to temperature and pressure and can usually be obtained by looking up tables or calculated by empirical formulas.

[0036] The controller's precise calculation of the total enthalpy and heat of the recycled exhaust gas provides a solid energy foundation for subsequent refined dust suppression control. During the operation of the dust suppression grain conveying device, the suction and separation component performs gas-solid separation on the exhaust gas rich in water vapor and dust to obtain clean, moist, and hot exhaust gas. This clean, moist, and hot exhaust gas is blown onto the surface of the cold grain in the moist dust suppression section 9 through the exhaust gas recycling pipeline 2. To ensure that the exhaust gas can effectively condense to form a micro-water film to agglomerate the dust particles, the controller first uses a sensor array (including a temperature and humidity meter and a wall temperature probe and a mass flow meter in the exhaust gas recycling pipeline 2) to obtain real-time parameters of the recycled exhaust gas, such as the cumulative dry gas mass, before performing a series of multi-modal model calculations such as the micro-water film phase change window index and the air curtain anti-interference blockade stiffness. Temperature of recycled wet exhaust gas and water vapor mass fraction .

[0037] At the same time, combined with the preset dry gas constant pressure specific heat capacity Ambient room temperature benchmark and latent heat of vaporization of water vapor Using physical constants and based on the laws of thermodynamics, the total enthalpy and heat carried by the recycled exhaust gas can be accurately calculated. This calculation process quantifies the sensible heat in the exhaust gas (from... (item manifestation) and latent heat (by) The total enthalpy (reflected by the total energy) is used to determine whether the current recycled exhaust gas has sufficient energy, especially latent heat, to drive the formation of a stable micro-water film on the surface of cold grain through real-time assessment of the total enthalpy. This quantitative perception of energy status enables the controller to avoid making ineffective subsequent control decisions when energy is insufficient, thereby ensuring the physical feasibility and stability of the exhaust gas recycling phase change dust suppression process and providing a reliable energy input basis for subsequent precise dust suppression by adjusting the opening of the diversion regulating valve.

[0038] The controller is also configured to obtain the latent heat ratio of the exhaust gas based on the conservation of mass transfer kinetics. The latent heat ratio of the exhaust gas is obtained by: using the difference between the absolute moisture content of the recycled exhaust gas and the absolute moisture content of saturated water vapor at the surface temperature of the cold grain, combined with the calibrated condensation mass transfer efficiency and the mass of recycled dry gas, to calculate the mass of the condensation micro-water film; and then calculating the ratio of the sum of the sensible heat used to heat the grain and the latent heat of the water film condensation to the total enthalpy of the recycled exhaust gas.

[0039] The controller obtains the mass of the condensate microfilm based on the conservation of mass transfer kinetics. And thus calculate the latent heat ratio of exhaust gas condensation. The calculation formula is as follows: ; ; In the formula, surface temperature of cold grain The mass fraction of saturated water vapor below; The mass transfer efficiency coefficient for condensation; The specific heat capacity of grain; To process the total mass of grain; For imported grain surface condensation temperature difference and .

[0040] The principle of mass transfer kinetics conservation is used here to describe the phase change and condensation process of water vapor in the hot, humid exhaust gas upon encountering the surface of cold grain. This principle ensures that the energy and mass balance is strictly adhered to when calculating the mass of the condensate microfilm. Specifically, it considers the rate of water vapor transformation from the gas phase to the liquid phase, as well as factors affecting this rate such as temperature, humidity gradient, and surface characteristics. It refers to the quality of the water film that condenses on the surface of cold grains, which is the key medium for achieving the dust suppression effect of micro-dust agglomeration.

[0041] This mass transfer efficiency is determined based on the principle of mass transfer kinetics conservation. It is achieved by monitoring the difference between the water vapor content in the exhaust gas and the saturated water vapor content on the surface of the cooled grain, and by quantifying this difference using the condensation mass transfer efficiency coefficient. The latent heat of condensation in the exhaust gas is also calculated. It is a dimensionless index used to quantify the proportion of thermal and wet energy in the recycled exhaust gas that is converted into dust suppression efficiency. It reflects the proportion of the latent heat released by the exhaust gas during the condensation process on the surface of cold grain to the total enthalpy heat of the exhaust gas. The higher the ratio, the higher the energy utilization efficiency of the recycled exhaust gas and the greater its contribution to dust suppression.

[0042] Saturated water vapor mass fraction This refers to the temperature at a specific point (i.e., the surface temperature of cold grain). The mass fraction of water vapor in the air when it reaches saturation can be calculated by consulting a water vapor saturation table or using empirical formulas (such as the Antoine equation) based on the real-time measured surface temperature T_{surf} of the cold grain.

[0043] Condensation mass transfer efficiency coefficient The empirical parameter used to characterize the condensation efficiency of water vapor on the surface of cold grain is affected by various factors such as grain surface characteristics, airflow velocity, and temperature gradient. This coefficient is obtained through experimental calibration. For example, the ratio of actual condensed water to theoretical maximum condensed water is measured under different operating conditions. Different types of grains (such as corn, wheat, and rice) have different specific heat capacities, and their values ​​will fluctuate slightly with changes in grain moisture content. This parameter can be estimated by consulting relevant literature, experimental measurement (such as differential scanning calorimetry DSC), or based on grain type and moisture content.

[0044] Processing total grain mass This refers to the total amount of grain passing through the pre-drying section 3 within a specific time period. This parameter can be measured in real time using a mass flow meter (such as a Coriolis mass flow meter or an impeller flow meter), or estimated using the speed of conveyor belt 1 and the thickness of the grain layer, as well as the condensation temperature difference on the inlet grain surface. This refers to the temperature of recycled wet exhaust gas. With the surface temperature of cold grain The temperature difference between the two is the key factor driving the condensation of water vapor on the surface of cold grain. The temperature and humidity were measured by a thermometer inside exhaust gas recycling pipe 2. The temperature was measured by an infrared thermometer in the humid dust suppression section 9.

[0045] The controller receives real-time data from the sensor array, including the temperature of the recycled humid exhaust gas measured by a hygrometer in exhaust gas reuse pipeline 2. and water vapor mass fraction The surface temperature of the cold grain measured by the infrared thermometer in the humid dust suppression section 9. The total mass of grain processed as measured by the mass flow meter .

[0046] Based on this real-time data, the controller first considers the surface temperature of the cold grain. Calculate the saturated water vapor mass fraction Subsequently, the controller utilizes the principle of mass transfer kinetics conservation, combined with the mass of the exhaust dry gas. (This value has been included in the calculation of the total enthalpy and heat of the recycled exhaust gas) (obtained at the time) and the preset condensation mass transfer efficiency coefficient The mass of the micro water film condensed on the surface of the cold grain was accurately calculated. ,this The quantification of this directly reflects the formation effect of the micro-water film, providing a physical basis for subsequent micro-dust aggregation.

[0047] Furthermore, under actual operating conditions, the aforementioned condensation mass transfer efficiency coefficient... Dynamic adaptive calibration can also be performed by combining the features extracted by the aforementioned visual sensors. When the hot and humid exhaust gas introduced by the exhaust gas reuse pipeline 2 condenses into a micro-water film on the surface of the cold grain in the humid dust suppression section 9, the specular reflectivity and optical texture of the grain surface will undergo microscopic changes. The controller incorporates a machine vision image processing algorithm to dynamically assess the actual surface wettability by comparing the changes in the visual gloss gradient of the grain flow surface on the conveyor belt 1 in consecutive video frames before and after condensation, and adjusts the condensation mass transfer efficiency coefficient online accordingly. The value of this non-contact compensation mechanism based on visual morphological features improves the quality of the condensation micro-water film. The calculation can break through the limitations of static empirical values ​​and more accurately reflect the actual physical phase transition state.

[0048] Based on this, the controller further calculates the temperature difference of condensation on the imported grain surface. And combined with the specific heat capacity of grain Total mass of grain processed and the latent heat of water vaporization The total heat released for heating the grain and forming the micro-water film was calculated, and this total heat was then compared with the previously calculated total enthalpy of the recycled exhaust gas. By making comparisons, the latent heat of exhaust gas condensation can be obtained. This ratio intuitively quantifies the proportion of thermal and wet energy in the recycled exhaust gas that is converted into dust suppression efficiency, providing quantitative parameter support for systematically evaluating the actual contribution of exhaust gas recycling to dust suppression.

[0049] Through the and The real-time calculation and monitoring of these two core indicators enable the controller to overcome the problem of insufficient precise control over the physical quantitative indicators of the condensation process in traditional solutions, thereby achieving accurate evaluation of the exhaust gas reuse effect, providing data support for the dynamic adjustment of the diversion regulating valve, and ensuring the optimization of dust suppression effect.

[0050] The micro-water film phase change window index extracted by the controller is configured with the following calculation model: constructing a squared Lorentz peak optimization function with the condensation temperature difference of the imported grain surface as the main variable, and integrating an anti-condensation smoothing function with the difference between the pipe wall temperature and the tail gas dew point temperature as the main variable; by normalizing the two functions at a set reference temperature and performing a nonlinear mapping, the normalized window index representing the non-condensation and condensation-promoting state is output.

[0051] The micro-water film phase change window index embedded in the controller The computational model is constructed using the product of the Lorentz peak operator and the algebraic smoothing operator, and its calculation formula is as follows: ; In the formula, The difference between the pipe wall temperature measured by the wall temperature probe and the exhaust gas dew point temperature; The reference temperature constant for calibrating the equipment under no-load conditions; Peak sharpness factor; This represents the optimal expected temperature difference ratio.

[0052] Among them, the micro water film phase transition window index The computational model aims to quantitatively assess whether the current physical environment is in the phase transition range most favorable for forming a uniform micro-water film on the surface of cold grain, while also taking into account the safety of system operation. This model can be implemented as a software module or algorithm library inside the controller, for example, by developing it using programming languages ​​such as C++, Python or MATLAB, and integrating it into the controller's firmware.

[0053] The Lorentz peak operator is a mathematical function used to describe a curve with a specific peak value and width. The computational model is used to characterize the effect of condensation temperature difference on the efficiency of micro-water film formation. This operator can identify and quantify the optimal temperature difference conditions. When the actual temperature difference deviates from the ideal value, its output value will drop rapidly. In terms of implementation, this operator can be calculated directly through the floating-point arithmetic unit in the controller, or approximate by using a lookup table method to improve the calculation speed.

[0054] The algebraic smoothing operator is a nonlinear function used to smooth input variables and... The computational model uses an operator to assess the risk of condensation inside the pipeline. This operator normalizes the difference between the pipe wall temperature and the exhaust gas dew point temperature, thus providing a smooth and continuous risk indication. This operator can also be implemented through mathematical operations within the controller, or by fitting a pre-calculated function curve.

[0055] Product construction refers to multiplying the calculation results of the Lorentz peak operator and the algebraic smoothing operator to obtain a comprehensive microwater film phase transition window index. This product relationship means that only when both conditions (i.e., optimal condensation temperature difference and low pipeline condensation risk) are simultaneously met, Only in this way can a higher value be achieved, thereby ensuring the synergistic optimization of dust suppression effect and system safety. In the controller, this is manifested as the outputs of the two sub-modules serving as the inputs for multiplication operations.

[0056] The difference between the pipe wall temperature measured by the wall temperature probe and the exhaust gas dew point temperature is a key parameter for assessing the risk of condensation inside the pipeline. The wall temperature probe can be a resistance temperature detector (RTD) or a thermocouple, which obtains the temperature of the inner wall of the exhaust gas reuse pipeline 2 through a contact measurement method. The exhaust gas dew point temperature can be obtained by measuring the relative humidity and temperature of the exhaust gas through a hygrometer inside the exhaust gas reuse pipeline 2, and then by looking up a table or calculation.

[0057] The controller receives signals from these sensors and calculates... , The reference temperature constant for calibrating the equipment under no-load conditions is a preset reference temperature value obtained through experimental calibration under no-load or stable operating conditions. This constant is used to perform dimensionless processing of temperature differences, making them comparable under different operating conditions. The calibration process can be carried out during the equipment installation and commissioning stage, and is determined by obtaining data through multiple experiments and performing statistical analysis.

[0058] The peak sharpness factor is a dimensionless parameter used to adjust the sharpness of the Lorentz peak operator curve. A larger value indicates a higher sharpness. A smaller value will make the curve narrower and sharper, meaning the system has a lower tolerance for temperature differences deviating from the optimal expected value, requiring more precise temperature difference control and a smaller [value]. A higher value makes the curve wider and flatter, indicating that the system is more adaptable to changes in temperature. This factor can be optimized experimentally or set according to process requirements.

[0059] The optimal temperature difference ratio is a dimensionless parameter representing the optimal ratio of the condensation temperature difference on the imported grain surface to the reference temperature constant under ideal conditions. This value is typically determined through extensive experimental data analysis and theoretical calculations to ensure that... The calculation model can accurately reflect the temperature difference conditions most favorable for the formation of micro water films.

[0060] By embedding the micro water film phase change window index in the controller The computational model enables precise quantitative assessment and control of the micro-water film formation process within the humid dust suppression section 9. A comprehensive evaluation index is constructed by multiplying the Lorentz peak operator and the algebraic smoothing operator. The Lorentz peak operator primarily focuses on the condensation temperature difference on the imported grain surface. The reference temperature constant calibrated with the equipment under no-load conditions The ratio of the two values ​​is used to introduce the optimal expected temperature difference ratio. and peak sharpness factor Its function is to accurately capture and quantify the temperature difference conditions that are most conducive to the formation of micro water films on the surface of cold grains.

[0061] When the actual condensation temperature difference is close to or at the optimal expected ratio, the operator outputs a high value, indicating high efficiency in the formation of the micro-water film. Once it deviates from this range, the output value decays rapidly, indicating poor condensation conditions. Meanwhile, the algebraic smoothing operator introduces the difference between the pipe wall temperature measured by the wall temperature probe and the exhaust gas dew point temperature. Its core function is to monitor the risk of condensation inside the exhaust gas reuse pipeline 2 in real time.

[0062] Through the By performing nonlinear smoothing, this operator can effectively assess the possibility of unexpected condensation caused by pipe wall overcooling. When the pipe wall temperature is much higher than the dew point temperature, the risk of condensation is low and the operator outputs a high value; conversely, when the pipe wall temperature is close to or lower than the dew point temperature, the risk of condensation increases and the operator outputs a low value.

[0063] Combining these two operators through multiplication results in the microwater film phase transition window exponent. It can simultaneously reflect the efficiency of micro-water film formation and the safety of pipeline operation. Only when condensation conditions are within the optimal window period and there is no significant risk of condensation inside the pipeline, Only in this way can a higher value be achieved. This product relationship ensures that the system, while pursuing efficient dust suppression, does not sacrifice the stability of pipeline operation, thus avoiding system failures caused by pipeline blockage. This index As a controller, it performs multimodal model calculations (such as subsequent co-fidelity). An important input for ) and the total enthalpy and heat of recycled exhaust gas condensation micro-water film quality and the latent heat ratio of exhaust gas condensation These parameters work together to provide key physical criteria for the controller to output the target servo split ratio, thereby enabling precise adjustment of the split regulating valve opening. This ensures that the clean, hot, and humid exhaust gas can be blown onto the surface of the cold grain in the best possible condition, effectively agglomerating fine dust and preventing pipeline blockage.

[0064] The calculation model for the air curtain anti-disturbance blocking stiffness extracted by the controller is configured as follows: extract the composite air pressure deviation characteristics of the air curtain balance differential pressure and the holding wind pressure relative to the static reference differential pressure inside the dust control hood, and combine them with the fluctuation attenuation penalty term formed by the differential pressure standard deviation; through an algebraic limiting mechanism, the above composite air pressure characteristics and attenuation penalty term are transformed into stiffness characteristic values ​​that characterize the dustproof air curtain's ability to resist dissipation under turbulence interference.

[0065] The controller has an embedded air curtain anti-interference and blocking stiffness. The computational model introduces a pressure composite offset operator. The specific calculation formula is as follows:

[0066]

[0067] In the formula, The differential pressure of the air curtain is measured by the differential pressure transmitter. To maintain air pressure; This is the static reference differential pressure; This represents the standard deviation of the differential pressure. The basic weak offset constant; , , These are the dimensionless pressure gain and fluctuation penalty coefficient, respectively.

[0068] Among them, the air curtain's anti-interference and blocking stiffness It is a dimensionless quantitative indicator used to evaluate the ability of an air curtain to resist external disturbances and maintain its dustproof effect. It reflects the ability of an air curtain to maintain its sealing integrity and effectiveness when disturbed by airflow fluctuations, external wind pressure, etc. It is calculated through a specific mathematical model that takes into account air pressure status and fluctuations.

[0069] Gas pressure composite offset operator It is a dimensionless composite index used to quantify the deviation of the current air pressure state from the ideal dust control benchmark. It is obtained by adjusting the differential pressure of the air curtain. Pressure holding wind pressure Differential pressure from static reference Weighted normalization is performed, and a weak foundation offset constant is subtracted. To calculate.

[0070] A differential pressure transmitter is an instrument that converts differential pressure signals into standard electrical signals for output, used to measure the differential pressure of a gas curtain. Micro differential pressure sensors, such as MEMS differential pressure sensors or capacitive differential pressure sensors, can be installed at the inlet and outlet of the dust control hood to monitor the pressure difference inside and outside the air curtain in real time and balance the differential pressure of the air curtain. The pressure difference between the inside and outside of the air curtain is used to control the overall strength of the air curtain, and is directly measured by a differential pressure transmitter.

[0071] Pressure holding wind pressure This refers to the minimum or target wind pressure required to maintain a stable air curtain under specific operating conditions. It can be preset through system design parameters, and is a static reference differential pressure. This refers to the reference differential pressure value that should be maintained at the inlet and outlet of the dust control hood under no-load or ideal dustproof conditions. It is determined by no-load calibration of the equipment or by setting based on empirical values.

[0072] Differential pressure standard deviation Reflected in the differential pressure of the air curtain over a period of time The fluctuation range is such that the larger the fluctuation, the larger the standard deviation. It is obtained by statistical calculation of multiple sets of gas curtain balance differential pressure data collected by the differential pressure transmitter, for example, by using the sliding window averaging method.

[0073] Foundation weak offset constant It is a preset constant used to correct the barometric composite offset operator. This allows it to reflect the inherent weaknesses or non-ideal states of the air curtain under specific conditions. This is achieved through experimental calibration or empirical setting, adjusting the pressure gain and fluctuation penalty coefficient. , , It is a dimensionless coefficient used to adjust the differential pressure of the air curtain. Pressure holding wind pressure and differential pressure standard deviation In calculating the composite displacement operator of air pressure and air curtain anti-disturbance blockade stiffness The relative importance of time is set and adjusted through system optimization, experimental testing, or expert experience.

[0074] In this embodiment, the controller receives the air curtain balance differential pressure measured by the differential pressure transmitter. And combined with the pressure holding wind pressure and preset static reference differential pressure By introducing the gas pressure composite offset operator These real-time and baseline pressure data are normalized, taking into account the foundation weak offset constant. This allows for the quantification of the degree to which the current air pressure deviates from the ideal dust control benchmark.

[0075] Based on this, the controller utilizes the air curtain's anti-disturbance blocking stiffness. The calculation model uses the pressure composite offset operator. The system is transformed into a stiffness value characterizing the air curtain's blocking capability through a nonlinear mapping in the form of a sigmoid function, and the differential pressure standard deviation is also introduced. and fluctuation penalty coefficient Penalizing air curtain pressure fluctuations means that even if the average pressure appears normal, if the fluctuations are severe, the air curtain's disturbance resistance stiffness will be compromised. This will also reduce accordingly, thus accurately reflecting the true stability of the air curtain. It solves the problem that traditional static pressure control cannot accurately assess the stability of air curtain blocking, especially under complex operating conditions such as airflow fluctuations, changes in equipment operating status, and external environmental interference. It can assess the air curtain's anti-interference capability in real time and dynamically, avoiding dust escape due to delayed or inaccurate assessments. This is achieved by quantifying the air curtain's anti-interference blocking stiffness. The controller can provide a subsequent target servo load ratio. The adjustment provides precise input, thereby enabling intelligent control of the opening of the diversion regulating valve and ensuring that the dustproof environment inside the dust control hood is always in optimal condition.

[0076] Furthermore, to further improve the gas pressure composite offset operator The system possesses strong anti-disturbance feedforward discrimination capabilities. Visual sensors installed at the inlet and outlet of the dust hood monitor in real time for the escape of trace amounts of dust. Using machine vision algorithms such as optical flow or background subtraction, it extracts features from the acquired images of the dust hood's edge in real time. When the visual algorithm detects highly concealed dust overflow trajectories caused by airflow fluctuations, the controller triggers a visual closed-loop compensation mechanism, dynamically increasing the fundamental weak offset constant in the calculation model accordingly. Or fluctuation penalty coefficient Thus, the system achieves cross-modal fusion correction from single pressure perception to dual perception of pressure difference and vision, completely eliminating the hidden dust emission under complex working conditions.

[0077] The thermal-mass penetration synergistic efficiency extracted by the controller is configured in the following way: the current unit dust suppression efficiency of the system is extracted as a positive benefit feature, and the standard deviation of cross-sectional grain turning temperature and dust circulation mass flow rate are introduced as negative penalty features; a composite benefit index is constructed by assigning corresponding weights to each feature, and an algebraic smoothing operator is used to map it into a comprehensive performance evaluation index that reflects the uniformity of heat transmission and the cost of dust prevention.

[0078] The controller's embedded thermal-mass penetration synergy performance The calculation model constructs a dimensionless compound return index. The formula for obtaining it is:

[0079]

[0080] In the formula, Dust suppression efficiency per unit This represents the theoretical maximum nominal energy efficiency. The standard deviation of the cross-sectional grain turning temperature; Dust circulation mass flow rate, The maximum permissible dust circulation flow rate is the baseline. , , These are the dimensionless benefit and penalty weights, respectively.

[0081] The computational model is a mathematical tool within the controller used to quantitatively evaluate the efficiency of heat and mass (moisture, dust) transfer and their synergistic effects during grain transportation. Its function is to integrate multiple key performance indicators into a comprehensive dimensionless index, so that the controller can fully and in real time grasp the efficiency and stability of the pre-drying process.

[0082] Dimensionless Compound Return Index This is an intermediate variable in the calculation model, comprehensively reflecting the system's performance in dust suppression, drying uniformity, and dust control. It is calculated by measuring the unit dust suppression energy efficiency. Standard deviation of cross-sectional grain turning temperature and dust circulation mass flow rate By making physical quantities with different dimensions dimensionless and then combining them with weights, performance indicators of different dimensions can be compared and evaluated within a unified framework.

[0083] Among them, unit dust suppression energy efficiency It refers to the energy consumed by the system to achieve a unit dust suppression effect. It is used to measure the energy utilization efficiency of the dust suppression process and can be calculated by monitoring the power consumption of the suction fan 5, the energy consumption of the heater, and the actual amount of dust captured or suppressed.

[0084] Theoretical maximum nominal energy efficiency This is the unit dust suppression energy efficiency under ideal operating conditions, i.e., under optimal design parameters and lossless conditions. It serves as a benchmark value for evaluating the relative performance of unit dust suppression energy efficiency in actual operation. The standard deviation of cross-sectional grain turning temperature is also included. It is an indicator for measuring the uniformity of temperature distribution on the cross-section of the grain layer in the pre-drying section 3. Its calculation depends on the data of multiple temperature measurement points obtained by the array temperature measurement probe, and reflects the degree of temperature dispersion through statistical methods.

[0085] Dust circulation mass flow rate This refers to the mass of dust circulating within the dust control hood, particularly between the pre-drying section 3 and the exhaust gas extraction section 6, per unit time. This indicator reflects the accumulation and resuspension of dust within the system, and represents the maximum permissible dust circulation flow rate. It represents the upper limit of the dust circulation mass flow rate that the system can tolerate while ensuring dust suppression and avoiding secondary pollution, with dimensionless benefit and penalty weights. , , It is a parameter used to adjust the relative importance of various indicators in the dimensionless compound return index Z, and can be adjusted according to actual production needs, process optimization goals, or expert experience.

[0086] Specifically, the controller first obtains the unit dust suppression energy efficiency. Standard deviation of cross-sectional grain turning temperature and dust circulation mass flow rate Real-time operational data, including unit dust suppression efficiency. This reflects the energy utilization efficiency of the dust suppression process, specifically the standard deviation of the cross-sectional grain turning temperature. The cross-sectional temperature data is obtained through an array of temperature probes.

[0087] Dust circulation mass flow rate The controller monitors the concentration of suspended dust inside the dust control hood in real time to prevent the risk of secondary pollution caused by excessive dust circulation. The controller then compares this real-time data with the preset theoretical maximum nominal energy efficiency. Maximum permissible dust circulation flow rate benchmark and reference temperature constant Comparisons were made, and the benefits and penalties were compared using dimensionless weights. , , Weighting is performed to calculate the dimensionless compound return index. .

[0088] index This comprehensively reflects the heat and mass exchange quality under the current drying environment, incorporating three key dimensions—energy utilization, drying uniformity, and dust control—into a unified evaluation system. Subsequently, the controller utilizes a nonlinear mapping function to incorporate the composite benefit index. Transformed into thermal mass penetration synergistic effect .

[0089] By introducing thermal-mass penetration synergistic effect This enables the controller to comprehensively and quantitatively evaluate the heat utilization and dust suppression effects during the drying and conveying process, along with the total enthalpy of the exhaust gas. condensation micro-water film quality Latent heat ratio of exhaust gas Microwater film phase transition window index and air curtain anti-interference and blocking stiffness These parameters together constitute the synergistic fidelity of multimodal phase change dust suppression. A comprehensive evaluation system.

[0090] Thermal Penetration Synergistic Effect The introduction of this technology compensates for the shortcomings of traditional solutions in evaluating the uniformity of heat and mass exchange and dust control. This allows the controller to consider not only the dust suppression effect and the conditions for the formation of micro-water film when optimizing the overall system, but also the efficiency and quality of pre-drying, thereby achieving more refined control of operating parameters.

[0091] The multimodal phase change dust suppression synergy fidelity calculated by the controller is configured as follows: based on the anti-collapse weighted harmonic average algorithm, the micro water film phase change window index, thermal mass penetration synergy efficiency, exhaust gas condensation latent heat ratio, and the measured grain surface water film activity are fused and evaluated; a physical fundamental noise constant is introduced in the underlying calculation to prevent the occurrence of calculation singularities, and the output is a fidelity value that reflects the degree of non-distortion of the multi-physics field.

[0092] The multimodal phase change dust suppression synergistic fidelity extracted by the controller The output uses a weighted harmonic mean norm with a minimum anti-collapse constant, and its calculation formula is as follows:

[0093] In the formula, The measured water film activity on the grain surface; To prevent the physical basis noise floor from being a minimum constant with a denominator of zero; , , , These are the dimensionless collaborative mapping weights for the feature dimensions of each submodal.

[0094] Among them, the synergistic fidelity of multimodal phase change dust suppression It is a quantitative indicator used to comprehensively evaluate the authenticity and reliability of the dust suppression effect of a dust-suppressing grain conveying device during operation, as well as the degree of synergy among its key physical processes. It reflects the system's overall ability to maintain high-efficiency dust suppression performance under complex and variable operating conditions. This fidelity... The extraction is not based on a single physical quantity, but rather integrates multiple interrelated submodal features, such as the microwater film phase transition window index. Synergistic effect of heat and mass penetration Latent heat ratio of exhaust gas and the activity of water film on grain surface .

[0095] Fidelity The calculation outputs a weighted harmonic mean norm with a minimum anti-collapse constant. The weighted harmonic mean norm is more sensitive to smaller values ​​and can effectively reflect the bottleneck effect in the system. Using the weighted harmonic mean norm here means that when any submodal feature (such as...) is less sensitive to smaller values, the output is less sensitive to smaller values. , , , When the value of ) is low, even if other characteristic values ​​are high, the overall fidelity is low. It will also decrease significantly, thus highlighting the weakest link in the system and ensuring that the controller can identify and respond to potential dust suppression failure risks in a timely manner. Its output is a dimensionless value between 0 and 1, which intuitively represents the fidelity of the current dust suppression state.

[0096] Minimum anti-collapse constant It is a preset, very small positive value. Its main function is to prevent numerical overflow problems during calculation, such as the denominator becoming zero or the calculation result becoming infinitely large, when a certain submodal eigenvalue approaches zero. This is achieved by adding a value to the denominator. This ensures the stability and robustness of the calculation, guaranteeing the effective calculation of fidelity F_{mc} even under extreme conditions, thus preventing model collapse. Furthermore, It can also be understood as the physical background noise or minimum disturbance that the system cannot completely eliminate even in an ideal state. Its existence ensures that even if the eigenvalue of a certain submode reaches zero in theory, the fidelity calculation can maintain physical continuity and stability, avoiding mathematical singularities, thereby enhancing the practical application value of the model.

[0097] in, The water film activity on the grain surface, as measured, is an important indicator of the free water content on the grain surface and its ability to bind with dust particles. A higher water film activity usually means that a micro-water film is more easily formed on the grain surface, thus more effectively agglomerating dust particles. The water film activity A_{w} on the grain surface can be measured in various ways; for example, the water activity of the grain sample can be directly measured using a water activity meter.

[0098] , , , These are the dimensionless co-mapping weights for the feature dimensions of each submodal. Used to adjust the features of different submodalities ( , , , In terms of overall fidelity The relative importance in the calculation, by setting these weights, allows the controller to dynamically adjust the contribution of each physical dimension to the final dust suppression effect assessment based on different grain types, environmental conditions, or dust suppression targets. These weights can be trained and adaptively adjusted through expert experience, historical operational data analysis, and machine learning-based optimization algorithms (such as genetic algorithms and neural networks).

[0099] Its core operation lies in utilizing several key physical mechanisms in the dust suppression process of the drying tower, including the formation and stability of the micro-water film (through the micro-water film phase change window index). Characterization), effective transfer of heat and mass in the grain layer (through the synergistic effect of heat and mass penetration). Characterization), the ability of water vapor in the exhaust gas to release latent heat through condensation (by the latent heat ratio of exhaust gas condensation). Characterization), and the actual wetting state of the grain surface (through the activity of the water film on the grain surface). The representations are integrated into a unified evaluation framework.

[0100] The controller acquires the raw data required for these sub-modal characteristics in real time through the sensor array, and derives the results based on the aforementioned calculation model. , and At the same time, direct measurement was obtained .

[0101] Subsequently, the controller uses these preprocessed submodal eigenvalues ​​as input and substitutes them into the formula for calculating the weighted harmonic mean norm. The unique feature of this formula is its high sensitivity to the bottleneck effect of each submodal characteristic. This means that if any key dust suppression physical process deteriorates significantly, even if other indicators perform well, the overall coherence fidelity will be compromised. It will also drop rapidly.

[0102] This non-linear weighting method allows the controller to accurately identify the most vulnerable links in the dust suppression system, thus avoiding the situation where traditional linear weighting methods may mask local problems due to averaging. Furthermore, the introduction of a minimum anti-collapse constant... This ensures that, under extreme operating conditions, the calculation process will not encounter mathematical singularities where the denominator is zero, thus guaranteeing fidelity. Numerical stability of the computation and robustness of the algorithm.

[0103] Meanwhile, by setting dimensionless collaborative mapping weights , , , The controller can flexibly adjust the relative importance of each sub-modal feature in the overall fidelity assessment based on the actual grain type, moisture content, dust characteristics, and desired dust suppression effect. Through the above mechanism, the controller no longer relies solely on a single or simple combination of parameters to judge the dust suppression effect, but instead constructs a comprehensive evaluation model based on multi-physics coupling.

[0104] The target servo split ratio output by the controller is configured in the following way: the driving deviation between the multimodal phase change dust suppression synergy fidelity and the preset target, and the margin deviation between the air curtain anti-interference blockade stiffness and the safety bottom line are obtained; a square root continuous amplitude limiting dual-target algebraic driving operator with anti-oscillation smoothing dead zone constant is constructed, and the stiffness safety margin is given an execution weight higher than that of the fidelity driving, and the output target execution increment is calculated based on the current split ratio.

[0105] The controller outputs the target servo split ratio based on the servo optimization model. The model uses a purely algebraic approach to calculate the fidelity driving potential. With stiffness safety margin The calculation formula is as follows:

[0106]

[0107]

[0108] In the formula, The current measured split ratio; This is the maximum single-cycle adjustment limit for the flow divider control valve; To set a preset fidelity target; This represents the minimum stiffness threshold. , To optimize and protect the weighting coefficients and satisfy ; , The smoothing dead zone constant is used to prevent high-frequency oscillations.

[0109] Among them, the servo optimization model is a dynamic optimization control strategy. Its core objective is to enable the system output (i.e., the target servo split ratio) to dynamically approach or reach the preset performance target through real-time or near-real-time calculation, while ensuring the stable operation of the system. This model can be built based on the simplified model predictive control (MPC) principle.

[0110] Fidelity driving force Used to quantify the deviation between the current dust suppression effect and the desired dust suppression effect, specifically, it represents the synergistic fidelity of multimodal phase change dust suppression. Compared with the preset fidelity target The difference between the values, in terms of magnitude and direction, directly indicates the gap between the current dust suppression performance of the system and the ideal state, thereby driving the controller to make adjustments to improve the dust suppression effect.

[0111] Stiffness safety margin Used to quantify the current air curtain's anti-interference and blocking stiffness. The distance from the minimum safety requirement, specifically, represents the air curtain's disturbance rejection stiffness. With stiffness baseline threshold The difference between the two margins ensures that the system can achieve dust suppression without sacrificing basic dust protection safety, providing a safety boundary for the controller. When the stiffness is close to or below the threshold, the system will prioritize safety.

[0112] Target servo split ratio This is the command value calculated by the controller based on the servo optimization model, used to adjust the opening of the diversion regulating valve. This command value directly affects the flow distribution of clean, humid, and hot exhaust gas in exhaust gas reuse pipeline 2, and is the core output parameter for achieving dynamic dust suppression control. It is achieved by precisely controlling the target servo diversion ratio. The dust suppression intensity of the wet dust suppression section 9 can be dynamically adjusted.

[0113] Current measured split ratio The current exhaust gas split ratio is obtained in real time by a sensor on the split control valve (e.g., a mass flow meter installed in the exhaust gas reuse pipeline 2 or the opening sensor of the split control valve itself). This parameter serves as the real-time input to the servo optimization model, reflecting the current operating status of the system and providing basic data for the dynamic adjustment of the model. The maximum single adjustment limit of the split control valve is also specified. This limit is used to restrict the maximum permissible change in opening of the flow control valve within a single control cycle. This limit is designed to prevent the control action from being too fast or too large, thereby avoiding system oscillation or instability and ensuring the smoothness of the control process and the overall stability of the system.

[0114] Preset fidelity target The system aims to achieve a high level of multimodal phase change dust suppression synergy fidelity. The ideal value, which can be set according to different grain types, environmental conditions, or process requirements, represents the optimization direction for dust suppression effects. The stiffness baseline threshold is also relevant. It is the minimum air curtain disturbance rejection stiffness that the system must maintain. This threshold value is a guarantee for the safe operation of the system, ensuring that the dustproof capability will not fall below this preset safety limit under any operating conditions.

[0115] Optimize and protect weight coefficients and This is used to balance the relative importance of fidelity optimization and stiffness safety assurance in control decisions, among which, Much larger The settings clearly demonstrate the system's control strategy of prioritizing dust suppression rigidity and safety while pursuing dust suppression effectiveness.

[0116] Smoothing dead zone constant and These constants are used to filter out small, unnecessary fluctuations when calculating the fidelity driving potential and stiffness safety margin. They can effectively prevent the controller from overreacting to noise in the sensor data, thereby avoiding high-frequency oscillations in the control loop and ensuring the smoothness and reliability of the flow control valve's operation.

[0117] By introducing a servo optimization model, the dust suppression control problem is transformed into a problem based on fidelity-driven potential. With stiffness safety margin Pure algebraic operations are used to achieve precise closed-loop control of the diversion regulating valve opening. Specifically, the controller first uses various parameters acquired in real time by the sensor array, combined with a preset calculation model (such as the total enthalpy and heat of the recycled exhaust gas, the mass of the condensate micro-water film, the latent heat ratio of the exhaust gas condensation, the phase change window index of the micro-water film, and the air curtain anti-disturbance blockade stiffness). Synergistic effect of thermal and mass penetration and synergistic fidelity of multimodal phase change dust suppression (etc.), to calculate the current multimodal phase change dust suppression synergistic fidelity in real time. and air curtain anti-disturbance blockade stiffness .

[0118] Based on this, the controller utilizes a servo optimization model to obtain real-time calculations. Compared with the preset fidelity target By comparison, the fidelity driving force is obtained. This driving force quantifies the deviation between the current dust suppression effect and the expected target, providing direction for system optimization.

[0119] At the same time, the controller will calculate in real time With stiffness baseline threshold By comparison, the stiffness safety margin is obtained. This margin ensures that the system still has sufficient dust protection capabilities when facing external disturbances, and serves as a basis for safety assurance.

[0120] Subsequently, the servo optimization model will and As the core input, combined with the current measured split ratio Maximum single-cycle adjustment limit of the diversion control valve Optimize and protect weight coefficients and and smoothing dead zone constant and The target servo split ratio is output in real time through pure algebraic operations. .

[0121] The target servo split ratio It is then sent to the diversion regulating valve, which precisely adjusts its opening to dynamically control the flow rate of clean, humid, and hot exhaust gas injected into the wet dust suppression section 9 from the exhaust gas reuse pipeline 2.

[0122] In this way, the controller can dynamically balance the optimization of dust suppression effect with the safety guarantee of dustproof rigidity in real time, driving the performance with high fidelity. The existence of this allows the system to continuously evolve towards the optimal dust suppression state, while the stiffness safety margin This ensures that under any circumstances, the system's dustproof capability will not fall below the preset safety threshold.

[0123] In addition, a single maximum adjustment limit is introduced. This effectively limits abrupt changes in the adjustment range, prevents instability in the control system, and optimizes and protects the weighting coefficients. and The settings, especially Much larger This ensures that while pursuing dust suppression efficiency, the system prioritizes dustproof rigidity and safety, and smooths the dead zone constant. and This effectively filters out minute fluctuations in the sensor data, eliminates high-frequency oscillations in the control loop, and ensures the smoothness and reliability of the flow control valve's operation.

[0124] When the controller acquires evaluation indicators, the differential pressure standard deviation is configured to be obtained by calculating the variance of the dispersion of the dust control hood air curtain balance differential pressure within a preset sampling period; the cross-sectional grain turning temperature standard deviation is configured to be obtained by calculating the variance of the temperature dispersion of multiple temperature measurement points acquired by the array temperature probe.

[0125] To ensure the accuracy of the data basis for formula calculations and the system's physical disturbance rejection capability, the differential pressure standard deviation... Standard deviation of grain turning temperature in the cross section The calculation formula is as follows:

[0126]

[0127] In the formula, For the first The differential pressure of the air curtain inside the dust control hood for the second sampling. The average differential pressure during the sampling period. This represents the total number of differential pressure sampling points. The cross-section obtained by the array temperature probe Grain flow surface temperature at each temperature measurement point Its horizontal mean, This represents the total number of temperature probes arranged horizontally.

[0128] Among them, the differential pressure standard deviation and cross-sectional temperature standard deviation of grain turning It is a statistical indicator used to quantify the fluctuation of airflow environment and the uniformity of grain flow surface temperature inside the dust control hood. It is calculated in real time by the digital signal processor (DSP) inside the controller. The calculation formula itself is the square root of the variance, which measures the degree of data dispersion in statistics. The controller can embed fixed mathematical library functions for calculation, or use hardware acceleration units (such as FPGA) to implement parallel computing to improve efficiency.

[0129] This represents the raw or pre-filtered instantaneous air curtain balance differential pressure data points collected by the differential pressure transmitter within a specific time interval. It is within the sampling period for The average value can be calculated using an arithmetic mean, weighted average, or moving average filter. This is the number of data points used to calculate the standard deviation of differential pressure. It can be set to a fixed number, such as data points collected within a fixed time window. This represents the instantaneous grain flow surface temperature data collected by an array of temperature probes (such as an infrared thermometer array or a thermocouple array) at different lateral positions. It is the average value of multiple temperature measurement points on a cross-section at the same time or within a short period of time. It can be the arithmetic mean of all transverse temperature measurement data. It is the total number of temperature probes arranged on the cross-section, which can be configured according to the width and accuracy requirements of the conveyor belt 1.

[0130] By introducing the standard deviation calculation method from statistics, the differential pressure of the air curtain and the surface temperature of the grain flow inside the dust control hood are discretized and quantified, thereby providing more robust input data for the subsequent control model.

[0131] In actual operation, due to the complex airflow environment inside the dust control hood and the randomness of grain turning, if control is based solely on instantaneous sampling values, it is easily affected by local airflow fluctuations or sensor noise, resulting in the calculated air curtain balance differential pressure and grain surface temperature data lacking statistical representativeness, which in turn leads to misjudgment or high-frequency oscillation in the control system.

[0132] By analyzing the differential pressure of the air curtain sampled multiple times over a period of time Statistical analysis was performed to calculate the standard deviation of the differential pressure. This can reflect the stability of the air curtain; a stable air curtain... The air curtain with smaller values ​​and larger fluctuations... The value is relatively large, which provides a basis for the controller to calculate the air curtain's disturbance rejection stiffness. It provides more reliable input and effectively avoids misjudgments caused by instantaneous disturbances.

[0133] Meanwhile, by measuring multiple temperature points across the cross-section Statistical analysis was conducted to calculate the standard deviation of the cross-sectional grain turning temperature. It can reflect the uniformity of grain surface temperature; a uniform temperature distribution... When the value is small, and there are localized areas of overheating or undercooling, then The value is relatively large, which provides the controller with a basis for calculating the synergistic effect of thermal-mass penetration. This provides a more precise physical basis, enabling it to identify potential thermomass distribution issues during grain turning.

[0134] Introducing these statistical characteristics into the control logic essentially elevates the system's control basis from an instantaneous state to a statistical state, by adjusting the total number of sampling points. Total number of horizontally arranged temperature probes The standardized processing ensures the coverage and representativeness of data acquisition, thereby significantly enhancing the system's physical disturbance rejection capability under complex operating conditions. This provides reliable data support for achieving precise dust suppression control, enabling the controller to make decisions based on more stable and representative data, thus ensuring the fidelity of multimodal phase change dust suppression synergy. and dustproof stiffness safety margin The accuracy ultimately leads to the target servo split ratio The adjustment is more precise and effective.

[0135] Finally, as a direct representation of the intelligent control of this invention, the controller not only outputs the target servo split ratio command to the split regulating valve on the exhaust gas reuse pipeline 2, but also supports the construction of a visual mapping interface for deep thermodynamic parameters. By combining the extracted visual features with the multimodal phase change dust suppression synergistic fidelity, the controller achieves this. Air curtain anti-interference and blocking stiffness By integrating the results of pure algebraic operators, a three-dimensional digital twin visualization interface for the dust suppression and conveying device is constructed on the host computer. The interface uses particle flow animations with different color gradients and densities to intuitively and dynamically map the film-forming quality of the invisible micro-water film in the wet dust suppression section 9 and the heat and mass penetration uniformity in the pre-drying section 3 to the operators, thus realizing a panoramic visual display of the deep multi-physics field collaborative control process.

[0136] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dust-prevention and grain conveying device for a drying tower, characterized in that: include: Conveyor belts are used to carry and transport grain. A dust control hood is installed above the conveyor belt, and its interior is divided into a wet dust suppression section, a pre-drying section and an exhaust gas extraction section along the grain walking direction. The grain turning and pre-drying assembly is located in the pre-drying section and includes a heater, a circulating fan, and a grain turning rake that rotates continuously across the grain surface. The suction and separation assembly is located in the exhaust gas suction section and includes a suction fan connected to the dust control hood and a gas-solid separator connected to its exhaust end, used for gas-solid separation to obtain clean, humid, and hot exhaust gas. The exhaust gas reuse pipeline connects the exhaust end of the gas-solid separator to the wet dust suppression section, and a diversion regulating valve is provided on the exhaust gas reuse pipeline. The sensor array includes differential pressure transmitters located at the inlet and outlet of the dust control hood, infrared thermometers in the humid dust suppression section, temperature and humidity meters and wall temperature probes in the exhaust gas reuse pipeline, micro-pressure gauges above the grain turning rake, array temperature probes at the outlet of the pre-drying section, moisture activity meters and mass flow meters. The controller is communicatively connected to the aforementioned components, pipelines, and sensor array; it is configured to perform real-time calculations based on sensor data to extract the micro-water film phase change window index, air curtain anti-interference blockade stiffness, and thermal-mass penetration synergistic performance; calculate the multi-modal phase change dust suppression synergistic fidelity and dustproof stiffness safety margin; and output the target servo diversion ratio for adjusting the opening of the diversion regulating valve using a pure algebraic operator.

2. The dust-suppressing grain conveying device for a drying tower according to claim 1, characterized in that: Before extracting multimodal features, the controller is configured to obtain the total enthalpy and heat of the recycled exhaust gas based on thermodynamic theory. The method for obtaining the total enthalpy heat of the recycled exhaust gas is as follows: Based on the mass of the recycled dry gas obtained from the mass flow meter, the sensible heat change determined by the constant pressure specific heat capacity and temperature difference of the recycled tail gas, and the latent heat change determined by the absolute moisture content and latent heat of water vaporization of the recycled tail gas, the two are summed and multiplied with the mass of the recycled dry gas to obtain the result.

3. A dust-prevention and grain conveying device for a drying tower according to claim 2, characterized in that: The controller is also configured to obtain the latent heat ratio of exhaust gas condensation based on the conservation of mass transfer dynamics. The method for obtaining the latent heat ratio of the exhaust gas is as follows: The mass of the condensate micro-water film is calculated by using the difference between the absolute moisture content of the recycled exhaust gas and the absolute moisture content of saturated water vapor at the surface temperature of the cold grain, combined with the calibrated condensation mass transfer efficiency and the mass of recycled dry gas. The sum of the sensible heat used to heat the grain and the latent heat of the water film condensation is then used as a ratio to the total enthalpy of the recycled exhaust gas.

4. A dust-prevention and grain conveying device for a drying tower according to claim 3, characterized in that: The micro-aqueous film phase transition window index extracted by the controller is configured with the following calculation model: A squared Lorentz peak optimization function with the temperature difference of condensation on the surface of imported grain as the main variable is constructed, and an anti-condensation smoothing function with the difference between pipe wall temperature and exhaust gas dew point temperature as the main variable is integrated. By normalizing the two functions at a set reference temperature and performing a nonlinear mapping, a normalized window index representing a non-condensing and condensation-promoting state is output.

5. A dust-prevention and grain conveying device for a drying tower according to claim 4, characterized in that: The calculation model for the air curtain anti-interference blockade stiffness extracted by the controller is configured as follows: Extract the composite air pressure deviation characteristics of the air curtain balance differential pressure and the holding wind pressure relative to the static reference differential pressure inside the dust control hood, and combine them with the fluctuation attenuation penalty term formed by the differential pressure standard deviation; Through an algebraic limiting mechanism, the aforementioned composite air pressure characteristics and attenuation penalty terms are transformed into stiffness characteristic values ​​that characterize the dustproof air curtain's ability to resist dissipation under turbulence.

6. A dust-prevention and grain conveying device for a drying tower according to claim 5, characterized in that: The thermal-mass penetration synergistic efficiency extracted by the controller is configured in the following calculation model: The current unit dust suppression efficiency of the system is extracted as a positive benefit feature, and the standard deviation of cross-sectional grain turning temperature and dust circulation mass flow rate are introduced as negative penalty features. By assigning corresponding weights to each feature, a composite benefit index is constructed, and an algebraic smoothing operator is used to map it into a comprehensive performance evaluation index that reflects the uniformity of heat transmission and the cost of dust prevention.

7. A dust-prevention and grain conveying device for a drying tower according to claim 6, characterized in that: The multimodal phase change dust suppression synergistic fidelity calculated by the controller is configured with the following calculation model: Based on the anti-collapse weighted harmonic average algorithm, the micro water film phase change window index, heat and mass penetration synergistic efficiency, exhaust gas condensation latent heat ratio, and the measured grain surface water film activity are fused and evaluated. A physical noise floor constant is introduced into the underlying computation to prevent computational singularities, and the output is a fidelity value that reflects the degree of undistorted multiphysics.

8. A dust-prevention and grain conveying device for a drying tower according to claim 7, characterized in that: The target servo split ratio output by the controller is calculated using the following model: The driving deviation between the multimodal phase change dust suppression synergistic fidelity and the preset target, and the margin deviation between the air curtain anti-interference blockade stiffness and the safety baseline are obtained; A square root continuous amplitude-limited bi-objective algebraic driving operator is constructed by introducing an anti-oscillation smoothing dead zone constant, and an execution weight with a stiffness safety margin higher than that of the fidelity driving is assigned. Based on this, the output target execution increment is calculated on the basis of the current split ratio.

9. A dust-prevention and grain conveying device for a drying tower according to claim 8, characterized in that: When the controller acquires evaluation indicators, the differential pressure standard deviation is configured to be obtained by calculating the variance of the deviation between the instantaneous air curtain balance differential pressure of the dust control hood and its average value within a preset sampling period and taking the square root. The standard deviation of the cross-sectional grain turning temperature is configured by calculating the variance of the deviation between the instantaneous temperature of multiple temperature measurement points obtained by the array temperature probe and its lateral mean, and then taking the square root.

Images