Grain and oil preservation method based on environmental condition transformation

Abstract

The invention provides a grain and oil storage method based on environmental condition transformation, which comprises the following steps: acquiring an initial environmental parameter set of a storage space through a grain condition monitoring unit, analyzing grain and oil category feature identification and a quality deterioration threshold value, and calling a matched environmental regulation and control rule set from a grain storage strategy library. And collecting a dynamic environment parameter set of the storage space in real time. And according to a deviation relationship between the quality deterioration threshold and the dynamic environment parameter set, generating an environment regulation and control instruction sequence, and sending the environment regulation and control instruction sequence to a grain storage execution system for execution. When the quality detection unit triggers a quality deterioration early warning signal, an emergency regulation and control instruction is generated in combination with the grain and oil deterioration kinetic model and is dynamically integrated into an environment regulation and control instruction sequence. The grain and oil storage environment can be accurately controlled, the quality deterioration can be effectively prevented, and the safety and the quality stability of grain and oil storage are improved.

Description

Technical Field

[0001] This invention relates to the field of food processing technology, and more specifically, to a method for preserving grains and oils based on changes in environmental conditions. Background Technology

[0002] Ensuring the quality and safety of grains and oils during storage has always been a core task of warehouse management. Traditional grain and oil preservation methods mainly rely on static environmental control, such as simple ventilation, dehumidification, and periodic fumigation. While these methods can maintain the basic quality of grains and oils to a certain extent, they often fail to effectively cope with complex and changing environmental conditions due to the lack of real-time monitoring and precise control of dynamic changes in the storage environment. For example, grains and oils are affected by a combination of factors during storage, including temperature, humidity, and gas composition. Traditional methods cannot monitor changes in these parameters in real time, nor can they provide personalized adjustments based on the specific type and quality requirements of the grains and oils. Furthermore, traditional methods lack a rapid and effective emergency response mechanism when dealing with sudden quality deterioration, leading to an increased risk of quality decline or even spoilage.

[0003] While some sensor network-based monitoring systems have been applied to monitor storage environments in existing grain and oil preservation technologies, most of these systems simply collect environmental data without integrating them with dynamic control strategies. For example, some systems can monitor temperature and humidity in storage spaces but cannot generate targeted control commands based on the characteristics and quality requirements of the grains and oils. Furthermore, while existing environmental control equipment can perform basic ventilation, dehumidification, and controlled atmosphere functions, it often lacks intelligent control logic in practical applications and cannot dynamically adjust operating modes based on real-time monitoring data. These problems result in significant shortcomings in existing technologies when dealing with complex storage environments and variable grain and oil quality requirements.

[0004] In implementing the embodiments of the present invention, the prior art has at least the following problems or defects: First, traditional grain and oil preservation methods cannot monitor the dynamic changes of the storage environment in real time, and cannot make precise adjustments according to the specific categories and quality requirements of grains and oils; second, although existing monitoring systems can collect environmental data, they lack integration with dynamic control strategies and cannot achieve intelligent environmental control; finally, when dealing with sudden quality deterioration, the prior art lacks a rapid and effective emergency response mechanism and cannot effectively guarantee the quality and safety of grains and oils. Summary of the Invention

[0005] This invention provides a method for preserving grains and oils based on changes in environmental conditions, comprising:

[0006] In response to the initial environmental parameter set of the storage space obtained by the grain condition monitoring unit, the category characteristics and quality deterioration threshold of the target grain and oil are analyzed.

[0007] Based on the category feature identifier, a matching set of environmental control rules is retrieved from the grain storage strategy library. The set of environmental control rules includes temperature stratification control strategy, humidity response strategy and controlled atmosphere dynamic matrix.

[0008] Real-time collection of dynamic environmental parameters of the storage space, including grain pile temperature distribution parameters, grain and oil surface moisture content parameters, and gas component concentration parameters;

[0009] Based on the deviation relationship between the quality deterioration threshold and the dynamic environmental parameter set, an environmental control instruction sequence is generated;

[0010] Send a sequence of environmental control commands to the grain storage execution system for execution:

[0011] Based on the temperature equalization instructions in the sequence, the ventilation system is activated to regulate the temperature gradient of the grain pile.

[0012] Based on the humidity correction instructions in the sequence, control the dehumidification device to adjust the moisture content of grains and oils;

[0013] Based on the gas replacement instructions in the sequence, operate the controlled atmosphere equipment to maintain the target gas composition;

[0014] In response to the quality deterioration warning signal triggered by the quality detection unit, an emergency control command is generated by combining the grain and oil deterioration dynamics model.

[0015] Emergency control instructions will be dynamically integrated into the environmental control instruction sequence.

[0016] Furthermore, the initial environmental parameter set includes the initial concentration of fungal toxins and the baseline pest density;

[0017] Before collecting dynamic environment parameter sets, perform the following operations:

[0018] When the initial concentration of fungal toxins exceeds a preset safety threshold, a toxin accumulation warning is generated.

[0019] When the pest density exceeds the preset pest warning line, a biological infection warning is generated.

[0020] When both toxin accumulation warning and biological invasion warning exist simultaneously, the fumigation intervention unit of the grain storage execution system is activated.

[0021] The generated environment control instruction sequence includes:

[0022] In response to the activation of the fumigation intervention unit, the fumigant release command is embedded into the environmental control command sequence.

[0023] Furthermore, generating the environmental control instruction sequence includes the following steps:

[0024] Perform thermodynamic anomaly analysis on the temperature distribution parameters of the grain pile and output the location information of the temperature imbalance area;

[0025] Perform condensation risk assessment on the surface moisture content parameter of grains and oils, and output a humidity risk level that represents the degree of risk;

[0026] When there is a temperature imbalance area or the humidity risk level reaches the preset risk level, the generation of an environmental control instruction sequence is triggered.

[0027] Furthermore, the thermodynamic anomaly analysis includes:

[0028] The grain pile was divided into multiple three-dimensional monitoring areas along the vertical direction;

[0029] Calculate the temperature variation coefficient for each monitoring area;

[0030] Regions where the temperature variation coefficient exceeds a preset variation threshold are designated as temperature imbalance regions.

[0031] Based on the three-dimensional distribution coordinates of the temperature imbalance region, a topology diagram guiding the ventilation path is generated.

[0032] Furthermore, the generated environmental control instruction sequence includes:

[0033] A stratified ventilation strategy is determined based on the depth characteristics of the temperature imbalance zone, where:

[0034] Low-intensity, slow-speed ventilation is used in deeper areas;

[0035] The middle layer area adopts a medium-intensity balanced ventilation mode;

[0036] The surface area employs a high-intensity directional ventilation mode;

[0037] When a vertical migration of a temperature imbalance area is detected, the ventilation mode is automatically switched.

[0038] The dehumidification intensity gradient is determined based on the humidity risk level, where:

[0039] Low-risk levels correspond to intermittent dehumidification mode;

[0040] Medium-risk level corresponds to continuous dehumidification mode;

[0041] High-risk levels correspond to combined dehumidification modes;

[0042] When the humidity risk level continues to rise for two consecutive monitoring cycles, the cross-level mode switching will be initiated.

[0043] The gas control update frequency is calculated based on gas component concentration parameters, where:

[0044] Increase the gas replacement frequency when the oxygen concentration is higher than the preset oxygen enrichment threshold.

[0045] Supplemental carbon dioxide gas is injected when the carbon dioxide concentration is below the preset insect-proof threshold.

[0046] The intensity of fumigation is determined based on the pest density baseline, where:

[0047] Low-density baseline matching preventative fumigation dosage;

[0048] Medium-density baseline matched controlled fumigation dosage;

[0049] High-density baseline matching eradicative fumigation dosage;

[0050] When the pest density increases beyond the preset mutation threshold within 24 hours, the fumigation intensity level should be immediately increased.

[0051] The stratified ventilation strategy, dehumidification intensity gradient, controlled atmosphere renewal frequency, and fumigation intensity are encapsulated into an environmental control instruction sequence.

[0052] Furthermore, determining the controlled atmosphere update frequency also includes:

[0053] Real-time monitoring of the spatial distribution of gas components inside the grain pile;

[0054] When the gas concentration distribution non-uniformity exceeds the preset uniformity threshold, the gas circulation homogenization program is activated.

[0055] The gas circulation homogenization procedure is executed sequentially:

[0056] Activate the bottom gas injection device to create a positive airflow;

[0057] Simultaneously activate the top gas suction device to establish a negative pressure gradient;

[0058] When the homogenization efficiency is lower than the preset standard, switch to pulsed airflow enhancement mode;

[0059] Continue operating the above device until the gas concentration distribution reaches the uniformity standard.

[0060] Furthermore, responding to quality deterioration warning signals includes:

[0061] The rate of change in fatty acid values ​​of grains and oils is continuously monitored using a spectral analysis device.

[0062] When the rate of change of fatty acid value exceeds the preset oxidation rate threshold, a quality deterioration warning signal is triggered.

[0063] Simultaneously acquire peroxide value acceleration data for grains and oils to verify the reliability of the deterioration warning level.

[0064] Furthermore, generating emergency control instructions includes:

[0065] A temperature suppression strategy was developed based on the rate of change in fatty acid values, wherein:

[0066] A low rate of change corresponds to a stepped cooling mode;

[0067] The rate of change corresponds to a linear cooling mode;

[0068] High rate of change affects emergency rapid cooling mode;

[0069] When there is a risk of localized condensation during the cooling process, switch to gradient cooling mode;

[0070] The critical moisture content boundary is dynamically calculated based on the grain and oil deterioration kinetic model. This boundary value is determined by real-time temperature parameters and relative humidity parameters.

[0071] When the moisture content is detected to be approaching the critical moisture content boundary, a composite dehumidification command is generated, which includes:

[0072] The thermal dehumidification device is activated during daytime operation.

[0073] During the nighttime operation phase, the system switches to an adsorption dehumidification device.

[0074] When the ambient humidity suddenly rises above the preset threshold, the dual-device parallel dehumidification mode is activated.

[0075] Furthermore, the dynamic integration of emergency control instructions includes:

[0076] Add time-period constraints to the temperature equalization command, including:

[0077] During the hot season, ventilation operations are limited to nighttime hours.

[0078] Ventilation is permitted around the clock during periods of low temperatures.

[0079] When the diurnal temperature difference exceeds the preset fluctuation threshold, the dynamic time period adjustment mechanism is activated;

[0080] Configure the space control strategy in the humidity correction command, where:

[0081] The surface of grains and oils is treated with a high-temperature, rapid dehumidification mode.

[0082] The middle layer of the grain pile adopts a medium-temperature and constant-humidity control mode;

[0083] The bottom layer of the grain pile maintains a natural humidity balance.

[0084] When the phenomenon of rising humid and hot airflow is detected, the reverse stratification control logic is activated;

[0085] Elevate the execution priority of the gas replacement command to the highest level.

[0086] Furthermore, it also includes a phase for evaluating the effectiveness of regulation:

[0087] After completing the environmental control operations, the dynamic environmental parameter set is collected again;

[0088] A quality maintenance index was constructed based on changes in fatty acid values ​​and increases in peroxide values.

[0089] When the quality maintenance index falls below the preset acceptable threshold, the control process, including the following steps, is re-executed:

[0090] The dynamic environmental parameter set is retrieved again, and a new environmental control instruction sequence is generated.

[0091] Execute the updated temperature equalization command, humidity correction command, and gas replacement command;

[0092] If the quality deterioration warning signal is triggered again, a new emergency control instruction will be generated and executed.

[0093] The embodiments of the present invention have at least the following beneficial effects:

[0094] 1. By collecting dynamic environmental parameters of the storage space in real time and combining them with grain and oil category characteristics and quality deterioration thresholds to generate an environmental control command sequence, precise control of the storage environment is achieved. This method can dynamically adjust temperature, humidity, and gas composition according to the specific needs of grains and oils, effectively solving the problem that traditional methods cannot perform personalized control according to grain and oil categories and quality requirements, thereby significantly improving the quality stability of grains and oils during storage.

[0095] 2. A quality deterioration early warning signal mechanism is introduced, which combines a grain and oil deterioration kinetic model to generate emergency control commands and dynamically integrates them into the environmental control command sequence. This mechanism can quickly respond to sudden quality deterioration and take timely and targeted emergency measures, such as temperature suppression and compound dehumidification, effectively solving the problem of the lack of a rapid response mechanism in existing technologies when dealing with sudden quality deterioration, and greatly reducing the risk of grain and oil spoilage.

[0096] 3. Through comprehensive control of tiered ventilation strategies, dehumidification intensity gradients, controlled atmosphere renewal frequency, and fumigation intensity, the storage environment has been optimized in all aspects. For example, different ventilation intensities are used according to different depths of temperature imbalance areas, and dehumidification modes are adjusted according to humidity risk levels. This effectively solves the problem of uneven temperature and humidity in the storage environment. At the same time, combined with gas circulation homogenization procedures and dynamic fumigation intensity adjustments, the storage environment has been further optimized, ensuring the safety of grain and oil storage. Attached Figure Description

[0097] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the invention are illustrated in the drawings by way of example, not limitation, in which:

[0098] Figure 1 This is a schematic flowchart of a grain and oil preservation method based on environmental condition changes, provided as an embodiment of the present invention. Detailed Implementation

[0099] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following drawings indicate similar items; therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0100] like Figure 1 As shown, this application proposes a method for preserving grains and oils based on changes in environmental conditions, including:

[0101] S1. Responding to the initial environmental parameter set of the storage space obtained by the grain condition monitoring unit, analyze the category characteristics and quality deterioration threshold of the target grain and oil.

[0102] S2. Based on the category feature identifier, retrieve the matching environmental control rule set from the grain storage strategy library. The environmental control rule set includes temperature stratification control strategy, humidity response strategy and controlled atmosphere dynamic matrix.

[0103] S3. Real-time collection of dynamic environmental parameters of the storage space, including grain pile temperature distribution parameters, grain and oil surface moisture content parameters, and gas component concentration parameters.

[0104] S4. Generate an environmental control instruction sequence based on the deviation relationship between the quality deterioration threshold and the dynamic environmental parameter set;

[0105] S5. Send a sequence of environmental control instructions to the grain storage execution system for execution:

[0106] S6. Based on the temperature equalization command in the sequence, activate the ventilation system to regulate the temperature gradient of the grain pile;

[0107] S7. According to the humidity correction instructions in the sequence, control the dehumidification device to adjust the moisture content of grains and oils;

[0108] S8. Based on the gas replacement instructions in the sequence, operate the gas conditioning equipment to maintain the target gas composition;

[0109] S9. In response to the quality deterioration warning signal triggered by the quality detection unit, generate emergency control instructions in combination with the grain and oil deterioration dynamics model.

[0110] S10. Dynamically integrate emergency control instructions into the environmental control instruction sequence.

[0111] This application generates a multi-dimensional collaborative control command sequence by real-time monitoring of the deviation between dynamic parameters of the storage environment and preset quality deterioration thresholds, and dynamically integrates emergency control mechanisms to achieve intelligent and precise control of the grain and oil storage environment.

[0112] The working process and principle of this application are as follows: First, the initial environmental parameter set of the storage space is obtained through the grain condition monitoring unit, and the category characteristics and quality deterioration threshold of the target grain and oil are analyzed. This step provides basic data support for subsequent environmental control.

[0113] Next, based on the category characteristic identifier, the matching environmental control rule set is retrieved from the grain storage strategy library. The environmental control rule set includes temperature stratification control strategies, humidity response strategies, and controlled atmosphere dynamic matrices. These strategies are customized for the characteristics of different grain and oil categories to achieve precise control.

[0114] The system then collects a set of dynamic environmental parameters of the storage space in real time, including grain pile temperature distribution parameters, grain and oil surface moisture content parameters, and gas component concentration parameters. This real-time data reflects the dynamic changes in the storage environment.

[0115] Based on the deviation relationship between the quality deterioration threshold and the dynamic environmental parameter set, the system generates a sequence of environmental control instructions. This step compares real-time data with preset thresholds to determine the control measures that need to be taken.

[0116] The generated environmental control command sequence is then sent to the grain storage execution system for execution. Specifically, this includes: activating the ventilation system to regulate the temperature gradient of the grain pile based on the temperature equalization command; controlling the dehumidification device to adjust the moisture content of the grain and oil based on the humidity correction command; and operating the controlled atmosphere equipment to maintain the target gas composition based on the gas replacement command. These three aspects of regulation work together to maintain the optimal storage environment.

[0117] Furthermore, the system can also respond to quality deterioration warning signals triggered by the quality detection unit. When a potential risk of quality deterioration is detected, the system generates emergency control instructions based on the grain and oil deterioration kinetic model and dynamically integrates them into the environmental control instruction sequence. This mechanism ensures that the system can respond promptly to sudden quality problems.

[0118] The initial environmental parameter set acquired by the grain condition monitoring unit refers to the real-time collection of basic data on the storage environment through a sensor network. This can be achieved using temperature and humidity sensors, gas composition analyzers, and pest detection devices, establishing a baseline reference for environmental control. Category characteristic identification and quality deterioration thresholds refer to storage condition parameters and critical values ​​for quality changes defined according to the type of grain and oil. This can be achieved by storing the temperature, humidity, and gas concentration tolerance ranges of different grains and oils in a database, used to match differentiated control strategies. The grain storage strategy library is a database storing environmental control rules corresponding to different grain and oil categories. This can be achieved using a relational database combined with machine learning models, used for quickly retrieving applicable control logic. The environmental control rule set includes temperature stratified control strategies, humidity response strategies, and a controlled atmosphere dynamic matrix, which refers to a set of control methods for different environmental dimensions. This can be achieved by using fuzzy control algorithms to set temperature gradients, humidity feedback mechanisms, and gas replacement frequency matrices, used to achieve coordinated control of multi-dimensional environmental parameters. The dynamic environmental parameter set, including grain pile temperature distribution parameters, grain and oil surface moisture content parameters, and gas component concentration parameters, refers to the set of environmental variables monitored in real time. This can be implemented using distributed temperature sensors, infrared moisture meters, and multi-channel gas detectors to capture dynamic environmental trends. The environmental control command sequence refers to the set of control operations generated based on real-time environmental deviations. This can be implemented using a priority queue combined with a time-triggered mechanism for the orderly execution of multi-device collaborative operations. The grain storage execution system refers to the set of hardware devices that execute environmental control commands. This can be implemented using variable frequency fans, intelligent dehumidifiers, and gas replacement devices for precise adjustment of physical environmental parameters. Emergency control commands are emergency operation orders to respond to sudden quality deterioration. This can be implemented using a dynamic priority queueing mechanism combined with a real-time calculation model to quickly halt the deterioration process.

[0119] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0120] In a large grain and oil storage facility, a grain condition monitoring unit is installed, including a temperature sensor network, humidity detectors, and gas concentration analyzers. When a new batch of corn enters the storage, the grain condition monitoring unit first acquires the initial environmental parameter set of the storage space, including temperature, humidity, and gas composition data. Simultaneously, the system analyzes the corn's category characteristics, such as variety, origin, and harvest time, and their corresponding quality deterioration thresholds, such as maximum permissible temperature, humidity, and carbon dioxide concentration.

[0121] For example, based on the variety characteristics of the corn, the system retrieves a matching set of environmental control rules from a pre-established grain storage strategy library. For instance, for this batch of corn, the temperature stratification control strategy might be set to 15-18℃ for the top layer, 12-15℃ for the middle layer, and 10-12℃ for the bottom layer; the humidity response strategy might specify that the relative humidity should be maintained at 60-65%; and the controlled atmosphere dynamic matrix might require the oxygen concentration to be controlled at 5-8% and the carbon dioxide concentration to be maintained at 12-15%.

[0122] The system collects dynamic environmental parameters in real time through a sensor network distributed throughout the storage space. Temperature sensors record the temperature of each layer of the grain pile at 5-minute intervals; humidity detectors continuously monitor the surface moisture content of the grain and oil; and gas concentration analyzers sample once an hour to measure the concentration of gaseous components such as oxygen and carbon dioxide.

[0123] The system compares and analyzes preset quality deterioration thresholds with real-time collected dynamic environmental parameters to generate a sequence of environmental control commands. For example, when the top layer temperature exceeds 18°C, a cooling command is generated; when the surface moisture content approaches the safe upper limit, a dehumidification command is generated; and when the oxygen concentration is higher than 8%, a gas replacement command is generated.

[0124] An environmental control command sequence is sent to the grain storage execution system. The ventilation system activates according to the temperature equalization command, adjusting fan speed and ventilation time to reduce the top-level temperature and equalize the temperature gradient. The dehumidification device activates according to the humidity correction command, reducing air humidity through condensation or adsorption. The controlled atmosphere equipment operates according to the gas replacement command, injecting nitrogen or carbon dioxide to adjust the gas composition within the storage silo.

[0125] Meanwhile, the quality inspection unit continuously monitors grain and oil quality indicators. When an abnormal increase in fatty acid values ​​is detected, a quality deterioration warning signal is triggered. The system immediately combines the grain and oil deterioration kinetic model to generate emergency control instructions, such as increasing ventilation and dehumidification intensity. These emergency instructions are dynamically integrated into the existing environmental control instruction sequence to form a new control scheme.

[0126] This application further proposes a grain and oil preservation method based on environmental condition changes, including: an initial environmental parameter set containing the initial concentration of mycotoxins and the base density of pests; before collecting the dynamic environmental parameter set, performing the following operations: when the initial concentration of mycotoxins exceeds a preset safety threshold, generating a toxin accumulation warning; when the base density of pests exceeds a preset pest warning line, generating a biological infection warning; when the toxin accumulation warning and the biological infection warning exist simultaneously, activating the fumigation intervention unit of the grain storage execution system; generating an environmental control command sequence including: in response to the activation of the fumigation intervention unit, embedding a fumigant release command into the environmental control command sequence.

[0127] The initial environmental parameter set is expanded to include mycotoxin concentration and pest density, establishing a biosafety monitoring benchmark through preset safety thresholds and pest warning lines. The generation logic for toxin accumulation warnings is based on the correlation between mycotoxin concentration and grain / oil quality, while pest density is acquired in real-time through pest activity monitoring devices. The activation condition for the fumigation intervention unit is set to a joint triggering of both toxin and pest warnings, ensuring comprehensive control of biological risks. The embedding of fumigant release commands is achieved through a command sequence priority adjustment module, forming a parallel execution logic with temperature and humidity control commands.

[0128] Specifically, during the initialization phase of the storage space, the initial concentration of mycotoxins is obtained through a toxin detection device, while the pest density is collected using a pest density sensor. When the mycotoxin concentration exceeds a preset safety threshold, a toxin accumulation warning signal is triggered. This threshold is set based on the tolerance characteristics of grain and oil varieties to toxins. The pest density is monitored periodically by an infrared monitoring device, scanning the surface of the grain pile for the number of active insects. When the density exceeds a preset pest warning line, a biological infection warning is generated. When both warning signals are present simultaneously, the control circuit of the fumigation intervention unit is activated, initiating the valve control mechanism of the fumigant storage container. The fumigant release command is encoded as an independent control command and inserted into the environmental control command sequence through the command distribution module of the grain storage execution system, forming a time-staggered execution mode with ventilation and dehumidification commands. The fumigant release dosage is dynamically adjusted according to the gradient range of the pest density, with a preventative dose for low density and an eradication dose for high density. After the fumigation operation is completed, the uniformity of fumigant diffusion is verified using a gas concentration sensor to ensure effective suppression of biological risks.

[0129] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0130] The initial environmental parameter set includes the initial concentration of fungal toxins and the baseline pest density. Before collecting the dynamic environmental parameter set, perform the following operations:

[0131] When the initial concentration of mycotoxins exceeds a preset safety threshold, a toxin accumulation warning is generated. For example, when the aflatoxin B1 content reaches 20 μg / kg, the system automatically triggers a toxin accumulation warning signal.

[0132] When the pest density exceeds a preset pest warning line, a biological infestation warning is generated. Specifically, when photoelectric sensors detect more than 5 stored grain pests per kilogram of grain, the system generates a biological infestation warning.

[0133] When both toxin accumulation and biological infestation warnings are present, the fumigation intervention unit of the grain storage system is activated. Furthermore, the system automatically starts the phosphine generator, preparing for fumigation operations.

[0134] The generated environmental control instruction sequence includes: in response to the activation of the fumigation intervention unit, embedding the fumigant release instruction into the environmental control instruction sequence. Thus, the system automatically calculates the required phosphine concentration based on the pest density and generates the corresponding fumigant release instruction, such as "maintain the phosphine concentration in the storage space at 1000 ppm for 48 hours".

[0135] This application further proposes to perform thermodynamic anomaly analysis on the temperature distribution parameters of grain piles and output the location information of temperature imbalance areas; to perform condensation risk assessment on the surface moisture content parameters of grain and oil and output the humidity risk level that characterizes the degree of risk; and to trigger the generation of an environmental control instruction sequence when there are temperature imbalance areas or the humidity risk level reaches a preset risk level.

[0136] Thermodynamic anomaly analysis involves dividing the grain pile into multi-layered, three-dimensional monitoring areas, calculating the temperature variation coefficient of each layer, and marking areas exceeding preset thresholds. Condensation risk assessment uses real-time data collection of surface moisture content parameters, combined with ambient temperature data, to calculate the dew point difference and output low, medium, and high risk levels. Triggering conditions are set to the presence of temperature imbalance areas or a risk level reaching a preset threshold; for example, a surface moisture content higher than 12% and a temperature gradient exceeding 3℃ / m are considered high-risk.

[0137] Specifically, the temperature distribution parameters of the grain pile are collected in real time through a distributed temperature sensor network, with each monitoring area covering a depth of 0.5 meters. The temperature variation coefficient is calculated as the ratio of the standard deviation to the mean, with a preset variation threshold of 0.15. When the variation coefficient of a certain layer exceeds the threshold, the coordinates of that layer are marked as a temperature imbalance area. The surface moisture content parameter is collected every 30 minutes by a near-infrared sensor, and the dew point difference is calculated by the difference between the current temperature and the dew point temperature corresponding to the moisture content. The preset risk levels are: a difference greater than 2℃ is low risk, 1-2℃ is medium risk, and less than 1℃ is high risk. When the system detects at least one temperature imbalance area or the surface risk level reaches medium risk or above, it automatically generates a sequence of instructions including ventilation path adjustment and dehumidification intensity enhancement. For example, when the temperature variation coefficient of the middle layer of the grain pile reaches 0.18 and the surface dew point difference is 0.8℃, the system simultaneously triggers a stratified ventilation instruction and a high-intensity dehumidification instruction, adjusting the ventilation system wind speed to 2.5m / s and activating the dual-mode dehumidification device to achieve precise environmental control.

[0138] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0139] Generating an environmental control instruction sequence includes the following steps:

[0140] Thermodynamic anomaly analysis was performed on the temperature distribution parameters of the grain pile. This analysis first divided the grain pile vertically into multiple monitoring zones; for example, a 20-meter-high grain pile was divided into ten 2-meter-high zones. Then, the temperature variation coefficient within each zone was calculated. Specifically, multiple temperature sensors were deployed within each zone to collect temperature data over a certain time period, and the ratio of the standard deviation to the mean was calculated. Next, the calculated temperature variation coefficient was compared with a preset variation threshold, such as 0.05. If the variation coefficient of a zone exceeded the threshold, that zone was marked as a temperature imbalance zone. Finally, based on the marked temperature imbalance zones, a topology map guiding ventilation paths was generated.

[0141] A condensation risk assessment is performed on the surface moisture content of grains and oilseeds. The assessment process begins by collecting moisture content data from multiple points on the surface of the grain pile. This data is then compared to a preset safe moisture content range. For example, for wheat, the safe moisture content range can be set at 12%-14%. Based on the comparison results, the risk level is classified into three levels: low, medium, and high. Specifically, when the moisture content is within the safe range, it is considered low risk; when the moisture content is close to the boundary of the safe range, it is considered medium risk; and when the moisture content exceeds the safe range, it is considered high risk.

[0142] When an area of ​​temperature imbalance is detected or the humidity risk level reaches a preset risk level, the generation of an environmental control command sequence is triggered. For example, if the area of ​​temperature imbalance exceeds 10% of the total grain pile area, or the humidity risk level reaches medium risk, the system will automatically start the command sequence generation program. This program comprehensively considers the temperature distribution and humidity risk situation to generate a command sequence that includes ventilation, dehumidification, and controlled atmosphere operations.

[0143] This application further proposes to divide the grain pile into multi-layer three-dimensional monitoring areas in the vertical direction; calculate the temperature variation coefficient of each monitoring area; mark areas where the temperature variation coefficient exceeds a preset variation threshold as temperature imbalance areas; and generate a topology map to guide ventilation paths based on the three-dimensional distribution coordinates of the temperature imbalance areas.

[0144] The division of multi-layer three-dimensional monitoring areas is achieved through preset height intervals, such as setting the height of each layer to 0.5 meters to 1.5 meters; the temperature variation coefficient is obtained by calculating the ratio of the standard deviation to the average value of the temperature data of each layer; the preset variation threshold is set according to the thermal stability of the grain type, for example, the threshold for wheat is set to 0.15 and the threshold for corn is set to 0.18; the three-dimensional distribution coordinates record the horizontal position and vertical depth of the temperature imbalance area through a three-dimensional coordinate system; the topology map generates ventilation routes by connecting adjacent temperature imbalance areas.

[0145] Specifically, after the grain pile is vertically layered, temperature data is collected independently for each layer, and the degree of temperature fluctuation in each layer is quantified by calculating the coefficient of variation. When the coefficient of variation of a certain layer exceeds a preset threshold, it is determined that there is a temperature imbalance in that layer, and its three-dimensional coordinates are recorded. Based on the coordinate data of all imbalanced areas, a topology map is generated to plan ventilation paths. For example, continuous imbalanced areas are prioritized in the horizontal direction, and a gradient ventilation sequence is adopted in the vertical direction. In this way, the ventilation system can accurately locate areas with abnormal temperatures, avoid ineffective ventilation operations, and reduce energy consumption. For example, when the coefficient of variation of temperature exceeds the standard in the middle layer of the grain pile, the topology map will generate a ring-shaped ventilation path for that layer to ensure uniform heat diffusion.

[0146] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0147] The grain pile is vertically divided into multi-layered, three-dimensional monitoring zones. For example, a 20-meter-high grain pile is divided into 10 monitoring zones, each 2 meters high. A temperature sensor array is installed within each monitoring zone, with 16 temperature sensors arranged in a 4x4 grid within each zone.

[0148] Calculate the temperature variation coefficient for each monitoring area. Specifically, perform statistical analysis on 16 temperature data points for each area to calculate the average temperature and standard deviation, and then divide the standard deviation by the average temperature to obtain the variation coefficient.

[0149] Regions whose temperature coefficient of variation exceeds a preset variation threshold are marked as temperature imbalance regions. For example, if the variation threshold is set to 0.1, when the coefficient of variation of a certain region exceeds 0.1, that region is marked as a temperature imbalance region.

[0150] Based on the three-dimensional distribution coordinates of the temperature imbalance regions, a topology map guiding ventilation paths is generated. Specifically, the location information of the temperature imbalance regions in three-dimensional space is mapped onto the topology map, and the optimal ventilation path is designed according to the distribution characteristics of the imbalance regions. For example, if the imbalance regions are mainly concentrated at the bottom of the grain pile, the ventilation path from the bottom upwards is marked on the topology map.

[0151] This application further proposes a sequence of environmental control instructions, including: determining a tiered ventilation strategy based on the depth of the temperature imbalance area, employing a low-intensity, slow-speed ventilation mode for deep areas, a medium-intensity, balanced ventilation mode for middle areas, and a high-intensity, directional ventilation mode for surface areas; automatically switching ventilation modes when vertical migration of the temperature imbalance area is detected; and determining a dehumidification intensity gradient based on the humidity risk level, with intermittent dehumidification mode corresponding to low risk levels, continuous dehumidification mode corresponding to medium risk levels, and combined dehumidification mode corresponding to high risk levels; and activating a cross-level mode when the humidity risk level continues to rise for two consecutive monitoring periods. The system employs several methods: 1) Calculate the modified atmosphere replacement frequency based on gas component concentration parameters; 2) Increase the gas replacement frequency when the oxygen concentration is higher than the preset oxygen enrichment threshold, and inject supplemental carbon dioxide gas when the carbon dioxide concentration is lower than the preset pest control threshold; 3) Determine the fumigation intensity based on the pest density baseline: Preventative fumigation dosage for low density baselines, control fumigation dosage for medium density baselines, and eradication fumigation dosage for high density baselines; 4) Immediately increase the fumigation intensity level when the pest density baseline increases beyond the preset mutation threshold within 24 hours; 5) Encapsulate the stratified ventilation strategy, dehumidification intensity gradient, modified atmosphere replacement frequency, and fumigation intensity into an environmental control instruction sequence.

[0152] Among them, the stratified ventilation strategy divides the ventilation intensity by vertical depth attribute. Low-intensity, slow ventilation is used in deep areas to avoid excessive airflow disturbance inside the grain pile, while high-intensity, directional ventilation is used in surface areas to quickly eliminate abnormal surface temperatures. The dehumidification intensity gradient dynamically adjusts the dehumidification mode according to the rate of change of risk level. When the humidity risk level rises for two consecutive cycles, a cross-level switch is triggered to prevent the accumulation of condensation risk. The modified atmosphere update frequency dynamically adjusts the gas replacement operation based on real-time monitoring data of oxygen and carbon dioxide concentrations. When the carbon dioxide concentration is detected to be below the pest control threshold, gas is injected to maintain the pest-suppressing environment. The fumigation intensity is graded and matched with the dosage according to the pest density base and its mutation rate. When the pest density increases beyond the mutation threshold within 24 hours, the intensity level is immediately increased to block the spread of pests.

[0153] Specifically, the depth of temperature imbalance zones is identified through vertical stratification monitoring data of the grain pile. Deep zones utilize a low-intensity, slow-speed ventilation mode to avoid structural damage; middle zones employ a medium-intensity, balanced ventilation mode to balance temperature distribution; and surface zones use a high-intensity, directional ventilation mode to quickly eliminate localized high temperatures. When a temperature imbalance zone migrates vertically, the ventilation system automatically switches the ventilation mode for the corresponding zone based on the migration direction. Humidity risk levels are output using a condensation risk assessment algorithm. Intermittent dehumidification mode periodically starts and stops equipment at low risk levels, continuous dehumidification mode keeps equipment running continuously at medium risk levels, and combined dehumidification mode simultaneously activates multiple devices to enhance dehumidification capacity at high risk levels. When the humidity risk level continues to rise for two consecutive monitoring cycles, the system automatically triggers a cross-level switching of the dehumidification mode. Gas component concentration parameters are collected in real time by sensors. When the oxygen concentration exceeds the oxygen enrichment threshold, the gas replacement frequency is increased to reduce the risk of oxidation. When the carbon dioxide concentration is below the insect control threshold, supplemental gas is injected to maintain an insect-suppressing environment. The fumigation dosage is graded and matched according to the insect density: the preventative dosage is used to inhibit egg hatching in low-density populations, the control dosage is used to kill adult insects in medium-density populations, and the eradication dosage is used to completely eliminate the insect population in high-density populations. When the insect density increases beyond the mutation threshold within 24 hours, the system immediately increases the fumigation intensity level to prevent an outbreak. These features, through dynamic matching and control parameters and real-time monitoring data, enable multi-dimensional and precise control of the storage environment.

[0154] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0155] A tiered ventilation strategy is determined based on the depth of the temperature imbalance zone. Deep zones utilize a low-intensity, slow-speed ventilation mode with an airflow velocity of 0.1-0.3 m / s for 8-12 hours. Mid-level zones employ a medium-intensity, balanced ventilation mode with an airflow velocity of 0.3-0.5 m / s for 4-6 hours. Surface zones utilize a high-intensity, directional ventilation mode with an airflow velocity of 0.5-0.8 m / s for 2-3 hours. The ventilation mode is automatically switched when vertical migration of the temperature imbalance zone is detected.

[0156] The dehumidification intensity gradient is determined based on the humidity risk level. Low risk level corresponds to intermittent dehumidification mode, where the dehumidifier operates for 15 minutes and then stops for 45 minutes, repeating this cycle. Medium risk level corresponds to continuous dehumidification mode, where the dehumidifier operates continuously for 2 hours and then stops for 30 minutes. High risk level corresponds to combined dehumidification mode, which simultaneously activates thermal dehumidification and adsorption dehumidification devices, operating continuously for 4 hours. When the humidity risk level continues to rise for two consecutive monitoring periods, a cross-level mode switch is initiated.

[0157] Calculate the frequency of controlled atmosphere (CA) renewal based on the gas component concentration parameters. When the oxygen concentration is higher than 18%, increase the gas replacement frequency to once per hour. When the carbon dioxide concentration is lower than 0.5%, inject supplementary carbon dioxide gas to increase the concentration to 1%.

[0158] Determine the fumigation intensity based on the pest density base number. For a low density base number, where the number of pests per kilogram of grain is less than 1, match the preventive fumigation dose and use aluminum phosphide tablets at 2 - 3 grams per cubic meter of grain. For a medium density base number, where the number of pests per kilogram of grain is 1 - 5, match the control fumigation dose and use aluminum phosphide tablets at 3 - 5 grams per cubic meter of grain. For a high density base number, where the number of pests per kilogram of grain is greater than 5, match the eradication fumigation dose and use aluminum phosphide tablets at 5 - 8 grams per cubic meter of grain. When the pest density base number increases by more than 100% within 24 hours, immediately increase the fumigation intensity level.

[0159] Package the stratified ventilation strategy, dehumidification intensity gradient, CA renewal frequency, and fumigation intensity into an environmental control instruction sequence. This instruction sequence is stored in JSON format and contains the specific values of each parameter and the execution time.

[0160] This application further proposes that determining the CA renewal frequency also includes: real - time monitoring of the spatial distribution state of gas components inside the grain pile; when the unevenness of gas concentration distribution exceeds the preset uniformity threshold, start the gas circulation homogenization program; the gas circulation homogenization program is executed in sequence: open the bottom gas injection device to form a positive air flow; simultaneously start the top gas suction device to establish a negative pressure gradient; when the homogenization efficiency is lower than the preset standard, switch to the pulsed air flow enhancement mode; continuously operate the above devices until the gas concentration distribution reaches the uniformity standard.

[0161] Among them, the bottom gas injection device covers the bottom area of the grain pile through a porous pipeline layout, and the positive air flow penetrates the grain pile upward at a constant flow rate; the top gas suction device forms a gas suction path from top to bottom through a negative pressure fan, forming a convection cycle with the bottom injection. The pulsed air flow enhancement mode impacts the gas stagnant area inside the grain pile through intermittent pressurized air flows, for example, releasing high - pressure air flows at a pulse frequency of three times per minute. The homogenization efficiency is calculated in real - time through a gas concentration sensor network, and it is determined to meet the standard when the concentration difference between adjacent monitoring points is less than 80% of the preset uniformity threshold.

[0162] Specifically, during the gas circulation homogenization process, the synchronized operation of the bottom gas injection device and the top suction device creates a bidirectional airflow circulation, accelerating the diffusion rate of gas components within the grain pile. For example, when the oxygen concentration in the middle layer of the grain pile exceeds the preset oxygen enrichment threshold, the inert gas injected at the bottom migrates upwards through the forward airflow, while the top suction device removes the oxygen-enriched airflow from the storage space. If gas concentration differences still exist in the corner areas of the grain pile, a pulsed airflow enhancement mode breaks the local gas stagnation state through instantaneous high-pressure airflow. During this process, the gas concentration sensor continuously feeds back spatial distribution data until the concentration difference at all monitoring points drops below the homogenization threshold. Through this process, the coverage and response speed of gas regulation are improved, avoiding the risk of quality deterioration caused by local concentration anomalies.

[0163] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0164] Real-time monitoring of the spatial distribution of gas components inside the grain pile. Multiple gas concentration sensors are installed at different locations within the grain pile to continuously collect concentration data of key gas components such as oxygen and carbon dioxide. These sensors are distributed in a grid pattern at the top, middle, and bottom of the grain pile, forming a three-dimensional monitoring network.

[0165] When the gas concentration distribution non-uniformity exceeds a preset uniformity threshold, the gas circulation homogenization procedure is initiated. Specifically, the system calculates the concentration difference between each monitoring point, and triggers the homogenization procedure when the maximum concentration difference exceeds 10%.

[0166] The gas circulation homogenization procedure executes the following steps sequentially:

[0167] First, activate the bottom gas injection device to create a forward airflow. Multiple gas injection ports are installed at the bottom, and the gas injection rate and pressure are controlled by adjustable valves. The initial injection rate is set to 0.5 m³ / min, and the pressure to 0.2 MPa.

[0168] Secondly, the top gas extraction device is activated simultaneously to establish a negative pressure gradient. Multiple extraction ports are installed at the top, and the extraction intensity is adjusted by a variable frequency fan. The initial extraction rate is set to 0.6 m³ / min, creating a negative pressure of -0.1 MPa.

[0169] Furthermore, when the homogenization efficiency falls below a preset standard, the system switches to a pulsed airflow enhancement mode. Every 30 seconds, the system alternately turns the bottom air injection and top air extraction on and off, generating a pulsed airflow to enhance the gas mixing effect.

[0170] Finally, continue running the above device until the gas concentration distribution reaches the uniformity standard. The system performs a concentration distribution assessment every 5 minutes, and stops the homogenization process when the concentration difference between monitoring points drops below 5%.

[0171] This application further proposes a response to the quality deterioration warning signal, including: continuously monitoring the rate of change of fatty acid value of grains and oils through a spectral analysis device; triggering the quality deterioration warning signal when the rate of change of fatty acid value exceeds a preset oxidation rate threshold; and simultaneously acquiring the peroxide value acceleration data of grains and oils to verify the credibility of the deterioration warning level.

[0172] Among them, the spectral analysis device continuously collects spectral data of grain and oil samples in a non-contact manner, and analyzes the changing trend of fatty acid values ​​through a preset algorithm; the preset oxidation rate threshold is dynamically adjusted according to the characteristic identification of grain and oil categories, with different categories corresponding to different safe ranges of oxidation rates; the peroxide value acceleration data is obtained by real-time monitoring of the second derivative of peroxide value, which is used to reflect the accelerated state of the oxidation reaction; the fatty acid value change rate and peroxide value acceleration data are correlated through time series analysis to establish a two-parameter verification model.

[0173] Specifically, the spectral analysis device scans the surface and middle layers of the grain pile at a fixed sampling frequency to acquire reflectance spectral data. The real-time change in fatty acid values ​​is calculated using the shift of spectral characteristic peaks, with the rate of change derived from the differential of the change per unit time. When the rate of change exceeds the oxidation rate threshold corresponding to the current variety, a primary warning signal is triggered. Simultaneously, the peroxide value monitoring module is activated, collecting peroxide value data from the grain and oil samples via an electrochemical sensor and calculating its acceleration value. If the correlation between the acceleration value and the rate of change meets a preset verification standard, the credibility of the warning level is confirmed, and a formal warning signal is generated. If the two contradict each other, a re-inspection procedure is initiated, and sample data is collected again. This dual-parameter dynamic verification mechanism avoids misjudgments caused by single sensor failure or local environmental interference, ensuring the accuracy of the generated control commands.

[0174] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0175] The rate of change in fatty acid values ​​of grains and oils is continuously monitored using a spectral analysis device. The device employs near-infrared spectroscopy, scanning grain and oil samples at 5-minute intervals. After preprocessing and correction, the acquired spectral data is used to establish a fatty acid value prediction model using partial least squares (PLS) method. This model updates the fatty acid values ​​hourly and calculates the rate of change over 24 hours.

[0176] When the rate of change in fatty acid value exceeds a preset oxidation rate threshold, a quality deterioration warning signal is triggered. The preset oxidation rate threshold is set according to different grain and oil varieties; for example, for soybean oil, the threshold is set to 0.5 mg KOH / g·day. The system compares the actual rate of change with the threshold, and generates a warning signal once the threshold is exceeded.

[0177] Simultaneously acquire peroxide value acceleration data for grains and oils to verify the reliability of deterioration warning levels. Peroxide value is determined by iodometric titration, measured every 4 hours. The system calculates the second-order difference of three consecutive measurement results to obtain the peroxide value acceleration. Cross-validate the acceleration data with the warning signal to improve the accuracy of the warning.

[0178] This application further proposes generating emergency control instructions, including: formulating a temperature suppression strategy based on the rate of change of fatty acid values, with a step-down cooling mode corresponding to a low rate of change, a linear cooling mode corresponding to a medium rate of change, and an emergency rapid cooling mode corresponding to a high rate of change; switching to a gradient slow cooling mode when there is a risk of local condensation during the cooling process; dynamically calculating the critical moisture content boundary based on the grain and oil deterioration kinetic model, the boundary value being jointly determined by real-time temperature parameters and relative humidity parameters; generating a composite dehumidification instruction when the moisture content is detected to be approaching the critical moisture content boundary, the instruction including activating the thermal dehumidification device during the daytime operation phase and switching to the adsorption dehumidification device during the nighttime operation phase; and activating the dual-device parallel dehumidification mode when the ambient humidity suddenly rises above the preset abrupt change threshold.

[0179] Among them, the temperature suppression strategy is divided into step-type, linear and rapid cooling modes according to the rate of change of fatty acid value. The gradient slow cooling mode avoids condensation by adjusting the cooling rate in stages. The critical moisture content boundary is calculated by substituting the temperature and relative humidity parameters collected in real time into the grain and oil deterioration kinetic model to ensure the accuracy of dynamic adjustment. The composite dehumidification command switches between thermal dehumidification and adsorption dehumidification devices according to the difference between day and night environment. The dual-device parallel mode is used to deal with sudden changes in humidity.

[0180] Specifically, when the rate of change in fatty acid values ​​exceeds a threshold, the system selects the corresponding cooling mode based on the rate level. For example, a high rate of change triggers rapid cooling, but if the local temperature difference in the grain pile exceeds a preset range, it automatically switches to a gradient cooling mode to reduce the temperature in stages to avoid condensation. The critical moisture content boundary is updated in real time through a model. When the moisture content approaches the boundary value, the system selects the dehumidification device based on the current time period: thermal dehumidification is used during the day to improve dehumidification efficiency using ambient temperature; at night, it switches to adsorption dehumidification to avoid the decrease in thermal dehumidification efficiency caused by low temperatures. If the humidity suddenly rises above the mutation threshold, both the thermal and adsorption devices are activated simultaneously, rapidly reducing humidity through parallel operation. Thus, through dynamic calculation and mode switching, the risk of condensation is avoided while improving dehumidification efficiency, ensuring stable grain and oil quality.

[0181] As a preferred embodiment, the solution of this application is implemented as follows: When the rate of change of fatty acid value reaches 0.15% per minute, a quality deterioration warning signal is triggered, at which point the temperature suppression strategy is activated. Specifically, if the rate of change of fatty acid value is detected to be in the range of 0.12%-0.18% per minute, a stepped cooling mode is initiated, reducing the grain pile temperature by 1°C per hour; when the rate exceeds 0.18% per minute, a rapid cooling mode is switched to, using a liquid nitrogen injection device to reduce the grain pile temperature by 5°C within 30 minutes. During the cooling process, if the dew point temperature on the surface of the grain pile is less than 2°C from the ambient temperature, the cooling mode is immediately adjusted to a gradient slow cooling mode, with a temperature reduction of no more than 0.5°C per hour.

[0182] The critical moisture content boundary is calculated by inputting real-time collected temperature and relative humidity parameters into the grain and oil deterioration kinetic model. When the temperature in the middle layer of the grain pile is maintained at 15℃ and the relative humidity is 65%, the model outputs a critical moisture content boundary of 13.5%. When the surface moisture content of the grain pile reaches 13.2%, a composite dehumidification command is generated: during sufficient daylight, the thermal dehumidification device is activated to reduce the moisture content by 0.3% per hour; at night when the ambient temperature is below 15℃, the device switches to adsorption dehumidification to reduce the moisture content by 0.2% per hour. If the relative humidity of the storage space rises by more than 10% within one hour, both the thermal dehumidification device and the adsorption dehumidification device are activated simultaneously, forming a parallel dehumidification mode.

[0183] This application further proposes a method for generating emergency control commands, including formulating a temperature suppression strategy based on the rate of change of fatty acid value, dynamically calculating the critical moisture content boundary based on real-time environmental parameters, generating a composite dehumidification command, and integrating a dual-device parallel dehumidification mode.

[0184] The temperature suppression strategy includes a stepped cooling mode, a linear cooling mode, and a rapid cooling mode, corresponding to low, medium, and high rate of change scenarios, respectively. When a risk of local condensation is detected, the system automatically switches to a gradual cooling mode. The critical moisture content boundary is calculated by combining real-time temperature and relative humidity parameters to generate a composite dehumidification command. During daytime operation, the thermal dehumidification device is activated, while during nighttime operation, it switches to the adsorption dehumidification device. When the ambient humidity suddenly rises above a preset abrupt change threshold, both the thermal dehumidification device and the adsorption dehumidification device are activated simultaneously to form a parallel operating mode.

[0185] Specifically, when the spectral analysis device detects that the rate of change in fatty acid values ​​exceeds the preset oxidation rate threshold, the system selects the corresponding temperature suppression mode based on the rate range. For example, when the rate is in the 5%-10% / h range, a stepped cooling mode is triggered, reducing the temperature by 1°C every half hour; when the rate is in the 10%-15% / h range, a linear cooling mode is used, reducing the temperature at a constant slope; when the rate exceeds 15% / h, a rapid cooling mode is activated, reducing the temperature by 5°C within 10 minutes. During the cooling process, if the difference between the surface moisture content of the grain pile and the real-time temperature reaches the dew point, the system switches to a gradient slow cooling mode, adjusting the cooling rate to 0.5°C every half hour. The critical moisture content boundary is calculated by substituting real-time temperature parameters and relative humidity parameters into a preset formula. When the moisture content is detected to be approaching this boundary, a composite dehumidification command controls the thermal dehumidification device to maintain an operating temperature of 50°C during the day and switches to an adsorption dehumidification device at 25°C at night. When the ambient humidity rises by more than 20% in a single hour, the system simultaneously activates both types of dehumidifiers, increasing the dehumidification efficiency to 1.8 times that of the conventional mode. This mechanism achieves precise execution of emergency control commands and risk avoidance by dynamically matching changes in environmental parameters with equipment operating status.

[0186] As a preferred embodiment, the solution of this application is implemented as follows: During the dynamic integration of emergency control commands, the temperature balancing command is subject to time-limited constraints. Specifically, ventilation operations during high-temperature seasons are limited to nighttime hours, while ventilation operations are allowed throughout the day during low-temperature seasons. When the diurnal temperature difference exceeds a set fluctuation threshold, a dynamic time-limited adjustment mechanism is activated, and the ventilation period is automatically extended or shortened based on real-time temperature difference data. The humidity correction command is configured with a spatial control strategy, wherein the surface layer of the grain and oil pile adopts a high-temperature rapid dehumidification mode, the middle layer of the grain pile adopts a medium-temperature constant humidity control mode, and the bottom layer of the grain pile maintains a natural humidity balance mode. When a rising humid and hot airflow is detected, the reverse stratified control logic is activated, the bottom layer starts a forced dehumidification mode while the surface layer switches to a humidity maintenance mode. The execution priority of the gas replacement command is set to the highest level. When both temperature control and gas replacement requirements exist simultaneously, the gas replacement operation receives priority in equipment resource allocation.

[0187] This application further proposes that after completing the environmental control operation, the dynamic environmental parameter set is re-collected; a quality maintenance index is constructed based on the change in fatty acid value and the increase in peroxide value; when the quality maintenance index is lower than the preset qualified threshold, the control process including the following steps is re-executed: the dynamic environmental parameter set is acquired again and a new environmental control instruction sequence is generated; the updated temperature equalization instruction, humidity correction instruction and gas replacement instruction are executed; if the quality deterioration warning signal is triggered again, a new emergency control instruction is generated and executed.

[0188] The process involves re-collecting dynamic environmental parameters, including grain pile temperature distribution, surface moisture content, and gas component concentration, to ensure consistency between the assessment data and the actual state after the control operations. A quality maintenance index is constructed using a linear combination of changes in fatty acid values ​​and increases in peroxide values, with a comprehensive score calculated through preset weighting coefficients. Preset qualification thresholds are dynamically adjusted based on the characteristics of different grain and oil categories; for example, the threshold for cereals is higher than that for oilseeds. When the index falls below the threshold, iterative execution of the control process is triggered. When generating a new sequence of environmental control instructions, differentiated strategies are prioritized, such as using a higher-intensity ventilation mode for areas with temperature imbalances. If an early warning signal is triggered again, emergency control instructions take precedence over regular instructions; for example, rapid cooling takes precedence over stepped cooling.

[0189] Specifically, after the environmental control operation is completed, the temperature, humidity, and gas parameters of the storage space are re-acquired through the grain condition monitoring unit to ensure data coverage of all three-dimensional monitoring areas of the grain pile. The quality maintenance index is calculated based on the weighted sum of the rate of change of fatty acid value and the acceleration of peroxide value, with the weighting coefficients retrieved from the grain storage strategy database according to the characteristics of grain and oil categories. When the index calculation result is lower than the preset threshold, it is determined that the current control effect has not met the standard, and the control process needs to be re-executed. When generating a new environmental control command sequence, the ventilation path in the temperature equalization command is optimized by combining the latest collected dynamic environmental parameter set, such as switching the ventilation mode for migrating temperature imbalance areas. The humidity correction command adjusts the dehumidification intensity gradient according to the re-detected surface moisture content parameter, such as activating the reverse stratified control logic when a rising humid and hot airflow is detected. The execution priority of the gas replacement command is raised to the highest level, such as immediately initiating high-frequency gas replacement when the oxygen concentration exceeds the standard again. If the quality detection unit triggers an early warning signal again during the re-execution process, the emergency control command is generated based on the real-time deterioration kinetic model, such as switching to the gradient descent mode when the rate of change of fatty acid value continues to rise. Through multiple iterations of adjustment and evaluation, until the quality maintenance index reaches the qualified threshold, the continuous and stable control of grain and oil quality is achieved.

[0190] As a preferred embodiment, the specific implementation of this application is as follows: After completing the operations of regulating the temperature gradient of the grain pile through the ventilation system, adjusting the moisture content through the dehumidification device, and maintaining the gas composition through the controlled atmosphere equipment, the temperature distribution parameters, surface moisture content parameters, and gas composition concentration parameters of each monitoring point in the storage space are re-collected through a distributed sensor array. The change in fatty acid values ​​of the grain and oil samples is obtained based on a near-infrared spectroscopy analysis device, and the increase in peroxide value is detected using an electrochemical sensor. Both data are input into a preset weighted calculation model to generate a quality maintenance index. When this index is lower than a preset threshold of 0.85, the control unit triggers a restart mechanism for the control process: First, the updated abnormal temperature data of the middle layer of the grain pile and the surface humidity distribution map are obtained again through a wireless sensor network, generating a control sequence including a deep slow ventilation command and a surface high-temperature dehumidification command; then, the controlled atmosphere equipment is operated to reduce the oxygen concentration from 19% to 16% and increase the carbon dioxide concentration to 12%; if the near-infrared spectroscopy detects that the rate of change in fatty acid values ​​still exceeds 0.3% / h, the emergency control module is activated to generate a nitrogen injection command and a rapid cooling command.

[0191] Through the above technical solution, this application achieves closed-loop verification and dynamic optimization of the control effect on grain and oil storage environment. By constructing a multi-dimensional quality maintenance evaluation system, it can accurately identify areas of control failure and automatically trigger supplementary control measures based on real-time data. This mechanism effectively solves the problem of continuous quality deterioration caused by incomplete single control in traditional methods, and shows significant advantages in maintaining the chemical stability of grains and oils. In particular, when dealing with the chain reaction of deterioration caused by sudden changes in the storage environment, it can quickly converge to a safe threshold range through multiple rounds of control iterations.

[0192] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A grain and oil storage method based on environmental condition transformation, characterized in that, The method comprises the following steps: In response to the initial environmental parameter set of the storage space being acquired by the grain condition monitoring unit, the category characteristic identifier and the quality deterioration threshold of the target grain and oil are analyzed; Based on the category characteristic identifier, the matched environmental regulation rule set is called from the grain storage strategy library, and the environmental regulation rule set includes temperature stratification control strategy, humidity response strategy and dynamic gas regulation matrix; Real-time collection of dynamic environmental parameter set of storage space, including grain pile temperature distribution parameter, grain and oil surface moisture content parameter and gas component concentration parameter; According to the deviation relationship between the quality deterioration threshold and the dynamic environmental parameter set, the environmental regulation instruction sequence is generated; The environmental regulation instruction sequence is sent to the grain storage execution system for execution: According to the temperature equalization instruction in the sequence, the ventilation system is started to regulate the temperature gradient of the grain pile; According to the humidity correction instruction in the sequence, the dehumidification device is controlled to adjust the moisture content of the grain and oil; According to the gas replacement instruction in the sequence, the gas regulation equipment is operated to maintain the target gas component; In response to the quality deterioration early warning signal triggered by the quality detection unit, the emergency regulation instruction is generated combined with the grain and oil deterioration dynamics model; The emergency regulation instruction is dynamically integrated into the environmental regulation instruction sequence.

2. The method of claim 1, wherein: The initial environmental parameter set includes the initial concentration of mycotoxin and the base number of insect infestation; Before collecting the dynamic environmental parameter set, the following operations are performed: When the initial concentration of mycotoxin exceeds the preset safety threshold, a toxin accumulation warning is generated; When the base number of insect infestation exceeds the preset insect infestation warning line, a biological infestation warning is generated; When the toxin accumulation warning and the biological infestation warning exist at the same time, the fumigation intervention unit of the grain storage execution system is activated; The generation of the environmental regulation instruction sequence includes: In response to the activation of the fumigation intervention unit, the fumigant release instruction is embedded in the environmental regulation instruction sequence.

3. The method of claim 2, wherein, The generation of the environmental regulation instruction sequence includes the following steps: Performing thermodynamic anomaly analysis on the grain pile temperature distribution parameter, outputting the position information of the temperature imbalance area; Performing dew risk judgment on the grain and oil surface moisture content parameter, outputting the humidity risk level representing the risk degree; When there is a temperature imbalance area or the humidity risk level reaches a preset risk level, the generation of the environmental regulation instruction sequence is triggered.

4. The method of claim 3, wherein, The thermodynamic anomaly analysis includes: Divide the grain pile into multiple vertical monitoring areas; Calculate the temperature variation coefficient of each monitoring area; Mark the area with temperature variation coefficient exceeding the preset variation threshold as the temperature imbalance area; Based on the three-dimensional distribution coordinates of the temperature imbalance area, a topological structure diagram guiding the ventilation path is generated.

5. The method of claim 4, wherein, The generation of the environmental regulation instruction sequence includes: Determine the stratified ventilation strategy according to the depth attribute of the temperature imbalance area, wherein: Low-intensity slow-velocity ventilation mode is adopted for deep area; Medium-intensity balanced ventilation mode is adopted for middle layer area; High-intensity directional ventilation mode is adopted for surface layer area; When the temperature imbalance area is detected to migrate in the vertical direction, the ventilation mode is automatically switched; Determine the dehumidification intensity gradient according to the humidity risk level, wherein: Intermittent dehumidification mode corresponds to low risk level; Continuous dehumidification mode corresponds to medium risk level; Combined dehumidification mode corresponds to high risk level; When the humidity risk level keeps rising for two consecutive monitoring periods, the cross-level mode switching is started; The gas replacement frequency is calculated based on the gas component concentration parameters, wherein: The gas replacement frequency is increased when the oxygen concentration is higher than the preset oxygen enrichment threshold; Supplementary carbon dioxide gas is injected when the carbon dioxide concentration is lower than the preset insect prevention threshold; The fumigation intensity is determined according to the insect density base, wherein: The low-density base matches the preventive fumigation dose; The medium-density base matches the control fumigation dose; The high-density base matches the eradication fumigation dose; When the insect density base increases by more than the preset mutation threshold within 24 hours, the fumigation intensity level is immediately increased; The layered ventilation strategy, the dehumidification intensity gradient, the gas replacement frequency and the fumigation intensity are packaged into an environmental control instruction sequence.

6. The method of claim 5, wherein, Determining the gas replacement frequency further includes: Real-time monitoring of the spatial distribution state of the gas components in the grain pile; When the gas concentration distribution unevenness exceeds the preset uniformity threshold, the gas circulation homogenization program is started; The gas circulation homogenization program is executed in turn: The bottom gas injection device is turned on to form a positive air flow; The top gas suction device is started synchronously to establish a negative pressure gradient; When the homogenization efficiency is lower than the preset standard, switch to the pulse air flow enhancement mode; The above devices are continuously operated until the gas concentration distribution reaches the uniformity standard.

7. The method of claim 3, wherein, The response quality deterioration early warning signal includes: The change rate of the grain oil fatty acid value is continuously monitored by a spectral analysis device; When the change rate of the fatty acid value exceeds the preset oxidation rate threshold, the quality deterioration early warning signal is triggered; The grain oil peroxide value acceleration data is synchronously acquired to verify the credibility of the deterioration early warning level.

8. The method of claim 7, wherein, Generating emergency control instructions includes: Formulating a temperature suppression strategy according to the change rate of the fatty acid value, wherein: Low change rate corresponds to stepwise cooling mode; Medium change rate corresponds to linear cooling mode; High change rate corresponds to emergency cooling mode; When there is a risk of local dew during the cooling process, switch to gradient slow cooling mode; The critical moisture content boundary is dynamically calculated based on the grain oil deterioration kinetics model, which is determined by real-time temperature parameters and relative humidity parameters; When the detected moisture content approaches the critical moisture content boundary, a composite dehumidification instruction is generated, which includes: The thermal dehumidification device is enabled during the daytime operation phase; Switch to the adsorption dehumidification device during the nighttime operation phase; When the environmental humidity suddenly rises by more than the preset mutation threshold, start the parallel dehumidification mode of the two devices.

9. The method of claim 8, wherein, Dynamic integration of emergency control instructions includes: Add time period constraints to the temperature equalization instruction, wherein: In high temperature seasons, ventilation operation is limited to nighttime; In low temperature seasons, ventilation operation is allowed at all times; When the diurnal temperature difference exceeds the preset fluctuation threshold, enable the dynamic time period adjustment mechanism; Configure the spatial control strategy in the humidity correction instruction, wherein: The surface layer of the grain oil adopts high-temperature rapid dehumidification mode; The middle layer of the grain pile adopts medium-temperature constant humidity control mode; The bottom layer of the grain pile maintains natural humidity balance mode; When the wet and hot air flow is detected, activate the reverse layered control logic; The execution priority of the gas replacement instruction is raised to the highest level.

10. The method of claim 1, wherein, It also includes a control efficiency evaluation stage: After completing the environmental control operation, the dynamic environmental parameter set is re-collected; An index of quality maintenance degree is constructed based on the change amount of the fatty acid value and the increment of the peroxide value; When the index of quality maintenance degree is lower than a preset qualified threshold, a regulation process including the following steps is re-executed: The dynamic environmental parameter set is acquired again and a new environmental regulation instruction sequence is generated; The updated temperature equalization instruction, humidity correction instruction and gas replacement instruction are executed; If the quality deterioration early warning signal is triggered again, a new emergency regulation instruction is generated and executed.

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