A method and system for controlling the ventilation of a granary

Abstract

The present invention relates to the technical field of grain storage ventilation control, and particularly relates to a method and system for controlling the ventilation of a granary. The method includes the following steps: identifying the type of grain, and determining the optimal storage temperature and optimal storage humidity of the grain pile based on the type of grain; obtaining the actual temperature and actual humidity of the grain pile, obtaining a temperature difference value according to the optimal storage temperature and the actual temperature, and obtaining a humidity difference value according to the optimal storage humidity and the actual humidity; constructing an objective function for adjusting the control parameters of the ventilation equipment; constructing a control parameter matrix with the control parameters of the temperature control module and the humidity control module, and forming a population solution with the control parameter matrix as an individual solution; using the objective function for adjusting the control parameters of the ventilation equipment and the population solution for iterative solution to obtain the optimal control parameters of the ventilation equipment; and completing the ventilation control of the granary based on the optimal control parameters of the ventilation equipment, the temperature difference value, and the humidity difference value. The present invention solves the problem of intelligently controlling ventilation equipment according to grain storage conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of grain storage ventilation control, and particularly relates to a method and a system for controlling the ventilation of a granary. Background Art

[0002] Grain storage is an ecological process in which various abiotic and biotic factors interact with each other. The abiotic factors mainly include living environments such as temperature, humidity, light, wind, and air, which directly affect the distribution, growth, development, reproduction, and behavior of all individuals in the entire biological community of the ecosystem; the biotic factors mainly include the interactions between grains and microorganisms and between microorganisms and other organisms. The activities and interactions of microorganisms affect and change the quality of stored grains; among all factors, grain temperature and moisture are the most critical factors affecting the safety of stored grains, and they are closely related to grain quality, dry matter loss, and the growth of insects and molds. All organisms that cause grain loss, such as bacteria, insects, molds, mites, etc., their growth is affected by the temperature and humidity of their growth environment; within a certain temperature range, the higher the environmental humidity, the more vigorous the metabolism of stored-grain pests, the faster the reproduction rate, and the more serious the harm to grains. This is the general law of the interaction between environmental temperature and humidity affecting stored-grain pests, and it is also the main reason why grain storage requires low temperature and dryness. The key technology for regulating the temperature and moisture of stored grains is ventilation technology. For the grains piled up in a granary, there are certain gaps between the grain particles. As a carrier of heat and mass transfer, the flowing air, when passing through the gaps between the grain particles, undergoes convective heat and mass transfer with the grains, carrying out the excess heat and moisture in the grain pile. According to the state of the grains, by ventilating the stored grains, the temperature and moisture of the grains can be adjusted to ensure that they are within the safe storage range.

[0003] Traditional ventilation control methods often rely on manual experience and have problems of untimely and inaccurate regulation. In order to effectively control the temperature and humidity conditions in the granary, prevent grains from getting damp, mildewing, and deteriorating, reduce labor costs, and improve work efficiency, it is urgent to intelligently control the ventilation of the granary. Summary of the Invention

[0004] In view of the deficiencies of the existing methods and the requirements of practical applications, on the one hand, the present invention provides a method for controlling the ventilation of a granary, including the following steps:

[0005] Identify the type of grain, and based on the type of grain, determine the optimal storage temperature and optimal storage humidity of the grain pile; obtain the actual temperature and actual humidity of the grain pile, obtain the temperature difference value according to the optimal storage temperature and the actual temperature, and obtain the humidity difference value according to the optimal storage humidity and the actual humidity; construct an objective function for adjusting the control parameters of the ventilation equipment; construct a control parameter matrix with the control parameters of the temperature control module and the humidity control module, and use the control parameter matrix as an individual solution to form a population solution; use the objective function for adjusting the control parameters of the ventilation equipment and the population solution to perform iterative solution to obtain the optimal control parameters of the ventilation equipment; based on the optimal control parameters of the ventilation equipment, the temperature difference value and the humidity difference value, complete the ventilation control of the granary.

[0006] The present invention obtains the control parameters of the ventilation equipment through iterative optimization, and then adjusts the output of the ventilation equipment based on the optimal storage temperature and humidity of the grain and the actual storage temperature and humidity, so as to quickly and accurately make the granary reach the optimal storage conditions in a timely manner, complete the intelligent real-time control of the ventilation equipment, reduce the labor cost, solve the problems of untimely and inaccurate regulation in manual control, avoid the losses caused by ineffective ventilation or even excessive ventilation, and achieve green and energy-saving grain storage.

[0007] Optionally, the constructed objective function for adjusting the control parameters of the ventilation equipment satisfies the following formula:

[0008] ,

[0009] where, represents the objective function for adjusting the control parameters of the ventilation equipment, represents the temperature control weight coefficient, represents the temperature of the grain pile after simulated ventilation, represents the optimal storage temperature of the grain pile, represents the humidity control weight coefficient, represents the humidity of the grain pile after simulated ventilation, represents the optimal storage humidity of the grain pile. The objective function constructed by the present invention can effectively evaluate the adjustment of the control parameters of the ventilation equipment, and further ensure the control accuracy of the present invention.

[0010] Optionally, the step of using the objective function for adjusting the control parameters of the ventilation equipment and the population solution to perform iterative solution to obtain the optimal control parameters of the ventilation equipment includes the following steps:

[0011] In the early stage of iterative solution, perform the first iterative solution algorithm or the second iterative solution algorithm on the population solution; in the later stage of iterative solution, perform the third iterative solution algorithm on the population solution. The present invention performs different adjustment strategies in the early and later stages of iterative solution, which is beneficial to improving the optimization speed and optimization quality of the final solution.

[0012] Optionally, perform a first iterative solution algorithm on the population solution, which satisfies the following formula:

[0013] , where represents the solution after performing the first iterative solution algorithm at the -th iteration of the -th individual solution, represents a random number obeying Levy flight, represents the -th individual solution at the -th iteration, represents a random number between represents the -th iteration, and

[0014] Optionally, perform a second iterative solution algorithm on the population solution, which satisfies the following formula:

[0015] , where represents the solution after performing the second iterative solution algorithm at the -th iteration of the -th individual solution, represents a random number obeying the Cauchy standard distribution, represents the -th individual solution at the -th iteration, represents a random number between represents the -th iteration, and

[0016] Optionally, perform a third iterative solution algorithm on the population solution, which satisfies the following formula:

[0017] , where represents the solution after performing the third iterative solution algorithm at the -th iteration of the -th individual solution, represents the maximum number of iterations, represents the -th individual solution at the -th iteration, represents the local search regulation factor, represents the -th individual solution in the previous The optimal solution at the

[0018] Optionally, the iterative solution of the objective function and the population solution by using the ventilation equipment control parameters to obtain the optimal ventilation equipment control parameters further includes perturbing the population solution according to a first probability during each iteration. By perturbing and mutating some solutions, the present invention further improves the quality of the final solution obtained.

[0019] Optionally, the first probability satisfies the following formula:

[0020] , where represents the first probability that the -th individual solution is perturbed, represents the perturbation probability threshold, represents the number of individual solutions in one iteration process, represents the maximum number of iterations.

[0021] Optionally, the perturbation of the population solution satisfies the following formula:

[0022] , where represents the solution of the -th individual solution after being perturbed, represents a random number between, represents a random number between, represents the upper boundary, represents the lower boundary, represents the -th individual solution at the -th iteration, represents the maximum number of iterations. By setting the first probability and the perturbation rule, the present invention perturbs the individual solutions with lower rankings with a high probability in the initial stage of iteration, improves the diversity of solutions, and further improves the control efficiency of the present invention.

[0023] In a second aspect, to efficiently execute a grain bin ventilation control method provided by the present invention, the present invention further provides a grain bin ventilation control system, including a processor, an input device, an output device, and a memory. The processor, the input device, the output device, and the memory are interconnected. Among them, the memory is used to store a computer program, the computer program contains program instructions, and the processor is configured to call the program instructions to execute a grain bin ventilation control method as described in the first aspect of the present invention. The grain bin ventilation control system of the present invention has a compact structure and stable performance, and can stably execute the grain bin ventilation control method provided by the present invention, further improving the overall applicability and practical application ability of the present invention.

[0024] Beneficial effects: The present invention obtains the control parameters of the ventilation equipment through iterative optimization, and then adjusts the output of the ventilation equipment based on the optimal storage temperature and humidity of the grain and the actual storage temperature and humidity, so as to quickly and accurately make the grain bin reach the optimal storage conditions in a timely manner, complete the intelligent real-time control of the ventilation equipment, reduce the labor cost, solve the problems of untimely and inaccurate regulation in manual control, avoid the losses caused by ineffective ventilation or even excessive ventilation, and realize green and energy-saving grain storage. Description of the Drawings

[0025] Figure 1 It is a flowchart of a grain bin ventilation control method provided by an embodiment of the present invention;

[0026] Figure 2 It is a framework diagram of a grain bin ventilation control system provided by an embodiment of the present invention;

[0027] Figure 3 It is a schematic structural diagram of a grain bin ventilation control device provided by an embodiment of the present invention. Detailed Embodiments

[0028] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described here are only for illustrative purposes and are not used to limit the present invention. In the following description, in order to provide a thorough understanding of the present invention, a large number of specific details are set forth. However, it is obvious to those of ordinary skill in the art that the present invention does not have to employ these specific details. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the present invention.

[0029] Throughout the specification, references to "one embodiment", "an embodiment", "one example" or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Thus, the phrases "in one embodiment", "in an embodiment", "one example" or "an example" appearing throughout the specification do not necessarily all refer to the same embodiment or example. In addition, specific features, structures, or characteristics may be combined in any suitable combination and / or sub-combination in one or more embodiments or examples. Furthermore, those of ordinary skill in the art should understand that the diagrams provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0030] Please refer to Figure 1 , in order to effectively control the temperature and humidity conditions in the granary, prevent grain from getting damp, moldy, or deteriorating, reduce labor costs, improve work efficiency, and solve the problems of untimely and inaccurate regulation in manual control, the present invention provides a method for controlling granary ventilation, as Figure 1 shown, the method includes the following steps:

[0031] S1. Identify the type of grain, and based on the type of grain, determine the optimal storage temperature and optimal storage humidity of the grain pile.

[0032] In an embodiment, the type of grain is identified by a machine recognition method, and based on the identified type of grain, in combination with relevant specifications for grain storage, the optimal storage temperature and optimal storage humidity of the grain pile are determined.

[0033] Grains mainly include wheat, beans, rice, coarse grains, etc. Specific types are such as wheat, barley, highland barley, soybeans, mung beans, japonica rice, indica rice, glutinous rice, corn, sorghum, buckwheat, etc. Each type of grain has its unique physical and chemical properties, and these properties determine their optimal conditions during storage.

[0034] Optimal storage temperature for wheat (such as wheat, barley): Usually stored below 15 - 20 °C to avoid enhanced respiration and quality degradation caused by high temperature. Under low temperature conditions, the respiration of wheat weakens, which is beneficial to maintaining its nutritional value and taste; Optimal storage humidity: The humidity should be controlled between 60% - 70% to prevent quality problems caused by excessive drying or high humidity of the grain.

[0035] Optimal storage temperature for beans (such as soybeans, mung beans): Similar to wheat, beans should also be stored below 15 - 20 °C to maintain their quality and extend the shelf life; Optimal storage humidity: The humidity should also be controlled between 60% - 70% to ensure the dryness of beans and prevent mildew.

[0036] Optimal storage temperature for rice (such as japonica rice, indica rice): For rice, the safety limit of the temperature of the grain pile should not exceed 15°C, and ideally it should be maintained between 10 - 15°C. This temperature range helps to inhibit the growth of mold and maintain the quality of rice; Optimal storage humidity: The humidity should be controlled between 60% - 70% to prevent the rice from drying out or getting damp.

[0037] Optimal storage temperature for coarse grains (such as corn, sorghum): The storage temperature of coarse grains should also be below 15 - 20°C to ensure their quality and extend the shelf life; Optimal storage humidity: Humidity control is equally important, generally it should be maintained between 60% - 75%, depending on the moisture content of the grains and the storage environment.

[0038] Different types of grains require different temperature and humidity conditions during storage. Generally speaking, the optimal storage temperature for most grains should be below 15 - 20°C, and the humidity should be controlled between 60% - 75%. The specific humidity range may vary depending on the type of grain and its moisture content. These conditions help to inhibit the growth of mold, reduce respiration, and maintain the nutritional value and taste of the grains.

[0039] S2. Obtain the actual temperature and actual humidity of the grain pile, obtain the temperature difference value according to the optimal storage temperature and the actual temperature, and obtain the humidity difference value according to the optimal storage humidity and the actual humidity.

[0040] Specifically, through a temperature sensor and a humidity sensor, obtain the actual temperature and actual humidity of the grain pile, and then obtain the temperature difference value according to the optimal storage temperature and the actual temperature, and obtain the humidity difference value according to the optimal storage humidity and the actual humidity.

[0041] S3. Construct an objective function for adjusting the control parameters of the ventilation equipment.

[0042] In the embodiment, the constructed objective function for adjusting the control parameters of the ventilation equipment satisfies the following formula:

[0043] ,

[0044] where, represents the objective function for adjusting the control parameters of the ventilation equipment, represents the temperature control weight coefficient, represents the temperature of the grain pile after simulated ventilation, represents the optimal storage temperature of the grain pile, represents the humidity control weight coefficient, represents the humidity of the grain pile after simulated ventilation, represents the optimal storage humidity of the grain pile.

[0045] Furthermore, the temperature control weight coefficient and the humidity control weight coefficient are adjusted according to the environmental parameters of the granary, and the environmental parameters include indoor air temperature, indoor air humidity, outdoor air temperature, and outdoor air humidity. , , represents the temperature difference coefficient, , represents the outdoor air temperature, represents the indoor air temperature, represents the humidity difference coefficient, , represents the outdoor air humidity, represents the indoor air humidity.

[0046] Furthermore, the temperature and humidity of the grain pile after simulated ventilation can be completed by combining the grain moisture balance equation, the air humidity balance equation, the grain heat balance equation, and the air heat balance equation between grain particles with Matlab simulation software.

[0047] S4. Construct a control parameter matrix with the control parameters of the temperature control module and the humidity control module, and use the control parameter matrix as an individual solution to form a population solution.

[0048] Specifically, both the temperature control module and the humidity control module are PID control modules. The PID control module is a crucial part of the industrial control system. It combines three control algorithms: proportional, integral, and derivative to achieve precise control of the controlled object.

[0049] The PID control module maintains the state of the controlled object near the set value by continuously adjusting the output of the controller, achieving stable and precise automatic control. Its basic principle is to adjust the output signal according to the difference, that is, the error, between the current state of the controlled object and the set value, so that the difference approaches zero; the PID controller calculates the output signal according to the weight combination of the proportional, integral, and derivative parts, thereby achieving precise control of the controlled object.

[0050] Proportional link (P): According to the magnitude of the error signal, it amplifies it by a certain proportion to generate a corresponding control signal. Proportional control can quickly respond to the system error and make the system quickly approach the set value, but it may cause overshoot and oscillation.

[0051] Integral link (I): Integrates the error signal to obtain the error accumulation value and converts it into a control signal. Integral control can eliminate the steady-state error of the system and ensure that the system finally stabilizes near the set value, but it may also cause overshoot and oscillation.

[0052] Derivative link (D): Detects the change in the error signal to make corrections before a large error occurs in the system. Derivative control can predict the future state change trend of the system, thereby reducing overshoot and improving the stability of the system, but it may also increase the sensitivity of the system to noise.

[0053] The PID control module can achieve stable control. The PID controller can adjust the control signal in real time according to the system error, making the output of the controlled object gradually approach the desired output to achieve stable control.

[0054] It can also eliminate the steady-state error. Through the action of the integral link, the PID controller can continuously integrate the system error, thereby gradually eliminating the steady-state error of the system and improving the control accuracy and performance of the system.

[0055] And improve the system sensitivity. The role of the derivative link enables the PID controller to make corrections before a large error occurs in the system, thereby improving the response speed and sensitivity of the system.

[0056] Furthermore, since humidity and temperature are also coupled, the constructed control parameter matrix satisfies:

[0057] , represents the control parameter matrix, represents the proportional coefficient of the temperature control PID module, represents the integral coefficient of the temperature control PID module, represents the derivative coefficient of the temperature control PID module, represents the proportional coefficient of the humidity control PID module, represents the integral coefficient of the humidity control PID module, represents the derivative coefficient of the humidity control PID module, represents the humidity decoupling coefficient of the temperature control PID module, represents the temperature decoupling coefficient of the humidity control PID module.

[0058] Furthermore, according to the corresponding specifications and experience, set the value range of the control parameters to obtain multiple control parameter matrices, and then form a population solution.

[0059] S5. Use the ventilation equipment control parameter adjustment objective function and the population solution to perform iterative solution to obtain the optimal ventilation equipment control parameters.

[0060] Specifically, step S5 of using the ventilation equipment control parameter adjustment objective function and the population solution to perform iterative solution to obtain the optimal ventilation equipment control parameters includes the following steps:

[0061] S51. In the early stage of iterative solution, execute the first iterative solution algorithm or the second iterative solution algorithm on the population solution.

[0062] Specifically, when executing the first iterative solution algorithm on the population solution, the following formula is satisfied:

[0063] , where represents the solution after executing the first iterative solution algorithm at the -th iteration of the -th individual solution, represents a random number obeying Lévy flight, represents the solution at the -th iteration of the -th individual solution, represents a random number between and represents the average value of the solutions at the

[0064] Further, when executing the second iterative solution algorithm on the population solution, the following formula is satisfied:

[0065] , where represents the solution after executing the second iterative solution algorithm at the -th iteration of the -th individual solution, represents a random number obeying the Cauchy standard distribution, represents the solution at the -th iteration of the -th individual solution, represents a random number between and represents the optimal value of the population solution at the

[0066] In the embodiment, the early stage of iterative solution is divided based on half of the maximum number of iterations; executing the first iterative solution algorithm or the second iterative solution algorithm on the population solution includes randomly assigning a tag value between to each individual solution. If the tag value belongs to (-1, 0], the corresponding individual solution will execute the first iterative solution algorithm in the next iteration. If the tag value belongs to (0, 1), the corresponding individual solution will execute the second iterative solution algorithm in the next iteration. In some other embodiments, other rules can also be set.

[0067] S52. In the later stage of iterative solution, execute the third iterative solution algorithm on the population solution.

[0068] Specifically, when executing the third iterative solution algorithm on the population solution, the following formula is satisfied:

[0069] , where represents the solution after the third iterative solution algorithm is executed at the -th individual solution in the -th iteration, represents the maximum number of iterations, represents the -th individual solution at the -th iteration, represents the local search control factor, represents the -th individual solution's optimal solution in the previous iterations.

[0070] Furthermore, the iterative solution of the objective function and the population solution using the ventilation equipment control parameters described in step S5 to obtain the optimal ventilation equipment control parameters further includes disturbing the population solution according to the first probability during each iteration.

[0071] The first probability satisfies the following formula:

[0072] , where represents the first probability of the -th individual solution being disturbed, represents the disturbance probability threshold, represents the number of individual solutions in one iteration process, represents the maximum number of iterations. represents that the -th individual solution is not disturbed, represents the -th individual solution being disturbed.

[0073] Furthermore, disturbing the population solution satisfies the following formula:

[0074] ,

[0075] where represents the solution of the -th individual solution after being disturbed, represents a random number between and , represents the upper boundary, represents the lower boundary, represents the -th individual solution at the -th iteration, represents the maximum number of iterations.

[0076] S6. Based on the optimal ventilation equipment control parameters, the temperature difference value, and the humidity difference value, complete the grain bin ventilation control.

[0077] Specifically, based on the optimal ventilation equipment control parameters, adjust the ventilation equipment according to the temperature difference value and the humidity difference value until the temperature difference value and the humidity difference value are less than the threshold value. At this time, the grain bin is in the optimal storage state; when the temperature difference value and the humidity difference value exceed the threshold value, start the ventilation equipment again for adjustment to complete the intelligent control of the grain bin ventilation equipment.

[0078] Please refer to Figure 2 , in the embodiment, to efficiently execute a grain bin ventilation control method provided by the present invention, the present invention further provides a grain bin ventilation control system, including: an input device, an output device, a processor, and a memory. The input device, the output device, the processor, and the memory are interconnected. The memory contains program instructions for the steps of the grain bin ventilation control method. The grain bin ventilation control system of the present invention has a compact structure and stable performance, and can stably execute the grain bin ventilation control method of the present invention, further improving the overall applicability and practical application ability of the present invention.

[0079] In the embodiment, the so-called processor may be a central processing unit (CPU), and this processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or this processor may also be any conventional processor, etc. The input device may be used to obtain data information. The output device may be used to output the result obtained from the program instructions included in the computer program stored in the memory provided by the present invention. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory may also include a non-volatile random access memory.

[0080] In another optional embodiment, please refer to Figure 3 , to efficiently execute a grain bin ventilation control method provided by the present invention, this embodiment further provides a grain bin ventilation control device, as Figure 3 shown, including:

[0081] A memory 10 for storing a computer program; a processor 20 for executing the computer program to implement the above-mentioned grain bin ventilation control method. The memory 10, the processor 20, a communication interface 31, and a communication bus 32. The memory 10, the processor 20, and the communication interface 31 all complete communication with each other through the communication bus 32.

[0082] In an embodiment, the memory 10 is used to store one or more program instructions. The memory 10 may store program instructions for implementing the following functions:

[0083] Identify the type of grain, and based on the type of grain, determine the optimal storage temperature and optimal storage humidity of the grain pile; obtain the actual temperature and actual humidity of the grain pile, obtain a temperature difference value according to the optimal storage temperature and the actual temperature, and obtain a humidity difference value according to the optimal storage humidity and the actual humidity; construct an objective function for adjusting the control parameters of the ventilation equipment; construct a control parameter matrix with the control parameters of the temperature control module and the humidity control module, and form a population solution with the control parameter matrix as an individual solution; use the objective function for adjusting the control parameters of the ventilation equipment and the population solution to perform iterative solution to obtain the optimal ventilation equipment control parameters; based on the optimal ventilation equipment control parameters, the temperature difference value, and the humidity difference value, complete the ventilation control of the grain bin.

[0084] In a possible implementation, the memory 10 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system and application programs required for at least one function, etc.; the data storage area may store data created during use. In addition, the memory 10 may include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory may also include NVRAM. The memory stores an operating system and operation instructions, executable modules, or data structures, or subsets thereof, or extended sets thereof. Among them, the operation instructions may include various operation instructions for implementing various operations. The operating system may include various system programs for implementing various basic tasks and processing hardware-based tasks.

[0085] The processor 20 may be a central processing unit (CPU), an application-specific integrated circuit, a digital signal processor, a field programmable gate array, or other programmable logic devices. The processor 20 may be a microprocessor or any conventional processor, etc. The processor 20 may call the program stored in the memory 10. The communication interface 31 may be an interface of a communication module for connecting to other devices or systems.

[0086] Of course, it should be noted that Figure 3The structure shown does not constitute a limitation on the grain bin ventilation control equipment in this embodiment. In actual applications, the grain bin ventilation control equipment may include more or fewer components than Figure 3 those shown, or combine certain components.

[0087] The embodiment also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned grain bin ventilation control method are implemented.

[0088] The storage medium may include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0089] In summary, the present invention obtains the control parameters of the ventilation equipment through iterative optimization, and then adjusts the output of the ventilation equipment based on the optimal storage temperature and humidity of the grain and the actual storage temperature and humidity, so as to quickly and accurately make the grain bin reach the optimal storage conditions in a timely manner, complete the intelligent real-time control of the ventilation equipment, reduce the labor cost, solve the problems of untimely and inaccurate regulation in manual control, avoid the losses caused by ineffective ventilation or even excessive ventilation, and achieve green and energy-saving grain storage.

[0090] Therefore, the present invention effectively overcomes various disadvantages in the prior art and has high industrial utilization value.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present invention, and they should all be covered by the scope described in the present invention.

Claims

1. A method for controlling ventilation in a granary, characterized in that: The granary ventilation control method comprises the following steps: Identify the type of grain, and determine the optimal storage temperature and optimal storage humidity of the grain pile based on the type of grain; Acquire the actual temperature and actual humidity of the grain pile, obtain a temperature difference value according to the optimal storage temperature and the actual temperature, and obtain a humidity difference value according to the optimal storage humidity and the actual humidity; Construct the objective function of ventilation equipment control parameter adjustment; Constructing a control parameter matrix using the control parameters of the temperature control module and the humidity control module, and using the control parameter matrix as an individual solution to form a population solution; Using the ventilation equipment control parameter to adjust the objective function and the population solution to perform iterative solution to obtain the optimal ventilation equipment control parameter; Based on the optimal ventilation equipment control parameters, the temperature difference value and the humidity difference value, the granary ventilation control is completed; The constructed ventilation equipment control parameter adjustment objective function satisfies the following formula: ， in, represents the objective function for adjusting the ventilation equipment control parameters, represents the temperature control weight coefficient, represents the temperature of the grain pile after simulated ventilation, Indicates the optimal storage temperature of the grain pile, represents the humidity control weight coefficient, It represents the humidity of the grain pile after simulated ventilation. Indicates the optimal storage humidity of the grain pile.

2. A grain silo ventilation control method according to claim 1, characterized in that: The method of using the ventilation equipment control parameter adjustment objective function and the population solution to iteratively solve and obtain the optimal ventilation equipment control parameter comprises the following steps: In the early stage of iterative solution, the first iterative solution algorithm or the second iterative solution algorithm is executed on the population solution; At the later stage of iterative solution, a third iterative solution algorithm is executed on the population solution.

3. A granary ventilation control method according to claim 2, characterized in that: The first iterative solution algorithm is executed on the population solution to satisfy the following formula: ， in, Indicates Individual solution The solution after executing the first iteration solution algorithm is represents the random number subject to Levy flight, Indicates Individual solution The solution at the iteration is express A random number between Indicates The average of the solutions from iterations.

4. A grain silo ventilation control method according to claim 2, characterized in that: The second iterative solution algorithm is executed on the population solution to satisfy the following formula: ， in, Indicates Individual solution The solution after executing the second iteration solution algorithm is represents random numbers that follow the Cauchy standard distribution, Indicates Individual solution The solution at the iteration is express A random number between Indicates The optimal value of the population solution of iterations.

5. A grain silo ventilation control method according to claim 2, characterized in that: The third iterative solution algorithm is executed on the population solution to satisfy the following formula: ， in, Indicates Individual solution The solution after executing the third iteration solution algorithm is represents the maximum number of iterations, Indicates Individual solution The solution at the iteration is represents the local search regulatory factor, Indicates Before individual solution The optimal solution at the iteration.

6. A grain silo ventilation control method according to claim 1, characterized in that: The method of using the ventilation equipment control parameter to adjust the objective function and the population solution to iteratively solve the optimal ventilation equipment control parameter also includes perturbing the population solution according to a first probability during each iteration.

7. A grain silo ventilation control method according to claim 6, characterized in that: The first probability satisfies the following formula: ， in, Indicates The first probability of a perturbation of an individual solution is represents the disturbance probability threshold, represents the number of individual solutions in one iteration, Indicates the maximum number of iterations.

8. A grain silo ventilation control method according to claim 6, characterized in that: The perturbation of the population solution satisfies the following formula: ， in, Indicates The solution of each individual solution after being disturbed is express A random number between express A random number between represents the upper boundary, represents the lower boundary, Indicates Individual solution The solution at the iteration is Indicates the maximum number of iterations.

9. A grain silo ventilation control system, characterized in that: The granary ventilation control system includes: an input device, an output device, a processor, and a memory. The input device, output device, processor, and memory are interconnected. The memory includes program instructions, and the program instructions are used to execute the granary ventilation control method according to any one of claims 1-8.

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