Granary ventilation control method and system

Abstract

The invention relates to the technical field of grain storage ventilation control, in particular to a granary ventilation control method and system. The method comprises the following steps: identifying a grain type, and determining the optimal storage temperature and the optimal storage humidity of a grain pile based on the grain type; the actual temperature and the actual humidity of the grain pile are obtained, a temperature difference value is obtained according to the optimal storage temperature and the actual temperature, and a humidity difference value is obtained according to the optimal storage humidity and the actual humidity; constructing a ventilation equipment control parameter adjustment objective function; constructing a control parameter matrix by using the control parameters of the temperature control module and the humidity control module, and forming a population solution by using the control parameter matrix as an individual solution; using the ventilation equipment control parameter to adjust the objective function and the population solution to carry out iterative solution, and obtaining the optimal ventilation equipment control parameter; and completing granary ventilation control based on the optimal ventilation equipment control parameters, the temperature difference value and the humidity difference value. The problem of intelligently controlling ventilation equipment according to grain storage conditions is solved.

Description

Technical Field

[0001] The invention relates to the technical field of grain storage ventilation control, and in particular to a grain silo ventilation control method and a system thereof. Background Art

[0002] Grain storage is an ecological process in which various non-biological and biological factors interact with each other. Non-biological 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; biological factors mainly include the interaction between grains and microorganisms, and between microorganisms and other organisms. The activities of microorganisms and their interactions affect and change the quality of stored grain; among all factors, grain temperature and moisture are the most critical factors affecting grain storage safety. They are closely related to grain quality, dry matter loss, and insect and mold growth. All organisms that cause grain loss, such as bacteria, insects, mold, mites, etc., their growth is affected by the temperature and humidity of their growth environment. Influence; 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 damage to grain. This is the general law that the interaction between environmental temperature and humidity affects 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 grain is ventilation technology. There are certain gaps between the grain particles of grain piled up in the granary. The flowing air acts as a carrier of heat and mass transfer. When passing through the gaps between grain particles, convective heat and mass transfer occurs with the grain, carrying away excess heat and moisture in the grain pile. According to the state of the grain, the temperature and moisture of the grain can be adjusted by ventilating the stored grain to ensure that it is within the range of safe storage.

[0003] Traditional ventilation control methods often rely on manual experience, and there are problems with untimely and inaccurate regulation. In order to effectively control the temperature and humidity conditions in the granary, prevent the grain from getting damp, moldy, 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 shortcomings of the existing methods and the needs of practical applications, on the one hand, the present invention provides a grain silo ventilation control method, comprising 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; obtain the actual temperature and actual humidity of the grain pile, obtain a temperature difference value based on the optimal storage temperature and the actual temperature, and obtain a humidity difference value based on the optimal storage humidity and the actual humidity; construct a ventilation equipment control parameter adjustment objective function; 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 ventilation equipment control parameter adjustment objective function and the population solution to iteratively solve and obtain the optimal ventilation equipment control parameters; complete the granary ventilation control based on the optimal ventilation equipment control parameters, the temperature difference value and the humidity difference value.

[0005] The present invention obtains ventilation equipment control parameters through iterative optimization, and then adjusts ventilation equipment output based on the optimal storage temperature and humidity of grain and the actual storage temperature and humidity, so as to timely, accurately and quickly make the granary reach the optimal storage condition, complete intelligent real-time control of ventilation equipment, reduce labor costs, solve the problems of untimely and inaccurate regulation in manual control, avoid losses caused by ineffective ventilation or even excessive ventilation, and realize green and energy-saving grain storage.

[0006] Optionally, 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. 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.

[0007] Optionally, the step of using the ventilation equipment control parameter adjustment objective function and the population solution to iteratively solve to 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; in the late stage of iterative solution, the third iterative solution algorithm is executed on the population solution. The present invention is conducive to improving the optimization speed and optimization quality of the final solution by executing different adjustment strategies in the early stage and late stage of iterative solution.

[0008] Optionally, a first iterative solution algorithm is performed 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 invention introduces Levy flight parameters to improve the global search capability and the control efficiency of the invention.

[0009] Optionally, a second iterative solution algorithm is performed 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 invention introduces the Cauchy parameter to improve the global search capability and further improve the control efficiency of the invention.

[0010] Optionally, a third iterative solution algorithm is performed 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 invention adaptively adjusts the weight factor of the individual solution according to the number of iterations, and then improves the local optimization capability through a spiral optimization method, thereby improving the speed and quality of obtaining the final solution.

[0011] Optionally, the step of iteratively solving the optimal ventilation equipment control parameter by adjusting the objective function and the population solution using the ventilation equipment control parameter further comprises perturbing the population solution according to a first probability during each iteration. The present invention further improves the quality of obtaining a final solution by perturbing and varying a partial solution.

[0012] Optionally, 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.

[0013] Optionally, 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 The present invention sets the first probability and the perturbation rule, and performs high-probability perturbations on the individual solutions ranked low at the beginning of the iteration, thereby improving the diversity of solutions and further improving the control efficiency of the present invention.

[0014] In the second aspect, in order to be able to efficiently execute a granary ventilation control method provided by the present invention, the present invention also provides a granary ventilation control system, including a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute a granary ventilation control method as described in the first aspect of the present invention. A granary ventilation control system of the present invention has a compact structure and stable performance, and can stably execute a granary ventilation control method provided by the present invention, further improving the overall applicability and practical application capabilities of the present invention.

[0015] Beneficial effects: The present invention obtains ventilation equipment control parameters through iterative optimization, and then adjusts the ventilation equipment output based on the optimal storage temperature and humidity of grain and the actual storage temperature and humidity, so as to timely, accurately and quickly make the granary reach the optimal storage conditions, complete the intelligent real-time control of the ventilation equipment, reduce labor costs, solve the problems of untimely and inaccurate regulation in manual control, avoid losses caused by ineffective ventilation or even excessive ventilation, and realize green and energy-saving grain storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a grain silo ventilation control method provided by an embodiment of the present invention; Figure 2 A framework diagram of a granary ventilation control system provided by an embodiment of the present invention; Figure 3 A schematic structural diagram of a granary ventilation control device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0018] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0019] See also Figure 1 In order to effectively control the temperature and humidity conditions in the granary, prevent the grain from getting damp, moldy, and deteriorating, reduce labor costs, improve work efficiency, and solve the problems of untimely and inaccurate regulation in manual control, the present invention provides a granary ventilation control method, such as Figure 1 As shown, the method comprises the following steps: 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.

[0020] In an embodiment, the type of grain is identified by machine recognition, and the optimal storage temperature and optimal storage humidity of the grain pile are determined based on the identified type of grain and in combination with relevant grain storage specifications.

[0021] Grains mainly include wheat, beans, rice, coarse grains, etc. Specific types include wheat, barley, highland barley, soybeans, mung beans, japonica rice, indica rice, glutinous rice, corn, sorghum, buckwheat, etc. Each grain has its own unique physical and chemical properties, which determine the optimal conditions for their storage process.

[0022] The optimal storage temperature for wheat (such as wheat and barley): It is usually stored below 15-20°C to avoid increased respiration and quality degradation caused by high temperature. Under low temperature conditions, the respiration of wheat is weakened, which is conducive to maintaining its nutritional value and taste; The optimal storage humidity: The humidity should be controlled between 60% and 70% to prevent quality problems caused by excessive drying of the grain or excessive humidity.

[0023] The optimal storage temperature for beans (such as soybeans and mung beans): Similar to wheat, beans should also be stored below 15-20°C to maintain their quality and extend their shelf life; the optimal storage humidity: the humidity should also be controlled between 60% and 70% to ensure the dryness of the beans and prevent mold.

[0024] Optimal storage temperature for rice (such as japonica rice and indica rice): For rice, the safe limit of its grain pile temperature should not exceed 15°C, and ideally it should be maintained between 10 and 15°C. This temperature range helps inhibit mold growth and maintain the quality of rice; Optimal storage humidity: Humidity should be controlled between 60% and 70% to prevent the rice from being overly dry or damp.

[0025] Optimal storage temperature for coarse grains (such as corn and sorghum): The storage temperature of coarse grains should also be below 15-20°C to ensure their quality and extend their shelf life; Optimal storage humidity: Humidity control is equally important and should generally be maintained between 60% and 75%, depending on the moisture content of the grain and the storage environment.

[0026] 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% and 75%. The specific humidity range may vary depending on the type of grain and its moisture content. These conditions help inhibit mold growth, reduce respiration, and maintain the nutritional value and taste of the grain.

[0027] S2. 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.

[0028] Specifically, the actual temperature and actual humidity of the grain pile are obtained through a temperature sensor and a humidity sensor, and then a temperature difference value is obtained based on the optimal storage temperature and the actual temperature, and a humidity difference value is obtained based on the optimal storage humidity and the actual humidity.

[0029] S3. Construct the objective function for adjusting the control parameters of ventilation equipment.

[0030] In the embodiment, the ventilation equipment control parameter adjustment objective function is constructed to satisfy 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.

[0031] Furthermore, the temperature control weight coefficient and the humidity control weight coefficient are adjusted according to the environmental parameters of the granary, which include indoor air temperature, indoor air humidity, outdoor air temperature and outdoor air humidity. , , represents the temperature difference coefficient, , represents the outdoor air temperature, Indicates the indoor air temperature, represents the humidity difference coefficient, , Indicates the outdoor air humidity. Indicates the indoor air humidity.

[0032] Furthermore, the simulation of the temperature and humidity of the grain pile after ventilation can be completed based on the grain moisture balance equation, air humidity balance equation, grain heat balance equation and air heat balance equation between grain particles combined with Matlab simulation software.

[0033] S4. Construct a control parameter matrix using 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.

[0034] Specifically, the temperature control module and the humidity control module are both PID control modules. The PID control module is a vital component in industrial control systems. It achieves precise control of the controlled object based on the combination of three control algorithms: proportional, integral, and differential.

[0035] The PID control module maintains the state of the controlled object near the set value by continuously adjusting the output of the controller to achieve stable and accurate automatic control. Its basic principle is to adjust the output signal according to the difference between the current state of the controlled object and the set value, that is, the error, so that the difference approaches zero; the PID controller calculates the output signal based on the weighted combination of the proportional, integral, and differential parts, thereby achieving precise control of the controlled object.

[0036] Proportional link (P): According to the size of the error signal, it is amplified by a certain proportion to generate a corresponding control signal. Proportional control can respond quickly to system errors and make the system quickly approach the set value, but it may cause overshoot and oscillation.

[0037] Integral link (I): Integrate the error signal to obtain the accumulated error value, and convert it into a control signal. Integral control can eliminate the steady-state error of the system and ensure that the system eventually stabilizes near the set value, but it may also cause overshoot and oscillation.

[0038] Differential link (D): Detects changes in the error signal so that corrections can be made before a large error occurs in the system. Differential control can predict the future state change trend of the system, thereby reducing overshoot and improving system stability, but it may also increase the system's sensitivity to noise.

[0039] The PID control module can achieve stable control. The PID controller can adjust the control signal in real time according to the system error, so that the output of the controlled object gradually approaches the expected output and achieves stable control. It can also eliminate static errors. Through the role of the integral link, the PID controller can continuously integrate the system error, thereby gradually eliminating the static error of the system and improving the control accuracy and performance of the system. As well as improving the system sensitivity, the role of the differential link enables the PID controller to make corrections before large errors occur in the system, thereby improving the response speed and sensitivity of the system.

[0040] Furthermore, since humidity and temperature are coupled, the constructed control parameter matrix satisfies: , represents the control parameter matrix, Indicates the proportional coefficient of the temperature control PID module, Indicates the integral coefficient of the temperature control PID module, Indicates the differential coefficient of the temperature control PID module, Indicates the proportional coefficient of the humidity control PID module, Indicates the integral coefficient of the humidity control PID module, Indicates the differential coefficient of the humidity control PID module, Indicates the humidity decoupling coefficient of the temperature control PID module, Indicates the temperature decoupling coefficient of the humidity control PID module.

[0041] Furthermore, according to the corresponding specifications and experience, the value range of the control parameters is set, and multiple control parameter matrices are obtained to form a population solution.

[0042] S5. 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.

[0043] Specifically, the step S5 uses the ventilation equipment control parameter adjustment objective function and the population solution to iteratively solve to obtain the optimal ventilation equipment control parameter, including the following steps: S51. In the early stage of iterative solution, the first iterative solution algorithm or the second iterative solution algorithm is executed on the population solution.

[0044] Specifically, a first iterative solution algorithm is performed 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.

[0045] Furthermore, a second iterative solution algorithm is performed 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.

[0046] In the embodiment, the early stage of the iterative solution is based on half of the maximum number of iterations as the basis for division; the first iterative solution algorithm or the second iterative solution algorithm is executed on the population solution, including randomly assigning a If the label value belongs to (-1,0], the corresponding individual solution executes the first iterative solution algorithm in the next iteration; if the label value belongs to (0,1), the corresponding individual solution executes the second iterative solution algorithm in the next iteration. In some other embodiments, other rules can also be set.

[0047] S52. In the later stage of iterative solution, a third iterative solution algorithm is executed on the population solution.

[0048] Specifically, 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.

[0049] Furthermore, the step S5 uses the ventilation equipment control parameter to adjust the objective function and the population solution to iteratively solve to obtain the optimal ventilation equipment control parameter, and also includes perturbing the population solution according to the first probability during each iteration.

[0050] 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. Indicates The individual solutions are not disturbed. Indicates The individual solutions are disturbed.

[0051] Furthermore, the population solution is disturbed to satisfy 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.

[0052] S6. Complete the granary ventilation control based on the optimal ventilation equipment control parameters, the temperature difference value and the humidity difference value.

[0053] Specifically, based on the optimal ventilation equipment control parameters, the ventilation equipment is adjusted 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 which time the granary is in the optimal storage state; when the temperature difference value and the humidity difference value exceed the threshold value, the ventilation equipment is started again for adjustment to complete the intelligent control of the granary ventilation equipment.

[0054] See also Figure 2 In an embodiment, in order to efficiently execute a granary ventilation control method provided by the present invention, the present invention further provides a granary ventilation control system, including: an input device, an output device, a processor, and a memory, wherein the input device, the output device, the processor, and the memory are interconnected, and the memory contains program instructions, and the program instructions are used for the steps of the granary ventilation control method. The granary ventilation control system of the present invention has a compact structure and stable performance, and can stably execute a granary ventilation control method of the present invention, further improving the overall applicability and practical application ability of the present invention.

[0055] In an embodiment, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. An input device may be used to obtain data information. An output device may be used to output the results obtained by storing program instructions contained in a computer program in a 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 portion of the memory may also include a non-volatile random access memory.

[0056] In yet another alternative embodiment, see Figure 3 In order to efficiently execute the grain silo ventilation control method provided by the present invention, this embodiment also provides a grain silo ventilation control device, such as Figure 3 As shown, including: The memory 10 is used to store computer programs; the processor 20 is used to execute the computer programs to implement the above-mentioned grain silo ventilation control method. The memory 10, the processor 20, the communication interface 31 and the communication bus 32. The memory 10, the processor 20 and the communication interface 31 all communicate with each other through the communication bus 32.

[0057] 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: 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; obtain the actual temperature and actual humidity of the grain pile, obtain a temperature difference value based on the optimal storage temperature and the actual temperature, and obtain a humidity difference value based on the optimal storage humidity and the actual humidity; construct a ventilation equipment control parameter adjustment objective function; 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 ventilation equipment control parameter adjustment objective function and the population solution to iteratively solve and obtain the optimal ventilation equipment control parameters; complete the granary ventilation control based on the optimal ventilation equipment control parameters, the temperature difference value and the humidity difference value.

[0058] In one possible implementation, the memory 10 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, and at least one application required for a 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 portion of the memory may also include NVRAM. The memory stores an operating system and operating instructions, executable modules or data structures, or a subset thereof, or an extended set thereof, wherein the operating instructions may include various operating instructions for implementing various operations. The operating system may include various system programs for implementing various basic tasks and processing hardware-based tasks.

[0059] 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 device, and the processor 20 may be a microprocessor or any conventional processor, etc. The processor 20 may call a program stored in the memory 10. The communication interface 31 may be an interface of a communication module, and is used to connect with other devices or systems.

[0060] Of course, it should be noted that Figure 3 The structure shown does not constitute a limitation on the grain silo ventilation control device in this embodiment. In actual applications, the grain silo ventilation control device may include Figure 3 More or fewer components than shown, or combinations of certain components.

[0061] The embodiment further provides a storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned grain silo ventilation control method are implemented.

[0062] The storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0063] To summarize, the present invention obtains the ventilation equipment control parameters through iterative optimization, and then adjusts the ventilation equipment output based on the optimal storage temperature and humidity of the grain and the actual storage temperature and humidity, so as to timely, accurately and quickly make the granary reach the optimal storage conditions, complete the intelligent real-time control of the ventilation equipment, reduce labor costs, solve the problems of untimely and inaccurate regulation in manual control, avoid losses caused by ineffective ventilation or even excessive ventilation, and realize green and energy-saving grain storage.

[0064] Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial utilization value.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope recorded 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 iteratively solve, 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.

2. A grain silo ventilation control method according to claim 1, characterized in that: 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.

3. A granary 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, executing the first iterative solution algorithm or the second iterative solution algorithm on the population solution; At the later stage of iterative solution, a third iterative solution algorithm is executed on the population solution.

4. A grain silo ventilation control method according to claim 3, 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.

5. A granary ventilation control method according to claim 3, 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.

6. A grain silo ventilation control method according to claim 3, 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.

7. 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.

8. A grain silo ventilation control method according to claim 7, 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.

9. A grain silo ventilation control method according to claim 7, 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.

10. 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 1-9.

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