Granary heat preservation and insulation property detection method and device based on grain storage multi-field coupling theory
The method and device for detecting the thermal insulation performance of grain warehouses based on the multi-field coupling theory of grain storage have solved the problem of the disconnect between the evaluation of the thermal insulation performance of grain warehouses and the actual grain storage effect in the existing technology. It has realized the accurate and real-time detection of the thermal insulation performance of grain warehouses and ensured food security.
Patent Information
- Application Number
- CN202610076618.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-20
- Publication Date
- 2026-03-06
AI Technical Summary
Existing methods for evaluating the thermal insulation performance of grain silos are out of touch with actual grain storage results, making it difficult to monitor changes in the thermal insulation performance of grain silos in real time, which makes it difficult to guarantee food security.
A method and device for detecting the thermal insulation performance of grain silos based on the multi-field coupling theory of grain storage are adopted. By acquiring the real-time temperature at different monitoring points in the grain silo, a temperature field model of the grain pile is constructed. Combined with the air flow and thermal conductivity inside the grain, the thermal insulation performance of the grain silo can be accurately and in real time detected.
It improves the accuracy and real-time performance of grain silo insulation performance testing, enabling real-time monitoring of changes in the insulation performance of grain silos during grain storage, thus ensuring food security.
Smart Images
Figure CN121612928A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of food security technology, and in particular to a method and device for detecting the thermal insulation performance of grain warehouses based on the multi-field coupling theory of grain storage. Background Technology
[0002] Grain silos are crucial for ensuring food security. They must balance structural safety with functional aspects such as thermal insulation, requiring strict control of internal temperature and humidity to prevent mold and pests during grain storage. Due to the diverse structures of grain silos (tall flat silos, shallow round silos, vertical silos, etc.) and varying construction methods, it is necessary to test the thermal insulation performance of grain silos to meet the quantity and quality safety requirements for multi-variety and long-term grain storage. However, existing methods for evaluating the thermal insulation performance of grain silos lack integration with actual grain storage effectiveness, as specifically demonstrated below: 1. Theoretical calculations are difficult to meet actual requirements: Current evaluation methods for the thermal insulation of grain warehouses mainly rely on theoretical simulations based on the thermal conductivity of building materials and construction technology, without combining them with the actual storage environment and the actual conditions of grain, resulting in a discrepancy between theoretical results and reality.
[0003] 2. Difficulty in grasping real-time conditions: After a grain silo is built, it will be used for at least several decades. During long-term use, objective factors such as foundation settlement, wall damage, and material aging will cause the insulation of the grain silo to gradually deteriorate. Therefore, it is difficult to conduct real-time assessment using theoretical simulation values from the initial construction.
[0004] 3. Existing testing methods are difficult to implement: The thermal insulation performance of grain silos can only be tested when the silos are empty, which makes it difficult to perform the test on grain silos that are already filled with grain. In order to ensure the safety of the grain stored in the silos, it is often necessary to monitor the thermal insulation performance and changes of the grain silos in real time. Summary of the Invention
[0005] The purpose of this application is to provide a method and device for testing the thermal insulation performance of grain silos based on the multi-field coupling theory of grain storage, so as to improve the accuracy and real-time performance of testing the thermal insulation performance of grain silos.
[0006] To achieve the above objectives, this application provides the following solution.
[0007] Firstly, this application provides a method for detecting the thermal insulation performance of grain silos based on the multi-field coupling theory of grain storage, including: Obtain the real-time temperature at different monitoring points in the grain warehouse; Based on the real-time temperature at each monitoring point, a spatiotemporal temperature field of the grain pile is constructed using a grain pile temperature field model; the grain pile temperature field model is constructed based on the multi-field coupling theory of grain storage. Based on the spatiotemporal temperature field of the grain pile, the thermal insulation performance of the grain silo is determined.
[0008] Secondly, this application provides a grain storage insulation and heat insulation testing device based on the multi-field coupling theory of grain storage, including multiple sub-nodes, a main control system, a gateway and a cloud system; Each of the child nodes is connected to the main control system, and the main control system is connected to the cloud system through the gateway. Multiple sub-nodes are respectively set at different monitoring points within the grain warehouse; The sub-node is used to detect the temperature of the corresponding monitoring point and send the temperature to the main control system; The main control system is used to send the temperature of each monitoring point to the cloud system through the gateway; The cloud system is used to determine the thermal insulation performance of grain warehouses by employing the aforementioned grain warehouse insulation performance testing method based on the multi-field coupling theory of grain storage.
[0009] According to the specific embodiments provided in this application, this application has the following technical effects.
[0010] This application provides a method and apparatus for detecting the thermal insulation performance of grain silos based on the multi-field coupling theory of grain storage. First, the real-time temperature at different monitoring points in the grain silo is acquired. Then, based on the real-time temperature at each monitoring point, a spatiotemporal temperature field of the grain pile is constructed using a grain pile temperature field model. This grain pile temperature field model is constructed based on the multi-field coupling theory of grain storage. Finally, based on the spatiotemporal temperature field of the grain pile, the thermal insulation performance of the grain silo is determined. This application uses a grain pile temperature field model constructed using the multi-field coupling theory of grain storage. This model can simulate the internal temperature field of the grain pile by combining factors such as airflow inside the grain and the thermal conductivity of the grain itself, thus obtaining the spatiotemporal temperature field of the grain pile and enabling the detection of the thermal insulation performance of the grain silo. This application combines the actual storage conditions of the grain silo to detect its thermal insulation performance and can perform real-time detection during grain storage, improving the accuracy and real-time performance of the grain silo thermal insulation performance detection. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0012] Figure 1 This is a flowchart illustrating a method for detecting the thermal insulation performance of grain storage based on the multi-field coupling theory of grain storage, provided as an embodiment of this application.
[0013] Figure 2This is a schematic diagram of a grain storage insulation performance testing device based on the multi-field coupling theory of grain storage, provided as an embodiment of this application.
[0014] Figure 3 This is a schematic diagram illustrating the working principle of a grain storage insulation performance testing device based on the multi-field coupling theory of grain storage, provided as an embodiment of this application.
[0015] Figure 4 A summer wheat mid-vertical surface temperature field cloud map provided in an embodiment of this application.
[0016] Figure 5 Temperature field cloud map of corn near the wall in summer, provided as an embodiment of this application. Detailed Implementation
[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0019] In one exemplary embodiment, a method for detecting the thermal insulation performance of grain silos based on the multi-field coupling theory of grain storage is provided, such as... Figure 1 As shown, it includes the following steps 101-103.
[0020] Step 101: Obtain the real-time temperature at different monitoring points in the grain warehouse.
[0021] Step 102: Based on the real-time temperature of each monitoring point, construct the spatiotemporal temperature field of the grain pile using the grain pile temperature field model; the grain pile temperature field model is constructed based on the multi-field coupling theory of grain storage.
[0022] Step 103: Determine the thermal insulation performance of the grain silo based on the spatiotemporal temperature field of the grain pile.
[0023] Implementing steps 101-103 above can improve the accuracy and real-time performance of grain warehouse insulation performance testing.
[0024] A grain pile is a complex storage ecosystem, which includes physical factors such as solar radiation, temperature, humidity, and gases, as well as biological factors such as microorganisms, pests, and the grain itself, and the storage facilities (i.e., grain warehouses) that connect the environment to the grain pile. Therefore, the thermal insulation performance of grain warehouses directly affects the temperature and humidity of the stored grain pile, and thus affects the quality and safety of the stored grain.
[0025] In another exemplary embodiment, the above-mentioned grain pile temperature field model is constructed based on the multi-field coupling theory of grain storage, as follows: ; ; ; ; ; ; ; ; in, The porosity of grain is expressed as a percentage (%). It can be directly measured using a volumetric porosity analyzer. Generally, the porosity of grain is between 21% and 44%. , , and These represent the pressure, density, specific heat capacity, and temperature of the air within the pores of the grain pile, respectively, in Pa and kg / m³. 3 , J / (kg•℃), ℃, , and These represent the density, specific heat capacity, and temperature of the grain within the grain pile, respectively, in kg / m³. 3 J / (kg•℃), ℃; grain density was determined using a grain bulk density meter, and air density was measured using a constant of 1.2 kg / m³. 3 ; Let 's' be the time variable, 's'. The velocity of airflow between the pores of the grain is expressed in m / s. The effective thermal conductivity within the grain pile; For temperature field, For temperature The latent heat of vaporization of liquid water The mass of water in grain, expressed in kg; The dynamic viscosity of air, Pa / s. The pressure gradient (∇ is the gradient operator, P is the fluid pressure), Pa / m. The thermal buoyancy force per unit volume of the grain pile, in N; The moisture content of the air is dimensionless. per unit volume for A closed shape projected onto the XOY plane. In units of height, The acceleration due to gravity is m / s². 2 , It is a universal gas constant. , , These are the x-axis, y-axis, and z-axis coordinates of the grain pile in three-dimensional space.
[0026] In another exemplary embodiment, the implementation process of the above-mentioned grain pile temperature field model is as follows: When simulating the temperature at any point within a grain pile, first determine one or more monitoring points close to that point (if there is only one, directly obtain the real-time temperature of that monitoring point as part of the model). and When there are multiple values, the average of the multiple values can be calculated as the value in the model. and (The specific method is not limited here), and then determine the unit volume centered at that point.
[0027] Furthermore, using the formula Calculate the change in airflow velocity between grain pores. ,use calculate Then use the formula This allows you to obtain the real-time temperature at that point.
[0028] The real-time temperature at various points within the grain pile constitutes the spatiotemporal temperature field of the grain pile.
[0029] In another exemplary embodiment, step 103 described above can be replaced by steps 201-203.
[0030] Step 201: Based on the spatiotemporal temperature field of the grain pile, calculate the judgment index for different locations of the grain pile.
[0031] Step 202: Determine the location where the judgment index exceeds the index threshold as an abnormal location.
[0032] Step 203: If there is an abnormal location, it is determined that the thermal insulation performance of the grain silo does not meet the thermal insulation requirements.
[0033] In another exemplary embodiment, under the influence of the annual sinusoidal variation in the external storage environment temperature, the temperature changes of the grain pile at different times and spaces are judged based on the thermal conductivity and heat transfer properties of grains with different moisture contents. The aforementioned judgment indicators include kurtosis and / or standard score.
[0034] Kurtosis is used to describe the sharpness of the distribution of grain temperature data. A threshold of 3 is typically used; a kurtosis greater than 3 indicates a sharp distribution, while a kurtosis less than 3 indicates a more gradual distribution. The calculation method is as follows: ; in, Let be the kurtosis of the i-th cross-section of the grain pile. Let represent the spatiotemporal temperature field of the i-th cross-section of the grain pile. Let j be the temperature value at the j-th sampling point on the i-th cross-section. The number of sampling points on the same cross surface. The average temperature of all sampling points on the i-th cross-section. Let be the temperature standard deviation of all sampling points on the i-th cross-section.
[0035] The standard score is used to identify temperature anomalies by calculating the deviation of data points from the mean; its threshold is typically set to 3 or 2.5. The calculation formula is as follows: ; in, Let the standard score be the score of the j-th sampling point on the i-th cross-section. Let j be the temperature value at the j-th sampling point on the i-th cross-section. The average temperature of all sampling points on the grain pile. is the standard deviation of temperature at all sampling points in the grain pile.
[0036] In another exemplary embodiment, after determining that the thermal insulation performance of the grain silo does not meet the thermal insulation requirements, the following steps 204-206 are also set.
[0037] Step 204: Generate temperature field cloud maps of the grain pile at different times and from different perspectives based on the spatiotemporal temperature field of the grain pile. Step 205: Based on the temperature field cloud maps of the grain pile at different times and from different perspectives, obtain the spatiotemporal temperature field changes of the grain pile from each perspective. Step 206: Compare the spatiotemporal temperature field changes of the grain pile from each perspective with the spatiotemporal change patterns of the corresponding perspective to determine the areas of the grain silo that do not meet the requirements for heat preservation.
[0038] In another exemplary embodiment, steps 205 and 206 are implemented as follows: Based on the previously drawn temperature field cloud map of the grain pile, the spatiotemporal distribution and changes of the stored grain temperature field are first analyzed according to the thermal conductivity of the grain itself and the spatiotemporal variation threshold of the grain pile temperature field. When the temperature field change of the grain pile is less than the spatiotemporal variation pattern, it indicates that the heat insulation of the grain silo meets the requirements; when the temperature field change of the grain pile is much less than the spatiotemporal variation pattern, it indicates that the heat insulation of the grain silo is good; when the temperature field change of the grain pile is greater than the spatiotemporal variation pattern, it indicates that the heat insulation of the grain silo is poor.
[0039] In one exemplary embodiment, a grain silo insulation performance testing device based on the multi-field coupling theory of grain storage is provided, such as... Figure 2 As shown, the device includes multiple sub-nodes, a main control system, a gateway, and a cloud system. Each sub-node is connected to the main control system, which in turn connects to the cloud system via the gateway. The sub-nodes are respectively positioned at different monitoring points within the grain silo. Each sub-node detects the temperature at its corresponding monitoring point and sends the temperature data to the main control system. The main control system sends the temperatures of each monitoring point to the cloud system via the gateway. The cloud system uses the aforementioned grain silo insulation performance testing method based on multi-field coupling theory to determine the insulation performance of the grain silo.
[0040] In another exemplary embodiment, the aforementioned child node is a wired child node or a wireless child node, preferably a wireless child node.
[0041] In another exemplary embodiment, the wireless sub-nodes are mainly used to collect different data such as grain temperature, grain moisture, warehouse temperature, warehouse moisture, air temperature, and humidity at corresponding locations, and transmit them to the main control system. This includes: a first power management module, a first central processing unit, a first communication chip, and temperature sensors, etc.
[0042] The main control system is primarily used to record and transmit data such as the temperature at various points within the grain pile, as well as the internal and external ambient temperatures. It includes: a second power management module, a second central processing unit, data input terminals, an LED display screen, a second communication chip, and a third communication chip.
[0043] Gateways and cloud systems are primarily used for data transmission, analysis, and display, as well as solution delivery. The cloud system includes: an IoT switching platform, a cloud computing platform, a cloud database, and a data visualization console.
[0044] The data recorded by the main control system is transmitted to the gateway through the third communication chip, and the gateway then sends it to the IoT transfer platform. The IoT switching platform receives data transmitted from the gateway, decodes it, and then transmits the valid data to the cloud computing platform and cloud database.
[0045] The cloud computing platform inputs data from sub-nodes and the main control system into the grain pile temperature field model for calculation, and uses a visualization language program to draw a real-time spatiotemporal distribution map of the grain pile temperature field. It then analyzes and alarms anomalies by combining the spatiotemporal change threshold of the temperature field, and transmits the spatiotemporal distribution map of the grain pile temperature results, analysis, and anomaly warning results to the data visualization console.
[0046] The cloud database mainly stores data from child nodes and the main control system, data information such as calculation results and abnormal results of the cloud computing platform, graphical information and solution suggestions from the data visualization control platform, etc.
[0047] The data visualization console is used to view and store data information transmitted by the main control system, analysis and abnormal results information from the cloud computing platform, real-time temperature status of the grain pile plot drawn by the cloud computing platform, and decision-making suggestions.
[0048] In another exemplary embodiment, such as Figure 3 As shown, the working principle of the grain storage insulation and heat insulation detection device based on the multi-field coupling theory of grain storage is as follows: the grain pile temperature and other data detected by the sub-nodes are uploaded to the main control system. The main control system transmits the grain pile temperature and other data to the cloud database in the cloud system in real time through the gateway. The cloud computing platform loads the data information of the grain temperature and grain moisture database into the cloud database and substitutes it into the temperature field model in the cloud computing platform for calculation. The grain pile temperature data is substituted into the background grain pile temperature field cloud map program of the cloud computing platform to draw the grain pile temperature field cloud map from different perspectives such as front view, top view, and side view. The cloud map result is then transmitted to the visualization control platform for display.
[0049] In an exemplary embodiment, the above-described method and apparatus can be used to evaluate the thermal insulation performance of grain silos and accurately locate areas with poor thermal insulation performance, facilitating the construction of new high-standard grain silos and the performance improvement of existing grain silos. However, it is not limited to the following case of evaluating the thermal insulation performance of grain silos based on multi-field coupling theory.
[0050] 1. Taking a tall, flat-roofed warehouse in a southern region as an example, its dimensions are: length × width × grain pile height = 30m × 21m × 6m, ridge height 13.5m, eaves height 11.8m, and it was constructed using cast-in-place concrete. The stored grain is wheat, with an initial moisture content of 11.5% wb and an impurity content of 0.6%. The simulated summer vertical temperature field cloud map of the wheat is shown below. Figure 4 As shown.
[0051] Depend on Figure 4 Analysis shows that as the outside temperature rises in summer, the temperature of grain piles near the warehouse walls, the ground, and on the surface of the grain piles all increase. Furthermore, since grain is a poor heat conductor, a low-temperature zone forms in the center of the grain pile. Figure 3 The surface grain temperature is slightly lower than the rest of the grain temperature. Combined with the grain storage operation, air conditioning is used to control the upper air temperature inside the silo to lower the surface grain temperature. Therefore, condensation easily forms at the junction of the higher grain temperature area in the lower middle zone and the lower grain temperature area in the upper zone. This indicates that the insulation of the silo roof meets the requirements, but the insulation of the silo walls and foundation ground does not. Therefore, the insulation of the walls and foundation ground of this silo is insufficient and needs further improvement.
[0052] 2. Taking a tall, flat-roofed warehouse in North China as an example, its dimensions are: length × width × grain pile height = 60m × 21m × 8m, ridge height 15.5m, eaves height 12.1m, and it was constructed using cast-in-place concrete. The stored grain, corn, had an initial moisture content of 12.5% wb and an impurity content of 0.7%. The simulated summer temperature field cloud map near the corn wall is shown below. Figure 5 As shown.
[0053] Depend on Figure 5 Analysis shows that as the outside temperature rises in summer, the temperature of grain piles, especially those close to the warehouse walls and the ground, as well as the surface grain piles, will rise. At the same time, due to the increased intensity of the western sun, the temperature and magnitude of the grain near the western wall rise are greater and faster than those on the eastern side. Figure 5 The grain temperature on the west-facing wall is higher than that on the east-facing wall, especially at the lower part of the west-facing wall. Additionally, the near-ground grain temperature in the central and eastern parts of the warehouse shows a significant increase, exceeding the threshold value of 3. This indicates that the ventilation openings in these areas lack proper insulation, leading to strong convection currents between the vents and the ground, resulting in a substantial temperature rise far exceeding the threshold value of 3. In summary, the roof insulation of the grain warehouse is relatively good, but the lower and middle parts of the west wall have poor insulation, and the foundation insulation of the central and eastern warehouse floors is extremely poor. Appropriate airtight insulation improvements are needed in these areas to ensure the safety of stored grain.
[0054] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0055] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for detecting the heat insulation performance of a grain depot based on the multi-field coupling theory of stored grain, characterized in that, The method comprises: acquiring real-time temperatures of different monitoring points in the granary; constructing a time-space temperature field of the grain pile according to the real-time temperatures of the monitoring points by using a grain pile temperature field model; the grain pile temperature field model is constructed based on a multi-field coupling theory of stored grain; determining the heat insulation performance of the granary based on the time-space temperature field of the grain pile.
2. The method for detecting the heat insulation performance of a grain depot based on the multi-field coupling theory of stored grain according to claim 1, characterized in that, The grain pile temperature field model is as follows: ； ； ； ； ； ； ； ； wherein, is the porosity of the grain, , , and are the pressure, density, specific heat capacity and temperature of the air in the interstitial space of the grain, respectively, , and are the density, specific heat capacity and temperature of the grain, respectively, is the time variable, is the flow velocity of the air in the interstitial space of the grain, is the effective thermal conductivity in the grain pile, is the temperature field, is the temperature latent heat of vaporization of liquid water at the temperature is the mass of water in the grain; the kinematic viscosity of air, the pressure gradient, the thermal buoyancy per volume of the grain pile; for the water content in air; is the unit volume, is the unit height, is the closed figure projected on the XOY plane, is the unit height, is the acceleration of gravity, is the universal gas constant, , , are the x-axis, y-axis and z-axis coordinates of the three-dimensional space of the grain pile, respectively.
3. The method for detecting the heat insulation performance of a grain depot based on the multi-field coupling theory of stored grain according to claim 1, characterized in that, determining the heat insulation performance of the granary based on the time-space temperature field of the grain pile, specifically comprising: calculating a determination index of different positions of the grain pile based on the time-space temperature field of the grain pile; determining a position where the determination index exceeds an index threshold as an abnormal position; if there is an abnormal position, determining that the heat insulation performance of the granary does not meet the heat insulation requirement.
4. The method for detecting the heat insulation performance of a grain depot based on the multi-field coupling theory of stored grain according to claim 3, characterized in that, The determination index comprises kurtosis and / or a standard score.
5. The method according to claim 4, wherein the method is characterized by, The calculation formula of the kurtosis is as follows: ； wherein, Kurtosis of the i-th cross-section of the grain pile, represents the spatio-temporal temperature field of the i-th cross-section of the grain pile, is the temperature value of the j-th sampling point on the i-th cross-section, is the number of sampling points on the same cross-section, is the temperature mean value of all sampling points on the i-th cross-section, is the temperature standard deviation of all sampling points on the i-th cross-section; The calculation formula of the standard score is as follows: ； wherein, is the standard score of the jth sampling point on the ith cross section, is the temperature value of the jth sampling point on the ith cross section, is the mean temperature of all sampling points of the grain pile, is the standard deviation of temperature of all sampling points of the grain pile.
6. The method for detecting the heat insulation performance of a grain depot based on the multi-field coupling theory of stored grain according to claim 3, characterized in that, determining that the heat insulation performance of the granary does not meet the heat insulation requirement, and then comprising: generating a grain pile temperature field cloud map of different times and different perspectives according to the time-space temperature field of the grain pile; obtaining a time-space temperature field change of the grain pile at each perspective based on the grain pile temperature field cloud map of different times and different perspectives; comparing the time-space temperature field change of the grain pile at each perspective with a time-space change rule of the corresponding perspective to determine a region of the granary that does not meet the heat insulation requirement.
7. A grain depot heat preservation and insulation detection device based on a multi-field coupling theory of stored grain, characterized in that, The system comprises a plurality of sub-nodes, a master control system, a gateway and a cloud system; each of the sub-nodes is connected to the master control system, and the master control system is connected to the cloud system through the gateway; the plurality of sub-nodes are respectively arranged at different monitoring points in the granary; the sub-nodes are used to detect temperatures of the corresponding monitoring points and send the temperatures to the master control system; the master control system is used to send the temperatures of the monitoring points to the cloud system through the gateway; the cloud system is used to determine the heat insulation performance of the granary by using the method for detecting the heat insulation performance of the granary based on the multi-field coupling theory of stored grain according to any one of claims 1-6.
8. The grain depot heat preservation and insulation detection device based on the multi-field coupling theory of stored grain according to claim 7, characterized in that, The sub-nodes comprise a first power management module, a first central processing unit, a first communication chip and a temperature sensor; the first power management module is connected to the first central processing unit, the first communication chip and the temperature sensor respectively; the temperature sensor and the first communication chip are connected to the first central processing unit, and the first communication chip is connected to the master control system.
9. The grain depot heat preservation and insulation detection device based on the multi-field coupling theory of the grain depot according to claim 8, characterized in that, The master control system comprises a second power management module, a second central processing unit, an LED display screen, a data information input end, a second communication chip and a third communication chip; the second power management module is connected to the second central processing unit, the LED display screen and the second communication chip respectively; the LED display screen, the data information input end, the second communication chip and the third communication chip are connected to the second central processing unit, and the second communication chip is connected to the first communication chip; the third communication chip is connected to the gateway.
10. The grain storage heat preservation and insulation detection device based on the multi-field coupling theory of stored grain according to claim 7, characterized in that, The cloud system comprises an Internet of Things switching platform, a cloud computing platform, a cloud database and a data visualization control platform; the Internet of Things switching platform is connected to the gateway, the cloud computing platform and the cloud database respectively; The cloud computing platform is connected with the cloud database and the data visualization control platform respectively; The cloud database is also connected with the data visualization control platform.