Method and device for measuring loading mass of cereal warehouse, cereal warehouse and storage medium

Abstract

The invention relates to the technical field of agricultural machinery, and provides a cereal warehouse loading mass measuring method and device, a cereal warehouse and a storage medium, and the method comprises the steps: obtaining distance point cloud data obtained through the measurement of a multi-beam laser ranging radar, carrying out the preprocessing of the distance point cloud data, obtaining effective cereal distance point cloud data, and carrying out the calculation of the effective cereal distance point cloud data; determining the average stacking height of the grain stacking surface according to the effective grain distance point cloud data, obtaining the designed volume in the grain warehouse, determining the volume of a cavity above the grain stacking surface according to the average stacking height, and determining the stacking volume of the grain warehouse according to the designed volume in the warehouse and the volume of the cavity, the grain average density of the grain warehouse is determined, and the loading mass of the grain warehouse is determined according to the stockpiling volume and the grain average density. The device does not need to be in direct contact with grain piles, the whole measurement process can be automatically carried out, manual intervention is reduced, real-time measurement can be carried out according to changes of grains in a bin, and the measurement efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural machinery, and in particular to a method and device for measuring the loading mass of a grain bin, a grain bin and a storage medium. Background Art

[0002] Obtaining relevant data information at all stages of agricultural production is an important requirement for realizing agricultural informatization. During the drying process, the quality and volume of grains will change with the height of the pile and the evaporation of water. Obtaining relevant data can help determine the drying situation and ensure that the grains meet the requirements for subsequent processing.

[0003] In the prior art, the determination of grain loading mass mainly relies on weighing or flow meters. Although these methods can provide accurate loading information to a certain extent, they have many shortcomings. Among them, the weighing method requires real-time measurement during the grain loading or unloading process, which is not only time-consuming and labor-intensive, but also easily affected by various factors such as environmental conditions, equipment accuracy and operational norms, making it difficult to ensure the accuracy of the measurement results. At the same time, weighing equipment usually requires a large initial investment, and the subsequent maintenance costs are relatively high, which is a heavy economic burden for some agricultural enterprises or farmers.

[0004] The flow meter method relies on accurate monitoring and calculation of the grain flow state, which is difficult to implement in practice. The grain flow state is complex and changeable, so the flow meter method often has large errors in its measurement results.

[0005] In view of this, it is necessary to propose a method and device for measuring the loading mass of a grain silo, a grain silo and a storage medium to solve or at least alleviate the above-mentioned defects. Summary of the invention

[0006] The main purpose of the present invention is to provide a method and device for measuring the loading mass of a grain silo, a grain silo and a storage medium, so as to solve the problem that the existing measurement of the loading mass of grains is time-consuming, labor-intensive and difficult to operate.

[0007] To achieve the above object, the present invention provides a method for measuring the loading mass of a grain silo, comprising the following steps:

[0008] S1, obtaining distance point cloud data measured by a multi-beam laser ranging radar, and preprocessing the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar is installed on the top of the silo body of the grain silo to measure the distance between the silo and the grain stacking surface;

[0009] S2, determining an average stockpile height of the grain stockpile surface according to the effective grain distance point cloud data;

[0010] S3, obtaining the designed volume of the grain silo, determining the volume of the cavity above the grain stockpile surface according to the average stockpile height, and determining the stockpile volume of the grain silo according to the designed volume of the silo and the volume of the cavity;

[0011] S4, determining an average density of grains in the grain bin, and determining a loading mass of the grain bin according to the stockpile volume and the average density of grains.

[0012] Preferably, the step S1 of preprocessing the distance point cloud data to obtain effective grain distance point cloud data specifically comprises the following steps:

[0013] S11, obtaining the point cloud with the largest height value in the distance point cloud data as a reference point cloud, and constructing a reference horizontal plane with the reference point cloud;

[0014] S12, taking the point where the laser beam emission point of the multi-beam laser ranging radar is vertically projected to the reference horizontal plane as the center of the circle, taking the reference point cloud to the center of the circle as the radius, and taking the center of the circle to the laser beam emission point as the central axis to construct a cylindrical space;

[0015] S13, eliminating distance point cloud data outside the cylindrical space;

[0016] S14, filtering the remaining distance point cloud data to obtain filtered distance point cloud data and using the filtered distance point cloud data as effective grain distance point cloud data.

[0017] Preferably, the step S2 specifically includes the following steps:

[0018] S21, using the formula Determine the average grain pile height h avg ; Where n is the number of point clouds in the effective grain distance point cloud data, Z i is the height value of the i-th valid grain distance point cloud data.

[0019] Preferably, determining the average density of grains in the grain bin in step S4 specifically comprises the following steps:

[0020] S41, obtain dry grain density;

[0021] S42, obtaining the average moisture content of grains;

[0022] S43, using formula Determine the wet density ρ of the grain, and use the wet density ρ as the average density of the grain; where ρ d is the dry grain density, H avg is the average moisture content of grains.

[0023] Preferably, the average moisture content H of the grains in step S42 is avg The specific steps are as follows:

[0024] Using formula Determine the average moisture content H of the grain avg ; Among them, H j is the moisture content measured by the jth online moisture meter, w j is the calculation weight corresponding to the jth online moisture meter, and m is the number of online moisture meters.

[0025] Preferably, determining the cavity volume above the grain pile surface according to the average pile height in step S3 specifically comprises the following steps:

[0026] Using formula V g =V0-S*h avg Determine the volume of the cavity above the grain pile surface V g ; Among them, the area above the grain stacking surface is a section of equal diameter, V0 is the designed volume in the bin, and S is the cross-sectional area of ​​the area above the grain stacking surface of the grain bin.

[0027] The present invention also provides a device for measuring the loading amount of a grain warehouse, comprising:

[0028] A point cloud data acquisition unit is used to acquire distance point cloud data measured by a multi-beam laser ranging radar, and pre-process the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar is installed on the top of the silo body of the grain silo to measure the distance to the grain stacking surface;

[0029] An average stockpile height determination unit, used to determine an average stockpile height of a grain stockpile surface according to the effective grain distance point cloud data;

[0030] A stockpile volume determination unit, used to obtain the designed volume of the grain silo, determine the volume of the cavity above the grain silo surface according to the average stockpile height, and determine the stockpile volume of the grain silo according to the designed volume of the silo and the volume of the cavity;

[0031] The loading mass determination unit is used to determine the average density of grains in the grain bin, and determine the loading mass of the grain bin according to the stockpile volume and the average density of grains.

[0032] The present invention also provides a grain silo, comprising a silo body, and also comprising a multi-beam laser ranging radar and a control system arranged on the top of the silo body, wherein the multi-beam laser ranging radar is used to measure the distance to the grain pile surface, the multi-beam laser ranging radar is connected to the control system, the control system comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for measuring the loading mass of the grain silo as described above are implemented.

[0033] The present invention also provides a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for measuring the loading mass of a grain silo as described above.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention provides a method and device for measuring the loading mass of a grain bin, a grain bin and a storage medium. The method comprises obtaining distance point cloud data obtained by measuring a multi-beam laser ranging radar and preprocessing the distance point cloud data to obtain effective grain distance point cloud data. The average stockpile height of a grain stockpile surface is determined according to the effective grain distance point cloud data, the designed internal volume of the grain bin is obtained, and the volume of a cavity above the grain stockpile surface is determined according to the average stockpile height. The stockpile volume of the grain bin is determined according to the designed internal volume and the cavity volume, the average density of grains in the grain bin is determined, and the loading mass of the grain bin is determined according to the stockpile volume and the average density of grains.

[0036] The multi-beam laser ranging radar of the present application can provide high-precision distance measurement, thereby ensuring accurate calculation of the height and volume of the grain pile. The present application does not require direct contact with the grain pile, and also solves the problem that visual equipment is difficult to use due to dim light in the grain warehouse; the entire measurement process can be automated, reducing human intervention, and can be measured in real time according to changes in the grain in the warehouse, thereby improving measurement efficiency and accuracy; the present application can grasp the loading status of the grain in real time, and can help determine the drying status in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0038] Figure 1 It is a schematic diagram of a flow chart in one embodiment of the present invention;

[0039] Figure 2 This is a flow chart showing the steps of preprocessing the distance point cloud data to obtain effective grain distance point cloud data in step S1 in one embodiment of the present invention:

[0040] Figure 3 It is a schematic structural diagram of a grain warehouse in one embodiment of the present invention.

[0041] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments.

[0042] Description of Figure Numbers:

[0043] 10. Multi-beam laser ranging radar; 20. Grain warehouse; 30. Grain stacking surface. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0047] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0048] Please see attached Figures 1 to 3 The present invention provides a method for measuring the loading mass of a grain warehouse, comprising the following steps:

[0049] S1, obtaining distance point cloud data measured by a multi-beam laser ranging radar 10, and preprocessing the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar 10 is installed on the top of the silo body of the grain silo 20, and is used to measure the distance between the silo and the grain stacking surface 30;

[0050] S2, determining an average stockpile height of the grain stockpile surface 30 according to the effective grain distance point cloud data;

[0051] S3, obtaining the designed volume of the grain silo 20, and determining the volume of the cavity above the grain stockpile surface 30 according to the average stockpile height, and determining the stockpile volume of the grain silo 20 according to the designed volume of the silo and the volume of the cavity;

[0052] S4, determining an average density of grains in the grain bin 20, and determining a loading mass of the grain bin 20 according to the stockpile volume and the average density of grains.

[0053] Specifically, since the light in the grain warehouse 20 is dim and a lot of dust is generated during the drying process, it is difficult to use visual measurement, while a laser radar with good penetration can achieve high-precision distance measurement at a long distance. At the same time, since the grain stacking surface 30 of the grain warehouse 20 will change during the stacking process, the height and shape of the grain stacking surface 30 will change. In order to more accurately determine the shape and height information of the grain stacking surface 30, the present application uses a multi-beam laser ranging radar 10 for measurement. The multi-line laser radar usually contains multiple laser transmitters and receivers. These transmitters can emit multiple laser beams simultaneously or sequentially, and the receiver is responsible for receiving the echo signals of these laser beams after being reflected by the object. Through the emission and reception of multiple laser beams, as well as distance measurement, the multi-line laser radar can obtain three-dimensional point cloud data of the surrounding environment. These point cloud data contain information such as the position, shape and distance of the object, which can be used to construct a three-dimensional model of the environment.

[0054] like Figure 3 As shown, the multi-beam laser ranging radar 10 is installed on the top of the grain silo 20. It emits multiple laser beams downward. After hitting the grain pile surface 30, the laser beams will be reflected back. The radar receives these reflected signals. The preprocessing step is to remove these noise data and obtain effective grain distance point cloud data. By analyzing the effective grain distance point cloud data, the average stockpile height of the grain pile surface 30 can be calculated.

[0055] The designed volume in the silo is a fixed value determined when the grain silo 20 is designed, which represents the maximum volume of the silo body. The cavity volume above the grain pile surface 30 can be calculated based on the average pile height. The actual volume of the grain pile can be obtained by subtracting the cavity volume from the designed volume in the silo.

[0056] The average density of grains can be determined by experimental measurement or based on empirical data or by the implementation method described below; the loading mass can be calculated by multiplying the stockpile volume by the average density of grains to obtain the loading mass of the grain bin 20.

[0057] The multi-beam laser ranging radar 10 of the present application can provide high-precision distance measurement, thereby ensuring accurate calculation of the height and volume of the grain pile. The present application scheme does not require direct contact with the grain pile, avoiding potential safety hazards and errors in traditional measurement methods, and also solves the problem that visual equipment is difficult to use due to dim light in the grain bin 20; the entire measurement process can be automated, reducing human intervention, and can be measured in real time according to changes in the grain in the bin, thereby improving measurement efficiency and accuracy; the present application can grasp the loading status of the grain in real time, and can help determine the drying status in a timely manner.

[0058] As a preferred implementation, the step S1 of preprocessing the distance point cloud data to obtain effective grain distance point cloud data specifically includes the following steps:

[0059] S11, obtaining the point cloud with the largest height value in the distance point cloud data as a reference point cloud, and constructing a reference horizontal plane with the reference point cloud;

[0060] S12, taking the point where the laser beam emission point of the multi-beam laser ranging radar 10 is vertically projected to the reference horizontal plane as the center of the circle, taking the reference point cloud to the center of the circle as the radius, and taking the center of the circle to the laser beam emission point as the central axis to construct a cylindrical space;

[0061] S13, eliminating distance point cloud data outside the cylindrical space;

[0062] S14, filtering the remaining distance point cloud data to obtain filtered distance point cloud data and using the filtered distance point cloud data as effective grain distance point cloud data.

[0063] Specifically, from the original distance point cloud data, the point cloud with the largest height value is selected as the reference point cloud. It can be understood that, combined with the shape of a large number of grain pile surfaces 30, it can be known that the reference point cloud will basically be located at the lowest point on the edge of the grain pile surface 30 (the maximum value for the multi-beam laser ranging radar 10), that is, the intersection with the warehouse wall. Based on the reference point cloud, a reference horizontal plane is constructed, and this horizontal plane represents the lowest horizontal position of the grain pile surface 30.

[0064] For the laser beam emission point of the multi-beam laser ranging radar 10, it is vertically projected onto the reference horizontal plane to obtain the projection point. With the projection point as the center of the circle, the distance from the reference point cloud to the corresponding center point as the radius, and the line from the center of the circle to the laser beam emission point as the central axis, a cylindrical space is constructed. The cylindrical space is the upper space corresponding to the grain stacking surface 30.

[0065] The distance point cloud data outside the cylindrical space are eliminated. The point cloud data outside the cylindrical space may be the distance point cloud data corresponding to the silo wall and have nothing to do with the measurement of the grain stacking surface 30 .

[0066] The remaining distance point cloud data is filtered to remove noise and unnecessary details. For example, a straight-through filter can be set to remove unnecessary data, and a radius filter can be set to filter outliers according to the number of adjacent points within the radius range of the spatial point.

[0067] The preprocessed effective grain distance point cloud data of this embodiment more accurately reflects the actual situation of grain piles, and provides a reliable basis for subsequent pile height, volume and quality measurements.

[0068] As a preferred implementation, step S2 specifically includes the following steps:

[0069] S21, using the formula Determine the average grain pile height h of the grain pile surface 30 avg ; Where n is the number of point clouds in the effective grain distance point cloud data, Z i is the height value of the i-th valid grain distance point cloud data.

[0070] This embodiment can obtain an accurate average stockpile height by calculating the average value of the height values ​​of all valid grains from the point cloud data, thereby improving the final measurement accuracy.

[0071] As a preferred embodiment, determining the average density of grains in the grain bin 20 in step S4 specifically includes the following steps:

[0072] S41, obtain dry grain density;

[0073] S42, obtaining the average moisture content of grains;

[0074] S43, using formula Determine the wet density ρ of the grain, and use the wet density ρ as the average density of the grain; where ρ d is the dry grain density, H avg is the average moisture content of grains.

[0075] Specifically, dry grain density refers to the mass of dry grain per unit volume, usually expressed in kilograms per cubic meter (kg / m 3 ) or grams per cubic centimeter (g / cm 3 ) is widely used in agriculture, food processing, logistics and transportation. The density of dry grains can be measured in the laboratory, or by consulting existing standard documents or databases to obtain the standard density value of a specific grain variety. For example: wheat: about 700-800kg / m 3 , corn: about 650-720kg / m 3 , rice: about 600-700kg / m 3 ;

[0076] In order to obtain a more accurate average moisture content, multiple online moisture meters can be installed at different heights inside the grain bin 20. For example, according to the height of the dryer, several equally spaced height points (such as the top, middle and bottom) can be selected, and an online moisture meter can be installed at each height point.

[0077] As a preferred embodiment, the average moisture content H of the grains in step S42 is avg The specific steps are as follows:

[0078] Using formula Determine the average moisture content H of the grain avg ; Among them, H j is the moisture content measured by the jth online moisture meter, w j is the calculation weight corresponding to the jth online moisture meter, and m is the number of online moisture meters.

[0079] By installing multiple online moisture meters, real-time monitoring of grain moisture content at different heights, calculating the average moisture content of grains, and combining it with the known dry grain density, the average density of grains can be accurately determined, and then the total weight of grains can be calculated. This method not only improves the accuracy and reliability of measurement, but also adapts to the characteristics of grain moisture content changing with height.

[0080] Furthermore, the step S3 of determining the cavity volume above the grain pile surface 30 according to the average pile height specifically includes the following steps:

[0081] Using formula V g =V0-S*h avgDetermine the volume V of the cavity above 30° of the grain pile surface g ; Among them, the area above the grain stacking surface 30 is a constant diameter section, V0 is the designed volume in the warehouse, and S is the cross-sectional area of ​​the area above the grain stacking surface 30 of the grain warehouse 20.

[0082] The present invention also provides a device for measuring the loading amount of a grain bin 20, comprising:

[0083] A point cloud data acquisition unit is used to acquire distance point cloud data measured by the multi-beam laser ranging radar 10, and pre-process the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar 10 is installed on the top of the silo body of the grain silo 20, and is used to measure the distance between the silo and the grain stacking surface 30;

[0084] an average stockpile height determination unit, configured to determine an average stockpile height of a grain stockpile surface 30 according to the effective grain distance point cloud data;

[0085] A stockpile volume determination unit, used to obtain the designed volume of the grain silo 20, determine the cavity volume above the grain stockpile surface 30 according to the average stockpile height, and determine the stockpile volume of the grain silo 20 according to the designed volume of the silo and the cavity volume;

[0086] The loading mass determination unit is used to determine the average density of grains in the grain bin 20, and determine the loading mass of the grain bin 20 according to the stockpile volume and the average density of grains.

[0087] The present invention also provides a grain silo 20, comprising a silo body, and also comprising a multi-beam laser ranging radar 10 and a control system arranged on the top of the silo body, wherein the multi-beam laser ranging radar 10 is used to measure the distance to the grain stacking surface 30, and the multi-beam laser ranging radar 10 is connected to the control system, and the control system comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for measuring the loading mass of the grain silo 20 as described above are implemented.

[0088] The present invention further provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for measuring the loading mass of the grain silo 20 are implemented. It can be understood that when the computer program is executed by the processor, the method for measuring the loading mass of the grain silo 20 is implemented, and therefore all embodiments of the above method are applicable to the storage medium, and can achieve the same or similar beneficial effects.

[0089] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereto. Any equivalent structure or equivalent process transformation made by using the contents of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for measuring the loading mass of a grain silo, characterized in that: The following steps are involved: S1, obtaining distance point cloud data measured by a multi-beam laser ranging radar, and preprocessing the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar is installed on the top of the silo body of the grain silo to measure the distance between the silo and the grain stacking surface; S2, determining an average stockpile height of the grain stockpile surface according to the effective grain distance point cloud data; S3, obtaining the designed volume of the grain silo, determining the volume of the cavity above the grain stockpile surface according to the average stockpile height, and determining the stockpile volume of the grain silo according to the designed volume of the silo and the volume of the cavity; S4, determining an average density of grains in the grain bin, and determining a loading mass of the grain bin according to the stockpile volume and the average density of grains.

2. The method for measuring the loading mass of a grain silo according to claim 1, characterized in that: The step S1 of preprocessing the distance point cloud data to obtain effective grain distance point cloud data specifically includes the following steps: S11, obtaining the point cloud with the largest height value in the distance point cloud data as a reference point cloud, and constructing a reference horizontal plane with the reference point cloud; S12, taking the point where the laser beam emission point of the multi-beam laser ranging radar is vertically projected to the reference horizontal plane as the center of the circle, taking the reference point cloud to the center of the circle as the radius, and taking the center of the circle to the laser beam emission point as the central axis to construct a cylindrical space; S13, eliminating distance point cloud data outside the cylindrical space; S14, filtering the remaining distance point cloud data to obtain filtered distance point cloud data and using the filtered distance point cloud data as effective grain distance point cloud data.

3. The method for measuring the loading mass of a grain silo according to claim 2, characterized in that: The step S2 specifically includes the following steps: S21, using the formula Determine the average grain pile height h avg ; Where n is the number of point clouds in the effective grain distance point cloud data, Z i is the height value of the i-th valid grain distance point cloud data.

4. The method for measuring the loading mass of a grain silo according to claim 3, characterized in that: Determining the average density of grains in the grain bin in step S4 specifically includes the following steps: S41, obtain dry grain density; S42, obtaining the average moisture content of grains; S43, using formula Determine the wet density ρ of the grain, and use the wet density ρ as the average density of the grain; where ρ d is the dry grain density, H avg is the average moisture content of grains.

5. The method for measuring the loading mass of a grain silo according to claim 4, characterized in that: The average moisture content H of the grains in step S42 avg The specific steps are as follows: Using formula Determine the average moisture content H of the grain avg ; Among them, H j is the moisture content measured by the jth online moisture meter, w j is the calculation weight corresponding to the jth online moisture meter, and m is the number of online moisture meters.

6. The method for measuring the loading mass of a grain silo according to claim 3, characterized in that: Determining the cavity volume above the grain pile surface according to the average pile height in step S3 specifically includes the following steps: Using formula V g =V0-S*h avg Determine the volume of the cavity above the grain pile surface V g ; Among them, the area above the grain stacking surface is a section of equal diameter, V0 is the designed volume in the bin, and S is the cross-sectional area of ​​the area above the grain stacking surface of the grain bin.

7. A device for measuring the loading amount of a grain silo, characterized in that: include: A point cloud data acquisition unit is used to acquire distance point cloud data measured by a multi-beam laser ranging radar, and pre-process the distance point cloud data to obtain effective grain distance point cloud data; wherein the multi-beam laser ranging radar is installed on the top of the silo body of the grain silo to measure the distance to the grain stacking surface; An average stockpile height determination unit, used to determine an average stockpile height of a grain stockpile surface according to the effective grain distance point cloud data; A stockpile volume determination unit, used to obtain the designed volume of the grain silo, determine the volume of the cavity above the grain silo surface according to the average stockpile height, and determine the stockpile volume of the grain silo according to the designed volume of the silo and the volume of the cavity; The loading mass determination unit is used to determine the average density of grains in the grain bin, and determine the loading mass of the grain bin according to the stockpile volume and the average density of grains.

8. A grain silo, comprising a silo body, characterized in that: It also includes a multi-beam laser ranging radar and a control system arranged on the top of the silo body, wherein the multi-beam laser ranging radar is used to measure the distance to the grain pile surface, the multi-beam laser ranging radar is connected to the control system, the control system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method for measuring the loading quality of a grain silo as described in any one of claims 1 to 6 are implemented.

9. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for measuring the loading mass of a grain silo as described in any one of claims 1 to 6 are implemented.

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