A grain silo clearing system control method

Abstract

The present invention relates to the field of intelligent warehouse clearing technology, specifically a method for controlling a warehouse clearing system for a grain silo, the method comprising the following steps: designing a silo data monitoring network based on the grain silo structure and stored grain properties, obtaining grain silo monitoring data through the silo data monitoring network; establishing a spatial motion analysis model based on the grain silo monitoring data, obtaining the spatial motion of a warehouse clearing robot based on the spatial motion analysis model and the grain silo monitoring data; constructing a warehouse clearing force prediction model based on the grain silo monitoring data, analyzing the optimal force required for the grain silo through the warehouse clearing force prediction model; and dynamically adjusting the grain warehouse clearing plan based on the spatial position, spatial motion, and optimal force of the warehouse clearing robot to ensure the smooth progress of the warehouse clearing process. The present invention dynamically adjusts the warehouse clearing plan based on the silo structure, grain properties, and machine motion, thereby improving work efficiency, reducing operating costs, and promoting technological progress.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent silo clearing, and in particular to a method for controlling a grain silo clearing system. Background Art

[0002] Traditional methods for clearing grain silos rely heavily on manual labor or simple mechanical equipment, resulting in low efficiency, high labor intensity, high safety risks, and significant grain losses. Manual clearing requires significant human resources and is inefficient, resulting in a lengthy and time-consuming process. Furthermore, mechanical clearing can subject grain to physical damage, such as squeezing and collisions, which can degrade grain quality. Traditional methods are also poorly adaptable to different materials and struggle to meet the needs of clearing grain of varying types and conditions.

[0003] Grain silo clearing technology also needs to be transformed and upgraded towards intelligent and automated processes. Traditional silo clearing technology needs to be further optimized. Through intelligent control, clearing operations can be automated and continuous, improving efficiency and precisely controlling the clearing process. This will reduce physical damage and waste during the clearing process, protect grain quality, and provide strong support for the sustainable development of the grain storage industry. Summary of the Invention

[0004] In response to the shortcomings of existing methods and the needs of practical applications, in order to optimize traditional grain silo clearing technology, the present invention proposes an intelligent grain silo clearing method. This method utilizes advanced technologies such as the Internet of Things and artificial intelligence to achieve intelligent and automated upgrades to clearing operations. On the one hand, the present invention provides a grain silo clearing system control method, which includes the following steps: designing a silo data monitoring network based on the grain silo structure and stored grain properties, and obtaining grain silo monitoring data through the silo data monitoring network; establishing a spatial motion analysis model based on the grain silo monitoring data, and obtaining the spatial motion of a silo clearing robot based on the spatial motion analysis model and the grain silo monitoring data; constructing a silo clearing force prediction model based on the grain silo monitoring data, and analyzing the optimal force required for the grain silo through the silo clearing force prediction model; and dynamically adjusting the grain clearing plan based on the spatial position, spatial motion, and optimal force of the silo clearing robot to ensure the smooth progress of the clearing process. By designing a data monitoring network based on the grain silo structure and stored grain properties and dynamically adjusting the clearing plan, the present invention can improve silo clearing efficiency, reduce grain losses, and enhance operational safety, while also providing technical support for the transformation and upgrading of the grain storage industry.

[0005] Optionally, designing a silo data monitoring network based on the grain silo structure and stored grain properties, and obtaining grain silo monitoring data through the silo data monitoring network includes: designing a silo data monitoring network based on the grain silo structure and stored grain properties, the silo data monitoring network including temperature and humidity sensors, laser ranging sensors, dust concentration sensors, wireless cameras, and smoke alarms; and monitoring the grain status and environmental parameters in the silo through the silo data monitoring network to obtain the grain silo monitoring data. The present invention accurately measures key parameters such as temperature and humidity within the silo, as well as grain stacking height, using high-precision sensors, providing accurate data support for subsequent grain management and warehouse clearance operations.

[0006] Optionally, establishing a spatial motion analysis model based on the grain silo monitoring data includes: introducing three-dimensional analysis technology, combining the three-dimensional analysis technology with the grain silo monitoring data to analyze the center of gravity position of the warehouse-clearing robot; and establishing the spatial motion analysis model based on the warehouse-clearing robot's characteristics and the center of gravity position. The present invention integrates multiple technologies, such as three-dimensional analysis technology, sensor technology, and robotics technology, into the spatial motion analysis model, promoting the development of the grain storage industry towards intelligent and automated development.

[0007] Optionally, the spatial motion analysis model satisfies the following relationship:

[0008]

[0009] in, represents the spatial motion coordinate system of the warehouse cleaning robot, Represents the x-axis of the center-of-gravity vector coordinate system of the warehouse cleaning robot, Represents the y-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the z-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the rotation transformation matrix of the x-axis of the clearance robot, Represents the rotation transformation matrix of the y-axis of the clearance robot, Represents the rotation transformation matrix of the z-axis of the warehouse cleaning robot, Represents the parameters of a homogeneous coordinate system. This invention decomposes the motion of a warehouse cleaning robot into rotation and displacement along three axes and uses a rotation transformation matrix to accurately analyze the robot's motion state, reducing errors and uncertainties in the robot's motion and improving the accuracy of warehouse cleaning operations.

[0010] Optionally, constructing a clearance force prediction model based on the grain silo monitoring data includes: establishing a machine traction force analysis function based on the grain silo monitoring data; constructing a clearance interaction force prediction function based on the grain silo monitoring data; and constructing a clearance force prediction model based on the machine traction force analysis function and the clearance interaction force prediction function. The present invention utilizes grain silo monitoring data to more accurately reflect the interaction between machinery and grain during the clearance process, facilitates the construction of a more accurate clearance force prediction model, and improves the feasibility of prediction results.

[0011] Optionally, the clearance interaction force prediction function satisfies the following relationship:

[0012]

[0013] in, represents the interaction force between the cleaning robot and the silo environment, represents the environmental stiffness of the silo, Indicates the damping parameter of the x-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearing robot in the x-axis direction, Indicates the movement position of the x-axis of the clearance robot space, Indicates the damping parameter of the y-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearance robot in the y-axis direction, Indicates the movement position of the clearance robot on the y-axis space, Indicates the damping parameters of the cleaning robot in the z-axis direction and the silo environment, Indicates the end position of the clearance robot in the z-axis direction, The proposed warehouse clearance interaction force prediction function comprehensively considers multiple factors to predict the interaction force between the robot and the silo environment, providing strong support for optimizing operation strategies, improving operation efficiency, enhancing system stability, and promoting intelligent development.

[0014] Optionally, the clearance force prediction model satisfies the following relationship:

[0015]

[0016] in, represents the optimal force of the warehouse cleaning robot, represents the environmental stiffness of the silo, Represents the center of gravity vector coordinate system of the warehouse cleaning robot, represents the desired coordinate system of the center of gravity of the warehouse cleaning robot, represents the inertia coefficient of the silo, represents the expected speed of the clearance robot, Indicates the actual movement speed of the clearance robot, represents the expected acceleration of the clearance robot, Indicates the actual motion acceleration of the clearance robot, represents the interaction force between the cleaning robot and the silo environment, The minimum force required to pull a warehouse-clearing robot is represented by a model. This paper calculates the optimal force required to pull a warehouse-clearing robot, ensuring the robot operates optimally during operation. This helps reduce grain loss, mechanical wear, and operational errors caused by improper force.

[0017] Optionally, dynamically adjusting the grain clearance scheme based on the spatial position, spatial motion, and optimal force of the clearance robot includes presetting a grain clearance time based on the grain silo structure and stored grain properties, and dividing the grain clearance time into multiple time intervals. Dividing the clearance time into multiple time intervals allows for more precise planning and management of clearance operations, ensuring the robot operates in optimal conditions and improving clearance efficiency.

[0018] Optionally, dynamically adjusting the grain clearing plan based on the clearing robot's spatial position, spatial motion, and optimal force includes updating the clearing robot's spatial position, spatial motion, and optimal force in real time based on the multiple time intervals and grain silo monitoring data to achieve dynamic adjustment of the grain clearing plan. The present invention updates the clearing robot's spatial position, spatial motion, and optimal force in real time, enabling the system to rapidly respond to environmental changes within the silo, ensuring flexibility and accuracy in clearing operations, enhancing system stability and intelligence, and providing strong support for the sustainable development of the grain storage industry.

[0019] On the second aspect, in order to efficiently execute the grain silo clearing system control method provided by the present invention, the present invention also provides a grain silo clearing system, including a processor, an input device, an output device and a memory, the processor, input device, output device and 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 the grain silo clearing system control method described in the first aspect of the present invention. The grain silo clearing system of the present invention has a compact structure and stable performance, and can stably execute the grain silo clearing system control method provided by the present invention, thereby improving the overall applicability and practical application capabilities of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of the grain silo clearing system control method of the present invention;

[0021] Figure 2 A vector diagram of the center of gravity position of a grain silo cleaning robot in the grain silo cleaning system control method of the present invention;

[0022] Figure 3 Schematic diagram of the rotation of different axes of a cleaning robot in the grain silo cleaning system control method of the present invention;

[0023] Figure 4 This is a structural diagram of the grain silo clearing system of the present invention. DETAILED DESCRIPTION

[0024] Specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the present invention. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details are not necessarily required to practice the present invention. In other instances, well-known circuits, software, or methods are not specifically described to avoid obscuring the present invention.

[0025] Throughout this specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "in one embodiment," "in an embodiment," "an example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples. Furthermore, those of ordinary skill in the art will appreciate that the figures provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0026] See Figure 1 The intelligent grain silo clearing technology of the present invention integrates the Internet of Things and artificial intelligence technologies to conduct all-round, high-precision real-time monitoring of the clearing robot. It can accurately analyze the spatial position, motion state, and force of the clearing robot, thereby promoting the development of intelligent and automated clearing operations. The present invention provides a grain silo clearing system control method, which includes the following steps:

[0027] S1. Design a silo data monitoring network based on the grain silo structure and stored grain properties. Obtain grain silo monitoring data through the silo data monitoring network. The specific implementation steps and contents are as follows:

[0028] In this embodiment, a silo data monitoring network is designed based on the grain silo structure and stored grain properties. In this embodiment, the silo data monitoring network mainly includes: temperature and humidity sensors, laser ranging sensors, dust concentration sensors, wireless cameras, and smoke alarms. The silo data monitoring network monitors the grain status and environmental parameters in the silo to obtain grain silo monitoring data. The specific implementation content is as follows:

[0029] To monitor and accurately acquire grain silo data in real time, the example first conducts an on-site survey of the silo's physical structure, including but not limited to its structural layout, specific dimensions, and construction materials. The stored grain types are also classified, and their inherent properties, such as moisture absorption, flammability, and hardness, are analyzed. These properties directly influence the setting of monitoring parameters and the selection of sensors.

[0030] Based on the grain silo structure and the properties of stored grain, the core points and accuracy standards of the monitoring work are clarified. That is, it is necessary to accurately capture and record in real time the changes in temperature and humidity in the silo, the real-time height of grain stacking, the fluctuations in dust concentration in the air, and ensure the safety of grain through visual monitoring. At the same time, attention should be paid to the fire warning function to ensure the safety and stability of grain storage.

[0031] Based on this design, the silo data monitoring network can not only reasonably arrange various sensors, but also ensure that the data monitoring network can closely meet actual needs and realize efficient and accurate intelligent monitoring of grain silos.

[0032] Then the monitoring network equipment was designed and selected, which mainly included temperature and humidity sensors, laser ranging sensors, dust concentration sensors, wireless cameras and smoke alarms.

[0033] Select appropriate temperature and humidity sensors based on the size of the silo and the type of grain to ensure comprehensive coverage and accurate data. Sensors should be installed at different heights and locations in the silo to obtain more comprehensive environmental data and conduct real-time monitoring of environmental parameters. This can accurately capture and record changes in the silo environment in real time, helping to adjust storage conditions in a timely manner and prevent temperature and humidity fluctuations from adversely affecting grain quality.

[0034] The laser ranging sensor needs to be installed on the top of the silo or other appropriate location to measure the grain stacking height, which is conducive to monitoring the grain storage volume. It can also achieve continuous monitoring of the grain stacking height through other non-contact measurement technologies to ensure accurate grasp of the grain storage volume and prevent structural safety hazards caused by excessive stacking.

[0035] Given that a large amount of dust is generated during grain processing, dust concentration sensors need to be configured in the silo data monitoring network to monitor changes in dust concentration in the silo air in real time, issue timely warnings and take measures to reduce dust concentration, while reducing the risk of dust explosions. This is conducive to monitoring and issuing warnings of dust exceeding the standard and ensuring operational safety.

[0036] In an optional embodiment, to ensure the safety of grain clearance operations and the working environment, the dust concentration monitoring sensor in the silo data monitoring network can continuously detect changes in dust concentration in the air inside the silo. Once an abnormal increase in concentration is detected, the early warning mechanism is immediately triggered to remind management personnel to respond quickly and take effective measures, such as ventilation, sprinkling water to reduce dust, etc., to reduce the dust concentration in the silo, thereby significantly reducing the risk of explosion caused by dust accumulation. This not only helps to accurately monitor and prevent dust concentration from exceeding the standard, but also is an important barrier to the safety of personnel on the job site and the protection of production facilities.

[0037] High-definition wireless cameras are installed inside and around the silo to achieve all-weather video surveillance, which is convenient for remote monitoring and recording of abnormal situations. In the embodiment, a high-definition video monitoring system is equipped, combined with intelligent image recognition technology, to monitor the status of grain in the silo around the clock and without blind spots. It can promptly detect and report abnormal situations such as grain mildew and insect pests, thereby ensuring the quality and safety of grain in the warehouse.

[0038] Smoke alarms can effectively prevent fires. Smoke alarms are installed in silos. Once smoke is detected, they will sound an alarm immediately and work in conjunction with the fire protection system. Furthermore, a fire warning system with integrated smoke alarms, temperature anomaly monitoring, and flame identification functions can be established to ensure that an alarm can be sounded in the early stages of a fire. This can be combined with automatic fire extinguishing devices or emergency evacuation plans to minimize fire losses.

[0039] In the embodiment, various sensors and intelligent devices are scientifically arranged to build an all-round, multi-level, high-precision silo data monitoring network, which can not only reflect the environmental conditions and grain status in the silo in real time, but also identify potential risks in advance through data analysis and early warning mechanisms, providing solid protection for the safe storage of grain silos.

[0040] Furthermore, various sensors must be properly arranged and installed. The sensor installation locations and quantity should be planned based on the silo structure and monitoring requirements. Sensors and equipment should be installed according to the design plan to ensure stability and reliability while avoiding interference with grain storage. Furthermore, these sensors and equipment should be provided with a stable power supply and equipped with a reliable wireless communication network, such as Wi-Fi and LoRa, to ensure real-time transmission of monitoring data to the intelligent warehouse clearance system's data storage center.

[0041] The grain silo monitoring data is obtained through the above-mentioned silo data monitoring network.

[0042] The silo data monitoring network can capture and aggregate monitoring data from various sensors in real time. The data comprehensively covers the environmental status and grain conditions in the grain silo. In order to efficiently process the monitoring data, the grain silo intelligent clearance system integrates advanced data acquisition and reception modules. The modules can seamlessly connect to various sensors to achieve unified reception and immediate processing of monitoring data.

[0043] In the embodiment, a grain silo data monitoring network is constructed, which not only ensures the accuracy and timeliness of the monitoring data, but also analyzes the data to reveal potential problems and optimization space in the grain storage process, providing data support for the safe storage and scientific management of grain, enabling grain managers to make more scientific and reasonable decisions based on real-time and accurate data, thereby further improving the efficiency and safety of grain storage.

[0044] Furthermore, the specific steps and methods for obtaining grain silo monitoring data in this embodiment are merely an optional condition of the present invention. In one or some other embodiments, the information acquisition method can be optimized according to the actual situation of the grain silo and the data collection requirements. Different grain silos have different structural characteristics, storage conditions or monitoring requirements. Through customized information acquisition methods, it is possible to better adapt to actual differences and ensure the practicality and effectiveness of the data monitoring network.

[0045] S2. Establish a spatial motion analysis model based on the grain silo monitoring data in step S1, and obtain the spatial motion of the warehouse cleaning robot based on the spatial motion analysis model and the grain silo monitoring data. The specific implementation steps and contents are as follows;

[0046] First, we introduced 3D analysis technology and combined it with grain silo monitoring data to analyze the center of gravity of the warehouse-clearing robot. The specific details are as follows:

[0047] In step S1, we obtain monitoring data for the grain silo, including but not limited to silo temperature and humidity, grain stack height, silo dust concentration, visual monitoring images, and possible fire warning information. Next, we analyze the spatial motion of the warehouse-clearing robot based on this silo monitoring data and using 3D analysis technology.

[0048] First, the grain silo monitoring data was filtered. Data directly related to the warehouse-clearing robot's movements, such as the robot's position coordinates, attitude angle, and rotation, was selected from the monitoring data. Outliers, missing values, and erroneous data were further removed to ensure the quality of the analyzed data. Furthermore, the data was formatted to a format suitable for 3D analysis.

[0049] During the spatial motion analysis, the embodiment utilized 3D analysis technology. Based on the actual dimensions and structure of the grain silo, a 3D model was constructed using 3D modeling software, ensuring a high degree of fidelity within the virtual environment. Simultaneously, a 3D digital model of the warehouse-clearing robot was created based on its design parameters. This model not only encompassed the robot's external form but also, to the greatest extent possible, captured key information such as its internal structure and weight distribution, enabling a more accurate simulation of the robot's motion characteristics.

[0050] To achieve seamless integration and efficient analysis, the 3D models of the grain silo and the cleaning robot were integrated into the same coordinate system. This ensured that their relative positions, orientations, and proportions in 3D space accurately matched those of the silo and robot, avoiding analytical errors caused by coordinate mismatches. This also enabled precise positioning and dynamic simulation of the cleaning robot within the grain silo, providing a solid foundation for subsequent analysis of the robot's spatial motion, cleaning path optimization, and potential collision prediction.

[0051] In one optional embodiment, a series of assumptions and settings are made regarding the operating state of the warehouse-clearing robot within the grain silo. To simplify the grain silo model and improve analysis efficiency, the warehouse-clearing robot is considered a rigid body system. This means that during movement, no deformation occurs between its guide wheels, drive wheels, supporting rollers, and tracks. Longitudinal and lateral slippage of the tracked running gear is also ignored. Furthermore, it is assumed that the center of gravity of the warehouse-clearing robot completely coincides with the geometric center of the tracked running gear, and that the instantaneous center of rotation of each track is precisely located at the center of the contact surface with the grain, ensuring uniform resistance and evenly distributed ground pressure across the track.

[0052] To more intuitively demonstrate the overall working conditions and structural details of the warehouse clearance robot, the examples used software tools to construct a three-dimensional digital model of the robot. This model not only reflects the robot's appearance but also includes its various characteristic parameters, laying the foundation for subsequent warehouse clearance control. Considering the pressure and resistance that the warehouse clearance robot must withstand during operation, the examples set clear requirements for the strength and rigidity of the robot's mechanical arm. Based on these requirements, specific material parameters such as alloy steel were selected, including but not limited to constant elastic modulus, Poisson's ratio, and density, to ensure the structural stability of the warehouse clearance robot.

[0053] The warehouse cleaning robot can accurately transport stored grain to the target location along a predetermined route. To achieve the above-mentioned warehouse cleaning goals, the warehouse cleaning robot in the embodiment has five degrees of freedom, including support movement, up and down movement, lower rotation, working telescopic movement (translational movement), and shovel movement (translational movement). However, in actual operation, the support movement and up and down movement are relatively static with respect to the telescopic arm, so the above two degrees of freedom can be ignored when describing the working state of the warehouse cleaning robot. Therefore, the main focus is on the remaining three degrees of freedom: lower rotation, working telescopic movement (translational movement), and shovel movement (translational movement), which together determine the working trajectory and movement form of the warehouse cleaning robot.

[0054] In order to accurately describe the motion position and shape of the warehouse cleaning robot, mathematical concept models such as vectors, planes, and coordinates are introduced in the embodiment. Based on this, the relative relationship between the support arm, coal shovel, and working arm can be analyzed more scientifically, thereby providing strong information support for the motion control and optimization of the warehouse cleaning robot. The vector diagram of the center of gravity position of the warehouse cleaning robot can be found in Figure 2 , where X, Y, and Z represent the x-axis, y-axis, and z-axis in the vector coordinate system, respectively; O represents the origin of the vector coordinate system; A represents the center of gravity of any one of the cleaning robots in the grain silo; and hx, hy, and hz represent the corresponding x-axis, y-axis, and z-axis in the center of gravity vector coordinate system of the cleaning robot, respectively.

[0055] based on Figure 2 It can be seen that after clarifying the vector coordinate system, any point in space can be accurately located by a unique position vector. The position vector can be mathematically expressed as a column vector, which contains the displacement components of any point in the coordinate system along the directions of each coordinate axis. For any point in the coordinate system, its position vector is not only a geometric description, but also contains rich physical meanings, including but not limited to the direction and distance of the point relative to the coordinate origin.

[0056] Furthermore, the center of gravity position of the warehouse-clearing robot is analyzed in the embodiment. The center of gravity position serves as a balance point of the distribution of the warehouse-clearing robot, and its position vector satisfies a specific physical relationship. Specifically, the center of gravity position vector is the weighted average of the mass of each part of the warehouse-clearing robot and its corresponding position vector, and the weight is the mass of each part, reflecting the close connection between the center of gravity position and the mass distribution of the object.

[0057] Therefore, the position of any point in space can be uniquely determined by a position column vector. The center of gravity position vector of the warehouse cleaning robot is the product of the position vectors of each particle of the warehouse cleaning robot and their mass, divided by the total mass of the object. The above relationship deeply reveals the mathematical and physical connection between the center of gravity position and the mass distribution of the object. In the embodiment, the center of gravity position vector of the warehouse cleaning robot satisfies the following relationship:

[0058]

[0059] in, Represents the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the x-axis of the center-of-gravity vector coordinate system of the warehouse cleaning robot, Represents the y-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the z-axis of the center of gravity vector coordinate system of the warehouse cleaning robot.

[0060] In a warehouse cleaning robot's center-of-gravity vector coordinate system, axis directions have specific meanings that are closely related to the robot's design, function, and operating environment. Axis directions vary depending on the warehouse cleaning robot model and application scenario. The examples are described based on the principles of a general robot coordinate system.

[0061] The x-axis of the center of gravity vector coordinate system of the warehouse cleaning robot refers to the working extension (translation) direction of the warehouse cleaning robot. The positive direction of the x-axis points to the main path of the robot's working arm when performing extension and translation movements. When the robot performs cleaning tasks, such as reaching into other grain material warehouses for cleaning, the main motion trajectory of its working arm will be along the x-axis, which means that the positive direction of the x-axis points to the main path when the robot performs the main extension or translation movement. This helps to more accurately describe and calculate the robot's movement in the control system, and thus can accurately control the extension and retraction length and position of components such as the robot's working arm or shovel.

[0062] The y-axis of the warehouse cleaning robot's center of gravity vector coordinate system refers to the direction of the robot's shovel's translational motion. The positive y-axis indicates the primary direction of the shovel's translational, or linear, motion. This means that when the robot performs cleaning tasks, such as scooping up grain and moving it, the shovel's primary motion trajectory will be along the y-axis. In a warehouse cleaning robot's operating scenario, the shovel's translational motion is one of the key actions required to complete the task. Setting the shovel's motion direction along the y-axis of the coordinate system helps to more intuitively represent and control the robot's key actions within the control system.

[0063] The z-axis of the warehouse cleaning robot's center of gravity vector coordinate system refers to the robot's downward rotation direction. In this coordinate system, the z-axis represents the robot's primary rotation axis around its base or a fixed point. This helps accurately describe and calculate the robot's motion and rotational movements in three-dimensional space. The positive direction of the z-axis points in the robot's upward motion, facilitating adjustments to the angle, height, or position of the working arm or shovel.

[0064] In three-dimensional space, the x-, y-, and z-axes together form the coordinate system of the warehouse cleaning robot. The x- and y-axes represent the two primary directions of motion in the horizontal plane, while the z-axis represents rotation or translation in the vertical direction. This three-dimensional coordinate system allows the warehouse cleaning robot to accurately locate and navigate in complex working environments. It helps accurately describe and calculate the warehouse cleaning robot's posture and rotational movements in three-dimensional space, thereby improving the robot's flexibility and accuracy in performing cleaning tasks. In actual applications, this setting method needs to be refined and adjusted according to the specific model of the warehouse cleaning robot, the working scenario, and the task requirements.

[0065] Then, a spatial motion analysis model is established based on the characteristics of the warehouse cleaning robot and the center of gravity position of the warehouse cleaning robot. The specific content is as follows:

[0066] In order to better identify the center of gravity of the warehouse cleaning robot and understand the stability of the robot in different postures, it is necessary to comprehensively consider factors such as the physical structure, kinematic characteristics, dynamic characteristics and working environment of the warehouse cleaning robot. The force balance and torque balance conditions of the warehouse cleaning robot are different in different postures and motion states. The warehouse cleaning robot has different working environments in different granaries. Establishing a spatial motion analysis model is conducive to the subsequent analysis of the relationship between its motion and force, the accessible working space of the warehouse cleaning robot in a specific working environment, and considering how to optimize its motion path to improve the efficiency of the warehouse cleaning work.

[0067] When describing the spatial motion of a warehouse cleaning robot, it is not enough to simply use a position vector to represent the position of its center of gravity. In order to fully describe the range of motion of the warehouse cleaning robot in different directions, it is necessary to introduce a spatial motion coordinate system and combine it with a rotation matrix to represent the motion of the warehouse cleaning robot in each axis. Based on the above implementation, it can be seen that in the center of gravity vector coordinate system of the warehouse cleaning robot, the x-axis represents the working extension (translational) direction of the warehouse cleaning robot, the y-axis represents the shovel movement (translational) direction of the warehouse cleaning robot, and the z-axis represents the lower rotation direction of the warehouse cleaning robot. Further consideration is given to the rotation of each axis of the warehouse cleaning robot. For details on the rotation of each axis of the warehouse cleaning robot in the embodiment, please refer to Figure 3 ,in They represent the rotation angles of the x-axis, y-axis, and z-axis of the cleaning robot respectively. X, Y, and Z represent the x-axis, y-axis, and z-axis in the vector coordinate system respectively. O represents the origin of the vector coordinate system. A represents the center of gravity of any cleaning robot in the grain silo.

[0068] The rotation angle of the x-axis of the clearing robot is , the rotation transformation matrix of the x-axis of the clearing robot satisfies the following relationship;

[0069]

[0070] in, Represents the rotation transformation matrix of the x-axis of the clearance robot, Indicates the rotation angle of the x-axis of the clearance robot.

[0071] Similarly, in the embodiment, the warehouse cleaning robot can also rotate around the y-axis and z-axis respectively. The rotation angle of the y-axis of the warehouse cleaning robot is , the rotation transformation matrix of the y-axis of the warehouse cleaning robot satisfies the following relationship:

[0072]

[0073] in, Represents the rotation transformation matrix of the y-axis of the clearance robot, Indicates the rotation angle of the y-axis of the clearance robot.

[0074] The rotation angle of the z-axis of the warehouse cleaning robot is , the rotation transformation matrix of the z-axis of the warehouse cleaning robot satisfies the following relationship:

[0075]

[0076] in, Represents the rotation transformation matrix of the z-axis of the warehouse cleaning robot, Indicates the rotation angle of the z-axis of the cleaning robot.

[0077] Based on these conditions and related information, a spatial motion analysis model is established to obtain the spatial motion coordinate system of the warehouse cleaning robot. To describe the complete motion of the warehouse cleaning robot in space, the rotation matrices of each axis are combined to form a composite transformation matrix. This composite transformation matrix can transform the warehouse cleaning robot from its initial posture to any specified posture.

[0078] The above spatial motion analysis model satisfies the following relationship:

[0079]

[0080] in, represents the spatial motion coordinate system of the warehouse cleaning robot, Represents the x-axis of the center-of-gravity vector coordinate system of the warehouse cleaning robot, Represents the y-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the z-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the rotation transformation matrix of the x-axis of the clearance robot, Represents the rotation transformation matrix of the y-axis of the clearance robot, Represents the rotation transformation matrix of the z-axis of the warehouse cleaning robot, Represents the homogeneous coordinate system parameters.

[0081] Homogeneous coordinate system parameters refer to adding an extra dimension to a three-dimensional space to represent points or vectors in the original space. This method allows for flexible translation, rotation, and scaling of related position information. Homogeneous coordinate systems can further simplify the representation of geometric transformations. In traditional coordinate representation methods, translation transformations are usually represented by addition, while rotation and scaling transformations are represented by multiplication. However, in a homogeneous coordinate system, all transformations can be represented as matrix-vector multiplication operations, thus achieving unified representation and calculation of transformations, further allowing the representation of points at infinity and simplifying geometric transformations.

[0082] in, represents the homogeneous coordinate system, represents the parameters in the homogeneous coordinate system.

[0083] Based on the spatial motion analysis model and grain silo monitoring data, the spatial motion of the warehouse cleaning robot is obtained. The specific implementation content is as follows:

[0084] In this example, a spatial motion analysis model is used to capture and analyze the spatial motion of a warehouse-clearing robot within a grain silo. This model incorporates a composite transformation matrix, which not only unifies the representation of multiple spatial transformations, such as translation, rotation, and scaling, but also greatly simplifies motion analysis, enabling a more intuitive and efficient understanding of the robot's motion characteristics.

[0085] In this embodiment, a spatial motion analysis model is constructed based on real-time monitoring data of a grain silo, including but not limited to key parameters such as the silo's geometry, the location of internal obstacles, the grain's stacking state, and ambient humidity and temperature. This model is then used to simulate the motion of a warehouse-clearing robot. During this simulation, the robot's position and posture, combined with task requirements such as the cleaning path and coverage area, dynamically calculates each spatial transformation the robot will undergo during its mission. This ensures the robot's continuity and stability during movement.

[0086] The spatial motion analysis model clearly defines the movement trajectory and posture of the warehouse cleaning robot within the silo. This not only helps optimize the robot's motion strategy to avoid collisions with obstacles, but also ensures that the robot can complete cleaning tasks efficiently and accurately. Furthermore, based on real-time monitoring data, the spatial motion analysis model can be dynamically adjusted and optimized to adapt to changes in the silo's internal environment, further improving the accuracy and efficiency of warehouse cleaning operations.

[0087] The embodiment closely combines the spatial motion analysis model with the grain silo monitoring data, providing an efficient and accurate method to analyze and manage the spatial motion of the warehouse cleaning robot, and provides strong support for the automation and intelligent development of the grain storage industry.

[0088] Furthermore, in this embodiment, the analysis method of the movement of the warehouse-clearing robot is only an optional condition of the present invention. In one or some other embodiments, the robot movement analysis method can be replaced according to the robot operation characteristics and the actual situation of the granary. The analysis method can be regarded as an optional condition and flexibly adjusted according to specific scenarios and needs to ensure that the robot can better adapt to various complex environments and improve the overall operation efficiency and cleaning effect.

[0089] S3. Construct a clearing force prediction model based on the grain silo monitoring data in step S1, and analyze the optimal force required for the grain silo through the clearing force prediction model. The specific implementation steps and contents are as follows:

[0090] Based on the grain silo environment and the requirements of the silo cleaning operation, a series of key parameters are designed for the silo cleaning robot in the embodiment to ensure that it can complete the task efficiently and safely while being able to adapt to various environmental constraints.

[0091] First of all, from the perspective of physical size, the warehouse cleaning robot should have a flexible geometric size range, that is, the length should be as close as possible to half of the diameter of the grain silo, so that it can adapt to the storage conditions of the grain silo and can move and operate flexibly inside the silo.

[0092] In terms of operational capabilities, the warehouse-clearing robot is equipped with a shovel system. The shoveling force of each shovel needs to be set and adjusted according to the properties of the stored grain and the warehouse-clearing goals. This means that hard grains can be easily cleaned, and grains with poor hardness will not damage the quality and appearance of the grain.

[0093] The embodiment is equipped with a hydraulic system with a pressure of over 17 MPa, providing ample power for the blade and other mechanical movements. To support the warehouse cleaning robot and cope with various workloads, each support arm has a support force of at least 40 kilonewtons, ensuring the robot's stability and safety in various working postures.

[0094] In order to achieve more flexible operating movements, each swing hydraulic cylinder has the ability to rotate 180 degrees, which enables the warehouse cleaning robot to easily cope with various complex terrains and grain accumulation situations during the cleaning process.

[0095] The robot's winch system demonstrates impressive traction capabilities, ensuring it maintains stable motion while climbing slopes and turning. The winch also safely lifts the robot to the outside of the silo after the operation is complete.

[0096] In an optional embodiment, a machine traction force analysis function is established based on grain silo monitoring data.

[0097] When moving in the grain silo, the warehouse cleaning robot needs to overcome multiple external resistances including climbing resistance, rolling resistance, inertial resistance and turning resistance. Although air resistance can be ignored when the robot is traveling at low speed, other resistances are fully considered and optimized in this embodiment to ensure that the warehouse cleaning robot can complete its tasks stably and efficiently.

[0098] Among them, the inertial resistance, climbing resistance, friction resistance, and turning resistance of the warehouse cleaning robot are obtained based on the grain silo monitoring data. Based on this, the machine traction force analysis function is established, and it satisfies the following relationship:

[0099]

[0100] in, It represents the minimum traction force required by the warehouse cleaning robot when moving in the granary. It represents the inertial resistance of the cleaning robot when it moves in the granary. It represents the climbing resistance of the warehouse cleaning robot when it moves in the granary. It represents the friction resistance of the cleaning robot when it moves in the granary. It represents the turning resistance of the warehouse cleaning robot when it moves in the granary.

[0101] Inertial resistance is the force generated by the mass of the warehouse cleaning robot when accelerating or decelerating. Its magnitude is related to the mass, acceleration, and direction of the acceleration of the warehouse cleaning robot. The calculation formula satisfies the following relationship:

[0102]

[0103] in, It represents the inertial resistance of the cleaning robot when it moves in the granary. Indicates the quality of the clearance robot, Indicates the acceleration of the clearance robot.

[0104] Climbing resistance is the component of gravity that the warehouse cleaning robot needs to overcome when climbing uphill. Its magnitude depends on the slope and the weight of the warehouse cleaning robot. Its calculation formula satisfies the following relationship:

[0105]

[0106] in, It represents the climbing resistance of the warehouse cleaning robot when it moves in the granary. Indicates the quality of the clearance robot, represents the acceleration due to gravity, Indicates the slope angle of the warehouse cleaning robot.

[0107] Frictional resistance is the resistance generated when the cleaning robot contacts the stored objects in the silo or the ground. It depends on the friction coefficient between the robot and the stored objects or the ground, as well as the positive pressure exerted by the robot on the stored objects or the ground. The calculation formula satisfies the following relationship:

[0108]

[0109] in, It represents the friction resistance of the cleaning robot when it moves in the granary. represents the friction coefficient, Indicates the quality of the clearance robot, Represents the acceleration due to gravity.

[0110] Turning resistance is a relatively complex force that involves the lateral friction between the warehouse cleaning robot and the ground, as well as a possible centripetal force component. In this embodiment, it can be assumed that turning resistance is related to the warehouse cleaning robot's speed, turning radius, and the friction coefficient between the tire and the ground.

[0111] In another optional embodiment, a warehouse clearance interaction force prediction function is constructed based on grain silo monitoring data.

[0112] In complex warehouse environments, warehouse-clearing robots inevitably come into contact with grain silos or other stored materials while performing their tasks. This contact involves not only the transmission of physical forces but also dynamic interactions. Therefore, treating the warehouse-clearing robot as an independent controlled object and simply adjusting its internal parameters to control its stability often makes it difficult to cope with the changing external environment.

[0113] In this embodiment, the warehouse-clearing robot and its surroundings are considered a tightly connected, interactive dynamic system, enabling more comprehensive and effective control and adjustment of the warehouse-clearing plan. Within this dynamic system framework, real-time sensing of environmental parameter changes is required, enabling analysis of the interaction between the warehouse-clearing robot and its surroundings, which helps maintain the robot's stability and performance.

[0114] The warehouse cleaning robot and the environment are considered as a dynamic system, and advanced control algorithms and sensor technologies are used to construct a warehouse cleaning interaction force prediction function. The above warehouse cleaning interaction force prediction function satisfies the following relationship:

[0115]

[0116] in, represents the interaction force between the cleaning robot and the silo environment, represents the environmental stiffness of the silo, Indicates the damping parameter of the x-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearing robot in the x-axis direction, Indicates the movement position of the x-axis of the clearance robot space, Indicates the damping parameter of the y-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearance robot in the y-axis direction, Indicates the movement position of the clearance robot on the y-axis space, Indicates the damping parameters of the cleaning robot in the z-axis direction and the silo environment, Indicates the end position of the clearance robot in the z-axis direction, Indicates the movement position of the z-axis in the warehouse cleaning robot space.

[0117] Stiffness refers to the ability of a material or structure to resist elastic deformation when subjected to force. It is an indication of the ease with which a material or structure can deform elastically. The above-mentioned silo environmental stiffness refers to the ability of the grain silo structure itself and its surroundings, including the foundation, supporting structure, filling materials, etc., to resist deformation when subjected to external forces.

[0118] In the silo environment, the damping parameters are mainly related to the silo structure, filling materials, external environment, and the interaction between the cleaning robot and the silo. The size of the damping parameters will affect the dynamic response characteristics of the silo and the materials therein, and thus affect the operating efficiency and stability of the cleaning robot. The damping parameters of the different axis directions of the cleaning robot and the silo environment refer to the degree to which the motion state of the different axes of the cleaning robot will be affected by the damping of the silo environment when the different axis directions are moving. In the embodiment, the degree to which different axes are affected by the damping of the silo environment is taken into account when analyzing the cleaning robot, which is conducive to ensuring the motion stability and control accuracy of the cleaning robot.

[0119] The end positions of the warehouse cleaning robot along different axes refer to the farthest endpoints that the warehouse cleaning robot can reach along different axes within its granary workspace. These end positions are the extreme positions of the warehouse cleaning robot's end effector along different axes when performing the warehouse cleaning task.

[0120] The motion positions of the warehouse cleaning robot along different spatial axes refer to any position that the warehouse cleaning robot can reach within its workspace along directions parallel to different axes. These positions are any points on the trajectory of the warehouse cleaning robot's end effector along different axes while performing the warehouse cleaning task.

[0121] A clearance force prediction model is constructed based on the above-mentioned machine traction force analysis function and clearance interaction force prediction function.

[0122] In this embodiment, a final clearance force prediction model is constructed based on the traction force analysis function and the clearance interaction force prediction function when the clearance robot moves in the grain silo. The traction force analysis function and the interaction force prediction function are integrated into a unified model, which should be able to output the optimal force required by the clearance robot.

[0123] The above clearance force prediction model satisfies the following relationship:

[0124]

[0125] in, represents the optimal force of the warehouse cleaning robot, represents the environmental stiffness of the silo, Represents the center of gravity vector coordinate system of the warehouse cleaning robot, represents the desired coordinate system of the center of gravity of the warehouse cleaning robot, represents the inertia coefficient of the silo, represents the expected speed of the clearance robot, Indicates the actual movement speed of the clearance robot, represents the expected acceleration of the clearance robot, Indicates the actual motion acceleration of the clearance robot, represents the interaction force between the cleaning robot and the silo environment, Indicates the minimum force required to pull the warehouse cleaning robot.

[0126] The desired coordinate system for a warehouse-clearing robot's center of gravity involves factors such as the robot's position, posture, and stability within a specific warehouse-clearing task or silo environment. In this embodiment, this refers to a desired or pre-set coordinate system for stable and efficient warehouse-clearing robot operation within a specific warehouse-clearing task. This desired coordinate system accurately describes the position and orientation of the warehouse-clearing robot's center of gravity within the task space. This desired coordinate system is determined based on a variety of factors, including the silo's historical storage information, the robot's performance, and the characteristics of the stored goods.

[0127] The silo's moment of inertia is a physical quantity related to its structure, material, and stress state. It primarily reflects the silo's ability to resist changes in its state of motion when subjected to external forces. This moment of inertia measures the grain silo's ability to maintain its original rotational state or resist changes in rotational state during rotation. It is related to factors such as the silo's cross-sectional shape, size, material density, and mass distribution.

[0128] The optimal force required for the grain silo is analyzed through the above-mentioned clearance force prediction model.

[0129] When a warehouse-clearing robot performs a granary-clearing task, ensuring that the robot's actuators contact and act on the grain is both efficient and non-destructive is crucial. To achieve this, an optimal force control strategy is employed in this embodiment. This strategy uses a warehouse-clearing force prediction model to regulate the robot's contact force.

[0130] Based on the key parameters of the clearing force prediction model, it can be seen that the position of the clearing robot, the force, the target position and the silo environment are closely linked. Based on the mathematical model, the force acting on the grain is controlled and optimized to achieve fine adjustment of the force. This can effectively avoid damage to the robot or grain caused by excessive contact force and optimize the interaction process between the clearing robot and the grain in the silo.

[0131] Furthermore, the method for analyzing the optimal clearing force in this embodiment is only an optional condition of the present invention. In one or some other embodiments, the force analysis method can be optimized according to the storage conditions and clearing targets. Optimizing the force analysis method for specific clearing targets can more accurately control the force output during the clearing process, reduce ineffective operations and repetitive operations, and thus improve overall operating efficiency.

[0132] S4. Dynamically adjust the grain clearance plan based on the clearance robot's spatial position, spatial motion, and optimal force to ensure a smooth clearance process. The specific implementation steps and content are as follows:

[0133] First, the grain clearance time is preset based on the grain silo structure and the properties of the stored grain. The grain clearance time is divided into multiple time intervals, the specific contents of which are as follows:

[0134] During grain silo clearing operations, to more effectively manage the workflow and ensure completion of the clearing task, a reasonable grain clearing time needs to be preset based on the silo structure and stored grain properties. In this embodiment, the grain clearing time is preset by comprehensively considering various factors, such as grain type, density, fluidity, silo size and shape, and the performance of the clearing equipment.

[0135] Next, dividing the preset grain clearance time into multiple time intervals facilitates more precise control and management of the clearance process. Each time interval can be based on different operational phases or objectives, including but not limited to the grain silo preparation phase, the initial clearance phase, the main clearance phase, and the final phase. In this embodiment, dividing the grain clearance time into multiple time intervals and setting specific operational objectives and tasks for each interval allows for a more orderly and efficient grain clearance task. This also helps to promptly identify and resolve problems that arise during the clearance process, ensuring the smooth progress of the grain clearance work.

[0136] Then, the spatial position, spatial movement and optimal force of the cleaning robot are updated in real time based on multiple time intervals and grain silo monitoring data to achieve dynamic adjustment of the grain cleaning plan.

[0137] The preparation stage for grain clearance, as the starting point of the clearance process, focuses on the implementation and confirmation of various preparatory tasks, including but not limited to the comprehensive inspection and commissioning of clearance equipment to ensure that it operates in the best condition. The above stage does not directly involve grain cleaning, but mainly lays the foundation for subsequent grain clearance operations.

[0138] The initial clearance phase begins with the robot's initial contact with the grain, as it slowly enters the silo. During this phase, particular attention is paid to controlling the contact force between the robot and the grain. Based on the silo structure, the stored grain properties, and a clearance force prediction model, the robot's motion parameters are precisely adjusted to ensure the appropriate force. The robot's operating position is closely monitored, ensuring that the grain flow is effectively promoted while minimizing damage caused by the clearance process. Furthermore, based on the initial reaction and flow of the grain, the effectiveness of the clearance plan is preliminarily evaluated, providing a reference for subsequent adjustments.

[0139] The main cleaning phase, the main part of the cleaning operation, occupies the majority of the operation time. During this phase, the cleaning robot continuously operates, gradually clearing the grain from the silo according to the established cleaning plan and preset path. To improve operational efficiency and effectiveness, it is necessary to monitor the grain accumulation pattern, fluidity, and robot performance characteristics in real time. Based on the cleaning operation goals and tasks, the cleaning robot's applied force and spatial motion position are monitored and dynamically adjusted in real time to ensure that the robot always maintains optimal working condition and efficiently completes the cleaning task.

[0140] Once the majority of the grain in the silo has been cleared, the final phase begins. The primary task of this phase is to thoroughly remove any remaining grain and impurities from the silo, ensuring its cleanliness and sanitation. Simultaneously, the silo cleaning robot undergoes a comprehensive inspection and maintenance to prepare for the next operation. Furthermore, a summary and evaluation of the silo cleaning mission is conducted to lay a solid foundation for subsequent grain storage and management efforts.

[0141] In this embodiment, a grain silo clearing system control method is proposed, and a data monitoring network is designed based on the specific structure of the grain silo and the inherent properties of the stored grain. The above-mentioned monitoring network can capture and transmit various key data inside the silo in real time, providing a solid information foundation for subsequent management decisions and clearing plans.

[0142] Based on the collected grain silo monitoring data, a spatial motion analysis model was constructed to accurately depict the real-time position, motion trajectory and dynamic changes of the warehouse-clearing robot in the silo. This process not only helps to understand the robot's motion state, but also provides a scientific basis for optimizing the intelligent warehouse-clearing process.

[0143] At the same time, a clearance force prediction model was further constructed using monitoring data. The prediction model can comprehensively consider factors such as the physical properties of the grain, the stacking status, and the operating parameters of the robot, and predict the optimal force required in different operation stages. This is of great significance for guiding the clearance robot to adjust the operation intensity and avoid grain damage.

[0144] Ultimately, by understanding the robot's spatial position, motion, and optimal force at different times, the grain clearing plan was dynamically adjusted. This process fully demonstrates the advantages of intelligent management, enabling flexible responses to various changing factors based on actual conditions to ensure the clearing process remains optimal. Continuous monitoring and adjustment not only improves clearing efficiency and quality, but also effectively reduces operational risks and costs, bringing greater convenience and benefits to grain storage and management.

[0145] See also Figure 4In an optional embodiment, in order to efficiently execute the grain silo clearing system control method provided by the present invention, the present invention further provides an intelligent grain silo clearing system, the system comprising a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, the computer program comprising program instructions, and the processor is configured to call the program instructions. The intelligent grain silo clearing system of the present invention has a complete structure, is objective and stable, and can efficiently execute the grain silo clearing system control method of the present invention, thereby improving the overall applicability and practical application capabilities of the present invention.

[0146] 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 above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. 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 of the claims and description of the present invention.

Claims

1. A grain silo clearing system control method, characterized in that: The steps include: Designing a silo data monitoring network based on the grain silo structure and stored grain properties, and obtaining grain silo monitoring data through the silo data monitoring network; Establishing a spatial motion analysis model according to the grain silo monitoring data, and obtaining the spatial motion of the warehouse cleaning robot based on the spatial motion analysis model and the grain silo monitoring data; constructing a clearance force prediction model based on the grain silo monitoring data, and analyzing the optimal force required for the grain silo through the clearance force prediction model; Dynamically adjust the grain clearance plan based on the clearance robot's spatial position, spatial motion, and optimal force to ensure a smooth clearance process. The constructing of a warehouse clearance force prediction model based on the grain silo monitoring data includes: Establishing a machine traction force analysis function based on the grain silo monitoring data; Constructing a warehouse clearance interaction force prediction function based on the grain silo monitoring data; Constructing a clearance force prediction model based on the machine traction force analysis function and the clearance interaction force prediction function; The clearance interaction force prediction function satisfies the following relationship: ， in, represents the interaction force between the cleaning robot and the silo environment, represents the environmental stiffness of the silo, Indicates the damping parameter of the x-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearing robot in the x-axis direction, Indicates the movement position of the x-axis of the clearance robot space, Indicates the damping parameter of the y-axis direction of the warehouse cleaning robot and the silo environment, Indicates the end position of the clearance robot in the y-axis direction, Indicates the movement position of the clearance robot on the y-axis space, Indicates the damping parameters of the cleaning robot in the z-axis direction and the silo environment, Indicates the end position of the clearance robot in the z-axis direction, Indicates the movement position of the z-axis of the warehouse cleaning robot; The clearance force prediction model satisfies the following relationship: ， in, represents the optimal force of the warehouse cleaning robot, represents the environmental stiffness of the silo, Represents the center of gravity vector coordinate system of the warehouse cleaning robot, represents the desired coordinate system of the center of gravity of the warehouse cleaning robot, represents the inertia coefficient of the silo, represents the expected speed of the clearance robot, Indicates the actual movement speed of the clearance robot, represents the expected acceleration of the clearance robot, Indicates the actual motion acceleration of the clearance robot, represents the interaction force between the cleaning robot and the silo environment, Indicates the minimum force required to pull the warehouse cleaning robot.

2. The grain silo clearing system control method according to claim 1, characterized in that: The silo data monitoring network is designed based on the grain silo structure and stored grain properties, and the grain silo monitoring data is obtained through the silo data monitoring network, including: Design a silo data monitoring network based on the grain silo structure and stored grain properties. The silo data monitoring network includes temperature and humidity sensors, laser ranging sensors, dust concentration sensors, wireless cameras, and smoke alarms. The grain status and environmental parameters in the silo are monitored through the silo data monitoring network to obtain grain silo monitoring data.

3. The grain silo clearing system control method according to claim 1, characterized in that: The establishing of a spatial motion analysis model based on the grain silo monitoring data includes: Introducing three-dimensional analysis technology, combining the three-dimensional analysis technology with the grain silo monitoring data to analyze the center of gravity position of the warehouse cleaning robot; A spatial motion analysis model is established based on the characteristics of the warehouse cleaning robot and the center of gravity position.

4. The grain silo clearing system control method according to claim 3, characterized in that: The spatial motion analysis model satisfies the following relationship: ， in, represents the spatial motion coordinate system of the warehouse cleaning robot, Represents the x-axis of the center-of-gravity vector coordinate system of the warehouse cleaning robot, Represents the y-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the z-axis of the center of gravity vector coordinate system of the warehouse cleaning robot, Represents the rotation transformation matrix of the x-axis of the clearance robot, Represents the rotation transformation matrix of the y-axis of the clearance robot, Represents the rotation transformation matrix of the z-axis of the warehouse cleaning robot, Represents the homogeneous coordinate system parameters.

5. The grain silo clearing system control method according to claim 1, characterized in that: The grain clearing scheme dynamically adjusted by combining the spatial position, spatial motion and optimal force of the clearing robot includes: A grain clearance time is preset based on the grain silo structure and stored grain properties, and the grain clearance time is divided into multiple time intervals.

6. The grain silo clearing system control method according to claim 5, characterized in that: The grain clearing scheme dynamically adjusted by combining the spatial position, spatial motion and optimal force of the clearing robot includes: The spatial position, spatial movement and optimal force of the warehouse-clearing robot are updated in real time according to the multiple time intervals and grain silo monitoring data, so as to realize dynamic adjustment of the grain warehouse-clearing plan.

7. A grain silo clearing system, characterized in that: The system includes a processor, an input device, an output device and a memory, which 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 the grain silo clearing system control method according to any one of claims 1 to 6.

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