Soybean plant general modeling method, equipment, medium and product

Abstract

The invention discloses a soybean plant general modeling method, device, medium and product, and relates to the technical field of agricultural engineering modeling analysis, the method comprises the following steps: constructing a stalk discrete element model, a bean discrete element model and a pod discrete element model; obtaining a stalk shear failure cohesive force mechanical parameter, a pod shear failure cohesive force mechanical parameter and a soybean compression fracture cohesive force mechanical parameter; and inputting the stalk discrete element model, the bean discrete element model, the pod discrete element model, the stalk shear failure cohesive force mechanical parameters, the pod shear failure cohesive force mechanical parameters and the bean compression fracture cohesive force mechanical parameters into discrete element software to obtain the flexible soybean plant model based on the discrete element method. According to the application, the problem that the interaction mechanism of crops and machinery equipment lacks models in the operation process of the soybean combine harvester can be solved, and the simulation reduction degree of the soybean plant model can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of agricultural engineering modeling analysis, and particularly to a general modeling method, device, medium and product for soybean plants. Background Art

[0002] Mechanized soybean harvesting is an important link in realizing the whole process of soybean production mechanization. As the core component of a combine harvester, after soybean crops enter the threshing system, they are threshed under the rubbing action of threshing elements and separated through a concave grid. Due to the short time of threshing and separation, it is difficult to study the interaction process between crops and mechanical equipment such as stem breakage, pod cracking and soybean breakage during the threshing and separation process by intuitive methods. Using the discrete element method to simulate the mechanical operation process of soybean plants can directly obtain the movement trajectory, force, deformation and breakage of crops in the operation system, and analyze the mechanism of soybean harvesting operation from a microscopic perspective. To study the interaction between soybean plants and mechanical components and optimize the structure and working parameters of mechanical components, it is very necessary to establish a soybean plant model with a high degree of reduction.

[0003] In the prior art, there are few methods for modeling soybean plant models. For modeling stems and soybeans, the random filling method and the space coordinate method can be used to obtain the position information of the spherical particles that make up the stems and soybeans. However, due to the curved surface characteristics of the pods and the structure of the soybeans inside the pods, it is difficult to model the pods.

[0004] In summary, due to the complex structure of the pods, there is currently a lack of a modeling method for soybean plant models that can improve the simulation reduction degree, which seriously affects the research on the operation mechanism and structure optimization of soybean operation systems. Summary of the Invention

[0005] The purpose of the present application is to provide a general modeling method, device, medium and product for soybean plants, which can improve the simulation reduction degree of the soybean plant modeling method.

[0006] To achieve the above purpose, the present application provides the following solutions:

[0007] In a first aspect, the present application provides a general modeling method for soybean plants, including:

[0008] Selecting several plants of the soybean variety to be modeled as soybean plant samples, and measuring the shape parameters of the stems and soybean grains of the soybean plant samples;

[0009] Analyzing and calculating the stem shape parameters to obtain stem model parameters; obtaining the position information of stem spherical particles based on the stem model parameters by the space coordinate method; and obtaining a stem discrete element model based on the position information of the stem spherical particles;

[0010] Use 3D laser scanning technology to scan the soybean grains in the soybean plant sample to obtain a 3D model of the soybean grains; use spherical particles to fill the 3D model of the soybean grains, and export the position information of the spherical particles of the soybean grains; obtain a discrete element model of the soybean grains based on the position information of the spherical particles of the soybean grains;

[0011] Use the 3D laser scanning technology to scan the pods in the soybean plant sample to obtain a 3D model of the pods; construct a 3D model of the soybean grains inside the pods based on the shape parameters of the soybean grains; use the virtual-real combination method, use spherical particles to fill the 3D model of the pods and the 3D model of the soybean grains inside the pods, and export the position information of the spherical particles of the pods and the position information of the spherical particles of the soybean grains inside the pods; obtain a discrete element model of the pods based on the position information of the spherical particles of the pods and the position information of the spherical particles of the soybean grains inside the pods;

[0012] Based on the discrete element model of the stem, the discrete element model of the soybean grains, and the discrete element model of the pods, obtain the shear failure bond mechanical parameters of the stem, the shear failure bond mechanical parameters of the pods, and the compression fracture bond mechanical parameters of the soybean grains respectively;

[0013] Input the discrete element model of the stem, the discrete element model of the pods, the shear failure bond mechanical parameters of the stem, the shear failure bond mechanical parameters of the pods, and the compression fracture bond mechanical parameters of the soybean grains into the discrete element software to obtain a flexible soybean plant model based on the discrete element method.

[0014] Optionally, based on the discrete element model of the stem, the discrete element model of the soybean grains, and the discrete element model of the pods, obtaining the shear failure bond mechanical parameters of the stem, the shear failure bond mechanical parameters of the pods, and the compression fracture bond mechanical parameters of the soybean grains respectively includes:

[0015] Conduct stem shear, pod shear, and soybean grain compression experiments on the soybean plant sample to obtain the ultimate load forces of stem shear fracture, pod shear fracture, and soybean grain compression fracture;

[0016] Taking the stem ultimate load force as the target value, conduct a stem shear simulation experiment on the discrete element model of the stem to calibrate the shear failure bond mechanical parameters of the stem;

[0017] Taking the soybean grain ultimate load force as the target value, conduct a soybean compression simulation experiment on the discrete element model of the soybean grains to calibrate the compression fracture bond mechanical parameters of the soybean grains;

[0018] Taking the pod ultimate load force as the target value, conduct a pod shear simulation experiment on the discrete element model of the pods to calibrate the shear failure bond mechanical parameters of the pods.

[0019] Optionally, the stalk shape parameters include plant height, top diameter of the stalk, middle diameter of the stalk, and root diameter of the stalk; the soybean grain shape parameters include the three-axis dimensions of the soybean grains.

[0020] Optionally, the spatial coordinate method is used to obtain the stalk spherical particle position information based on the stalk model parameters, including:

[0021] According to the double-layer structure of the stalk xylem and pith, the in-plane spherical particle position information of the stalk is obtained by using the in-plane inscribed circle calculation method;

[0022] The spatial coordinate method is used to obtain the stalk spherical particle position information based on the stalk model parameters and the in-plane spherical particle position information of the stalk.

[0023] Optionally, the virtual-real combination method is used to fill the three-dimensional model of the pod and the three-dimensional model of the soybeans inside the pod with spherical particles, and the pod spherical particle position information and the in-pod soybean spherical particle position information are exported, including:

[0024] Set the three-dimensional model of the soybeans inside the pod to the physical state, set the three-dimensional model of the pod to the virtual state, fill it with spherical particles, and then set the filled three-dimensional model of the pod to the physical state to export the pod spherical particle position information;

[0025] Set the three-dimensional model of the pod and the three-dimensional model of the soybeans inside the pod to the virtual state, fill it with spherical particles, and then set the filled three-dimensional model of the soybeans inside the pod to the physical state to export the in-pod soybean spherical particle position information.

[0026] Optionally, the stalk shear failure bonding mechanical parameters, the pod shear failure bonding mechanical parameters, and the soybean grain compression fracture bonding mechanical parameters all include: normal / tangential stiffness, normal / tangential stress, and bonding coefficient.

[0027] Optionally, the general modeling method for the soybean plant further includes:

[0028] Obtain the intrinsic parameters and contact mechanical parameters of the soybean plant sample; the intrinsic parameters of the soybean plant include: density, Poisson's ratio, and shear modulus; the contact mechanical parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient;

[0029] Input the stalk discrete element model, the pod discrete element model, the stalk shear failure bonding mechanical parameters, the pod shear failure bonding mechanical parameters, and the soybean grain compression fracture bonding mechanical parameters into the discrete element software, set the intrinsic parameters of the soybean plant and the contact mechanical parameters, and adjust the pose of the pod discrete element model to obtain a flexible soybean plant model based on the discrete element method.

[0030] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the general soybean plant modeling method described in any one of the above.

[0031] In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the general soybean plant modeling method described in any one of the above.

[0032] In a fourth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the general soybean plant modeling method described in any one of the above.

[0033] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0034] The present application provides a general soybean plant modeling method, device, medium, and product. By constructing a stem discrete element model, a bean discrete element model, and a pod discrete element model; obtaining the stem shear failure bonding mechanical parameters, the pod shear failure bonding mechanical parameters, and the soybean compression fracture bonding mechanical parameters; and inputting the stem discrete element model, the bean discrete element model, the pod discrete element model, the stem shear failure bonding mechanical parameters, the pod shear failure bonding mechanical parameters, and the bean compression fracture bonding mechanical parameters into the discrete element software, a flexible soybean plant model based on the discrete element method is obtained. This solves the problem of the lack of a model for the interaction mechanism between crops and machinery during the operation of a soybean combine harvester, and can improve the simulation reduction degree and model accuracy of the soybean plant model. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0036] Figure 1 It is a flowchart of a general soybean plant modeling method in an embodiment of the present application;

[0037] Figure 2 It is a front view of a flexible soybean plant model based on the discrete element method provided in an embodiment of the present application;

[0038] Figure 3 It is a top view of a flexible soybean plant model based on the discrete element method provided in an embodiment of the present application;

[0039] Figure 4 Axonometric view of the flexible soybean plant model based on the discrete element method provided by an embodiment of the present application

[0040] Figure 5 Schematic diagram of the positions of spherical particles on the stem cutting plane provided by an embodiment of the present application;

[0041] Figure 6 Schematic diagram of the construction process of the soybean grain discrete element model provided by an embodiment of the present application;

[0042] Figure 7 Schematic diagram of the construction process of the soybean pod discrete element model provided by an embodiment of the present application;

[0043] Figure 8 Schematic diagram of the assembly of the stem discrete element model and the soybean pod discrete element model provided by an embodiment of the present application;

[0044] Figure 9 Schematic diagram of the Zheng 1311 soybean plant model provided by an embodiment of the present application;

[0045] Figure 10 Schematic diagram of the soybean plant detachment simulation experiment provided by an embodiment of the present application;

[0046] Figure 11 Schematic diagram of the structure of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0047] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0048] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0049] In an exemplary embodiment, as Figure 1 shown, a general modeling method for soybean plants is provided. This method is executed by a computer device, and specifically, it can be executed alone by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, taking the construction of a soybean plant model using this method as an example for illustration, it includes:

[0050] Step 100, select several plants of the soybean variety to be modeled as soybean plant samples, and measure the shape parameters of the stems and soybean grains of the soybean plant samples.

[0051] Step 200: Analyze and calculate the stalk shape parameters to obtain the stalk model parameters. Based on the stalk model parameters, use the spatial coordinate method to obtain the stalk spherical particle position information. Based on the stalk spherical particle position information, obtain the stalk discrete element model.

[0052] Use the three-dimensional laser scanning technology to scan the soybean grains in the soybean plant sample to obtain the three-dimensional model of the soybean grains. Use spherical particles to fill the three-dimensional model of the soybean grains, and export the position information of the spherical particles of the soybean grains. Based on the position information of the spherical particles of the soybean grains, obtain the discrete element model of the soybean grains, as Figure 6 shown.

[0053] Use the three-dimensional laser scanning technology to scan the soybean pods in the soybean plant sample to obtain the three-dimensional model of the soybean pods. Based on the soybean grain shape parameters, construct the three-dimensional model of the soybean grains inside the soybean pods. Using the method of combining virtual and real, use spherical particles to fill the three-dimensional model of the soybean pods and the three-dimensional model of the soybean grains inside the soybean pods, and export the position information of the spherical particles of the soybean pods and the position information of the spherical particles of the soybean grains inside the soybean pods. Based on the position information of the spherical particles of the soybean pods and the position information of the spherical particles of the soybean grains inside the soybean pods, obtain the discrete element model of the soybean pods.

[0054] Step 300: Based on the stalk discrete element model, the soybean grain discrete element model, and the soybean pod discrete element model, respectively obtain the stalk shear failure bonding mechanical parameters, the soybean pod shear failure bonding mechanical parameters, and the soybean grain compression fracture bonding mechanical parameters.

[0055] Step 400: Input the stalk discrete element model, the soybean pod discrete element model, the stalk shear failure bonding mechanical parameters, the soybean pod shear failure bonding mechanical parameters, and the soybean grain compression fracture bonding mechanical parameters into the discrete element software to obtain the flexible soybean plant model based on the discrete element method.

[0056] As an alternative implementation, in order to improve the simulation reduction degree of the soybean plant model, step 300 includes:

[0057] 301: Conduct stalk shear, soybean pod shear, and soybean grain compression experiments on the soybean plant sample to obtain the ultimate load forces of stalk shear fracture, soybean pod shear fracture, and soybean grain compression fracture. Among them, the ultimate load forces of stalk shear fracture, soybean pod shear fracture, and soybean grain compression fracture are the load forces borne by the stalks, soybean pods, and soybean grains when they just start to fracture under the continuous action of the load.

[0058] 302. Taking the ultimate load acting force of the stalk as the target value, conduct a stalk shear simulation experiment on the stalk discrete element model to calibrate the cohesive mechanical parameters of stalk shear failure. For example, simulate the fracture of the stalk under shear force, and conduct Plackett - Burma test, Steepest Ascent test and Box - Behnken test on the stalk discrete element model. Obtain the significant factors affecting stalk fracture through the Plackett - Burma test. Obtain the parameter change range of the significant factors affecting stalk fracture through the Steepest Ascent test. Obtain the significant multi - factors affecting stalk fracture through the Box - Behnken test.

[0059] 303. Taking the ultimate load acting force of the soybean grain as the target value, conduct a soybean compression simulation experiment on the soybean grain discrete element model to calibrate the cohesive mechanical parameters of soybean grain compression fracture. For example, simulate the crushing of the soybean grain under compression, and conduct Steepest Ascent test and Box - Behnken test on the soybean grain discrete element model. Obtain the change range of the cohesive parameters affecting soybean grain crushing through the Steepest Ascent test. Obtain the multi - factors affecting soybean grain crushing through the Box - Behnken test.

[0060] 304. Taking the ultimate load acting force of the pod as the target value, conduct a pod shear simulation experiment on the pod discrete element model to calibrate the cohesive mechanical parameters of pod shear failure. For example, simulate the fracture of the pod under shear force. Conduct Steepest Ascent test and Box - Behnken test on the pod discrete element model. Obtain the change range of the cohesive parameters affecting pod shear through the Steepest Ascent test. Obtain the multi - factors affecting pod shear through the Box - Behnken test.

[0061] Based on the above description, in this embodiment, the finally obtained bond mechanical parameters of stem shear failure, pod shear failure, and bean grain compression fracture all include: normal / tangential stiffness, normal / tangential stress, and bond coefficient. For example, the bond mechanical parameters of stem shear failure include the normal / tangential stiffness of pith-pith, pith-xylem, xylem-xylem normal stiffness, xylem-xylem tangential stiffness, normal / tangential stress of pith-pith, pith-xylem, xylem-xylem normal stress, xylem-xylem tangential stress, pith particle bond radius coefficient, pith-xylem bond radius coefficient, and xylem particle bond radius coefficient. The bond mechanical parameters of bean grain compression fracture include the normal / tangential contact stiffness per unit area, normal / tangential stress, and bond coefficient between soybean grains. The bond mechanical parameters of pod shear failure include the normal / tangential contact stiffness per unit area, normal / tangential stress, and bond coefficient between soybean seeds (i.e., bean grains) inside the pod.

[0062] As an alternative implementation, the process of obtaining the flexible soybean plant model based on the discrete element method in step 400 can be as follows: Obtain the intrinsic parameters and contact mechanical parameters of the soybean plant sample. The intrinsic parameters of the soybean plant include density, Poisson's ratio, and shear modulus. The contact mechanical parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient. Input the stem discrete element model, pod discrete element model, bond mechanical parameters of stem shear failure, pod shear failure, and bean grain compression fracture into the discrete element software, set the intrinsic parameters and contact mechanical parameters of the soybean plant, and adjust the pose of the pod discrete element model to obtain the flexible soybean plant model based on the discrete element method. The pose of the pod discrete element model relative to the stem discrete element model is as Figure 8 shown. The front view, top view, and axonometric view of the finally obtained flexible soybean plant model based on the discrete element method are as Figures 2 - 4 shown.

[0063] Among them, the coefficient of restitution represents the recovery ability of the materials before and after collision, and is usually expressed as the ratio of the velocities of the materials before and after collision. In all the embodiments provided in this application, the coefficient of restitution between beans, between stalks, between pods, between beans and stalks, between beans and pods, and between stalks and pods is measured by the simple pendulum method with the aid of high-speed photography. The static friction coefficients between beans and steel plates, between beans and stalks, between beans and pods, between stalks and steel plates, between stalks and pods, between pods and steel plates, between beans and beans, between stalks and stalks, and between pods and pods are measured respectively by an inclined plane instrument with the aid of high-speed photography. The rolling friction coefficient is calibrated by the physical stacking angle and the simulated stacking angle. The mixed stacking angles between beans, stalks and pods are measured, and the mixed stacking angles between beans and stalks, between beans and pods, and between stalks and pods are measured. A simulated stacking angle test is established to fit and calibrate the simulated stacking angle, and the rolling friction coefficients of the contacts between beans, stalks and pods are obtained.

[0064] For example, according to the plant height, the height of the bottom pod, the beans inside the pod, and the number of beans, the quantity and positions of the discrete element models of the stalks, the discrete element models of the pods, and the discrete element models of the beans inside the pod are adjusted, as well as the spatial pose of the discrete element model of the pod. The spatial pose of the discrete element model of the pod is transformed based on the X, Y, and Z axes. Assume that the basic position of the discrete element model of the pod is D0: (D x , D y , D z ) represents the coordinates of the basic position D0. The pose of the i-th discrete element model of the pod in space is D i : Among them, the R matrix is composed of the rotation matrices R x (θ x ), R y (θ y ), and R z (θ z ) around the X, Y, and Z axes respectively, which are expressed as: In the formula, θ x , θ y , and θ z are the rotation angles of the discrete element model of the pod around the X, Y, and Z axes respectively. The translation matrix T is obtained through . In the formula, x i , y i , and z i are the translation distances of the discrete element model of the pod along the X, Y, and Z axes respectively.

[0065] As an alternative implementation, in step 100, the soybean plant samples (i.e., several plants of the soybean variety to be modeled) are the crops for the combine harvester at the mature stage. The stem shape parameters include plant height, the diameter at the top of the stem, the diameter in the middle of the stem, and the diameter at the root of the stem. The soybean grain shape parameters include the three-axis dimensions of the soybean grains.

[0066] In addition, the height of the bottom pod can also be obtained, that is, the distance between the pod closest to the ground in the soybean plant and the ground. Based on the height of the bottom pod, combined with the obtained pod discrete element model and the stem discrete element model, the setting position of the bottom pod discrete element model in the stem discrete element model can be obtained.

[0067] As an alternative implementation, in step 200, the method of using spatial coordinates to obtain the position information of the spherical particles on the stem based on the stem model parameters includes: according to the double-layer structure of the xylem and pith of the stem, the method of calculating the inscribed circle in the plane is used to obtain the position information of the spherical particles in the plane of the stem. The method of using spatial coordinates to obtain the position information of the spherical particles on the stem based on the stem model parameters and the position information of the spherical particles in the plane of the stem.

[0068] For example, through the analysis and calculation of the stem shape parameters, the stem model parameters are obtained. The stem model parameters include the average size of the stem and the plant height. According to the double-layer structure of the xylem and pith of the stem, the method of calculating the inscribed circle in the plane is used to arrange spherical particles with a radius of r in the plane, and the position information of the spherical particles in the inner pith and the outer xylem is obtained. The arrangement positions of the spherical particles in the xylem and pith of the stem are as Figure 5 shown. Based on the position information of the spherical particles in the inner pith and the outer xylem and the plant height in the stem model parameters, the position information of the spherical particles on the stem with the total length is obtained by using the method of spatial coordinates. Among them, the radius r of the spherical particles is obtained based on the average size of the stem.

[0069] The arrangement position information of the spherical particles that make up the inner pith and the xylem is expressed as:

[0070]

[0071] Among them, N i represents the three-dimensional coordinates of the position of the spherical particles in the i-th layer, z i represents the Z-direction coordinate position of the i-th layer. The three-dimensional coordinates of the spherical particles in the inner pith are The three-dimensional coordinates of the spherical particles in the outer xylem are

[0072] As Figure 7As shown, in step 200, the method of combining virtual and real is adopted. Spherical particles are used to fill the three-dimensional model of the pod and the three-dimensional model of the soybeans inside the pod, and the position information of the spherical particles in the pod and the position information of the spherical particles of the soybeans inside the pod are exported, including: setting the three-dimensional model of the soybeans inside the pod to the physical state, setting the three-dimensional model of the pod to the virtual state, after filling with spherical particles, setting the filled three-dimensional model of the pod to the physical state, and exporting the position information of the spherical particles in the pod. Setting the three-dimensional model of the pod and the three-dimensional model of the soybeans inside the pod to the virtual state, after filling with spherical particles, setting the filled three-dimensional model of the soybeans inside the pod to the physical state, and exporting the position information of the spherical particles of the soybeans inside the pod.

[0073] In practical applications, the soybean plant samples are artificially selected according to actual modeling requirements and can be the crops for the operation of a combine harvester at the mature stage. Without limitation, soybean plant samples can also be selected according to specific modeling requirements.

[0074] In an exemplary embodiment, taking the construction of the Zheng 1311 soybean model by using the general soybean plant modeling method provided in the above embodiment as an example for illustration.

[0075] S1. Randomly select 20 soybean plants as soybean plant samples, measure the shape parameters of the soybean plant stalks, pods and beans, as shown in Table 1. And obtain the intrinsic parameters of the 20 selected soybean plants.

[0076] Table 1 Shape parameter table

[0077]

[0078] S2. Analyze the stalk length required for the stalk shear test and the calculated average stalk diameter, and construct a stalk discrete element model with a radius r = 0.5 mm. The position information of the spherical particles on the tangent plane at the origin position is shown in Table 2. The arrangement positions of the spherical particles in the xylem and pith of the stalk are as Figure 5 shown. The three-dimensional coordinates of the spherical particles in the inner pith of the i-th layer are N0 to N6, and the three-dimensional coordinates of the spherical particles in the outer xylem are N7 to N 18 .

[0079] Table 2 Spherical particle position table

[0080]

[0081] S3. Construct a bean discrete element model and a pod discrete element model.

[0082] S4. Measure the ultimate load forces of stalk shear fracture, bean compression fracture, and pod shear fracture, and calculate the average ultimate load.

[0083] S5. Conduct a shear simulation test on the stem discrete element model. According to the Plackett-Burman test, the significant factors affecting stem fracture are found to be the xylem particle bonding radius coefficient, the xylem-xylem normal stiffness, and the xylem-xylem tangential stiffness. Through the Steepest Ascent test and the Box-Behnken test, the bonding mechanical parameters of stem shear failure are calibrated. As shown in Table 3.

[0084] Table 3 Bonding Mechanical Parameter Table of Stem Shear Failure

[0085]

[0086] Conduct a compression simulation test on the bean discrete element model. Through the Steepest Ascent test and the Box-Behnken test, the bonding mechanical parameters of bean compression fracture are calibrated: the normal / tangential stiffness per unit area of the bean is 4.7×10 10 N / m 3 , the normal / tangential stress of the bean is 5.3×10 8 Pa, and the bonding radius coefficient of the bean is 1.03.

[0087] Conduct a shear simulation test on the pod discrete element model. Through the Steepest Ascent test and the Box-Behnken test, the bonding mechanical parameters of pod shear failure are calibrated: the normal / tangential stiffness per unit area of the pod is 2.85×10 9 N / m 3 , the normal / tangential stress of the pod is 2.55×10 8 Pa, and the bonding radius coefficient of the pod is 1.08.

[0088] S6. The measured and calibrated contact mechanical parameters of the soybean plant are shown in Table 4, and the other parameters are set as default values.

[0089] Table 4 Contact Mechanical Parameter Table

[0090]

[0091]

[0092] S7. According to the plant height of 734 mm, the bottom pod height of 275 mm, 34 pods, the vertical spacing between pods is 80 mm, and there are 3 pods at the pod generation position. Reasonably arrange the pod discrete element model on the stem discrete element model. The original position of the pod discrete element model is at the origin. The stem discrete element model and the pod discrete element model are as Figure 8 shown. If the pod discrete element model is placed horizontally, the position information of the pod discrete element model needs to be set on the stem discrete element model as shown in Table 5.

[0093] Table 5 Position Information Table of the Pod Discrete Element Model

[0094]

[0095] The arrangement positions of the pod discrete element model on the stalk discrete element model are shown in Table 6.

[0096] Table 6 Pod Arrangement Position Table

[0097]

[0098]

[0099] S8. Import the stalk discrete element model, pod discrete element model, and bonding mechanical parameters obtained in the above steps into the discrete element software, and set the intrinsic parameters and contact mechanical parameters of the soybean plant, then the soybean plant model of Zheng 1311 can be obtained, as Figure 9 shown.

[0100] In an exemplary embodiment, through the soybean threshing simulation test, the feasibility of the modeling scheme in the above embodiment is verified: import the three-dimensional model of the soybean threshing device, set the rotational speed of the threshing cylinder and the particle factory of the soybean plant model to conduct a simulation test, and compare it with the actual test results. As Figure 10 shown, in the threshing simulation environment, the soybean plant realizes characteristics such as pod removal and pod cracking under the action of the rotational motion of the threshing cylinder. At the same time, as the rotational speed of the threshing cylinder increases, the soybean threshing damage rate increases, and the simulated threshing damage rate is closer to the actual test value. It fully verifies the feasibility of the general modeling method of soybean plants and the calibration of bonding parameters in this application, indicating that the soybean plant model established by using the soybean plant modeling method in this application can be used for the simulation analysis of the soybean threshing operation process, providing model and data support for the structural optimization of the threshing device and the improvement of operation quality.

[0101] According to the above embodiments provided in this application, this application has the following advantages:

[0102] 1. The modeling method proposed in this application is constructed based on three-dimensional laser scanning and measuring the sample parameters of soybean plants, and has strong versatility, suitable for discrete element modeling of soybean plants of various varieties such as Northeast soybeans, Huanghuaihai soybeans, and Southern soybeans.

[0103] 2. In existing soybean plant modeling methods, since mechanical properties such as stem breakage and pod breakage are not considered, the constructed soybean plant models are usually rigid bodies, and there are only stem and bean models, lacking a pod model, resulting in a low simulation reduction degree. In order to better reflect the flexibility and breakable characteristics of soybean plants, in this application, by calibrating the bonding mechanical parameters required for stem shear failure, pod shear failure, and bean compression fracture, the constructed soybean plant model has a certain degree of flexibility and can also simulate biomechanical properties such as stem breakage, pod splitting and breakage, and soybean breakage, greatly restoring the properties of soybean plants in real situations.

[0104] 3. Due to the relatively complex structure of the pod model, with beans wrapped inside the curved surface structure, there are currently no soybean plant models with a high reduction degree. The virtual-real combined modeling method described in this application can establish an empty pod and a soybean model inside the pod, with a high reduction degree compared to soybean plants in the real environment. At the same time, the modeling method proposed in this application has a high simulation accuracy in practical applications.

[0105] 4. The method for constructing a soybean plant model in this application has the advantages of high operability, high reduction degree, and simple construction process compared to existing methods, and can be used in large-scale plant population simulations such as header cutting, cross-bridge conveying, and threshing and separation.

[0106] 5. This method can also be used in the technical field of soybean harvesting machinery operation and the technical fields where enterprises need soybean plant modeling.

[0107] In an exemplary embodiment, a computer device is provided. This computer device can be a server or a terminal, and its internal structure diagram can be as Figure 11 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of this computer device is used to provide computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of this computer device is used to store data related to the general modeling method of soybean plants. The input / output interface of this computer device is used to exchange information between the processor and external devices. The communication interface of this computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a general modeling method for soybean plants.

[0108] Those skilled in the art can understand, Figure 11The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0109] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0110] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0111] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0112] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0113] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0114] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0115] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A general modeling method for soybean plants, characterized in that, The general modeling method for soybean plants includes: Selecting several plants of the soybean variety to be modeled as soybean plant samples, and measuring the shape parameters of the stems and soybean grains of the soybean plant samples; Analyzing and calculating the stem shape parameters to obtain stem model parameters; using the space coordinate method to obtain the stem spherical particle position information based on the stem model parameters; obtaining the stem discrete element model based on the stem spherical particle position information; Scanning the soybean grains in the soybean plant samples by using three-dimensional laser scanning technology to obtain a three-dimensional model of the soybean grains; filling the three-dimensional model of the soybean grains with spherical particles, and exporting the soybean grain spherical particle position information; obtaining the soybean grain discrete element model based on the soybean grain spherical particle position information; Scanning the soybean pods in the soybean plant samples by using the three-dimensional laser scanning technology to obtain a three-dimensional model of the soybean pods; constructing a three-dimensional model of the soybean grains inside the soybean pods based on the soybean grain shape parameters; using the method of combining virtual and real, filling the three-dimensional model of the soybean pods and the three-dimensional model of the soybean grains inside the soybean pods with spherical particles, and exporting the soybean pod spherical particle position information and the soybean grain spherical particle position information inside the soybean pods; obtaining the soybean pod discrete element model based on the soybean pod spherical particle position information and the soybean grain spherical particle position information inside the soybean pods; Based on the stem discrete element model, the soybean grain discrete element model and the soybean pod discrete element model, respectively obtaining the stem shear failure bond mechanical parameters, the soybean pod shear failure bond mechanical parameters and the soybean grain compression fracture bond mechanical parameters; Inputting the stem discrete element model, the soybean pod discrete element model, the stem shear failure bond mechanical parameters, the soybean pod shear failure bond mechanical parameters and the soybean grain compression fracture bond mechanical parameters into the discrete element software to obtain a flexible soybean plant model based on the discrete element method.

2. The general modeling method for soybean plants according to claim 1, wherein Based on the stem discrete element model, the soybean grain discrete element model and the soybean pod discrete element model, respectively obtaining the stem shear failure bond mechanical parameters, the soybean pod shear failure bond mechanical parameters and the soybean grain compression fracture bond mechanical parameters, including: Conducting stem shear, soybean pod shear and soybean grain compression experiments on the soybean plant samples to obtain the ultimate load forces of stem shear fracture, soybean pod shear fracture and soybean grain compression fracture; Taking the stem ultimate load force as the target value, conducting a stem shear simulation experiment on the stem discrete element model to calibrate the stem shear failure bond mechanical parameters; Taking the soybean grain ultimate load force as the target value, conducting a soybean compression simulation experiment on the soybean grain discrete element model to calibrate the soybean grain compression fracture bond mechanical parameters; Taking the soybean pod ultimate load force as the target value, conducting a soybean pod shear simulation experiment on the soybean pod discrete element model to calibrate the soybean pod shear failure bond mechanical parameters.

3. The general modeling method for soybean plants according to claim 1, characterized in that, The stem shape parameters include plant height, stem top diameter, stem middle diameter and stem root diameter; the soybean grain shape parameters include the three-axis dimensions of soybean seeds.

4. The general modeling method for soybean plants according to claim 1, characterized in that, Using the space coordinate method to obtain the stem spherical particle position information based on the stem model parameters, including: According to the double-layer structure of the stem xylem and pith, using the in-plane inscribed circle calculation method to obtain the stem in-plane spherical particle position information; The spatial coordinate method is adopted to obtain the position information of spherical particles on the stem based on the stem model parameters and the position information of spherical particles in the stem plane.

5. The general modeling method for soybean plants according to claim 1, characterized in that The method of combining virtual and real is adopted. Spherical particles are used to fill the three-dimensional model of the pod and the three-dimensional model of the soybean inside the pod, and the position information of spherical particles in the pod and the position information of spherical particles of soybeans inside the pod are exported, including: The three-dimensional model of the beans inside the pod is set to the physical state, and the three-dimensional model of the pod is set to the virtual state. After filling with spherical particles, the filled three-dimensional model of the pod is set to the physical state, and the position information of spherical particles in the pod is exported; The three-dimensional model of the pod and the three-dimensional model of the beans inside the pod are set to the virtual state. After filling with spherical particles, the filled three-dimensional model of the beans inside the pod is set to the physical state, and the position information of spherical particles of the beans inside the pod is exported.

6. The general modeling method for soybean plants according to claim 1, wherein The shear failure bonding mechanical parameters of the stem, the shear failure bonding mechanical parameters of the pod, and the compression fracture bonding mechanical parameters of the bean grains all include: normal / tangential stiffness, normal / tangential stress, and bonding coefficient.

7. The general modeling method for soybean plants according to claim 1, wherein, The general modeling method of the soybean plant further includes: Obtaining the intrinsic parameters and contact mechanical parameters of the soybean plant sample; the intrinsic parameters of the soybean plant include: density, Poisson's ratio, and shear modulus; the contact mechanical parameters include the collision recovery coefficient, static friction coefficient, and rolling friction coefficient; Inputting the discrete element model of the stem, the discrete element model of the pod, the shear failure bonding mechanical parameters of the stem, the shear failure bonding mechanical parameters of the pod, and the compression fracture bonding mechanical parameters of the bean grains into the discrete element software, setting the intrinsic parameters of the soybean plant and the contact mechanical parameters, and adjusting the pose of the discrete element model of the pod to obtain a flexible soybean plant model based on the discrete element method.

8. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the general modeling method of the soybean plant according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the general modeling method of the soybean plant according to any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the general modeling method of the soybean plant according to any one of claims 1-7.

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