Method for testing compaction depth of soil

Abstract

The invention discloses a soil compaction depth testing method. The method comprises the following steps: calibrating soil particle parameters; establishing a simulation soil bin model according to a parameter calibration result; eDEM and Recurdyn software are utilized for coupling simulation analysis of the influence of different operation factors on the soil compaction depth, a single-factor test is conducted, and the operation factors with the remarkable compaction depth are screened out for further simulation test; performing simulation by using the screened operation factors to obtain corresponding soil compaction depths of the operation factors in different parameter ranges, performing nonlinear power function regression analysis on simulation test results by using SPSS 27 software, and establishing a mathematical model between the screened factors and the soil compaction depths; by using the method, a mathematical model of the operation factor and the compaction depth can be accurately established, real-time acquisition of the soil compaction depth during operation is facilitated, and a basis is provided for precision improvement during later tilling depth detection.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural machinery operation parameter detection, and in particular to a method for testing soil compaction depth. Background Art

[0002] In traditional technology, the measurement method of tillage depth in China is mainly based on manual sampling, which has poor measurement accuracy and low efficiency, and cannot accurately obtain tillage depth data in real time, resulting in delayed adjustment and inability to ensure post-tillage quality. In the existing technology, the tillage depth detection model is established based on the angle of the tractor's lower pull rod by analyzing the changes in the working posture of agricultural implements. Although it solves the problem of low detection efficiency in traditional technology, it does not consider the impact of the tractor's tires on the ground compaction depth, which affects the accuracy of tillage depth detection.

[0003] However, current research on soil compaction mainly focuses on its impact on soil stress, soil properties and crops, and there is little research on the depth of soil compaction. Therefore, there is an urgent need for a testing method that can reliably detect the depth of soil compaction. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above-mentioned problems existing in the existing soil compaction depth test, the present invention is proposed. The present invention uses the soil compression ratio as the evaluation index for determining the various parameters of the soil EEPA contact model, establishes a soil trough model based on the parameter calibration results, and uses coupled simulation to screen out the operating factors that are significant to the compaction depth through single-factor experiments. Finally, a mathematical model of the operating factors and compaction depth is established, which provides a basis for improving the accuracy of subsequent tillage depth detection.

[0006] In order to solve the above technical problems, the present invention provides the following technical solution, a method for testing soil compaction depth, comprising the following steps:

[0007] S1 Calibration of soil particle parameters, determination of coefficient of restitution, static friction coefficient, rolling friction coefficient, surface energy, plastic deformation ratio, bond branching index and tangential stiffness factor;

[0008] S2 establishes a simulated soil trough model according to the parameter calibration results;

[0009] S3 uses EDEM and Recurdyn software to couple simulation and analyze the effects of different operating factors on soil compaction depth, conducts single factor tests, and selects operating factors with significant effects on compaction depth for further simulation tests;

[0010] S4 simulates the screened operating factors to obtain the soil compaction depth corresponding to the operating factors under different parameter ranges. SPSS27 software is used to perform nonlinear power function regression analysis on the simulation test results to establish a mathematical model between the screened factors and the soil compaction depth.

[0011] As a preferred solution of the soil compaction depth test method in the present invention, the specific steps of calibration are: S101, calculating the compression ratio to evaluate the compression performance of the soil by the height of the consolidated sample after the load is completely unloaded;

[0012] S102 calibrates soil particle parameters based on soil uniaxial compression test, takes recovery coefficient X1, static friction coefficient X2, rolling friction coefficient X3, surface energy X4, plastic deformation ratio X5, bonding branch index X6 and tangential stiffness factor X7 as test factors, and takes soil compression performance index α as evaluation index. First, the Plackett-Burman test is used to screen out model parameters significantly related to soil compression performance, and then the regression model of compression performance index and significant factors is obtained through Box-Behnken Design test, and the factor parameters corresponding to the actual compression performance index are solved;

[0013] S103 determines relevant parameters of the straw discrete element model.

[0014] As a preferred solution of the soil compaction depth testing method in the present invention, wherein: in step S101, the calculation formula of the compression ratio is:

[0015]

[0016] Among them, h6 is the soil height of the consolidated sample with a load of 100 kPa, mm; h7 is the soil height of the consolidated sample with a load of 200 kPa after compression, mm; h8 is the initial height of the consolidated sample with a load of 100 kPa, mm; h9 is the initial height of the consolidated sample with a load of 200 kPa.

[0017] As a preferred solution of the test method for soil compaction depth in the present invention, when a uniaxial closed compression simulation test is performed in EDEM, a cylinder with a height of 250 mm and a bottom diameter of 50 mm is used to simulate an acrylic cylinder, the particle-cylinder simulation parameters are set, the particle-contact component model selects the Hertze-Mindlin model, a particle factory is set in the cylinder, 300 g of soil particles are generated, the initial height of the model is measured, and a compression simulation test is performed at a loading speed of 30 mm / s. When the axial pressure reaches 196.3 N, it moves in the opposite direction at the same rate until the pressure is completely unloaded. The height h6 of the model at this time is measured, and the simulation test is repeated. When the axial pressure is 392.7 N, the carriage is returned at the same rate. After complete unloading, the consolidation height h7 of the sample is measured, and the compression ratio α is calculated.

[0018] As a preferred solution of the soil compaction depth test method in the present invention, in which: in step S102, the surface soil is modeled with particles with a radius of 5 mm. According to the contribution analysis of the 7 test factors to the soil compression performance and bearing capacity in the Plackett-Burman compression test, the contribution of the 5 mm soil particle compression performance is ranked from large to small as X5, X2, X7, X6, X1, X4, and X3. A Box-Behnken Design test is designed to analyze and find the optimal solution. The test results are subjected to multiple regression analysis using Design expert. The insignificant items in the variance analysis are eliminated, and the regression model of the 5 mm particle compression ratio Y1 is obtained as follows:

[0019] Y1=a1+a2*X2+a3*X5+a4*X2*X5+a5*X5*X7-a6X7 2 ;

[0020] Among them, a1~a6 are constants.

[0021] As a preferred solution of the soil compaction depth test method in the present invention, the bottom soil is modeled with particles with a radius of 10 mm, and the contribution of the 10 mm soil particles to the compression performance is ranked from large to small as X3, X5, X2, X7, X1, X4, and X6. According to the parameter sensitivity analysis results, a Box-Behnken Design test is designed to analyze and find the optimal solution. The test results are subjected to multiple regression analysis using Design expert, and the insignificant items in the variance analysis are eliminated to obtain the regression model of the 10 mm particle compression ratio Y2:

[0022] Y2=b1+b2*X2+b3*X3+b4*X5-b5*X2*X5-b6*X2 2 -b7*X3 2 -b8*X5 2 ;

[0023] Among them, b1~b8 are constants.

[0024] As a preferred embodiment of the method for testing the soil compaction depth in the present invention, step S3 specifically includes the following steps:

[0025] S301 introduces three cones into EDEM, gives a vertical downward speed of 0.1m / s, measures the firmness of the soil model at a depth of 0 to 20cm every 5cm, extracts the peak pressure on the cones and calculates the average value, obtains different soil firmness by adjusting the compaction degree of the soil trough model, and establishes soil trough models with different firmness;

[0026] S302 uses CATIA to establish a three-dimensional structural model of a tractor herringbone tire, and imports the established three-dimensional structural model of the tire into Recurdyn software;

[0027] S303 uses EDEM-Recurdyn software for coupled simulation, and uses the step function to let the tire fall freely onto the soil trough model within 0 to 0.5 seconds, and accelerate the tire to the operating speed evenly within 0.5 to 0.7 seconds. After 0.7 seconds, the tire moves forward at a uniform speed for compaction simulation test to obtain the compaction depth of the tire on the soil trough model under different operating factors, including operating speed, soil firmness and straw coverage.

[0028] S304 screens out operational factors that are significant to the compaction depth.

[0029] As a preferred solution of the method for testing the soil compaction depth in the present invention, the operating factor screened out as being significant for the compaction depth is soil firmness.

[0030] As a preferred embodiment of the method for testing the soil compaction depth in the present invention, the mathematical model between the soil compaction depth and the soil firmness is:

[0031] L6=a*Y3 -b ;

[0032] Wherein, L6 is the soil compaction depth, the mathematical unit is mm; Y3 is the soil firmness, the mathematical unit is MPa, and a and b are positive constants.

[0033] The beneficial effects of the present invention are as follows: by taking the compression ratio of the soil as an evaluation index for determining various parameters of the soil EEPA contact model during the simulation test, three test factors with significant effects on the compression ratio are screened out from seven test factors, the insignificant items in the variance analysis are eliminated, and the test results are subjected to multiple regression analysis using the Design expert software, and regression models of the compression ratios of 5 mm particles and 10 mm particles are obtained respectively, thereby obtaining parameters corresponding to the simulation test that are consistent with the field test results, and finally, the operating factors with significant effects on the compaction depth are screened out, and a mathematical model of the operating factors and the compaction depth is established, so as to facilitate the acquisition of the compaction depth and provide a basis for improving the accuracy of later tillage depth detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0035] Figure 1 It is a schematic diagram of soil compression in the present invention.

[0036] Figure 2 This is a scene diagram when a uniaxial compression test of soil is performed in the present invention, in which 1 is a universal testing machine, 2 is an acrylic cylinder, and 3 is a hoop.

[0037] Figure 3 These are the four soil contact models commonly used in EDEM.

[0038] Figure 4 This is a simulation test diagram of soil uniaxial compression in the present invention.

[0039] Figure 5 This is a measurement diagram of measuring the static friction coefficient of straw-rubber using an inclined plane test in the present invention.

[0040] Figure 6 This is the test diagram for measuring the coefficient of recovery of straw-rubber collision.

[0041] Figure 7 Schematic diagram of straw length measurement.

[0042] Figure 8 This is the straw discrete element model established in the present invention.

[0043] Fig. 9 This is a diagram of the working posture of the tractor's lower pull rod.

[0044] Fig.10 This is a three-dimensional image of the tire created using CATIA in the present invention.

[0045] Fig.11 This is a solidity measurement diagram of the soil trench model in the present invention.

[0046] Fig.12 It is a simulation process diagram of soil compaction in the present invention.

[0047] Fig.13 This is the soil-straw discrete element soil trough model established in the present invention.

[0048] Fig.14 This is a diagram of tire compaction traces during the simulation test in the present invention.

[0049] Fig.15 It is a cross-sectional diagram of the compaction traces during the simulation test in the present invention.

[0050] Fig.16 Figure 1. Field test of tire compaction

[0051] Fig.17 This is the soil compaction simulation result diagram.

[0052] Fig.18 This is a graph showing the results of a soil compaction field test. DETAILED DESCRIPTION

[0053] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0055] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0056] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0057] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0058] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0059] In the present invention, EDEM is a multi-purpose discrete element method modeling software, Recurdyn is a multi-body system dynamics simulation software, EEPA (Edinburgh Elasto-Plastic Adhesion Model) is the Edinburgh elastic-plastic adhesion model, Hertze-Mindlin (no slip) is the Hertz-Mindlin (anti-slip) model, Design expert is a response surface analysis software, and SPSS (Statistical Package for the Social Sciences) is a social science statistical software package. The software used in this application is the prior art.

[0060] Example 1

[0061] Reference Figure 1 to Figure 4 , Figure 8 and Figure 10 to Figure 15 , which is the first embodiment of the present invention, provides a method for testing soil compaction depth, comprising the following steps:

[0062] S1: Calibration of soil particle parameters:

[0063] S101 uses the height of the consolidated sample after the load is completely unloaded to calculate the compression ratio to evaluate the compression performance of the soil. The calculation formula for the compression ratio is:

[0064]

[0065] Among them, h6 is the soil height of the consolidated sample with a load of 100 kPa, mm; h7 is the soil height of the consolidated sample with a load of 200 kPa after compression, mm; h8 is the initial height of the consolidated sample with a load of 100 kPa, mm; h9 is the initial height of the consolidated sample with a load of 200 kPa;

[0066] S102 calibrates the soil particle parameters. First, a uniaxial compression test of the soil is carried out to calculate the compression ratio. The coefficient of recovery X1, static friction coefficient X2, rolling friction coefficient X3, surface energy X4, plastic deformation ratio X5, bonding branch index X6 and tangential stiffness factor X7 are used as test factors. A uniaxial closed compression simulation test is carried out in EDEM. A cylinder with a height of 250 mm and a bottom diameter of 50 mm is used to simulate an acrylic cylinder. The particle-cylinder simulation parameters are set, and the particle-contact component model selects the Hertze-Mindlin model. A particle factory is set in the cylinder to generate 300 g of soil. Particles, measure the initial height of the model, use a loading speed of 30mm / s to perform a compression simulation test, when the axial pressure reaches 196.3N, move in the opposite direction at the same rate until the pressure is completely unloaded, measure the height h6 of the model at this time, repeat the simulation test, when the axial pressure is 392.7N, return at the same rate, after complete unloading, measure the consolidation height h7 of the sample, calculate the compression ratio α, take the soil compression performance index α as the evaluation index, first use the Plackett-Burman test to screen out the model parameters significantly related to the soil compression performance, then use the Box-Behnken Design test to obtain the regression model of the compression performance index and the significant factors, and solve the factor parameters corresponding to the actual compression performance index;

[0067] S103 determines relevant parameters of the straw discrete element model;

[0068] S2 establishes a simulated soil trough model according to the parameter calibration results;

[0069] S3 uses EDEM and Recurdyn software to couple simulation and analyze soil firmness, and selects the operating factors that have significant impact on compaction depth for further simulation tests. Specifically,

[0070] S301 introduces three cones into EDEM, gives a vertical downward speed of 0.1m / s, measures the firmness of the soil model at a depth of 0 to 20cm every 5cm, extracts the peak pressure on the cones and calculates the average value, obtains different soil firmness by adjusting the compaction degree of the soil trough model, and establishes soil trough models with different firmness;

[0071] S302 uses CATIA to establish a three-dimensional structural model of a tractor herringbone tire, and imports the established three-dimensional structural model of the tire into Recurdyn software;

[0072] S303 uses EDEM-Recurdyn software for coupled simulation, and uses the step function to let the tire fall freely onto the soil trough model within 0 to 0.5 seconds, and accelerate the tire to the operating speed evenly within 0.5 to 0.7 seconds. After 0.7 seconds, the tire moves forward at a uniform speed for compaction simulation test ( Fig.12 (a) is the interface display in EDEM during simulation. Fig.12 (b) is the interface display in Recurdyn during simulation), and the compaction depth of the tire on the soil trough model under different operating factors is obtained. The different operating factors include operating speed, soil firmness and straw coverage;

[0073] S304 selects the operating factors that are significant to the compaction depth, and the selected operating factors that are significant to the compaction depth are soil firmness.

[0074] S4 simulates the selected operating factors to obtain the soil compaction depth corresponding to the operating factors under different parameters. SPSS27 software is used to perform nonlinear power function regression analysis on the simulation test results to establish a mathematical model between the selected factors and the soil compaction depth.

[0075] L6=a*Y3 -b ;

[0076] Wherein, L6 is the soil compaction depth, the mathematical unit is mm; Y3 is the soil firmness, the mathematical unit is MPa, and a and b are positive constants.

[0077] In step S102, the specific steps of the soil uniaxial compression test are:

[0078] An appropriate amount of lubricating oil was applied to the inner wall of an acrylic cylinder (cut along the axis) with an inner diameter of 50 mm, an outer diameter of 70 mm, and a height of 150 mm to reduce the friction between the soil particles and the inner wall during the test. The cylinder was fixed with a hoop, and a 300 g soil sample was placed in the cylinder. The initial height h8 of the soil sample was measured, and the universal testing machine was set to push the platen downward at a constant speed of 8 mm / s until the axial pressure on the platen was 196.3 N (load 100 kPa). The platen was moved upward at the same rate until the pressure was completely unloaded. The soil height h6 at this time was measured. The above test was repeated, and the axial pressure on the platen was set to 392.7 N (load 200 kPa). The platen was moved upward at the same rate, and the consolidation height h7 and initial height h9 of the sample were measured, and the compression ratio α was calculated. The test was repeated three times, and the average value was taken to obtain the compression ratio of the surface soil and the compression ratio of the bottom soil.

[0079] The specific steps of the soil uniaxial compression simulation test are as follows:

[0080] To ensure that the particle factory generates enough particles, a cylinder with a height of 250mm and a bottom diameter of 50mm is used to simulate an acrylic cylinder. The particle-contact component model selects the Hertze-Mindlin (no slip) model. A particle factory is set up in the cylinder to generate 300g of soil particles and measure the initial height of the model. In the simulation compression test, it was found that the compression ratio obtained by applying a loading speed of 8mm / s and 30mm / s to the same sample was the same. In order to improve the simulation efficiency, a compression simulation test was performed using a loading speed of 30mm / s. Figure 4 This is the compression simulation test process. During the test, the pressure plate moves downward at 30 mm / s, and when the axial pressure reaches 196.3 N (load 100 kPa), it moves in the opposite direction at the same rate until the pressure is completely unloaded, and the height h6 of the model is measured at this time. The simulation test was repeated. When the axial pressure was 392.7N (load 200kPa), the carriage was returned at the same speed. After complete unloading, the consolidation height h7 of the sample was measured, and the compression ratio α was calculated. The amount of soil particle modeling was huge. In order to balance the calculation efficiency and simulation quality, two sizes of particles were selected for modeling. The surface soil was modeled with particles with a radius of 5mm, and the bottom soil was modeled with particles with a radius of 10mm. According to the contribution analysis of the seven experimental factors in the Plackett-Burman compression test to the soil compression performance and bearing capacity, the contribution of the 5mm soil particle compression performance was ranked from large to small as X5, X2, X7, X6, X1, X4, and X3, and the contribution of the 10mm soil particle compression performance was ranked from large to small as X3, X5, X2, X7, X1, X4, and X6. A Box-Behnken Design experiment was designed to analyze and find the optimal solution. The Design The expert conducted a multivariate regression analysis on the test results, eliminated the insignificant items in the variance analysis, and obtained the regression model of the 5mm particle compression ratio Y1 as follows:

[0081] Y1=a1+a2*X2+a3*X5+a4*X2*X5+a5*X5*X7-a6X7 2 ; a1~a6 are constants.

[0082] The regression model for the compression ratio Y2 of 10mm particles is:

[0083] Y2=b1+b2*X2+b3*X3+b4*X5-b5*X2*X5-b6*X2 2 -b7*X3 2 -b8*X5 2 ; b1~b8 are constants.

[0084] The present invention uses the soil compression ratio as an evaluation index for determining various parameters in a simulation test, selects three test factors that have a significant impact on the compression ratio from seven test factors, eliminates insignificant items in variance analysis, uses Design expert software to perform multiple regression analysis on the test results, and obtains regression models of the compression ratios of 5 mm particles and 10 mm particles, respectively, thereby obtaining soil EEPA model parameters corresponding to the simulation test that are consistent with the field test results, and finally selects the operating factors that are significant for the compaction depth, and establishes a mathematical model of the operating factors and the compaction depth, so as to facilitate the acquisition of the compaction depth and provide a basis for improving the accuracy of later tillage depth detection.

[0085] Example 2

[0086] Reference Figures 5 to 8 , which is the first embodiment of the present invention, provides a method for testing soil compaction depth, which can further determine relevant parameters of the straw discrete element model in combination with actual experiments.

[0087] Specifically, three straw collection points were randomly selected in the test field, and 10 pieces of broken straw were collected at each collection point. The straw length was measured with a steel ruler, and the straw diameter was measured with a vernier caliper. Finally, the average value was calculated, and the average straw length was 85.4 mm, the average diameter was 4.96 mm, and the straw density was 153 kg / m 3 , set Poisson's ratio to 0.4 and shear modulus to 1MPa;

[0088] In EDEM, a rigid unit consisting of five spherical particles with a diameter of 5 mm, a spherical center distance of 3 mm, and a length of 17 mm was established. The five rigid units were spliced ​​into a straw model through the element particles, with a total length of 85 mm. The adjacent rigid units were connected by bonding bonds in the BondingV2 model, and the normal bonding stiffness was set to 1.2×10 7 N / m 3 , tangential bond stiffness 1×10 7 N / m 3 , normal critical stress 4.3×10 7 N / m 2 , tangential critical stress 1.26×10 7 N / m 2 ;

[0089] The EEPA contact model was selected to restore the elastic-plastic and viscous contact characteristics inside the straw pile and between the straw and the soil when the straw was squeezed by the tire. The parameters of the EEPA contact model inside the straw were set as follows: the constant pull-off force was 0, the surface energy was 5.194 J / m 2, contact plastic deformation ratio is 0.5, loading branch index is 1.5, bonding branch index is 1.662, and tangential stiffness factor is 0.6; the parameters of the straw-soil EEPA contact model are: constant pull-off force 0, surface energy 10 J / m 2 , contact plastic deformation ratio 0.4, loading branch index 1.5, bond branch index 1.75 and tangential stiffness factor 0.667.

[0090] In this application, the tire selected is a 18.4-38 tractor herringbone tire, with a pattern type of R2, a standard rim W16L, a rim diameter of 970mm, a rated air pressure of 230kPa, an inflated outer diameter of 1807mm, a section width of 467mm, and a tire density of 1208kg / m 3 , rubber is an incompressible material, Poisson's ratio is set to 0.5, and the shear modulus is set to 2900 MPa. The final contact parameters between soil, straw, and rubber are shown in Table 1.

[0091] Table 1 Contact parameters of soil, straw and rubber

[0092]

[0093] The specific steps for determining the coefficient of restitution between straw and tire are:

[0094] After the rice was harvested, the rice straw was naturally dried for 10 days. The static friction coefficient of the rice straw-rubber was measured by an inclined plane test. Figure 5 (a) is the static friction coefficient measurement scenario. During the test, a straw is placed longitudinally on a rubber plate, and the rubber plate is slowly lifted. The lifting is stopped at the moment when the straw starts to slide on the rubber plate. The inclination angle of the rubber plate is measured at this time. The test is repeated 10 times and the average value is taken to obtain a straw-rubber static friction coefficient of 0.82.

[0095] The measurement method of rolling friction coefficient is the same as that of static friction coefficient. Figure 5 (b) is the rolling friction coefficient measurement scenario. A straw is placed horizontally on a rubber plate, and the rubber plate is slowly lifted. The lifting is stopped when the straw starts to roll on the rubber plate. The inclination angle of the rubber plate is measured at this time. The test is repeated 10 times and the average value is taken to obtain a straw-rubber rolling friction coefficient of 0.16.

[0096] The collision restitution coefficient is the ratio of the relative velocity of two objects after the collision to the relative velocity before the collision. It is only related to the materials of the colliding objects. Its calculation formula is: H1 is the initial height of the straw when it falls, mm; H2 is the maximum height of the straw that bounces after collision, mm.

[0097] Figure 6This is the test scenario for measuring the recovery coefficient of straw-rubber collision. During the test, the straw falls freely from a height of 300 mm and bounces back after colliding with the rubber plate. A high-speed camera is used to record the maximum height after the bounce. The test is repeated 10 times, and the average value is calculated to obtain a recovery coefficient of 0.45 between the straw and rubber.

[0098] Example 3

[0099] This is the third embodiment of the present invention. This embodiment is based on the first embodiment and further implements the derivation of the calculation formula of the compression ratio.

[0100] In soil mechanics, the standard compression coefficient a is usually used. 1-2 To evaluate the compressibility of soil, the larger the compression coefficient, the higher the compressibility. 1-2 It is defined as the decrease in porosity caused by the unit vertical pressure increment when the load increases from p1 (100 kPa) to p2 (200 kPa) when the soil is under uniaxial compression (fully confined):

[0101]

[0102] Where e1 is the porosity at a load of 100 kPa, and e2 is the porosity at a load of 200 kPa.

[0103] The porosity ratio is the ratio of the pore volume in the soil to the volume of soil particles. Figure 1 The following is a schematic diagram of the volume change of soil during compression. P3 is the initial load on the soil before compression, and P4 is the load on the soil after compression. Soil compression is mainly caused by the compression of pore volume. The compression of soil particles is very small, and the particle height before and after compression can be considered to remain unchanged.

[0104]

[0105] In the formula, h s is the height of soil particles, mm; h1 is the sum of the heights of soil particles and gaps before compression, mm; e3 is the porosity when the initial load on the soil is P3, which is calculated from the initial moisture content, initial density, water density and soil particle density before soil compression and can be regarded as a constant; h2 is the sum of the heights of soil particles and gaps after compression, mm; e4 is the porosity when the load on the soil is P4; s is the compression distance, mm.

[0106] From formula (2), we can get e4 as:

[0107]

[0108] It can be seen from formula (3) that when h1 is constant, e4 is linearly correlated with s. To simplify the analysis, the sum of the heights of the voids, particles, and water in the soil is regarded as the total height of the soil, and the compression reduction ratio α of the soil height when the load on the soil increases from 100 kPa to 200 kPa is used to evaluate the compression performance of the soil:

[0109]

[0110] Where, h3 is the height of the soil when the load is 100 kPa, mm; h4 is the height of the soil when the load is 200 kPa, mm; h5 is the initial height of the soil, mm;

[0111] The soil compression deformation is mainly plastic deformation, accompanied by a small degree of elastic deformation. When the load is greater than 100kPa in the uniaxial closed compression simulation test of soil in EDEM software, the uncompacted soil model will produce a larger elastic deformation during compression than the actual compression test, that is, the compression reduction ratio of the simulation test under the same conditions will be greater than the actual compression test, which is inconsistent with the actual test. Therefore, the compression ratio is calculated based on the height of the consolidated sample after the load is completely unloaded to evaluate the compression performance of the soil, and α is corrected to:

[0112] Example 4

[0113] Reference Figures 1 to 18 , which is the fourth embodiment of the present invention, is based on embodiment 2. This embodiment is combined with specific field experiments to further verify the reliability of the present application.

[0114] The soil sampling site was the rice stubble experimental field in Jiangdu District, Yangzhou City. The soil type was clay. Soil sampling was carried out at the surface layer with a depth of 0-225 mm and the bottom layer with a depth of 225-450 mm. The density of soil particles was measured using the pycnometer method. The measurement was repeated three times and the average value was taken. The surface soil density was measured to be 2009 kg / m 3 The density of the bottom soil is 2173kg / m 3 ,During the uniaxial compression test of soil, the compression ratio of the surface soil is 6.57%, and the compression ratio of the bottom soil is 5.63%.

[0115] In the soil uniaxial compression simulation test, the soil contact model uses the EEPA (Edinburgh Elasto-Plastic Adhesion) model. The parameters that need to be determined include constant pull-off force (f0), surface energy (△γ), contact plastic deformation ratio (λp), loading branch index (n), bonding branch index (X) and tangential stiffness factor (ktm). Among them, f0 is defined as 0. In EDEM, the loading branch index n can only be selected as 1 or 1.5. Since the stress-strain characteristics of actual soil are nonlinear, n is set to 1.5. The contact parameters that need to be determined in the soil discrete element model include the collision recovery coefficient (e) between soil particles, the static friction coefficient (μs), and the rolling friction coefficient (μr). The soil Poisson's ratio is set to 0.38 and the soil shear modulus is set to 1MPa. When conducting a uniaxial closed compression simulation test, in order to ensure that the particle factory generates sufficient particles, a cylinder with a height of 250 mm and a bottom diameter of 50 mm is used to simulate the acrylic cylinder. The particle-cylinder simulation parameter settings are shown in Table 2. The particle-contact component model selects the Hertze-Mindlin (no slip) model. A particle factory is set in the cylinder to generate 300 g of soil particles and measure the initial height of the model. In the simulation compression test, it was found that the compression ratio obtained by applying a loading speed of 8 mm / s and 30 mm / s to the same sample was the same. In order to improve the simulation efficiency, a compression simulation test was performed using a loading speed of 30 mm / s. Figure 4 This is the compression simulation test process. During the test, the pressure plate moves downward at 30mm / s. When the axial pressure reaches 196.3N (load 100kPa), it moves in the opposite direction at the same rate until the pressure is completely unloaded. The height h6 of the model is measured at this time. Repeat the simulation test. When the axial pressure is 392.7N (load 200kPa), return at the same rate. After complete unloading, the consolidation height h7 of the sample is measured, and the compression ratio α is calculated.

[0116] Table 2 Particle-cylinder simulation parameters

[0117]

[0118] Taking the soil compression performance index as the response value, the Plackett-Burman test is first used to screen out the model parameters significantly related to the compression performance to reduce the parameter calibration factors, and then the regression model of the compression performance index and the significant factors is obtained through the Box-Behnken Design test to solve the factor parameters corresponding to the actual compression performance index. The soil model parameter levels determined according to the existing technology and combined with the actual simulation situation are shown in Table 3, with one high level and one low level for each, for a total of 7 parameters.

[0119] Table 3 Simulation test factors and levels

[0120]

[0121] The amount of soil particle modeling is huge. In order to balance the calculation efficiency and simulation quality, two sizes of particles are selected for modeling. The surface soil is modeled with particles with a radius of 5 mm, and the bottom soil is modeled with particles with a radius of 10 mm. Due to the different contact parameters between soil particles of different sizes, the Plackett-Burman test is used to study the sensitivity of the model parameters of the two sizes of particles. The simulation test plan is designed using the software Design Expert. The simulation test design plan and results are shown in Table 3. Set X8~X 11 A total of 4 blank columns are used for error analysis.

[0122] Table 4 Plackett-Burman simulation compression test design and results

[0123]

[0124]

[0125] Considering that the height of the soil discrete element model will decrease after compaction, and the depth of the soil compacted by the tire generally does not exceed the depth of the surface soil, the test uses the average value of the soil firmness at a depth of 0 to 20 cm as the level of soil firmness. The soil firmness at a depth of 0 to 20 cm was measured every 5 cm in different test plots by using the TJS-100 soil firmness meter, and then the average value was calculated to determine the range of soil firmness levels. The range of factor levels was determined according to the tractor operating speed, soil firmness of the test field, and straw coverage, as shown in Table 5.

[0126] Table 5 Factor levels of soil compaction test

[0127]

[0128] A single factor simulation test was designed to analyze the influence of operating speed, soil firmness, and straw coverage on the soil compaction depth of tires, and then a uniform test was designed based on the test results to establish a soil compaction depth model. Each factor was taken at 5 levels, and a single factor soil compaction simulation test was designed as shown in Table 6. Since the soil firmness of the test field is difficult to adjust manually, it is impossible to select different soil firmnesses at the same level. According to the actual situation of the firmness of different test plots in Jiangdu District, Yangzhou City, a single factor soil compaction field test was designed as shown in Table 7.

[0129] Table 6 Soil compaction single factor simulation test design

[0130]

[0131]

[0132] Table 7 Single factor field test design for soil compaction

[0133]

[0134] The contribution of seven factors to soil compression performance and bearing capacity in the Plackett-Burman compression test is shown in Table 8. The contribution of 5mm soil particles to the compression performance is ranked from large to small as X5, X2, X7, X6, X1, X4, and X3, and the contribution of 10mm soil particles to the compression performance is ranked from large to small as X3, X5, X2, X7, X1, X4, and X6. According to the results of parameter sensitivity analysis, a Box-Behnken Design experiment is designed to analyze and find the optimal solution. For the 5mm particle model, the plastic deformation ratio X5, static friction coefficient X2, and tangential stiffness factor X7 are selected to design the levels of each factor as shown in Table 9, and the design of the Box-Behnken Design experiment is shown in Table 10. For the 10mm particle model, the rolling friction coefficient X3, plastic deformation ratio X5, and static friction coefficient X2 are selected to design the levels of each factor as shown in Table 11, and the design of the Box-Behnken Design experiment is shown in Table 12. The parameters of other factors are set to intermediate values.

[0135] Table 8 Plackett-Burman compression test sensitivity analysis

[0136]

[0137] Table 9 Factor levels of Box-Behnken test for 5 mm particles

[0138]

[0139] Table 10 Box-Behnken test scheme and results for particles with a radius of 5 mm

[0140]

[0141] Table 11 Factor levels of Box-Behnken test for particles with a radius of 10 mm

[0142]

[0143] Table 12 Box-Behnken test plan and results for particles with a radius of 10 mm

[0144]

[0145]

[0146] The variance analysis of the quadratic regression model is shown in Table 13. X2 and X5 have significant effects on the compression ratio in the uniaxial compression test of particles with a radius of 5 mm, and the significance of the effect is X5>X2. X2X5 and X5X7 have significant effects on the compression ratio, and the other interaction terms have no significant effect on the compression ratio. The quadratic term X7 2 The compression ratio is significantly affected, X2 2 、X5 2 The effect on the compression ratio is not significant. Using Design Expert to perform multiple regression analysis on the test results, eliminating the insignificant items in the variance analysis, the regression model of the compression ratio of 5mm particles is obtained as follows:

[0147] Y1=5.69+1.16X2+3.12X5+2.19X2X5+0.88X5X7-1.37X7 2 ;

[0148] The coefficient of determination R of the model 2 is 0.97, R adj 2 It is 0.93, and the regression equation has a good fitting degree and high reliability.

[0149] The Design expert constraint solving tool was used to solve the compression ratio of 6.57% as the target value. The soil compression simulation test was carried out to verify the obtained several groups of solutions, and the group of solutions with the smallest relative error between the simulation compression ratio and the test compression ratio was selected. The optimal solution of the 5mm radius particle model is: static friction coefficient X2 is 0.45, plastic deformation ratio X5 is 0.64, and tangential stiffness factor X7 is 0.63. Five soil compression simulation tests were carried out using the above parameters, and the remaining parameters were taken at the middle level. The average soil compression ratio was 6.47%, and the relative error with the actual test measurement value was -1.52%. Analysis shows that the error between the simulation result and the actual test compression ratio is small.

[0150] Table 13 Analysis of variance of quadratic regression model for Box-Behnken test of 5 mm particles

[0151]

[0152]

[0153] For the particle model with a radius of 10mm, the Design expert software was used to solve the problem with a compression ratio of 5.63% as the target value. The solved parameters were used for soil compression simulation test, and a set of solutions with the smallest difference between the simulation compression ratio and the test compression ratio was selected. The optimal solution obtained was: static friction coefficient X2 was 0.36, rolling friction coefficient X3 was 0.25, and plastic deformation ratio X5 was 0.65. Five soil compression simulation tests were carried out using the optimal solution, and the average value of the five tests was 5.81%, which was close to the actual value, with a relative error of 3.20%. The error between the simulation result and the actual test compression ratio was small.

[0154] Table 14 Analysis of variance of quadratic regression model for Box-Behnken test of 10 mm particles

[0155]

[0156] Note: P value < 0.05 indicates significant, and < 0.01 indicates extremely significant.

[0157] From the variance analysis table 14, it can be seen that in the simulation compression test of particles with a radius of 10 mm, X2, X3, and X5 have significant effects on the compression ratio, and the significance of the influence is X3>X5>X2. X2X5 has a significant effect on the compression ratio, while X2X3 and X3X5 have no significant effect on the compression ratio. The quadratic term X2 2 、X5 2 、X7 2 The compression ratio is significantly affected. Using Design Expert to perform multiple regression analysis on the test results, eliminating the insignificant items in the variance analysis, the regression model of the compression ratio of 10mm particles is obtained as follows:

[0158] Y2=6.88+0.76X2+1.25X3+0.92X5-0.72X2X5-1.19X2 2 -1.31X3 2 -1.87X5 2 (twenty two)

[0159] The coefficient of determination R of the model 2 is 0.99, R adj 2 It is 0.97, indicating that the regression equation has a good fit and high reliability.

[0160] The coefficient of restitution between the surface soil and the bottom soil is set to 0.3, the coefficient of static friction is set to 0.5, and the coefficient of rolling friction is set to 0.3. Since the calibration results of the EEPA contact model parameters of the surface and bottom soil particles are similar, the EEPA model of the contact between the surface and bottom soil particles takes the average of the calibration values ​​of the two, that is, the surface energy is 12.5 J / m 2, contact plastic deformation ratio 0.645, bond branching index 2.25, and tangential stiffness factor 0.665.

[0161] Fig.13 This is the soil-straw discrete element model diagram. According to the parameter calibration results, a 225 mm high bottom soil layer is established using 10 mm radius particles, with a total of 97,590 particles generated. A 225 mm high surface soil layer is established using 5 mm radius particles, with a total of 772,085 particles generated. A straw pile is generated on the surface soil, with a total of 91,950 straws generated (1.2 kg / m 2 coverage amount). Fig.14 Figure 2. The tire compaction traces in EDEM and Recurdyn. Fig.15 It is a cross-sectional view of the compaction trace. It can be seen from the figure that the straw broke and bent under the compression of the tire and mixed with the soil particles, which is consistent with the actual test, indicating that the constructed model can simulate the real test scene well. Fig.16 (a) is the tire compaction field test scene. Fig.16 (b) is the tire compaction mark, Fig.16 (c) Soil compaction depth measurement.

[0162] Fig.17 is the soil compaction simulation result. Fig.18 The results of the soil compaction field test. When the soil firmness and straw coverage remain unchanged, the tire compaction depth in both the simulation test and the field test decreases with the increase of the operating speed. This is because when the tire compacts the soil, the higher the speed, the shorter the time it takes to compact the soil, that is, the shorter the time the pressure acts on the soil, resulting in a decrease in the compaction depth. In the simulation test, the compaction depth at a speed of 7.5 km / h is 94.81% of the compaction depth at a speed of 1.5 km / h, a decrease of 5.2 mm; in the field test, the compaction depth at a speed of 7.5 km / h is 93.88% of the compaction depth at a speed of 1.5 km / h, a decrease of 6 mm. In general, the effect of the change in operating speed on the compaction depth is not significant. As the operating speed increases, the degree of reduction in the soil compaction depth is small. In subsequent simulation tests, the operating speed is taken as the middle value of the test factor range, that is, 4.5 km / h.

[0163] When the operating speed and the amount of straw coverage remain unchanged, the compaction depth of both the simulation test and the field test decreases with the increase of firmness. In the simulation test, the compaction depth of the compaction depth of 3MPa is 64.36% of the compaction depth of 1MPa, which is 43.8mm lower; in the field test, the compaction depth of 2.87MPa is 66.11% of the compaction depth of 1.12MPa, which is 41mm lower. It can be seen that the change of firmness has a significant impact on the compaction depth. For every 0.5MPa increase in firmness, the soil compaction depth decreases by 12.5mm, 11.9mm, 10.2mm, and 9.2mm, respectively, and gradually decreases. This is because as the soil firmness increases, the soil's ability to resist external compaction becomes stronger and becomes more and more difficult to compress.

[0164] When the operating speed and soil firmness remain unchanged, the compaction depth decreases with the increase of straw coverage. The straw plays a certain buffering role when the tire compacts the soil, reducing the degree of soil compaction by the tire. In the simulation test, the straw coverage is 1.2kg / m 2 The compaction depth was 96.12% of that without straw covering, which was 3.9 mm lower. The straw covering amount in the field test was 1.2 kg / m 2 The compaction depth is 94.90% of that without straw covering, which is 5mm lower. It can be seen that the change of straw covering amount has no significant effect on the compaction depth. In the subsequent simulation test, the straw covering amount is taken as the middle value of the test factor range, that is, 0.6kg / m 2 .

[0165] According to the single factor test results, the operating speed was set to 4.5 km / h and the straw coverage was set to 0.6 kg / m 2 , taking soil firmness as the test factor and soil compaction depth as the response quantity, a single factor nine-level equal-level simulation test was designed and the results are shown in Table 15.

[0166] Table 15 Design and results of equal-level simulation tests

[0167]

[0168] From a theoretical analysis, assuming that the soil depth is infinite, when the soil firmness tends to infinity, the compaction depth tends to 0. When the soil firmness tends to 0, the tire will sink into the soil and the compaction depth tends to infinity. Therefore, the compaction depth model should be a power function. In order to reduce the error, the actual firmness of the discrete element model is used as the independent variable, and the simulation test results are analyzed by nonlinear power function regression using SPSS27 software. The fitting results are as follows:

[0169] L6=127.339*Y3 -0.401

[0170] In the formula, the correlation coefficient R of the model is 2 The value is 0.992, which indicates that the model has a good fit.

[0171] To verify the soil compaction depth model, five test plots with different soil compaction densities were randomly selected for tire compaction tests. The tractor speed was 4.5 km / h and the straw coverage was 0.6 kg / m 2 ,The test results are shown in Table 16. It can be seen that the relative error is within the range of ±3.44%, and the consistency between the model prediction value and the test value is good.

[0172] Table 16 Verification results of soil compaction depth model test

[0173]

[0174] It can be seen from this embodiment that the present invention can be used to establish a mathematical model of the soil compaction depth of agricultural machinery during field operations, providing a research basis for improving the accuracy of subsequent tillage depth detection.

[0175] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed dedicated integrated circuit for this purpose.

[0176] Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. A computer program includes a plurality of instructions that may be executed by one or more processors.

[0177] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or communicates with a charged particle tool or other imaging device, etc. Aspects of the present invention can be implemented in a machine-readable code stored on a non-transitory storage medium or device, whether it is removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by a computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention herein includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself. The computer program can be applied to input data to perform the functions of this article, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on a display.

[0178] As used in this application, the terms "component", "module", "system", etc. are intended to refer to a computer-related entity, which can be hardware, firmware, a combination of hardware and software, software, or software in operation. For example, a component can be, but is not limited to: a process running on a processor, a processor, an object, an executable file, a thread in execution, a program, and / or a computer. As an example, an application running on a computing device and the computing device can both be components. One or more components can exist in a process and / or thread in execution, and a component can be located in a computer and / or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures thereon. These components can communicate in a local and / or remote process manner, such as according to a signal having one or more data packets (e.g., data from a component that interacts with another component in a local system, a distributed system, and / or interacts with other systems in a signal manner through a network such as the Internet).

Claims

1. A method for testing soil compaction depth, characterized in that: The following steps are involved: S1 Calibration of soil particle parameters, determination of coefficient of restitution, static friction coefficient, rolling friction coefficient, surface energy, plastic deformation ratio, bond branching index and tangential stiffness factor; S2 establishes a simulated soil trough model according to the parameter calibration results; S3 uses EDEM and Recurdyn software to couple simulation and analyze the effects of different operating factors on soil compaction depth, conducts single factor tests, and selects operating factors with significant effects on compaction depth for further simulation tests; S4 simulates the screened operating factors to obtain the soil compaction depth corresponding to the operating factors under different parameter ranges. SPSS 27 software is used to perform nonlinear power function regression analysis on the simulation test results to establish a mathematical model between the screened factors and the soil compaction depth.

2. The method for testing soil compaction depth according to claim 1, characterized in that: The specific steps of calibration are: S101 evaluates the compression performance of soil by calculating the compression ratio based on the height of the consolidated specimen after the load is completely unloaded; S102 calibrates soil particle parameters based on soil uniaxial compression test, takes recovery coefficient X1, static friction coefficient X2, rolling friction coefficient X3, surface energy X4, plastic deformation ratio X5, bonding branch index X6 and tangential stiffness factor X7 as test factors, and takes soil compression performance index α as evaluation index. First, the Plackett-Burman test is used to screen out model parameters significantly related to soil compression performance, and then the regression model of compression performance index and significant factors is obtained through Box-Behnken Design test, and the factor parameters corresponding to the actual compression performance index are solved; S103 determines relevant parameters of the straw discrete element model.

3. The method for testing soil compaction depth according to claim 2, characterized in that: In step S101, the calculation formula of the compression ratio is: ； Among them, h6 is the soil height of the consolidated sample with a load of 100 kPa, mm; h7 is the soil height of the consolidated sample with a load of 200 kPa after compression, mm; h8 is the initial height of the consolidated sample with a load of 100 kPa, mm; h9 is the initial height of the consolidated sample with a load of 200 kPa.

4. The method for testing soil compaction depth according to claim 3, characterized in that: When conducting a uniaxial closed compression simulation test in EDEM, a cylinder with a height of 250 mm and a bottom diameter of 50 mm was used to simulate an acrylic cylinder. The particle-cylinder simulation parameters were set, and the Hertze-Mindlin model was selected as the particle-contact component model. A particle factory was set in the cylinder to generate 300 g of soil particles. The initial height of the model was measured and a compression simulation test was carried out using a loading speed of 30 mm / s. When the axial pressure reached 196.3 N, it moved in the opposite direction at the same rate until the pressure was completely unloaded. The height h6 of the model was measured at this time, and the simulation test was repeated. When the axial pressure was 392.7 N, the car was returned at the same rate. After complete unloading, the consolidation height h7 of the sample was measured, and the compression ratio α was calculated.

5. The method for testing soil compaction depth according to claim 4, characterized in that: In step S102, the surface soil is modeled with particles of 5 mm radius. According to the contribution analysis of the seven test factors to the soil compression performance and bearing capacity in the Plackett-Burman compression test, the contribution of the 5 mm soil particle compression performance is ranked from large to small as X5, X2, X7, X6, X1, X4, and X3. A Box-Behnken Design test is designed to analyze and find the optimal solution. The test results are subjected to multiple regression analysis using Design expert. The insignificant items in the variance analysis are eliminated, and the regression model of the 5 mm particle compression ratio Y1 is obtained as follows: <h2 style=";text-align:left;direction:ltr">Y1=a1+a2*X2+a3*X5+a4*X2*X5+a5*X5*X7-a6X7<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> ; Among them, a1~a6 are constants.

6. The method for testing soil compaction depth according to claim 4, characterized in that: The bottom soil is modeled with particles of 10 mm radius. The contribution of the 10 mm soil particles to the compression performance is ranked from large to small as X3, X5, X2, X7, X1, X4, and X6. According to the results of parameter sensitivity analysis, a Box-Behnken Design experiment is designed to analyze and find the optimal solution. The test results are analyzed by multiple regression analysis using Design expert. After eliminating the insignificant items in the variance analysis, the regression model of the 10 mm particle compression ratio Y2 is obtained as follows: <h2 style=";text-align:left;direction:ltr">Y2=b1+b2*X2+b3*X3+b4*X5-b5*X2*X5-b6*X2<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> - b7*X3<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> - b8*X5<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> ; Among them, b1~b8 are constants.

7. The method for testing soil compaction depth according to claim 4, characterized in that: Step S3 specifically The following steps are included: S301 introduced three cones into EDEM, set a vertical downward speed of 0.1 m / s, measured the firmness of the soil model at a depth of 0 to 20 cm every 5 cm, extracted the peak pressure on the cones and calculated the average value, and obtained different soil firmness by adjusting the compaction degree of the soil trough model, and established soil trough models with different firmness; S302 uses CATIA to establish a three-dimensional structural model of a tractor herringbone tire, and imports the established three-dimensional structural model of the tire into Recurdyn software; S303 EDEM-Recurdyn software coupling simulation was used to make the tire fall freely onto the soil trough model within 0-0.5 s using the step function, and the tire was uniformly accelerated to the operating speed within 0.5 s-0.7 s. After 0.7 s, the tire moved forward at a uniform speed for compaction simulation test to obtain the compaction depth of the tire on the soil trough model under different operating factors, including operating speed, soil firmness and straw coverage. S304 Screen out operational factors that have significant impact on compaction depth.

8. The method for testing soil compaction depth according to claim 7, characterized in that: The operational factor screened out as significant for compaction depth is soil firmness.

9. The method for testing soil compaction depth according to claim 8, characterized in that: The mathematical model between soil compaction depth and soil firmness is, L6=a*Y3 -b ; Wherein, L6 is the soil compaction depth, the mathematical unit is mm; Y3 is the soil firmness, the mathematical unit is MPa, and a and b are positive constants.

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