Innovative Design and Mechanical Analysis of Low-Resistance Fritilariae Ussuriensis Maxim Excavation Device

Abstract

Fritilariae ussuriensis maxim can be used as a medicine with little difficulty in its planting, but owing to its fragile characteristics, Fritilariae ussuriensis maxim is mainly collected by manual excavation. In order to solve the problems of the low working efficiency and poor environmental adaptability of the harvesting equipment of Fritilariae ussuriensis maxim, this paper designs a new excavation device, which can effectively reduce the operation resistance and improve the excavation efficiency of Fritilariae ussuriensis maxim. In this paper, the finite element method and discrete element method are used to simulate and analyze the operation performance of the excavation device. Combined with the orthogonal test and single factor test, the factors affecting the operating performance of the excavating device were explored. The excavating experimental platform was designed and built, and the simulation results were verified with experimental excavation data. This study shows that the operating speed, shovel face inclination angle, and digging depth had significant effects on the digging resistance of the shovel body, with the shovel face inclination angle having the highest influencing factor and the operating speed having the lowest influencing factor. Combined with the orthogonal test analysis and response surface design, the optimal operating parameters of the shovel body are: operating speed 0.5 m/s, shovel face inclination angle 25°, and excavation depth 120 mm.

1. Introduction

The bulb of Fritilariae ussuriensis maxim can be used as a medicine. It has the effects of relieving coughs, resolving phlegm, moistening the lungs, and dispersing knots. It can be used as the primary treatment for bronchitis, tuberculosis, pneumonia, whooping cough, phlegm and asthma, ulcers, lymphoid tuberculosis, mastitis, carbuncles, and other diseases [1]. At the same time, Fritilariae ussuriensis maxim has low difficulty in planting and high output, making it suitable for large-scale planting. But currently, the harvesting of Fritilariae ussuriensis maxim in China is still dominated by manual excavation and sorting, and there is a huge demand for human labor in the harvesting process [2]. The manual excavation and sorting method is not only time-consuming and inefficient, but it is also difficult to complete the harvesting operation of Fritilariae ussuriensis maxim during the best harvesting period. Therefore, it is of great significance to research excavation devices as mechanized harvesting equipment to improve the efficiency and quality of the harvesting operations.

Zhao studied the development of potato harvesting machinery at home and abroad, and found that the harvesting efficiency of potato harvesting machinery was low and cannot meet the rapid development needs of the potato industry [3]. Yang et al. designed a vertical circular separation and transportation device for a potato combine harvester to solve the problems of poor separation and transportation efficiency, and inflexible operation. Through the theoretical analysis of the separation and conveying device, mathematical models were established for parameter optimization between various experimental factors and indicators, producing optimal design parameters [4]. Matmurodov et al. proposed a new harvester scheme and developed a mathematical simulation for its transmission mechanism. This model could help harvester developers to determine the required dimensions and dynamic parameters [5]. Yu et al. designed a biomimetic potato-digging shovel using the biomimetic form of mole fingers to reduce the traction of traditional flat potato-digging shovels. They compared and analyzed the traditional and biomimetic digging shovels using the finite element method, soil tank test method, and on-site test method, verifying the feasibility and effectiveness of the biomimetic potato-digging shovels [6]. Li et al. designed a new kind of bionic potato soil shovel based on pangolin scales, used the discrete element method to simulate the drag reduction performance of the new shovel under clay conditions, and compared it with an ordinary flat shovel. The results showed that the drag reduction rates of the new biomimetic shovel in soil tank tests and on-site tests were 22.26% and 14.19%, respectively, which were better than those of ordinary flat shovels [7]. Naveen Kumar et al. proposed a new design method that utilized the availability of electricity after removing the tillage components of the rotary tiller to transform a single-row potato excavator into an accessory for power tillers. This improvement resulted in 60% cost savings for excavators compared with manual excavation using shovels [8]. Shi et al. developed a disc grate potato excavator that was compatible with four-wheeled tractors. The machine adopted a grid-type excavation device and a disc grid-type separation device, and the key parameters of the excavation device and separation device were determined through calculation, effectively improving the separation efficiency of the excavator [9].

With the continuous development of the Fritilariae ussuriensis maxim industry, the existing harvesting equipment [10,11,12,13] had gradually encountered problems, such as low operational efficiency and poor environmental adaptability. As the core component of Fritilariae ussuriensis maxim harvesters, the excavating device directly affects the quality of the harvesting operation. Based on this, this paper improves the design of the digging device of a 4QPB-1201 Fritilariae ussuriensis maxim harvester and explores the factors affecting the performance of the digging device, providing a theoretical basis for the design of digging devices for Fritilariae ussuriensis maxim harvesters.

2. Materials and Methods

2.1. Structural Design and Statics Simulation of the Excavation Device of Fritilariae Ussuriensis Maxim

2.1.1. Overall Scheme Design

In this paper, the excavation device of a 4QPB-1201 Fritilariae ussuriensis maxim harvester was studied in depth. The shovel blade of the excavation device is a monolithic structure fixed on a frame, which cannot be adjusted to the specific operating environment of the harvesting site regarding the shovel face inclination and operating depth. There is no extension mechanism with preliminary screening after the excavation shovel, resulting in an inability to perform initial screening of the shoveled shellac mixture. The shovel structure is a whole flat shovel plate, and there is no baffle at the end of the shovel plate, which could cause soil overflow and influence the overall working effect of the shovel to some extent. The soil crushing knife is a straight knife with an edge, which has better soil crushing performance, but it easily causes damage to Fritilariae ussuriensis maxim bulbs and the edge is easily worn by gravel. The 4QPB-1201 Fritilariae ussuriensis maxim harvester is shown in Figure 1.

In response to the above problems, a new type of Fritilariae ussuriensis maxim excavation harvester is designed, as shown in Figure 2. The device is mainly composed of a excavator shovel mechanism and a bulldozer shovel mechanism. The hydraulic system of the supporting tractor provides the power source for the hydraulic cylinder of bulldozer shovel mechanism and hydraulic motor of excavator shovel mechanism respectively. Before the start of the harvesting operation, the operator can make targeted adjustments to the bulldozer shovel and excavator shovel according to the thickness of the overburden layer and the bulbs’ growth depth of the Fritilariae ussuriensis maxim at the work site, so as to improve the operating efficiency of the harvester and reduce the working pressure of the lifting and screening device. During the harvesting operation, the bulldozer shovel and excavator shovel cut into the border soil in turn. As the harvester continues to advance, the bulldozer shovel pushes the cover soil layer to the bottom of the two sides, and the excavator shovel digs out the Fritilariae ussuriensis maxim and soil mixture, which is transported to the screening mechanism through the lifting device, thus completing the whole harvesting task.

2.1.2. Design of Excavator Shovel Mechanism

The excavator shovel mechanism is mainly composed of first-order shovel blade, second-order shovel blade, extension fence, hydraulic motor, slider linkage, and other components. The excavator shovel mechanism is shown in Figure 3. During operation, the mechanism can adjust the operating parameters of the first-order shovel, according to the specific conditions of the work site, by driving the slider connecting rod mechanism with the hydraulic motor, so as to improve the overall operation quality of the harvesting equipment. The blade shape of the first-order shovel body is a wave, and the more the shovel tips in this shape, the better the soil performance, but the damage rate of the Fritilariae ussuriensis maxim also increases [14]. Therefore, the number of shovel tips was set to 10 after considering various factors. The second-order shovel body consists of curved shovel blades, with an 8 mm gap set between each blade. Therefore, under the premise of ensuring the net rate, the soil breaking performance of the curved shovel blades was fully utilized to separate the Fritilariae ussuriensis maxim and soil for the first time.

2.1.3. Design of Bulldozer Shovel Mechanism

As shown in Figure 4, the bulldozer shovel consists of main mechanisms such as the shovel body, connecting rod, slide rail, locking lever, SBR slide rail, and hydraulic cylinder. The excavator shovel pushes the slide table by hydraulic cylinder, and drives the connecting rod to move along the track of slide groove, so as to adjust the inclination of the bulldozer shovel surface. In order to improve the soil penetration and crushing performance of the bulldozer blade, the blade of the bulldozer was designed as an alternating arrangement of soil fragments and triangular blades. The shovel blade inherits the excellent soil performance of the wave blade and further strengthens the soil crushing performance. In order to improve the mechanical properties of the shovel body, 65 Mn is selected as the manufacturing material.

2.1.4. Force Analysis of Excavation Device

In addition to the above parameters, the main parameters of shovel type include the inclination angle of shovel surface, the opening angle of the shovel blade, and the length of the shovel blade. During the operation, the force exerted on the surface of the shovel body is shown in Figure 5.

Through mechanical analysis, the equation of shovel entry angle $\alpha$ can be obtained as follows:

$$\alpha =arctan\frac{P-\mu G}{P+\mu G}$$

(1)

where P—inertial force of the soil, N; G—gravitational force on the mixture of Fritilariae ussuriensis maxim and soil, N; $\mu$—friction coefficient between the shovel blade and the mixture of Fritilariae ussuriensis maxim and soil.

Combined with the relevant design literature [15,16,17], it can be obtained that the value of the shovel face inclination angle ranges from 15° to 30°; the smaller the shovel face inclination angle, the smaller the digging resistance of the shovel body, the worse the soil breaking performance. If the inclination of the shovel face becomes larger, the digging resistance of the shovel body will also become larger, but the soil breaking performance will be better. In order to take into account the two indicators of soil entry performance and digging resistance, the shovel face inclination angle is usually taken as 25° under ideal operating conditions.

The relationship among the length of the shovel blade, the working depth and the inclination angle into the soil is shown in Equation (2):

$$L=\frac{H}{\sin \alpha }$$

(2)

where L—length of shovel blade, mm; $\alpha$—inclination of the shovel blade into the soil, °; H—digging depth of shovel blade, mm.

The minimum digging depth of 100 mm and the maximum entry angle of 30° are substituted into Equation (2) to obtain the shovel blade length L of 200 mm.

P and F are interactive forces, the formula for calculating the digging resistance is shown in Equation (3):

$$F=KPB$$

(3)

where F—excavation resistance, N; K—resistance per unit area, N·mm⁻²; B—shovel blade operating width, mm.

According to the soil environment of the Fritilariae ussuriensis maxim planting area, the value of 4~5 N·mm⁻² was determined, and the value of 5 N·mm⁻² was taken for the excavation operation, and the relevant design parameters of the shovel blade are shown in

Table 1. Parameters table of shovel blade.

Parameters	Numerical Value	Parameters	Numerical Value
First-order shovel blade digging depth	180 mm	Second-order shovel blade digging depth	90 mm
First-order shovel blade working width	140 mm	Second-order shovel blade working width	68 mm
Digging resistance F1	1260 N	Digging resistance F2	306 N

.

Similarly, the force analysis of the operation process of the bulldozer, combined with the relevant design theory can be obtained, the working width of the bulldozer is taken as 1400 mm; the minimum digging depth is taken as 120 mm, brought into Equation (2), the shovel body length can be found as 240 mm; K = 4 × 10⁻² N·mm⁻², H = 100 mm, B = 1200 mm, we can obtain the digging resistance F is 4800 N.

2.1.5. Statics Analysis of Excavating Device

(1)

Statics analysis of excavating shovel

Statistical analysis of the excavation device based on the results of the force analysis. The shovel material is set as 65 Mn, and Young’s modulus 8.19 × 10¹⁰ Pa, Poisson’s ratio 0.288, density 7.81 g/cm³, yield strength 4.3 × 10⁸ Pa, and tensile strength 7.35 × 10⁸ Pa; then, complete the mesh division of shovel model. According to the force analysis results, a force of 1260 N is loaded on the force surface of the first-order shovel model, with a load direction of 25° to the shovel surface; a force of 306 N is loaded on the force surface of the second-order shovel, with the load direction at 30° to the shovel surface, as shown in Figure 6. The calculated total deformation cloud, elastic deformation cloud, and equivalent force cloud are shown in Figure 7, Figure 8, and Figure 9, respectively.

As shown in Figure 7, the maximum deformation values of the first-order and second-order shovels under predicted conditions are 0.0016729 mm and 0.00094758 mm, respectively. During the harvesting operation of the Fritilariae ussuriensis maxim harvester, the working depth value of the tip part of the first-order shovel is the largest, and the digging resistance value is slightly larger than that of other shovel areas. Moreover, this part mainly undertakes the task of crushing soil, so the maximum deformation occurs here. Although the maximum deformation value is less than 0.002 mm, it should be noted that the tip part is prone to wear during operation. With the accumulation of effective operation time, the thickness at this point will gradually decrease, which will eventually affect the operation quality. Therefore, during the machining process of the shovel body, processes such as heat treatment or wear-resistant coating should be adopted to improve the overall performance of shovel tip. The first and last ends of the second-order shovel are both fixed on the support rod of the frame, so the deformation is mainly concentrated in the middle surface area. However, this deformation variable is less than 0.001 mm, which can be almost ignored and will not affect the quality of the second-order shovel operation.

As shown in Figure 8, the maximum elastic deformation point is 2.7121 × 10⁻⁵ mm, and the minimum elastic deformation point is 2.1362 × 10⁻¹¹ mm; when the load of the second-order shovel is set at 306 N and the angle is set at 30°, the maximum elastic deformation point is located at the bolt connection at the first end of the shovel body with a value of 2.3391 × 10⁻⁵ mm, and the minimum elastic deformation point is located at the end corner of the shovel body with a value of 2.5605 × 10⁻⁹ mm. The maximum elastic deformation values mentioned above do exceed 2.8 × 10⁻⁵ mm. In other words, during the operation process, the elastic deformation values of the shovel body are small, which will not have adverse effects on the performance of the whole machine.

As shown in Figure 9, the maximum stress point is located on the right angle connection line between the first-order shovel and the support, and its value is 3.0703 Pa; the minimum stress point is located at the tip of the shovel, and its value is 2.3618 × 10⁻⁶ Pa. The maximum and minimum stress points of the first-order shovel are the same as the maximum and minimum elastic deformation points. When the load is set at 306 N and the angle is set at 30°, the maximum stress is 2.6056 Pa and the minimum stress is 0.00054021 Pa. The maximum and minimum strain points are the same as the maximum and minimum elastic deformation points. The maximum stress values of the first- and second-order shovels are all less than 4.30 × 10⁸ Pa. In other words, the strength of the first- and second-order shovels meets the design requirements.

(2)

Statics analysis of bulldozer shovel

The Static Structural component of ANSYS software was used to carry out statics analysis on the bulldozer shovel. The model type is set to linear, elastic, and isotropic. The simulation material for the bulldozer body is 65 Mn, and the minimum mesh size is 4 mm; a fixed constraint is added to the tail joint of the simulation model, a torque of 10 N·mm is added to the shaft hole, a force of 4800 N is loaded on the front force surface, and the load direction is at an angle of 25° with the surface of bulldozer. The calculated static simulation analysis of the bulldozer is shown in Figure 10.

From the simulation results in Figure 10, it can be seen that when the load is set to 1260 N and the angle is set to 25°, the maximum deformation value of the bulldozer shovel is 0.17848 mm, which is mainly concentrated on both sides of the shovel blade; the maximum elastic deformation is 0.00068853 mm and the minimum elastic deformation is 5.3811 × 10⁻¹¹ mm. The maximum stress value is 107.81 Pa, and the minimum stress value is 1.0762 × 10⁻⁶ Pa. Its deformation value, stress value, and elastic deformation are in accordance with the design requirements.

2.2. Field Harvesting Experiment

In order to test the performance of the optimized harvester in the field, a field harvesting trial was conducted in June 2022 at the planting base of Fritilariae ussuriensis maxim in Heilongjiang Infinity Forest Town Green Organic Agriculture Development Co. Ltd. The basic conditions for planting Fritilariae ussuriensis maxim at the base are as follows: the bottom of the border is 1200 mm wide, the border is 1100 mm wide, the border height is 50 mm, the walkway ditch is 500 mm wide, and the average thickness of the mulch layer is 10 mm; the average thickness of the mixed layer of Fritilariae ussuriensis maxim and soil was 30 mm, the diameter of flat maidenhair was 2.5~18 mm, and the moisture content of the soil was 17.8%; the soil was loose, the black soil layer was thick, the humus content was high, the soil structure was good, and the nutrients were rich. The supporting power of the Fritilariae ussuriensis maxim harvester is the Dongfanghong (First Tractor) LX904 wheeled tractor with power of 66.2 kW and operation speed of 1.65 km/h, one step slower, as shown in Figure 11.

The main indicators of harvesting performance of the harvesting machine are the removal rate of bulbs, the damage rate of bulbs, the soil content rate, and the harvesting efficiency. The damage rate of bulbs directly affects the market value of Fritilariae ussuriensis maxim and the harvesting efficiency is the main index of economic performance of harvester. According to the conclusion of the optimized design of the excavation shovel, adjust the angle $\alpha$ of entry of the shovel blade into the soil, with reference to the national standards “General Provisions for the Determination of Agricultural Machinery Test Conditions” (GB/T5262-2008), “Agricultural Machinery Production Test Methods” (GB5667-2008), and the harvesting test methods of other underground cash crops [18], three sets of tests with the entry angle α of 20°, 25°, and 30° were set in turn, and the specific data of the three sets of tests are shown in

Table 2. Field test results.

Blade Penetration Angle α (°)	Excavation Depth (mm)	Net Recovery Rate (%)	Damage Rate (%)	Soil Content (%)	Recovery Efficiency (hm2·h−1)
20	82	93.5	5.6	12.9	0.15
25	101	97.6	3.9	15.3	0.13
30	120	99.2	1.2	18.6	0.10

.

As seen from Table 2, the excavation depth gradually increased when the entry angle α is 20°, 25°, and 30°. With the increase in excavation depth, the collection rate of bulbs of Fritilariae ussuriensis maxim increased from 93.5% to 99.2%. At the same time, the soil content in the mixture of Fritilariae ussuriensis maxim’s bulbs and soil increased with the increase in excavation depth, resulting in the increase in soil content from 12.9% to 18.6%. With the increase in excavation depth, the chance of direct contact between the excavation shovel and Fritilariae ussuriensis maxim’s bulbs decreased, so the damage rate of bulbs decreased from 5.6% to 1.2%. The gradual increase in digging depth also leads to the gradual increase in digging resistance, resulting in the decrease in harvesting efficiency from 0.15 hm²·h⁻¹ to 0.10 hm²·h⁻¹. Considering all the indicators of the test, it can be concluded that the field operation performance of the harvester is most ideal when the angle α of digging shovel into the soil is 25°.

2.3. Discrete Element Modeling

During the harvesting operation of Fritilariae ussuriensis maxim, the main objects of study are the soil–Fritilariae ussuriensis maxim’s bulbs–root system agglomerates. Therefore, before conducting the excavation simulation test of Pinnacle, it is necessary to first establish a soil–Fritilariae ussuriensis maxim’s bulbs–root cluster model.

2.3.1. Parameter Determination

The soil and Fritilariae ussuriensis maxim selected in this paper are all from the planting base of Fritilariae ussuriensis maxim in Lanxi County, Heilongjiang Province, with a soil texture type of sandy loam. The ring tool method, drying method, screening method, and cylinder lifting method are used to detect the soil samples [19,20,21], and the particle diameter ratio in the soil samples is measured as shown in

Table 3. Percentage of particles in soil samples.

Particle Diameter	Numerical Value
≥2 mm	18.66%
>1~2 mm	23.05%
>0.1~1 mm	48.36%
≤0.1 mm	9.93%

.

The main particle size distribution interval is 0.1 to 2 mm; soil density is 1.59 g/cm³; soil moisture content is 17.8%; soil accumulation angle is 38.9°. The samples of Fritilariae ussuriensis maxim are obtained by detecting and analyzing the three-dimensional mean values of bulbs of Fritilariae ussuriensis maxim are 20.34 mm, 18.22 mm, and 12.31 mm; the density of bulbs is 1.104 g/cm³, the moisture content of bulbs is 77.50%, the elastic modulus of bulbs $E$ is 3.5 MPa; the ratio of bulbs $\mu$ is 0.35; the density of roots is 0.1 g/cm³, the ratio of roots is 0.5.

2.3.2. Simulation Model Building

The main function of the first-order shovel blade of the digging shovel mechanism is to dig the bulbs of Fritilariae ussuriensis maxim out of the soil, and transport them to the transfer mechanism. The design of its structure shape will directly affect its soil breaking performance, soil blocking resistance, and excavation resistance. Therefore, the simulation analysis is mainly conducted on its excavation performance.

Combined with the measured parameters, agricultural planting characteristics, and harvesting process characteristics of Fritilariae ussuriensis maxim, the main parameters of the soil particle model and soil-Fritilariae ussuriensis maxim’s bulb-root system agglomerate model were determined in EDEM by using particle filling, virtual parameter calibration of the soil accumulation angle [22,23,24,25], and other methods, as shown in

Table 4. Parameter table of EDEM soil particle model.

Particle Model	--	Physical Radius	Contact Radius	Particle Ratio
Single-ball pellet	--	3.5	3.5	10
Double-ball pellet	Particle 1	3.5	3.5	48
	Particle 2	3.5	3.5
Three-ball pellets	Particle 1	3.5	3.5	23
	Particle 2	3.5	3.5
	Particle 3	3.5	3.5
Four-ball pellet	Particle 1	3.5	3.5	19
	Particle 2	3.5	3.5
	Particle 3	3.5	3.5
	Particle 4	3.5	3.5

and

Table 5. Parameters of soil-Fritillaria bulb-root aggregate model.

Model Parameters	Numerical Value
Soil density (g/cm3)	1.590
Soil Poisson’s ratio	0.35
Soil shear modulus (Pa)	1.1 × 106
Soil–soil recovery coefficient	0.8
Soil–soil static friction coefficient	0.89
Soil–soil kinetic friction coefficient	0.2
Soil–soil kinetic friction coefficient (g/cm3)	1.070
Poisson’s ratio of roots	0.5
Root shear modulus (Pa)	1 × 106
Root–root recovery coefficient	0.8
Root–root static friction coefficient	0.8
Root–root dynamic friction coefficient	0.8
Root–soil recovery coefficient	0.1
Root–soil static friction coefficient	0.4
Root–soil dynamic friction coefficient	0.01
Root–65 Mn recovery factor	0.4
Root–65 Mn static friction coefficient	0.5
Root–65 Mn dynamic friction coefficient	0.01
65 Mn material density (g/cm3)	7.81
Soil density (g/cm3)	1.590
Soil–65 Mn recovery factor	0.2
Soil–65 Mn static friction coefficient	0.65
Soil–65 Mn dynamic friction coefficient	0.15
Fritillaria ussuriensis maxim’s density (g/cm3)	2.500
Poisson’s ratio of fritillaria ussuriensis maxim	0.25
Shear modulus of fritillaria ussuriensis maxim (Pa)	1 × 107
FUM’s bulb–FUM’s bulb recovery factor	0.3
FUM’s bulb–FUM’s bulb static friction coefficient	0.4
FUM’s bulb–FUM’s bulb kinetic friction Coefficient	0.04
FUM’s bulb–65 Mn recovery coefficient	0.72
FUM’s bulb–65 Mn static friction coefficient	0.56
FUM’s bulb–65 Mn dynamic friction coefficient	0.16
FUM’s bulb–root recovery coefficient	0.2
FUM’s bulb–root static friction coefficient	0.4
FUM’s bulb–root dynamic friction coefficient	0.1
FUM’s bulb–soil recovery coefficient	0.16
FUM’s bulb–soil static friction coefficient	0.5
FUM’s bulb–soil dynamic friction coefficient	0.01
65 Mn material shear modulus (Pa)	8.19 × 1010

Note: FUM’s bulb for fritillaria ussuriensis maxim’s bulb.

, respectively. The soil-Fritilariae ussuriensis maxim’s bulb-root system agglomerate model [26,27,28,29,30] is established according to the parameters, and the first-order shovel was introduced into the aggregate model to complete the establishment of the aggregate model and the aggregate digging shovel system model, as shown in Figure 12 and Figure 13, respectively.

3. Analysis of Results

3.1. Discrete Element Simulation Analysis

3.1.1. Design and Construction of Excavation Test Platform

In order to ensure the accuracy of the test results, this test platform restores the simulation environment to the maximum extent during the parameter design process, and its specific design is shown in Figure 14a. The supporting frame of the test bench was made of 3030 aluminum profile and its supporting corner pieces, in which the middle aluminum profile frame can be changed in height by adjusting the locking position of the supporting corner pieces, which were mainly used to fix and adjust the Z-axis coordinates of the supporting plate. The SBR slider guide mechanism and the screw nut mechanism were located on the supporting plate, and the attachment plate 1 fixed the screw nut and the SBR slider in the same vertical plane. The first-order shovel blade and the shovel body pallet were fixed under the attachment plate 1 by the attachment plate 2. An acrylic plate at the lower part of the test bench was used to form a transparent soil tank to observe the changes of the shovel body and the soil tank during the test. To ensure the accuracy of the test, the soil in the transparent soil tank was obtained from the test site of Fritilariae ussuriensis maxim in Lanxi County, Harbin City, Heilongjiang Province, and the germinating Fritilariae ussuriensis maxim’s bulbs from the same site were planted in it after the soil was fully thawed, as shown in Figure 14b. In order to prevent damage caused by contact with soil, the pressure measuring main control board was wrapped in plastic film and fixed to the attachment plate 2.

3.1.2. Reunion Model Reliability Validation Test

Before the formal testing begins, a preliminary test is required to verify the reliability of the aggregate model. The pre-test consists of two parts: a discrete element simulation test and a solid model verification test. The reliability of the discrete element model was evaluated, according to the fitting analysis of the simulation test values and the measured values on the test bench.

The parameters of the simulation test are set as follows: the motion mode of the shovel blade is set to Linear Translation, the forward positive direction is the X-axis negative direction, the shovel body material is 65 Mn, the digging depth is 100 mm, the shovel face inclination angle is 25°, the operating speed is 0.3 m/s, the time step is 20%, and the total simulation time is 5 s, with an effective operating time of 3.1 s.

In the solid model validation test, each parameter of the first-order excavation shovel is kept consistent with the simulation test parameters. After the validation test of the physical model is completed, the measured data and simulation data were fitted and processed to generate the model reliability analysis curve as shown in Figure 15.

By comparing and analyzing the two curves in Figure 15, it can be seen that the measured value on the test bench is slightly larger than the simulation test value, and the relative error between the simulated test value and the measured value on the test bench is about 14%, which is mainly related to the boundary condition setting of the simulation test and the complexity of soil particle composition. Although the overall simulated test value is smaller than the actual measured value in the test bench, the curve of the simulated test value and the actual measured value in the test bench have the same variation trend within the error tolerance, which indicates that the above discrete element simulation model is reliable and can be used as the technical support for the first-order shovel excavation test.

3.1.3. Orthogonal Test Analysis

In this paper, the interaction between the level of each factor and the system in the excavation shovel is investigated by the orthogonal test method [31,32,33,34]. The three factors that have the greatest influence on the working resistance of the shovel and the overall energy consumption of the Fritilariae ussuriensis maxim harvester are the shovel surface inclination, digging speed, and digging depth in the Fritilariae ussuriensis maxim harvesting and excavation operation. In order to investigate the specific influence of the above three factors on the digging resistance of the shovel blade and soil compression force, and to provide some research objectives and basis for kinematic simulation analysis, a three-factor and three-level orthogonal test is designed. This orthogonal test is performed by using L₉(3⁴) orthogonal table, and the experimental data are processed by polar difference analysis and the best combination of parameters is selected.

Based on the agronomic characteristics and harvesting techniques of Fritilariae ussuriensis maxim, the excavation depth of this experiment is set at 100–140 mm. The rated working speed of the Fritilariae ussuriensis maxim harvester ranges from 0.25 to 0.55 m/s, so the operating speed is 0.3 m/s, 0.4 m/s, and 0.5 m/s. Excavation shovel face inclination and digging resistance are closely related, the shovel face inclination becomes larger, the soil breaking performance becomes better, but the digging resistance will also increase; the shovel face inclination becomes smaller, the digging resistance becomes smaller, but the soil breaking performance will also be weakened. When the shovel inclination angle is too large or too small, it will affect the whole machine efficiency of the Fritilariae ussuriensis maxim harvester. Therefore, the shovel inclination angle is selected within the range of values of 20°, 25°, and 30° for the test. The factor levels of the orthogonal test are displayed in

Table 6. Orthogonal test factor level table.

Level	Operating Speed A (m/s)	Shovel Surface Inclination B (°)	Digging Depth C (mm)
1	0.3	20	100
2	0.4	25	120
3	0.5	30	140

.

This test is designed with reference to the L₉(3⁴) orthogonal test table, and a total of nine groups of simulation tests are conducted. The changes in digging resistance of the corresponding groups is derived separately, and the mean value of the parameters in the table within the stable phase is taken as the response value. The specific experimental design is shown in

Table 7. Orthogonal experimental design.

Serial Number	Operating Speed A (m/s)	Shovel Surface Inclination B (°)	Digging Depth C (mm)	Excavation Resistance F (N)
1	0.3	20	100	217.94
2	0.3	25	120	330.92
3	0.3	30	140	428.4
4	0.4	20	120	279.82
5	0.4	25	140	408.86
6	0.4	30	100	410.51
7	0.5	20	140	305.64
8	0.5	25	100	327.09
9	0.5	30	120	406.16

.

By analyzing the nine sets of data in Table 7, the range analysis details of the orthogonal experiment can be obtained, as shown in

Table 8. Range analysis of orthogonal test.

Factors	Operating Speed A (m/s)	Shovel Surface Inclination B (°)	Digging Depth C (mm)
K1	977.26	803.4	955.54
K2	1099.19	1066.87	1016.9
K3	1038.89	1245.07	1142.9
k1	325.75	267.8	318.51
k2	366.40	355.62	338.97
k3	346.30	415.02	380.97
Range	40.64	147.22	62.45
Impact rate	B > C > A

. From Table 8, it can be seen that the digging resistance F and three factors are positively correlated, where the shovel face inclination B has the most significant effect on the value of digging resistance, followed by the digging depth, and the operating speed. However, when choosing the optimal combination of parameters during the operation, it is not only necessary to consider excavation resistance F, but also to consider the specific force situation of the agglomerate during the operation process, the planting and harvesting process requirements of Fritilariae ussuriensis maxim, and the specific operating environment for setting.

3.1.4. Single-Factor Analysis

(1)

Analysis of the effect of different operating speeds on digging resistance

In order to further analyze the excavation mechanism of shovel body, the single factor analysis method is adopted on the basis of orthogonal test to discuss the influence of excavation speed, excavation angle, and excavation depth on the test results. On the basis of test 5, two groups of test 10 and test 11 are added for comparison, the digging depth is set to 140 mm, the shovel face inclination is set to 25°, and the operating speed of the digging shovel is set to 0.3 m/s, 0.4 m/s, and 0.5 m/s, respectively. At the end of the simulation run, the horizontal resistance and vertical resistance of the excavation shovel in the stable operation stage are extracted, and the average value is taken to obtain the analysis table of the impact of excavation speed is obtained, as shown in

Table 9. Mining speed impact analysis table.

Serial Number	Digging Speed A (m/s)	Angle of Entry B (°)	Digging Depth C (mm)	Horizontal Resistance F1 (N)	Vertical Resistance F2 (N)
10	0.3	25	140	329.24	69.23
5	0.4	25	140	356.60	81.7
11	0.5	25	140	379.91	67.47

.

As seen from Table 9, with the increase in operating speed A, the horizontal resistance $F_1$ shows an increasing trend. The vertical resistance $F_2$ shows a trend of increasing first and then decreasing, but compared with the horizontal resistance $F_1$, the value of vertical resistance fluctuates $F_2$ is smaller. Therefore, as the operating speed A, the overall digging resistance of the shovel body tends to increase. In order to further analyze the effect of different operating speeds on the excavation resistance caused by the excavation shovel, the velocity vector diagram of agglomerate particles at different operating speeds is obtained using the cross-sectional analysis tool that comes with EDEM 2020, as shown in Figure 16. The larger the agglomerate particle velocity in the figure, the more the color of the agglomerate vector leans towards red, while the color of the agglomerate vector leans towards dark blue.

As seen from Figure 16, under the premise of maintaining the same inclination angle and excavation depth of the shovel surface, the vector color of the agglomerate particle in the front and middle of the shovel body surface gradually turns red with the increase in the operating speed. It indicates that the excavation resistance of the excavation shovel is also increasing with the increase in the operating speed. Within a certain range, increasing the operating speed of the excavation shovel can have the effect of increasing the harvesting equipment’s operating speed. If the operating speed of the excavation shovel is too fast, it may cause excessive disturbance to the aggregates, thereby increasing the rate of Fritilariae ussuriensis maxim. Therefore, when setting the operating speed, it is necessary to select an appropriate parameter between the harvesting speed and excavation resistance under the premise of meeting the demand of Fritilariae ussuriensis maxim harvesting, so as to improve the operating productivity.

(2)

Analysis of the effect of different shovel face inclination on digging resistance

In order to investigate the influence of the shovel face inclination angle on the digging resistance caused by the shovel body, this simulation test analysis added test 12 and test 13 for comparison on the basis of test 9 after fully referring to the agronomic requirements of Fritilariae ussuriensis maxim cultivation and harvesting operation process requirements. The excavation depth is set to 120 mm, the operation speed is set to 0.5 m/s, and the shovel face inclination of the excavation shovel is set to 20°, 25°, and 30°, respectively. At the end of the simulation run, the horizontal resistance and vertical resistance of the excavating shovel in the smooth operation stage are extracted and the average value is taken, and the analysis table of the influence of the shovel face inclination angle is obtained, as shown in

Table 10. Influence analysis table of shovel angle.

Serial Number	Digging Speed A (m/s)	Angle of Entry B (°)	Digging Depth C (mm)	Horizontal Resistance F1 (N)	Vertical Resistance F2 (N)
12	0.5	20	120	267.37	61.28
13	0.5	25	120	330.17	84.96
9	0.5	30	120	394.41	90.32

.

In Table 10, it can be seen that as the inclination angle B of shovel face increases, the horizontal resistance and vertical resistance show an increasing trend. Compared with the operating speed A, the impact amplitude of the shovel surface inclination angle B on the digging resistance of shovel body is more obvious. The values of horizontal resistance show significant changes within the range of the angle of penetration, while the values of vertical resistance show more significant changes within the range of 20~25°, but the change in value is not obvious in the range of 25~30°. In order to further analyze the effect of different shovel surface inclination angles on the digging resistance of the shovel body, the expression of the agglomerate particles is set to CONE on the EDEM post-processing page, and the conical spherules of the agglomerate particles with different shovel surface inclination angles are generated, as shown in Figure 17. The direction pointed by the tip of the conical spheroid is the direction of the agglomerate particle movement at that moment. In addition, the larger the volume of the conical spherules, the larger the volume of the agglomerate particles it replaces.

As seen from Figure 17, when the operating speed and excavation depth are kept consistent, the disturbance of the agglomerate particles located in the front middle of the shovel body is intensified with the increase in the shovel surface inclination. It can be seen that the excavation resistance of the shovel is mainly concentrated in the front middle of the shovel body. Therefore, when designing the shovel, it is possible to strengthen the design of the front middle of the shovel body based on the stress characteristics. In addition, within a certain parameter range, the influence of the shovel face inclination on the shovel body’s excavation resistance is even higher than the shovel body’s operating speed, and the parameter setting of the shovel face inclination is less restricted compared with the operating speed. Therefore, before the excavation and harvesting operation of the Fritilariae ussuriensis maxim, the shovel surface inclination of the shovel should be adjusted in advance according to the weather and soil environment of the operating site, so as to improve the operating quality of the shovel and further improve the operation efficiency.

(3)

Analysis of the effect of different digging depths on digging resistance

In order to investigate the effect of digging depth on the digging resistance caused by the shovel body, this simulation test analysis added a set of test 14 for comparison on the basis of test 2 and test 10 after fully referring to the agronomic requirements of Fritilariae ussuriensis maxim cultivation and harvesting operation process requirements. The operating speed is set to 0.3 m/s, the shovel face inclination is set to 25°, and the digging depth of the shovel is set to 100 mm, 120 mm, and 140 mm. At the end of the simulation run, the horizontal resistance and vertical resistance of the shovel in the smooth operation stage are extracted and the average value is taken, and the analysis table of the influence of digging depth is obtained, as shown in

Table 11. Impact analysis table of excavation depth.

Serial Number	Digging Speed A (m/s)	Angle of Entry B (°)	Digging Depth C (mm)	Horizontal Resistance F1 (N)	Vertical Resistance F2 (N)
14	0.3	25	100	278.54	87.37
2	0.3	25	120	305.32	82.72
10	0.3	25	140	329.24	69.23

.

As seen from Table 11, with the increase in excavation depth C, horizontal resistance F₁ tends to increase while vertical resistance F₂ tends to decrease. Compared to operating speed A and shovel face inclination B, the digging depth C has less influence on the digging resistance of the shovel body. In order to further analyze the effect of different excavation depths on the excavation resistance caused by the shovel body, the expression of the agglomerate particles is set to stream in the EDEM 2020 post-processing interface, and the simulation time is recalled to the point before the shovel enters the agglomerate model. In the model display interface, the time step is set from Iterations to Times, and the model type is changed from Playback Speed to Step Playback. After the setting is completed, click Run to generate the trajectory change graph of agglomerate particles, as shown in Figure 18.

As seen from Figure 18, when the operating speed and shovel surface inclination are kept consistent, the trajectory of agglomerate particles in the front and middle of the shovel body surface gradually changes from blue-green to green as the digging depth increases. At 140 mm, the trajectory of agglomerate particles near the shovel blade starts to appear red. However, from the overall changes, the impact of excavation depth on the excavation resistance of the shovel body is not very significant. Hence, prior to adjusting the excavation depth parameters, it is crucial to determine if the surface disturbance on the shovel body will inflict harm upon the Fritilariae ussuriensis maxim bulbs. On the premise of ensuring high net harvest rate and low damage rate, specific parameters should be set based on the variation in excavation resistance on the shovel body with excavation depth.

3.2. First-Order Shovel Blade Excavation Test Study

3.2.1. Experimental Design and Results

The common response surface design methods include central composite design and Box–Behnken. Central composite design is mainly applicable to multi-factor and multi-level tests with continuous variables, while Box–Behnken is mainly applicable to three-level tests with relatively few factors. The three factors, which have the greatest influence on the working resistance of the shovel and the overall energy consumption of the Fritilariae ussuriensis maxim harvester, are the entry angle, digging speed, and digging depth in the harvesting and excavation operation. Based on the analysis of the excavation resistance factors, a three-levels Box-–Behnken test design is adopted in this experiment, so as to further explore the specific influence of the above three factors on the excavation resistance of the shovel body.

The relevant parameters are set with reference to Table 5, and five groups of central tests for error estimation are added, then seventeen groups of experimental design scenarios are generated. The experiments are conducted sequentially as planned, and the average value of the measured data during the motion operation stage is taken as the response value for this group of experiments. The Box–Behnken mining experimental design and results parameters are shown in

Table 12. Box–Behnken Mining simulation test design and result parameters.

Serial Number	Running Speed A (m/s)	Shovel Surface Inclination B (°)	Digging Depth C (mm)	Excavation Resistance R2 (N)
1	1	−1	0	341.45
2	0	0	0	378.25
3	1	0	1	408.2
4	0	−1	1	334.61
5	−1	−1	0	286.07
6	0	−1	−1	278.51
7	0	1	−1	439.37
8	0	0	0	370.15
9	−1	0	−1	348.49
10	−1	0	1	374.37
11	0	1	1	492.36
12	1	0	−1	361.4
13	0	0	0	385.25
14	−1	1	0	490.93
15	1	1	0	520.77
16	0	0	0	379.45
17	0	0	0	368.56

.

3.2.2. Analysis of Test Results

The data in Table 12 were regressed by multivariate quadratic fitting using the Design Expert software, and the quadratic multinomial regression equation of excavation resistance on the three factors of running speed, shovel face inclination, and excavation depth was derived, as shown in Equation (4).

$$\begin{array}{l}{R}_2=376.33+16.50\times A+87.85\times B+22.72\times C-6.39\times AB\\ +5.23\times AC-0.78\times BC+10.19\times A^2+23.29\times B^2-13.40\times C^2\end{array}$$

(4)

This article conducts a more in-depth analysis of variance on the regression model, resulting in the analysis of variance for mining resistance in

Table 13. Mining the resistance variance analysis table.

Source of Variance	Degree of Freedom	Quadratic Sum	Mean Square	F-Value	p-Value	Significance
Model	9	71,718.33	7968.7	51.66	<0.0001	Very significant
B	1	2176.68	2176.68	14.11	0.0071	Very significant
C	1	61,739.22	61739.22	400.24	<0.0001	Very significant
D	1	4130.04	4130.04	26.77	0.0013	Very significant
BC	1	163.07	163.07	1.06	0.3381	Not significant
BD	1	109.41	109.41	0.71	0.4275	Not significant
CD	1	2.42	2.42	0.016	0.9039	Not significant
B2	1	437.01	437.01	2.83	0.1362	Not significant
C2	1	2282.96	2282.96	14.8	0.0063	Very significant
D2	1	756.58	756.58	4.9	0.0624	Significant
Residuals	7	1079.78	154.25	-	-	-
Loss of proposed items	3	888.23	296.08	6.18	0.0554	Not significant
Pure Error	4	191.55	47.89	-	-	-
Total	16	72798.11	-	-	-	-

Note: p < 0.01 indicates highly significant; p < 0.05 indicates a significant difference, p < 0.1 indicates significant.

, the evaluation chart for regression fitting model in Figure 19, and the three-dimensional response surface graph in Figure 20.

From Table 13, it can be seen that the regression fit model of excavation resistance R₁ has p < 0.0001 (highly significant) and the influencing factor misfit term has p = 0.0554 (not significant). In addition, the corrected coefficient of determination is Adj.R² = 0.9661 and the model coefficient of determination is R² = 0.9852 for this regression fitting model. The above parameters indicate that the regression fitting model of excavation resistance R₁ fits very significantly, the correlation between predicted and measured values is good, and the model as a whole is very reliable.

The multiple regression equation can be summarized as response value = (constant + predicted value) + error; that is, response value = deterministic parameters + random error. The deterministic parameters mainly refer to the predictive functions of the independent variables, which refer to all the interpretable and predictable data in the regression model. Random error refers to all the uninterpretable and unpredictable values in the model, which is a collection of the data aggregate of randomness and unpredictability. From Figure 19a, it can be seen that the residuals of the regression fitting model of excavation resistance R₁ obey a normal distribution, which is consistent with the principle of randomness. From Figure 19b, it can be seen that none of the residuals of the regression fitting model of excavation resistance R₁ have any regular distribution, which is consistent with the principle of unpredictability. In summary, the regression fitting model of the excavation resistance R₁ can be used for the prediction and analysis of the excavation resistance of the shovel body.

As seen from Figure 20, the most significant effect is of shovel face inclination B on digging resistance R₁. With the growth in shovel face inclination, digging resistance significantly increases. In contrast, the effect of digging depth C on digging resistance is relatively weak. As the operating speed A grows, so does the value of the digging resistance R₁, which grows at a rate that lies between the shovel surface inclination B and the digging depth C. Among the three factors, the magnitude of the ability to influence the digging resistance is shovel surface inclination B > operating speed A > digging depth C. This result remains consistent with the analysis above.

3.2.3. Optimal Parameter Verification

From the previous analysis, it is clear that the soil disturbance on the upper and lower surfaces of the shovel body near the shovel blade is extremely serious. When the digging depth is set to 100 mm, some of the Fritilariae ussuriensis maxim bulbs with a shallow growth depth will be damaged, so the digging depth of the shovel body should be greater than 120 mm. Compared to the inclination angle of the shovel surface, the impact of operating speed on the excavation resistance of the shovel body is less significant. Therefore, the speed of operation can be increased to improve the harvesting efficiency while ensuring the quality of operation. The Optimization module of the Design Expert software is used to analyze and process the data, following the principle of minimizing the excavation resistance of the shovel body under the premise of high operational efficiency and low damage rate. Combining the boundary conditions of each factor, a nonlinear planning parameter model is constructed, as shown in Equation (5).

$$\left\{\begin{array}{l}\left\{\begin{array}{l}\min R_1(A,B,C)\\ \max A\\ C\ge 120\end{array}\right.\\ s.t.1\left\{\begin{array}{l}0.3\le A\le 0.5\\ 20°\le B\le 30°\\ 100\le C\le 120\end{array}\right.\end{array}\right.$$

(5)

where R₁—digging resistance of shovel body, N; A—operating speed, m/s; B—shovel surface inclination, °; C—digging depth, mm.

The optimal solution can be found in the Post Analysis module of the software: the operating speed A is 0.5 m/s, the shovel face inclination angle B is 25°, the digging depth C is 120 mm. Under the optimal parameters, the digging resistance R₁ of the shovel body is 344.84 N. The experiment was conducted in five rounds, and the results were taken as the average, as shown in

Table 14. Optimal parameter verification.

Test Number	Measured Results (N)	Relative Error (%)
1	356.17	3.29
2	359.56	4.29
3	349.81	1.44
4	332.89	3.47
5	336.56	2.4
Average value	347	2.98

.

As seen from Table 14, the measured values of the test bench do not differ much from the predicted values of the optimal parameter, and the average relative error is less than 5%, indicating that the parameter is highly reliable. The research method can be used to optimize the design of future Fritilariae ussuriensis maxim excavation shovels.

4. Discussion

Although the research on harvesting machinery for rhizome crops is relatively mature both domestically and internationally, there is still relatively little research on harvesting machinery in the field of Fritilariae ussuriensis maxim. As the core component of the harvesting machinery for Fritilariae ussuriensis maxim, the excavation device not only directly affects the overall performance of the harvesting machinery, but also is a key step in achieving the mechanization of the entire process of planting Fritilariae ussuriensis maxim. In order to develop a new type of Fritilariae ussuriensis maxim harvester that can meet the needs of the rapid development of Fritilariae ussuriensis maxim planting industry, the purpose of this study was to study the digging device of the harvester by finite element method and discrete element simulation technology, and to explore the factors affecting the performance of the digging device. The results of this study provide some suggestions for the optimal design of the excavating device of Fritilariae ussuriensis maxim in the future.

The finite element method is used to conduct a static analysis of the excavation device in this paper. The maximum stress and maximum deformation of the excavation device can meet the strength design requirements, determine the stability and safety of the structure, and save the time and costs of traditional experiments. In addition, the EDEM simulation software is used to simulate the actual operation process of the excavation device. For gaining a deeper understanding of the motion and interaction between the discrete element model of Fritilariae ussuriensis maxim and the soil particle model during excavation operations, a discrete element model of Fritilariae ussuriensis maxim and a soil particle model are established. At the same time, the EDEM simulation software is used to replace traditional experimental methods, which can reduce uncertainty in the experimental process and save costs and time. The soil particle model is simplified during the simulation process, since the actual shape of soil particles is very complex. Therefore, in future simulations, it is necessary to establish a model that is closer to the shape of soil particles.

The mutual influence relationship between the levels of various factors in the excavation device and the system is discussed through the orthogonal experimental method. Parameter evaluation is completed in a small amount of experiments, and the optimal parameter combination is obtained by combining single factor experiments. The error between the predicted value of the optimal parameter and the actual experimental results is less than 5%. However, in the orthogonal experimental design, this article only considers the influencing factor of excavation resistance F. In order to conduct a more comprehensive study on the performance of the excavation device for Fritilariae ussuriensis maxim, future research should consider as many influencing factors as possible, such as the stress situation of soil aggregates during the operation process, the requirements for planting and harvesting techniques of Fritilariae ussuriensis maxim, and the operating environment. By comprehensively considering these factors, the working process of the excavation device can be more accurately simulated and the equipment parameters and working strategies can be optimized to improve the work efficiency and excavation performance of the device, which can also provide a more comprehensive theoretical basis for the development of harvesting machinery for Fritilariae ussuriensis maxim.

5. Conclusions

(1)

Through finite element analysis, it can be seen that under the maximum resistance state, the maximum deformation values of the first- and second-order shovel blades are less than 0.01 mm, and the maximum stress is less than 4.0 Pa. Under the maximum load, the maximum deformation value of the bulldozer body is 0.17848 mm, and the maximum elastic deformation is 6.8853 × 10^–4 mm, with a maximum stress value of 107.81 Pa. The simulation results show that the strength of the shovel body of the bulldozer and excavator mechanisms meet the requirements.

(2)

Through the orthogonal test and single factor test, it can be seen that for the three factors of operating speed, shovel face inclination, and excavation depth, the shovel face inclination has the most significant impact on the excavation resistance of the shovel body, and this factor has little impact on the other performance of the Fritilariae ussuriensis maxim harvester, and the optimal shovel face inclination is 25°.

(3)

The digging depth has a weaker influence on the digging resistance of the shovel body than the shovel surface inclination angle, but the digging depth setting will directly affect the damage rate of the Fritilariae ussuriensis maxim. In the actual production process, the growth depth and the thickness of the surface layer of the Fritilariae ussuriensis maxim bulbs may change, and the operation depth of 100 mm cannot guarantee that all the Fritilariae ussuriensis maxim bulbs are outside the area of severe soil disturbance. Therefore, the optimal depth of excavation is 120 mm.

(4)

The operating speed has the weakest influencing factor on the digging resistance of the shovel body, and this factor will directly affect the whole machine operating efficiency of the Fritilariae ussuriensis maxim harvester. Therefore, it is necessary to enhance the operating speed as much as possible under the premise of ensuring the lowest damage rate, the highest net collection rate, and the relatively low digging resistance of the Fritilariae ussuriensis maxim, and the optimal operating speed is 0.5 m/s.