Design and Experimental Study of a Bionic Blade for Harvesting the Wild Chrysanthemum Stem

Abstract

Wild chrysanthemum has a high medicinal value. Its mechanized harvest can improve harvesting efficiency, reduce labor costs and improve planting benefits, which is an important way to promote artificial planting. However, one of the difficulties in mechanized harvesting is the large diameter and hardness of the stem, leading to high cutting resistance and power consumption. In order to reduce cutting resistance and power consumption, a bionic cutting blade is designed in this paper by employing the bionics principle and the contour of the cricket’s upper jaw incisor lobe instead of the sharp triangular teeth of the standard harvester blade. Using the finite element method, the cutting-edge angle, cutting angle, and reciprocating speed were taken as test factors. The maximum shear force and power consumption were taken as evaluation indexes. At the same time, the center combination simulation test was carried out to optimize the cutting body and to determine the optimal cutting speed. When the cutting-edge angle was 21°, the cutting angle was 66°, the reciprocating speed was 1.29 m/s, and the maximum shear force and power consumption were minimal. The results showed that the maximum shear force of the bionic cutter was reduced by 18% and the power consumption by 15.8%. The bench test showed that the maximum shear force and power consumption of the bionic cutter were reduced by 10.5% and 10.8%, respectively, when the entire wild chrysanthemum stem was cut. The results can provide a reference for the mechanical harvesting of wild chrysanthemum stems.

1. Introduction

Wild chrysanthemum is widely distributed in China, India, Japan, Korea, and Russia and can treat diseases such as influenza and cerebrospinal meningitis [1,2]. The wild chrysanthemum has a high medicinal value and is the main medicinal component, such as in cold medication. The mechanized harvest of wild chrysanthemums is mainly divided into mechanical harvesting and flower picking by hand. The existing grass mower is generally used in the harvesting process. However, wild chrysanthemum stems are thick and disorderly, making them difficult to cut and affecting the harvesting effect and efficiency. Therefore, developing special harvesting machines suitable for wild chrysanthemums is urgent, as shown in Figure 1. The cutting blade is an important reaper part and an important factor in determining the cutting quality and power consumption. Optimizing the cutting blade significantly improves the cutting quality of wild chrysanthemum stems.

Bionics refers to the science of constructing technical systems by imitating the characteristics of biological systems or making artificial systems according to the characteristics of biological systems, i.e., the science of imitating biological systems [3]. Applying animal physiological and morphological characteristics to agricultural machinery design through bionics provides a new research idea for researchers regarding drag reduction and consumption reduction. Hong et al. [4] used a sixth-order polynomial function to fit the contour of the outer edge of locust mouthparts and design a saw blade shape. Soni et al. [5,6] applied a Scarab’s head’s non-smooth convex hull structure to the plowshare design. The authors concluded that drag and power consumption could be reduced by 8–36%, and the drag reduction effect was improved when the convex hull height-to-diameter ratio was 0.25 and the water content was 37.2%. Based on the structural features of the surface bumps of dung beetle heads, Qaisrani et al. [7,8] modified the surface of the smooth bumps and developed non-smooth bumps. With an increase in the soil water content, the push-back resistance decreased, and the average maximum drag reduction in the bionic push-back reached up to 30%. Meyers et al. [9] designed bionic scissors based on the tooth configuration characteristics of Amazon piranha, improving the processing efficiency of meat tissue. Chang et al. [10] designed a bionic corn stubble-cutting machine with the front claws of cryptotympana. They found that sawtooth structure design is the main factor in reducing cutting resistance. Tian et al. [11] used the bionic cannabis cutting blade of the longicorn. Compared with the ordinary cutter, the average maximum shear force of the bionic cutter was reduced by 7.4%, and the average cutting power consumption was reduced by 8.0%. You et al. [12] designed two bionic cutting tools based on the surface structure of the dung beetle’s head to solve the problem of metal cutting wear, greatly improving the wear resistance. Ling et al. [13] extracted the structural features of large water lily leaf ribs and cactus stems to investigate mechanical weight reduction. They applied them to the bionic design of the beam of the gantry processing center of Lin MC6000. The authors found that the weight was reduced by 3.31%.

The finite element method has been widely utilized in the field of farm machinery. Abo-Elnor et al. [14] used an advanced three-dimensional finite element analysis to model soil–blade interactions in sandy soils. The results showed that blade cutting width, lateral boundary width and soil swelling had significant effects on cutting force. Bentaher et al. [15] conducted a finite element simulation of the interaction between moldboard and soil and investigated the effects of the cutting angle (angle between the horizontal generatrix and the tillage direction) and the lifting angle (angle between the moldboard surface and the horizontal line in an orthogonal section to the cutting edge) on draught force. The optimal values of these angles are consistent with the experimental data in the literature.

In the previous study, the finite element calibration of stem parameters of the wild chrysanthemum was completed [16]. On this basis, the bionic blade of the chrysanthemum stem was designed, and the blade body was optimized, which filled the blank in the research of a chrysanthemum stem-cutting blade. Crickets are one of the common agricultural pests. They chew stems for a long time, and natural selection helps to keep the outline of their incisor lobe sharp. As chewing mouthparts, crickets are very suitable for cutting stems. Therefore, the incisor lobe of a cricket’s upper jaw was taken as the bionic prototype in this paper. Moreover, the contour of cricket’s mouthparts was applied to the cutting blade design of wild chrysanthemum stem to develop a cutting blade with a low cutting resistance, low power consumption, and good cutting quality [17,18].

2. Materials and Methods

2.1. Selecting the Cricket’s Contour Curve

Many scholars have studied the bionics of cricket mouth parts with similar contour features extracted. In this section, the curve was not extracted and fitted directly from scratch, but rather the existing contour curve of the crickets’ upper jaw incisor lobe was directly used for cutter design. The contour curve of the cricket upper jaw incisor lobe fitted by Du [19] is shown in Figure 2. The fifth-degree polynomial of the contour curve of the incisor lobe is shown in Equation (1). The fit degree of this formula R = 0.999 indicated that it was close enough to the original curve, and no higher-order polynomial was required to describe the contour curve of the incisor lobe.

$$y\left(x\right)=0.162+2.641x+0.036x^2-0.006x^3-2.61\times {10}^{-6}{x}^4+2.02\times {10}^{-6}{x}^5$$

(1)

2.2. Blade Design

2.2.1. Moving Blade Design

The moving blade is shown in Figure 3, and the parameter range of the moving blade is shown in

Table 1. Parameters of the moving blade.

Physical Characteristics	Parameters	Values	Units	Source
a	Bottom length	76	mm	Standard cutter
e	Upper sole length	13	mm	[20]
β	Cutting angle	58~68	°	[20]
α	Cutting edge angle	20~25	°	[20]
δ	Thickness	2	mm	comparative maturity

. Considering that cutting wear may cause the blade to become dull, the cutting edge adopts the toothed cutting edge. During reciprocating cutting, the cut stem is brushed along the teeth, and the cutting edge and teeth are rubbed and worn by the stem. Moreover, the teeth are deepened to ensure that the sharpness of the serrated cutting edge can be maintained, and the self-sharpening effect can be obtained. According to the design manual of agricultural machinery [20], the height of the cutting teeth of agricultural machinery is between 1 ± 0.2 mm, and the median value of 1 mm was used within the design. The abovementioned bionic fitting curve was scaled down to a height of 1 mm, and the optimized curve equation was as follows:

$$y\left(x\right)=\frac{0.162+76.589x+30.276x^2-146.334x^3-1.85x^4+41.43x^5}{29}$$

(2)

The spline curve of the crickets’ upper jaw incisor lobe was used as the tooth profile equation, and the tooth profile spline curve was evenly arranged on the blade surface on both blade sides.

2.2.2. Fixed Blade Selection

The fixed blade is the supporting part, usually the light blade. However, a toothed edge can also prevent the stem from slipping out. A trapezoidal tooth blade was selected as the fixed blade here, as shown in Figure 4, preventing the stem from sliding out during cutting.

2.3. Establishing the Finite Element Model

2.3.1. Model Simplification

According to the previous study conducted by the authors [16], the ratio of the inner diameter to the outer diameter of stems of wild chrysanthemums is 0.41. The cutting height is also important for the cutting quality of wild chrysanthemum stems. The ground of the wild chrysanthemum base is uneven, and the cutter may touch the ground if the cutting height is too low. On the other hand, if the cutting height is too high, it will affect the related process of the base in the next year. Therefore, it was considered that the cutting height of 20 cm above the ground is suitable. The cutter and wild chrysanthemum stem model were simplified when establishing the cutting system model by considering the actual stem-cutting process as follows:

(1)

The inner medulla of the stem was ignored, and the stem was regarded as a hollow cylinder with a diameter of 11 mm and an inner diameter of 4.51 mm;

(2)

The soil constraint on the stem of the wild chrysanthemum was regarded as the fixed-end constraint;

(3)

The modeling object was a single stem without considering the interaction between stems;

(4)

The stem geometric model was simplified, and the stem length was set to 30 cm;

(5)

The cutting position was set to 10 cm from the top of the stem.

2.3.2. Establishing the Cutting System

The geometric model was created using SOLIDWORKS 2018 3D software and imported into the Explicit Dynamic (LS-DYNA Export) module of Ansys Workbench19.0 for grid division. The grid size of the wild chrysanthemum stem was set to 1 mm. The blade mesh was refined at the position where the blade contacts the stem, as shown in Figure 5.

The material settings of wild chrysanthemum stem and blades were carried out in LS-PrePost software, and the material parameters were calibrated [16]. Parameters of the stem and the blades are shown in

Table 2. Stem parameter settings of the wild chrysanthemum.

Parameters	Units	Value
Density	kg/m3	1100
Elastic modulus	MPa	1000
Poisson’s ratio	-	0.3
Yield stress	MPa	17.96
Shear modulus	MPa	0.5
Hardening parameter	-	0.05
Strain rate (C)	-	87.27
Strain rate (P)	-	8
Failure strain	-	0.0387

and

Table 3. Blade parameter settings.

Parameters	Units	Value
Density	kg/m3	7800
Elasticity modulus	GPa	2.07 × 105
Poisson’s ratio	-	0.3

, respectively. Since the blade penetrates the stem, the type of contact between the blade and the stem was defined as eroding surface to surface. The blade surface was defined as the contact surface, the stem surface as the target surface, the static friction coefficient was 0.15, and the dynamic friction coefficient was 0.1 [16].

The hourglass is a zero-energy mode with a multi-frequency oscillation that produces a zigzag grid. The hourglass appearance invalidates the analysis results. Therefore, during simulation and analysis, the hourglass should be controlled to an appropriate degree, which requires the hourglass energy to be lower than 10% during simulation. The hourglass control type was selected as rigid, the coefficient as 0.002, the volume viscosity quadratic coefficient as 1.5, and other parameters were set to default values [21].

According to the actual situation, the wild chrysanthemum stem was buried in the soil, and the bottom of the stem was considered the part buried in the soil. All unit nodes at the bottom of the stem of a wild chrysanthemum were selected, and the bottom of the stem was set as a full constraint.

The ratio of the cutting speed to the forward speed for a crop mower depends on the type of crop to be cut, generally between 1.0 and 1.2 for the mower. The theoretical forward speed of the mower was 4.25 km/h (1.18 m/s) in the second gear of the tractor. The cutting line speed of the cutter can be expressed as:

$$v_p=\beta v_m$$

(3)

where v_p is the reciprocating cutting speed of the cutter, m/s; β is the ratio of the reciprocating cutting speed to the forward speed; v_m is the forward speed of the mower, m/s.

Finally, the reciprocating speed of the cutter was determined as 1.18–1.42 m/s.

2.4. Experimental Design

The multi-factor simulation test was carried out to obtain optimal bionic cutter parameters. The cutting-edge angle, cutting angle, and reciprocating speed were used as test factors, and the maximum shear force and cutting power consumption were used as evaluation indexes. In this study, Central Composite design and Design-Expert 11 software were used to complete the orthogonal combination experiment design. The factor codes are shown in

Table 4. Central composite design factor coding.

Factor Level	Cutting Edge Angle X1	Cutting Angle X2	Reciprocating Speed X3
−1.68	20	58	1.18
−1	21	60	1.23
0	22.5	63	1.3
1	24	66	1.37
1.68	25	68	1.42

.

2.5. Bench Tests

Bench tests were carried out to test the feasibility of the simulation data of the bionic blade for the chrysanthemum stem and verify the cutting performance of the bionic blade. The test bench could accurately simulate the field operation state of wild chrysanthemum stem harvesting and has good adaptability. The cutting and conveying speeds of the stem could be adjusted, and the cutting blades could be changed to meet the requirements of wild chrysanthemum harvest technology.

2.5.1. Test Materials and Equipment

The experimental materials (varieties of high-quality wild chrysanthemums with 2% luteolin content) were selected from the planting base of wild chrysanthemums in Qianxian county, Shaanxi Province. Test equipment included a self-made test bench, a torque sensor (FC-DAQ), a tension pressure sensor (DYLY-103, supply voltage: 5~15 V, output sensitivity: 2.0 mv/v, total error: 0.03% F.S), a wrench, and a screwdriver. The test bed design is shown in Figure 6, while the test bench machining prototype is shown in Figure 7.

2.5.2. Operating Principle

The wild chrysanthemum stem was cut from the root, and the entire cluster was clamped with the wild chrysanthemum stem clamping device. The conveying device simulated the forward motion of the mower in the field and used the frequency converter to change the cutting speed of the cutter and the forward speed of the conveying mechanism. Consequently, the cutting operation of the wild chrysanthemum stem was completed. Bench cutting parameters were set via the optimal parameter combination of the reciprocating cutter in the working process obtained by the finite element simulation test. Five groups of tests were conducted in this bench test. After each test, the maximum shear force of the wild chrysanthemum stem was recorded, and the cutting power consumption was calculated according to the torque value.

3. Results and Discussion

3.1. Analysis of the Simulation Process

The state of the wild chrysanthemum stem and cutter before cutting is shown in Figure 8a. The cutting moment of the cutter is shown in Figure 8b. At this moment, there was point–plane contact between the stems of the wild chrysanthemum and the blade. Moreover, the cutting edge of the cutter impelled the surface of the stems, damaging the stems of the wild chrysanthemum. According to Figure 8c, when the cutter cut into the stem of the wild chrysanthemum with half of its diameter, it was squeezed by the inclined plane of the cutter. Some parts of the stem that were not cut cracked, and the upper part also showed equivalent stress changes. Lastly, the fracture stage, when the stem fracture was completely separated, is shown in Figure 8d.

The cutting force during wild chrysanthemum stem cutting is shown in Figure 9. The cutting force reached the maximum value when it was approximately half of the diameter of the wild chrysanthemum stem. It can be concluded that, from the beginning of cutting (when the blade contacted the point surface of the stem), the shear force gradually increased from zero. When the half point of the cutting position was reached, the shear force reached the maximum value and then decreased to zero when the stalk was cut.

The changes in the internal and hourglass energy during wild chrysanthemum stem cutting are shown in Figure 10. When the simulation is effective, the hourglass energy should be less than 10% of the total internal energy. The ratio of the hourglass energy to the total internal energy being less than 10% indicates that the set hourglass energy could effectively control the unit distortion to achieve the expected simulation target. Therefore, it can be evaluated that the meshing and parameter settings were appropriate, and the simulation results were reliable, reflecting the fracture and deformation of a chrysanthemum stem.

3.2. Central Composite Design Experiment

The experimental design scheme and results are shown in

Table 5. Results of the central composite test.

No.	X1	X2	X3	Maximum Shear Force/N	Power Dissipation (J)
1	22.5	63	1.3	205.9	0.97
2	23.9865	65.973	1.37135	249.3	1
3	22.5	63	1.3	201.1	0.92
4	20	63	1.3	150.8	0.92
5	21.0135	65.973	1.22865	170.5	0.85
6	22.5	68	1.3	202.6	0.9
7	21.0135	60.027	1.22865	213.2	1.12
8	25	63	1.3	201.1	0.89
9	23.9865	60.027	1.22865	183.7	0.84
10	21.0135	65.973	1.37135	165.1	0.89
11	21.0135	60.027	1.37135	160.8	1.02
12	23.9865	60.027	1.37135	202.3	0.96
13	22.5	63	1.3	200.9	0.97
14	23.9865	65.973	1.22865	185.8	0.8
15	22.5	63	1.3	200.6	0.89
16	22.5	63	1.18	199.3	0.93
17	22.5	63	1.3	198.3	0.97
18	22.5	58	1.3	191.2	1
19	22.5	63	1.42	204	1.05

Note: X₁ represents the cutting-edge angle, X₂ represents the cutting angle, and X₃ represents the reciprocating speed.

. Multiple regression fittings were conducted on the data provided in Table 5. Thus, the regression equation of maximum shear force and power consumption of wild chrysanthemum stem could be obtained:

Y₁ = 201.34 + 14.36X₁ + 2.19X₂ + 2.36X₃ + 10.94X₁X₂ + 17.49X₁X₃ + 11.49X₂X₃ − 8.89X₁² − 1.48X₂² + 0.1954X₃²

(4)

Y₂ = 0.9445 − 0.0242X₁ − 0.0416X₂ + 0.0338X₃ + 0.05X₁X₂ + 0.0475X₁X₃ + 0.0275X₂X₃ − 0.0167X₁² − 0.0008X₂² + 0.0134X₃²

(5)

The variance analysis results of maximum shear force and power consumption were obtained using the Design-Expert 11 software, as shown in

Table 6. ANOVA of central composite design experiment.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	8528.58/0.0986	9	947.62/0.0110	146.34/9.66	<0.0001 **/0.0012 **
X1	2815.65/0.0080	1	2815.65/0.0080	434.82/7.05	<0.0001 **/0.0263 **
X2	65.34/0.0236	1	65.34/0.0236	10.09/20.84	0.0112 */0.0014 **
X3	75.94/0.0156	1	75.94/0.0156	11.73/13.77	0.0076 **/0.0048 **
X1X2	957.03/0.0200	1	957.03/0.0200	147.79/17.63	<0.0001 **/0.0023 **
X1X3	2446.50/0.0181	1	2446.50/0.0181	377.81/15.91	<0.0001 **/0.0032 **
X2X3	1055.70/0.0061	1	1055.70/0.0061	163.03/5.33	<0.0001 **/0.0463 *
X12	1079.02/0.0038	1	1079.02/0.0038	166.63/3.35	<0.0001 **/0.1004
X22	30.06/8.251 × 10−6	1	30.06/8.25 × 10−6	4.64/0.0073	0.0596/0.9339
X32	0.5211/0.0024	1	0.5211/0.0024	0.0805/2.15	0.7831/0.1767
Residual	58.28/0.0102	9	6.48/0.0011
Lack of fit	27.45/0.0047	5	5.49/0.0009	0.7122/0.6796	0.6465/0.6638
Pure error	30.83/0.0055	4	7.71/0.0014
Core total	8586.86/0.1089	18

Note: ** represents extremely significant effect (p < 0.01), * represents significant effect (p < 0.05).

. The fitting degree of the regression equation was analyzed according to the results.

For the maximum shear force, the p value of the model was less than 0.0001, and the lack of fit was higher than 0.05, indicating that the significance of the experimental model was extremely high and the design of the test scheme was reasonable. Each test factor, X₁, X₃, X₁X₂, X₁X₃, X₂X₃, and X₁², extremely significantly affected the maximum shear force, while X₂ significantly affected the shear force. Test factors X₂² and X₃² were insignificant, indicating that the influence of test factors on the overall response value had a higher power relationship. The coefficient of determination R² was 0.99, indicating that the regression model agreed with the results and could be used to predict the maximum stem shear force.

The power consumption (P) of the model was 0.0012. Moreover, the lack of fit was higher than 0.05, indicating the experimental model’s extremely high significance and a reasonable test scheme design. Each test factor, X₁, X₂, X₃, X₁X₂, and X₁X₃, extremely significantly affected the power consumption, while X₂X₃ significantly affected power consumption. Factors X₁², X₂², and X₃² had no significant effect on power consumption, indicating that the influence of test factors on the overall response value had a higher power relationship. The coefficient of determination R² was 0.91, indicating that the regression model agreed with the results and could be used to predict the power consumption of stem cutting.

3.3. Response Surface Interaction Analysis

The response surface analysis method can draw a response surface, as shown in Figure 11 and Figure 12. These graphs take two independent variables as coordinates to directly reflect the influence degree of each independent variable on the response value, reflect the interaction between each variable, and represent the significant degree of mutual influence between the two variables. If the contour line approaches a circle, the interaction is weak; if the contour line approaches an oval, the interaction is stronger (in the coordinate axis, X₁ represents the cutting-edge angle, X₂ represents the cutting angle, and X₃ represents the reciprocating speed).

3.3.1. Maximum Shear Force

The interaction between the cutting-edge angle (X₁) and the cutting angle (X₂) on the maximum shear force for the reciprocating speed (X₃) of 1.3 m/s is shown in Figure 11a. The contour map shows an oval shape, indicating that the two greatly influenced the maximum shear force. When the cutting angle was constant, the maximum shear force increased with the edge angle. This is because the greater the cutting-edge angle into the material, the greater the cutting force required. When the edge angle was relatively small, the maximum shear force changed with an obvious increase in the edge angle, after which the growth rate slowed down. According to the variance analysis table, the F value of the effect of the edge angle on the maximum shear force was 434.82, and the F value of the cutting angle on the maximum shear force was 10.09. Therefore, the effect of the cutting-edge angle on the maximum cutting force was more significant than that of the cutting angle.

The interaction between the cutting-edge angle (X₁) and the reciprocating speed (X₃) on the maximum shear force for the cutting angle (X₂) of 63° is shown in Figure 11b. The contour map shows an oval shape, indicating that the two had a relatively considerable influence on the maximum shear force. When the reciprocating speed was constant, the maximum shear force increased with the increase in the edge angle (This is because the greater the cutting-edge angle into the material, the greater the cutting force required), and the growth rate was relatively stable. According to the variance analysis table, the F value of the effect of edge angle on the maximum shear force was 434.82, and the F value of the effect of reciprocating speed on the maximum shear force was 11.73. Therefore, the effect of the edge angle on the maximum cutting force was more significant than that of the reciprocating speed.

The interaction between the cutting angle (X₂) and the reciprocating speed (X₃) on the maximum shear force for the edge angle (X₁) is 22.5° is shown in Figure 11c. The contour map shows an oval shape, indicating that the two had a relatively considerable influence on the maximum shear force. When the reciprocating speed was constant, the maximum shear force increased with the cutting angle, similar to the abovementioned phenomenon (This is because the greater the cutting angle, the greater the cutting-edge angle into the material, so the greater the cutting force required). According to the variance analysis table, the F value of the cutting angle to the maximum shear force was 10.09, and the F value of the reciprocating speed to the maximum shear force was 11.73. Therefore, the effect of reciprocating speed on the maximum cutting force was more significant than that of the cutting angle.

3.3.2. Power Consumption

The interaction between the edge angle (X₁) and the cutting angle (X₂) on the power consumption for the reciprocating speed (X₃) of 1.3 m/s is shown in Figure 12a. The contour map shows an oval shape, indicating that the two had a relatively considerable influence on power consumption. When the cutting angle was constant, the power consumption decreased with an increase in the edge angle. According to the variance analysis table, the F value of the effect of the edge angle on power consumption was 7.05, and the F value of the cutting angle on power consumption was 20.84. Therefore, the influence of cutting angle on power consumption was more significant than that of the cutting-edge angle.

The interaction of edge angle (X₁) and reciprocating speed (X₃) on power consumption for the cutting angle (X₂) of 63° is shown in Figure 12b. The contour map shows an oval shape, indicating that the two significantly affected power consumption. When the reciprocating speed was constant, the power consumption decreased with an increase in the edge angle. The higher the edge angle, the more intense the power consumption reduction speed. According to the variance analysis table, the F value of the effect of edge angle on power consumption was 7.05, and the F value of reciprocating speed on power consumption was 13.77. Therefore, the influence of reciprocating speed on power consumption was more significant than that of the edge angle.

The interaction between the cutting angle (X₂) and the reciprocating speed (X₃) on the power consumption for the edge angle (X₁) of 22.5° is shown in Figure 12c. The contour map shows an oval shape, indicating that the two had a relatively considerable influence on power consumption. When the reciprocating speed was constant, the power consumption decreased with an increase in the cutting angle. According to the variance analysis table, the F value of the cutting angle to power consumption was 20.84, and that of reciprocating speed to power consumption was 13.77. Therefore, the influence of the cutting angle on power consumption was more significant than that of the reciprocating speed.

3.4. Parameter Optimization

The ideal result of numerical optimization is to minimize the maximum shear force and power consumption within the range of constraints. With the minimization of both maximum shear force and power consumption as optimization objectives, the response surface method was used to optimize and solve the quadratic multinomial regression model. The optimal parameter combination in the working process of a reciprocating cutter was obtained as follows: the cutting-edge angle was 21°, the cutting angle was 66°, the reciprocating cutting speed was 1.29 m/s, the maximum shear force was 168.1 N, and the minimum power consumption was 0.85 J. The final optimized bionic blade is shown in Figure 13.

3.5. Contrast Test

The simulation experiment of cutting wild chrysanthemum stem with an ordinary blade was conducted under the same conditions. A comparison was made between cutting wild chrysanthemum stems with the optimized bionic blade. The common conditions of the two are as follows: the upper bottom of the blade was 13 mm, the lower bottom was 76 mm, the blade thickness was 2 mm, the cutting-edge angle was 21°, the cutting angle was 66°, the forward cutting speed was 1.18 m/s, and the reciprocating speed of the cutter was 1.29 m/s. The comparison results are shown in

Table 7. Performance comparison results between an ordinary and a bionic blade.

Blade Type	Condition	Maximum Shear Force/N	Power Dissipation (J)
Ordinary blade	ordinary tooth	205	1.01
Bionic blade	bionic tooth	168.1	0.85
Rate of performance improvement		18%	15.8%

.

In summary, compared with the ordinary blade, the cutting performance of the bionic blade improved, the maximum shear force was reduced by 18%, and the power consumption was reduced by 15.8%. The results show that the designed bionic reduced maximum shear force and consumption.

3.6. Analysis of Bench Test Results

The layout of the stems in the bench test is shown in Figure 14, and a comparison of the cutting effects of two types of cutting tools is shown in Figure 15. On the left is the bionic blade cutting stubble, and on the right is the ordinary blade.

The bench test results are shown in

Table 8. Bench test results.

No.	Maximum Shear Force/N		Power Dissipation (J)
	Bionic Blade	Ordinary Blade	Bionic Blade	Ordinary Blade
1	380	413	20.2	23.3
2	383	422	21.1	24.1
3	351	388	16.9	18.3
4	399	467	23.3	25.8
5	321	359	18.2	20.1
average	366.8	409.8	19.9	22.3

.

According to the bench test results, the average maximum cutting force and cutting power consumption of a bionic blade and an ordinary blade were 366.8 N and 409.8 N and 19.9 J, and 22.3 J, respectively. Compared with the bionic and ordinary blades, the average maximum cutting force and power consumption were reduced by 10.5% and 10.8%, respectively.

Different animal and plant profiles were selected to design different crop cutters, whose performance improvement effects were not completely consistent. In this paper, the incisor lobe of a cricket’s upper jaw was used to replace the common harvester blade’s triangular sharp teeth, and the cutter body was optimized. The cutting performance was improved, and the maximum shear force and power consumption when cutting a single wild chrysanthemum stem were reduced by 18% and 15.8%, respectively. The obtained results are similar to the study of Tian et al. [11] and Hong et al. [4]. However, Jin et al. [22]. designed a disk-type bionic cutting knife based on the mandibular incisor profile of the foot elephant larvae, whose energy consumption was reduced by 12.8% compared with the conventional blade while the cutting efficiency was increased by 12.5%. Contrary to the abovementioned cutters for reciprocating cutting, the bionic blade designed by Jin et al. performs disc cutting. In addition, the abovementioned investigations only used a universal testing machine or simple bench to verify the cutting performance of a bionic cutter. On the other hand, the bench test designed in this paper simulated the field operation status of wild chrysanthemum stem harvesting to the maximum extent. Therefore, a stronger reference for the mechanical harvesting of wild chrysanthemum stems was provided. In addition, the durability and reliability of agricultural machinery are also very important, and there are relatively few studies on them in the existing literature. Later, the reliability research of agricultural machinery under harsh environment should be increased [23,24].

4. Conclusions

(1)

Combined with bionics, the bionic cutting blade was designed by replacing the sharp triangular teeth of the ordinary harvester blade with the contour of the cricket’s upper jaw incisor lobe. The cutting-edge angle, cutting angle, and reciprocating speed were used as test factors by employing the finite element method. The maximum shear force and power consumption were used as evaluation indexes. The bionic body was optimized, and optimal cutting speed was determined by employing the center combination simulation test. The maximum shear force and power consumption were minimized when the cutting-edge angle was 21°, the cutting angle was 66°, and the reciprocating speed was 1.29 m/s;

(2)

A comparison test was conducted between the ordinary blade and the bionic blade to cut the stems of the wild chrysanthemum and validate the cutting performance of the bionic blade. The results showed that the bionic blade had a stronger cutting performance, the maximum shear force was reduced by 18%, and the cutting power consumption was reduced by 15.8%;

(3)

A cutting bench was set up to verify the performance of the bionic cutting blade for wild chrysanthemum stems. Contrary to the simulation test, an entire plant of wild chrysanthemum was cut in the bench test. The results showed that the maximum shear force and power consumption of the bionic cutting blade for the stems of wild chrysanthemums were reduced by 10.5% and 10.8%, respectively. The results can provide a reference for the mechanical harvesting of chrysanthemum stems;

(4)

This paper only optimized the cutter through simulation and bench experiment, and field experiments should be carried out in the later research on this basis, so that the results obtained will be more reliable.