*2.4. Experiment and Methods*

In order to verify the accuracy of the numerical simulation results and detect the cutting effect under the best parameters of the reciprocating cutting system, the cutting performance experiment was carried out.

The Chinese little greens variety used were Nanjing Yongxin, with a growth cycle of 35 days. The average height of the selected Chinese little greens selected in the experiments was 180 ± 30 mm, the length of the cutting position was 10 ± 3 mm, and the diameter of the stalk was 7 ± 2 mm. Before the cutting test, five Chinese little greens roots were randomly weighed and recorded. They were then dried continuously in an oven for 24 h (ASABE standard, 2012). The equation for calculating moisture content follows:

$$M = \frac{M\_L}{M\_W} \times 100\% \tag{3}$$

where *M* is the moisture content, %; *ML* is the weight lost, g; and *MW* is the sample weight, g.

The leaves of the root were removed, and the whole plant was transplanted into a seedling tray and fixed. The test sample is shown in Figure 5a. A reciprocating cutting stress measurement system for the Chinese little greens was built [34]. The test system was mainly composed of a stalk-feeding device, a cutting device, and a cutting stress measurement system. The specific working parameters of the test bench are shown in Table 4.

**Figure 5.** Schematic diagram of measurement system of cutting stress: (**a**) test sample; (**b**) cutting stress measurement system.


**Table 4.** Parameters of the reciprocating cutting test system.

The stalk-feeding device includes a frequency converter, an AC motor, a conveyor belt, and a stalk-fixing seedling tray. The stalk-fixing tray of greens was placed on the center of the conveyor belt, which was powered by an AC motor to drive the seedling tray forward. The frequency converter was used to adjust the feeding speed of the stems, and the specific structure is shown in Figure 6a. The cutting device was fixed on the frame by fastening bolts, including a controller, a DC motor, a cutter, a transmission device, and a frame. In operation, the double eccentric wheel mechanism was driven by the stepping motor. The phase difference between the two eccentric wheels was transmitted to the eccentric shaft through the reduction gear, thereby driving the upper and bottom blades to make a reciprocating linear motion. The average cutting speed can be adjusted by the DC motor, and its structure is shown in Figure 6b. The test system mainly includes a resistance strain gauge and a DH5902N solid data acquisition system. A set of adjacent blades for each of the upper and bottom blades was selected, and the surface of the blades was polished and cleaned. A set of strain gauges at the center of the blades was installed in rectangular distribution, so that the principal stresses of the blades in the *X* and *Y* directions were collected. The *X* direction was in line with the cutting direction, and the *Y* direction was in line with the stalk-feeding direction. The strain gauge was connected to the data acquisition system through wiring. It sends the mechanical signals of the cutter to the dynamic signal acquisition and analysis system for real-time data recording of stress data. The specific structure is shown in Figure 6c.

**Figure 6.** Structural diagram of the cutting force measurement system.

Before the test, stalks with a diameter of 5 mm were selected, and the leaf crown on the top of the parsley was constructed and fixed on the conveying device. By adjusting the distance between the cutting blade and the conveying device by adjusting the fastening bolt between the blade holder and the frame, the appropriate cutting position was determined. In the test, start the test system and motor, and adjust the frequency converter to adjust the control frequency, and keep the stalk-feeding speed at a constant value of 200 mm/s. The structural parameters of the cutting blade were kept unchanged, but the frequency operation of the cutting motor was adjusted by controller to obtain different average cutting speeds. After the various systems of the test bench enter stable operation, the motor of the conveying device was started [34]. The installation and wiring diagram of the resistance strain gauge sensor is shown in Figure 7. The sensor collected four sets of data for the cutting normal stress of the upper and bottom blades in real time, and then the data were transmitted to the PC terminal after being processed by the dynamic data acquisition system. Considering that the maximum cutting stress was an influencing factor that affects cutting power consumption and effect, the maximum cutting stress was taken as the test result. Each test was repeated three times, and the average value of the ultimate cutting stress was taken as the reference value and compared with the results of numerical simulation [24].

**Figure 7.** Schematic diagram of arrangement and wiring of strain gauge: (**a**) installation locations of the strain gauges on the upper blade; (**b**) installation locations of strain gauges on the bottom blade; (**c**) wire connection between the data acquisition instrument and computer.

### **3. Results**

#### *3.1. Post-Processing Results and Analysis of Numerical Simulation*

After calculating the numerical simulation, the calculation results underwent postprocessing [23]. The equivalent stress distribution cloud diagram was obtained in the cutting process when the sliding–cutting angle was 20◦, the oblique angle was 35◦, and the average cutting speed was 300 mm/s. Figure 8 reflects the dynamic change in equivalent stress during the cutting process. It can be seen from Figure 8a that when t is 0 ms, the cutting blade and the stalk were out of touch, and the equivalent stress between the cutting blade and the greens was 0 Mpa. Then the cutting blade moved toward the stalk at 300 mm/s, and contacted the stalk at 25.9 ms. Figure 8b (t = 26.8 ms) shows the cloud map of the equivalent stress distribution at the initial cutting stage. The cutting blade compressed the stalk locally to produce significant buckling and plastic deformation, and the fiber tensile stress continued to increase, and the shear strain exceeded the tensile strength of the fibers. Hence, the unit was damaged and failed, the fibers of the stalk broke at the blade edge, and then the cutter gradually cut into the stalk. At this time, both the upper and bottom cutting blades had stress concentration, and the maximum equivalent stresses appeared at the contact point on the stalk, which were 0.31 and 0.68 Mpa, respectively. The sheared part of the stalk showed the maximum equivalent stress, which was 3.93 Mpa, which was consistent with the actual working conditions. As shown in Figure 8c (t = 30.3 ms), at the stage of stalk rupture, when the blade cut into about one-half the diameter of the stalk, and the stem tissues at the tip of the blade were further bent and deformed, which eventually caused the entire fiber layer to slip and break, resulting in shear damage to the entire stem. At this stage, stress concentration occurred throughout

the cutting edge. The reason might be that the stalk exerted greater squeezing and friction on the cutter at a deeper position. At this time, the cutting cross section had a tendency to crack, and the surface of the stubble of the cracked part was uneven with poor quality. Therefore, the relevant cutting parameters should be optimized to reduce this phenomenon. Figure 8d reflects the process of separating stalks from the stubbles after the cutting was completed. During this process, the stalks were cut and separated. The stress concentration of the cutting blade and the stalks gradually disappeared, then reaching the minimum. The effect force was significantly reduced, but the cutter still had residual stress.

**Figure 8.** The effective stress cloud diagram of cutting unit.

The equivalent stress curves are shown in Figure 9. It can be seen that the cutting blade and the stalk contacted each other at about 26 ms, and the cutting operation was completed at about t = 36 ms. The entire cutting process lasted about 10 ms, during which the cutting equivalent stress of the process continued to change dynamically, which was consistent with the actual working conditions of the shearing process. There was no interaction between the cutter and the stalk after separation; however, since the cutter was still affected by the residual stress, the stress of the cutter at this stage was not zero. When t = 28.1 ms, the maximum equivalent stress of the upper cutting blade was 1.05 Mpa. The maximum equivalent stress of the lower cutting blade occurred at t = 36.6 ms, which was 0.90 Mpa. The maximum equivalent stress of the cutting blade is much lower than 355 Mpa, which is the tool material yield limit. It means that the cutter would not undergo significant plastic deformation.

**Figure 9.** Equivalent stress curves of cutting blade: (**a**) upper cutting blade; (**b**) bottom cutting blade.

Figure 10 shows cloud diagrams for the maximum equivalent stress distribution of the cutting blade during the cutting process. Taking the description of Figure 10a as an example, it can be seen that area A, where the upper cutting blade contacts the stalk, received the greatest reaction stress, and here was the peak value of local stress. In addition, the stress mainly occurred in the edge area of the cutting blade, which showed that the method and position of the strain gauges used in this study were reasonable.

**Figure 10.** Maximum equivalent stress distribution cloud diagram: (**a**) upper cutting blade; (**b**) bottom cutting blade.

#### *3.2. Orthogonal Test Results and Significance Analysis*

According to the test method described in Section 2.2, the numerical simulation of the cutting orthogonal test was carried out using Design-Expert 10.0.7 software. A total of 20 sets of simulation tests were performed; the test results are shown in Table 5.


**Table 5.** Design and results of the orthogonal test in numerical simulation.

The test results were analyzed by multiple regression fitting using Design-Expert 10.0.7 software, and the regression equation between maximum cutting equivalent stresses and each influencing factor were established. The insignificant terms were then removed. Regression equations are shown in Equations (4) and (5):

$$Y\_1 = 1.11 - 0.08X\_1 + 0.14X\_2 - 0.052X\_3 - 0.067X\_1X\_2 + 0.11X\_{22} \tag{4}$$

$$Y\_2 = 0.88 - 0.093X\_1 + 0.19X\_2 - 0.061X\_3 - 0.13X\_1X\_2 + 0.10X\_{12} + 0.19X\_{22} \tag{5}$$

The variance analysis of the regression equation is shown in Tables 6 and 7. According to the variance analysis of the maximum cutting equivalent stresses *Y*<sup>1</sup> and *Y*<sup>2</sup> of the cutter, it can be seen that the significance level *p* values of the two models were both less than 0.01, indicating that the models were extremely significant. The values for the lack-of-fit items of the regression model were all greater than 0.05, indicating that the regression model had a high fitting accuracy. The coefficients of determination *R*<sup>2</sup> for the two models were 90.4% and 93.9%, respectively, indicating 90.4% and 93.9% of the total variation in the limit cutting force can be explained by this model, so that both models had high reliability [35–37]. Therefore, the structural and working parameters of the reciprocating cutting system can be optimized and analyzed by models.

It can be seen from the results of the variance analysis that various factors had different effects on the indicators. The *p* value reflected the degree of influence for each parameter of the regression equation. The smaller *p* value had more significant effect. The oblique angle had the greatest influence, followed by the sliding–cutting angle and average cutting speed, and these three factors were significant items (*p* < 0.05).


**Table 6.** Variance analysis results for *Y*1.

**Table 7.** Variance analysis results for *Y*2.


According to Tables 6 and 7, it can be seen that the interaction terms of factor *X*<sup>1</sup> and *X*<sup>2</sup> had a significant impact on the two indicators (*p* < 0.05), and the three-dimensional response surface of the two-factor interaction effect are shown in Figures 11 and 12 [38,39]. The change rate of the test index for the upper cutter and bottom cutter along the factor *X*<sup>2</sup> direction was faster than that along the factor *X*<sup>1</sup> direction. At the same time, as the sliding–cutting angle increased, the cutting resistance on the cutter gradually decreased. The reason is that the cutting has a sliding progression during the cutting process. The larger sliding–cutting angle of the cutter can make more tangential slip. When the oblique angle of the cutter was 35~38◦, the stress on the cutter gradually decreased, and then when the oblique angle continued to increase, the stress on the cutting knife gradually increased. It can be seen from the contour map that the rate of change in the test index along the factor *X*<sup>2</sup> direction is faster than for the factor *X*1, which means that the oblique angle has a more significant influence on the cutting stress than the sliding angle.

**Figure 11.** Effects of the sliding–cutting angle and the oblique angle on maximum equivalent stress of the upper cutting blade.

**Figure 12.** Effects of the sliding–cutting angle and the oblique angle on maximum equivalent stress of the bottom cutting blade.
