# Simulation and Experimental Study on the Shrub-Cutting Performance of Quasi-Planetary Cutter
## 4 Results and Discussion
### Orthogonal Experiment Results and Analysis
#### 4.2.2 Analysis  
The experimental results were subjected to multivariate fitting using Design-Expert 13 software, followed by variance analysis. The variance analysis of the experimental results is presented in Table 7. From Table 7, it is evident that the \(p\)-values of the models for peak cutting force and peak cutting power are both less than 0.01, indicating that the established regression models are highly significant (\(p<\) 0.01 is extremely significant, 0.01 \(<\)\(p<\) 0.05 is significant, and \(p\) > 0.05 is not significant [28]). The \(p\)-values for the lack-of-fit terms of the two models are 0.19 and 0.2211, respectively--both greater than 0.05--suggesting that the regression equations exhibit minimal errors and strong fitting performance. The coefficients of determination (R\({}^{2}\)) for peak cutting force and peak cutting power are 99.36% and 98.54%, respectively, indicating high fitting accuracy and the feasibility of further parameter optimisation within the experimental range [29]. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Groups** & \(\mathbf{n}\) **(r/min)** & \(\mathbf{v}\) **(mm/s)** & \(\mathbf{w}\) **(mm)** & \(\mathbf{F_{\text{max}}}\) **(N)** & \(\mathbf{P_{\text{max}}}\) **(W)** \\ \hline  
\hline \end{tabular}
\end{table} 
Table 6: Orthogonal Test Results. In the peak cutting force model, the first-order terms of tool rotational speed (\(n\)), feed speed (\(v\)), and shrub moisture content (\(w\)) as well as the quadratic term of tool rotational speed (\(n^{2}\)) have an extremely significant impact on the model. The quadratic term of feed speed (\(v^{2}\)) has a significant impact, whereas the interaction terms between tool rotational speed and feed speed (\(n\cdot v\)), tool rotational speed and shrub moisture content (\(n\cdot w\)), feed speed and shrub moisture content (\(v\cdot w\)), and the quadratic term of shrub moisture content (\(w^{2}\)) have no significant impact. In the peak cutting power model, the first-order terms of tool rotational speed (\(n\)), feed speed (\(v\)), and shrub moisture content (\(w\)) as well as the interaction term between tool rotational speed and feed speed (\(n\cdot v\)) and the quadratic term of tool rotational speed (\(n^{2}\)) have an extremely significant impact on the model. The quadratic term of feed speed (\(v^{2}\)) has a significant impact, whereas the interaction terms between tool rotational speed and shrub moisture content (\(n\cdot w\)), feed speed and shrub moisture content (\(v\cdot w\)), and the quadratic term of shrub moisture content (\(w^{2}\)) have no significant impact. After removing the non-significant terms, the simplified models are given in Equations (6) and (7):  
\[F=9.74-1.11n+0.6925v+0.3105w+0.3641n^{2}+0.1481v^{2} \tag{6}\]  
\[P=312.29+10.85n+22.5v+9.99w+6.83n\cdot v+6.59n^{2}+4.79v^{2} \tag{7}\]  
The 3D response surfaces [30] for peak cutting force and peak cutting power are shown in Figures 11 and 12, respectively. As rotational speed increases, the peak cutting force exhibits a continuously decreasing trend, while peak cutting power shows a continuously increasing trend. As feed speed increases, both peak cutting force and peak cutting power follow a continuously increasing trend. Similarly, as moisture content increases, both peak cutting force and peak cutting power also exhibit a continuously increasing trend. As shown in Figure 13, a comparison between the single-factor simulation results and the orthogonal experiment results indicates that the observed trends in rotational speed and feed speed are largely consistent with the patterns identified in the single-factor experiments. The results of the orthogonal experiments are slightly higher than those of the simulations. This discrepancy can be attributed to the fact that the simulation neglected the influence of bush moisture content on the cutting process. Moreover, dynamic factors such as vibration, impact, and rebound occurring during actual bush cutting further contribute to the difference.