## 3 Simulation Signal Analysis
The calculated correlation coefficient  
Figure 6: A time–frequency diagram of the original signal; (**a**) Noiseless STFT; (**b**) Noiseless CWT; (**c**) Noise-containing STFT; (**d**) Noise-containing CWT. between the original signal and the denoised reconstruction is 0.8957. Combined with Figure 8, it can be seen that although the original signal is somewhat distorted, it is generally well preserved. This indicates that the proposed method effectively reduces the impact of strong noise signals on the original signal. To provide a clearer and more intuitive assessment of the effectiveness of the joint noise reduction method, Figure 9 illustrates the time-domain graphs of the following signals: the noise-free test signal, the original signal containing noise, and the reconstructed signal obtained using the noise reduction method proposed in this paper. The graph clearly demonstrates the notable improvement achieved in reducing noise through the application of the proposed method. Figure 8: The time–frequency plot of the noise-containing signal after SVD thresholding noise reduction reconstruction with improved CEEMDAN decomposition; (**a**) STFT; (**b**) CWT. Figure 7: The time–frequency plot of the noise-containing raw signal after direct SVD thresholding noise reduction; (**a**) STFT; (**b**) CWT. Figure 9: Signal Denoising Effect Comparison. Table 3 shows that in the decomposed IMFs, the improved CEEMDAN has relatively lower sample entropy values compared with EMD, EEMD, CEEMD, and CEEMDAN. CEEMDAN has a relatively low sample entropy value compared with EMD, CEEMD, and CEEMDAN. Higher sample entropy values indicate higher complexity in the signal sequence. Therefore, the improved CEEMDAN decomposition can effectively decompose the signal while maintaining a higher decomposition accuracy. This is advantageous for the further denoising analysis of the signal. From Table 3, it can be seen that for the test \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Decomposition Algorithm** & **Decomposition Order** & **Kurtosis** & **Sample Entropy** \\ \hline \hline \multirow{8}{*}{EMD} & IMF1 & 2.8850 & 1.5207 \\  & IMF2 & 4.0809 & 1.1447 \\  & IMF3 & 3.2409 & 0.676 \\  & IMF4 & 3.2129 & 0.5941 \\  & IMF5 & 2.7578 & 0.4715 \\  & IMF6 & 2.6045 & 0.2547 \\ \hline \multirow{8}{*}{EEMD} & IMF1 & 2.9901 & 1.4206 \\  & IMF2 & 3.8286 & 1.2053 \\  & IMF3 & 3.0479 & 0.7125 \\  & IMF4 & 3.1395 & 0.6053 \\  & IMF5 & 2.7688 & 0.4845 \\  & IMF6 & 3.8040 & 0.2774 \\ \hline \multirow{8}{*}{CEEMD} & IMF1 & 3.6328 & 1.8710 \\  & IMF2 & 4.0387 & 1.5538 \\  & IMF3 & 3.8680 & 0.9767 \\ \cline{1-1}  & IMF4 & 2.9873 & 0.6612 \\ \cline{1-1}  & IMF5 & 2.9404 & 0.5448 \\ \cline{1-1}  & IMF6 & 2.8592 & 0.3943 \\ \hline \multirow{8}{*}{CEEMDAN} & IMF1 & 3.0208 & 1.4703 \\  & IMF2 & 4.8258 & 1.1438 \\ \cline{1-1}  & IMF3 & 3.0152 & 0.6755 \\ \cline{1-1}  & IMF4 & 2.9912 & 0.6007 \\ \cline{1-1}  & IMF5 & 2.8928 & 0.4823 \\ \cline{1-1}  & IMF6 & 2.5921 & 0.2651 \\ \hline \multirow{8}{*}{Improving} & IMF1 & 3.0247 & 1.4234 \\ \cline{1-1}  & IMF2 & 4.7644 & 0.8495 \\ \cline{1-1} \cline{2-2}  & IMF3 & 3.1458 & 0.6765 \\ \cline{1-1} \cline{2-2}  & IMF4 & 3.4839 & 0.5855 \\ \cline{1-1} \cline{2-2}  & IMF5 & 2.8339 & 0.4688 \\ \cline{1-1} \cline{2-2}  & IMF6 & 2.3244 & 0.2183 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Indicators of the test signal after decomposition. Figure 13: The decomposition of the IMF of each order using improved CEEMDAN decomposition. signals, the improved CEEMDAN decomposition has the largest kurtosis values for IMF2 and IMF4; therefore, it can be assumed that IMF2 and IMF4 contain more effective signals. Figures 14 and 15 show the original test signal, the STFT and the CWT after the SVD noise reduction technique, respectively. For the combined harvester test signal, the method proposed in this paper was used for noise reduction.