## 4 Experimental Investigations
### Obtain the Measured Signals and Classification Results
WPT using Daubechies wavelet (Db18) is employed to decompose each segment into three layers, and the data processing procedures are similar to those used in Section 3.2. Table 5 shows the typical five time domain feature parameters for the eight frequency bands in the first segment (400 data points) gained from four faults (shown in Figure 11). Table 6 presents the final classification results, i.e., the classification accuracy ratios for the misalignment and the unbalance are 82% and 87%, respectively, whereas, for the rub-impact and the combination of rub-impact and unbalance, the classification accuracy ratios are 73% and 79%. The final results show that the proposed personalized fault diagnosis methodology might be used in practical applications. However, further works, such as the high performance finite element model updating techniques, the contact surface stiffness and damping parameters, the two- and three-dimensional geometry models of complex mechanical systems, etc., should be investigated in depth to improve the classification accuracy ratios and extend the application of the present methodology. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Different Types Faults** & \begin{tabular}{c} **Training** \\ **Samples** \\ \end{tabular} & \begin{tabular}{c} **Testing** \\ **Samples** \\ \end{tabular} & \
\begin{tabular}{c} **Faults** \\ **Labels** \\ \end{tabular} &
\begin{tabular}{c} **Classification** \\ **Accuracy** \\ \end{tabular} \\ \hline Unbalance & 20 & 20 & 1 & 87\% \\ Misalignment & 20 & 20 & 2 & 82\% \\ Rub-impact & 20 & 20 & 3 & 73\% \\ combination of rub-impact and unbalance & 20 & 20 & 4 & 79\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The different types of faults’ recognition results. \begin{table} \begin{tabular}{c c c c c c c c c} \hline \hline
**Unbalance** & \multicolumn{6}{c}{**The Calculated Results in 8 Frequency Bands of Unbalance Fault**} \\ \cline{2-9}  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline SD & \(1.17\times 10^{-2}\) & \(2.12\times 10^{-4}\) & \(1.30\times 10^{-4}\) & \(1.4\times 10^{-4}\) & \(1.10\times 10^{-5}\) & \(1.20\times 10^{-5}\) & \(1.2\times 10^{-4}\) & \(1.10\times 10^{-5}\) \\ Peak & \(2.15\times 10^{-2}\) & \(5.4\times 10^{-4}\) & \(3.80\times 10^{-4}\) & \(5.20\times 10^{-4}\) & \(3.40\times 10^{-4}\) & \(3.10\times 10^{-4}\) & \(3.9\times 10^{-4}\) & \(2.80\times 10^{-4}\) \\ Kurtosis & 1.88 & 2.70 & 3.45 & 3.27 & 2.91 & 2.66 & 3.29 & 2.89 \\ CLF & 2.41 & 3.87 & 4.75 & 5.88 & 4.39 & 3.78 & 4.73 & 4.14 \\ IF & 2.14 & 3.30 & 3.91 & 4.98 & 3.70 & 3.20 & 3.99 & 3.46 \\ \hline \hline \end{tabular} \begin{tabular}{c c c c c c c c} \hline \hline
**Misalignment** & \multicolumn{6}{c}{**The Calculated Results in 8 Frequency Bands of Unbalance Fault**} \\ \cline{2-9}  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline SD & \(1.05\times 10^{-2}\) & \(4.80\times 10^{-4}\) & \(1.30\times 10^{-4}\) & \(1.10\times 10^{-4}\) & \(1.10\times 10^{-4}\) & \(1.20\times 10^{-4}\) & \(1.20\times 10^{-4}\) & \(1.30\times 10^{-4}\) \\ Peak & \(2.01\times 10^{-2}\) & \(1.64\times 10^{-3}\) & \(3.70\times 10^{-4}\) & \(3.10\times 10^{-4}\) & \(2.90\times 10^{-4}\) & \(3.90\times 10^{-4}\) & \(3.40\times 10^{-4}\) & \(3.90\times 10^{-4}\) \\ Kurtosis & 2.21 & 3.25 & 3.195 & 2.70 & 3.20 & 3.73 & 3.02 & 3.05 \\ CLF & 2.61 & 5.05 & 4.305 & 3.85 & 4.41 & 5.27 & 4.33 & 4.42 \\ IF & 2.29 & 4.28 & 3.62 & 3.33 & 3.60 & 4.41 & 3.64 & 3.71 \\ \hline \hline \end{tabular}