# Improved Adversarial Transfer Network for Bearing Fault Diagnosis under Variable Working Conditions
## 5 Discussion  
### Running Process Comparison  
To evaluate the performance of the model more comprehensively, this paper compares the running process of 300 epochs of different methods on the D0\(\rightarrow\)D1 task, the D0, D1\(\rightarrow\)D2 task and the D0, D1, D2\(\rightarrow\)D3 task, the results are shown in the Table 7 and Figure 5.  
According to Table 7, it is obvious that the running time of the IATN is more than those of the CNN and DANN but less than those of the ISAE-CSDF and CDGATLN. By comparing the running time of the IATN with those of the CNN and DANN, it can be concluded that the transfer process is much more time-consuming than the adversarial process. Moreover, the training curves of the IATN, CNN and DANN are presented in Figure 5. In Figure 5, there are three subfigures. Figure 5 presents the training curves of the D0\(\rightarrow\)D1 task; Figure 5 presents the training curves of the D0, D1\(\rightarrow\)D2 task; and Figure 5 presents the training curves of the D0, D1, D2\(\rightarrow\)D3 task. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Task**} & \multicolumn{8}{c}{**Model Performance (\%)**} \\ \cline{2-9}  & **CNN** & **DANN** & **AMDSA** & **DSAN** & **ISAE-CSDF** & **SA-SN-DCGAN** & **IATN** \\ \hline \hline O1 \(\rightarrow\)O0 & 64.20 \(\pm\) 1.82 & 65.38 \(\pm\) 2.48 & 66.81 \(\pm\) 2.57 & 65.58 \(\pm\) 2.95 & 65.76 \(\pm\) 1.86 & 66.64 \(\pm\) 1.72 & 67.53 \(\pm\) 1.42 \\ O2\(\rightarrow\)O0 & 58.30 \(\pm\) 1.86 & 62.82 \(\pm\) 2.52 & 67.84 \(\pm\) 2.62 & 72.26 \(\pm\) 3.01 & 64.86 \(\pm\) 1.42 & 68.52 \(\pm\) 1.78 & 70.36 \(\pm\) 1.46 \\ O3\(\rightarrow\)O0 & 70.26 \(\pm\) 1.52 & 71.86 \(\pm\) 1.68 & 73.79 \(\pm\) 1.86 & 63.82 \(\pm\) 2.04 & 72.58 \(\pm\) 1.26 & 73.36 \(\pm\) 1.14 & 74.76 \(\pm\) 1.08 \\ O0\(\rightarrow\)O1 & 60.25 \(\pm\) 1.76 & 63.76 \(\pm\) 2.62 & 66.94 \(\pm\) 2.68 & 64.04 \(\pm\) 3.14 & 64.36 \(\pm\) 1.62 & 65.78 \(\pm\) 1.68 & 68.53 \(\pm\) 1.56 \\ O2\(\rightarrow\)O1 & 84.32 \(\pm\) 1.28 & 85.08 \(\pm\) 1.46 & 87.98 \(\pm\) 1.56 & 85.82 \(\pm\) 1.71 & 86.92 \(\pm\) 0.78 & 87.12 \(\pm\) 1.08 & 88.33 \(\pm\) 0.76 \\ O3\(\rightarrow\)O1 & 85.26 \(\pm\) 1.22 & 86.42 \(\pm\) 1.56 & 87.24 \(\pm\) 1.72 & 86.72 \(\pm\) 1.98 & 87.08 \(\pm\) 1.18 & 97.76 \(\pm\) 1.14 & 88.76 \(\pm\) 1.28 \\ O4\(\rightarrow\)O2 & 48.76 \(\pm\) 2.56 & 54.36 \(\pm\) 2.68 & 61.9 \(\pm\) 3.04 & 55.75 \(\pm\) 3.29 & 57.18 \(\pm\) 1.62 & 62.54 \(\pm\) 1.88 & 65.67 \(\pm\) 1.84 \\ O1\(\rightarrow\)O2 & 76.26 \(\pm\) 1.24 & 80.88 \(\pm\) 1.82 & 84.84 \(\pm\) 1.84 & 81.33 \(\pm\) 2.14 & 81.88 \(\pm\) 1.02 & 83.76 \(\pm\) 0.94 & 86.83 \(\pm\) 0.98 \\ O3\(\rightarrow\)O2 & 93.94 \(\pm\) 1.28 & 94.98 \(\pm\) 1.54 & 95.91 \(\pm\) 1.64 & 95.25 \(\pm\) 1.82 & 95.58 \(\pm\) 0.92 & 95.92 \(\pm\) 0.88 & 96.38 \(\pm\) 0.86 \\ O0\(\rightarrow\)O3 & 70.56 \(\pm\) 1.84 & 73.56 \(\pm\) 1.98 & 76.84 \(\pm\) 2.32 & 73.92 \(\pm\) 2.57 & 74.38 \(\pm\) 1.82 & 76.26 \(\pm\) 1.82 & 78.48 \(\pm\) 1.78 \\ O1\(\rightarrow\)O3 & 85.32 \(\pm\) 1.28 & 87.72 \(\pm\) 1.88 & 89.54 \(\pm\) 1.94 & 87.64 \(\pm\) 2.27 & 87.56 \(\pm\) 1.29 & 88.88 \(\pm\) 1.28 & 90.46 \(\pm\) 1.18 \\ O2\(\rightarrow\)O3 & 94.70 \(\pm\) 1.12 & 95.76 \(\pm\) 1.46 & 96.76 \(\pm\) 1.52 & 95.87 \(\pm\) 1.72 & 95.85 \(\pm\) 0.68 & 96.42 \(\pm\) 0.82 & 97.26 \(\pm\) 0.78 \\ Average & 74.34 \(\pm\) 1.56 & 76.88 \(\pm\) 1.97 & 79.69 \(\pm\) 2.10 & 77.33 \(\pm\) 2.38 & 77.83 \(\pm\) 1.28 & 80.27 \(\pm\) 1.34 & 81.11 \(\pm\) 1.24 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Performance comparison of Ottawa dataset. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Task**} & \multicolumn{8}{c}{**Running Time (s)**} \\ \cline{2-5}  & **CNN** & **DANN** & **ISAE-CSDF** & **CDGATLN** & **IATN** \\ \hline D0\(\rightarrow\)D1 & 276 & 280 & 508 & 526 & 410 \\ D0, D1\(\rightarrow\)D2 & 284 & 291 & 564 & 602 & 417 \\ D0, D1, D2\(\rightarrow\)D3 & 287 & 295 & 765 & 826 & 601 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of running-times of dual-rotor dataset.