# Acoustic Emission Based Fault Detection of Substation Power Transformer
## 4 Results and Discussions
### The Influence of Various Parameters on the Classification System in Multi-Classification Problem
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Algorithms**} & \multicolumn{6}{c}{**Perprocessing**} \\ \cline{3-10} \multicolumn{2}{c}{} & \multicolumn{1}{c}{**PCA (Sum = 1302, 1300, 32)**} & \multicolumn{6}{c}{**2 DPCA (Sum = 1550, 1350, 33)**} \\ \cline{2-10} \multicolumn{2}{c}{} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.75}\)**} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.9}\)**} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.96}\)**} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.75}\)**} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.95}\)**} & \multicolumn{1}{c}{**\(\mathbf{\mu=0.99}\)**} \\ \multicolumn{2}{c}{} & \multicolumn{1}{c}{**Prediction = 2**} & \multicolumn{1}{c}{**Prediction = 3**} & \multicolumn{1}{c}{**Prediction = 11**} & \multicolumn{1}{c}{**Prediction = 1**} & \multicolumn{1}{c}{**Prediction = 2**} & \multicolumn{1}{c}{**Prediction = 5**} \\ \hline \multirow{8}{*}{**SVM**} & \multirow{4}{*}{Linear} & ERR sum = 6503 & ERR sum = 4766 & ERR sum = 4704 & ERR sum = 4766 & ERR sum = 3490 & ERR sum = 2500 \\  & & ACC = 99.45\% & ACC = 69.0\% & ACC = 69.0\% & ACC = 69.0\% & ACC = 69.2\% & ACC = 77.8\% & ACC = 83.8\% \\  & & SUN = 64.49\% & KAPPA = 8.0\% & KAPPA = 7.4\% & SAN = 72.5\% & SAN = 79.4\% & SAN = 84.1\% \\  & & test time = 3.87\% \(\times\) 10\({}^{-1}\) & test time = 9.25\% \(\times\) 10\({}^{-1}\) & test time = 9.25\% \(\times\) 10\({}^{-1}\) & test time = 1.56\% & test time = 1.57\% & KAPPA = 7.9\% & SAN = 79.4\% \\  & & ERR sum = 5601 & ERR sum = 4342 & ERR sum = 4244 & ERR sum = 4098 & ERR sum = 3180 & test time = 9.24\% \\  & & ACC = 67.9\% & ACC = 72.1\% & ACC = 72.9\% & ACC = 73.9\% & ACC = 75.9\% & ACC = 86.1\% \\  & & SEN = 72.10\% & SEN = 77.0\% & SEN = 77.2\% & SAN = 78.2\% & SAN = 80.1\% & SAN = 80.1\% \\  & & KAPPA = 8.8\% & KAPPA = 64.8\% & KAPPA = 63.4\% & KAPPA = 64.1\% & KAPPA = 7.9\% & KAPPA = 64.2\% \\  & & test time = 5.75\% \(\times\) 10\({}^{-1}\) & test time = 1.6\% & test time = 2.4\% & test time = 1.8\% & test time = 2.1\% & test time = 3.6\% \\ \hline \multirow{8}{*}{**KNN**} & \multirow{4}{*}{Linear} & ERR sum = 5607 & ERR sum = 5144 & ERR sum = 4881 & ERR sum = 4581 & ERR sum = 3523 & ERR sum = 2944 \\  & & ACC = 63.2\% & ACC = 66.5\% & ACC = 65.8\% & ACC = 70.6\% & ACC = 73.7\% & ACC = 84.5\% \\  & & SEN = 68.72\% & SN = 71.1\% & SEN = 74.4\% & SEN = 73.5\% & SEN = 79.5\% & SEN = 87.0\% \\  & & KAPPA = 53.5\% & KAPPA = 8.0\% & KAPPA = 60.1\% & KAPPA = 72.1\% & KAPPA = 8.0\% \\  & & test time = 6.32\% \(\times\) 10\({}^{-1}\) & test time = 1.8\% & test time = 1.9\% & test time = 1.9\% & test time = 2.4\% & test time = 3.9\% \\ \cline{2-10}  & & ERR sum = 5125 & ERR sum = 4042 & ERR sum = 4034 & ERR sum = 4340 & ERR sum = 3470 & ERR sum = 2400 \\  & & ACC = 66.9\% & ACC = 72.2\% & ACC = 72.0\% & ACC = 76.1\% & ACC = 75.4\% & ACC = 84.2\% \\  & & SEN = 72.1\% & SEN = 87.4\% & SEN = 77.2\% & SEN = 80.4\% & SEN = 88.0\% \\  & & KAPPA = 7.9\% & KAPPA = 64.1\% & KAPPA = 63.5\% & KAPPA = 64.0\% & KAPPA = 71.8\% & KAPPA = 8.0\% \\  & & test time = 3.370\(\times\) 10\({}^{-1}\) & test time = 1.2\% & test time = 4.0\% & test time = 2.8\% & test time = 4.2\% & test time = 1.3\% \\ \hline \multirow{8}{*}{**CNN**} & \multirow{4}{*}{Linear} & ERR sum = 5609 & ERR sum = 4726 & ERR sum = 4858 & ERR sum = 4729 & ERR sum = 7947 & ERR sum = 7248 \\  & & ACC = 63.8\% & ACC = 69.4\% & ACC = 66.0\% & KAP = 69.3\% & ACC = 75.8\% & SEN = 84.0\% \\ \cline{1-1}  & & SEN = 69.4\% & SNN = 79.5\% & SNN = 72.4\% & SNN = 79.4\% & SEN = 79.0\% & SEN = 84.0\% \\ \cline{1-1}  & & KAPPA = 53.5\% & KAPPA = 61.1\% & KAPPA = 60.1\% & KAPPA = 69.4\% & KAPPA = 7.9\% & KAPPA = 7.75\% \\ \cline{1-1}  & & & test time = 5.79\% \(\times\) 10\({}^{-1}\) & test time = 2.297 \(\times\) 10\({}^{-1}\) & \(\mathbf{\mu=1.58}\) & 3.76\% & 5.87\% & 11.6\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of the experiment for testing sets including three machine learning algorithms, tenfold cross validation, and six variants of signal preprocessing results of the multi-classification experiment.