# Acoustic Emission Based Fault Detection of Substation Power Transformer
## 4 Results and Discussions
### The Fault Detection by SVM Binary Classification Method
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithms**} & \multicolumn{2}{c}{**Without PCA**} & \multicolumn{4}{c}{**With PCA (Sum = 1532, 1520, 33)**} & \multicolumn{4}{c}{**With 2 DPCA (Sum = 1532, 1530, 33)**} \\ \cline{3-11}  & & & & \multicolumn{2}{c}{**n = 0.95**} & \multicolumn{2}{c}{**n = 0.96**} & \multicolumn{2}{c}{**n = 0.75**} & \multicolumn{2}{c}{**n = 0.95**} & \multicolumn{2}{c}{**n = 0.95**} \\  & & & & & \multicolumn{2}{c}{**P Injection = 2**} & \multicolumn{2}{c}{**P Projection = 3**} & \multicolumn{2}{c}{**P Projection = 10**} & \multicolumn{2}{c}{**P Projection = 1**} & \multicolumn{2}{c}{**P Projection = 2**} & \multicolumn{2}{c}{**P Projection = 5**} \\ \hline \multirow{5}{*}{SVM} & \multirow{5}{*}{Linear} & ERR sum = 1043 & ERR sum = 118 & ERR sum = 29 & ERR sum = 171 & ERR sum = 6 & ERR sum = 98 & ERR sum = 1607 \\  & & ACC = 0.9235, & ACC = 0.988, & ACC = 0.988, & ACC = 0.987, & ACC = 0.989, & ACC = 0.986, & ACC = 0.937, & ACC = 0.926, \\  & & SEN = 8.4670, & SEN = 8.975, & SEN = 8.975, & SEN = 8.975, & SEN = 1.007, & SEN = 1.007, & SEN = 1.007, & SEN = 9.875, \\  & & test time = 12.285 & test time = 2.520 \(\times\) 10\({}^{-}\)s & test time = 4.033 \(\times\) 10\({}^{-}\)s & test time = 12.208 & test time = 0.068, & test time = 0.906, & test time = 2.997, \\ \cline{2-11}  & & ERR sum = 3.235 & ERR sum = 2200 & ERR sum = 291 & ERR sum = 306 & ERR sum = 201 & ERR sum = 2018 & ERR sum = 2028 \\  & & ACC = 7.916, & ACC = 0.659, & ACC = 0.729, & ACC = 0.807, & ACC = 0.807, & ACC = 0.867, & ACC = 0.866, & ACC = 0.887, \\  & & SEN = 8.525, & SEN = 8.505, & SEN = 8.844, & ACC = 0.814, & SEN = 9.25, & SEN = 9.315, & SEN = 9.307, & SEN = 9.307, \\  & & test time = 13.51, s & test time = 2.570 \(\times\) 10\({}^{-}\)s & test time = 3.021 \(\times\) 10\({}^{-}\)s & test time = 0.550, & test time = 0.880, & test time = 1.362, & test time = 4.110, \\ \cline{2-11}  & & ERR sum = 206 & ERR sum = 227 & ERR sum = 202 & ERR sum = 200 & ERR sum = 101 & ERR sum = 1800 & ERR sum = 1900 \\  & & ACC = 8.147, & ACC = 0.814, & ACC = 0.867, & ACC = 0.847, & ACC = 0.935, & SEN = 9.307, & SEN = 9.315, \\  & & SEN = 7.219, & SEN = 1003 & SEN = 8.987, & SEN = 9.75, & SEN = 1007, & SEN = 9.531, & SEN = 9.95 \\  & & test time = 11.22, s & test time = 2.027 \(\times\) 10\({}^{-}\)s & test time = 2.460, \(\times\) 10\({}^{-}\)s & test time = 3.036, & test time = 0.880, & test time = 1.028 & test time = 3.500, \\ \cline{2-11}  & & ERR sum = 4061 & ERR sum = 228 & ERR sum = 2719 & ERR sum = 303 & ERR sum = 1380 & ERR sum = 1380 & ERR sum = 2827 & ERR sum = 3015 \\  & & ACC = 7.835, & ACC = 0.807, & ACC = 82.84, & ACC = 0.769, & ACC = 0.415, & ACC = 0.317, & ACC = 0.372, & ACC = 0.737, \\ \cline{2-11}  & & ERR sum = 8.715, & SEN = 8.944, & SEN = 8.875, & SEN = 8.915, & SEN = 8.98, & SEN = 8.84, & SEN = 8.945, & SEN = 8.946, \\ \hline \multirow{5}{*}{KNN} & \multirow{5}{*}{\(p\) = 2} & ERR sum = 1316 & ERR sum = 1314 & ERR sum = 1516 & ERR sum = 1121 & ERR sum = 2348 & ERR sum = 2511 \\  & & ACC = 0.935, & ACC = 0.978, & ACC = 0.915, & ACC = 0.925, & ACC = 0.928, & ACC = 0.927, & ACC = 0.828, \\ \cline{1-1}  & & \(p\) = 2 & ERR = 2.046, & SEN = 9.245, & SEN = 9.125, & SEN = 9.496, & SEN = 9.496, & SEN = 9.496, & SEN = 9.815, \\ \cline{1-1}  & & & test time = 2.507 \(\times\) 10\({}^{-}\)s & test time = 1.265 \(\times\) 10\({}^{-}\)s & test time = 1.301 s & test time = 2.205 s & test time = 4.387 s & test time = 10.300 s \\ \hline \multirow{5}{*}{CNN} & \multirow{5}{*}{\(p\) = 2} & ERR sum = 276 & ERR sum = 276 & ERR sum = 276 & ERR sum = 276 & ERR sum = 276 & ERR sum = 276 \\ \cline{1-1}  & & ACC = 0.812, & ACC = 0.819, & ACC = 0.812, & ACC = 0.812, & ACC = 0.812, & ACC = 0.812, \\ \cline{1-1}  & & & SEN = 9.18, & SEN = 9.18, & SEN = 9.18, & SEN = 9.18, & SEN = 9.44, & SEN = 9.496, \\ \cline{1-1}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & & \\ \cline{1-1} \cline{2-11}  & & & & & & & & & &Sliding AE signals and discharge AE signals are taken as fault samples, they constitute the fault category, the others constitute the normal category (see Table 1).