Table 4.
Comparison fault detection result by F1-score.
States | PCA | Typical LSTM | Optimized LSTM | SVM using a linear kernel | Auto encoder | The proposed approach in this paper |
---|---|---|---|---|---|---|
Fault1 | 1 | 0.09 | 0.68 | 0.87 | 0.98 | 1 |
Fault2 | 0.79 | 0.12 | 0.78 | 0.88 | 0.85 | 0.89 |
Fault3 | 0.34 | 0.03 | 0.45 | 0.79 | 0.91 | 0.94 |
Fault4 | 0.99 | 0.04 | 0.75 | 0.9 | 0.89 | 0.99 |
Fault5 | 0.56 | 0.2 | 0.89 | 0.9 | 0.93 | 0.94 |
Fault6 | 0.99 | 0.34 | 1 | 0.95 | 0.85 | 1 |
Fault7 | 1 | 0.19 | 0.89 | 0.92 | 0.80 | 1 |
Fault8 | 0.97 | 0.22 | 0.71 | 0.63 | 0.73 | 0.99 |
Fault9 | 0.78 | 0.01 | 0.67 | 0.76 | 0.76 | 0.81 |
Fault10 | 0.66 | 0.28 | 0.77 | 0.89 | 0.79 | 0.99 |
Fault11 | 0.71 | 0.12 | 0.83 | 0.9 | 0.77 | 0.88 |
Fault12 | 0.99 | 0.31 | 0.56 | 0.75 | 0.93 | 0.99 |
Fault13 | 0.87 | 0.22 | 0.89 | 0.82 | 0.91 | 0.89 |
Fault14 | 0.98 | 0.41 | 0.99 | 0.88 | 0.78 | 0.99 |
Fault15 | 0.26 | 0.01 | 0 | 0.21 | 0.01 | 0.22 |
Fault16 | 0.24 | 0.12 | 0 | 0.14 | 0.33 | 0.31 |
Fault17 | 0.99 | 0.24 | 0.2 | 0.79 | 0.89 | 0.97 |
Fault18 | 0.78 | 0.31 | 0.88 | 0.66 | 0.95 | 0.89 |
Fault19 | 0.88 | 0.17 | 0.91 | 0.86 | 0.64 | 0.97 |
Fault20 | 0.82 | 0.28 | 0.64 | 0.78 | 0.83 | 0.85 |