Research Article
Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures
Table 6
The identification results of damage locations when two braces are damaged.
| | Damage scenarios | aj (%) | T (°C) | Output nodes | | First | Second | Third |
| | DC 4 | 50 | 20 | 1 (1) | 3.66 × 10−8 (0) | 8.99 × 10−9 (0) | | 30 | 1 (1) | 1.32 × 10−8 (0) | 4.68 × 10−10 (0) | | 70 | 20 | 1 (1) | 7.08 × 10−7 (0) | 4.58 × 10−9 (0) | | 30 | 1 (1) | 3.51 × 10−7 (0) | 1.04 × 10−8 (0) | | DC 5 | 50 | 20 | 1.03 × 10−5 (0) | 0.99857 (1) | 1.93 × 10−5 (0) | | 30 | 5.61 × 10−7 (0) | 0.9816 (1) | 0.010006 (0) | | 70 | 20 | 3.84 × 10−8 (0) | 1 (1) | 1.25 × 10−6 (0) | | 30 | 3.02 × 10−7 (0) | 1 (1) | 1.35 × 10−6 (0) | | DC 6 | 50 | 20 | 5.31 × 10−5 (0) | 4.95 × 10−7 (0) | 0.99953 (1) | | 30 | 1.41 × 10−4 (0) | 2.66 × 10−7 (0) | 0.99957 (1) | | 70 | 20 | 7.44 × 10−7 (0) | 1.84 × 10−6 (0) | 0.99999 (1) | | 30 | 4.98 × 10−7 (0) | 7.60 × 10−7 (0) | 0.99999 (1) |
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The target results of networks are shown in the parentheses.
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