Research Article
Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures
Table 10
The identification results of damage locations when two braces are damaged with noises.
| | Damage scenarios | aj (%) | T (°C) | Output nodes | | Noise intensity (1%) | Noise intensity (3%) | | First | Second | Third | First | Second | Third |
| | DC 4 | 50 | 20 | 0.999987 (1) | 1.99 × 10−6 (0) | 1.34 × 10−4 (0) | 0.999997 (1) | 0.000372 (0) | 3.37 × 10−6 (0) | | 30 | 0.999999 (1) | 3.69 × 10−6 (0) | 1.96 × 10−6 (0) | 0.999999 (1) | 0.000174 (0) | 9.04 × 10−8 (0) | | 70 | 20 | 0.999994 (1) | 2.97 × 10−6 (0) | 3.85 × 10−5 (0) | 0.999960 (1) | 4.00 × 10−5 (0) | 5.17 × 10−3 (0) | | 30 | 0.999997 (1) | 5.64 × 10−6 (0) | 1.68 × 10−5 (0) | 0.999999 (1) | 2.96 × 10−6 (0) | 2.33 × 10−6 (0) | | DC 5 | 50 | 20 | 7.19 × 10−4 (0) | 0.999967 (1) | 7.14 × 10−8 (0) | 0.031974 (0) | 0.999966 (1) | 5.06 × 10−8 (0) | | 30 | 2.61 × 10−2 (0) | 0.999996 (1) | 1.16 × 10−8 (0) | 0.011941 (0) | 0.999970 (1) | 6.86 × 10−8 (0) | | 70 | 20 | 2.61 × 10−8 (0) | 0.999855 (1) | 4.84 × 10−4 (0) | 5.12 × 10−8 (0) | 0.999957 (1) | 1.68 × 10−3 (0) | | 30 | 1.08 × 10−8 (0) | 1 (1) | 4.50 × 10−4 (0) | 0.000281 (0) | 0.999975 (1) | 1.86 × 10−6 (0) | | DC 6 | 50 | 20 | 2.16 × 10−6 (0) | 1.63 × 10−6 (0) | 0.999998 (1) | 0.086943 (0) | 1.16 × 10−6 (0) | 0.998469 (1) | | 30 | 1.92 × 10−6 (0) | 1.63 × 10−6 (0) | 0.999998 (1) | 0.000482 (0) | 1.36 × 10−6 (0) | 0.999981 (1) | | 70 | 20 | 2.67 × 10−5 (0) | 1.32 × 10−6 (0) | 0.999982 (1) | 0.306331 (0) | 8.76 × 10−6 (0) | 0.990272 (1) | | 30 | 7.32 × 10−3 (0) | 5.53 × 10−6 (0) | 0.989758 (1) | 0.228254 (0) | 8.42 × 10−6 (0) | 0.796207 (1) |
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The target results of networks are shown in the parentheses.
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