Research Article
Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures
Table 9
The identification results of damage severities when one brace is damaged with noises.
| Damaged brace | aj (%) | T (°C) | Target output | Noise intensity (1%) | Noise intensity (3%) | Actual output | Relative error (%) | Actual output | Relative error (%) |
| 1 | 50 | 20 | 0.5 | 0.457 | 8.57 | 0.48937 | −2.13 | 30 | 0.5 | 0.534 | −6.74 | 0.52943 | 5.89 | 70 | 20 | 0.7 | 0.712 | −1.76 | 0.6847 | −2.19 | 30 | 0.7 | 0.727 | −3.91 | 0.7735 | 10.50 | 4 | 50 | 20 | 0.5 | 0.492 | 1.50 | 0.47049 | −5.90 | 30 | 0.5 | 0.468 | 6.39 | 0.45675 | −8.65 | 70 | 20 | 0.7 | 0.769 | −9.81 | 0.76837 | 9.77 | 30 | 0.7 | 0.743 | −6.15 | 0.71513 | 2.16 | 5 | 50 | 20 | 0.5 | 0.491 | 1.74 | 0.41528 | −16.94 | 30 | 0.5 | 0.528 | −5.53 | 0.41918 | −16.16 | 70 | 20 | 0.7 | 0.740 | −5.67 | 0.72871 | 4.10 | 30 | 0.7 | 0.738 | −5.40 | 0.72388 | 3.41 |
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