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Terrestrial Laser Scanning-Based Bridge Structural Condition Assessment. Tech Transfer Summary.
| 题名： | Terrestrial Laser Scanning-Based Bridge Structural Condition Assessment. Tech Transfer Summary. |
| 作者： | Turkan, Y.; Laflamme, S.; Tan, L. |
| 关键词： | bridge structural condition, Terrestrial laser scanner, Transportation safety, Bridge condition assessment, Crack detection, Wavelet neural networks, Pattern recognition, Safety risk, Automatic identification system, Performance measurement |
| 摘要： | Most bridge condition assessments in the US currently require trained inspectors to conduct complex and time-consuming visual inspections. TLS is a promising alternative method for documenting infrastructure condition. This advanced imaging technology rapidly measures the three-dimensional (3D) coordinates of densely scanned points within a scene to produce 3D point clouds, which are then analyzed using computer vision algorithms to assess structural conditions. This technology has been shown to effectively identify structural condition indicators, such as cracks, displacements, and deflected shapes, and is able to provide high coverage and accuracy at long ranges. However, large-scale, high-resolution scanning requires a significant amount of time on site, and data file sizes are typically very large and require extensive computational resources. Therefore, advanced algorithms are needed that would enable automated 3D shape detection from low-resolution point clouds during data collection. |
| 总页数： | Turkan, Y.; Laflamme, S.; Tan, L. |
| 报告类型： | 科技报告 |
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