改进的桥梁三维重构及裂缝检测系统

针对桥梁病害检测问题, 尤其是损害程度较高的裂缝检测, 结合已有的桥梁检测系统, 本文提出一种改进的桥梁检测系统, 改进后的系统硬件是大疆M210-RTK无人机, 软件由图像数据获取模块、裂缝检测模块、3D模型构建模块构成. 其中, 裂缝检测模块增加了裂缝长宽计算功能, 对裂缝分段迭代后进行曲线拟合求取长度, 骨架法计算宽度. 在实验中设置无人机的飞行轨迹、扫描间距, 拍摄距离以及对待检测桥梁桥墩分区域编号, 最终拍摄了200张桥墩桥面图片和采集了桥梁视频数据. 通过对桥墩桥面裂缝种类的识别和裂缝长宽计算, 更全面的了解了裂缝信息及危害程度, 减少了后期人工测量, 并结合Ubuntu 16.04系统, 使用直接稀疏里程计法(DSO)进行桥梁3D建模, 3D模型能够方便直观的展示桥梁概况. 改进后的系统稳定, 方法省时省力, 适用性广, 特别是对一些跨海大桥及周边环境复杂的桥梁检测具有重要意义.

Improved Bridge 3D Reconstruction and Crack Detection System

Aiming at the problem of bridge disease detection, especially the crack detection with high degree of damage, combined with the previous bridge detection system, an improved bridge detection system was proposed in this study. The hardware of the improved system is the DJI M210-RTK Unmanned Aerial Vehicle (UAV), and the software consists of image data acquisition module, crack detection module, and a module of 3D model building. In this study, calculation function of crack length and width is added to the crack detection module, and the length of the crack is calculated by curve fitting after iteration, besides, skeleton method is used to calculate the width. In the experiment, by setting the flight path, scanning distance, shooting distance of the UAV and the sub-region number of the bridge pier to be tested in advance, 200 pictures of the bridge pier deck and the video data of the bridge were collected. By identifying the crack types of bridge deck, and calculating length and width of crack, it can make us having a more comprehensive understanding of crack information and the degree of damage, and manual measurement in later period can be reduced, besides, combined with Ubuntu 16.04 system, the 3D model can easily and intuitively display the general situation of the bridge with using Direct Sparse Odometry (DSO) to carry out bridge 3D modeling. The improved system is stable, the method saves time and effort, and has wide applicability, especially for the detection of some sea-crossing bridges and bridges with complex surrounding environments.