CCTV视觉图像处理方法在土石坝涵管病害诊断中的应用

Application of CCTV visual image processing method in culvert disease diagnosis of earth-rock fill dam

随着土石坝服役时间延长,其下伏涵管病害尤其是渗漏现象亟需快速精准的安全诊断。提出了一种可用于土石坝涵管病害诊断的多视角视觉图像拼接方法,通过Closed Circuit Television(CCTV)管道机器人采集土石坝涵管全景视觉图像,结合多视几何三维重建技术构建涵管三维点云,再利用三维曲面估计技术判断出模型曲面,并对图像进行展平拼接,实现了土石坝涵管图像的渗漏与裂缝缺陷数字化自动识别和准确定位,为病害处治提供了参考依据。以湖南省某中型水库导流涵管为例,采用CCTV管道机器人采集涵管图像,通过多视角视觉图像拼接方法,获取了涵管全景数字展开图,与现场实地检查情况一致。该方法具有检测灵活、快速精准以及成本低廉等优点,在土石坝涵管病害检测领域具有广泛的应用前景。

The earth-rockfill dam construction in China has been greatly improved in the past few decades. However, with the extension of the service period of the earth-rockfill dam, its underlying culvert pipe diseases, especially leakage phenomenon, need to be diagnosed quickly and accurately. Therefore, a multi-view visual image stitching method is proposed for the diagnosis of culvert pipe diseases in the earth-rockfill dam. By use of closed circuit television(CCTV) pipeline robot collecting panoramic visual images of the culvert pipe in the earth-rockfill dam, based on multi-view geometry three-dimensional reconstruction technology, the three-dimensional point cloud of the culvert pipe is developed. Then, the surface of the model is judged by using three-dimensional surface estimation technology, and the images are flattened and stitched. The digital automatic identification and accurate location of water seepage and crack defection in the culvert pipe images of the earth-rockfill dam are realized, and the diagnosis results coincide with those of the field inspection, which can provide a reference for disease treatment. This diagnosis method has the advantages of flexible, fast and accurate detection and low cost, and has a wide application prospect in the field of the culvert disease inspection of the earth-rockfill dams.