Ecological Engineering Laboratory (ECOL), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Water Sci Technol. 2009;60(9):2281-9. doi: 10.2166/wst.2009.659.
Combined sewer overflows and stormwater discharges represent an important source of contamination to the environment. However, the harsh environment inside sewers and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. In the following, we present and evaluate an in situ system for the monitoring of water flow in sewers based on video images. This paper focuses on the measurement of the water level based on image-processing techniques. The developed image-based water level algorithms identify the wall/water interface from sewer images and measure its position with respect to real world coordinates. A web-based user interface and a 3-tier system architecture enable the remote configuration of the cameras and the image-processing algorithms. Images acquired and processed by our system were found to reliably measure water levels and thereby to provide crucial information leading to better understand particular hydraulic behaviors. In terms of robustness and accuracy, the water level algorithm provided equal or better results compared to traditional water level probes in three different in situ configurations.
合流制污水溢流和雨水排放是环境污染的一个重要来源。然而,污水管道内部恶劣的环境以及降雨事件期间特殊的水力条件,降低了传统流量测量探头的可靠性。在接下来的内容中,我们将展示和评估一种基于视频图像的污水管道内水流原位监测系统。本文重点介绍了基于图像处理技术的水位测量。所开发的基于图像的水位算法可以从污水管道图像中识别出壁面/水面界面,并测量其相对于实际世界坐标的位置。基于网络的用户界面和三层系统架构可实现对摄像机和图像处理算法的远程配置。通过我们的系统获取和处理的图像被发现可以可靠地测量水位,从而提供关键信息,以更好地理解特定的水力行为。在鲁棒性和准确性方面,该水位算法在三种不同的原位配置中提供的结果与传统水位探头相当或更好。