利用管道胶囊进行排水管网协同检测的新方法

Collaborative Inspection for the Sewer Pipe Network Using Pipe Capsules

  • 摘要: 排水管网是城市基础设施的重要组成部分,对排水管网进行周期性的全面检测是快速发现管道病害、及时进行维修整改和提高管道建设质量的关键。管道胶囊是一种新型管道检测设备,可以在管道内部随流体运动时拍摄管道内壁图像,智能高效地检测出管道病害。该方法弥补了传统方法检测效率低、作业成本高等不足。在大范围管网检测工作中,多名工作人员可以相互配合,同时,操作多胶囊进行协同检测。因此,设计胶囊的投放、打捞位置,以及规划工作人员运动路径对于提高检测效率至关重要。提出了一种基于管道胶囊的排水管网协同检测方法,以最短工作时间、最短运动距离、最大检测范围、最大检测度为目标,利用模拟退火算法求解出最优协同检测方案。实验结果显示,基于管道胶囊的排水管网协同检测方法能够在实际检测作业中高效地完成管网检测任务,准确地识别管道病害区域。

     

    Abstract:
      Objectives   The sewer pipeline network is an essential urban infrastructure. It is easy to be with faults because of the complicated circumstance under the ground, as well as undertaking the transportation and circulation of water. To avoid serious accidents caused by the faults, periodic and systematical inspection devices and methods are necessary. While current methods exist a variety of limitations, especially for large-scale and hard-inspected urban sewer pipe networks. Thus, we proposed a novel collaborative inspection method with high efficiency and availability, and low cost for urban sewer pipe networks.
      Methods  Firstly, we invent a novel device named pipe capsule equipped with video cameras, lights, and a data storage facility. It will be dropped into pipes, move along with water flow, and record the videos of the inner walls until salvaged by the staff from the downstream. Such that, the video is captured to inspect the underground pipe. Multiple capsules are cooperated to complete the inspection task. A collaborative inspection method is designed through well design practice plan by maximizing the inspection range and degree, as well as minimizing the traveling length and time of the workers. Simulated annealing with a simple neighborhood search strategy is used to find the best practice plan.
      Results  Taking the sewer pipe network at Shenzhen University, China an example, an experiment was conducted to verify the performance of the proposed approach. The results demonstrate that the collaborative inspection method achieves the same inspection with a shorter working time.
      Conclusion  This study presented a collaborative inspection approach to detect the large-scale and complicated urban sewer networks with machine vision. It will benefit the inspection and operation of the urban underground pipe network.

     

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