4.7 Article

Subsea pipeline leak inspection by autonomous underwater vehicle

期刊

APPLIED OCEAN RESEARCH
卷 107, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apor.2020.102321

关键词

AUV; Pipeline inspection; Multibeam echo sounder; Forward looking sonar; Obstacle avoidance

资金

  1. National Natural Science Foundation of China [51675372, 51721003]
  2. major national science and technology projects of China [2016ZX05057-005]
  3. CNOOC Deep Sea Development Co., Ltd

向作者/读者索取更多资源

This study developed a scheme using AUV equipped with MBES and FLS for automatic inspection of submarine pipelines, with sea trial results verifying its effectiveness. The adoption of VBS system enhances navigation efficiency, and an improved Otsu algorithm is proposed to improve obstacle avoidance.
Faced with the difficulty in finding and locating leakage points of submarine pipelines timely as well as the high cost of pipeline routine inspection, a scheme using autonomous underwater vehicle (AUV) equipped with multi beam echo sounder (MBES) and forward looking sonar (FLS) for automatic inspection of submarine pipelines was developed. In the process of inspection, the AUV maintains autonomous navigation along the pre-set pipeline route at a fixed height above the pipeline, while the MBES collects water column images. After extracting the outline characteristics of gas-filled bubbles and making a leakage risk judgment, it rises to the sea surface to issue an alarm to the shore-based command center via satellite. The results of sea trial verify the effectiveness of sub-sea pipeline leak detection and real-time obstacle avoidance of the vehicle proposed in this study. Additionally, a variable buoyancy system (VBS) is adopted, which enhances the navigation efficiency of the vehicle. On the other hand, considering the complex operation environment of the pipeline inspection, the online collision avoidance is indispensable. The traditional image segmentation algorithm is not ideal for the high noise and bottom reverberation in operation sea area. Based on the traditional algorithm, an improved Otsu algorithm is proposed to improve the operation speed and denoise effect. As a result, an improved Otsu algorithm is proposed to accurately identify obstacles. Moreover, Kalman filtering is also introduced to estimate dynamic obstacles.

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