An Efficient Method for Detection and Quantitation of Underwater Gas Leakage Based on a 300-kHz Multibeam Sonar

Author:

Zhang WanyuanORCID,Zhou TianORCID,Li JianghuiORCID,Xu ChaoORCID

Abstract

In recent years, multibeam sonar has become the most effective and sensitive tool for the detection and quantitation of underwater gas leakage and its rise through the water column. Motivated by recent research, this paper presents an efficient method for the detection and quantitation of gas leakage based on a 300-kHz multibeam sonar. In the proposed gas leakage detection method based on multibeam sonar water column images, not only the backscattering strength of the gas bubbles but also the size and aspect ratio of a gas plume are used to isolate interference objects. This paper also presents a volume-scattering strength optimization model to estimate the gas flux. The bubble size distribution, volume, and flux of gas leaks are determined by matching the theoretical and measured values of the volume-scattering strength of the gas bubbles. The efficiency and effectiveness of the proposed method have been verified by a case study at the artificial gas leakage site in the northern South China Sea. The results show that the leaking gas flux is approximately between 29.39 L/min and 56.43 L/min under a bubble radius ranging from 1 mm to 12 mm. The estimated results are in good agreement with the recorded data (32–67 L/min) for gas leaks generated by an air compressor. The experimental results demonstrate that the proposed method can achieve effective and accurate detection and quantitation of gas leakages.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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1. Underwater Gas Leakage Flow Detection and Classification Based on Multibeam Forward-Looking Sonar;Journal of Marine Science and Application;2024-08-28

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4. A Lightweight Underwater Target Detection Network for Forward-Looking Sonar Images;IEEE Transactions on Instrumentation and Measurement;2024

5. SSE-YOLO : A Lighter and Faster Object Detection Network for Small Targets in Sonar Images;2023 IEEE 11th International Conference on Computer Science and Network Technology (ICCSNT);2023-10-21

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