High-accuracy acoustic sediment classification using sub-bottom profile data

He, Linbang; Zhao, Jianhu; Lu, Jianhua; Qiu, Zhaobin

doi:10.1016/j.ecss.2021.107701

Cited by 7 publications

(3 citation statements)

References 51 publications

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“…The rapid advancement of acoustic technology has led to the widespread utilization of sub-bottom profilers in the detection of submarine sediment. These profilers are employed in various applications including submarine geological classification [ [20] , [21] , [22] ], research on submarine disasters [ [23] , [24] , [25] ], and exploration of submarine pipelines [ 26 , 27 ]. This is due to their high accuracy, non-immersibility, real-time data display, portability, ease of operation, strong penetration, and relatively minimal attenuation in liquid [ 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Shallow mud detection algorithm for submarine channels based on improved YOLOv5s

Hou,

Zhang

2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Shallow mud detection algorithm for submarine channels based on improved YOLOv5s

Hou,

Zhang

2024

Heliyon

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“…Back-propagation neural network [11][12] is mostly used in the current research on SBP image classification. The basic principle and training algorithm of BP neural network are relatively simple and easy to understand and implement.…”

Section: Introductionmentioning

confidence: 99%

Reflection signal classification of deep-sea surface sediment based on 1DCNN-DLSTM networks

Qu,

Zhi,

Cao

et al. 2023

International Workshop on Signal Processing and Machine Learning (WSPML 2023)

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“…Sub-bottom profiling is a type of seabed acoustic mapping technology that uses the propagation and reflection characteristics of acoustic waves in seawater and seabed sediments to continuously detect seabed sediments and obtain visual sub-bottom profiles (He et al, 2022). The acoustic characteristics and internal organization of sediments have certain effects on the propagation of acoustic waves (Hamilton and Bachman, 1982).…”

mentioning

confidence: 99%

Creep characteristics of muddy submarine channel slope instability

Cun-yong¹,

Hou²

2022

Front. Mar. Sci.

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Creep is an important factor of muddy submarine channel slope instability. In this study, a sub-bottom profiler was used to monitor the continuous internal change of a muddy submarine channel slope in the laboratory to better understand the creep characteristics and mechanism of slope instability. The creep process was analyzed according to changes in the slope internal sound intensity. The results indicate a notable change of the creep characteristics during the slope instability process. Changes in the sound intensity time series decrease with increasing slope depth, and the fluctuation depth of the vertical sound intensity series varies during the slope creep process. The creep process of slope instability can be roughly divided into four stages based on the sub-bottom profile data: an expansion stage; an unstable expansion stage; a fracture stage; and a post-fracture development stage. An adjustment of the sediment microstructure in the slope is ascribed to slope creep deformation. This study highlights the prospects of high-resolution acoustic monitoring to detect and quantify the entire creep process of muddy submarine channel slope instability, which is of great significance for the evaluation and early warning prediction of channel slope instability.

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High-accuracy acoustic sediment classification using sub-bottom profile data

Cited by 7 publications

References 51 publications

Shallow mud detection algorithm for submarine channels based on improved YOLOv5s

Shallow mud detection algorithm for submarine channels based on improved YOLOv5s

Reflection signal classification of deep-sea surface sediment based on 1DCNN-DLSTM networks

Creep characteristics of muddy submarine channel slope instability

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