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Acoustic Assessment of Polymetallic Nodule Abundance Using Sidescan Sonar and Altimeter
IEEE Journal of Oceanic Engineering ( IF 4.1 ) Pub Date : 2021-01-01 , DOI: 10.1109/joe.2020.2967108
Liang Jie Wong , Bharath Kalyan , Mandar Chitre , Hari Vishnu

Polymetallic nodules (PMN) are potato-sized concretions containing metals, such as manganese, copper, nickel, cobalt, and rare earth elements, and are a potential valuable resource of minerals. They occur in high abundance and are unevenly distributed across the Clarion Clipperton Fracture Zone. Existing PMN abundance estimation methods using box corers, and manual assessment through seabed photographs are labor and time intensive, and can only survey small sections of seabed at a time. Compared to an underwater camera, acoustic sensors are able to survey the PMN abundance across larger tracts of seabed at a time. In this article, we present a method for PMN abundance assessment using heterogeneous acoustic data, which is a combination of bathymetry information and sidescan sonar measurements of seabed backscatter. We achieve this using an artificial neural network model that classifies a given region into a low or high PMN density region using these features. Our model will enable faster estimation of PMN abundance for future deep seabed site surveys without the need for underwater cameras. To date, our proposed method yields an average accuracy of 85.36% on a testing data set, demonstrating our method's effectiveness in estimating PMN abundance.

中文翻译:

使用侧扫声纳和高度计对多金属结核丰度进行声学评估

多金属结核(PMN)是马铃薯大小的结核,含有锰、铜、镍、钴和稀土元素等金属元素,是一种潜在的宝贵矿产资源。它们以高丰度出现并且在克拉里昂克利珀顿断裂带中分布不均。现有的 PMN 丰度估计方法使用箱形取芯器和通过海底照片进行人工评估是劳动密集型和时间密集型的,并且一次只能调查海床的一小部分。与水下相机相比,声学传感器能够一次测量大片海床的 PMN 丰度。在本文中,我们提出了一种使用异构声学数据进行 PMN 丰度评估的方法,该方法结合了测深信息和海底反向散射的侧扫声纳测量。我们使用人工神经网络模型实现这一点,该模型使用这些特征将给定区域分类为低或高 PMN 密度区域。我们的模型将能够在不需要水下相机的情况下更快地估计 PMN 丰度,以用于未来的深海海底现场调查。迄今为止,我们提出的方法在测试数据集上的平均准确率为 85.36%,证明了我们的方法在估计 PMN 丰度方面的有效性。
更新日期:2021-01-01
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