Shanghai Acoustics Laboratory, Chinese Academy of Sciences, Shanghai 201805, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2019 Oct 4;19(19):4300. doi: 10.3390/s19194300.
Cobalt-rich manganese crusts (CRCs) are important as a potential mineral source that could occur throughout the Pacific on seamounts, ridges, and plateaus. We built a prototype parametric acoustic probe to complete the task of thickness measurements to estimate the volumetric distribution of deep-sea mineral. The prototype is designed with dual-channels for receiving the primary and secondary signal, which lays a foundation for improving the thickness extraction algorithm. Considering that the signal quality is degraded by the system interference and ambient noise, some improvements to the algorithm are proposed by including the wavelet-based envelope extraction method and the adaptive estimation strategy based on the dual-channel information. Additionally, wavelet regression is applied to reduce the measuring noise assuming that the CRCs have local thickness invariability. The algorithm is suitable for the CRCs with the structure of the multilayers at the top surface and one single layer at the bottom surface. A laboratory experiment is performed to validate the effectiveness of the algorithm. The experiments carried out on the China Ocean 51th voyage in the Western Pacific Ocean on Aug 30, 2018, are described and the data obtained by using the stationary measurement are processed to validate the design of the prototype.
富钴结壳是一种重要的潜在矿产资源，可能存在于太平洋中的海山、海脊和高原上。我们构建了一个原型参数声波探头，以完成厚度测量任务，从而估计深海矿物的体积分布。该原型设计有双通道，用于接收主信号和次信号，这为改进厚度提取算法奠定了基础。考虑到系统干扰和环境噪声会降低信号质量，我们通过引入基于小波的包络提取方法和基于双通道信息的自适应估计策略，对算法进行了一些改进。此外，我们还应用小波回归来减少测量噪声，假设富钴结壳的顶层具有局部厚度不变性。该算法适用于顶层具有多层结构、底层具有单层结构的富钴结壳。我们进行了实验室实验来验证算法的有效性。实验是在中国海洋第 51 航次（2018 年 8 月 30 日）期间的西太平洋进行的，并对使用固定测量获得的数据进行了处理，以验证原型的设计。
