Underwater large-area high resolution monitoring by Distributed Optical Fibre Acoustic Sensors

分布式光纤声传感器水下大面积高分辨率监测

• 批准号: NE/T005890/1
• 负责人: Gilberto Brambilla
• 金额: $ 30.82万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FT005890%2F1
• 关键词: Underwater; large; area; resolution; monitoring; Underwater; large; area; resolution; monitoring

A variety of problems in environmental science involve determining the location and time of origin of acoustic or seismic signals. Various marine species including whales may be tracked by triangulating their vocalisations. Active faulting and magma intrusion beneath the seabed may be located by tracking the associated seismicity. Similar approaches may be used to track gas escaping through the seabed, which is now important in the context of sub-seabed carbon capture and storage (CCS), where it is important to verify that stored gas is not escaping back to the seabed. Currently in all of these applications, sound is detected by an array comprising a relatively small number (typically a few to a few tens) of point detectors, that may be towed or (more commonly) deployed on or near the seabed. Optical-fibre Distributed Acoustic Sensing (DAS) is a new technology that allows acoustic measurements to be made at an unlimited number of locations along a fibre, with a trade-off between measurement density and sensitivity. The fibre can also be manufactured relatively cheaply and at today's market prices telecom fibres coated with a polymer layer costs less than 1p per metre. Even with fibres are engineered with additional armouring to resist the weight of vehicles passing on them, their cost only increases to a few pounds per metre. Thus, this technology has the potential to locate and quantify sound sources in and beneath the ocean with much greater accuracy, and potentially much lower cost, than hitherto possible. Deployment of this technology in the ocean is limited by poor understanding of the coupling between acoustic waves and a DAS fibre within the water column or resting on the ocean floor. In this feasibility study, we propose to use a DAS system manufactured in Southampton, which can be specifically tailored for the monitoring of underwater acoustic signals and operate at frequencies commonly not used in commercial systems, to reconstruct a 3D map of acoustic fields in the ocean. Our approach will be to firstly determine the relationship between an acoustic signal in the ocean and the signal generated in the DAS fibre laid on the seabed. We will then determine a 3D model of the acoustic sources from the sensing enabled by the seabed fibre. Our next step is to then determine how to adapt and apply DAS technology so that it is suitable for detecting, locating and quantifying acoustic noise sources in the ocean. We will do some simple tests of the new technology in test tanks and in the marine environment (a dock within the port of Southampton). This project will build on research currently funded by NERC, EPSRC, Carbon Trust, the Royal Academy of Engineering and the Royal Society to provide a novel distributed acoustic sensor network capable of high-resolution 3D detection and analysis of underwater acoustic sources

环境科学中的各种问题涉及确定声学或地震信号的起源的位置和时间。可以通过三角剖分来跟踪包括鲸鱼在内的各种海洋物种。通过跟踪相关的地震性，可以找到海底下方的主动断层和岩浆入侵。可以使用类似的方法来跟踪海床的气体逃脱，这在次海碳捕获和存储（CCS）的背景下很重要，在这里，重要的是要验证储存的气体不会逃回海床很重要。目前，在所有这些应用中，声音都是通过一个相对较少数字（通常是几至几十个）的示波器来检测的，可以拖曳或（更常见）在海床上或附近部署。光纤分布式声感应（DAS）是一项新技术，允许在沿着光纤数量的位置进行声学测量，并在测量密度和灵敏度之间进行权衡。该纤维也可以相对便宜地制造，在当今的市场价格上，电信纤维涂有聚合物层的成本低于每米1便士。即使纤维进行了额外的装甲设计，以抵抗传递它们的车辆的重量，它们的成本也只会增加到每米几磅。因此，这项技术具有比迄今为止可能的更高的精度，可能要低得多的成本来定位和量化海洋中和下方的声源。这项技术在海洋中的部署受到对声波与水柱内的DAS纤维之间耦合的了解不足或在海底休息的限制。在这项可行性研究中，我们建议使用在南安普敦制造的DAS系统，该系统可以专门针对监测水下声学信号进行监测，并以商业系统中通常不使用的频率进行操作，以重建海洋中声道的3D图。我们的方法是首先确定海洋中的声学信号与铺设在海床上的DAS纤维中产生的信号之间的关系。然后，我们将从海底纤维启用的感应中确定声源的3D模型。我们的下一步是确定如何适应和应用DAS技术，以便它适合于海洋中检测，定位和量化声噪声源。我们将对测试罐和海洋环境（南安普敦港口的码头）中的新技术进行一些简单的测试。该项目将建立在NERC，EPSRC，Carbon Trust，皇家工程学院和皇家学会目前资助的研究的基础上，以提供一种新颖的分布式声学传感器网络，能够高分辨率3D检测和分析水下声学。