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首页> 外文期刊>Journal of Robotic Systems >Estimation of Volumetric Oxygen Concentration in a Marine Environment with an Autonomous Underwater Vehicle
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Estimation of Volumetric Oxygen Concentration in a Marine Environment with an Autonomous Underwater Vehicle

机译：水下自动航行器在海洋环境中的体积氧浓度估算

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摘要

Dissolved oxygen (DO) concentration is a key indicator of the health and productivity of an aquatic ecosystem. This paper presents a new method for high-resolution characterization of DO as a function of both space and time. The implementation of a new oxygen optode in an Iver2 autonomous underwater vehicle (AUV) is described, which enables the system to measure both absolute oxygen concentration and percentage saturation. Also described are details of AUV missions in Hopavagen Bay, Norway, which consisted of a series of repeated undulating lawnmower patterns that covered the bay. Through offline postprocessing of data, sensor characteristic models were developed, as well as a 3D lattice time series model. The model was constructed by estimating DO at each 3D lattice node location using a 1D Kalman filter that fused local measurements obtained with the AUV. By repeating model construction for several missions that spanned 24 h, estimates of DO as a function of space and time were calculated. Results demonstrated (1) the AUVs ability to repeatedly gather high-spatial-resolution data (2) significant spatial and temporal variation in DO in the water body investigated, and (3) that a 3D model of DO provides better estimates of total DO in a volume than extrapolating from only a single 2D plane. Given the importance of oxygen within an ecosystem, this new method of estimating the quantity of DO per volume has the potential to become a reliable test for the health of an underwater ecosystem. Also, it can be refined for detecting and monitoring a range of soluble gases and dispersed particles in aquatic environments, such as dissolved O_2 and CO_2 around production facilities such as fish farms, or dispersed hydrocarbons and other pollutants in fragile ecosystems.
机译：溶解氧（DO）浓度是水生生态系统健康和生产力的关键指标。本文提出了一种根据空间和时间对DO进行高分辨率表征的新方法。描述了在Iver2自主水下航行器（AUV）中实施新的氧传感器的方法，该方法使系统能够测量绝对氧浓度和饱和度百分比。还介绍了AUV在挪威霍帕瓦根湾的飞行任务的详细信息，该任务由覆盖海湾的一系列重复起伏的割草机图案组成。通过对数据进行离线后处理，开发了传感器特性模型以及3D晶格时间序列模型。该模型是通过使用1D Kalman滤波器估计每个3D晶格节点位置处的DO来构建的，该滤波器融合了AUV获得的局部测量值。通过对跨越24小时的多个任务重复模型构建，可以计算出DO随时间和空间变化的估计值。结果表明（1）AUV能够重复收集高空间分辨率数据（2）被调查水体中DO的显着时空变化，以及（3）DO的3D模型可以更好地估算水体中的总DO比仅从单个2D平面外推的体积大。考虑到氧气在生态系统中的重要性，这种估算每体积DO数量的新方法有可能成为对水下生态系统健康进行可靠测试的方法。此外，它还可以进行精炼，以检测和监视水生环境中的一系列可溶性气体和分散颗粒，例如生产设施（如养鱼场）周围的溶解的O_2和CO_2，或脆弱的生态系统中的分散的碳氢化合物和其他污染物。

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  • 来源
    《Journal of Robotic Systems》 |2013年第1期|1-16|共16页
  • 作者

    Christopher M. Clark; Kasper Hancke; Alex Xydes; Kevin Hall; Frank Schreiber; Jessica Klemme; Jane Lehr; Mark Moline;

  • 作者单位

    Department of Computer Science, California Polytechnic State University, San Luis Obispo, California 93407;

    Institute of Biology and Nordic Center for Earth Evolution, University of Southern Denmark, Odense, Denmark;

    Department of Computer Science, California Polytechnic State University, San Luis Obispo, California 93407;

    Department of Computer Science, California Polytechnic State University, San Luis Obispo, California 93407;

    Department of Computer Science, California Polytechnic State University, San Luis Obispo, California 93407;

    Department of Computer Science, California Polytechnic State University, San Luis Obispo, California 93407;

    Department of Ethnic Studies, California Polytechnic State University, San Luis Obispo, California 93407;

    Department of Biological Sciences, California Polytechnic State University, San Luis Obispo, California 93407;

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