Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2021 Nov 4;21(21):7344. doi: 10.3390/s21217344.
Suspended particles affect the state and vitality of the marine ecosystem. In situ probing and accurately classifying the suspended particles in seawater have an important impact on ecological research and environmental monitoring. Individual measurement of the optical polarization parameters scattered by the suspended particles has been proven to be a powerful tool to classify the particulate compositions in seawater. In previous works, the temporal polarized light pulses are sampled and averaged to evaluate the polarization parameters. In this paper, a method based on dense sampling of polarized light pulses is proposed and the experimental setup is built. The experimental results show that the dense sampling method optimizes the classification and increases the average accuracy by at least 16% than the average method. We demonstrate the feasibility of dense sampling method by classifying the multiple types of particles in mixed suspensions and show its excellent generalization ability by multi-classification of the particles. Additional analysis indicates that the dense sampling method basically takes advantage of the high-quality polarization parameters to optimize the classification performance. The above results suggest that the proposed dense sampling method has the potential to probe the suspended particles in seawater in red-tide early warning, as well as sediment and microplastics monitoring.
悬浮颗粒会影响海洋生态系统的状态和活力。原位探测和准确分类海水中的悬浮颗粒对生态研究和环境监测有重要影响。已经证明，测量悬浮颗粒散射的光学偏振参数的个体测量是对海水中颗粒成分进行分类的有力工具。在以前的工作中，通过对时间偏振光脉冲进行采样和平均来评估偏振参数。本文提出了一种基于偏振光脉冲密集采样的方法，并建立了实验装置。实验结果表明，密集采样方法通过分类优化了分类，平均准确率至少提高了 16%，比平均方法高。我们通过对混合悬浮液中的多种颗粒进行分类来证明密集采样方法的可行性，并通过对颗粒进行多分类来展示其出色的泛化能力。进一步的分析表明，密集采样方法基本利用了高质量的偏振参数来优化分类性能。上述结果表明，所提出的密集采样方法有可能用于赤潮预警、沉积物和微塑料监测等领域中探测海水中的悬浮颗粒。
