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Keywords = single-point laser-induced fluorescence (LIF)

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19 pages, 6722 KiB  
Article
Transition Routes of Electrokinetic Flow in a Divergent Microchannel with Bending Walls
by Yanxia Shi, Ming Zeng, Haoxin Bai, Shuangshuang Meng, Chen Zhang, Xiaoqiang Feng, Ce Zhang, Kaige Wang and Wei Zhao
Micromachines 2023, 14(2), 474; https://doi.org/10.3390/mi14020474 - 18 Feb 2023
Cited by 4 | Viewed by 2036
Abstract
Electrokinetic flow can be generated as a highly coupled phenomenon among velocity fields, electric conductivity fields, and electric fields. It can exhibit different responses to AC electric fields in different frequency regimes, according to different instability/receptivity mechanisms. In this investigation, by both flow [...] Read more.
Electrokinetic flow can be generated as a highly coupled phenomenon among velocity fields, electric conductivity fields, and electric fields. It can exhibit different responses to AC electric fields in different frequency regimes, according to different instability/receptivity mechanisms. In this investigation, by both flow visualization and single-point laser-induced fluorescence (LIF) method, the response of AC electrokinetic flow and the transition routes towards chaos and turbulence have been experimentally investigated. It is found, when the AC frequency ff>30 Hz, the interface responds at both the neutral frequency of the basic flow and the AC frequency. However, when ff30 Hz, the interface responds only at the neutral frequency of the basic flow. Both periodic doubling and subcritical bifurcations have been observed in the transition of AC electrokinetic flow. We hope the current investigation can promote our current understanding of the ultrafast transition process of electrokinetic flow from laminar state to turbulence. Full article
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18 pages, 6333 KiB  
Article
Active 3D Imaging of Vegetation Based on Multi-Wavelength Fluorescence LiDAR
by Xingmin Zhao, Shuo Shi, Jian Yang, Wei Gong, Jia Sun, Biwu Chen, Kuanghui Guo and Bowen Chen
Sensors 2020, 20(3), 935; https://doi.org/10.3390/s20030935 - 10 Feb 2020
Cited by 18 | Viewed by 4461
Abstract
Comprehensive and accurate vegetation monitoring is required in forestry and agricultural applications. The optical remote sensing method could be a solution. However, the traditional light detection and ranging (LiDAR) scans a surface to create point clouds and provide only 3D-state information. Active laser-induced [...] Read more.
Comprehensive and accurate vegetation monitoring is required in forestry and agricultural applications. The optical remote sensing method could be a solution. However, the traditional light detection and ranging (LiDAR) scans a surface to create point clouds and provide only 3D-state information. Active laser-induced fluorescence (LIF) only measures the photosynthesis and biochemical status of vegetation and lacks information about spatial structures. In this work, we present a new Multi-Wavelength Fluorescence LiDAR (MWFL) system. The system extended the multi-channel fluorescence detection of LIF on the basis of the LiDAR scanning and ranging mechanism. Based on the principle prototype of the MWFL system, we carried out vegetation-monitoring experiments in the laboratory. The results showed that MWFL simultaneously acquires the 3D spatial structure and physiological states for precision vegetation monitoring. Laboratory experiments on interior scenes verified the system’s performance. Fluorescence point cloud classification results were evaluated at four wavelengths and by comparing them with normal vectors, to assess the MWFL system capabilities. The overall classification accuracy and Kappa coefficient increased from 70.7% and 0.17 at the single wavelength to 88.9% and 0.75 at four wavelengths. The overall classification accuracy and Kappa coefficient improved from 76.2% and 0.29 at the normal vectors to 92.5% and 0.84 at the normal vectors with four wavelengths. The study demonstrated that active 3D fluorescence imaging of vegetation based on the MWFL system has a great application potential in the field of remote sensing detection and vegetation monitoring. Full article
(This article belongs to the Special Issue Imaging Sensors and Applications)
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