Acta Optica Sinica, Volume. 44, Issue 16, 1612001(2024)

Method of Particle Field Reconstruction in Light Field Particle Image Velocimetry Based on Deep Residual Neural Networks

Mengxi Fu1, Xiaoyu Zhu1、**, Liang Zhang2, and Chuanlong Xu1、*
Author Affiliations
  • 1National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, Jiangsu , China
  • 2Basic & Applied Research Center, Aero Engine Academy of China, Beijing 101304, China
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    References(27)

    [5] Li X H, Wang H W, Huang Z et al. Research advances of tomographic particle image velocimetry[J]. Journal of Experiments in Fluid Mechanics, 35, 86-96(2021).

    [13] Atkinson C H, Soria J. Algebraic reconstruction techniques for tomographic particle image velocimetry[C](2007).

    [19] Zhu X Y, Zhang B, Li J et al. Reconstruction of tracer particle distribution in light field PIV using pre-recognition-based SART algorithm[J]. Journal of Engineering Thermophysics, 41, 1445-1451(2020).

    [25] Jia T. A study of common optimization algorithms for deep learning[J]. Information Technology and Network Security, 38, 42-46(2019).

    [26] Liu Y F, Zhang J R. Research advances in deep neural networks learning rate strategies[J]. Control and Decision, 38, 2444-2460(2023).

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    Mengxi Fu, Xiaoyu Zhu, Liang Zhang, Chuanlong Xu. Method of Particle Field Reconstruction in Light Field Particle Image Velocimetry Based on Deep Residual Neural Networks[J]. Acta Optica Sinica, 2024, 44(16): 1612001

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Mar. 11, 2024

    Accepted: Apr. 16, 2024

    Published Online: Jul. 17, 2024

    The Author Email: Zhu Xiaoyu (zhuxiaoyu@seu.edu.cn), Xu Chuanlong (chuanlongxu@seu.edu.cn)

    DOI:10.3788/AOS240721

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