Shape recognition and size measurement of particles in hybrid particle field based on interference technology
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1.Tianjin Key Laboratory of Optoelectronic Detection Technology and System, Tianjin 300387, China;2. School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China[* This work has been supported by the National Natural Science Foundation of China (No.42005066), and the Natural Science Foundation of Tianjin City (No.22JCQNJC01380).

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    Abstract:

    An algorithm that can implement particle shape recognition and size measurement in hybrid particle field is proposed. Based on the defocused images obtained by the interferometric particle imaging (IPI) system, shape recognition of particles can be realized through ResNet50. Two-dimensional (2D) Fourier transform and 2D autocorrelation transform are used to obtain the size of spherical and non-spherical particles, respectively. The shape and size of the particle in hybrid particle field are determined. Numerical simulation and experiment results suggest that the method has good accuracy in measuring the particle size in hybrid particle field.

    Reference
    [1] MAEDA M, KAWAGUCHI T, HISHIDA K. Novel interferometric measurement of size and velocity distributions of spherical particles in fluid flows[J]. Measurement science and technology, 2000, 11(12):13-18.
    [2] CHUANG P Y, SAW E W, SMALL J D, et al. Airborne phase Doppler interferometry for cloud microphysical measurements[J]. Aerosol science and technology, 2008, 42(8):685-703.
    [3] QUEREL A, LEMAITRE P, BRUNEL M, et al. Real-time global interferometric laser imaging for the droplet sizing (ILIDS) algorithm for airborne research[J]. Measurement science and technology, 2009, 21(1):015306.
    [4] LANCE S, BROCK C A, ROGERS D, et al. Water droplet calibration of the cloud droplet probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC[J]. Atmospheric measurement techniques, 2010, 3(6):1683-1706.
    [5] LU Q N, JIN W H, LU T, et al. High-accuracy particle sizing by interferometric particle imaging[J]. Optics communications, 2014, 312:312-318.
    [6] HIRST E, KAYE P H, GREENAWAY R S, et al. Discrimination of micrometre-sized ice and super-cooled droplets in mixed-phase cloud[J]. Atmospheric environment, 2001, 35(1):33-47.
    [7] J P, SCHULZ T J, SHAW R A. Practical methods for automated reconstruction and characterization of particles in digital in-line holograms[J]. Measurement science and technology, 2009, 20(7):075501.
    [8] K?NIG G, ANDERS K, FROHN A. A new light-scattering technique to measure the diameter of periodically generated moving droplets[J]. Journal of aerosol science, 1986, 17(2):157-167.
    [9] BILSKY A V, LOZHKIN Y A, MARKOVICH D M. Interferometric technique for measurement of droplet diameter[J]. Thermophysics and aeromechanics, 2011, 18:1-12.
    [10] GLOVER A R, SKIPPON S M, BOYLE R D. Interferometric laser imaging for droplet sizing:a method for droplet-size measurement in sparse spray systems[J]. Applied optics, 1995, 34(36):8409-8421.
    [11] PAN G, SHAKAL J, LAI W, et al. Simultaneous global size and velocity measurement of droplets and sprays[C]//Proceedings of the 20th ILASS-Europe Meeting, September 4-7, 2005, Orléans, France. Naples:Citeseer:2005, 2:91-96.
    [12] HARDALUPAS Y, SAHU S, TAYLOR A M K P, et al. Simultaneous planar measurement of droplet velocity and size with gas phase velocities in a spray by combined ILIDS and PIV techniques[J]. Experiments in fluids, 2010, 49:417-434.
    [13] ZHANG H X, LI Z H, LI J, et al. Simultaneous shape and size measurements of irregular rough particles by an IPI system with double receivers[J]. Journal of modern optics, 2019, 66(11):1226-1234.
    [14] BRUNEL M, ABAD A, DELESTRE B, et al. Analysis and numerical correction of aberration in interferometric particle imaging[J]. Journal of quantitative spectroscopy and radiative transfer, 2023:108579.
    [15] SUN J L, ZHANG H X, LI J, et al. Hybrid spherical particle field measurement based on interference technology[J]. Measurement science and technology, 2017, 28(3):035204.
    [16] STEPANOV R A, BATALOV V G. Determination of spray droplet size by wavelet analysis of interferometric images[J]. Measurement techniques, 2022, 64(9):718-723.
    [17] BRUNEL M, COETMELLEC S, GRéHAN G, et al. Interferometric out-of-focus imaging simulator for irregular rough particles[J]. Journal of the European optical society-rapid publications, 2014, 9:14008.
    [18] BRUNEL M, SHEN H, CO?TMELLEC S, et al. Determination of the size of irregular particles using interferometric out-of-focus imaging[J]. International journal of optics, 2014, 2014:1-8.
    [19] BRUNEL M, RUIZ S G, JACQUOT J, et al. On the morphology of irregular rough particles from the analysis of speckle-like interferometric out-of-focus images[J]. Optics communications, 2015, 338:193-198.
    [20] KIELAR J J, WU Y, CO?TMELLEC S, et al. Size determination of mixed liquid and frozen water droplets using interferometric out-of-focus imaging[J]. Journal of quantitative spectroscopy and radiative transfer, 2016, 178:108-116.
    [21] KIELAR J J, LEMAITRE P, GOBIN C, et al. Simultaneous interferometric in-focus and out-of-focus imaging of ice crystals[J]. Optics communications, 2016, 372:185-195.
    [22] WU X C, SHI L L, LIN Z M, et al. Dual-beam interferometric particle imaging for size and shape characterization of irregular coal micro-particle:validation with digital inline holography[J]. Journal of quantitative spectroscopy and radiative transfer, 2020, 241:106728.
    [23] WU Y C, GONG Y, SHI L, et al. Backward interferometric speckle imaging for evaluating size and morphology of irregular coal particles[J]. Optics communications, 2021, 491:126957.
    [24] ZHANG H X, ZHAI M R, SUN J L, et al. Discrimination between spheres and spheroids in a detection system for single particles based on polarization characteristics[J]. Journal of quantitative spectroscopy and radiative transfer, 2017, 187:62-75.
    [25] POLAT ?, POLAT A, EKICI T. Automatic classification of volcanic rocks from thin section images using transfer learning networks[J]. Neural computing and applications, 2021, 33(18):11531-11540.
    [26] SHAFIQ M, GU Z. Deep residual learning for image recognition:a survey[J]. Applied sciences, 2022, 12(18):8972.
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SUN Jinlu, QIU Yue, WU Yuhang, ZHAO Dan, MIAO Changyun. Shape recognition and size measurement of particles in hybrid particle field based on interference technology[J]. Optoelectronics Letters,2024,20(8):472-476

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History
  • Received:October 17,2023
  • Revised:March 05,2024
  • Online: July 24,2024
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