skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images

Abstract

Quantitative understanding of the physics of dust or granular matter transport significantly impacts several aspects of burning plasma science and technology. Here, this work takes machine vision techniques popular in robotics and self-driving cars and applies them to identification and analysis of microparticles generated from exploding wires. Using only the image frames and knowledge of the intrinsic properties of the cameras, a Python code was written to identify the particles, automatically calibrate the relative image positions, and extract trajectory data. After identifying approximately 50 particles based on the timing of secondary particle explosions, the eight point and random sample consensus algorithms were used to determine the geometric correlation between the cameras. Over 100 particle matches were found between the two camera views. These correlated trajectories were used in subsequent 3D track reconstruction and analysis of the physics behind the particle motion. The 3D reconstruction resulted in accurate positioning of the particles with respect to the experimental setup. The particle motion was consistent with the effects of a 1 g gravitational field modified by drag forces. Lastly, the methods and analyses presented here can be used in many facets of high temperature plasma diagnostics.

Authors:
 [1]; ORCiD logo [2];  [1]
  1. Univ. of Illinois at Urbana–Champaign, Urbana, IL (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC). Fusion Energy Sciences (FES) (SC-24)
OSTI Identifier:
1565813
Report Number(s):
LA-UR-19-29177
Journal ID: ISSN 0034-6748; TRN: US2000902
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Review of Scientific Instruments
Additional Journal Information:
Journal Volume: 89; Journal Issue: 10; Journal ID: ISSN 0034-6748
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; Magnetic Fusion Energy

Citation Formats

Szott, Matthew, Wang, Zhehui, and Ruzic, David N. Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images. United States: N. p., 2018. Web. doi:10.1063/1.5039373.
Szott, Matthew, Wang, Zhehui, & Ruzic, David N. Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images. United States. doi:10.1063/1.5039373.
Szott, Matthew, Wang, Zhehui, and Ruzic, David N. Wed . "Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images". United States. doi:10.1063/1.5039373. https://www.osti.gov/servlets/purl/1565813.
@article{osti_1565813,
title = {Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images},
author = {Szott, Matthew and Wang, Zhehui and Ruzic, David N.},
abstractNote = {Quantitative understanding of the physics of dust or granular matter transport significantly impacts several aspects of burning plasma science and technology. Here, this work takes machine vision techniques popular in robotics and self-driving cars and applies them to identification and analysis of microparticles generated from exploding wires. Using only the image frames and knowledge of the intrinsic properties of the cameras, a Python code was written to identify the particles, automatically calibrate the relative image positions, and extract trajectory data. After identifying approximately 50 particles based on the timing of secondary particle explosions, the eight point and random sample consensus algorithms were used to determine the geometric correlation between the cameras. Over 100 particle matches were found between the two camera views. These correlated trajectories were used in subsequent 3D track reconstruction and analysis of the physics behind the particle motion. The 3D reconstruction resulted in accurate positioning of the particles with respect to the experimental setup. The particle motion was consistent with the effects of a 1 g gravitational field modified by drag forces. Lastly, the methods and analyses presented here can be used in many facets of high temperature plasma diagnostics.},
doi = {10.1063/1.5039373},
journal = {Review of Scientific Instruments},
number = 10,
volume = 89,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

Figures / Tables:

FIG. 1 FIG. 1: Stereo images of the supporting leads and the wire immediately prior to disintegration. This support was removed via image subtraction during particle identification and analysis.

Save / Share:

Works referenced in this record:

First observations of ELM triggering by injected lithium granules in EAST
journal, September 2013


Three-dimensional reconstruction of dust particle trajectories in the NSTX
journal, October 2008

  • Boeglin, W. U.; Roquemore, A. L.; Maqueda, R.
  • Review of Scientific Instruments, Vol. 79, Issue 10
  • DOI: 10.1063/1.2965001

Methods of Digital Video Microscopy for Colloidal Studies
journal, April 1996

  • Crocker, John C.; Grier, David G.
  • Journal of Colloid and Interface Science, Vol. 179, Issue 1
  • DOI: 10.1006/jcis.1996.0217

In defense of the eight-point algorithm
journal, June 1997

  • Hartley, R. I.
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, Issue 6
  • DOI: 10.1109/34.601246

Dust trajectories and diagnostic applications beyond strongly coupled dusty plasmas
journal, October 2007

  • Wang, Zhehui; Ticoş, Cătălin M.; Wurden, Glen A.
  • Physics of Plasmas, Vol. 14, Issue 10
  • DOI: 10.1063/1.2778416

Imaging system for hypervelocity dust injection diagnostic on NSTX
journal, October 2006

  • Dorf, L. A.; Roquemore, A. L.; Wurden, G. A.
  • Review of Scientific Instruments, Vol. 77, Issue 10
  • DOI: 10.1063/1.2336790

Plasma dragged microparticles as a method to measure plasma flows
journal, October 2006

  • Ticoş, Cătălin M.; Wang, Zhehui; Delzanno, Gian Luca
  • Physics of Plasmas, Vol. 13, Issue 10
  • DOI: 10.1063/1.2356316

Four-dimensional (4D) tracking of high-temperature microparticles
journal, July 2016

  • Wang, Zhehui; Liu, Q.; Waganaar, W.
  • Review of Scientific Instruments, Vol. 87, Issue 11
  • DOI: 10.1063/1.4955280

Fiji: an open-source platform for biological-image analysis
journal, June 2012

  • Schindelin, Johannes; Arganda-Carreras, Ignacio; Frise, Erwin
  • Nature Methods, Vol. 9, Issue 7
  • DOI: 10.1038/nmeth.2019

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
journal, June 1981

  • Fischler, Martin A.; Bolles, Robert C.
  • Communications of the ACM, Vol. 24, Issue 6
  • DOI: 10.1145/358669.358692

    Works referencing / citing this record:

    Kinetic effects in a plasma crystal induced by an external electron beam
    journal, April 2019

    • Ticoş, Cătălin M.; Ticoş, Dorina; Williams, Jeremiah D.
    • Physics of Plasmas, Vol. 26, Issue 4
    • DOI: 10.1063/1.5092749

      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.