Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas

Shaffer, Franklin D.

Title: Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas

Abstract

The application relates to particle trajectory recognition from a Centroid Population comprised of Centroids having an (x, y, t) or (x, y, f) coordinate. The method is applicable to visualization and measurement of particle flow fields of high particle. In one embodiment, the centroids are generated from particle images recorded on camera frames. The application encompasses digital computer systems and distribution mediums implementing the method disclosed and is particularly applicable to recognizing trajectories of particles in particle flows of high particle concentration. The method accomplishes trajectory recognition by forming Candidate Trajectory Trees and repeated searches at varying Search Velocities, such that initial search areas are set to a minimum size in order to recognize only the slowest, least accelerating particles which produce higher local concentrations. When a trajectory is recognized, the centroids in that trajectory are removed from consideration in future searches.

Inventors:: Shaffer, Franklin D.

Issue Date:: 2013-03-12

Research Org.:: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1083066

Patent Number(s):: 8391552

Application Number:: 12/765,317

Assignee:: U.S. Department of Energy (Washington, DC)

Patent Classifications (CPCs):: G - PHYSICS G01 - MEASURING G01P - MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK

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G - PHYSICS G01 - MEASURING G01P - MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK
G01P5/001 - {Full-field flow measurement, e.g. determining flow velocity and direction in a whole region at the same time, flow visualisation}
G01P5/20 - using particles entrained by a fluid stream

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Resource Type:: Patent

Country of Publication:: United States

Language:: English

Subject:: 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Citation Formats


                    Shaffer, Franklin D. Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas.  United States: N. p., 2013. 
        Web.

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                    Shaffer, Franklin D. Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas.  United States.

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                    Shaffer, Franklin D. Tue .  
        "Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas".  United States.  https://www.osti.gov/servlets/purl/1083066.

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@article{osti_1083066,

  title        = {Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas},

  author       = {Shaffer, Franklin D.},

  abstractNote = {The application relates to particle trajectory recognition from a Centroid Population comprised of Centroids having an (x, y, t) or (x, y, f) coordinate. The method is applicable to visualization and measurement of particle flow fields of high particle. In one embodiment, the centroids are generated from particle images recorded on camera frames. The application encompasses digital computer systems and distribution mediums implementing the method disclosed and is particularly applicable to recognizing trajectories of particles in particle flows of high particle concentration. The method accomplishes trajectory recognition by forming Candidate Trajectory Trees and repeated searches at varying Search Velocities, such that initial search areas are set to a minimum size in order to recognize only the slowest, least accelerating particles which produce higher local concentrations. When a trajectory is recognized, the centroids in that trajectory are removed from consideration in future searches.},

  doi          = {},

  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2013},

  month        = {3}

}

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Works referenced in this record:

Algorithms for fully automated three-dimensional particle tracking velocimetry
journal, August 1994

Guezennec, Y. G.; Brodkey, R. S.; Trigui, N.
Experiments in Fluids, Vol. 17, Issue 4
https://doi.org/10.1007/BF00203039

Establishing motion correspondence using extended temporal scope
journal, April 2003

Veenman, C. J.; Reinders, M. J. T.; Backer, E.
Artificial Intelligence, Vol. 145, Issue 1-2
https://doi.org/10.1016/S0004-3702(02)00380-6

Multiple cell-particle tracking based on multi-resolution block-matching using genetic algorithm
conference, January 2006

Bhaskar, H.; Kingsland, R. L.; Singh, S.
IET 3rd International Conference MEDSIP 2006. Advances in Medical, Signal and Information Processing
https://doi.org/10.1049/cp:20060375

A review of statistical data association techniques for motion correspondence
journal, February 1993

Cox, Ingemar J.
International Journal of Computer Vision, Vol. 10, Issue 1
https://doi.org/10.1007/BF01440847

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Similar Records

Title: Method of particle trajectory recognition in particle flows of high particle concentration using a candidate trajectory tree process with variable search areas

Abstract

Citation Formats

Algorithms for fully automated three-dimensional particle tracking velocimetry journal, August 1994

Establishing motion correspondence using extended temporal scope journal, April 2003

Multiple cell-particle tracking based on multi-resolution block-matching using genetic algorithm conference, January 2006

A review of statistical data association techniques for motion correspondence journal, February 1993

Algorithms for fully automated three-dimensional particle tracking velocimetry
journal, August 1994

Establishing motion correspondence using extended temporal scope
journal, April 2003

Multiple cell-particle tracking based on multi-resolution block-matching using genetic algorithm
conference, January 2006

A review of statistical data association techniques for motion correspondence
journal, February 1993