TY - JOUR
T1 - A complete 3D particle tracking algorithm and its applications to the indoor airflow study
AU - Biwole, Pascal Henry
AU - Yan, Wei
AU - Zhang, Yanhui
AU - Roux, Jean Jacques
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - While most research on particle tracking velocimetry (PTV) is devoted either to 2D flows or to small-scale 3D flows, this paper describes a complete 3D PTV algorithm and some applications to indoor airflow velocity measurements. A particle detection procedure especially adapted to the physical characteristics of neutrally buoyant helium-filled soap bubbles is described. To recover longer trajectories, a temporal tracking algorithm is used based on polynomial regression and including a cross-gap and a forward-backward strategy. In order to increase the measurement area and the number of trajectories, the correspondence problem is addressed by a new procedure involving fundamental matrices from both a three and a two-camera arrangement. 3D reconstruction is done by a least-squares method. Some guidelines are given in terms of camera and light positioning for 3D PTV in large volumes. Applications of the algorithm include Lagrangian tracking in (i) a 3.1 m × 3.1 m × 2.5 m light-gray walled test-room; (ii) a 5.5 m × 3.7 m × 2.4 m black walled test-room; (iii) over a heat source; (iv) inside an experimental aircraft cabin. Results show that the algorithm is capable of tracking more than 1400 tracers in volumes up to 3 m × 3 m × 1.2 m.
AB - While most research on particle tracking velocimetry (PTV) is devoted either to 2D flows or to small-scale 3D flows, this paper describes a complete 3D PTV algorithm and some applications to indoor airflow velocity measurements. A particle detection procedure especially adapted to the physical characteristics of neutrally buoyant helium-filled soap bubbles is described. To recover longer trajectories, a temporal tracking algorithm is used based on polynomial regression and including a cross-gap and a forward-backward strategy. In order to increase the measurement area and the number of trajectories, the correspondence problem is addressed by a new procedure involving fundamental matrices from both a three and a two-camera arrangement. 3D reconstruction is done by a least-squares method. Some guidelines are given in terms of camera and light positioning for 3D PTV in large volumes. Applications of the algorithm include Lagrangian tracking in (i) a 3.1 m × 3.1 m × 2.5 m light-gray walled test-room; (ii) a 5.5 m × 3.7 m × 2.4 m black walled test-room; (iii) over a heat source; (iv) inside an experimental aircraft cabin. Results show that the algorithm is capable of tracking more than 1400 tracers in volumes up to 3 m × 3 m × 1.2 m.
KW - 3D particle tracking velocimetry
KW - Air quality engineering
KW - Airflow measurement
KW - Helium-filled bubbles
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U2 - 10.1088/0957-0233/20/11/115403
DO - 10.1088/0957-0233/20/11/115403
M3 - Article
AN - SCOPUS:72149115961
SN - 0957-0233
VL - 20
JO - Measurement Science and Technology
JF - Measurement Science and Technology
IS - 11
M1 - 115403
ER -