Tracking Algorithm
If particle positions are known at two or more successive points in time (see here), this can be used to determine shifts or velocities by means of tracking. In addition to cross correlation based techniques, particle tracking algorithms are also being developed at the institute. Tracking offers advantages for the resolution of small flow structures and strong velocity gradients, as tracking does not require spatial averaging due to the finite evaluation window size as with classic PIV evaluation.
The focus of particle tracking development is on double-pulse algorithms. In contrast to time-resolved tracking algorithms, measurements can also be carried out at high flow velocities. A non-iterative tracking method was developed at the institute, which can reliably determine the displacement of the particles even at high particle densities. The motion patterns of adjacent particles are analyzed to determine the most likely particle movement.
Of course, time-resolved and multi-pulse tracking algorithms are also used, if the possibility of a high-speed or multi-pulse measurement is given.
The focus of particle tracking development is on double-pulse algorithms. In contrast to time-resolved tracking algorithms, measurements can also be carried out at high flow velocities. A non-iterative tracking method was developed at the institute, which can reliably determine the displacement of the particles even at high particle densities. The motion patterns of adjacent particles are analyzed to determine the most likely particle movement.
Of course, time-resolved and multi-pulse tracking algorithms are also used, if the possibility of a high-speed or multi-pulse measurement is given.
Person in charge:
Publications:
-
Cierpka C, Lütke B, Kähler CJ (2013) Higher order multi-frame particle tracking velocimetry. Experiments in Fluids 54:1533
-
Fuchs T, Hain R, Kähler CJ (2017) Non-iterative double-frame 2D/3D particle tracking velocimetry. Experiments in Fluids 58:119