Particle Tracking Velocimetry Using the Genetic Algorithm

Article type: Research Article

Authors: Ohmi, K. | Panday, S. P.

Affiliations: Faculty of Engineering, Osaka Sangyo University, Daito-shi, Osaka 5748530, Japan. Tel 072-875-3001 Fax 072-870-1401 E-mail: ohmi@ise.osaka-sandai.ac.jp | Graduate Student of Faculty of Engineering, Osaka Sangyo University, Daito-shi, Osaka 5748530, Japan. Tel 072-875-3001 Fax 072-870-1401 E-mail: sanjeeb@wind.ise.osaka-sandai.ac.jp

Abstract: A new concept genetic algorithm (GA) has been implemented and tested for the use in the 2-D and 3-D Particle Tracking Velocimetry (PTV). The algorithm is applicable to particle images with larger (greater than 2000) number of particles without losing the excellent accuracy in the particle matching results. This is mainly due to a new fitness function as well as unique genetic operations devised especially for the purpose of particle matching problem. The new fitness function is based on the relaxation of movement of a group of particles and is particularly suited for an increased density of particle images. The unique genetic operations give rise to the concentration of more fit genes in the forward part of the gene strings where the crossover and mutation processes are suppressed. The new algorithm also profits from the new genetic encoding scheme which can deal with the loss-of-pair particles (i.e., those particles which exist in one frame but do not have their matching pair in the other frame), a typical problem in the real image particle tracking velocimetry. In the present study, the new method is tested with 2-D and 3-D synthetic as well as real particle images with a large number of particles.

Keywords: Particle tracking velocimetry, 2-D PTV, 3-D PTV, Particle matching problem, Genetic algorithm

Journal: Journal of Visualization, vol. 12, no. 3, pp. 217-232, 2009