Affiliations: Faculty of Engineering, Osaka Sangyo University,
Daito-shi, Osaka 5748530, Japan. Tel 072-875-3001 Fax 072-870-1401 E-mail:
[email protected] | Graduate Student of Faculty of Engineering, Osaka
Sangyo University, Daito-shi, Osaka 5748530, Japan. Tel 072-875-3001 Fax
072-870-1401 E-mail: [email protected]
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.