Reconstructing irregularly sampled laser Doppler velocimetry signals by using artificial neural networks

Author

Peña, F. López ; Bellas, F. ; Duro, R.J. ; Simó, M. Sánchez

Author_Institution

Escuela Politecnica Superior, Univ. da Coruna, Ferrol

fYear

2003

fDate

8-10 Sept. 2003

Firstpage

99

Lastpage

105

Abstract

The analysis of turbulent flow signals irregularly sampled by a laser Doppler velocimeter is assessed by means of ANNs. This technique has been proven to correctly predict the time evolution of turbulent signals. We are taking advantage of this ability to obtain models of unevenly sampled signals and thus be able to reconstruct and resample them at a regular pace in order to allow for their conventional analysis

Keywords

laser Doppler anemometry; laser velocimeters; laser velocimetry; neural nets; signal reconstruction; signal sampling; turbulence; ANN; artificial neural network; conventional analysis; laser Doppler velocimeter; turbulent flow signals; turbulent signal time evolution; unevenly sampled signals; Artificial neural networks; Laser beams; Laser velocimetry; Light scattering; Linear discriminant analysis; Optical scattering; Particle beams; Particle measurements; Signal analysis; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings of the Second IEEE International Workshop on

Conference_Location

Lviv

Print_ISBN

0-7803-8138-6

Type

conf

DOI

10.1109/IDAACS.2003.1249526

Filename

1249526