Research on Processing of Signals and Images of Critical Heat Flux in Natural Circulation Based on Wavelet Transform and Edge Detection

Abstract:

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Based on the experimental data acquired from natural circulation experiment, critical heat flux (CHF) was detected through applying Fourier transform and wavelet transform firstly. Then, the technology of edge detection was applied in detecting CHF regions under different heating powers from the photos which were taken in experiment. Results showed that wavelet transform could detect the occurrence of CHF much more accurate than Fourier transform. The apply of wavelet transform using of db1 wavelet and edge detection technology using of Canny algorithm could accurately distinguish the singularity of CHF in one-dimensional temperature signal and dry patch regions that represented CHF phenomena in two-dimensional photographs respectively, which can provide a new approach in the analysis of CHF experimental studies of natural circulation.

Info:

Periodical:

Edited by:

Paul P. Lin and Chunliang Zhang

Pages:

2000-2004

DOI:

10.4028/www.scientific.net/AMM.105-107.2000

Citation:

C. Sheng et al., "Research on Processing of Signals and Images of Critical Heat Flux in Natural Circulation Based on Wavelet Transform and Edge Detection", Applied Mechanics and Materials, Vols. 105-107, pp. 2000-2004, 2012

Online since:

September 2011

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$35.00

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