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

摘要

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 dbl wavelet and edge detection technology using of Canny algorithm could accurately distinguish the singularity of CHF in onedimensional 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.