Anti-noise and denoising performance of global rainbow processing

This study simulated and experimentally evaluates the effect of signal noise of 5-60 dB on the inversion accuracy of the global rainbow signals of droplets with three typical size distributions (normal, lognormal, and bimodal normal), using a local minimum-based algorithm for parameter retrieval and empirical mode decomposition for denoising. For the simulated noise-free global rainbow signals of droplets with normal size distributions, the inversion algorithm has the highest accuracy, with the maximum relative error of droplet mean diameter D and the maximum absolute error of refractive index n being only 0.34% and 1.3 x 10 -5 . The empirical mode decomposition provides the best denoising and stability when preprocessing global rainbow signals of bimodal-normal size distributed droplets, reducing the errors of D and n from 51.4%, 9 x 10 -4 to 7.9%, 2.4 x 10 -4 even at a signal-to-noise ratio of 5 dB. Experiments were conducted based on a typical global rainbow measurement system. The errors of D and the n retrieved before and after denoising the noisy experimental signal are less than 5.2%, 1.4 x 10 -4 and 2.4%, 0.51 x10 -4 respectively. Experimental results verify the feasibility and effectiveness of the noisy global rainbow processing procedures consisting of an original inversion algorithm and EMD denoising. (c) 2023 Elsevier Ltd. All rights reserved.