Ocean Turbulence Denoising and Analysis Using a Novel EMD-Based Denoising Method

Abstract

Ocean turbulence measurement in the wild sea has contributed significantly to improving our understanding of ocean mixing processes. Restricted by observation instruments and methods, the measured turbulence signal contains much information about the marine energy evolution mixed with a large amount of noise. Aiming at eliminating noise in deep sea exploration, a novel EMD-based (empirical mode decomposition) denoising method was designed. In this method, the collected ocean turbulence signal is first decomposed using EMD algorithm to obtain the intrinsic mode functions (IMFs). Then, the correlation coefficient between each IMF and the raw turbulence shear as well as the accelerations signal is calculated, which is taken as vibration reference signal. Finally, search for the proper IMF that has the following features (i) the correlation coefficient with the raw shear is larger than that with the accelerations signal; (ii) maximum difference exists between two adjacent correlation coefficients with the accelerations. IMFs that have these features are searched for signal reconstruction to realize the denoising of non-stationary turbulence. Turbulence signals collected with a self-designed autonomous reciprocating turbulence observation profiler (ARTP) deployed in the South China Sea (SCS) are used to validate the effectiveness and feasibility of the novel denoising method. Through comparison with the Nasmyth theoretical spectrum, the results show that the denoising method can not only effectively remove the noise component, but also maintain the detail characteristics of the effective turbulence signal under high noise, which offers a good theoretical foundation for the analysis of the ocean turbulent characteristics and energy evolution.

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Complex Background Removal Method for Video of an Inclined Cable Based on UAV Detection of Structural Vibration Frequencies

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