The random ocean waves have a natural tendency to form groups of waves that produced due to the interaction of lower and higher frequency wave components. In this paper Hilbert Huang Transformation is considered, which is the result of the empirical mode decomposition (EMD) and the Hilbert spectral analysis (HSA). HHT uses the EMD method to decompose a signal into socalled intrinsic mode functions, and uses the HSA method to obtain instantaneous frequency data. Using EMD method, any nonstationary data set can be decomposed into a finite and often small number of components, which are intrinsic mode functions (IMF). This decomposition method operating in the time domain is adaptive and highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it can be applied to nonlinear and non stationary processes. This method is applied to the field data collected in the Natural Ocean Engineering Laboratory (NOEL, Reggio Calabria, Italy) and results on the wave groups in crossing sea are discussed.

Analysis of wave groups in crossing seas using Hilbert Huang transformation / Senthilkumar, R; Romolo, A; Fiamma, V; Arena, F; Murali, K. - 116:1(2015), pp. 1042-1049. (Intervento presentato al convegno 8th International Conference on Asian and Pacific coasts (APAC 2015) tenutosi a Madras, India nel 7-10 september) [10.1016/j.proeng.2015.08.341].

Analysis of wave groups in crossing seas using Hilbert Huang transformation

Romolo A;Fiamma V;Arena F;
2015-01-01

Abstract

The random ocean waves have a natural tendency to form groups of waves that produced due to the interaction of lower and higher frequency wave components. In this paper Hilbert Huang Transformation is considered, which is the result of the empirical mode decomposition (EMD) and the Hilbert spectral analysis (HSA). HHT uses the EMD method to decompose a signal into socalled intrinsic mode functions, and uses the HSA method to obtain instantaneous frequency data. Using EMD method, any nonstationary data set can be decomposed into a finite and often small number of components, which are intrinsic mode functions (IMF). This decomposition method operating in the time domain is adaptive and highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it can be applied to nonlinear and non stationary processes. This method is applied to the field data collected in the Natural Ocean Engineering Laboratory (NOEL, Reggio Calabria, Italy) and results on the wave groups in crossing sea are discussed.
2015
EMD; Groupiness factor; HHT; IMF; Wave group
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/13889
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