Applications of the Empirical Mode Decomposition Method in Speckle Metrology

BERNINI, M. B.; GALIZZI, G. E.; FEDERICO, A; KAUFMANN, G. H.

Alexandroupolis, Grecia

Congreso; XIII International Conference on Experimental Mechanics; 2007

In the last decade, Huang et al. presented a non-linear method called Empirical Mode Decomposition (EMD) for adaptively representing a non-stationary signal as a sum of zero-mean well-behaved fast and slow oscillation empirical modes, which are known as Intrinsic Mode Functions (IMFs). An IMF is a function that satisfies two conditions: (1) in the whole data set, the number of extrema and the number of zero crossings must be either equal or differ at most by one; (2) at any point, the mean values of the envelopes defined by the local maxima and minima are zero. This decomposition is carried out through a sifting algorithm that generates a fully data-driven method, so that no basis functions are fixed in the analysis process. Therefore, the frequency discrimination does not correspond to a predetermined sub-band filtering and the mode selection corresponds to an automatic and adaptive filtering. Consequently, the evaluation of the performance of the EMD method in a given field must be analysed by means of numerical analysis. In addition, the sifting process facilitates the application of the Hilbert transform to each IMF, so that it can be associated to an instantaneous amplitude and frequency obtained by means of the implementation of its analytic signal. This paper shows the application of the EMD method to the reduction of speckle noise in digital speckle pattern interferometry (DSPI) fringes and to the analysis of the activity of dynamic speckle.