Space-spectrum empirical model for unmasking modal components contained into space-time varying data measurements

This paper describes a space-spectrum empirical model for unmasking modal components contained into space-time varying data measurements obtained from interconnected dynamical systems using an empirical biorthogonal representation. The method incorporates frequency domain responses obtained from the application of the complex Fourier analysis to problems of spectral decomposition for space-time varying data sets. In addition, the model provides a frequency band based denoising procedure to effectively reduce the noise level in the data used. This is achieved by extending the empirical orthogonal function analysis of time series to the frequency domain where their fundamental properties are based on the interpretation of pre-selected frequencies contained into the eigenvectors of a cross-spectrum matrix. Without loss of generality, the method is applied to a synthetic example of a spring-mass mechanical system to demonstrate the performance of the decomposition method incorporating frequency domain responses where the details of its practical implementation are described.