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Deformation extraction and its analysis based on wavelet transform

Explanation of deformation results is crucial to obtain deformation mechanism. So far, various kinds of math models for modeling or prediction of deformation information are obtained. Each model shows its merit and demerit. For example, Auto Regressive (AR), Moving Average (MA) or ARMA is fit for modeling or prediction, but it is hard to obtain deformation mechanism from it. Wavelet transform that is the result of contemporary mathematics development has shown great role in information extraction and identification. It is used as a tool to deal with deformation extraction and analysis in this paper. Tests have shown that it can be applied to distinguish different components from mixed observation serials. We start from introduction on wavelet transform to some engineering application and analysis. It is known that an observed serial in deformation monitoring is composed of sophisticated components and each represents different contents and is attributed to some acting factors. In this research, regional and engineering deformation observation is employed as inputs for wavelet decomposition; contents from different frequency scales are obtained at different layers. Deformation trend and rapid deformation changes are found from this multiple inspection transformation. Practical examples are given to reveal the feasibility of wavelet decomposition as a useful inspection tool for deformation analysis.