Advances in Extraction of Signal From Ground Motion Time Histories Using Time-Frequency Analysis

Time-frequency representation and spectral features extraction from a digitally recorded ground motion time history of an earthquake is cornerstone in earthquake engineering signal processing and interpretation. Recently developed time-frequency analysis (TFA) techniques are one of the most suitable techniques for the spectral estimation of signals whose frequency content varies with time. The most often used TFA techniques are short-term Fourier transform, Gabor transform, wavelet transform, Wigner-Ville distribution, Choi-William distribution, and cone shape distribution. The spectrograms of TFA reveal better spectral estimation in time-frequency domain and hence recommended to estimate local frequencies, dominate frequency and their incident time. Moreover, the time of occurrence of frequency component corresponding to maximum energy burst as well as its variation with time can also be identified. Results obtained from TFA techniques shows better picture of the spectral content in the data than the other conventional techniques.