Application of wavelet theory with denoising to estimate the parameters of an earthquake

In this paper, strong ground mot (SGM) parameters are calculated using discrete wavelet transform (DWT) in different kinds of soils with different magnitudes. The main earthquake record (MER) is divided into approximation and detailed signals using wavelet transform with denoising. The high and low frequencies of MER are separated from each other. Previous studies showed that the approximation signal has the greatest effect on dynamic response and it is very similar to the main signal. Then SGM parameters of the new signal are calculated by DWT decomposition. This process continues over five levels and, in each level, SGM parameters are calculated and compared with the MER and its error percentage is presented. In DWT with the denoising method, the curve becomes softer such that the calculation time reduces. Results show that the error percentage in the first two levels is less than 1% and for the third level, this index is less than 3%. In addition, the reduction percentage of calculation time is 1%, 4%, and 8%, respectively, in the first to third levels. The best result is relative to the third decomposition level in which error value as well as computational time reduction is nearly 3% and 8%.