Improving Quality of Microtremor Data with Application of Empirical Mode Decomposition Method, Case Study: East Tanjung Karang, Bandar Lampung

Abstract

Abstract Microtremor can be used for determining ground dynamical characteristic. We have measured microtremor data in East Tanjung Karang, Bandar Lampung. Collecting proper data in some urban areas like East Tanjung Karang is a difficult work because it produced data with a lot of transient signal caused by many human activities and industrial work. One of method to removed transient signal is Empirical Decomposite Method (EMD). EMD decompose an input signal (in time series) into several intrinsic mode functions (IMF) and a residual function. We made the first synthetic signal contained frequency with 1, 10, 20, and 30 Hz. EMD method was applied to the signal and obtained some Instrinsic Mode Function (IMF). IMF 1 has some frequency peaks that are 10, 20, and 30 Hz with power spectral density (PSD) amplitude 0.2, 0.9, and 1 W/Hz respectively. The second synthetic signal contained same frequency with the first one butbut the amplitude was 1, 1, 10, and 50 m. The results in IMF 1 from the second signal still have some peaks but spectral density in 10 Hz increases from 1 W/Hz (before applied EMD) to ±5 W/Hz (after applied EMD, in IMF 1). We applied EMD method also to Y1, Y2, and Y8 microtremor data. We remove IMF 1 or IMF 2 from the original data. The results are the removed IMF 1 data has less spike or transient signal in microtremor time series, but the removed IMF 2 data did not have significant change from the original microtremor. We sugested that higher IMF number, lower the dominant frequency. IMF cannot be related as a single oscillatory source because the result showed that IMF content more than one frequency peak. Removing IMF 1 produced by EMD method can improving quality of micrtremor data because it remove some transient data. This transient can be related to noise in higher frequency that originated locally. it can also decrease maximum standard deviation of HVSR curve. This study revealed revealed that removed IMF 1 data is has less change for both fundamental frequency and amplification factor than removed IMF 2 data in HVSR Curve.