Applications of the Hilbert-Huang Transform to Microtremor Data Analysis Enhancement

Abstract eng:
In this paper we discuss the use of the Hilbert-Huang transform (HHT) to enhance the time-frequency analysis of microtremor measurements. HHT is a powerful algorithm that combines the process of empirical mode decomposition (EMD) and the Hilbert transform to compose the Hilbert-Huang spectrum that contains the time-frequency information of the recorded signals. HHT is essentially an empirical algorithm and does not require the signals to be linear or stationary. HHT is advantageous to analyzing microtremor data, since observed microtremors are commonly contaminated by non-stationary transient noises close to the recording instruments. This is especially true when microtremors are measured in an urban environment. In this paper, using HHT we present the enhancement of the microtremor data analysis by 1) eliminating the unwanted transient component from microtremor data with EMD analysis by using only the coherent portion of the data to carry out the widely used horizontal to vertical spectral ratio (H/V) method; and 2) enhancing the H/V analysis by using the Hilbert-Huang spectrum (HHS). Application of the proposed approach to a microtremor field dataset acquired in metropolitan Beijing area demonstrated the efficacy of this procedure. This project is supported by Ministry of Science and Technology of China with Project No. 2006DFA21650 and the Institute of Earthquake Science (Project No. 0207690229).

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