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Using Hilbert–Huang Transform (HHT) to Extract Infrasound Generated by the 2013 Lushan Earthquake in China

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Abstract

We applied the Hilbert–Huang transform (HHT) method to extract the infrasound generated by the 2013 Lushan earthquake and its following aftershocks in China from a nearly continuous infrasound recode made 130 km from the earthquake epicenter. An improved STA/LTA algorithm was adopted for detecting the ambient infrasonic events from the data record. A powerful processing technique for non-stationary signal, the HHT, was applied to extract the significant intrinsic mode functions (IMFs) of the infrasonic signal associated with the earthquakes. The features of the extracted IMFs, such as the dominant frequency, the maximum amplitude and the spectral entropy, were investigated using Hilbert spectral analysis. Regression analysis between the maximum amplitude in the infrasound spectra and the magnitudes of the earthquakes was carried out to verify the source of the infrasound events detected. The results demonstrated that the HHT method could successfully identify the infrasound related to the earthquakes.

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Acknowledgements

This research was supported by the National Basic Research Program (973 Program) (Grant No. 2013CB733200, 2014CB744703), the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 41502293), and Project supported by the Funds for Creative Research Groups of China (Grant No. 41521002). We would like to extend special thanks to Prof. Mauri Mcsaveney for all his valuable suggestions in greatly improving the quality of this paper.

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  1. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology), Chengdu, 610059, Sichuan, People’s Republic of China

    X. Zhu, Q. Xu & H. X. Liu

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  1. X. Zhu
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  2. Q. Xu
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  3. H. X. Liu
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Correspondence to Q. Xu.

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Zhu, X., Xu, Q. & Liu, H.X. Using Hilbert–Huang Transform (HHT) to Extract Infrasound Generated by the 2013 Lushan Earthquake in China. Pure Appl. Geophys. 174, 865–874 (2017). https://doi.org/10.1007/s00024-016-1438-1

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  • DOI: https://doi.org/10.1007/s00024-016-1438-1

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