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Restoration of clipped seismic waveforms using projection onto convex sets method

The seismic waveforms would be clipped when the amplitude exceeds the upper-limit dynamic range of seismometer. Clipped waveforms are typically assumed not useful and seldom used in waveform-based research. Here, we assume the clipped components of the waveform share the same frequency content with...

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Autores principales: Zhang, Jinhai, Hao, Jinlai, Zhao, Xu, Wang, Shuqin, Zhao, Lianfeng, Wang, Weimin, Yao, Zhenxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5155270/
https://www.ncbi.nlm.nih.gov/pubmed/27966618
http://dx.doi.org/10.1038/srep39056
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author Zhang, Jinhai
Hao, Jinlai
Zhao, Xu
Wang, Shuqin
Zhao, Lianfeng
Wang, Weimin
Yao, Zhenxing
author_facet Zhang, Jinhai
Hao, Jinlai
Zhao, Xu
Wang, Shuqin
Zhao, Lianfeng
Wang, Weimin
Yao, Zhenxing
author_sort Zhang, Jinhai
collection PubMed
description The seismic waveforms would be clipped when the amplitude exceeds the upper-limit dynamic range of seismometer. Clipped waveforms are typically assumed not useful and seldom used in waveform-based research. Here, we assume the clipped components of the waveform share the same frequency content with the un-clipped components. We leverage this similarity to convert clipped waveforms to true waveforms by iteratively reconstructing the frequency spectrum using the projection onto convex sets method. Using artificially clipped data we find that statistically the restoration error is ~1% and ~5% when clipped at 70% and 40% peak amplitude, respectively. We verify our method using real data recorded at co-located seismometers that have different gain controls, one set to record large amplitudes on scale and the other set to record low amplitudes on scale. Using our restoration method we recover 87 out of 93 clipped broadband records from the 2013 Mw6.6 Lushan earthquake. Estimating that we recover 20 clipped waveforms for each M5.0+ earthquake, so for the ~1,500 M5.0+ events that occur each year we could restore ~30,000 clipped waveforms each year, which would greatly enhance useable waveform data archives. These restored waveform data would also improve the azimuthal station coverage and spatial footprint.
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spelling pubmed-51552702016-12-20 Restoration of clipped seismic waveforms using projection onto convex sets method Zhang, Jinhai Hao, Jinlai Zhao, Xu Wang, Shuqin Zhao, Lianfeng Wang, Weimin Yao, Zhenxing Sci Rep Article The seismic waveforms would be clipped when the amplitude exceeds the upper-limit dynamic range of seismometer. Clipped waveforms are typically assumed not useful and seldom used in waveform-based research. Here, we assume the clipped components of the waveform share the same frequency content with the un-clipped components. We leverage this similarity to convert clipped waveforms to true waveforms by iteratively reconstructing the frequency spectrum using the projection onto convex sets method. Using artificially clipped data we find that statistically the restoration error is ~1% and ~5% when clipped at 70% and 40% peak amplitude, respectively. We verify our method using real data recorded at co-located seismometers that have different gain controls, one set to record large amplitudes on scale and the other set to record low amplitudes on scale. Using our restoration method we recover 87 out of 93 clipped broadband records from the 2013 Mw6.6 Lushan earthquake. Estimating that we recover 20 clipped waveforms for each M5.0+ earthquake, so for the ~1,500 M5.0+ events that occur each year we could restore ~30,000 clipped waveforms each year, which would greatly enhance useable waveform data archives. These restored waveform data would also improve the azimuthal station coverage and spatial footprint. Nature Publishing Group 2016-12-14 /pmc/articles/PMC5155270/ /pubmed/27966618 http://dx.doi.org/10.1038/srep39056 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Zhang, Jinhai
Hao, Jinlai
Zhao, Xu
Wang, Shuqin
Zhao, Lianfeng
Wang, Weimin
Yao, Zhenxing
Restoration of clipped seismic waveforms using projection onto convex sets method
title Restoration of clipped seismic waveforms using projection onto convex sets method
title_full Restoration of clipped seismic waveforms using projection onto convex sets method
title_fullStr Restoration of clipped seismic waveforms using projection onto convex sets method
title_full_unstemmed Restoration of clipped seismic waveforms using projection onto convex sets method
title_short Restoration of clipped seismic waveforms using projection onto convex sets method
title_sort restoration of clipped seismic waveforms using projection onto convex sets method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5155270/
https://www.ncbi.nlm.nih.gov/pubmed/27966618
http://dx.doi.org/10.1038/srep39056
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