Author
Listed:
- Guocheng Hao
(China University of Geosciences
Chinese Academy of Sciences
Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems
China University of Geosciences)
- Panpan Wang
(China University of Geosciences
Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems
China University of Geosciences)
- Xiangyun Hu
(China University of Geosciences
Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems)
- Juan Guo
(China University of Geosciences
Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems
China University of Geosciences)
- Guocheng Wang
(Chinese Academy of Sciences)
- Songyuan Tan
(China University of Geosciences
Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems
China University of Geosciences)
Abstract
The Earth's natural pulse electromagnetic field (ENPEMF) signal, is generally considered to be a nonlinear or nonstationary signal received from our instrument, placed on the surface near the source area. To obtain latent information on the ENPEMF signal, this paper employs the time–frequency analysis (TFA) method to get the instantaneous frequency (IF) of the signal. The traditional Data-driven time–frequency analysis (DDTFA) requires to know the initial phase function (IPF) set of the signal, to accomplish the signal decomposition and its IFA. However, it's difficult to observe directly the IPF set of the ENPEMF signal. To acquire accurate time–frequency distribution, an improved DDTFA method was proposed, which adopts differential evolution (DE) to calculate multiple IPF of multi-component non-stationary signals. In this paper, the ENPEMF signal received from the Lushan $${M}_{w}$$ M w 6.6 earthquake on April 20, 2013, was taken as an example, and the improved method, DE-DDTFA, was used to decompose the signal into multiple intrinsic mode function (IMF) components, and obtained the IF of each IMF. It is demonstrated by the experimental that the number of IMF is 200% more than usual time, and the energy of the signal had grown by approximately 10–20 times, or even more compared with usual in just one week before the earthquake. The experimental result illustrates that the amount of IMF and the energy of the ENPEMF signal show an overall upward trend, which is a distinct trait before the earthquake, and DDTFA is a good reference for studying the time–frequency distribution and energy spectrum variation characteristics of electromagnetic signals before earthquakes.
Suggested Citation
Guocheng Hao & Panpan Wang & Xiangyun Hu & Juan Guo & Guocheng Wang & Songyuan Tan, 2022.
"Time–frequency characteristics and trend feature of the ENPEMF signal before Lushan $${{\varvec{M}}}_{{\varvec{w}}}$$ M w 6.6 earthquake via DE-DDTFA method,"
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 1869-1885, February.
Handle:
RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05016-w
DOI: 10.1007/s11069-021-05016-w
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05016-w. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.