Low-frequency differentiators and integrators for biomedical and seismic signals

2001 ◽  
Vol 48 (8) ◽  
pp. 1006-1011 ◽  
Author(s):  
M.A. Al-Alaoui
Keyword(s):  
Low Frequency ◽  
Seismic Signals

Overview of observed seismic signals on Mars

2020 ◽  
Author(s):  
Savas Ceylan ◽  
John F. Clinton ◽  
Domenico Giardini ◽  
Maren Böse ◽  
Martin van Driel ◽  
...  
Keyword(s):  
Energy Content ◽  
Low Frequency ◽  
Careful Analysis ◽  
Atmospheric Effects ◽  
Seismic Signals ◽  
S Wave ◽  
Ground Segment ◽  
Short Period ◽  
Data Content ◽  
Set Up

<p>InSight landed on Mars in late November 2018, and the SEIS package, which consists of one short period and one very broadband sensor, was deployed on the surface shortly after. The data returned by the InSight is monitored in a timely manner by the Marsquake Service (MQS), a ground segment support group of InSight that has been set up to establish and maintain the seismicity catalogue. The MQS has at least one member on duty who routinely checks the data for any type of seismic signals. All suspicious signals are then communicated to the InSight team after evaluation.</p><p>To date, MQS has identified more than 365 events which are classified into two general families as high and low frequency, with each family having unique features in terms of their energy content. The most distinct quakes detected so far belong to the low frequency family that occurred on Sol 173 and 235, and have clear P and S-wave arrivals that reveal a distance around 30 degrees east of the lander, pointing the region in the vicinity of Cerberus Fossae. In addition to the signals of seismic origin, the SEIS data contain features that originate from other sources such as atmospheric effects or electronics. Part of these non-seismic observations may resemble quakes which may lead to wrong interpretations, and therefore require careful analysis.</p><p>Here, we show examples of signals of both seismic and non-seismic origins. We describe the characteristics of these observations in time and frequency domains in order to give an overview of martian data content.</p>

Seismic signals preceding the explosive eruption of Mount St. Helens, Washington, on 18 May 1980

1983 ◽  
Vol 73 (6A) ◽  
pp. 1797-1813
Author(s):  
Anthony Qamar ◽  
William St. Lawrence ◽  
Johnnie N. Moore ◽  
George Kendrick
Keyword(s):  
Seismic Waves ◽  
Low Frequency ◽  
Seismic Energy ◽  
B Value ◽  
Volcanic Earthquake ◽  
Seismic Signals ◽  
Volcanic Earthquakes ◽  
Short Period ◽  
Stressed Region ◽  
Mount St Helens

Abstract The intense seismic activity which preceded the 18 May 1980 eruption of Mount St. Helens, Washington, released 2 to 3 × 1018 ergs/day in earthquakes that did not correlate temporally with phreatic eruptions which occurred during the same period. Although the b value and amplitude ratios (long-period/short-period) of the earthquakes vary with time, there are no definitive precursors to the 18 May earthquake and eruption. A Mogi type II frequency-magnitude relation, with critical magnitude Mc = 4.6, constrains the characteristic dimension of the highly stressed region under Mount St. Helens to approximately 3 km, preceding the eruption. A major increase in seismic energy release and a decrease in b value around 1 April 1980 may indicate the first major influx of magma into the upper portion of the volcano. Seismic waves from low-frequency volcanic earthquake have large periods at all epicentral distances. Recordings of volcanic earthquakes from 2 to 4 April 1980 at sites 4 to 9 km from Mount St. Helens show two predominant periods of 0.55 and 1.0 sec. We speculate that seismic signals from the low-frequency volcanic earthquakes have a tectonic origin, but may be modified by pressure oscillations in nearby magma.

The seismic sound of deep volcanic processes

2020 ◽  
Author(s):  
Simone Cesca ◽  
Torsten Dahm ◽  
Sebastian Heimann ◽  
Martin Hensch ◽  
Jean Letort ◽  
...  
Keyword(s):  
Progressive Failure ◽  
Low Frequency ◽  
Moho Depth ◽  
Seismic Signals ◽  
Magma Intrusion ◽  
Long Period ◽  
First Case ◽  
Long Duration ◽  
Volcanic Processes ◽  
Fluid Transfer

<p>Deep volcanic processes and magma intrusion episodes through the crust are typically accompanied by a variety of seismic signals, including volcano-tectonic (VT) seismicity, very long period (VLP) signals and deep low-frequency (DLF) events. These signals can reveal the migration of magma batches and the resonance of magma reservoirs and dikes. The recent 2018-2019 unrest offshore the island of Mayotte, Comoros archipelago, represents the first case of a geophysically monitored magmatic intrusion from a deep sub-Moho reservoir through the whole crust reaching the surface. At Mayotte, a huge magma movement and the following drainage of a deep reservoir were accompanied by a complex seismic sequence, including a massive VT swarm and energetic long-duration very long period (VLP) signals recorded globally. The identification and characterization of ~7000 VTs and ~400 VLPs by applying waveforms-based seismological methods allowed us to reconst the unrest phases: early VTs, migrating upward, were driven by the ascent of a magmatic dike, and tracked its propagating from Moho depth to the seafloor, while later VTs marked the progressive failure of the reservoir’s roof, triggering its resonance and the generation of long-duration VLPs. At the Eifel, Germany, weak DLFs earthquakes have been recorded over the last decades and located along a deep channel-like structure, extending from sub-Moho depth (~40-45 km) to the upper crust (~5-10 km). While not showing any clear migration, they reveal a different way of fluid transfer from depth towards the surface, possibly marking intermediate small reservoirs along a feeding channel. Here, brittle failure occurring in the vicinity of the reservoirs may cause their resonance. The Mayotte and Eifel observations are example of end member models for deep fluid transfer processes through the crust. These examples show that, by listening to seismic signals at different distances and by analysing them with modern waveform based methods, we can provide a detailed picture of deep magmatic processes and enable future eruption early warning.</p>

Denoising of seismic signals based on empirical mode decomposition-wavelet thresholding

2020 ◽  
pp. 107754632092684
Author(s):  
Li Long ◽  
Xiulan Wen ◽  
Yixue Lin
Keyword(s):  
Empirical Mode Decomposition ◽  
Seismic Waves ◽  
Low Frequency ◽  
Wavelet Thresholding ◽  
Seismic Signals ◽  
Denoising Method ◽  
Intrusion Prevention ◽  
Mode Decomposition ◽  
Empirical Mode Decomposition Method ◽  
Feature Information

Unattended object detection systems have seen full applications in military surveillance, object recognition, and intrusion prevention. When applied to actual work scenarios, these systems have problems such as low recognition accuracy, low positioning accuracy, and weak detection effect of distant objects. Obtainment of enough feature information concerning the effective signals is critical to target recognition. This work focuses on interference in seismic signals and the way to store the feature information of effective signals. First, the authors analyzed the frequency and attenuation characteristics of seismic waves of typical target sites, in which the Rayleigh wave is suitable for the detection of the energy of seismic signals produced by human targets and vehicles. As seismic signals are low-frequency waves, the authors researched the performance of the empirical mode decomposition method and the wavelet thresholding method in denoising seismic signals, and an improved empirical mode decomposition-wavelet threshold denoising method is proposed. The test result shows that the improved denoising method can effectively remove noise in seismic signals and preserve the effective signals of the target.

scholarly journals Exposure to seismic air gun signals causes physiological harm and alters behavior in the scallop Pecten fumatus

2017 ◽  
Vol 114 (40) ◽  
pp. E8537-E8546 ◽  
Author(s):  
Ryan D. Day ◽  
Robert D. McCauley ◽  
Quinn P. Fitzgibbon ◽  
Klaas Hartmann ◽  
Jayson M. Semmens
Keyword(s):  
Blood Cell ◽  
Sublethal Effects ◽  
Low Frequency ◽  
Repeated Exposure ◽  
Seismic Signals ◽  
Seismic Surveys ◽  
Naturally Occurring ◽  
Air Gun ◽  
Behavioral Parameters ◽  
The Impact

Seismic surveys map the seabed using intense, low-frequency sound signals that penetrate kilometers into the Earth’s crust. Little is known regarding how invertebrates, including economically and ecologically important bivalves, are affected by exposure to seismic signals. In a series of field-based experiments, we investigate the impact of exposure to seismic surveys on scallops, using measurements of physiological and behavioral parameters to determine whether exposure may cause mass mortality or result in other sublethal effects. Exposure to seismic signals was found to significantly increase mortality, particularly over a chronic (months postexposure) time scale, though not beyond naturally occurring rates of mortality. Exposure did not elicit energetically expensive behaviors, but scallops showed significant changes in behavioral patterns during exposure, through a reduction in classic behaviors and demonstration of a nonclassic “flinch” response to air gun signals. Furthermore, scallops showed persistent alterations in recessing reflex behavior following exposure, with the rate of recessing increasing with repeated exposure. Hemolymph (blood analog) physiology showed a compromised capacity for homeostasis and potential immunodeficiency, as a range of hemolymph biochemistry parameters were altered and the density of circulating hemocytes (blood cell analog) was significantly reduced, with effects observed over acute (hours to days) and chronic (months) scales. The size of the air gun had no effect, but repeated exposure intensified responses. We postulate that the observed impacts resulted from high seabed ground accelerations driven by the air gun signal. Given the scope of physiological disruption, we conclude that seismic exposure can harm scallops.

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