Statistical characteristics and stationarity properties of low-frequency seismic signals

2008 ◽  
Vol 44 (1) ◽  
pp. 50-59 ◽  
Author(s):  
A. V. Gorbatikov ◽  
M. Yu. Stepanova
Keyword(s):  
Low Frequency ◽  
Statistical Characteristics ◽  
Seismic Signals

scholarly journals Vibrations in CDFW

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 704
Author(s):  
Daniel Soares de Alcantara ◽  
Pedro Paulo Balestrassi ◽  
José Henrique Freitas Gomes ◽  
Carlos Alberto Carvalho Castro
Keyword(s):  
Time Domain ◽  
Low Frequency ◽  
Welding Process ◽  
Statistical Characteristics ◽  
Crest Factor ◽  
Vibration Signals ◽  
Mode Decomposition ◽  
Complex Process ◽  
The Time Domain ◽  
Peak Value

Continuous drive friction welding is a solid-state welding process that has been experimentally proven to be a fast and reliable method. This is a complex process; deformations in the viscosity of a material alter the friction between the surfaces of the pieces. All these dynamics cause changes in the vibration signals; the interpretation of these signals can reveal important information. The vibration signals generated during the friction and forging stages are measured on the stationary part of the structure to determine the influence of the manipulated variables on the time domain statistical characteristics (root mean square, peak value, crest factor, and kurtosis). In the frequency domain, empirical mode decomposition is used to characterize frequencies. It was observed that it is possible to identify the effects of the manipulated variables on the calculated statistical characteristics. The results also indicate that the effect of manipulated variables is stronger on low-frequency signals.

Statistical Considerations on Pressure Pulses from a Cavitating Venturi

1986 ◽  
Vol 200 (6) ◽  
pp. 381-387
Author(s):  
S Li ◽  
Y Zhang ◽  
F G Hammitt
Keyword(s):  
Closed Loop ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Resonant Interaction ◽  
Statistical Characteristics ◽  
Pressure Pulsations ◽  
Cavitation Inception ◽  
Flow Noise ◽  
Pressure Pulses ◽  
Liquid Portion

Pressure pulses emitted from cavitating venturi flows are measured and investigated statistically. The results show that according to the degree of cavitation, the overall pressure pulsations consist of different combinations of three components, that is basic flow noise, cavitation pulses and low-frequency pressure fluctuations, due primarily to overall loop characteristics. The statistical characteristics are presented and compared. It is believed that the low-frequency fluctuations result from a resonant interaction between the cavitation ‘cloud’ and the liquid portion of the closed loop. They occur near cavitation inception, reach a maximum at a particular cavitation number, σres, then gradually disappear for increased σ. Their frequency is basically constant for all σ. An empirical-theoretical model of this behaviour is presented.

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>

scholarly journals RESEARCH ON THE FRACTAL STATISTICAL CHARACTERISTICS AS POSSIBLE PROGNOSTIC PARAMETERS FOR EARTHQUAKES, GENERATED IN THE SEISMIC ZONE OF VRANCEA, IN THE PERIOD BETWEEN 01.08.2016 AND 30.12.2016

2019 ◽  
Vol 1 (8(38)) ◽  
pp. 3-12
Author(s):  
E. Oynakov ◽  
D. Solakov ◽  
I. Aleksandrova
Keyword(s):  
Fractal Analysis ◽  
Low Frequency ◽  
Focal Mechanisms ◽  
Statistical Characteristics ◽  
Seismic Zone ◽  
Coherence Measure ◽  
Noise Structure ◽  
Scientific Goal ◽  
Seismic Records ◽  
The Individual

Using fractal analysis is an excellent alternative method for decode the seismic noise structure. Fractal analysis of microseismic noise could also be an appropriate method to detect earthquake indicators. The scientific goal is to detect standard signals, based on different earthquakes’ focal mechanisms, separating the "individual" behavior of the elements of the monitoring systems.The method for describing low-frequency microseismic noise from the network of seismic stations in a seismically active region of the Vrancea used. Seismic records of twenty-three broadband stations were analyzed, situated at distances of 20 to 500 km from the Vrancea earthquakes whit magnitudes Mw=5.7 and Mw=5.6 on September 23 and December 27, 2016, respectively. The daily assessment values of three multifractal parameters (characteristics of the multifractal singularity spectra of the waveform) from each station used for the description.The present paper is a continuation of previous work [Oynakov et al., 2019], where the effects of synchronization in the low-frequency microseismic field were found before the Vrancea earthquake with magnitude Mp=5.6 on October 28, 2019.The study shows that the noise coherence measure increased for stations, closer to the epicenter. However, the question of the source of this coherence remains open.

SIMULATION OF UNDERWATER ACOUSTICAL FIELD FLUCTUATIONS IN RANGE-DEPENDENT RANDOM ENVIRONMENT OF SHALLOW SEA

2014 ◽  
Vol 22 (01) ◽  
pp. 1440006 ◽  
Author(s):  
OLEG E. GULIN ◽  
IGOR O. YAROSHCHUK
Keyword(s):  
Explicit Form ◽  
Adiabatic Approximation ◽  
Spatial Scales ◽  
Low Frequency ◽  
Form Solution ◽  
Statistical Characteristics ◽  
Local Mode ◽  
Shallow Sea ◽  
Field Fluctuations ◽  
General Statistical

To investigate statistical problem of moderate to low-frequency sound scattering on the two-dimensional (2D) random inhomogeneities of a shallow sea with horizontal boundaries (bottom and surface) and loss local-mode approach has been utilized. An explicit-form solution by quadrature for modal amplitudes as a function of distance is represented. In adiabatic approximation asymptotical estimations have been performed, which demonstrate how medium weak fluctuations influence the local eigenvalues and statistical characteristics of a field. It is shown that general effects previously established while studying the random layered problem keep the force. Spatial scales of statistical influence and laws of dependences are determined. Also it follows from the analysis of the explicit-form solution for modal amplitudes that in this shallow-sea model with horizontal boundaries and in the absence of regular variations of sound speed the coupling of modes is insignificant. General statistical effects are described well within the framework of adiabatic approximation.

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