Detecting local and regional seismic events using the data-adaptive method at the VAF seismograph station in Finland

1991 ◽  
Vol 81 (4) ◽  
pp. 1373-1379
Author(s):  
Matti Tarvainen
Keyword(s):  
Detection Threshold ◽  
Seismic Signal ◽  
Adaptive Method ◽  
Digital Data ◽  
Seismic Events ◽  
Visual Methods ◽  
Long Period ◽  
Detection Window ◽  
Seismograph Station ◽  
Data Adaptive

Abstract The data-adaptive autoregressive (hereafter DA) method was used to detect local and regional seismic events using digital data from the Vaasa (VAF) station with co-ordinates (62.3°N, 22.2°E) in western Finland. The seismic signal and the noise were assumed to have been normally distributed stochastic processes with a zero mean. The parameters of these processes were then adapted on the change of the registered signal as a function of time within a predefined detection window. The accuracy of the method presented is compared with the STA/LTA and visual methods. When the same detection threshold was used with the DA detector and the STA/LTA detector, it was found that the DA detector was more precise in detecting the onsets of seismic events. Bandpass (1.5 to 20 Hz) filtering was used in all the events discussed. This was done to reject the long-period microseismic noise. In one case, the detector was used on nonfiltered as well as filtered data, in order to show coinciding results.

scholarly journals A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3416
Author(s):  
Pawel Burdziakowski ◽  
Angelika Zakrzewska
Keyword(s):  
Data Integration ◽  
Point Cloud ◽  
Laser Scanning ◽  
Detection Threshold ◽  
Measurement Data ◽  
Steel Structures ◽  
Adaptive Method ◽  
Edge Extraction ◽  
Geometric Structures ◽  
Redundant Data

The continuous and intensive development of measurement technologies for reality modelling with appropriate data processing algorithms is currently being observed. The most popular methods include remote sensing techniques based on reflected-light digital cameras, and on active methods in which the device emits a beam. This research paper presents the process of data integration from terrestrial laser scanning (TLS) and image data from an unmanned aerial vehicle (UAV) that was aimed at the spatial mapping of a complicated steel structure, and a new automatic structure extraction method. We proposed an innovative method to minimize the data size and automatically extract a set of points (in the form of structural elements) that is vital from the perspective of engineering and comparative analyses. The outcome of the research was a complete technology for the acquisition of precise information with regard to complex and high steel structures. The developed technology includes such elements as a data integration method, a redundant data elimination method, integrated photogrammetric data filtration and a new adaptive method of structure edge extraction. In order to extract significant geometric structures, a new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied object without losing important data and information. The new algorithm automatically self-adapts to the received data. It does not require any pre-setting or initial parameters. The detection threshold is also adaptively selected based on the acquired data.

Performance of a rotational sensor at Etna, Italy focusing on back-azimuth estimations of volcano-seismic events

2021 ◽  
Author(s):  
Martina Rosskopf ◽  
Eva P. S. Eibl ◽  
Gilda Currenti ◽  
Philippe Jousset ◽  
Joachim Wassermann ◽  
...  
Keyword(s):  
Rotation Rate ◽  
Mount Etna ◽  
Seismic Events ◽  
Volcano Seismology ◽  
Rotational Seismology ◽  
Long Period ◽  
Tectonic Events ◽  
Back Azimuth ◽  
Seismic Wavefield

<p>The field of rotational seismology has only recently emerged. Portable 3 component rotational sensors are commercially available since a few years which opens the pathway for a first use in volcano-seismology. The combination of rotational and translational components of the wavefield allows identifying and filtering for specific seismic wave types, estimating the back azimuth of an earthquake, and calculating local seismic phase velocities.</p><p>Our work focuses on back-azimuth calculations of volcano-tectonic and long-period events detected at Etna volcano in Italy. Therefore, a continuous full seismic wavefield of 30 days was recorded by a BlueSeis-3A, the first portable rotational sensor, and a broadband Trillium Compact seismometer located next to each other at Mount Etna in August and September of 2019. In this study, we applied two methods for back-azimuth calculations. The first one is based on the similarity of the vertical rotation rate to the horizontal acceleration and the second one uses a polarization analysis from the two horizontal components of the rotation rate. The estimated back-azimuths for volcano-tectonic events were compared to theoretical back-azimuths based on the INGV event catalog and the long-period event back-azimuths were analyzed for their dominant directions. We discuss the quality of our back azimuths with respect to event locations and evaluate the sensitivity and benefits of the rotational sensor focusing on volcano-seismic events on Etna regarding the signal to noise ratios, locations, distances, and magnitudes.</p>

An ocean-bottom seismometer capsule

1974 ◽  
Vol 64 (4) ◽  
pp. 1251-1262
Author(s):  
William A. Prothero
Keyword(s):  
Seismic Event ◽  
Field Tests ◽  
Data Interpretation ◽  
Seismic Signal ◽  
Digital Data ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Event Trigger ◽  
Analog Output ◽  
Predetermined Time

abstract An ocean-bottom seismometer capsule containing a 1-Hz vertical seismometer and triggered digital recording system has been developed and tested off the coast of San Diego. The output of the seismometer is continuously digitized at 64, 128, or 256 samples per second. The digital data is mixed with a time code and passed through a 256 sample shift register which acts as a delay line. It is then mixed with synchronization characters, serialized, encoded, and recorded on a SONY TC800B tape recorder which is turned on when a seismic event occurs. The event trigger occurs when the seismic signal jumps to at least twice the time-averaged input signal. Data are recovered using the same recorder for playback and a decoder which provides an analog output for field data interpretation or a digital output for computer analysis. The capsule itself falls freely to the ocean bottom. After a predetermined time it is released from a 150-lb steel tripod and floats to the surface. A dual timer and explosive bolt system provides a high recovery reliability. A number of seismic events have been measured in field tests and the system has proven to be extremely simple to check out, diagnose, and deploy.

scholarly journals Monitoring and analysis of seismic data during the 2018 sunda strait tsunami

2021 ◽  
Vol 331 ◽  
pp. 07006
Author(s):  
Wahyu Kurniawan ◽  
Daryono ◽  
IDK Kerta ◽  
Bayu Pranata ◽  
Tri Winugroho
Keyword(s):  
Seismic Data ◽  
Warning System ◽  
Seismic Signal ◽  
The Body ◽  
Volcanic Earthquake ◽  
Time Zone ◽  
Ground Shaking ◽  
Tsunami Early Warning ◽  
Seismograph Station ◽  
Tsunami Signal

The tsunami of Sunda Strait occurred on December 22, 2018, at 21:03 West Indonesia Time (zone). An eruption of Mount Anak Krakatau caused an eruption that triggered a landslide on the slopes of Mount Anak Krakatau covering an area of 64 hectares that hit the coastal area of western Banten and southern Lampung and resulted in 437 deaths, 14.059 people were injured, and 33.721 people were displaced. Before the tsunami, signal transmissions (gaps) at the Lava seismograph station installed on the body of Mount Anak Krakatau experienced broken so that Mount Anak Krakatau Observation Post could not record volcanic earthquake signals since December 22, 2018, at 21.03 West Indonesia Time (zone). Given these facts, proper monitoring and analysis were required to monitor and analyze the source of ground vibrations originating from the eruption of Mount Anak Krakatau. Therefore, this study aims to confirm the eruptive activity of Mount Anak Krakatau based on seismic monitoring and analysis sourced from the BMKG's seismic sensor network. The method the author uses is by monitoring the seismic signal recorded by the seismometer and analyzing the seismic signal using the Seiscomp3 software. By the results of monitoring and analysis of seismic data, it was found that the location of the center of the ground shaking was on Mount Anak Krakatau with a magnitude of 3.4, and a depth of 1 km. To anticipate similar tsunami events in the future, it is very necessary to have a tsunami early warning system originating from volcanic activity and volcanic body avalanches.

A stable data adaptive method for matched‐field array processing in acoustic waveguides

1989 ◽  
Vol 85 (S1) ◽  
pp. S17-S17
Author(s):  
C. L. Byrne ◽  
R. I. Brent ◽  
C. Feuillade ◽  
D. R. DelBalzo
Keyword(s):  
Array Processing ◽  
Adaptive Method ◽  
Acoustic Waveguides ◽  
Data Adaptive

Very-Long-Period (VLP) Seismic Artifacts during the 2018 Caldera Collapse at Kīlauea, Hawai‘i

2020 ◽  
Vol 91 (6) ◽  
pp. 3417-3432
Author(s):  
Ashton F. Flinders ◽  
Ingrid A. Johanson ◽  
Phillip B. Dawson ◽  
Kyle R. Anderson ◽  
Matthew M. Haney ◽  
...  
Keyword(s):  
Amplitude Spectrum ◽  
Low Frequency ◽  
Seismic Signal ◽  
Sinc Function ◽  
Caldera Collapse ◽  
Velocity Amplitude ◽  
Long Period ◽  
Ramp Function ◽  
Instrument Response ◽  
Summit Caldera

Abstract Throughout the 2018 eruption of Kīlauea volcano (Hawai‘i), episodic collapses of a portion of the volcano’s summit caldera produced repeated Mw 4.9–5.3 earthquakes. Each of these 62 events was characterized by a very-long-period (VLP) seismic signal (>40  s). Although collapses in the later stage of the eruption produced earthquakes with significant amplitude clipping on near-summit broadband seismometers, the first 12 were accurately recorded. For these initial collapse events, we compare average VLP seismograms at six near-summit locations to synthetic seismograms derived from displacements at collocated Global Positioning System stations. We show that the VLP seismic signal was generated by a radially outward and upward ramp function in displacement. We propose that at local distances the period of the VLP seismic signal is solely dependent on the duration of this ramp function and the instrument transfer function, that is, the seismic VLP is an artifact of the bandlimited instrument response and not representative of real ground motion. The displacement ramp function imposes a sinc-function velocity amplitude spectrum that cannot be fully recovered through standard seismic instrument deconvolution. Any near-summit VLP signals in instrument-response-corrected velocity or displacement seismograms from these collapse events are subject to severe band limitation. Similarly, the seismic amplitude response is not flat through the low-frequency corner, for example, instrument-response-uncorrected seismograms scaled by instrument sensitivity are equally prone to band limitation. This observation is crucial when attempting to clarify the different contributions to the VLP source signature. Not accounting for this effect could lead to misunderstanding of the magmatic processes involved.

LONG‐PERIOD SIGNAL PROCESSING RESULTS FOR THE LARGE APERTURE SEISMIC ARRAY

Geophysics ◽  
1969 ◽  
Vol 34 (3) ◽  
pp. 305-329 ◽  
Author(s):  
J. Capon ◽  
R. J. Greenfield ◽  
R. T. Lacoss
Keyword(s):  
Signal Processing ◽  
Surface Wave ◽  
Maximum Likelihood ◽  
Surface Waves ◽  
Body Wave ◽  
Seismic Array ◽  
Seismic Events ◽  
Long Period ◽  
Large Aperture ◽  
Period Data

The results of a series of off‐line signal processing experiments are presented for long‐period data obtained from the Large Aperture Seismic Array (LASA) located in eastern Montana. The signal‐to‐noise ratio gains obtained with maximum‐likelihood processing, as well as other simpler forms of processing, are presented for body‐wave as well as surface‐wave phases. A discussion of the frequency‐wavenumber characteristics of the noise which led to these results is also given. On the basis of these experiments, several recommendations are made concerning optimum long‐period array configurations and on‐line or off‐line processing methods. The usefulness of maximum‐likelihood processing in suppressing an interfering teleseism is demonstrated. An experiment is given in which maximum‐likelihood processing achieved about 20 db suppression of an interfering teleseism, while simpler forms of processing such as beam‐forming obtained about 11 db. The matched filtering of surface waves using chirp waveforms is shown to be highly effective. A useful discriminant for distinguishing between natural seismic events and underground nuclear explosions, using both the long‐period and short‐period data, was found to be the relationship between the surface‐wave and body‐wave magnitudes. Measurements of this discriminant made on events from four tectonic regions of the earth are presented. It is shown that 60 and 100 percent detectability of surface waves for natural seismic events from the Central Asian‐Kurile Islands‐Kamchatka region occurs at about LASA body‐wave magnitudes 4.5 and 4.9, respectively.

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