Seismometer Self-Noise and Measuring Methods

Ringler, Adam T.; Sleeman, Reinoud; Hutt, C. R.; Gee, L. S.

doi:10.1007/978-3-642-36197-5_175-1

Cited by 14 publications

(17 citation statements)

References 20 publications

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“…Also shown in green is the SP L4 requirement ment methods, which can be only as good as the reference sensors used-see e.g. Ringler et al (2014). At the limit of performance that we reach (below 10 −9 m/s 2 / √ Hz), it is often difficult to discriminate between self-noise, environmental perturbations and mathematical artefacts to data processing (sampling, synchronization.…”

Section: Limitations Of the Vbb Noise Modelmentioning

confidence: 93%

“…Due to sensitivity to the electronics components' properties and performance, each long-period seismometer has its own characteristics and often quality variations can change the performance between different instruments of the same model sensor as described in Ringler et al (2014). The sensor self-noise is therefore often given by providers as a general shape with intrinsic variability, e.g.…”

Section: The Need Of a Noise Model For Insightmentioning

confidence: 99%

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The Noise Model of the SEIS Seismometer of the InSight Mission to Mars

et al. 2017

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The SEIS (Seismic Experiment for Interior Structures) instrument on board the InSight mission to Mars is the critical instrument for determining the interior structure of Mars, the current level of tectonic activity and the meteorite flux. Meeting the performance requirements of the SEIS instrument is vital to successfully achieve these mission objectives. The InSight noise model is a key tool for the InSight mission and SEIS instrument requirement setup. It will also be used for future operation planning. This paper presents the analyses made to build a model of the Martian seismic noise as measured by the SEIS seismometer, around the seismic bandwidth of the instrument (from 0.01 Hz to 1 Hz). It includes the instrument self-noise, but also the environment parameters that impact the measurements. We present the general approach for the model determination, the environment assumptions, and we analyze the major and minor contributors to the noise model.

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Section: Limitations Of the Vbb Noise Modelmentioning

confidence: 93%

Section: The Need Of a Noise Model For Insightmentioning

confidence: 99%

The Noise Model of the SEIS Seismometer of the InSight Mission to Mars

et al. 2017

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“…To determine a quantitative self-noise model, the measurement of seven quiet days, recorded after two days of settling, was compared with the noise record of a collocated STS-2 seismometer (International Federation of Digital Seismograph Networks [FDSN] ID: OE.CONA.51.BHZ). Details of determining an instrument self-noise using one or two reference sensors can be found in Ringler et al (2014), but given that the self-noise of the CMG-40T-OBS is orders of magnitude higher than the one of an STS-2, we used the simple method of Holcomb (1989) to calculate a self-noise curve (see Fig. 2 and Table 1).…”

Section: Sensor Self-noisementioning

confidence: 99%

A Self‐Noise Model for the German DEPAS OBS Pool

Stähler

Schmidt‐Aursch

Hein

et al. 2018

Seismological Research Letters

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Ocean-bottom seismometers (OBSs) allow us to extend seismological research to the oceans to constrain offshore seismicity but also image the marine subsurface. A challenge is the high noise level on OBS records, which is created not only by bottom currents but also by the specific seismometer models used. We present a quantitative noise model for the LOBSTER OBS, which is the main instrument of the DEutscher Geräte-Pool für Amphibische Seismologie (DEPAS), currently the largest European OBS pool, stationed at AWI Bremerhaven. Studying sensor noise in vault conditions and current sensitivity at an oceanographic measurement mast, we can show that the previously reported high noise level of the instrument is caused by the original sensor (Güralp CMG-40T-OBS). We also show that a strong signal that has been reported between 1 and 5 Hz can be attributed to head-buoy cable strumming. We provide a currentdependent quantitative noise model that can be used for experiment design in future deployments and show that the performance of the pool OBS can be improved at moderate cost by replacing the CMG-40T-OBS with a sensor of a proven noise floor below 10 −8 nm=s 2 , for example, a Trillium compact.

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“…Different coherence analytical techniques, including the two-and three-sensor methods, have been investigated well. The three-sensor method has become the preferred approach for estimating self-noise of broadband sensors owing to its relative stability and robustness in a broad range of frequencies (Ringler et al 2015b). During the mathematical computation, the Welch method is typically adopted to evaluate the signal power spectral density (PSD), wherein specific parameters, such as sample size, sample rate, bandwidth, and windowing, need to be decided before the computation.…”

Section: Introductionmentioning

confidence: 99%

“…Several studies (Holcomb 1990;Sleeman and Melichar 2012;Tasič and Runovc 2013;Gerner and Bokelmann 2013;Ringler et al 2015aRingler et al , 2015bGerner et al 2017) have shown that sensor misalignment is an important source of error during self-noise testing of seismometers based on collocation methods. A synthetic test was conducted to quantify the effect of sensor misalignment as a function of signal-to-noise ratio (SNR) on the self-noise estimate.…”

Section: Introductionmentioning

confidence: 99%

A case study of seismograph self-noise test from Trillium 120QA seismometer and Reftek 130 data logger

Yuan

2019

J Seismol

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Seismograph self-noise has become a de facto standard for instrument comparisons and their performance assessment and is considered as one of the most vital parameters for instrument comparison. For self-noise testing of modern force-balance feedback broadband seismometers, several factors have been thoroughly discussed and thought to be attributable to the self-noise estimate, including the data selection criteria, sensor alignment correction, timing error, correlation analysis method, and computational parameter selection during the computational process. This study focuses on some other factors, such as local site conditions, temperature insulating methods, and data logger self-noise interferences, with an aim to differentiate the self-noise contribution of these sources and their dependencies on time and frequency. A series of experiments were conducted at the Beijing National Earth Observatory using a Trillium 120QA seismometer and Reftek-130 data acquisition system at three different locations ranging from the ordinary equipment warehouse to global seismographic network level cave with a hardrock base. Results show that noise-free site is necessary for the self-noise test in a frequency band greater than approximately 0.1 Hz. However, for a frequency band less than 0.1 Hz, the insulation method and installation procedures are far more important, although the influence of the site location cannot be neglected fully. A suitable preamp should be selected in the data logger configurations to ensure that the low-noise amplitude of the sensor signal is above the digitizer noise level.

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Seismometer Self-Noise and Measuring Methods

Cited by 14 publications

References 20 publications

The Noise Model of the SEIS Seismometer of the InSight Mission to Mars

The Noise Model of the SEIS Seismometer of the InSight Mission to Mars

A Self‐Noise Model for the German DEPAS OBS Pool

A case study of seismograph self-noise test from Trillium 120QA seismometer and Reftek 130 data logger

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