High Sensitivity Very Low Frequency Receiver for Earthquake Data Acquisition

ABSTRAKPenelitian ini membahas mengenai penerima gelombang extremely low frequency (ELF) untuk pengolahan akuisisi data gempa bumi. Penerima ELF dirancang menggunakan operational amplifier (Op-Amp) dengan masukan takmembalik. Sinyal yang diterima oleh antena diteruskan ke penerima ELF yang terdiri dari preamplifier dan amplifier untuk proses penguatan, serta filter aktif orde 2 untuk menekan sinyal di atas frekuensi cut-off sebesar 50Hz. Karakterisasi penerima ELF dilakukan dengan mengamati perbandingan level tegangan sinyal keluaran terhadap level tegangan sinyal masukan, sensitivitas, serta bentuk sinyal keluaran dari penerima ELF dalam domain waktu. Hasil simulasi menunjukkan bahwa penerima ELF menghasilkan penguatan sebesar 60,8dB dengan sensitifitas tinggi untuk level sinyal masukan di bawah -30dB yang mampu memenuhi level sinyal untuk pengolahan akuisisi data.Kata kunci: extremely low frequency, penerima ELF, operational amplifier, filter aktif, gempa bumi ABSTRACTThis research presents extremely low frequency (ELF) receiver for earthquake data acquisition processing. The ELF receiver is designed based on non-inverting operational amplifier (Op-Amp). The signal received by the antenna is fed into ELF receiver which consists of preamplifier and amplifier for amplification, and second order active filter to suppress unwanted signal above the cut-off frequency of 50Hz. Characterization of ELF receiver is performed by observing the comparison of the level output signal to level input signal, sensitivity, and ELF receiver signal output in time domain. The simulation results show that the ELF receiver has gain of 60.8dB with high sensitivity for low level input signals below -30dB that is able to meet signal level for data acquisition processing.Keywords: extremely low frequency, ELF receiver, operational amplifier, active filter, earthquake

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Development of very low frequency (VLF) data acquisition system using Raspberry Pi

2015 International Conference on Space Science and Communication (IconSpace) ◽

10.1109/iconspace.2015.7283807 ◽

2015 ◽

Cited By ~ 2

Author(s):

Y. L. Soon ◽

K. B. Gan ◽

M. Abdullah

Keyword(s):

Data Acquisition ◽

Low Frequency ◽

Data Acquisition System ◽

Acquisition System ◽

Raspberry Pi ◽

Very Low Frequency

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The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

Journal of Psychophysiology ◽

10.1027/0269-8803.23.4.191 ◽

2009 ◽

Vol 23 (4) ◽

pp. 191-198 ◽

Cited By ~ 26

Author(s):

Suzannah K. Helps ◽

Samantha J. Broyd ◽

Christopher J. James ◽

Anke Karl ◽

Edmund J. S. Sonuga-Barke

Keyword(s):

Brain Activity ◽

Sampling Rate ◽

Low Frequency ◽

Future Research ◽

Adhd Symptoms ◽

Default Mode ◽

Very Low Frequency ◽

Wide Range ◽

Interference Hypothesis ◽

Mode Interference

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.

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