• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.23-29
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• 2019

In this paper, a deep learning-based detection and classification using multi-band frequency signals is presented for detecting earthquakes prevalent in Korea. Based on an analysis of the previous earthquakes in Korea, it is observed that multi-band signals are appropriate for classifying earthquake signals. Therefore, in this paper, we propose a deep CNN (Convolutional Neural Network) using multi-band signals as training data. The proposed algorithm extracts the multi-band signals (Low/Medium/High frequency) by applying band pass filters to mel-spectrum of earthquake signals. Then, we construct three CNN architecture pipelines for extracting features and classifying the earthquake signals by a late fusion of the three CNNs. We validate effectiveness of the proposed method by performing various experiments for classifying the domestic earthquake signals detected in 2018.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.549-557
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• 2019

In this paper, we focus on the real-time detection method of a seismic ionospheric disturbance using Global Navigation Satellite System (GNSS) signal. First, the monitor for the detection of the seismic ionospheric disturbance is studied based on the estimated ionospheric delay using the GNSS signals. And then, the threshold for the automatic detection is computed. Moreover, to discriminate the seismic ionospheric disturbance against the other ionospheric anomalies due to other error sources such as cycle slips, the signatures of the ionospheric perturbation caused by the seismic wave is investigated. Based on the observation, the detection strategy is proposed. Using GPS observations collected from the 47 permanent stations in South Korea and Japan, the proposed real-time detection method is evaluated.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.47-54
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• 2015

In this study, we developed strategies for pre-processing GNSS data for the purpose of separating geodetic factors from crustal deformation due to the earthquakes. Before interpreting GNSS data analysis results, we removed false signals from GNSS coordinate time series. Because permanent GNSS stations are located on a large tectonic plate, GNSS position estimates should be affected by the tectonic velocity of the plate. Also, stations with surrounding trees have seasonal signals in their three-dimensional coordinate estimates. Thus, we have estimated the location of an Euler pole and angular velocities to deduce the plate tectonic velocity and verified with geological models. Also, annual amplitudes and initial phases were estimated to get rid of those false annual signals showing up in the time series. By considering the two effects, truly geodetic analysis was possible and the result was used as preliminary data for analyzing post-seismic deformation of the Korean peninsula due to the Tohoku-oki earthquake.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.616-622
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• 2018

Energy which is released by a huge earthquake can reach the ionosphere and induce disturbances. Those disturbances can detected by analyzing the global navigation satellite system (GNSS) satellite's signal. For detecting those disturbances, band-pass filter is generally used. Therefore, it is important to select proper pass band that can contain disturbance's frequency. In this paper, we analyzed a frequency of the ionospheric disturbances which are induced by earthquake by using GNSS signal. For analyzing seismogenic ionospheric disturbances, we calculated a geometry free combination of carrier phase to obtain a ionospheric delay. After that, the fast Fourier transform was applied to the 1 mHz high-passed ionospheric delay. As a result of analyzing disturbances, the frequency band of earlier disturbances was 4.5 mHz~11mHz and the representative frequency was 5.7 mHz. The frequency band of subsequent disturbances was 6 mHz~10 mHz and the representative frequency was 7.3 mHz.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.491-501
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• 2014

Recently, the need for disaster-preventing broadcast has increased gradually to cope with natural disaster like earthquake and tsunami causing enormous losses of both life and property. In disaster-preventing broadcast system, the wake-up signal is used to alert user terminal and switch the current state of channel to the emergency channel, which is for the fast and efficient delivery of emergency information. In this paper, we propose the detection method of wake-up signal for disaster-preventing broadcast systems. The wake-up signals for disaster-preventing broadcast should have a good auto-correlation property in low power and narrow-band conditions that does not affect the existing digital television (DTV) system. The suitability of the m-sequence and complementary code (CC) is analyzed for wake-up signals according to signal to noise ratio. A wake-up signal is proposed by combining the direct sequence spread spectrum (DSSS) technique and pseudo noise (PN) sequences such as Barker and Walsh-Hadamard codes. By using the proposed method, a higher detecting performance can be achieved by the spreading gain compared to the single long m-sequence and the Golay code.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.316-327
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• 2009

A standard for national seismological observatory was proposed on 1999. Since then, Quanterra digitizer has been installed and is operating on almost all of seismic stations which belong to major seismic monitoring organizations. Quanterra digitizer produce and transmit real-time event packet and data packet. Characteristics of event packet and arrival time of each channel's data packet on data center were investigated. Packet selection criteria using signal to noise ratio (hereafter SNR) and signal period from real-time event packet based on 100 samples per second (hereafter sps) velocity data were developed. Estimation of epicenter using time information of the selected event packet were performed and tested. A series of experiment show that event packets were received approximately 3~4 second earlier than data packets and the number of event packet was only 0.3% compare to data packets. Just about 5% against all of event packets were selected as event packet were related P wave of real earthquake. Using the selected event packets we can estimate an epicenter with misfit less than 10 km within 20 sec for local earthquake over magnitude 2.5.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.49-56
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• 2018

As the energy generated by earthquake, tsunami, etc. propagates through the air and disturbs the electron density in the ionosphere, the perturbation can be detected by analyzing the ionospheric delay in satellite signal. The electron density in the ionosphere is affected by various factors such as solar activity, latitude, season, and local time. To distinguish from the anomaly, therefore, it is required to inspect the normal trend of the ionosphere. Also, as the perturbation magnitude diminishes by distance it is necessary to develop an appropriate algorithm to detect long-distance disturbances. In this paper, normal condition ionosphere trend is analyzed via IONEX data. We selected monitoring value that has no tendency and developed an algorithm to effectively detect the long-distance ionospheric disturbances by using the lasting characteristics of the disturbances. In the end, we concluded the $2^{nd}$ derivative of ionospheric delay would be proper monitoring value, and the false alarm with the developed algorithm turned out to be 1.4e-6 level. It was applied to 2011 Tohoku earthquake case and the ionospheric disturbance was successfully detected.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.57-65
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• 2006

This paper presents hybrid structural damage monitoring system which performs both global damage assessment of structure and damage detection of local structural joints. Hybrid damage monitoring system is composed of vibration-based technique and electro/mechanic impedance technique. Vibration-based technique detects global characteristic change ot structure using modal characteristic change of structure, and electro/mechanical impedance technique detects damage existence of local structural joints using impedance change of PZT sensor. For the verification of the proposed hybrid monitoring system, a series of damage scenarios are designed to loosened bolts situations of the structural joints, and acceleration response and impedance response signatures are measured. The proposed hybrid monitoring system is implemented to monitor global damage-state and local damages in structural joints.

• Tunnel and Underground Space
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• v.18 no.1
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• pp.1-9
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• 2008

Acoustic emission (AE) and Microseimsic (MS) activities are law-energy seismic events associated with a sudden inelastic deformation such as the sudden movement of existing fractures, the generation of new fractures or the propagation of fractures. These events rapidly increase before major failure and happen within a given rock volume and radiate detectable seismic waves. The main difference between AE and MS signals is that the seismic motion frequencies of AE signals are higher than those of MS signals. As the failure of geotechnical structures usually happens as a high velocity and small displacement, it is nat easy ta determine the precursor and initiation stress level of failure in displacement detection method. To overcame this problem, AE/MS techniques far detection of structure failure and damage have recently adapt in civil engineering. This study deal with the basic theory of AE/MS and state of arts in monitoring technique using AE/MS.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.1-8
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• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.