• Tunnel and Underground Space
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• v.21 no.5
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• pp.349-358
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• 2011

This paper introduces a new P wave arrival time determination algorithm of acoustic emission (AE) suitable to identify P waves with low signal-to-noise ratio generated in rock masses around the high-level radioactive waste disposal repositories. The algorithms adopted for this paper were amplitude threshold picker, Akaike Information Criterion (AIC), two step AIC, and Hinkley criterion. The elastic waves were generated by Pencil Lead Break test on a granite sample, then mixed with white noise to make it difficult to distinguish P wave artificially. The results obtained from amplitude threshold picker, AIC, and Hinkley criterion produced relatively large error due to the low signal-to-noise ratio. On the other hand, two step AIC algorithm provided the correct results regardless of white noise so that the accuracy of source localization was more improved and could be satisfied with the error range.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.103-113
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• 2015

This study presents a novel algorithm for determining the P-wave arrival time using amoving window function to improve source localization in low-SNR (signal-to-noise ratio)acoustic emissions. The proposed algorithm was applied to low-SNR signals to verify the accuracy of measurements against existing algorithms. When other algorithms were applied, the test results revealed that SNR decreased and accuracy was reduced, especially where SNR wasless than 2.14. The proposed algorithm using amoving window function considers the frequency characteristic and signal amplitude simultaneously, and produced reliable results where SNR was 2.14.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.133-143
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• 2020

Purpose: This study aims to derive a predictive empirical equation for PGV prediction from P-wave using earthquake records in Korea and to verify the reliability of Onsite EEW. Method: The noise of P wave is removed from the observations of 627 seismic events in Korea to derive an empirical equation with PGV on the base rock, and reliability of Onsite alarms is verified from comparing PGV's predictions and observations through simulation using the empirical equation. Result: P-waves were extracted using the Filter Picker from earthquake observation records that eliminated noises, a linear regression with PGV was used to derive a predictive empirical equation for Onsite EEW. Through the on-site warning simulation we could get a success rate of 80% within the MMI±1 error range above MMI IV or higher. Conclusion: Through this study, the design feasibility and performance of Onsite EEWS using domestic earthquake records were verified. In order to increase validity, additional medium-sized seismic observations from abroad are required, the mis-detection of P waves is controlled, and the effect of seismic amplification on the surface is required.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.447-454
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• 2011

Power-line interference(PLI) can distort certain regions in analysing the ECG signal. In particular, the regions such as P and R wave that are important element in diagnosing with arrhythmia is expressed as different type of noise according to the case whether power-line frequency is multiples of sampling frequency and or not. Noise characteristics is also divided into linearity and non-linearity. In this paper, adaptive subtraction method for removing variable PLI of ECG signal is proposed. We classify the multiple relationship between power line and sampling frequency as Multiple and Non-multiple. PLI of Linear segment is extracted through moving average filter, PLI of non-linear segment is extracted through the interference component that is extracted in the linear segment and stored in the temporary buffer. The performance of P wave and R wave detection is evaluated by using 119 data record of MIT-BIH arrhythmia database. The achieved scores indicate P wave detection rate of 97.91%, R wave detection rate of 96.66% and P wave detection rate of 99.01%, R wave detection rate of 97.93% accuracy respectively for Notch filter and proposed subtraction method.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.287-291
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• 2005

Two-dimensional velocity tomograms of P- and S-waves were obtained by inverting traveltimes of first arrivals. The two sections of shear-wave velocity show similar features as a whole, with smaller values on the section from surface wave dispersions. Difficulties in picking SH-wave phases due to noise and later arrivals than P waves and PS converted waves are experienced. In addition, a flat layer model based on the surface wave inversion prohibits applications of the method where sgear wave velocities vary strongly in the lateral direction.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.39-46
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• 1998

One of the main techniques for diagnosing heart disease is by examining the electrocardiogram(ECG). Many studies on detecting the QRS complex, P, and T waves have been performed because meaningful information is contained in these parameters. However, the earlier detection techniques can not effectively extract those parameters from the ECG that is severely contaminated by noise source. In this paper, we performed the extracting parameters from and recovering the ECG signal using wavelets transform that has recently been applying to various fields.

• Journal of the Korean Geophysical Society
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• v.4 no.2
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• pp.113-120
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• 2001

The discrete wavelet transform(DWT) has potential as a tool for supplying discriminatory attributes with which to distinguish seismic events. The wavelet transform has the great advantage over the Fourier transform in being able to localize changes. In this study, a discrete wavelet transform is applied to seismic traces for identifying seismic events and picking of arrival times for first breaks and S-wave arrivals. The precise determination of arrival times can greatly improve the quality of a number of geophysical studies, such as velocity analysis, refraction seismic survey, seismic tomography, down-hole and cross-hole survey, and sonic logging, etc. provide precise determination of seismic velocities. Tests for picking of P- and S- wave arrival times with the wavelet transform method is conducted with synthetic seismic traces which have or do not have noises. The results show that this picking algorithm can be successfully applied to noisy traces. The first arrival can be precisely determined with the field data, too.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.11-17
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• 1998

One of the main techniques for diagnosing heart disease is by examining the electrocardiogram(ECG). Many studies on detecting the QRS complex, p, and T waves have been performed because meaningful information is contained in these parameters. However, the earlier detecting techniques can not effectively extract those parameters from the ECG that is severely contaminated by noise source. In this paper, we performed the extracting parameters from and recovering the ECG signal using wavelets transform that has recently been applying to various fields.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1587-1595
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• 2016

P wave is cardiac parameters that represent the electrical and physiological characteristics, it is very important to diagnose atrial arrhythmia. However, It is very difficult to detect because of the small size compared to R wave and the various morphology. Several methods for detecting P wave has been proposed, such as frequency analysis and non-linear approach. However, in the case of conduction abnormality such as AV block or atrial arrhythmia, detection accuracy is at the lower level. We propose P wave detection algorithm through adaptive threshold and QRS peak variability. For this purpose, we detected Q, R, S wave from noise-free ECG signal through the preprocessing method. And then we classified three pattern of P wave by peak variability and detected adaptive window and threshold. The performance of P wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 92.60%.

• Journal of the Korean Geophysical Society
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• v.8 no.2
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• pp.67-74
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• 2005

Two-dimensional S-wave velocity sections from SH-wave refraction tomography and surface wave dispersions were obtained by inverting traveltimes of first arrivals and surface wave dispersions, respectively. For the purpose of comparison, a P-wave velocity tomogram was also obtained from a P-wave refraction profiling. P and Rayleigh waves generated by vertical blows on a plate with a sledgehammer were received by 100- and 4.5-Hz geophones, respectively. SH-waves generated by horizontal blows on both sides of a 50 kg timber were received by 8 Hz horizontal geophones. The shear-wave signals were enhanced subtracting data of left-side blows from ones of the right-side blows. Shear-wave velocities from tomography inversion of first-arrival times were compared with ones from inverting dispersion curves of Rayleigh waves. Although the two velocity sections look similar to each other in general, the one from the surface waves tends to have lower velocities. First arrival picking of SH waves is troublesome since P and PS-converted waves arrive earlier than SH waves. Application of the surface wave method, on the other hand, is limited where lateral variation of subsurface tructures is not mild.