• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.269-278
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• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• ETRI Journal
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• v.26 no.6
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• pp.635-640
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• 2004

A new low-complexity differential detection technique, fractional multi-bit differential detection (FMDD), is proposed in order to improve the performance of continuous phase modulation (CPM) signals such as Gaussian minimum shift keying (GMSK) and Gaussian frequency shift keying (GFSK). In comparison to conventional one-bit differential detected (1DD) GFSK, the FMDD-employed GFSK provides a signal-to-noise ratio advantage of up to 1.8 dB in an AWGN channel. Thus, the bit-error rate performance of the proposed FMDD is brought close to that of an ideal coherent detection while avoiding the implementation complexity associated with the carrier recovery. In the adjacent channel interference environment, FMDD achieves an even larger SNR advantage compared to 1DD.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.53.3-53.3
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• 2017

The pilot study of SLGT (Superconducting Low-frequency Gravitational-wave Telescope) is being performed by KKN (KASI-KISTI-NIMS) collaboration. In this presentation, we discuss prospectives of detecting GWs in the low-frequency band (0.1-10 Hz), which is a target frequency band of SLGT, but can be hardly observed by advanced LIGO. IMBHBs (Intermediate Mass Black Hole Binaries) and IMRIs (Intermediate Mass Ratio Inspirals) with total masses of O(1000) up to O(10,000) solar masses are most probable sources between 0.1-10 Hz. We estimate horizon distances and signal to noise ratios of IMBHBs and IMRIs for different SLGT design sensitivities. Based on our calculations, detection rates for IMBHBs and IMRIs with SLGT will be discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2187-2193
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• 2010

A specific radar system can be implemented more easily using the frequency modulated continuous wave comparing with the pulse Doppler radar. It also has the advantage of LPI (low probability of interception) because of the low power and wide bandwidth characteristics. These radars are usually used to cover the short range area and to obtain the high resolution measurements of the target range and velocity information. The transmitted waveform is used in the mixer to demodulate the received echo signal and the resulting beat signal can be obtained. This beat signal is analyzed using the FFT method for the purpose of clutter removal, detection of a target, extraction of velocity and range information, etc. However, for the case of short signal acquisition time, this FFT method can cause the serious leakage effect which disables the detection of weaker echo signals masked by strong side lobes of the clutter. Therefore, in this paper, the weighting window method is analyzed to suppress the strong side lobes while maintaining the proper main lobe width. Also, the results of FFT beat spectrum analysis are shown under various environments.

• Proceedings of the KIEE Conference
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• 2008.09a
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• pp.214-217
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• 2008

To detect partial discharge of 154kV joint box, we have made experiment by using the HFCT sensor. Generally the signals which are detected in partial discharge test of underground power transmission cable are accompanied with both noises of high voltage and noises of surrounding Power cable. The most noise in near to end part of joint box is corona, beside other noises flowed from surrounding area. Partial discharge test is difficulty due to these noises. First, we test reliability on both injection of calibration signal in NJB and removal of low frequency. After that, we had analyzed frequencies by measuring signals in IJB with 300[m] distance from NJB. Also we had measured S/N ratio by using the indirected injection method of calibration signal in IJB. In this experiment, two measurement methods were difference of detection acquisition, but these had the equal frequency properties.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.672-678
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• 2009

Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.110-117
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• 2016

Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.

• Composites Research
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• v.17 no.2
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• pp.28-33
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• 2004

Failure detection in a cross-ply laminated composite beam under tensile loading were performed using a fiber Bragg grating (FBG) sensor. A Passive Mach-Zehnder interferometric demodulator was proposed to enhance sensitivity and bandwidth. The proposed FBG sensor system without active device such as a phase modulator is very simple in configuration, easy to implement and enables the measurement of high-frequency vibration with low strain amplitude such as impact or failure signal. Failure signals detected by a FBG sensor had offset value corresponding to the strain shift with vibration at a maximum frequency of several hundreds of kilohertz. at the instant of transverse crack propagation in the 90 degree layer of composite beam.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.359-364
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• 2006

Interference can seriously degrade the performance of GPS receiver because GPS signal has extremely low power at earth surface. This paper presents a Narrowband Interference Excision Filter (NIEF) in frequency domain that removes narrowband interferences with small signal loss. A NIEF transforms the received GPS signals with interferences into the frequency domain with FFT and then compute statistics such as mean and standard deviation to determine an excision threshold. All spectrums exceeding the threshold are removed and the remaining spectrums are restored by IFFT. A NIEF effectively can remove various and strong interferences with a simple structure. However, the signal power loss is unavoidable during FFT and IFFT. Besides the hamming window and overlap technique, a threshold-whitening technique and an adaptive detection threshold are adopted to effectively reduce the signal power loss. The performance of implemented NIEF is evaluated using real signals obtained by 12 bit GPS signal acquisition board. The output of NIEF is fed into the Software Defined Receiver to evaluate the acquisition and tracking performance. Experimental results shows that many types of interference such as single-tone CWI, AM, FM, swept CWI and multi-tones CWI are effectively mitigated with small signal power loss.