• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3122-3125
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• 2021

Electromagnetic vortex flowmeter is a new type of instrument for detecting leakage of steam generator, and the signal processing method based on the envelope to calculate energy ratio can effectively detect bubbles in sodium flow. The signal processing method is not affected by changes in the amplitude of the sensor output signal, which is caused by changes in magnetic field strength and other factors. However, the detection sensitivity of the electromagnetic vortex flowmeter is reduced. To this end, a signal processing method based on inverse Fourier transform to calculate energy ratio is proposed. According to the difference between the frequency band of the bubble noise signal and the flow signal, only the amplitude in the frequency band of the flow signal is retained in the frequency domain, and then the flow signal is obtained by the inverse Fourier transform method, thereby calculating the energy ratio. Using this method to process the experimental data, the results show that it can detect 0.1 g/s leak rate of water in the steam generator, and its performance is significantly better than that of the signal processing method based on the envelope to calculate energy ratio.

• Speech Sciences
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• v.10 no.2
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• pp.85-95
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• 2003

In speech signal processing, it is very important to detect the pitch exactly in speech recognition, synthesis and analysis. If we exactly pitch detect in speech signal, in the analysis, we can use the pitch to obtain properly the vocal tract parameter. It can be used to easily change or to maintain the naturalness and intelligibility of quality in speech synthesis and to eliminate the personality for speaker-independence in speech recognition. In this paper, we proposed a new pitch detection algorithm. First, positive center clipping is process by using the incline of speech in order to emphasize pitch period with a glottal component of removed vocal tract characteristic in time domain. And rough formant envelope is computed through peak-fitting spectrum of original speech signal infrequence domain. Using the roughed formant envelope, obtain the smoothed formant envelope through calculate the linear interpolation. As well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. Inverse fast fourier transform (IFFT) compute this flattened harmonics. After all, we obtain Residual signal which is removed vocal tract element. The performance was compared with LPC and Cepstrum, ACF. Owing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.572-577
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• 2011

The acoustic emission (AE) technique is a well-known non-destructive test technique, both in research and for industrial applications. It is mainly used to monitor the onset of cracking processes in materials and components. Predicting and preventing the crack phenomenon has attracted the attention of many researchers and has continued to provide a large incentive for the use of condition monitoring techniques to detect the earliest stages of cracks. In this research, goal is in grasping features of AE signal caused by crack growth. The envelope analysis with discrete wavelet transform (DWT) is used to find the characteristic of AE signal. To estimate feature of divided into three by crack length, the time waveform and the power spectrum were generated by the raw signals and the transferred signal processed by envelope analysis with DWT.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.381-384
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• 2002

In speech signal processing, it Is very important to detect the pitch exactly in speech recognition, synthesis and analysis. but, it is very difficult to pitch detection from speech signal because of formant and transition amplitude affect. therefore, in this paper, we proposed a pitch detection using the spectrum flattening techniques. Spectrum flattening is to eliminate the formant and transition amplitude affect. In time domain, positive center clipping is process in order to emphasize pitch period with a glottal component of removed vocal tract characteristic. And rough formant envelope is computed through peak-fitting spectrum of original speech signal in frequency domain. As a results, well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. After all, we obtain residual signal which is removed vocal tract element The performance was compared with LPC and Cepstrum, ACF 0wing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.331-337
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• 2013

Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and Wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet. Therefore, in this paper two methods which are Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94% classification accuracy with the parameter of the RBF 0.08, 12 feature selection.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.2
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• pp.258-266
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• 2012

Recently, Acoustic Emission (AE) technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.689-694
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• 2011

Objective: The aim of this study is to evaluate the fluctuation of signal amplitude during repetitive dynamic contraction based on surface electromyography(EMG). Background: The most previous studies were considered isometric muscle contraction and they were difference to smoothing window length by moving average filter. In practical, the human movement is dynamic state. Dynamic EMG signal which indicated as the nonstationary pattern should be analyzed differently compared with the static EMG signal. Method: Ten male subjects participated in this experiment, and EMG signal was recorded by biceps brachii, anterior/posterior deltoid, and upper/lower trapezius muscles. The subject was performed to repetitive right horizontal lifting task during ten cycles. This study was considered three independent variables(muscle, amplitude processing technique, and smoothing window length) as the within-subject experimental design. This study was estimated muscular activation by means of the linear envelope technique(LE). The dependent variable was set coefficient of variation(CV) of LE for each cycle. Results: The ANOVA results showed that the main and interaction effects between the amplitude processing technique and smoothing window length were significant difference. The CV value of peak LE was higher than mean LE. According to increase the smoothing window length, this study shows that the CV trend of peak LE was decreased. However, the CV of mean LE was analyzed constant fluctuation trend regardless of the smoothing window length. Conclusion: Based on these results, we expected that using the mean LE and 300ms window length increased reproducibility and signal noise ratio during repetitive dynamic muscle contraction. Application: These results can be used to provide fundamental information for repetitive dynamic EMG signal processing.

• Proceedings of the Acoustical Society of Korea Conference
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• 1996.10a
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• pp.70-75
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• 1996

In this paper, the pre-precessing method for the recognition of single vowels by use of spectrum envelope is presented , we use new method of an extrating spectrum envelope using the diffusion filter bank. We reduced the total processing time, and got higher enhancement of discrimination . By getting 88.3% of average recognition rate for single vowels of real voice through computer simulation, we confirmed it to be useful for speech recongition which use spectrum analysis for voice signal to have many frequency components.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.148-155
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• 2014

In this research a signal processing system is designed for detecting the ultrasonic signal envelope using Xilinx's Zynq SoC(system on chip). As a design tool, Vivado IDE(integrated design environment) is used to hierarchically design the whole signal processing system. The proposed system consists of a Zynq-internal ADC, an FIR(finite impulse response) BPF(band pass filter), an absolute value calculator, an FIR LPF(lpw pass filter), and the Kalman filter. Under this configuration, two design schemes, HW design scheme with LPF as a final stage and HW/SW co-design scheme with a Kalman filter as a final stage, are compared in terms of the performance and efficiency. As a result, envelope detecting performances of the two schemes are proved to be almost same, but the HW/SW co-design is verified to be much more efficient than the HW design considering the much smaller time consumption during system design.

• Journal of Dairy Science and Biotechnology
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• v.36 no.4
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• pp.208-219
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• 2018

Emergence of drug resistant strains of Salmonella enterica threatens milk processing and related dairy industries, thereby increasing the need for development of new anti-bacterials. Developments of antibacterial drugs are largely aimed to target the bacterial envelope, but screening their efficacy on bacterial envelope is laborious. This study presents a potential biosensor for envelope-specific stress in which a gfp reporter gene fused to spy gene encoding a periplasmic chaperone protein Spy (spheroplast protein y) that can sense envelope stress signals transduced by two major two-component signal transduction systems BaeSR and CpxAR in Salmonella enterica serovars Enteritidis and S. Gallinarum. Using spy-gfp operon fusions in S. Enterititis and S. Gallinarum, we found that spy transcription in both serovars was greatly induced when Salmonella cells were forming the spheroplast and were treated with ethanol or a membrane-disrupting antibiotic polymyxin B. These envelope stress-specific inductions of spy transcription were abrogated in mutant Salmonella lacking either BaeR or CpxR. Results illustrate that induction of Spy expression can be efficiently triggered by two-component signal transduction systems sensing envelope stress conditions, and thereby suggest that monitoring the spy transcription by spy-gfp operon fusions would be helpful to determine if developing antimicrobials can damage envelopes of S. Enteritidis and S. Gallinarum.