• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.742-746
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• 2008

With the trend of factory automation, nowadays, much industrial machinery tends to be put into 24-hours operation a day. However, these trends in industrial equipments also increase the possibility of various mechanical problems and bring about innumerable maintenance cost. There is a strong need of the condition monitoring and diagnosis for industrial equipment, especially rotating machinery, since they are connected not only to the reduction in the maintenance costs but also connected to the enhancement of production efficiency. Generally, to evaluate the operating conditions in the machinery in the industrial field, various physical properties are monitored. Among them, vibration and Noise signals are the mist important indicator and it is effectively used in many diagnosis systems for machinery. Much previous research is based in the FFT (Fast Fourier Transform) method. The spectral analysis is assumed that the signal is stationary. However, almost random signals are non-stationary. The wavelet transform has been recognized an efficient Method. Most interesting sounds have time-varying features. Signal processing techniques for the analysis of transient sound have been not clearly given yet.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.108-115
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• 1996

This paper proposes an algorithm and a model topology for the connected speech recognition using Discrete Hidden Markov Models. A proposed model uses diphone and triphone model which consider the recognition rate and recognisable vocabulary. Considering more exact inter- phoneme segmentation and execution speed of algorithm, 4 states have to exist in diphone model where the first state and the last state are keeping a steady state, the other states hold a transient state. 7 states have to exist in triphone model where 7 states are specified and improved to 3 steady states and 4 transition states. Also, the proposed speech recognition algorithm is designed to detect the inter-phoneme segmentation during the recognition processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1558-1563
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• 2013

In this paper, we analyze the radio propagation path loss characteristics for the vertical electric dipole radiation over the perfect electric conductor(PEC) ground plane. Most research have been performed about the electromagnetic analysis of vertical electric dipole in free space for time domain or frequency domain. But this paper present the radio propagation path loss over PEC ground plane in time domain under the assumption of the vertical electric dipole as a base station. From the simulated results, the ground plane effect can change the location of near field from transmitting antenna and the transient responses at mobile are calculated. The results of this paper can be applied to surface radar or signal processing applications.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.421-428
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• 2006

This paper proposes an integrated recovery approach applying retry and rollback techniques to recover the TMR failure. Combining the time redundancy techniques with W system is apparently effective to recover the TMR failure(or masked error) primarily caused by transient faults. These policies need fewer reconfigurations at the cost of extra time required for the time redundant schemes. The optimal numbers of retry and rollback to minimize the mean execution time of tasks are derived for the proposed method through computing the likelihoods of all possible states of the failed system. The effectiveness of the proposed method is validated through examining certain numerical examples and simulations conducted with a variety of parameters governing environmental characteristics.

• Science of Emotion and Sensibility
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• v.18 no.2
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• pp.55-64
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• 2015

The aim of the study was to investigate the neural substrates associated with processing anger among young males with alcohol use disorders (AUDs) using functional magnetic resonance imaging (fMRI). Eighteen individuals with AUD and 15 demographically similar non-abusers participated in the study. Participants were scanned on their brain functioning while they viewed an audio-visual film clip that was previously designed specifically to induce anger emotion, followed by anpsychological assessment. Greater brain activities were detected in the left inferior frontal gyrus (IFG) and dorsal anterior cingulate cortex (dACC) among subjects with AUD compared to the controls during the exposure to anger-provoking stimuli. Despite the same level of subjective anger during anger induction, the greater activations both in the IFG and dACC regions may suggestthat individuals with AUD have a greater propensity to undergo cognitive control and self-regulation while experiencing anger.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.713-717
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• 2014

This paper presents a beamforming technique for locating impulsive sound source. The conventional frequency-domain beamformer is advantageous for localizing noise sources for a certain frequency band of concern, but the existence of many frequency components in the wide-band spectrum of impulsive noise makes the beamforming image less clear. In contrast to a frequency-domain beamformer, it has been reported that a time-domain beamformer can be better suited for transient signals. Although both frequency- and time-domain beamformers produce the same result for the beamforming power, which is defined as the RMS value of its output, we can use alternative directional estimators such as the peak value and crest factor to enhance the performance of a time-domain beamformer. In this study, the performance of three different directional estimators, the peak, crest factor and RMS output values, are investigated and compared with the incoherent interfering noise embedded in multiple microphone signals. The proposed formula is verified via experiments in an anechoic chamber using a uniformly spaced linear array. The results show that the peak estimation of beamformer output determines the location with better spatial resolution and a lower side lobe level than crest factor and RMS estimation in noise free condition, but it is possible to accurately estimate the direction of the impulsive sound source using crest factor estimation in noisy environment with stationary interfering noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.9
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• pp.702-708
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• 2002

The spectrum of impulse response signal from an impulse hammer testing is widely used to obtain frequency response function(FRF). However the FRFs obtained from impact hammer testing have not only leakage errors but also finite record length errors when the record length for the signal processing is not sufficiently long. The errors cannot be removed with the conventional signal analyzer which treats the signals as if they are always steady and periodic. Since the response signals generated by the impact hammer are transient and have damping, they are undoubtedly non-periodic. It is inevitable that the signals be acquired for limited recording time, which causes the errors. This paper makes clear the relation between the errors of FRF and the length of recording time. A new method is suggested to reduce the errors of FRF in this paper. Several numerical examples for 1-dof model are carried out to show the property of the errors and the validity of the proposed method.

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.304-310
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• 2011

The application of time-domain methods in emission measurement instruments allows for a reduction in scan time by several orders of magnitude and for new evaluation methods to be realized such as the real-time spectrogram to characterize transient emissions. In this paper two novel systems for time-domain EMI measurements above 1 GHz are presented. The first system combines ultra-fast analog-to-digital-conversion and real-time digital signal processing on a field-programmable-gate-array (FPGA) with ultra-broadband multi-stage down-conversion to enable measurements in the range from 10 Hz to 26 GHz with high sensitivity and full-compliance with the requirements of CISPR 16-1-1. The required IF bandwidths were added to allow for measurements according to MIL-461F and DO-160F. The second system realizes a system of time-interleaved analog-to-digital converters (ADCs) and has an upper bandwidth limit of 4 GHz. With the implementation of an automatic mismatch calibration, the system fulfills CISPR 16-1-1 dynamic range requirements. Measurements of the radiated emissions of electronic consumer devices and household appliances like the non-stationary emissions of a microwave oven are presented. A measurement of a personal computer's conducted emissions on a power supply line according to DO-160F is given.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2488-2491
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• 2000

A Neural network is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping. When a fault occur in system, a state of system is changed with transient state. Because of a previous state signal is considered as a information. DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights, so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.36-40
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• 1997

In speech signal processing, it is necessary and important to detect exactly the pitch. The algorithms of pitch extraction which have been proposed until now are difficult exactly pitches over wide range speech signals. In this paper, thus, we proposed a new pitch detection algorithm that finds the fundamental period of speech signal in the residual signal quantized by the uniform quantizer as PCM. The proposed method shows little gross error of average 0.25% for clean speech and average 3.39% for SNR of 0dB. It also achieves results of the pitch contours, improving the accuracy of pitch detection in transient phonemes and noise environments.