• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.366-368
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• 2006

Electronic warfare Support(ES) system measures pulse characteristics for received RF signals that received from all directions. ES system discriminates the pulse trains that have a rule, correlationship, continuance from collected data and analyze the characteristics of the data, and identify the emitters by comparison with emitter identification data(EID). Because pulse density is very high and various signal source exists at modem signal environments, high-speed and accurate signal analysis is needed for realtime countermeasure to emitters. Grouping alleviates the load of signal analysis process and supports reliable analysis. In this paper, we suggest an adaptive clustering scheme regarding signal patterns.

• Journal of the Korean Society of Safety
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• v.15 no.4
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• pp.134-138
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• 2000

Signal words such as DANGER, WARNING, CAUTION, etc. have been used in order to transmit a potential hazard easily and quickly. But they were applied to a number of the sites without consistency. Thus, this study took Quantification Method and Cluster Analysis in order to judge the signal words corresponding to the urgency of situations, and to analyze whether signal words are used properly or not. According to the result of Quantification Method II signal words were most affected by Understanding, Severity and Likelihood in both student group and industrial worker group. And in Quantification Method III CAUTION corresponded to Immediacy and Understanding whereas NOTICE did to Receptivity, WARNING, DEADLY and DANCER did to Likelihood, Dangerousness and Severity. Finally, Cluster Analysis showed that CAUTION and NOTICE were recognized as similar words.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.274-277
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• 2001

This paper describes the simulation study. conducted on the propagation characteristics of AE signal. In the case of gas insulation, such as $SF_6$, the equipment is less affected by the environment condition than air insulation, because the component parts of equipment were placed in the enclosure, which is filled with compressed gas. But. when the breakdown in the electric insulation occurs. it takes much time and economical efforts to repair. Therefore it is very important to diagnose the equipment before the accident. And. in general. UHF and AE signal is the most common transducer to diagnose the state of the power equipment, so, in this investigation, we make a experimental apparatus with aluminum plate and transient analysis with ANSYS to observe the propagation characteristics of AE signal. Through the result of the analysis. we can make a further understanding on the propagation characteristics of AE signal, and get the fundamental skills for the GIS diagnosis.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1799-1802
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• 2002

This paper proposes an improved method for formant frequencies estimation based on the complex autocorrelation function of the speech signal. Instead of using the incoming signal as an input fur the LPC analysis, the analytic signal of the autocorrelation function of the speech signal is computed and itself used as an input for the LPC analysis. Due to the properties of the analytic signal, which occupies half of the bandwidth of the original signal, the required model order for the LPC analysis is halved. The accuracy of the proposed method in noisy environments is examined on five natural vowels. The effectiveness of the proposed method is shown by the estimated spectral shapes and the estimation errors of the formant frequencies.

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.3
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• pp.30-36
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• 1975

Distortions are analyzed and compared for two TDM channel expansion methods- periodic sample skipping and sampling frequency reduction. Signal is assumed to be stationary random signal with zero.mean. Channel noise and interference are not considered in the analysis. For speech signal, it is shown that the periodic sample skipping method could be a better choice under practical design constraints.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.5
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• pp.364-370
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• 2000

A large-signal average model for the controlled on-time boost power factor correction(PFC) circuit is developed and subsequently linearized resulting in a small-signal model for the PFC circuit. Ac analyses are performed using the small-signal model, revealing new results new on small-signal dynamics of the PFC circuit. The analysis results and model predictions are confirmed with experimental measurements on 200W prototype PFC circuit.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.274-277
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• 2001

This paper describes the simulation study, conducted on the propagation characteristics of AE signal. In the case of gas insulation, such as SF6, the equipment is less affected by the environment condition than air insulation, because the component parts of equipment were placed in the enclosure, which is filled with compressed gas. But, when the breakdown in the electric insulation occurs, it takes much time and economical efforts to repair. Therefore it is very important to diagnose the equipment before the accident. And, in general, UHF and AE signal is the most common transducer to diagnose the state of the power equipment, so, in this investigation, we make a experimental apparatus with aluminum plate and transient analysis with ANSYS to observe the propagation characteristics of AE signal. Through the result of the analysis, we can make a further understanding on the propagation characteristics of AE signal, and get the fundamental skills for the GIS diagnosis.

• Journal of the Korean Society for Railway
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• v.4 no.3
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• pp.79-86
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• 2001

The signal pattern recognition method by acoustic emission signal is applied to detect and classify the defects of a journal bearing in a power plant. AE signals of main defects such as overheating, wear and corrosion are obtained from a small scale model. To detect and classify the defects, AE signal pattern recognition program is developed. As the classification methods, the wavelet transformation analysis, the frequency domain analysis and time domain analysis are used. Among three analyses, the wavelet transformation analysis is most effective to detect and classify the defects of the journal bearing..

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.905-910
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• 2008

Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.302-305
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• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and denpends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.