• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.75-78
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• 1997

In this paper we present new sound spectral analysis methods or prosthetic heart valve sounds. Phonocardiograms(PCG) of prosthetic heart valve were analyzed in order to derive frequency domain feature suitable or the classification of the valve state. The fast orthogonal search method and MUSIC (MUltiple SIgnal Classification) method are described or finding the significant frequencies in PCG. The fast orthogonal search method is effective with short data records and cope with noisy, missing and unequally-spaced data. MUSIC method's key to the performance is the division of the information in the autocorrelation matrix or the data matrix into two vector subspaces, one a signal subspace and the other a noise subspace.

• Speech Sciences
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• v.4 no.2
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• pp.41-54
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• 1998

Speech signals are, depending on the characteristics of waveform, classified as voiced sound, unvoiced sound, and silence. Voiced sound, produced by an air flow generated by the vibration of the vocal cords, is quasi-periodic, while unvoiced sound, produced by a turbulent air flow passed through some constriction in the vocal tract, is noise-like. Silence represents the ambient noise signal during the absence of speech. The need for deciding whether a given segment of a speech waveform should be classified as voiced, unvoiced, or silence has arisen in many speech analysis systems. In this paper, a voiced/unvoiced/silence classification algorithm using spectral change in the wavelet transformed signal is proposed and then, experimental results are demonstrated with our discussions.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.310-312
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• 2004

The aim of this study was to analyze the characteristics of knee joint sound in frequency domain and classify the knee joint diseases. The spectral analysis of knee joint sounds was performed using LPC(Linear Predictive Coding) and Wigner-Ville distribution. Ten normal subjects and 5 patients with meniscal tearing were enrolled. Each subject was seated on a chair and underwent active knee flexion and extension for 60 seconds. Sampling frequency was 10kHz and electronic stethoscope and electro-goniometer were applied during the knee motion for data collection. The spectral analysis showed 3 peaks in both groups and the difference energy distribution in time-frequency domain. These results suggest that the diagnosis of knee joint pathology using the auscultation could be easier and more correct.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.189-195
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• 2003

This paper represents an identification procedure for leading mechanism of a car A/V system which is composed of a DC motor and a set of plastic gears. In addition, we studied dominant noise source of rattle noise generated by external forced vibration as a car drives. we made a dynamometer to produce stationary operation on loading mechanism of A/V system because noise generated by actual loading mechanism is non-stationary signal. operating the dynamometer setup at various motor speeds, sound pressure spectra are measured and the results are analyzed. its dominant noise source is also identified by using a sound Intensity technique. we made use of multi-dimensional spectral analysis to rind a dominant rattle noise. this method is so useful to eliminate coherence between vibration sources and helps us obtain coherent output spectrum of individual vibration source which make a rattle noise.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.40-49
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• 1996

With the advance of the standard of living, the demand on automobile goes beyond the simple transportion equipment, therefore the interior noise reduction has been the important factor for improvement of the ride quality. Idling noise is a major vehicle characteristic determining occupant comfort. In the present research two approaches for noise source identification based on theory for multi-input system have been investigated. The concept of the frequency response function and the multi-dimensional spectral analysis were used to estimated the spectra of the noise source.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Journal of Drive and Control
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• v.13 no.2
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• pp.19-25
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• 2016

Recently, drivers have begun to regard comfort in the cabin as one of the most important factors in construction equipment like forklifts. Accordingly, it has become more important to design a forklift cabin with a better sound quality as well as lower sound level, which can make a driver more comfortable. In this paper, the correlation between subjective evaluation and Zwicker's sound quality index was analyzed through a blind test by a few workers in forklifts and other construction equipment in several countries. Correlation analysis showed that Loudness and Sharpness were ranked in sequence, and tendencies were different from country to country. Also, contribution analysis for Loudness and Sharpness using operational transfer path analysis (OTPA), which is widely used in the field of noise, vibration, and harshness (NVH), was performed. However, Loudness and Sharpness cannot be used with OTPA directly because there are no linear relationships between the sources and receivers. In this paper, both are calculated by applying the DIN 45631 method with a contribution rate (%) of 1/3 Octave Sound Pressure Level by OTPA method in addition to considering spectral masking.

• Journal of Sensor Science and Technology
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• v.24 no.4
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• pp.247-251
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• 2015

In this study, electroglottographic spectral tilt (EST) was investigated for characterization of vocal cords vibration. EST was analyzed from the power spectrum of electroglottographic signals by dividing frequency analysis range as full range (0~4 octave), low range (0~2 octave), and high range (2~4 octave). EST of all ranges in female were greater than those in male. In female and male groups, EST of high range was higher than that of low range. This result suggests that EST has at least two components and dividing frequency range in analysis of EST is effective for investigating characteristics of vocal cords vibration.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.629-633
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• 2005

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to $R^2$ value and F-value. And testing for regression model is necessary to Independence, Homoscedesticity and Normality. Also we selected optimum layout of damping material using Taguchi method. As a result of application, sound quality is improved by more quiet, powerful, expensive, smooth.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.6 s.249
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• pp.728-733
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• 2006

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to $R^2$ value and F-value. And testing for regression model is necessary to independence, homoscedesticity and normality. Also we selected optimum layout of damping material using Taguchi method. As a result of application, sound quality is improved more quietly, powerfully, even though costly, and smoothly.