• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.496-499
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• 2008

The noise reducing devices installed on the noise barrier have been developed in many shapes and ways to reduce noise around road traffic areas. In this study, test and estimation method for the noise reducing device witch installed on the top of a noise barrier was suggested. For this, the authors have considered sound power flow around the device and sound pressure levels for the far field area. To estimate the area effect behind the barrier, area average of noise pressure level difference divided by two area, upper and bellow the sight-line. Comparing the attenuation difference of these areas, the tendency of noise reduction effect was studied according to type of noise reducing devices. Compared with noise shielding efficiency of the devices that using equivalent height of a simple barrier calculated by the SoundPlan, the commercial environment noise simulation software.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1043-1050
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• 2011

This paper presents practical results for the estimation of vibration level inside a powertrain based on the rigid body theory and measurement. The vibration level of inside powertrain has been used for the calculation of excitation force of an engine indirectly. However it was difficult to estimate or measure the vibration level inside of a powertrain when a powertrain works on the driving condition of a vehicle. To do this work, the rigid body theory is employed. At the first, the vibration on the surface of a powertrain is measured and its results are secondly used for the estimation the vibration level inside of powertrain together with rigid body theory. Also did research on how to decrease the error rate when the rigid body theory is applied. This method is successfully applied to the estimation of the vibration level on arbitrary point of powertrain on the driving condition at the road.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.17-20
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• 2008

An Electric motor is used for user-friendly equipment in vehicles. In this paper, an electric motor for windows is considered for the tunning of engineering inspection concerned with noise level from it. Noise from the electric window motor is a kind of structure-borne noise and becomes a reference parameter for its engineering performance. Estimation of noise from the motors shows the quantitative values such as overall noise. Noise level at each frequency and the qualitative figures for the transient characteristics of sound are also revealed. The loudness level, one of the qualitative parameters, distinguishes the performances of every components by the comparison of its magnitude. In summary, it is found that the qualitative comparisons become useful means for the inspection of electric motors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.120-125
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• 2009

For effective noise removal prior to video processing, noise power or noise variance of an input video sequence needs to be found exactly, but it is actually a very difficult process. This paper presents an accurate noise variance estimation algorithm based on motion compensation between two adjacent noisy pictures. Firstly, motion estimation is performed for each block in a picture, and the residue variance of the best motion-compensated block is calculated. Then, a noise variance estimate of the picture is obtained by adaptively averaging and properly scaling the variances close to the best variance. The simulation results show that the proposed noise estimation algorithm is very accurate and stable irrespective of noise level.

• Journal of Advanced Navigation Technology
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• v.2 no.2
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• pp.75-83
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• 1998

This paper presents a low cost and high accuracy integrated Global Positioning System (GPS)/dead reckoning (DR) system. The integrated GPS/DR system is capable of providing highly accurate position data in real-time or in post processing. Based on the analysis of the main error source affecting the DR measurements, an eight-state mathematical model for the integrated system has been developed to represent these errors. This eight-state model has been used to build a nonlinear filter for the estimation of the state vector at every epoch when DR measurements are available. The accuracy of the system has been evaluated using 1Hz DR measurements and 3Hz continuous GPS position estimates. Through numerical simulation the system performance during periods with GPS outage has been investigated by comparing two different noise models. While one model is the position estimation filter containing a single noise model, the other filter includes two-level noise model. The simulation results have shown that the estimation filter containing two-level noise model for computing the position error of the integrated GPS/DR system yields better performance than that the filter including the single-level noise model does.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.38-46
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• 2005

The destructive method is reliable and widely used for the estimation of material degradation but it have time-consuming and a great difficulty in preparing specimens from in-service industrial facilities. Therefore, the estimation of degraded structural materials used at high temperature by nondestructive evaluation such as electric resistance method, replica method, Barkhausen noise method, electro-chemical method and ultrasonic method are strongly desired. In this study, various nondestructive evaluation(NDE) parameters of the Barkhausen noise method, such as MPA(Maximum Peak Amplitude), RMS, IABNS(Internal Area of Barkhausen Noise on Signal) and average amplitude of frequency spectrum are investigated and correlated with thermal damage level of 2.25cr-1.0Mo steel using wavelet analysis. Those parameters tend to increase while thermal degradation proceeds. It also turns out that the wavelet technique can help to reduce experimental false call in data analysis.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.581-588
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• 2002

Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1045-1049
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• 2001

Before building houses or apartments, we need to predict noise propagation to eliminate possible noise problems to residents. However, we do not try to predict noise propagation during estimation of noise effect for the developing area since we did not have a good mathematical model to predict noise level due to a traffic noise. In this article, an adequate mathematical model has been developed and proved to predict noise effect to living area due to a traffic noise.