• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.12
• /
• pp.2476-2484
• /
• 2015

Narrow band signal estimation and broad band signal estimation can be used to detect the ship-radiated noise. The broad band signal estimation method to detect the ship-radiated noise is called DEMON (Detection of Envelop Modulation On Noise). This paper proposes a new DEMON algorithm applying compressed sensing algorithm to filter bank and autocorrelation. We show the proposed algorithm estimates the hidden period in the wide band signal better than the conventional DEMON algorithm and the recently proposed filter-bank based DEMON algorithm. Especially we show that the proposed algorithm needs shorter data length than the conventional DEMON algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.7
• /
• pp.1262-1269
• /
• 2002

It is inevitable to evaluate the life of turbine rotor because the operating periods of power plants need to be extended. For the test, seven kinds of specimens with different degradation levels were prepared by the isothermal heat treatment at $630^{\circ}C$. Magnetic methods utilizing Barkhausen noise coercive force($BN_c$) were applied to detect the degradation caused by thermal aging. Magnetic property of material is related with domain dynamics and that is affected by the microstructure of material. Therefore $BN_c$ is very sensitive to the microstructure change of the material. With the increase of degradation, $BN_c$ was decreased and this phenomenon is considered due to precipitations and grain size. The result was compared with Vickers hardness($H_v$) and coercive force($H_c$) to detect the relative variation, and was related with $H_v$ and YS to estimate the change of the mechanical properties with the degradation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.175-179
• /
• 2007

To existing method which uses energy variation and spectrum deviation to detect the underwater transient signal is useful to detect white noise environment, but it is not useful to do colored noise environment. To improve capacity of detecting the underwater transient signal both in white noise environment and colored noise environment, this study takes advantage of Double Density Discrete Wavelet Transform and CFAR Power-Law.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39B no.8
• /
• pp.538-543
• /
• 2014

Narrow band signal estimation and broad band signal estimation can be used to detect the ship-radiated noise. The broad band signal estimation method to detect the ship-radiated noise is called DEMON (Detection of Envelop Modulation On Noise). This paper proposes a new DEMON algorithm using filter bank and autocorrelation. We show the proposed algorithm estimates the hidden period in the wide band signal better than the conventional DEMON algorithm and the recently proposed filter-bank based DEMON algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.64-67
• /
• 2004

Points of sharp variations in images are the most important components when we analyze singularities of images. Therefore a lot of researches for detecting those edges have been continuing even now. However, existing methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. for this reason, this paper detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in noise environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.11a
• /
• pp.229-229
• /
• 2006

WECPNL(Weighted Equivalent Continuous Perceived Noise Level) which designated currently in Domestic 'The Stanrd Method of Measuring Noise and Vibration' is composed of different factor with WECPNL that published in ICAO. Domestic WECPNL is concerned in application of $L_{MAX}$ measurement. On the other hand, ICAO's WECPNL is based on EPNL that includes factors of the pure tone correction and the duration time. NNI and NEF also are each based on PNL and EPNL. Because a military aircraft noise, especially, has the pure tone of high frequency and the irregular duration, it seems to be undesirable to estimate aircraft noise for using Domestic WECPNL. Therefore, this study was performed to detect a flaw of Korean WECPNL, through comparison of the trend of each other aircraft noise index by using equivalent rawdata.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.5
• /
• pp.281-286
• /
• 2013

In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

• Journal of Ocean Engineering and Technology
• /
• v.22 no.1
• /
• pp.30-36
• /
• 2008

Underwater ambient noise originating from geophysical, biological, and man-made acoustic sources contains information on the source and the ocean environment. Such noise affectsthe performance of sonar equipment. In this paper, three steps are used to identify the ambient noise source, detection, feature extraction, and similarity measurement. First, we use the zero-crossing rate to detect the ambient noisesource from background noise. Then, a set of feature vectors is proposed forthe ambient noise source using the Hilbert-Huang transform and the Karhunen-Loeve transform. Finally, the Euclidean distance is used to measure the similarity between the standard feature vector and the feature vector of the unknown ambient noise source. The developed algorithm is applied to the observed ocean data, and the results are presented and discussed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.157.4-157
• /
• 2001

An effective approach to detect and diagnose multiple failures in a dynamic system is proposed for the case where the measurement noise is correlated sequentially in time. It is based on the modified interacting multiple-model (MIMM) estimation algorithm in which a generalized decorrelation process is developed by employing the autoregressive (AR) model for the correlated measurement noise. Numerical example for the nuclear steam generator is provided to illustrate the enhanced performance of the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.4
• /
• pp.72-80
• /
• 1996

In this paper, variable windowing mean filter to remove speckle noise and a measure to detect thin edge in ultrasonic images are proposed. Because ultrasonic images are corrupted by speckle noise showing a granular appearance, good edge detection is difficult. As a result, noise removing filter is needed in preprocessing stage. The speckle noise removing filter is based on mean filter whose window size is changed by the ratio of standard deviation to mean for image signal and noise signal in local area. And the measure expressed the difference of means between tow windows is used for detecting thin edge in filtered image. Results show that variable windowing mean filter removes speckle noise effectively, and proposed measure is useful in detecting thin edge.