• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.1134-1139
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• 2003

Vibration problems are an intrinsic characteristic in a washing machine owing to rotation working mechanism. Therefore, a right comprehension of working principle and the analysis on dynamic behavior of a washing machine is essential to design anti-vibration or vibration reduction. In this paper, we choose two kinds of a washing machine: a suspension type pulsator/drum type washing machine. Each the structure and working principle of a washing machine is discussed briefly and the dynamic behavior of it is investigated, then, the vibration detection problems of transient or excessive vibration is tented in each category. Some vibration experimented results in a washing machine are presented also.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.134-139
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• 2004

The correlation dimension of a nonlinear method for the diagnosis on the clearance of rotating machinery is introduced in this paper. The correlation dimension can provide some intrinsic information of an underlying dynamic system by reconstructing measured scalar time series. Vibration signals measured from a rotor with different operating conditions are analyzed using the correlation dimension. The results show that the correlation dimension method can identify the magnitude of the clearance of a rotor and the lubricating condition.

• Molecules and Cells
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• 제20권2호
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• pp.157-166
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• 2005

The c-myc proto-oncogene encodes a nuclear protein that is deregulated and/or mutated in most human cancers. Acting primarily as an activator and sometimes as a repressor, MYC protein controls the synthesis of up to 10-15% of genes. The key MYC targets contributing to oncogenesis are incompletely enumerated and it is not known whether pathology arises from the expression of physiologic targets at abnormal levels or from the pathologic response of new target genes that are not normally regulated by MYC. Regardless of which, available evidence indicates that the level of MYC expression is an important determinant of MYC biology. The c-myc promoter has architectural and functional features that contribute to uniform expression and help to prevent or mitigate conditions that might otherwise create noisy expression. Those features include the use of an expanded proximal promoter, the averaging of input from dozens of transcription factors, and real-time feedback using the supercoil-deformable Far UpStream Element (FUSE) as physical sensor of ongoing transcriptional activity, and the FUSE binding protein (FBP) as well as the FBP interacting repressor (FIR) as effectors to enforce normal transcription from the c-myc promoter.

• Structural Engineering and Mechanics
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• 제39권6호
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• pp.813-831
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• 2011

This paper presents an efficient version of Hilbert-Huang transform for nonlinear non-stationary systems analyses. An ensemble empirical mode decomposition (EEMD) is introduced to alleviate the problem of mode mixing between intrinsic mode functions (IMFs) decomposed by EMD. Yet the problem has not been fully resolved when a signal of a similar scale resides in different IMF components. Instead of using a trial and error method to select the "best" outcome generated by EEMD, a hybrid algorithm based on EEMD and EMD is proposed for multi-mode signal processing. The developed approach comprises the steps from a bandpass filter design for regrouping modes of the IMFs obtained from EEMD, to the mode extraction using EMD, and to the assessment of each mode in the marginal spectrum. A simulated two-mode signal is tested to demonstrate the efficiency and robustness of the approach, showing average relative errors all equal to 1.46% for various noise levels added to the signal. The developed approach is also applied to a real bridge structure, showing more reliable results than the pure EMD. Discussions on the mode determination are offered to explain the connection between modegrouping form on the one hand, and mode-grouping performance on the other.

• 한국음향학회지
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• 제39권2호
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• pp.77-86
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• 2020

본 연구에서는 날개 끝 와류 공동(Blade-Tip Vortex Cavitation, BTVC)과 이에 기인한 유동 소음을 예측하기 위하여 Eulerian/Lagrangian 연성 해석기법을 제안하였다. 제안한 방법은 크게 연속적인 4단계로 구성되며, 각각 전산유체역학을 이용한 유동장 모사, 와류모델을 이용한 날개 끝 와류의 재구성, 기포 동역학 모델을 이용한 BTVC의 생성, 그리고 음향상사법을 이용한 음향파 예측이다. 일반적으로 전산유체역학 자체가 지니는 고유한 수치감쇠와 과도한 난류 강도로 인해 와류 강도를 심각하게 작게 예측하므로, 유동방향의 날개 끝 와류는 와류모델을 사용하여 재생하였다. 다음으로 Reyleigh-Plesset 방정식에 기반한 기포 동역학 모델을 사용하여 BTVC의 발생과 변화를 모사하였다. 마지막으로 BTVC에 의한 유동소음을 각각의 구형 버블을 그 부피 시간변화율의 변화율에 크기가 비례하는 홀극원으로 모델링하여 예측하였다. 제안한 수치 방법의 유효성을 예측값과 측정값을 비교하여 검토하였다.

• 천문학회지
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• 제46권2호
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• pp.75-91
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• 2013

We estimate the power spectra of the cosmic microwave background radiation (CMB) temperature anisotropy in localized regions of the sky using the Wilkinson Microwave Anisotropy Probe (WMAP) 7-year data. We find that the north and south hat regions at high Galactic latitude ($|b|{\geq}30^{\circ}C$) show an anomaly in the power spectrum amplitude around the third peak, which is statistically significant up to 3. We try to explain the cause of the observed anomaly by analyzing the low Galactic latitude ($|b|$ < $30^{\circ}C$) regions where the galaxy contamination is expected to be stronger, and the regions weakly or strongly dominated byWMAP instrument noise. We also consider the possible effect of unresolved radio point sources. We find another but less statistically significant anomaly in the low Galactic latitude north and south regions whose behavior is opposite to the one at high latitude. Our analysis shows that the observed north-south anomaly at high latitude becomes weaker on regions with high number of observations (weak instrument noise), suggesting that the anomaly is significant at sky regions that are dominated by the WMAP instrument noise. We have checked that the observed north-south anomaly has weak dependences on the bin-width used in the power spectrum estimation, and on the Galactic latitude cut. We also discuss the possibility that the detected anomaly may hinge on the particular choice of the multipole bin around the third peak. We anticipate that the issue of whether or not the anomaly is intrinsic one or due to WMAP instrument noise will be resolved by the forthcoming Planck data.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1812-1824
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• 2016

The neural dynamics underlying the causal network during motor planning or imagery in the human brain are not well understood. The lack of signal processing tools suitable for the analysis of nonlinear and nonstationary electroencephalographic (EEG) hinders such analyses. In this study, noise-assisted multivariate empirical mode decomposition (NA-MEMD) is used to estimate the causal inference in the frequency domain, i.e., partial directed coherence (PDC). Natural and intrinsic oscillations corresponding to the motor imagery tasks can be extracted due to the data-driven approach of NA-MEMD, which does not employ predefined basis functions. Simulations based on synthetic data with a time delay between two signals demonstrated that NA-MEMD was the optimal method for estimating the delay between two signals. Furthermore, classification analysis of the motor imagery responses of 29 subjects revealed that NA-MEMD is a prerequisite process for estimating the causal network across multichannel EEG data during mental tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권4호
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• pp.1441-1456
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• 2015

The bidimensional empirical mode decomposition (BEMD) algorithm with high adaptability is more suitable to process multiple image fusion than traditional image fusion. However, the advantages of this algorithm are limited by the end effects problem, multiscale integration problem and number difference of intrinsic mode functions in multiple images decomposition. This study proposes the multiscale self-coordination BEMD algorithm to solve this problem. This algorithm outside extending the feather information with the support vector machine which has a high degree of generalization, then it also overcomes the BEMD end effects problem with conventional mirror extension methods of data processing,. The coordination of the extreme value point of the source image helps solve the problem of multiscale information fusion. Results show that the proposed method is better than the wavelet and NSCT method in retaining the characteristics of the source image information and the details of the mutation information inherited from the source image and in significantly improving the signal-to-noise ratio.

• Structural Monitoring and Maintenance
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• 제8권4호
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• 한국음향학회지
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• 제34권1호
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• pp.36-45
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• 2015

유동광대역소음을 효율적으로 예측하기 위하여 통계적으로 난류를 재생하는 방법에 대한 많은 연구들이 최근에 진행되고 있다. 그 중에서도, FRPM(Fast Random Particle Mesh) 기법은 RANS(Reynolds-Averaged Navier-Stokes) 방정식 해석을 통해 도출된 정상상태 유동장의 난류 운동에너지와 소산 값을 이용하여 특정한 통계적 특성을 가지는 난류를 재생하는 기법으로서 유동광대역소음 문제 등에 성공적인 적용 예에 대해서 보고되고 있다. 하지만 기존의 FRPM 방법은 축류팬과 같이 축 대칭 특성을 갖는 기계의 경우 정상상태의 유동장을 기초로 광대역소음을 예측하는 문제에는 적용할 수 있으나, 원심팬과 같이 볼루트 영역으로 인하여 축 대칭이 성립되지 않는 기계류의 유동광대역소음에는 적용할 수 없다. 본 연구에서는 이러한 FRPM 기법을 확장하여, 원심팬에서 발생하는 광대역소음을 효율적으로 예측하기 위하여 비정상 RANS 방정식의 수치해와 연계하여 광대역소음원으로 고려되는 난류를 특정한 통계적 특성을 가지도록 재생할 수 있는 U-FRPM(Unsteady-FRPM) 기법을 제안하였다. 먼저 전산유체역학을 사용하여 RANS 방정식을 해석함으로써, 원심팬 주위의 비정상상태 유동장 정보를 도출하고, 음향상사법(Acoustic Analogy)을 기초로 도출된 유동소음원을 U-FRPM을 이용하여 모델링하였다. 모델링된 소음원은 경계요소법을 통해 구현되는 선형음향전파모델과 연계하여 수음점에서 광대역소음을 예측하는데 이용되었다. 예측된 결과와 실험결과의 비교를 통해 본 논문에서 제시한 방법의 유효성을 확인하였다.