• Nuclear Engineering and Technology
• /
• 제38권4호
• /
• pp.343-352
• /
• 2006

Convenient analytical tools for evaluation of the aperiodic and the fluctuating instabilities of the passive residual heat removal system (PRHRS) of an integral reactor are developed and results are discussed from the viewpoint of the system design. First, a static model for the aperiodic instability using the system hydraulic loss relation and the downcomer feedwater heating equations is developed. The calculated hydraulic relation between the pressure drop and the feedwater flow rate shows that several static states can exist with various numbers of water-mode feedwater module pipes. It is shown that the most probable state can exist by basic physical reasoning, that there is no flow rate through the steam-mode feedwater module pipes. Second, a dynamic model for the fluctuating instability due to steam generation retardation in the steam generator and the dynamic interaction of two compressible volumes, that is, the steam volume of the main steam pipe lines and the gas volume of the compensating tank is formulated and the D-decomposition method is applied after linearization of the governing equations. The results show that the PRHRS becomes stabilized with a smaller volume compensating tank, a larger volume steam space and higher hydraulic resistance of the path $a_{ct}$. Increasing the operating steam pressure has a stabilizing effect. The analytical model and the results obtained from this study will be utilized for PRHRS performance improvement.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.475-476
• /
• 2007

Electroglottography (EGG) is a technique used to register laryngeal behavior indirectly by a measuring the change in electrical impedance across the throat during speaking. However, EGG waveform is affected by laryngeal muscles which fluctuate the vocal cords, and which result in baseline wander. It is required to reduce baseline wander in EGG waveform, because EGG waveform is used for input signal of nonlinear speech synthesizer in next chapter. In vocal cords, the abduction-adduction of glottis is mainly controlled by the posterior cricoarytenoid (abductor) and interarytenoid (adductor) muscles respectively. Empirical Mode Decomposition method was adopted in cancellation of EGG waveform baseline wandering, and showd better performance than that of high pass filter with 500 order.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2015년도 학술발표회
• /
• pp.153-153
• /
• 2015

최근 지구온난화와 같은 기후변화로 인한 기상이변으로 홍수, 태풍 등이 빈번히 발생하면서 지면서 그로 인한 피해도 점점 증가하고 있으며, 이러한 기상 이변으로 인한 피해를 최소화 하기 위하여 기후변화가 수문량에 미치는 영향에 대한 연구가 활발히 진행되고 있다. 그 중, 기후변화로 인한 강수현상의 변화를 분석하기 위한 방법 중 하나로 강수 현상이 주변 기후 요소의 분포에 영향을 받으며, 이를 바탕으로 강수현상에 영향을 미치는 기상인자를 통하여 강수를 분석하는 방법이 있다. 동으로는 태평양을 마주한 아시아 대륙 끝에 위치한 우리나라의 지형적 특성상, 강수 현상에 있어 대륙과 해양의 영향을 모두 받은 위치에 있다. 따라서 우리나라의 강수현상에 영향을 미치는 기상인자를 분석할 경우 대륙에서의 기상변화를 반영한 기상인자와 더불어 태평양에서의 기상변화를 반영한 모든 기상인자를 적용할 필요가 있다고 판단되어 본 연구를 수행하였다. 본 연구에서는 우리나라 자료기간이 30년 이상인 주요 지점의 강수량 자료를 바탕으로 Empirical Mode Decomposition(EMD)을 이용하여 과거의 기후변화에 따른 강수량 변동성과 경향성에 대하여 분석하고, 이를 다양한 기상인자와의 지연상관관계를 분석함으로써, 기후변화에 따른 우리나라 강수량의 변동이 어느 요소에 민감한지를 판단해 보고, 상관관계가 높은 지연개월 수를 판단하여기상인자를 통한 강수량의 예측 가능성을 제시 하고자 한다.

• 한국철도학회논문집
• /
• 제17권5호
• /
• pp.321-327
• /
• 2014

본 연구에서는 구속된 다물체계의 비선형 운동방정식으로부터 QR분해법을 이용하여 선형 운동방정식을 유도하는 방법을 제시하였다. 다물체계의 선형 진동 방정식을 철도차량 대차에 적용하여 대차의 고유 진동모드를 구하고 레일의 변위 입력에 대한 대차프레임의 전달 함수를 구하여 대차의 진동 특성을 분석하였다. 대차의 고유 모드는 35Hz이하에서 나타났고 198Hz이상에서 국부모드가 계산되었다. 대차 프레임의 수직변위 전달함수는 수직변위 모드와 피치 모드가 속도에 영향을 받기 때문에 속도에 따라 변화하는 것으로 나타났다. 횡방향 전달함수는 매우 작게 나타났으며 전후방향 전달함수는 속도에 관계없이 전후방향 변위 모드가 주로 가진되는 것으로 나타났다.

• Steel and Composite Structures
• /
• 제25권2호
• /
• pp.231-244
• /
• 2017

This paper presents the structural identification of an arch dam model for the damaged, repaired and strengthened conditions under different water levels. For this aim, an arch dam-reservoir-foundation model has been constructed. Ambient vibration tests have been performed on the damaged, repaired and strengthened dam models for the empty reservoir (0 cm), 10 cm, 20 cm, 30 cm, 40 cm, 50 cm and full reservoir (60 cm) water levels to illustrate the effects of water levels on the dynamics characteristics. Enhanced Frequency Domain Decomposition Method in the frequency domain has been used to extract the dynamic characteristics. The dynamic characteristics obtained from the damaged, repaired and strengthened dam models show that the natural frequencies and damping ratios are considerably affected from the varying water level. The maximum differences between the frequencies for the empty and full reservoir are obtained as 16%, 33%, and 25% for damaged, repaired and strengthened model respectively. Mode shapes obtained from the all models are not affected by the increasing water level. Also, after the repairing and strengthening implementations, the natural frequencies of the arch dam model increase significantly. After strengthening, between 46-92% and 43-62% recovery in the frequencies are calculated for empty and full reservoir respectively. Apparently, after strengthening implementation, the mode shapes obtained are more acceptable and distinctive compared to those for the damaged model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권8호
• /
• pp.3862-3879
• /
• 2019

More and more problems for public security have occurred due to the limited solutions for drone detection especially for micro-drone in long range conditions. This paper aims at dealing with drones detection using a radar system. The radio frequency (RF) signals emitted by a controller can be acquired using the radar, which are usually too weak to extract. To detect the drone successfully, the static clutters and linear trend terms are suppressed based on the background estimation algorithm and linear trend suppression. The principal component analysis technique is used to classify the noises and effective RF signals. The automatic gain control technique is used to enhance the signal to noise ratios (SNR) of RF signals. Meanwhile, the empirical mode decomposition (EMD) based wavelet transform (WT) is developed to decrease the influences of the Gaussian white noises. Then, both the azimuth information between the drone and radar and the bandwidth of the RF signals are acquired based on the statistical analysis algorithm developed in this paper. Meanwhile, the proposed accumulation algorithm can also provide the bandwidth estimation, which can be used to make a decision accurately whether there are drones or not in the detection environments based on the probability theory. The detection performance is validated with several experiments conducted outdoors with strong interferences.

• Smart Structures and Systems
• /
• 제31권2호
• /
• pp.155-169
• /
• 2023

The quasi-static component of the moving vehicle-induced dynamic response is promising in damage detection as it is sensitive to bridge damage but insensitive to environmental changes. However, accurate extraction of quasi-static component from the dynamic response is challenging especially when the vehicle velocity is high. This paper proposes an adaptive quasi-static component extraction method based on the modified variational mode decomposition (VMD) algorithm. Firstly the analytical solutions of the frequency components caused by road surface roughness, high-frequency dynamic components controlled by bridge natural frequency and quasi-static components in the vehicle-induced bridge response are derived. Then a modified VMD algorithm based on particle swarm algorithm (PSO) and mutual information entropy (MIE) criterion is proposed to adaptively extract the quasi-static components from the vehicle-induced bridge dynamic response. Numerical simulations and real bridge tests are conducted to demonstrate the feasibility of the proposed extraction method. The results indicate that the improved VMD algorithm could extract the quasi-static component of the vehicle-induced bridge dynamic response with high accuracy in the presence of the road surface roughness and measurement noise.

• 감성과학
• /
• 제18권1호
• /
• pp.15-26
• /
• 2015

본 논문에서는 경험적 모드 분해 방법을 이용하여 시각자극 출현에 따른 과제 수행 시 발생하는 뇌 유발전위의 ${\theta}$와 ${\alpha}$대역에 대한 진폭과 위상변화를 확인하였다. 과제수행에 대한 뇌 유발전위를 구성 주파수 대역 별로 분해하기 위하여 경험적 모드 분해 방법을 적용하였고, 분해된 각 내재모드함수에 힐버트 변환을 적용하여 뇌 유발전위의 ${\theta}$와 ${\alpha}$대역의 순간 진폭과 위상 변화를 확인하였다. 과제 수행 시 뇌 유발전위의 P2, N2과 P3지점에서 ${\theta}$와 ${\alpha}$대역의 진폭이 크게 관찰되었으며, N1, P2부근에서 순간 위상의 변화가 최대가 되었다. 시각 자극 출현에 따른 응시 상태에서는 두 대역 모두 관련된 위상 변화시점이 확인되지 않았다. 대역통과필터 방법 적용 시, 경험적 모드 분해 방법에 비해 시간과 주파수 해상도가 떨어졌으며, 필터의 파라미터에 따라 위상 변화 시점의 결과에 차이가 발생하였다. 연구를 통해 ${\theta}$와 ${\alpha}$대역이 시각 자극 출현에 따른 과제 수행에 대한 뇌 유발전위의 주요성분인 ${\theta}$와 ${\alpha}$대역의 위상변화와 뇌 유발전위의 생성을 위상 변화와 연관 지어 해석하였다.

• International Journal of Control, Automation, and Systems
• /
• 제3권2호
• /
• pp.217-224
• /
• 2005

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system because the UFV contains both pitch and depth angle variables as well as multiple control planes, it requires robustness because of the possibility that it may encounter uncertainties such as parameter variations and disturbances, it requires a continuous control input because the system that has reduced power consumption and acoustic noise is more practical, and further, it has the speed dependency of controller parameters because the control forces of control planes depend on the operating speed. To solve these problems, an adaptive fuzzy sliding mode controller (AFSMC), which is based on the decomposition method using expert knowledge in the UFV depth control and utilizes a fuzzy basis function expansion (FBFE) and a proportional integral augmented sliding signal, is proposed. To verify the performance of the AFSMC, UFV depth control is performed. Simulation results show that the AFSMC solves all problems experienced in the UFV depth control system online.

• 한국소음진동공학회논문집
• /
• 제24권8호
• /
• pp.636-642
• /
• 2014

The sensor configuration of the magnetostrictive guided wave system can be described as a single continuous transducing element which makes it difficult to separate the individual modes from the reflected signal. In this work we develop the mode decomposition technique employing chirplet transform, which is able to separate the individual modes from dispersive and multimodal waveform measured with the magnetostrictive sensor, and to estimate the time-frequency centers and individual energies of the reflection, which would be used to locate and characterize defects. The reflection coefficients are calculated using the modal energies of the separated mode. Results from experimental results on a carbon steel pipe are presented, which show that the accurate and quantitative defect characterization could become enabled using the proposed technique.