• Wind and Structures
• /
• 제9권6호
• /
• pp.441-455
• /
• 2006

A more applicable optimization model for extracting flutter derivatives of bridge decks is presented, which is suitable for time-varying weights for fitting errors and different lengths of vertical bending and torsional free vibration data. A stochastic search technique for searching the optimal solution of optimization problem is developed, which is more convenient in understanding and programming than the alternate iteration technique, and testified to be a valid and efficient method using two numerical examples. On the basis of the section model test of Sutong Bridge deck, the flutter derivatives are extracted by the stochastic search technique, and compared with the identification results using the modified least-square method. The Empirical Mode Decomposition method is employed to eliminate noise, trends and zero excursion of the collected free vibration data of vertical bending and torsional motion, by which the identification precision of flutter derivatives is improved.

• Smart Structures and Systems
• /
• 제19권2호
• /
• pp.137-149
• /
• 2017

Under the interference of the temperature effect, the alternation of cable force due to damages of a cable-stayed bridge could be difficult to distinguish. Considering the convenience and applicability in engineering practice, simple air or cable temperature measurements are adopted in the current study for the exclusion of temperature effect from the variation of cable force. Using the data collected from Ai-Lan Bridge located in central Taiwan, this work applies the ensemble empirical mode decomposition to process the time histories of cable force, air temperature, and cable temperature. It is evidently observed that the cable force and both types of temperature can all be categorized as the daily variation, long-term variation, and high-frequency noise in the order of decreasing weight. Moreover, the correlation analysis conducted for the decomposed variations of all these three quantities undoubtedly indicates that the daily and long-term variations with different time shifts have to be distinguished for accurately evaluating the temperature effect on the variation of cable force. Finally, consistent results in reducing the range of cable force variation after the elimination of temperature effect confirm the validity and stability of the developed method.

• Journal of Electrical Engineering and Technology
• /
• 제12권6호
• /
• pp.2166-2176
• /
• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• Ocean Systems Engineering
• /
• 제6권3호
• /
• pp.217-231
• /
• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• 인터넷정보학회논문지
• /
• 제11권2호
• /
• pp.99-107
• /
• 2010

본 연구에서는 디지털 영상의 블라인드 워터마킹 알고리즘을 제안하였다. 제안한 알고리즘은 웨이블릿 평면에서 처리되는 변환 평면 워터마킹 알고리즘으로서 2차원 EMD을 이용하여 분해된 워터마크의 EMF 성분들이 웨이블릿 대역에 삽입되어, 각 웨이블릿 대역은 워터마크의 일부 정보만을 포함하고 있는 것을 특징으로 하고 있다. 워터마크의 추출은 각 웨이블릿 대역에서 추출한 워터마크의 일부 정보들을 2차원 EMD의 선형적인 특징에 의해 산술적 또는 논리적 연산을 통하여 회복할 수 있도록 하였다. 개발한 워터마킹 알고리즘은 비가시성, 강인성 등 워터마킹 알고리즘에서 요구되는 조건들에 대한 실험을 수행하여 성능을 비교 분석하였다.

• 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.

• 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.

• 대한토목학회논문집
• /
• 제38권4호
• /
• pp.579-586
• /
• 2018

단기 통행속도 예측을 위해 데이터 기반 비모수적 기법들을 활용한 다양한 연구들이 수행되고 있다. 그럼에도 교통신호 및 교차로로 인한 복잡한 동적 특성을 가지는 도시부의 예측 연구는 상대적으로 부족한 실정이다. 본 연구는 도시부 통행 속도를 예측하기 위해 앙상블 경험적 모드 분해법(EEMD)과 인공신경망(ANN)을 이용한 하이브리드 접근법을 제안하는 것을 목적으로 한다. EEMD는 통행속도의 시계열 자료를 고유모드함수(IMF)와 오차항으로 분해한다. 분해된 IMF는 시간단위의 국지적 특성을 반영하며, ANN을 통해 개별적으로 예측된다. IMF는 원본데이터가 가진 비선형성, 비정상성, 진동 등의 복잡성을 완화하기 때문에, 원래의 통행속도에 비하여 더 정확하게 예측될 수 있다. 예측된 IMF들은 합산되어 예측 통행속도를 표현한다. 본 연구에서 제시된 방법을 검증하기 위하여 대구시의 DSRC로부터 구득된 통행속도 데이터가 활용된다. 성능평가는 도시부 링크 중 특히 예측이 어려운 지점에 대해 수행되었으며, 분석 결과 제시된 모형은 15분 후 예측에 대해 각각 평상시 10.41%, 와해상태시 25.35%의 오차율을 가지며, 단순 ANN 기법에 비하여 우수한 성능을 보이는 것으로 확인된다. 본 연구에서 개발된 모형은 도시교통관리체계의 신뢰성 있는 교통정보를 제공하는 데에 기여할 수 있을 것으로 기대된다.

• 한국공간구조학회논문집
• /
• 제20권2호
• /
• pp.77-85
• /
• 2020

This paper examined the dynamic instability of a shallow arch according to the response characteristics when nearing critical loads. The frequency changing feathers of the time-domain increasing the loads are analyzed using Fast Fourier Transformation (FFT), while the response signal around the critical loads are analyzed using Hilbert-Huang Transformation (HHT). This study reveals that the models with an arch shape of h = 3 or higher exhibit buckling, which is very sensitive to the asymmetric initial conditions. Also, the critical buckling load increases as the shape increases, with its feather varying depending on the asymmetric initial conditions. Decomposition results show the decrease in predominant frequency before the threshold as the load increases, and the predominant period doubles at the critical level. In the vicinity of the critical level, sections rapidly manifest the displacement increase, with the changes in Instantaneous Frequency (IF) and Instant Energy (IE) becoming apparent.

• 한국수자원학회논문집
• /
• 제49권3호
• /
• pp.207-215
• /
• 2016

본 연구에서는 우리나라 강수 및 기온과 다양한 기상인자와의 교차상관관계 분석을 통해 대규모 기후변동이 우리나라에 어떠한 영향을 주는지를 분석하였다. 강수 및 기온자료의 경우 앞선 연구인 "경험적 모드분해법을 이용한 기상인자와 우리나라 강수 및 기온의 상관관계 분석 : I. 자료의 분해 및 특성분석"의 연구결과를 통해 주기성, 경향성에 따라 분해한 강수 및 기온자료의 내재모드함수를 사용하여, 자료의 변동이 심하고 잡음이 포함된 원 자료를 통한 상관관계 분석보다 좀 더 명확한 상관계수를 계산하였다. 이렇게 분해된 기상자료와 기상인자간의 교차상관관계 분석을 통해 그 시간차와 상관계수를 계산하여, 주기성과 경향성 측면에서 어떠한 상관관계가 있는지를 분석하였다. 그 결과 주기성 측면에서 엘니뇨현상에 의한 기후변동이 우리나라 기상현상과 밀접한 관련이 있으며, 경향성 측면에서 기후변화로 인한 해수면 온도 증가추세가 우리나라 기상현상과 밀접한 연관이 있음을 알 수 있었다.