• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.2 s.95
• /
• pp.192-198
• /
• 2005

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.699-704
• /
• 2004

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The result by EMD method which has used only output vibration data is almost identical to the result by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• 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.

• Bulletin of the Korean Chemical Society
• /
• v.12 no.3
• /
• pp.309-315
• /
• 1991

The thermal transport coefficients-the self-diffusion coefficient, shear viscosity, and thermal conductivity-of liquid argon at 94.4 K and 1 atm are calculated by non-equilibrium molecular dynamics (NEMD) simulations of a Lennard-Jones potential and compared with those obtained from Green-Kubo relations using equilibrium molecular dynamics (EMD) simulations and with experimental data. The time-correlation functions-the velocity, pressure, and heat flux auto-correlation functions-of liquid argon obtained from the EMD simulations show well-behaved smooth curves which are not oscillating and decaying fast around 1.5 ps. The calculated self-diffusion coefficient from our NEMD simulation is found to be approximately 40% higher than the experimental result. The Lagrange extrapolated shear viscosity is in good agreement with the experimental result and the asymptotic formula of the calculated shear viscosities seems to be an exponential form rather than the square-root form predicted by other NEMD studies of shear viscosity. The agreement for thermal conductivity between the simulation results (NEMD and EMD) and the experimental result is within statistical error. In conclusion, through our NEMD and EMD simulations, the overall agreement is quite good, which means that the Green-Kubo relations and the NEMD algorithms of thermal transport coefficients for simple liquids are valid.

• Structural Monitoring and Maintenance
• /
• v.8 no.4
• /
• pp.379-402
• /
• 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.

• Korean Journal of Materials Research
• /
• v.22 no.12
• /
• pp.717-721
• /
• 2012

Manganese dioxide ($MnO_2$) is one of the most important cathode materials used in both aqueous and non-aqueous batteries. The $MnO_2$ polymorph that is used for lithium primary batteries is synthesized either by electrolytic (EMD-$MnO_2$) or chemical methods (CMD-$MnO_2$). Commonly, electrolytic manganese dioxide (EMD) is used as a cathode mixture material for dry-cell batteries, such as a alkaline batteries, zinc-carbon batteries, rechargeable alkaline batteries, etc. The characteristics of lithium/manganese-dioxide primary cells fabricated with EMD-$MnO_2$ powders as cathode were compared as a function of the parameters of a manufacturing process. The flexible primary cells were prepared with EMD-$MnO_2$, active carbon, and poly vinylidene fluoride (PVDF) binder (10 wt.%) coated on an Al foil substrate. A cathode sheet with micro-porous showed a higher discharge capacity than a cathode sheet compacted by a press process. As the amount of EMD-$MnO_2$ increased, the electrical conductivity decreased and the electrical capacity increased. The cell subjected to heat-treatment at $200^{\circ}C$ for 1 hr showed a high discharge capacity. The flexible primary cell made using the optimum conditions showed a capacity and an average voltage of 220 mAh/g and 2.8 V, respectively, at $437.5{\mu}A$.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.10
• /
• pp.159-168
• /
• 2022

The time series of foreign trade turnover is complex and variable and contains linear and nonlinear information. This paper proposes preprocessing the dataset by the EMD algorithm and combining the linear prediction advantage of the SARIMA model with the nonlinear prediction advantage of the EMD-LSTM model to construct the SARIMA-EMD-LSTM hybrid model by the weight assignment method. The forecast performance of the single models is compared with that of the hybrid models by using MAPE and RMSE metrics. Furthermore, it is confirmed that the weight assignment approach can benefit from the hybrid models. The results show that the SARIMA model can capture the fluctuation pattern of the time series, but it cannot effectively predict the sudden drop in foreign trade turnover caused by special reasons and has the lowest accuracy in long-term forecasting. The EMD-LSTM model successfully resolves the hysteresis phenomenon and has the highest forecast accuracy of all models, with a MAPE of 7.4304%. Therefore, it can be effectively used to forecast the Sino-Russia foreign trade turnover time series post-epidemic. Hybrid models cannot take advantage of SARIMA linear and LSTM nonlinear forecasting, so weight assignment is not the best method to construct hybrid models.

• Journal of Positioning, Navigation, and Timing
• /
• v.2 no.1
• /
• pp.67-74
• /
• 2013

In this study, a remote controller was designed using localization technique. The designed remote controller system consists of infrared transmit/receive module for time synchronization, ultrasonic transmit/receive module for measuring the TOA value, and micro-controller for processing the measured data value. For the position estimation method of remote controller, the Savarese method was used which does not have a problem of diverging solution depending on initial value. The noise included in the measured value was removed by separating the signal and noise with the use of EMD method which is the non-stationary signal analysis technique. The designed system was tested by constructing a simulation environment, and the improvement of accuracy and precision for the application of EMD method was examined.

• Journal of Magnetics
• /
• v.19 no.4
• /
• pp.378-384
• /
• 2014

Optimization design and robust design are significant measures for improving the performance and reliability of electromagnetic devices (EMDs, specifically refer to relays, contactors in this paper). However, the implementation of the above-mentioned design requires substantial calculation; consequently, on the premise of guaranteeing precision, how to improve the calculation speed is a problem that needs to be solved. This paper proposes a new method for establishing an approximate model for the EMD. It builds a relationship between the input and output of the EMD with different coil voltages and air gaps, by using a user-defined interpolating function. The coefficient of the fitting function is determined based on a quantum particle swarm optimization (QPSO) method. The effectiveness of the method proposed in this paper is verified by the electromagnetic force calculation results of an electromagnetic relay with permanent magnet.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.7
• /
• pp.1047-1055
• /
• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.