• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.94-101
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• 2019

Most of the existing rail structures have undergone a lot of aging since a considerable period of time has passed from completion. In particular, among existing railway bridges, many of the plate girder bridges are older bridges that have lived 40 to 60 years or more. Since the treadmill is directly connected to the girder without the ballast, the running load of the vehicle is directly transmitted to the bridge. Therefore, the shock and noise applied to the bridge are larger than those of the ballast bridge, and the dynamic shock and vibration are also relatively large. Therefore, it is very urgent to develop appropriate maintenance, repair and reinforcement technology for existing steel plate bridge. In this study, the authors introduced the characteristics of embedded rail (ERS) developed for improving the performance of the existing plate girder bridge and the techniques solving the vibration and noise problems. In order to evaluate the vibration and noise reduction performance of ERS, a non-ballast plate girder bridge with 5m length of sleepers installed and a plate girder bridge with ERS were fabricated. And, then, the vibration response generated under the same excitation condition was measured and analyzed. Also, the radiated noise analysis was performed using the vibration response data obtained from the experiment as the input data of the acoustic analysis model. As a result of experiments and analyses, it was confirmed that the plate girder bridge's vibration using ERS was reduced by 15.0~18.8dB and the average noise was reduced by 7.7dB(A) more than the non-ballast bridge.

• Smart Structures and Systems
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• v.2 no.2
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• pp.127-140
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• 2006

In this study, a wavelet-based covariance-driven system identification technique is proposed for damage assessment of structures under ambient excitation. Assuming the ambient excitation to be a white-noise process, the covariance computation is shown to be able to separate the effect of random excitation from the response measurement. Wavelet transform (WT) is then used to convert the covariance response in the time domain to the WT magnitude plot in the time-scale plane. The wavelet coefficients along the curves where energy concentrated are extracted and used to estimate the modal properties of the structure. These modal property estimations lead to the calculation of the stiffness matrix when either the spectral density of the random loading or the mass matrix is given. The predicted stiffness matrix hence provides a direct assessment on the possible location and severity of damage which results in stiffness alteration. To demonstrate the proposed wavelet-based damage assessment technique, a numerical example on a 3 degree-of-freedom (DOF) system and an experimental study on a three-story building model, which are all under a broad-band excitation, are presented. Both numerical and experimental results illustrate that the proposed technique can provide an accurate assessment on the damage location. It is however noted that the assessment of damage severity is not as accurate, which might be due to the errors associated with the mode shape estimations as well as the assumption of proportional damping adopted in the formulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1677-1688
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• 1998

In this paper, we analyze the performance of a DS-CDMA system employing adaptive adaptive array antenna technology at base-station. For the analysis the receiving architecture of a multiple team adaptive base-station array antenna is proposed as a major system omponent, and signal to interference and noise ratio(SINR) on the proposed architecture is developed. We show that the perfomance enhancement of the CDMA system is represented as great reduction of interfreence by employing an array antenna capable of resolving the angular distribution of the mobile users as seen at the ase-station. The energy associated with each mobile or a group of mobiles is thus confined within the addressed volume, greatly reducing the amount of co-channel interference experienced from and by neighboring co-channel cells. In order to ascertain the benefits of such an antenna, a theoretical approach, which eis based on the conventional and proposed antenna systems in a typical mobile radio environment, is adopted. Finally computer simulation results show the insight into how the adaptive array antenna operates when used in conjunction with DS-CDMA and illustrate the potential benefits in the SINR point of view.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.