• Journal of the Korean Solar Energy Society
• /
• v.37 no.6
• /
• pp.25-37
• /
• 2017

A study on factors influencing measurement error of Ground-based LiDAR(Light Detection And Ranging) system was conducted in Kimnyeong wind turbine test site on Jeju Island. Three properties of wind including inclined angle, turbulence intensity and power law exponent were taken into account as factors influencing the measurement error of Ground-based LiDAR. In order to calculate LiDAR measurements error, 2.5-month wind speed data collected from LiDAR (WindCube v2) were compared with concurrent data from the anemometer on a nearby 120m-high meteorological mast. In addition, data filtering was performed and its filtering criteria was based on the findings at previous researches. As a result, at 100m above ground level, absolute LiDAR error rate with absolute inclined angle showed 4.58~13.40% and 0.77 of the coefficients of determination, $R^2$. That with turbulence intensity showed 3.58~23.94% and 0.93 of $R^2$ while that with power law exponent showed 4.71~9.53% and 0.41 of $R^2$. Therefore, it was confirmed that the LiDAR measurement error was highly affected by inclined angle and turbulence intensity, while that did not much depend on power law exponent.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.4
• /
• pp.78-96
• /
• 2023

Urban traffic information is collected by various systems such as VDS, DSRC, and radar. Recently, with the development of deep learning technology, smart intersection systems are expanding, are more widely distributed, and it is possible to collect a variety of information such as traffic volume, and vehicle type and speed. However, as a result of reviewing related literature, the performance evaluation criteria so far are rbs-based evaluation systems that do not consider the deep learning area, and only consider the percent error of 'reference value-measured value'. Therefore, a new performance evaluation method is needed. Therefore, in this study, individual error, interval error, and overall error are calculated by using a formula that considers deep learning performance indicators such as precision and recall based on data ratio and weight. As a result, error rates for measurement value 1 were 3.99 and 3.54, and rates for measurement value 2 were 5.34 and 5.07.

• Journal of Power Electronics
• /
• v.5 no.2
• /
• pp.129-141
• /
• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• Journal of Industrial Technology
• /
• v.29 no.B
• /
• pp.41-45
• /
• 2009

The new cooling fan for various parts & equipments of KTX is developed and evaluated to improve fan performance and durability. The characteristic curve of the developed fan is obtained according to KSB 6311 of performance test regulation. 70 degree of the installation angle of blade makes the fan to produce a maximum flow rate. This angle is found out through trial-error and is confirmed through the verification test. In order to improve the blade strength, the blade is produced by a draw forming. The adoption of AL50 reduces a fan weight by 6 kg. The new blade makes a static pressure 170 (mmAq), a discharge rate $140(m^3/min)$, a rotational speed 2886 (rpm) at the power 10 kw. which results 54% of the static pressure improvement relative to the original blade.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.3
• /
• pp.19-28
• /
• 1998

This paper is concerned with the implementation of the equalization technique in a DCS 1800 system employing the soft-decision output Viterbi algorithm (SOVA), which makes the hardware complexity comparable to the hard decision MLSE and gives reliable performance. Also, the channel estimation technique with enhances the perfdormance of the soft-decision output equalizer is proposed, and the Viterbi decoder which operates effectively with the soft-decision output of the qualizer is implemented using the Very High Speed ICs Hardware Description Language (VHDL). From the simulation results, it is shown that the implemented Viterbi decoder operates effectively and the SOVA outperforms the hard-decision MLSE in terms of the frame erasure rate (FER) and bit error rate (BER).

• Journal of IKEEE
• /
• v.18 no.4
• /
• pp.502-508
• /
• 2014

This paper has reviewed the performances of various AGCs which can be adopted in IEEE802.11p modems. IEEE802.11p, a high speed mobile communication standard for vehicles, requires high performance signal detector since the channel impulse responses are varied rapidly in time. In order to select the optimal signal detector, we simulated the performances of three detection methods. One is using RSSI signal, the other is using RSSI signal and I/Q signal, and the third is using I/Q signal through the Monte Carlo simulation. We evaluated the performances of the algorithms using our own system based on MAX 2829 transceiver(MAXIM $Integrated^{TM}$) in a real vehicular environment. As a result, the experiment using Fully I/Q signal derives the most excellent performance with the lowest minimum receiver sensitivity, packet error rate (PER) and false alarm rate (FAR).

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.2
• /
• pp.47-53
• /
• 2010

This paper proposed Residual Image detection and Color Info using the face detection technique. The proposed technique was fast processing speed and high rate of face detection on the video. In addition, this technique is to detection error rate reduced through the calibration tasks for tilted face image. The first process is to extract target image from the transmitted video images. Next, extracted image processed by window rotated algorithm for detection of tilted face image. Feature extraction for face detection was used for AdaBoost algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5685-5700
• /
• 2018

Cyber intelligence, surveillance, and reconnaissance (ISR) has become more important than traditional military ISR. An agent used in cyber ISR resides in an enemy's networks and continually collects valuable information. Thus, this agent should be able to determine what is, and is not, useful in a short amount of time. Moreover, the agent should maintain a classification rate that is high enough to select useful data from the enemy's network. Traditional feature selection algorithms cannot comply with these requirements. Consequently, in this paper, we propose an effective hybrid feature selection method derived from the filter and wrapper methods. We illustrate the design of the proposed model and the experimental results of the performance comparison between the proposed model and the existing model.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.10 no.1
• /
• pp.244-254
• /
• 2002

To enhance the acceleration performance and fuel consumption rate of a vehicle, the torque converter is modified or newly-developed with reliable analysis model. Up to recently, the one dimensional performance model has been used for the analysis and design of torque converter. The model is described with constant parameters based on the concept of mean flow path. When it is used in practice, some experiential correction factors are needed to minimize tole estimated error. These factors have poor physical meaning and cannot be applied confidently to the other specification of torque converter. In this study, the detail dynamic model of torque converter is presented to establish the physical meaning of correction factors. To verify the validity of model, performance test was carried out with various input speed and oil temperature. The effect of oil temperature on the performance is analysed, and it is applied to the dynamic model. And, to obtain the internal flow pattern of torque converter, CFD(Computational Fluid Dyanmics) analysis is carried out on three-dimensional turbulent flow. Correction factors are determined from the internal flow pattern, and their variation is presented with the speed ratio of torque converter. Finally, the sensitivity of correction factors to the speed ratio is studied for the case of changing capacity factor with maintaining torque ratio.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.519-528
• /
• 2016

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.