• Journal of Biosystems Engineering
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• v.41 no.2
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• pp.67-74
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• 2016

Purpose: Many tractors have adopted the horizontal control system designed to maintain the three-point mounted implements in horizontal position when they are tilted sideways. The control system rotates the implement in the opposite direction to the inclination of rear axle of the tractor. However, the current control system was found to have poor performance in accuracy and response. A new control system was therefore developed to improve the performance. Methods: The new control system was designed to get the response of the implement to be started earlier by using the tilt information from the front axle of the tractor. By this approach, the rotation of the implement can be adjusted as required to make it horizontal at the expected time, even though the response is slow. The optimal values of the control parameters for the new system were determined by computer simulation and validated by a performance test conducted with an obstacle of 120 mm height on a flat concrete surface. The performance of the control system was evaluated by the root mean square error (RMSE) of the rotation angle of the implement with respect to the actual inclination of the rear axle. Results: The new control system reduced the RMSE of the current control system by 44.6% indicating a high performance improvement. The inclination of the front axle was easily obtained from a sensor mounted on the front axle of the tractor and used as input to the new control system. Conclusions: The method of getting the response of the implement to be started earlier by utilizing the inclination information of the front axle can be applied to improve the performance of the current control system at least cost.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.8
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• pp.387-393
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• 2001

This paper describes an advanced measuring method and precise evaluation of the ground resistance for the grounding system of energized substations and power equipments. A grounding system of substations consists of all interconnected grounding connections of grounded conductors, neutral ground wires, underground conductors of distribution lines, cable shields, grounding terminals of equipments, and etc. It is very difficult to measure the accurate ground resistance of the grounding terminals of equipments, and etc. It is very difficult to measure the accurate ground resistance of the grounding system of high voltage energized substations because of harmonic components caused by switched power supplies or overloads. The conventional fall-of-potential method may be subject to big error if stray ground currents and potentials are present. In this work, to improve the precision in measurements of the ground resistance by eliminating the effects of harmonic components and stray currents and potentials, the investigations of the ground resistance measurement by using a low pass filter in a model energized grounding system were conducted. The accuracy of ground resistance mesurements was evaluated as a function of the ratio of the test signal to noise (S/N). The errors due to the proposed ground resistance measurement method were decreased with increasing S/N and were less than 5[%] as S/N is 10. The proposed ground resistance measurement method appears to be considerably more accurate than the conventional fall-of -potential method. It is allows cancellation of the parasitic resistance of energized grounding systems, to employ the measurement method that allows cancellation of the parasitic effects due to other circulating ground currents and ground potential rises in practical situations.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.269-277
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• 1996

This paper has been presented a design of a POCSAG decoder in RT-level VHDL and implemented in a FPGA chip, and tested. In a single clock of 76.8KHz, the decoder receives all the data of the rate of 512/1200/2400bps and has maximum 2-own frames for service enhancement. To improve decoder performance, the decoder uses a preamble detection cosidering 9% frequency tolerance, a SCW detction and a ICW detection at each 4 bit. The decoder also corrects a address data and a message data up to 2 bits and proposes the PF (preamble frequency) error for saving battery. The decoder increases a battery life owing to turn off RF circuits when the preamble signal is detected with nises. The chip has been designed in RT-level VHdL, synthesized into logic gates using power view$^{TM}$ of viewlogic software. The chip has been implemented in an ALTERA EPF81188GC232-3 FPGA chip with 98% usability, and fully tested in shield room and field room. The chip has been proved that the wrong detection numbers of preamble of noises are significantly reduced in the pager system using PDI 2400 through the real field test. The receiving performance is improved by 20% of aaverage, compared with other existing systems.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.4
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• pp.30-37
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• 1999

This study suggested the Fuzzy Lyapunov dimension. The Fuzzy Lyapunov dimension is to evaluate the quantitative variation of the attractor. In this paper the speaker recognition is evaluated by the Fuzzy Lyapunov dimension. It has been proved that the suggested Fuzzy Lyapunov dimension is superior in the discrimination characteristics between standard reference pattern attractors, and in reference to the test pattern attractor, it has been verified that it is the speaker recognition parameter which absorbs the pattern variation. In order to evaluate the Fuzzy Lyapunov dimension as speaker recognition parameter, the mistaken recognition according to discrimination error in each of speaker and standard reference pattern was estimated, and the validity of the speaker recognition parameter was experimental. As the result of the speaker recognition experiment, 97.0[%] of recognition ratio was obtained, and it was confirmed that the Fuzzy Lyapunov dimension was fit for the speaker recognition parameter.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.33-41
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• 2008

Telematics system includes the "vehicle remote diagnosis technology", "driving pattern analysis technology" which are commercially attractive in the real life. To implement those technologies, we need vehicle signal interface, vehicle diagnosis interface, accelerometer/yaw-rate sensor interface, GPS data processing, driving pattern analysis, and CDMA data processing technique. Based on these technologies, we analyze the error existence by diagnosing the EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG in real time. And we are checking about a driving pattern and management of the vehicle, which are sent to the information center through the wireless communication. These database results will make the efficient vehicle and driver management possible. We show the effectiveness of our results by field driving test after completing the H/W & S/W design and implementation for vehicle remote diagnosis and driving pattern analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.900-908
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• 2016

In this paper, we have studied the tracking system with a single channel monopulse receiver that has a comparative advantage of costs, size, weight, and power consumption over the general 3-channel monopulse receivers. After the single channel monopulse system was composed of an antenna, a monopulse receiver, a servo unit, a RF signal processor unit and a power supply unit, we analyzed the basic tracking performance of the tracking error angle and the pointing loss. And we proved the tracking performance to a moving target in the outdoor environment. On the Analysis of the tracking test results, the single channel monopulse system shows a equal or higher performance over the general 3-channel monopulse system and also has advantages of the system implementation. Also, it is concluded that this study is useful to apply a single channel monopulse receiver with benefits of production price and miniaturization when the monopulse tracking systems will be developed in the future.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2914-2922
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• 1997

For FA (factory automation) and ATE (automatic test equipment) in the industrial area, the standard bus needs to increase the system performance of multiprocessor environment. VME(versa module european package format) bus is appropriated to the standard bus but has features of small package and low board density. Beside, the density of board and semiconductor have grown to become significant issues that affect development time, project cost and field diagnostics. To fit this trend, in this paper, we composed Revision C.1 (IEEE std. P1014-1987) of the integrated environment for the main function such as arbitration, interrupt and interface between, VMEbus and several control modules Also the designed, VME system controller is implemented on FPGA that can be located even into slot 1. The control and function modules are coded with VHDL mid-fixed description method and then those operations are verified by simulation. As a result of experiment, we confirmed the most important that is the operation of Bus timer about Bus error signal should occur within $56{\mu}m$, and both control and function modules have the reciprocal operation correctly. Thus, the constructed VHDL library will be able to apply the system based VMEbus and ASIC design.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.327-333
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• 2019

The Fuel-cut driving is started when the acceleration pedal released with transmission gear engaged. Fuel economy of the vehicle improves by active fuel-cut driving. A deep-learning technique is proposed to predict fuel-cut driving with vehicle speed, acceleration and road gradient data in the study. It's 3~10 of hidden layers and 10~20 of variables and is applied to the 9600 data obtained in the test driving of a vehicle in the road of 12km. Its accuracy is about 84.5% with 10 variables, 7 hidden layers and Relu as activation function. Its error is regarded from the fact that the change rate of input data is higher than the rate of fuel consumption data. Therefore the accuracy can be better by the normalizing process of input data. It's unnecessary to get the signal of vehicle injector or OBD, and a deep-learning technique applied to the data to be got easily, like GPS. It can contribute to eco-drive for the computing time small.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.106-113
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• 2019

In this paper, we propose an algorithm to classify the received active pulse when the active sonar system is operated as a non-cooperative mode. The proposed algorithm uses CNN (Convolutional Neural Networks) which shows good performance in various fields. As an input of CNN, time frequency analysis data which performs STFT (Short Time Fourier Transform) of the received signal is used. The CNN used in this paper consists of two convolution and pulling layers. We designed a database based neural network and a pulse feature based neural network according to the output layer design. To verify the performance of the algorithm, the data of 3110 CW (Continuous Wave) pulses and LFM (Linear Frequency Modulated) pulses received from the actual ocean were processed to construct training data and test data. As a result of simulation, the database based neural network showed 99.9 % accuracy and the feature based neural network showed about 96 % accuracy when allowing 2 pixel error.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.54.2-54.2
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• 2019

Removing noise which occurs inevitably when taking image data has been a big concern. There is a way to raise signal-to-noise ratio and it is regarded as the only way, image stacking. Image stacking is averaging or just adding all pixel values of multiple pictures taken of a specific area. Its performance and reliability are unquestioned, but its weaknesses are also evident. Object with fast proper motion can be vanished, and most of all, it takes too long time. So if we can handle single shot image well and achieve similar performance, we can overcome those weaknesses. Recent developments in deep learning have enabled things that were not possible with former algorithm-based programming. One of the things is generating data with more information from data with less information. As a part of that, we reproduced stacked image from single shot image using a kind of deep learning, conditional generative adversarial network (cGAN). r-band camcol2 south data were used from SDSS Stripe 82 data. From all fields, image data which is stacked with only 22 individual images and, as a pair of stacked image, single pass data which were included in all stacked image were used. All used fields are cut in $128{\times}128$ pixel size, so total number of image is 17930. 14234 pairs of all images were used for training cGAN and 3696 pairs were used for verify the result. As a result, RMS error of pixel values between generated data from the best condition and target data were $7.67{\times}10^{-4}$ compared to original input data, $1.24{\times}10^{-3}$. We also applied to a few test galaxy images and generated images were similar to stacked images qualitatively compared to other de-noising methods. In addition, with photometry, The number count of stacked-cGAN matched sources is larger than that of single pass-stacked one, especially for fainter objects. Also, magnitude completeness became better in fainter objects. With this work, it is possible to observe reliably 1 magnitude fainter object.