• Geophysics and Geophysical Exploration
• /
• v.8 no.4
• /
• pp.270-279
• /
• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.

• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.6
• /
• pp.633-641
• /
• 2015

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.

• Proceedings of the KIPE Conference
• /
• 2009.11a
• /
• pp.105-110
• /
• 2009

The On Line Electric Vehicles(OLEV) that can pick up inductive power from underground coils on driving with high efficiency have been developed this year, and is now proposed in this paper. The IPS(Inductive Power Supply) system consists of power supply inverters, power supply rails, pick up modules, and a regulator. There are 3 generations of IPS have been developed so far, and the $4^{th}$ generation IPS is being developed. The $1^{st}$ generation has been demonstrated this Feb. 27, which is equipped with mechanically auto tracking pick-up module with 1cm air gap, and showed 80% power efficiency. The $2^{nd}$ generation IPS applied to an 120kW (average)/240kW(peak) motor powered electric bus has 17cm air gap with 72% power efficiency. For the $2^{nd}$ generation IPS, the Power supply inverter has 440V, 3phase input and 200A @ 20kHz output. The test power supply rail of 240m long is segmented by 60m each, where newly developed core structure and power cable are constructed under the road covered with asphalt of 5cm thickness. The pick-up modules which consist of core, winding wire, and rectifiers are fixed to the bottom of the bus which can carry more than 40 passengers and can pick up max. 60kW. To remove parasitic component and to transfer maximum power between them resonant circuit topology is applied to the primary and secondary sides. The EMF level is below 62.5mG at 1.75m from the center of the road to meet the regulation. Several effective ways of reducing EMF levels have been developed. In addition, effective ways to solve problems related high frequency power cables buried in ground and it's proof from soil have been studied also. This development shows that the IPS system is capable of supplying enough power to the pick-up of OLEV and can reduce battery size, weight and cost, which means the IPS with OLEV is one of the best candidate for EV.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.3
• /
• pp.327-332
• /
• 2017

As Internet of Things (IoT) technology advances, there is a growing demand for location-based services (LBSs) to identify users' mobility and identity. The initial LBS system was mainly used to measure position information by measuring the phase of a signal transmitted from a global positioning system (GPS) satellite or by measuring distance to a satellite by tracking the code of a carrier signal. However, the use of GPS satellites is ineffective, because it is difficult to receive satellite signals indoors. Therefore, research on wireless communications systems like ultra-wide band (UWB), radio frequency identification (RFID), and ZigBee are being actively pursued for location recognition technology that can be utilized in an indoor environment. In this paper, we propose an LBS system that includes the 2.45GHz band for chirp spread spectrum (CSS), and the 3.1-10.6GHz band and the 250-750MHz bands for UWB using the IEEE 802.15.4a standard for low power-based location recognition. As a result, we confirmed that the 2.45GHz Industrial, Scientific and Medical (ISM) band RF transceiver and the ranging function can be realized in the hardware and has 0dBm output power.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.10
• /
• pp.777-784
• /
• 2017

Energy harvesting through a thermoelectric module normally makes use of the temperature gradient in the system's operational environment. Therefore, it is difficult to obtain the desired output power when the system is subjected to an environment in which a low temperature gradient is generated across the module, because the power generation efficiency of the thermoelectric device is not optimized. The utilization of solar energy, which is a form of renewable energy abundant in nature, has mostly been limited to photovoltaic solar cells and solar thermal energy generation. However, photovoltaic power generation is capable of utilizing only a narrow wavelength band from the sunlight and, thus, the power generation efficiency might be lowered by light scattering. In the case of solar thermal energy generation, the system usually requires large-scale facilities. In this study, a simple and small size thermoelectric power generation system with a solar concentrator was designed to create a large temperature gradient for enhanced performance. A solar tracking system was used to concentrate the solar thermal energy during the experiments and a liquid circulating chiller was installed to maintain a large temperature gradient in order to avoid heat transfer to the bottom of the thermoelectric module. Then, the setup was tested through a series of experiments and the performance of the system was analyzed for the purpose of evaluating its feasibility and validity.

• Journal of The Korean Astronomical Society
• /
• v.48 no.2
• /
• pp.125-137
• /
• 2015

We report results of the performance evaluation of a new hardware correlator in Korea, the Daejeon correlator, developed by the Korea Astronomy and Space Science Institute (KASI) and the National Astronomical Observatory of Japan (NAOJ). We conduct Very Long Baseline Interferometry (VLBI) observations at 22 GHz with the Korean VLBI Network (KVN) in Korea and the VLBI Exploration of Radio Astrometry (VERA) in Japan, and correlated the aquired data with the Daejeon correlator. For evaluating the performance of the new hardware correlator, we compare the correlation outputs from the Daejeon correlator for KVN observations with those from a software correlator, the Distributed FX (DiFX). We investigate the correlated flux densities and brightness distributions of extragalactic compact radio sources. The comparison of the two correlator outputs shows that they are consistent with each other within < 8%, which is comparable with the amplitude calibration uncertainties of KVN observations at 22 GHz. We also find that the 8% difference in flux density is caused mainly by (a) the difference in the way of fringe phase tracking between the DiFX software correlator and the Daejeon hardware correlator, and (b) an unusual pattern (a double-layer pattern) of the amplitude correlation output from the Daejeon correlator. The visibility amplitude loss by the double-layer pattern is as small as 3%. We conclude that the new hardware correlator produces reasonable correlation outputs for continuum observations, which are consistent with the outputs from the DiFX software correlator.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.4
• /
• pp.819-830
• /
• 2017

An FM radio based PCL system is a passive radar technique for detecting the multiple moving targets from FM radio signals and tracking the trajectories of the targets by calculating the cross-correlation function of direct-path signal and target echo signals. However, the interference signals are received from a surveillance channel, which is designed to receive the target echo signals. Because of this problem, the target echo signals are masked by the strong interference signals and this makes it difficult to detect the true targets from the cross-correlation function. Adaptive filters are known as effective methods for suppressing the interference signals but there is a problem to present their accurate performances in the PCL system because many literatures used the cross-correlation function and the ratio of input and output power as a measure of the performance analysis. In this paper, a performance analysis method is proposed to evaluate the performance of interference cancellation algorithms. By using the property that each component of the filter weight vector is adjusted to suppress the specific interference signal, a performance measure of the interference signal suppression is defined by a function of adaptive filter weights. Based on the proposed method, we compare the performance of the adaptive filters used in the PCL system. Simulation results show that the proposed method can be very effective for evaluating the performance of interference cancellation algorithms.

• Korean Journal of Applied Biomechanics
• /
• v.24 no.2
• /
• pp.181-187
• /
• 2014

In this study, a real-time evaluation system for quantitative dynamic fitting during pedaling was developed. The system is consisted of LED markers, a digital camera connected to a computer and a marker detecting program. LED markers are attached to hip, knee, ankle joint and fifth metatarsal in the sagittal plane. Playstation3 eye which is selected as a main digital camera in this paper has many merits for using motion capture, such as high FPS (Frame per second) about 180FPS, $320{\times}240$ resolution, and low-cost with easy to use. The maker detecting program was made by using Labview2010 with Vision builder. The program was made up of three parts, image acquisition & processing, marker detection & joint angle calculation, and output section. The digital camera's image was acquired in 95FPS, and the program was set-up to measure the lower-joint angle in real-time, providing the user as a graph, and allowing to save it as a test file. The system was verified by pedalling at three saddle heights (knee angle: 25, 35, $45^{\circ}$) and three cadences (30, 60, 90 rpm) at each saddle heights by using Holmes method, a method of measuring lower limbs angle, to determine the saddle height. The result has shown low average error and strong correlation of the system, respectively, $1.18{\pm}0.44^{\circ}$, $0.99{\pm}0.01^{\circ}$. There was little error due to the changes in the saddle height but absolute error occurred by cadence. Considering the average error is approximately $1^{\circ}$, it is a suitable system for quantitative dynamic fitting evaluation. It is necessary to decrease error by using two digital camera with frontal and sagittal plane in future study.

• Korean Journal of Optics and Photonics
• /
• v.2 no.3
• /
• pp.139-148
• /
• 1991

A fiber-optic magnetic sensor system for the detection of small ac magnetic field(200Hz-2 kHz) was constructed. Magnetic field sensing part was fabricated by bonding a section of optical fiber to amorphous metallic glass(2605SC) having large magnetostriction effect. And with the directional coupler, all fiber type Mach-Zehnder interferometer was constructed to measure the variation of the external magnetic field by translating it into the optical phase shift in the interferometer. The signal fading problem of the interferometer, which is due to random phase drifts originated from the environment, i.e., temperature fluctuation, vibrations, etc., was elliminated by feedback phase compensation. This allows the sensitivity to be maintained at the maximum by keeping the interferometer in quadrature phase condition. The frequency response of metallic glass was found to be nearly flat in the range of 90 Hz-2 kHz and dc bias field for the maximum ac response was 3.5 Oe. The interferometer output showed good linearity over the range $\pm$0.5 Oe. For 1 kHz ac magnetic field the scale factor S and the minimum detectable magnetic field were measured to be 8.0 rad/Oe and $3X10^{-6} Oe/\sqrt{Hz}$at 1 Hz detection bandwidth respectively.