• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.219-228
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• 2009

The growing application and the numerous qualities of induction motors (1M) in industrial processes that require high security and reliability levels has led to the development of multiple methods for early fault detection. However, various faults can occur, such as stator short-circuits and rotor failures. Traditionally the diagnosis machine is done through a sinusoidal power supply, in the present paper we study experimentally the effects of the rotor failures, such as broken rotor bars in function of the ac supplying, the load and show the impact of the converter from diagnosis of the machine. The technique diagnosis used is based on the spectral analysis of stator currents or stator voltages respectively according to the types of induction motor ac supplying. So, four different ac supplying are considered: ${\odot}$ the IM is directly by the balanced three-phase network voltage source, ${\odot}$ the IM is fed by a sinusoidal current source given the controlled by hysteresis, ${\odot}$ the IM is fed (in open loop) by a scalar control imposing through ratio V/f=constant, ${\odot}$ the IM is controlled through a vector control using space vector pulse width modulation (SVPWM) technique inverter with an outer speed loop.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.6-12
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• 2011

Electric vehicles and robots are real-time distributed control systems composed of multiple drive subsystems using micro controller units. Each control subsystem should be modular, compact, power saving, interoperable and fault tolerable in order to be incorporated into the networked real-time distributed control system. Under the networked real-time distributed control the synchronization problem can be occurred to the position and orientation tracking control due to the load variance, mismatch and time delay between the multiple drive subsystems. This paper suggests two types of position synchronization control of the single link manipulators. One of them is composed of cross controller, Kalman filter and disturbance observer, and the other uses the generation of target trajectories to minimize the gradient vector of the scalar function which is composed of the sum of square errors between the reference input vector and the output vectors. The availability of the proposed control schemes is shown through the control experiments.

• Journal of Korea Game Society
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• v.14 no.3
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• pp.55-62
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• 2014

In particle-based fluid simulation, applying sudden power to particle raise unnatural flow when wave is breaking. To solve this problem, we have used an linear interpolation technique that interpolate between fluid particle by subdividing the time interval in the previous work. Acceleration vector of the particle with increased pressure in boundary could change smoothly. However, particle looks like flow with viscosity because the number of the minimum samples to interpolate increases. We propose an weighted-interpolation technique to represent the realistic movement of fluid. it is accumulating that has added and assigned different weights to the previous acceleration vector and current one repeatedly. weighted-interpolation technique using less minium samples to flow than linear interpolation, so it can solve the problem which particle looks like flow with viscosity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.727-736
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• 2009

In this paper, the $arccos(cos^{-1})$ arithmetic unit for mobile graphics accelerator is designed. The mobile vector graphics applications need tight area, execution time, power dissipation, and accuracy constraints compared to desktop PC applications. The designed processor adopts 2nd-order polynomial approximation scheme based on IEEE floating point data format to satisfy speed and accuracy conditions and reduces area via hardware sharing structure. The arccosine processor consists of 15,280 gates and its estimated operating frequency is about 125Mhz at operating condition of $0.35{\mu}m$ CMOS technology. Because the processor can execute arccosine function within 7 clock cycles, it has about 17 MOPS(million arccos operations per second) execution rate and can be applicable to mobile OpenVG processor. And because of its flexible architecture, it can be applicable to the various transcendental functions such as exponential, trigonometric and logarithmic functions via replacement of ROM and minor hardware modification.

• Journal of the Korean Society for Railway
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• v.13 no.5
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• pp.493-499
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• 2010

The next generation domestic high speed railway system is a power dispersed type and uses vector control method for motor speed control. Nowadays, inverter driven induction motor system is widely used. However, recently PMSM drives are deeply considered as a alternative candidate instead of an induction motor driven system due to their advantages in efficiency, noise reduction and maintenance. In this paper, the maximum torque control approach is presented for the IPMSM drives with reluctance torque. The applied control method uses maximum torque control per ampere technique. Simulation programs based on Matlab/Simulink are developed. Finally the designed system is verified by simulation and their characteristics are analyzed by the simulation results.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.263-271
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• 2014

Corrective thermal performance analysis is required for thermal power plants to determine performance status of turbine cycle. We developed classification method for main feed water flow to make precise correction for performance analysis based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). The classification is based on feature identification of status of main water flow. Also we developed predictive algorithms for corrected main feed-water through Support Vector Machine (SVM) Model for each classified feature area. The results was compared to estimations using Neural Network(NN) and Kernel Regression(KR). The feature classification and predictive model of main feed-water flow provides more practical methods for corrective thermal performance analysis of turbine cycle.

• Progress in Superconductivity
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• v.5 no.2
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• pp.98-104
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• 2004

We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.158-166
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• 2002

In this paper, we proposed a contour shape description method which use the CFR(contour fluctuation ratio) feature. The CFR is the ratio of the line length to the curve length of a contour segment. The line length means the distance of two end points on a contour segment, and the curve length means the sum of distance of all adjacent two points on a contour segment. We should acquire rotation and scale invariant contour segments because each CFR is computed from contour segments. By using the interleaved contour segment of which length is proportion to the entire contour length and which is generated from all the points on contour, we could acquire rotation and scale invariant contour segments. The CFR can describes the local or global feature of contour shape according to the unit length of contour segment. Therefore we describe the shape of objects with the feature vector which represents the distribution of CFRs, and calculate the similarity by comparing the feature vector of corresponding unit length segments. We implemented the proposed method and experimented with rotated and scaled 165 fish images of fifteen types. The experimental result shows that the proposed method is not only invariant to rotation and scale but also superior to NCCH and TRP method in the clustering power.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.160-165
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• 2014

In this study, an efficiency test was performed by fabricating MEMS (Micro Electro Mechanical Systems) based 3-axis acceleration sensor modules and an earthquake monitoring system was composed. Data acquisition device (NI-9239) with a 24bit ADC (Analog to Digital Converter) was used for improving the performance of 3-axis acceleration sensor modules and filtered data (100Hz Low Pass Filter) was used for reducing noises. Also this paper focused on detecting meaningful vibration in the building by developing the earthquake monitoring software. If vector sum of 3-axis acceleration is greater than the preset value, the value will be recorded and saved to the file.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.153-160
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• 2020

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's predictive models of energy consumption. The data used includes lagging and leading reactive power lagging and leading current variable, emission of carbon dioxide (tCO2) and load type. Four statistical models are trained and tested in the test set: (a) Linear Regression (LR), (b) Radial Kernel Support Vector Machine (SVM RBF), (c) Gradient Boosting Machine (GBM), and (d) Random Forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used for calculating regression model predictive performance. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.