• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.7
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• pp.1169-1177
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• 1994

The function estimation characteristics of neural networks can be used sensor signal estimation of the nuclear power plants. In case of applying the neural network to the signal estimation of redundant sensors, it is an important problem that the redundant sensor signals used as the input signals of neural network should be validated. In this paper, we simplify the conventional parity space method in order to input the validated signal to the neural network and lso propose the sensor signal validation method, which estimates the reliable sensor output combining the neural network with the simplified parity space method. The acceptability of the proposed process variable estimation method is demonstrated by using the simulation data in safety injection accident of the nuclear power plant.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.4
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• pp.94-99
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• 1997

A new method of stbilizing the sagnac interferometric fiber optic current sensor inteh presence of birefringences and phase is presented. This method is realized by dividing the output of the ac current signal with the modulation signal output. Using the technique the stability of the current sensor was improve dmore than 4.5 times at 800Arms for 2 hours. The current sensor also shows good linearity up to 100Arms.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.483-489
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• 2016

The typical methods used for inspecting ferromagnetic pipes include the ultrasonic testing (UT) contact method and the following non-contact methods: magnetic flux leakage (MFL), electromagnetic acoustic transducers (EMAT), and remote field eddy current testing (RFECT). Among these methods, the RFECT method has the advantage of being able to establish a system smaller than the diameter of a pipe. However, the method has several disadvantages as well, including different sensitivities and difficult-to-repair coil sensors which comprise its array system. Therefore, a giant magneto-resistance (GMR) sensor was applied to address these issues. The GMR sensor is small, easy to replace, and has uniform sensitivity. In this experiment, the GMR sensor was used to measure remote field and defect signal characteristics (in the axial and radial directions) in a ferromagnetic pipe. These characteristics were measured in an effort to investigate standard defects at changing depths within a pipe. The results show that the experiment successfully demonstrated the applicability of the GMR sensor to RFECT signal detection in ferromagnetic pipe.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.28-37
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• 2013

This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used fault-tolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1254-1258
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• 2003

One of the major factors that effect sensor performance is analog noise that added in a sensor signal such as voltage. In multi-axis force sensors, error sources may be classified mainly in two groups. One is structural error due to inaccuracy of sensor body. The other error source is noise signals existing in the sensed information. This paper presents a brief review about the principle of multi-axis force sensors, and then proposes a method that can reduce the effect of noise signal to sensor performance. The method is to convert analog voltage signal to digital numbers near sensor body and then to read these digital signals and conduct signal processing in the computer. By this way, we can eliminate a bad effect of electromagnetic wave emitted from computer and of 60 Hz noise emitted from AC source. The proposed method is investigated through experimental demonstration. The experimental results show that it improves S/N ratio of the sensor about 40 times in our experimental setup.

• Journal of Welding and Joining
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• v.14 no.6
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• pp.131-139
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• 1996

The response of the arc sensor using the welding current and/or welding voltage as its outputs has been obtained by the analysis and/or experiments of the static characteristics of arc sensor. But in order to improve the reliability of arc sensor, it is necessary to know its dynamic characteristics. So in this paper, it is presented the dynamic model of arc sensor including the power source, arc voltage, electrode burnoff rate, and wire feed rate. A numerical simulation of the dynamic model of arc sensor was implemented, computing the welding current with input of CTWD. The results of computer simulations and experiments of $CO_2$arc welding showed that a linear relationship between weaving center - weld line distance and current area difference was established. Additionally, a real-time weld seam tracking system interfaced with industrial welding robot was constructed, the result of the weld seam tracking experiment for weld line with an initial offset error of 5$^{\circ}$was good.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1551-1558
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• 2014

We propose a multi-rate sensor fusion of vision and radar using Kalman filter to solve problems of asynchronized and multi-rate sampling periods in object vehicle tracking. A model based prediction of object vehicles is performed with a decentralized multi-rate Kalman filter for each sensor (vision and radar sensors.) To obtain the improvement in the performance of position prediction, different weighting is applied to each sensor's predicted object position from the multi-rate Kalman filter. The proposed method can provide estimated position of the object vehicles at every sampling time of ECU. The Mahalanobis distance is used to make correspondence among the measured and predicted objects. Through the experimental results, we validate that the post-processed fusion data give us improved tracking performance. The proposed method obtained two times improvement in the object tracking performance compared to single sensor method (camera or radar sensor) in the view point of roots mean square error.

• Explosives and Blasting
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• v.38 no.1
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• pp.23-29
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• 2020

The measurement technique with dynamic shock sensor was widely used in academic experiment for blasting and impact. However, most of dynamic sensors are expensive so that it needs to be protected by external housing structures or damping devices. In this study, the calibration method for dynamic shock sensor under the distortion by external structures. Hopkinson pressure bar system was adopted to measure the input acceleration to the sensor, and it was compared to the acceleration measured by accelerometer with customized damping device. Consequently, it is conclued that this method can be useful to calibrate the dynamic shock sensor under the linear distortion.