• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.89-96
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• 2000

In this paper, we propose a vision algorithm for the inspection of very small RF-chip inductor which is used in mobile-communication terminal. The proposed method divides coil part from the inductor body by local adaptive thresholding and integral projection method. After dividing work, the coil components are extracted by thinning and labelling techniques. The test items are the number of turns, the intervals in coil, and the measure of uniformity between the extracted lines. If the values of these are more than the specific value a tested product is decided bad one. In the simulation, the proposed method has a good performance.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1669-1676
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• 2020

The IAEA held the IAEA Robotics Challenge 2017 (IRC2017) to protect workers during inspections of spent nuclear fuel and to improve work efficiency and accuracy rates. To this end, we developed an unmanned surface vehicle (USV) system called the spent fuel check vehicle (SCV). The SCV extracts and tracks the target through image processing, and it is necessary to find suitable parameters for the SNF storage environment in advance. This preliminary work takes time. It is also difficult to prepare the environment in which the work will proceed. In addition, if the preliminary work does not proceed as planned, the system will not move at the proper speed and will become unstable, with yawing and overshoot. To solve this problem, we developed a controller with a camera that can extract the depth at which the target is stored and allow distance-adaptive control. This controller is able to attenuate system instability factors such as yawing and overshoot better than existing controllers by continuously changing system operation parameters according to the depth. In addition, the time required for preliminary work during inspections can be shortened.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.969-975
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• 2013

As energy shortage is getting more serious, wind energy source is more promoted around the world. Blade is a key component of wind turbine. Local breakages and/or contamination in the blade bring degradation in aerodynamic efficiency and life-time. However, it is not easy and even dangerous for human workers to access the blade for inspection and maintenance since its size is huge and located at high mountains and rough sea, which are windy places. This paper deals with a novel moving mechanism that efficiently carries human workers or robots to the wind turbine blade. The proposed mechanism utilizes flexible tube with pressurized air that rolls and climbs over the blade surface. So, the tube naturally adapts the changing surface of the blade and acts no harm to it. This paper discusses about its concept, detail design, and advantages. The feasibility of the proposed mechanism is proved through experiments prototype.

• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.248-252
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• 2015

Currently composite manufacturing process, such as linear friction welding plus NC machining, is the main method for the manufacturing and repairing of complex parts with integrated structure. Due to different datum position and inevitable distortion from different processes, it is important to ensure sufficient machining allowance for complex parts during the NC machining process. In this paper, a workpiece localization approach for machining allowance optimization of complex parts based on CMM inspection is developed. This technique concerns an alignment process to ensure sufficient stock allowance for the single parts as well as the whole integrated parts. The mathematical model of the constrained alignment is firstly established, and then the symmetric block solution strategy is proposed to solve the optimization model. Experiment result shows that the approach is appropriate and feasible to distribute the machining allowance for the single and whole parts for adaptive machining of complex parts.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.33 no.4
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• pp.290-297
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• 1997

Underwater robotic vehicles(URVs) are used for various work assignments such as pipe-lining, inspection, data collection, drill support, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc. As the use of such vehicles increases the development of vehicles having greater autonomy becomes highly desirable. The vehicle control system is one of the most critic vehicle subsystems to increase autonomy of the vehicle. The vehicle dynamics is nonlinear and time-varying. Hydrodynamic coefficients are often difficult to accurately estimate. It was also observed by experiments that the effect of electrically powered thruster dynamics on the vehicle become significant at low speed or stationkeeping. The conventional linear controller with fixed gains based on the simplified vehicle dynamics, such as PID, may not be able to handle these properties and result in poor performance. Therefore, it is desirable to have a control system with the capability of learning and adapting to the changes in the vehicle dynamics and operating parameters and providing desired performance. This paper presents an adaptive and learning control system which estimates a new set of parameters defined as combinations of unknown bounded constants of system parameter matrices, rather than system parameters. The control system is described with the proof of stability and the effect of unmodeled thruster dynamics on a single thruster vehicle system is also investigated.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.107-117
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• 2016

STD method using a mean and standard deviation is widely used in various inspection systems. The result of detection using the STD method is very dependent on the threshold value. This paper proposes an adaptive defect detection algorithm to with a precise detection of an ultimate defect. The proposed method is determined threshold value adaptively using a skewness that indicates a similarity of intensity and normal distribution of image. In the experiment, we used a various TFT-LCD images for a quantitative evaluation of defect detection performance evaluation result to prove the performance of the proposed algorithm.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.5
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• pp.391-399
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• 2005

Laser-generated ultrasonic inspection system is a non-contact scanning inspection device with high spatial resolution and wide bandwidth. The amplitude of laser-generated ultrasound is varied according to the energy of pulse laser and the surface conditions of an object where the CW measuring laser beam is pointing. In this paper, we correct the generating errors by measuring the energy of pulse laser beam and correct the measuring errors by extracting the gain information of laser interferometer at each time. h dynamic stabilizer is developed to stably scan on the surface of an object for an laser-generated ultrasonic inspection system. The developed system generates ultrasound after adaptively finding the maximum gain time of an laser interferometer and processes the signal in real time after digitization with high speed. In this paper, we describe hardware configuration and control algorithm to build a stable laser-generated ultrasonic inspection system. Also, we confirmed through experiments that the proposed correction method for the generating errors and measuring errors is effective to improve the performance of a system.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.898-906
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• 1999

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

• Journal of Environmental Science International
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• v.5 no.2
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• pp.229-241
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• 1996

This study was performed to find the most desirable emission reduction for each mobile source pollutant and the optimal control strategy at a given level of expenditures in Pusan City in 2000 by using the interactive s-constraint method developed by Chang-Hyo Lee and Hyung-Wook Kim, which isone of the mathematical programming models. The most desirable emission reduction is 7093 ton/year for particulate (TSP), 4871 ton/year for NOx, 5148 ton/year for HC and 36779 ton/year for CO. The optimal control strategy is as follows; 1. As to passenger car and taxi, limiting VKT (vehicle kilometers travelled) in congested areas will be necessary. In addition to this, improving vehicie inspection Program should be enforced. 2. As to small-gasoline bus, traffic adaptive control system will be necessary. 3. As to small-diesel bus, non-adjustable engine parameters will have to be applied. .4. As to heal bus and heart truck, catalytic trap oxidizer and limiting VKT in congested areas will do necessary. 5. As to motorcycle, 2-cycle motorcycles should be converted to 4-cycle motorcycles.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.99.2-99
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• 2002

Contents 1 In this paper a machine vision system for recognizing and classifying the patterns and marks engraved by die molding or laser marking on glass panel of computer monitor is suggested and evaluated experimentally. The vision system is equipped with a neural network based pattern classifier and searching process based on normalized grayscale correlation and adaptive binarization, which is applicable to the cases in which the segmentation of the pattern area from background using the ordinary blob coloring technique is quite difficult. Inspection process is accomplished via the way of NGC hypothesis and ANN verification. The proposed pattern recognition system is composed of three...