• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1725-1728
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• 2009

This research developed process control device and FGV pattern generating device essential for full gate visual inspection to improve process so that defect detection capability may be maximized in specified environment. The devices developed in this research, which can be swiftly replaced in case loss or error occurs, are anticipated to improve module yield as well as maintain tact loss near '0'. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, detection rates were 98.1% and 99.1% respectively for pixel defect by tact and line defect, and yield of the entire module process including gate and visual level test increased up to 98.3%.

• Korean Journal of Optics and Photonics
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• v.7 no.2
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• pp.101-111
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• 1996

Optical microscopes integrated with CCD cameras are widely used for automatic inspection of precision circuit patterns fabricated on glass masks and silicon wafers. For this application it is important to position the object always is focus so that the image appears in good quality while the microscope scans the object. However, as the magnification of the microscope is taken large for fine resolution the depth of focus becomes small, often in submicron ranges, requiring special care in focusing. This study proposes a new auto-focusing method, which can be readily incorporated in existing optical configuration of microscope. This method is based on optical triangulation using a separate beam of laser and two photodiodes, eliminating focus errors caused by surface roughness and waviness. Experimental results prove that the method can produce focus error signals which are very sensitive with a resolution of 5 nm within 0.5 ${\mu}{\textrm}{m}$ accuracy.

• Smart Structures and Systems
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• v.25 no.3
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• pp.265-277
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• 2020

Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.

• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.513-517
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• 2013

Recently, maskless lithography (ML) systems have become popular in digital manufacturing technologies. To achieve high-throughput manufacturing processes, digital micromirror devices (DMD) in ML systems must be driven to their operational limits, often in harsh conditions. We propose an instrument and algorithm to detect DMD malfunctions to ensure perfect mask image transfer to the photoresist in ML systems. DMD malfunctions are caused by either bad DMD pixels or data transfer errors. We detect bad DMD pixels with $20{\times}20$ pixel by white and black image tests. To analyze data transfer errors at high frame rates, we monitor changes in the frame rate of a target DMD pixel driven by the input data with a set frame rate of up to 28000 frames per second (fps). For our data transfer error detection method, we verified that there are no data transfer errors in the test by confirming the agreement between the input frame rate and the output frame rate within the measurement accuracy of 1 fps.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.617-627
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• 2021

In the field of on-road motor vehicles, the level for autonomous driving technology is defined according to J3016, proposed by Society of Automotive Engineers (SAE) International. However, in the field of agricultural machinery, different standards are applied by country and manufacturer, without a standardized classification for autonomous driving technology which makes it difficult to clearly define and accurately evaluate the autonomous driving technology, for agricultural machinery. In this study, a method to classify the autonomy levels for autonomous agricultural machinery (ALAAM) is proposed by modifying the SAE International J3016 to better characterize various agricultural operations such as tillage, spraying and harvesting. The ALAAM was classified into 6 levels from 0 (manual) to 5 (full automation) depending on the status of operator and autonomous system interventions for each item related to the automation of agricultural tasks such as straight-curve path driving, path-implement operation, operation-environmental awareness, error response, and task area planning. The core of the ALAAM classification is based on the relative roles between the operator and autonomous system for the automation of agricultural machines. The proposed ALAAM is expected to promote the establishment of a standard to classify the autonomous driving levels of self-propelled agricultural machinery.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.69-75
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• 2019

Since gasoline engines are based on a combination of a cast iron liner and an aluminum block, which have different thermal properties and stiffnesses, bore shape distortion is likely to occur during honing due to uneven thermal deformation. To solve this problem, many tests and evaluations are needed to support the development of a high-performance honing stone with low heat generation. Moreover, performance evaluation, which depends on inspection and observation after work, often requires much trial and error to optimize tool design, due to challenges in the accurate interpretation of results. This study confirmed that the assessment of grinding capability was clarified by evaluating performance under severe work conditions and by in-situ measurement and recording of current consumption (workload) and heat generation during operation. As a result of using a honing stone with excellent grinding performance in engine block manufacture-in which cylinder bore distortion caused by thermal deformation during manufacture is a problem-a noticeable improvement in the degree of cylindricity was observed.

• Journal of Drive and Control
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• v.18 no.1
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• pp.31-38
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• 2021

This study presents a new principle for driving the robot aimed at reducing the position error for the boresonic examination of turbine rotor. The conventional method of inspection is performed by installing manipulator onto the flange of the turbine rotor and connecting a pipe, which is then being pushed into the bore. The longer the pipe gets, the greater sagging and distortion appear, making it difficult for the ultrasonic sensor to contact with the internal surface of the bore. A pneumatic pressure will ensure the front or rear feet of the robot in close contact with the inner wall to prevent slipping, while the ball screw on the body of the robot will rotate to drive it in the axial direction. The compression force required for tight contact was calculated in the form of a three-point support, and a static structural simulation analysis was performed by designing and modeling the robot mechanism. The driving performance and ultrasonic detection ability have been tested by fabricating the robot, the test piece for ultrasonic calibration and the transparent mock-up for robot demonstration. The tests have confirmed that no slipping occurs at a certain pneumatic pressure or over.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.153-166
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• 2020

DDI(Display Driver IC) are used to drive numerous pixels that make up display. For stable driving of DDI, it is necessary to attach a protective film to shield electromagnetic waves. When the protective film is attached, defects often occur if the film is inclined or the center point is not aligned. In order to minimize such defects, an algorithm for correcting the center point and the inclined angle using camera image information is required. This technology detects the corner coordinates of the protective film by image processing in order to correct the positional defects where the protective film is attached. Corner point coordinates are detected using an algorithm, and center point position finds and correction values are calculated using the detected coordinates. LUT (Lookup Table) is used to quickly find out whether the angle is inclined or not. These algorithms were described by Verilog HDL. The method using the existing software requires a memory to store the entire image after processing one image. Since the method proposed in this paper is a method of scanning by adding a line buffer in one scan, it is possible to scan even if only a part of the image is saved after processing one image. Compared to those written in software language, the execution time is shortened, the speed is very fast, and the error is relatively small.

• Progress in Superconductivity and Cryogenics
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• v.25 no.1
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• pp.16-20
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• 2023

The International Electrotechnical Commission (IEC) 61788-26:2020 provides guidelines for measuring the critical current of Rare-earth barium copper oxide (REBCO) tapes using two methods: linear ramp and step-hold methods. The critical current measurement criterion, 1 or 0.1 μV/cm of electric field from IEC 61788-26 has been normally applied to REBCO coils or magnets. No-insulation (NI) winding technique has many advantages in aspects of electrical and thermal stability and mechanical integrity. However, the leak current from the NI REBCO coil can cause distortion in critical current measurement due to the characteristic resistance which causes the radial current flow paths. In this paper, we simulated the NI REBCO coil by applying both linear ramp and step-hold methods based on a simplified equivalent circuit model. Using the circuit analysis, we analyzed and evaluated both methods. By using the equivalent circuit model, we can evaluate the critical current of the NI REBCO coil, resulting in an estimation error within 0.1%. We also evaluate the accuracy of critical current measurement using both the linear ramp and step-hold methods. The accuracy of the linear ramp method is influenced by the inductive voltage, whereas the accuracy of the step-hold method depends on the duration of the hold-time. An adequate hold time, typically 5 to 10 times the time constant (τ), makes the step-hold method more accurate than the linear ramp method.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.