• Journal of the Korean Society for Railway
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• v.11 no.2
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• pp.115-119
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• 2008

Korean Train Express (KTX) has opened to commercial traffic since 2004 at maximum speed 300km/h. As the speed of the train becomes higher, the conditions of the rail affect the behavior of the running train. To secure the safety and reliability of high speed railway, it is necessary to inspect rail irregularities and to maintain the rail regularly. The authors designed the high speed rain measurement system over 300km/h. And we installed the system to Korea High-speed Railway (HSR 350x). In this paper, we introduce the high speed rail measurement system for HSR 350x and show verification of the performance of the system through test runs.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.1
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• pp.74-88
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• 2013

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.3
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• pp.67-76
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• 2013

• Journal of Industrial Technology
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• v.21 no.B
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• pp.67-74
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• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.

• Smart Structures and Systems
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• v.21 no.5
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• pp.571-582
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• 2018

Track irregularities of high-speed Maglev lines have significant influence on ride comfort. Their adjustment is of key importance in the daily maintenance of these lines. In this study, an adjustment method is proposed and track irregularities analysis is performed. This study considers two modules: an inspection module and a vehicle-guideway coupling vibration analysis module. In the inspection module, an inertial reference method is employed for field-measurements of the Shanghai high-speed Maglev demonstration line. Then, a partial filtering, integration method, resampling method, and designed elliptic filter are employed to analyze the detection data, which reveals the required track irregularities. In the analysis module, a vehicle-guideway interaction model and an electromagnetic interaction model were developed. The influence of the measured line irregularities is considered for the calculations of the electromagnetic force. Numerical integration method was employed for the calculations. Based on the actual field detection results and analysis using the numerical model, a threshold analysis method is developed. Several irregularities modalities with different girder end's deviations were considered in the simulations. The inspection results indicated that long-wavelength irregularities with larger girder end's deviations were the dominant irregularities. In addition, the threshold analysis of the girder end's deviation shows that irregularities that have a deviation amplitude larger than 6 mm and certain modalities (e.g., M- and N-shape) are unfavorable. These types of irregularities should be adjusted during the daily maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3608-3626
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• 2021

The detection of bolts is an important task in high-speed train inspection systems, and it is frequently performed to ensure the safety of trains. The difficulty of the vision-based bolt inspection system lies in small sample defect detection, which makes the end-to-end network ineffective. In this paper, the problem is resolved in two stages, which includes the detection network and cascaded classification networks. For small bolt detection, all bolts including defective bolts and normal bolts are put together for conducting annotation training, a new loss function and a new boundingbox selection based on the smallest axis-aligned convex set are proposed. These allow YOLOv3 network to obtain the accurate position and bounding box of the various bolts. The average precision has been greatly improved on PASCAL VOC, MS COCO and actual data set. After that, the Siamese network is employed for estimating the status of the bolts. Using the convolutional Siamese network, we are able to get strong results on few-shot classification. Extensive experiments and comparisons on actual data set show that the system outperforms state-of-the-art algorithms in bolt inspection.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.943-950
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• 2008

A novel nondestructive testing (NDT) system, which is able to detect a crack with high speed and high spatial resolution, is urgently required for inspecting small cracks on express train wheels. This paper proposes a high speed scan type magnetic camera, which uses the multiple amplifying circuits and the crack indicating pulse output system. The linearly integrated Hall sensors are arrayed in parallel, and the Hall voltages from each sensor in the scanning direction are obtained and amplified. High-speed NDT can be achieved by using the exclusive analog-digital converter and micro-processor because the ${\partial}\;V_H/\;{\partial}$ x value, which provides the most important crack information, can be obtained by buffering and calculating. The effectiveness of the novel method was verified by examine using cracks on the wheel specimen model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.139-146
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• 2004

A 2D/3D complex optical system and its vision inspection algerian is proposed and implemented as a single probe system for high speed, precise vision inspection of the solder pastes. One pass un length labeling algorithm is proposed instead of the conventional two pass labeling algorithm for fast extraction of the 2D shape of the solder paste image from the recent line-scan camera as well as the conventional area-scan camera, and the optical probe path generation is also proposed for the efficient 2D/3D inspection. The Moire interferometry-based phase shift algerian and its optical system implementation is introduced, instead of the conventional laser slit-beam method, for the high precision 3D vision inspection. All of the time-critical algorithms are MMX SIMD parallel-coded for further speedup. The proposed system is implemented for simultaneous 2D/3D inspection of 10mm${\times}$10mm FOV with resolutions of 10 ${\mu}{\textrm}{m}$ for both x, y axis and 1 ${\mu}{\textrm}{m}$ for z axis. Experiments conducted on several nBs show that the 2D/3D inspection of an FOV, excluding an image capturing, results in high speed of about 0.011sec/0.01sec, respectively, after image capturing, with $\pm$1${\mu}{\textrm}{m}$ height accuracy.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.341-349
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• 2020

Recently, interest in ground subsidence in urban areas has increased after a large sinkhole occurred near the high-story building area in Jamsil, Seoul, Korea, in 2014. If a massive sinkhole occurs in an urban area, it is crucial to assess its risk rapidly. Access to humans for on-site safety diagnosis may be difficult because of the additional risk of collapse in the disaster area. Generally, inspection using drones equipped with high-speed lidar sensors can be utilized. However, if the sinkhole is created vertically to a depth of 100 m, similar to the sinkhole in Guatemala, the drone cannot be applied because of the wireless communication limit and turbulence inside the sinkhole. In this study, a three-dimensional (3D) scanning system was fabricated and operated using a towed cable in a massive vertical sinkhole to a depth of 200 m. A high-speed lidar sensor was used to obtain a continuous cross-sectional shape at a certain depth. An inertial-measuring unit was applied to compensate for the error owing to the rotation and pendulum movement of the measuring unit. A reconstruction algorithm, including the compensation scheme, was developed. In a vertical hole with a depth of 180 m in the mining area, the fabricated system was applied to scan 0-165 m depth. The reconstructed shape was depicted in a 3D graph.