• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.97-117
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• 1993

This paper considers inspection station location problem for a flexible assembly line that consists of multiple stages. By considering the trade-off between locating an station at an "early" stage and at a "late" stage, we have developed some dominance relations on a graph. Based on the dominance relations, we then present an algorithm that finds an optimal inspection plan and a heuristic approach that finds a near-optimal inspection plan. The effectiveness of these two algorithms is demonstrated by two numerical examples. numerical examples.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.3-88
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• 2001

In this paper, an on-line multi-sensor visual inspection technique for seamless steel pipe´s straightness is developed. The basic principle of the visual measuring method is detailed. The modeling of visual sensor, measurement system and data processing are presented. In order to test the accuracy of the multi-sensor visual inspection, an experiment inspecting the straightness of a 1500mm long seamless steel pipe is made. The experiment results show that the visual inspection technique can achieve on-line measurement and offers high precision and stability.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.805-807
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• 2011

In this paper, we propose a method to inspect defects of injection molded automotive parts. In order to inspect them, we developed and used a line detection algorithm and a defect analysis algorithm. The line detection algorithm defines center point of a laser line and the inspection algorithm determines the defects of automotive parts using pattern data of inspected objects and the data results from the line detection algorithm. We evaluated the accuracy and the processing time of inspection and they showed good performance.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.82-90
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• 2005

Recently, the in-line vision inspection has become the subject of growing research area in the visual control systems and robotic intelligent fields that are required exact three-dimensional pose. The objective of this article is to study the pc based in line visual inspection with the hand-eye structure. This paper suggests three dimensional structured light measuring principle and design method of laser sensor header. The hand-eye laser sensor have been studied for a long time. However, it is very difficult to perform kinematical analysis between laser sensor and robot because the complicated mathematical process are needed for the real environments. In this problem, this paper will propose auto-calibration concept. The detail process of this methodology will be described. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed in-line inspection module demonstrate the successful operation with hole, gap, width or V edge.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.629-636
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• 2003

This paper introduces the developed geometry PIG (Pipeline Inspection Gauge), one of several ILI (In-Line Inspection) tools, which provide a full picture of the pipeline from only single pass, and has compact size of the electronic device with not only low power consumption but also rapid response of sensors such as calipers, IMU and odometer. This tool is equipped with the several sensor systems. Caliper sensors measure the pipeline internal diameter, ovality and dent size and shape with high accuracy. The IMU (Inertial Measurement Unit) measures the precise trajectory of the PIG during its traverse of the pipeline. The IMU also provide three-dimensional coordination in space from measurement of inertial acceleration and angular rate. Three odometers mounted on the PIG body provide the distance moved along the line and instantaneous velocity during the PIG run. The datum measured by the sensor systems are stored in on-board solid state memory and magnetic tape devices. There is an electromagnetic transmitter at the back end of the tool, the transmitter enables the inspection operators to keep tracking the tool while it travels through the pipeline. An experiment was fulfilled in pull-rig facility and was adopted from Incheon LT (LNG Terminal) to Namdong GS (Governor Station) line, 13 km length.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.333-334
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• 2007

We propose a path planning method to decrease a inspection lead time of line scan camera in SMT(surface mount technology) in-line system. The inspection window area of printed circuit board should be minimized to consider the FOV(field of view) of line scan camera so that line scan inspector is going to find a optimal solution of path planning. We propose one of the hierarchical clustrering algorithm for a given board. Comparative simulation results are presented to verify the usefulness of proposed method.

• 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.