• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.85-96
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• 2000

An Eggcrate assembly is an important part to hold and support 16,000 tubes containing hot and contaminated water in the steam generator of nuclear power plant. As a great number of tubes should be inserted into the eggcrate assembly, the dimensions of each eggcrate grid are one of the critical factors to determine the availability of tube insertion. in this paper. we propose a machine vision algorithm for measuring the inner-circle diameter of each eggcrate grid whose shape is not exact quadrangular. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid height adjustment, and inner-circle diameter estimation. The algorithm is tested on real specimens and the results show that the algorithm works fairly well.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.795-801
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• 1998

In this paper, we propose a machine vision algorithm for inspecting inserts which are used for milling and turning operations. Major defects of the inserts are breakage and crack on insert surfaces. Among the defects, breakages on the face of the inserts can be detected through three stages of the algorithm developed in this paper. In the first stage, a multi-layer perceptron is used to recognize the inserts being inspected. Edge detection of the insert image is performed in the second stage. Finally, in the third stage breakages on the insert face are identified using Hough transform. The overall algorithm is tested on real specimens and the results show that the algorithm works fairly well.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1072-1080
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• 2013

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1367-1370
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• 1997

This paper presents a vision algorithm for finding the centers of steam generator tubes using the generalized symmetry transform, which is used for ECT(Eddy Current Test) of steam generator tubes in nuclear power plants. The geometrical properties of the image representing steam generator tubes shows that they have amost circular or somewhat elliptic appearances and each tube has strong symmetry about its center. So we apply the generalized symmetry transform to finding centers of steam geneator tubes. But applying the generalized symmetry transform itself without any modification gives difficulties in obtaining the exact centers of steam generator tubes. But applying the generalized symmetry transform itself without any modification gives difficulties in obtaining the exact centers of tubes due to the shadow effect generated by the local light installed inside steam generator. Therefore we make the generalized symmetry transform modified, which uses a modified phase weight function in getting the symmetry magnitude in order to overcome the misleading effect by the local light. The experimental results indicate that the proposed vision algorithm efficiently recongnizes centers of steam generator tubes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.381-386
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• 2002

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.141-146
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• 2000

We introduce the algorithms of 3-D position estimation using a laser sensor for automatic die remodeling. First, a vision sensor based on the optical triangulation was used to collect the range data of die surface. Second, line vector equations were constructed by the measured range data, and an analytic algorithm was proposed for recognizing the die location with these vector equations. This algorithm could make the transformation matrix without any specific corresponding points. To ascertain this algorithm, folded SUS plate was measured by the laser vision sensor attached to a 3-axis cartesian manipulator and the transformation matrix was calculated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.217-222
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• 2001

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.683-686
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• 2000

A new approach to the task of aligning a robot using camera is presented in this paper. We apply an elitist GA to find the joints angles of manipulator to reach target position instead of using nonlinear least error method. Since it employs parallel search and have good performance in solving optimization problems. In order to improve convergence speed, the floating coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using elitist genetic algorithm.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.14-23
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.182-187
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• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for similar model of fifth cell among the twelve cell for automatic test and assemblig in S company.