• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.491-497
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• 2016

This study aims to develop a vision inspection system for screw threads. To inspect external defects in screw threads, the vision inspection system was developed using front light illumination from which bright images can be obtained. The front light system, however, requires multiple side images for inspection of the entire thread surface, which can be performed by omnidirectional optics. In this study, an omnidirectional optical system was designed to obtain annular images of screw threads using an image sensor and two reflection mirrors; one large concave mirror and one small convex mirror. Optical simulations using backward and forward ray tracing were performed to determine the dimensional parameters of the proposed optical system, so that an annular image of the screw threads could be obtained with high quality and resolution. Microscale surface defects on the screw threads could be successfully detected using the developed annular inspection system.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.480-485
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• 2003

We Propose a Path planning method to reduce the Inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.161-167
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• 2007

It is dangerous that an inspector overhauls defects and condition of the inner parts of an oil tanker because of many harmful gases, complex structures, and etc. However, these inspections are necessary to many oil tankers over old years. In this study, we proposed the design of mobile robot for inspection of CAS in oil tanker. The developed CAS inspection mobile robot has four modules, a measurement module of oil tanker's thickness, a corrosion inspection module, a climbing module of the surface on a wall, and a monitoring module. In order to get over at a check position, the driving control algorithm was developed. Magnetic wheels are used to move on the surface of a wall. This study constructed a communication network and the monitoring program to operate the developed mobile robot from remote sites. In order to evaluate the inspection ability, the experiments about performance of CAS inspection using the developed mobile robot have been carried out.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.831-832
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• 2010

• Journal of Welding and Joining
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• v.23 no.5
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• pp.37-42
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• 2005

The non-destructive Inspection of the fillet weldment has difficulties due to its geometrical complexity and uneasy access. The surface shear horizontal wave (SH-wave), however, has been successfully applied to the detection of cracks on the surface and sub-surface of the filet weldment heel part. The conventional ultrasonic inspection using the surface SH-wave is usually a contact method using piezoelectric transducer. Thus, it is not suitable for a field application because the reliability and repeatability of inspection are significantly affected by test conditions such as couplant, contact pressure and pre-process. In order to overcome this problem, a non-contact SH-wave inspection method using EMAT is propose. The experimental results with this non-contact method are compared with those with a conventional ultrasonic method in fillet weldment with slit type defects. It is shown that the non-contact inspection technique requires simple procedure and less time in the fillet weldment inspection.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.1-6
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• 2012

In this paper, inspection system based on optical scanning mechanism is designed and developed for solar cell wafer. It consists of optical scanning mechanism, NIR camera optics, machinery and control system, algorithm of defect detection and software. Optical scanning mechanism is composed of geometrical camera optics and structured hybrid illumination system. It is used to inspection of surface defects. NIR camera optics is used for inspection of defects inside solar cell wafer. It is shown that surface and internal micro defects can be detected in developed inspection system for solar cell wafer.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.16-29
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• 1993

The objective of this research is in the development of a flexible 3-dimensional inspection system for the sculptured surface by integrating the Coordinate Measuring Machine (CMM), CAD database, and vision system. To achieve the proposed flexible inspection system, two research categories are discussed in the study: new inspection planning method includes a new measuring point selection method and various new probe path generation methods. The object recognition and localization process for the unknown surface can be easily carried out by introducing a new concept called "Z-Layer". The experimental results indicate that the developed flexible inspection system, with the proposed algorithm, can be inplemented in real situation.situation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3376-3382
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• 2014

The system developed inspects automatically defects existing on an inner surface of anodically treated aluminum cylinder-tubes. This system consists of automatic inspection software, and electronic endoscope and a conveyor moving device. By applying the optimal brightness conditions to searching for various defects on the inner surface of cylinder tube, the recognition rate of major defects, such as scratch, oxide and weld line reached 99%. If the present visual inspection process is replaced with the automatic defects inspection system, the physical fatigue of the operator could be reduced and the productivity could be increased. The automatic inspection system developed could also improve the quality of the products.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.865-870
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• 2018

A machine vision based industrial inspection includes defects detection and classification. Fast inspection is a fundamental problem for many applications of real-time vision systems. It requires little computation time and localizing defects robustly with high accuracy. Deep learning technique have been known not to be suitable for real-time applications. Recently a couple of fast region-based CNN algorithms for object detection are introduced, such as Faster R-CNN, and YOLOv2. We apply these methods for an industrial inspection problem. Three CNN based detection algorithms, VOV based CNN, Faster R-CNN, and YOLOv2, are experimented for defect detection on metal surface. The results for inspection time and various performance indices are compared and analysed.