• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.432-435
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• 2005

The Mega-pixel camera phones become main trends in mobile phone market. The lens modules used in mesa-pixel camera phones need high resolution. One of the main factors of resolution drop is the defects of bare lens. Though there are many advantages in auto-inspection of defects of bare lens, high technical problems take the defect inspections to be done with manual process. In this paper, the type and the source of defects were described and bare lens defect auto-inspection system design was explained. The designed auto-inspection system is composed of illumination optics part, focusing optics part and auto-moving system. With the proposed auto-inspection system, fast and uniform inspection of bare lens can be achieved.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.9-18
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• 2000

This study includes noise automatic inspection system for washing machine auto-transmission one of modern home necessary. We effort to find and certificate sound noise source by sound power and sound intensity, and apply to frequency analysis in vibration related sound noise. still more we have been studying to data acquisition and programming for MS VisualBasic version 5.0. System component is below. 1) Pentium PC or data acquisition. 2) DSO for noise acquisition. 3)S/W for comparison and decision. 4) I/F Board for data communication. Wave form data through the DSO are converting to ASCII code data. The ASCII code through binary converting S/W. Finally we will making noise monitoring system and automatic inspection system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

• Journal of Auto-vehicle Safety Association
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• v.8 no.4
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• pp.18-23
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• 2016

The objective of this study is to present the inspection standards of motorcycle brake system affecting motorcycle traffic accident. The inspection standards of motorcycle brake system recommended by CITA (International Motor Vehicle Inspection Committee) are studied. The brake performance for preventing the traffic accident is assessed by the brake efficiency. Considering the KMVSS (Korean Motor Vehicle Safety Standards) and the inspection standards of CITA, United Kingdom and Japan, the brake performance in the inspection standards of motorcycle is suggested. It is recommended that the efficiency of independent front and rear brakes are 40% and 27%, respectively. It is recommended that the efficiency of combined front and rear brakes is 50%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.373-374
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• 2013

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.55-60
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• 2017

This paper presents the motorcycle inspection standards of electrical system, frame & body, lights and speedometers. 187 real-world motorcycles are visually and mechanically inspected according to the developed inspection standards. The non-compliance rate of inspection standards of the lights is 23.7% and main causes are damage, tinting, painting and coloration of head-lamp, number plate lamp, front-rear position lights, stop lamp and direction indicators of motorcycles. Also, 28.4% of motorcycles are dropped from the luminous intensity inspection standard. Motorcycle electrical system cannot be visually inspected. The motorcycle inspections standards are improved reflecting 187 cases of real-world motorcycle inspection results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.310-315
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• 1998

This study includes noise automatic inspection system for washing machine auto-transmission one of modern home necessary. We effort to find and certificate sound noisesource by sound power and sound intensity, and apply to frequency analysis in vibration related sound noise. Still more we have been studying to data acquisition and programming for MS VisualBasic version 5.0. System component is below. 1) Pentium PC for data acquisition. 2) DSO for noise acquisition. 3) S/W for comparison and decision. 4) I/F Board for data communication. Wave form data through the DSO are converting to ASCII code data. The ASCII code through binary converting S/W are to be decision fitness or the badness comparison S/W. Finally, we will making noise monitoring system and automatic inspection system.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.2
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• pp.83-93
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• 2024

In this study, we present a sewer pipe inspection technique through a combination of active sonar technology and deep learning algorithms. It is difficult to inspect pipes containing water using conventional CCTV inspection methods, and there are various limitations, so a new approach is needed. In this paper, we introduce a inspection method using active sonar, and apply an auto encoder deep learning model to process sonar data to distinguish between normal and abnormal pipelines. This model underwent training on sonar data from a controlled environment under the assumption of normal pipeline conditions and utilized anomaly detection techniques to identify deviations from established standards. This approach presents a new perspective in pipeline inspection, promising to reduce the time and resources required for sewer system management and to enhance the reliability of pipeline inspections.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.472-478
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• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.106-106
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• 2000

This study is to embody automatic inspection system of motor body panel by visual system. since it is inefficient to examine the adhesion condition of components with the naked eye, picture processing algorithm is presented to replace the existing manual inspection process with an automatic inspection process. The developed automatic inspection system presents the examination method of the adhesion condition of components with a ixed camera, which leads to an increase of the productivity and a reduction of manufacturing cost.