• Proceedings of the KSR Conference
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• 2010.06a
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• pp.571-582
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• 2010

Typically nondestructive inspection methods of the large gear units are applied to penetrate non-destructive inspection. Nondestructive penetrating inspection put into the small openings of the defect to penetration liquid, remove to excess penetration liquid on the surface of the gear units, spread with developing solution and we can find the small defect by coating with penetration liquid. However, this method has so many issues because of penetrate nondestructive tests on the gear assembly. The steep angle of screw is hard to achieved full penetration and has the problem to remove the excess. In contrast, the magnetic nondestructive inspection is easy to detect subsurface defects and subtle defects. According to the inspection results the stress concentrates in gear surface, some internal defects and microscopic flaws exist on the gear units are not found to penetrate the nondestructive inspection, but magnetic nondestructive inspection could have found many defect. Therefore, a reasonable method of nondestructive inspection for the large gear units is suitable to magnetic nondestructive inspection.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.8-11
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• 2012

Automated Vision Inspection (AVI) systems automatically detect any defect feature in a surface image. The performance of the system can be measured under a special circumstances such as ultimate defect detection. In this situation, the defect signal level is similar to noise level and it becomes hard to make a solid decision with AVI systems. In this paper, we propose an effective preprocessing technique to enhance SNR (Signal to Noise Ratio). The method is motivated by some principles of HVS (Human Visual System) and RLC (Run Length Coding) techniques is used for this purpose. The proposed preprocessing technique enhances SNR under ultimate defect conditions and improves overall performance of AVI system.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.1-9
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• 2020

Large-scale industrial facility structures continue to deteriorate due to the effects of operating and environmental conditions. The problems of these industrial facilities are potentially causing economic losses, environmental pollution, casualties, and national losses. Accordingly, in order to prevent disaster accidents of large structures in advance, the necessity of diagnosing structures using non-destructive inspection techniques is being highlighted. The defect occurrence, location and defect type of the structure are important parameters for predicting the remaining life of the structure, so continuous defect observation is very important. Recently, many researchers have been actively researching real-time monitoring technology to solve these problems. Structure Health Monitoring Inspection is a technology that can identify and respond to the occurrence of defects in real time, but there is a limit to check the degree of defects and the direction of growth of defects. In order to compensate for the shortcomings of these technologies, the importance of defect imaging techniques is emerging, and in order to find defects in large structures, a method of inspecting a wide range using guided ultrasonic is effective. The work presented here introduces a calculation for the shape factor for evaluation of the damaged area, as well as a variable β parameter technique to correct a damaged shape. Also, we perform research in modeling simulation and an experiment for comparison with a suggested inspection method and verify its validity. The curved structure image obtained by the advanced RAPID algorithm showed a good match between the defect area and the shape.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.89-93
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• 2002

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.68-75
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• 1996

More accurate inspection method for facilities of nuclear power plants is required to guarantee the continuous and stable energy supply. The portion of inspection for pipes and pressure vessels is relatively big in the power plants. Conventional inspection methods using ultrasonic wave, x-ray and eddy current for nondestructive testing in nuclear power plants have been performed as the method of contact with objects to be inspected. With this reason these methods have been taken relatively much time, money and manpower. And the area to be inspected is limited by the location of probe or film. These difficulties make the inspection into a time-consuming work. We propose an optical defect detection method using phase shifting realtime holographic interferometry. This method has an advantage that the inspection can be performed at a time for relatively wide area illuminated by the laser beam, a coherent light source and can help an inspector recognize not only defects but also the high stressed areas. In this paper we show that the quantitative measurement using holographic interferometry and image processing for defect in pressure vessels is possible.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.619-625
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• 2015

There is a large interest to find reliable and automatic methods for crack detection and quantification in the railway bogie frame. The non-destructive inspection of railway bogie frame has been performed by ultrasonic and magnetic particle testing in general inspection. The magnetic particle method has been utilized in the defect inspection of the bogie frame but the grinding process is required before inspection and the dust is developed resulting from the processing. The objective of this paper is to apply the inspection method of bogie frame using infra-red thermography. The infra-red thermography system using the excitation of eddy current was performed for the defect evaluation of weld specimen inserted artificial defects. The result shows that the infra-red thermography method can detect the surface and inner defects in weld specimen for bogie frame.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.826-828
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• 2014

Recently trend of product is miniaturization. As a result, We need products surface as well as products internal defect inspection. Generally, Inspection products in production process uses a lot of optical inspection. However, This is difficult to internal inspection of products. We used optical device instead of X-ray generator. At the same time, We have developed system to determine the product defect. First, obtain X-ray image from Machine vision function. Next, Measured value is recognize suitability within error range. otherwise recognize defect. Results presence of defective products can be stored by user.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.727-734
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• 2003

Recently various quality assurance activities have been applied in software industry for the purpose of software qualify improvement, and the ultimate target of those activities are focused on removing defects from its developed applications. We declared "ZERO DEFECT 21" movement on March 1999 whose purpose is to deliver defect-free applications to the customer. In this paper we would like to introduce the followings $\circled1$ Approaching Methods, $\circled2$ Achievements of "ZERO DEFECT 21". After accomplishing first you of "ZERO DEFECT 21" movement which consist of Audits and Software inspections, we could get the following improvement . $\circled1$ due to conducting the "Audits," we could prevent 22 cases of customer claims, enhance 11.7% of design quality and improve 23.3% of deliverable reusability : $\circled2$ also, due to conducting the "Periodic Sampling inspection and Final inspection," we could enhance 123% of defect rate compared with early stage of development and 247% of defect rate compared with previous yew. Based on the survey results, we could conclude that "ZERO DEFECT 21 " movement provides confidence to project team members and reliability to our customers.ce to project team members and reliability to our customers.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.365-370
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1973-1979
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• 2000

Driving the need for machine vision system is growing consumer demand for quality and defect-free products. Especially it is the most important in tarpaulin's manufacturing process achieves automatically by machine vision instead of by man vision. In this paper pinholes detection is performed by using morphology algorithms. Top hat transform is one of morphology applications. This transform take high performance of defect detection in the case that unexpected changes occur in some non-uniform background. For pinholes defect, automatic visual inspection system has been developed, which was composed by a line-scan camera, illumination, a frame grabber, a motor driver and control units. This system has excellent capacity to defect pinholes to the 0.1 mm by 0.5 mm in size and to work in moving objects by maximum 20 m/min in speed.