• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. 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 and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.166-167
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• 2013

There has been a defect dispute of apartment building in Korea. The defect dispute is complicated by main issues and details of dispute. It is yet to be solved. Meanwhile, a judge does not a inspection and analysis, but, related field expert who contracted professional engineer does. As a result, defect consulting report that an important judgment is used in a defect dispute. Therefore, this study does research on structure of defect consulting report. A defect consulting report has same items, irrespective of a defect consultant as a result that check 7 indexes about 10 cases. It has different structure's details depending on each defect consultants. And, it inserts new detail or deletes existing detail, does not show clear distinction.

• Journal of Auto-vehicle Safety Association
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• v.4 no.2
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• pp.17-21
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• 2012

The periodic technical vehicle inspection is to prevent the accident through the finding and fixing the defects of the vehicle. The periodic technical vehicle inspection in Korea was studied for assessing the adequacy of the inspection frequency. The inspection frequencies of many countries including EU, USA and Japan were compared. The average mileages by the vehicle usage and type were represented. The warranty period and recommended replacement period of parts of the domestic auto makers was studied. Currently, the inspection frequency for the periodic technical vehicle inspection in Korea is appropriate. The pass-fail rate and the cost-benefit analysis for the periodic technical inspection in Korea will be needed in the decision making process for the inspection frequency.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.16-25
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• 2008

The micro needle means the ultrafine probe of 'Probe Card'. The size of micro needle is so minute that it is difficult to minute that it is difficult to inspect it with eyes. On the other hand it is very critical if there is a defect in micro needle of probe card. In this study, we developed an automatic visual inspection system for finding defect status in probe angle, tip length and diameter. Through the experimental results, we could find that our proposed method is better than human-eyes inspection method in accuracy and inspection speed, and also in robustness to lighting circumstances.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.116-121
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• 2018

According to the incresement of aging aircraft, Republic of Korea Air Force (RoKAF) conducted a teardown inspection of aircraft's EWIS (electrical wiring interconnection system) to determine the status of deterioration and the influence of failure occurrences due to it. The inspected aircraft were the retired fighter jets that had been used for more than 40 years. By analyzing defect type and the defect tendency, RoKAF can establish the necessary measures for the usage extension of their fleet and furthermore, the analysis results can be used as a basic data for the preparation of it's aircraft aging. EWIS inspection was done throughout careful visual inspection technique by removing all the ducts and pipes located in the fuselage and wings. For the aircraft wiring where no damage was found, the elongation tests were performed to determine the deterioration of wiring according to the location of the aircraft. The connectors, which is the main cause of intermittent failure, were completely disassembled and inspected for internal damage such as corrosion, abrasion, and traces of foreign objects. The detected defects were classified into 4 severity levels based on the type of damage, and the classified defects were weighted according to the criticality which may affects to it's system to establish the action plan.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.196-204
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• 2010

In this paper, we develope a defect inspection method for each buttons of keypad of cellular phones before they are assembled. The proposed algorithm consists of the similar color checking and its classification, font error detection, and scratch detection based on the segmentation of keypad area and font, translation and rotation processing sequentially. Especially, the proposed segmentation method approximate the pad region as B-spline function to deal with illumination change due to the shape of key button with the slant and curved surface followed by simple thresholding. And also, the rotational information is obtained by using eigen value and eigen vector very fast and effectively. The experimental results show that the performance of the proposed algorithm is good when it is applied to in-line process.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.622-634
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• 2003

This paper is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear plants. Problems on the shape identification are discussed arising in the characterization of a structural defect in a conductor using data of eddy current inspection. A surface defect on the generator tube ran be detected as a probe impedance trajectory by scanning a pancake type coil. First, a mathematical model of the inspection process is derived from the Maxwell's equation. Second, the input and output relation is given by the approximate model by virtue of the hybrid use of the finite element and boundary element method. In that model, the crack shape is characterized by the unknown coefficients of the B-spline function which approximates the crack shape geometry. Finally, a parameter estimation technique is proposed for recovering the crack shape using data from the probe coil. The computational experiments were successfully tested with the laboratory data.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2218-2223
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• 2014

A crack which is axially oriented with small size is hard to detect in conventional system. CMFL(Circumferential Magnetic Flux Leakage) type PIG(Pipelines Inspection Gauge) in the NDT(Nondestructive Testing), is operated to detect this defect called axially oriented cracks in the pipe. It is necessary to decompose the size and shapes of cracks for the maintenance of underground pipelines. This article is mainly focused on the decomposing method of the size and shape of the axially oriented cracks by using inspection signal data for defect.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.870-876
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• 2017

In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.