• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.6 no.1
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• pp.72-77
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• 2010

During the period of reinforcement work for the licensing renewal of CANDU NPP, the fuel channels, Calandria tubes and feeders of CANDU Reactor are replaced. The remote visual inspection of Calandria internal is also performed during the period of reinforcement work. This period is a unique opportunity to inspect the inside of the Calandria. The visual inspection for the Calandria vessel and its internals of Wolsong NPP Unit 1 was performed by Nuclear Engineering & Technology Institute(NETEC) of KHNP. To perform this inspection, NETEC developed equipment applied new technology such as the synchronization of 3D CAD, automatic alignment and control system. The inspection confirmed that the Calandria integrity of Wolsong NPP Unit 1 is perfect.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.99-105
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• 2009

Recently the research is much interested in about the inspection system using by computer vision system. In this paper, we deal with shape inspection technique for moving to be long and narrow object on conveyor belt. first, we are acquired for moving object on conveyor belt. then the object segmentation is using by color information for background and object. the object position be calculated by horizontal and a vertical histogram. second, we are checked for two hole in front part, widths and top/bottom side information in middle part, and finally checking for two holes in rear part. The performance of our proposed model is evaluated by experiments, within error of 1㎜, and can be checking to 17 object /min.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1120-1123
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• 1995

In this paper, an automatic B/STUD inspection system has been developed using the computer aided vision system. Index Table has been used to get the rapid measurement and multi-camera has been used to get the high resolution in mechanical system. Camera calibration was suggested to perform the reliable Inspection. Image processing and data analysis algorithms for B/STUD inspection system has been investigated and were performed quickly with high accuracy. As a result, Inspection system of a B/STUD can be measured with a high resolution in real time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.307-308
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• 2006

This paper is about the development of automatic inspection system of welded nuts on Support hinge using machine vision for the improvement of working condition. Until now, projection welding process was performed by operator. Also, inspection of welded nuts is performed manually and recorded by the operator's naked eye. So these processes caused the produce of poorly-made articles. To improve this manual operation, inspection system using machine vision is introduced. Test algorithm, lighting system and program showed good results to the designed inspection system and led to the increment of productivity.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.11-15
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• 2020

In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4145-4150
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• 2010

This research aims to design on an automatic machine vision system to replace eye inspection of alternator spool which is one of the key automotive parts. The alternator spool, plastic extrusion part would have various defects like unfinished, crack and burr. Through the design failure examples the optimized fast machine vision system will be designed to inspect all spools also focuses on the low cost machine for the middle sized company as 2'nd automotive supplier. 3-dimensional design softwares of Pro-Engineer & CATIA were used and the system were built based on the design. The system will contribute to satisfy the cycle time and can inspect each part in an absolutely accurate method, which is sufficient for industrial applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.365-371
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• 2011

Most recently issued paper money includes security patterns that can be only identified by ultra violet (UV) illuminations. We propose an automatic extraction method of UV patterns for paper money inspection systems. The image acquired by camera and UV illumination is transformed to input data through preprocessing. And then, the Gaussian mixture model (GMM) and split-and-merge expectation maximization (SMEM) algorithm are applied to segment the image represented by input data. In order to extract the UV pattern from the segmented image, we develop a criterion using the area of covariance vector and the weight value. The experimental results on various paper money are presented to verify the usefulness of the proposed method.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.784-791
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• 2022

Tack coat is a thin layer of asphalt between the existing pavement and asphalt overlay. During construction, insufficient tack coat layering can later cause surface defects such as slippage, shoving, and rutting. This paper proposed a method for tack coat inspection improvement using an unmanned aerial vehicle (UAV) and deep learning neural network for automatic non-uniform assessment of the applied tack coat area. In this method, the drone-captured images are exploited for assessment using a combination of Mask R-CNN and Grey Level Co-occurrence Matrix (GLCM). Mask R-CNN is utilized to detect the tack coat region and segment the region of interest from the surroundings. GLCM is used to analyze the texture of the segmented region and measure the uniformity and non-uniformity of the tack coat on the existing pavements. The results of the field experiment showed both the intersection over union of Mask R-CNN and the non-uniformity measured by GLCM were promising with respect to their accuracy. The proposed method is automatic and cost-efficient, which would be of value to state Departments of Transportation for better management of their work in pavement construction and rehabilitation.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• 한국기계연구소 소보
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• s.17
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• pp.61-68
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• 1987

The main objective of this paper is to develop the computer-aided vibrational signal processing and monitoring system of rotating machinery. This system has an automatic data acquisition capability and analyze for machine fault diagnosis. By spectrum analysis, machine’s failure can be identified. The monitoring system enables diagnosis of the fault in rotating machinery. In this study, the conventional electrical fans are selected as a model case. The date processing and fault monitoring system proposed here can be applied to the automation of the inspection process in assembling motor-shaft systems. The automatic inspection can enhance the product quality and keep it stable. Since the proposed system is developed for personal computers, it might be cheap in cost and easy in installation.