• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.873-880
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• 2008

When checking the state of deterioration or damage structures, regular visual inspection has very important role. At this point, a visual inspection is performed mainly by sketch or photography with a camera of inspectors. If that happens, it takes a lot of effort and time to inspect appearance damages. The purpose of this study is to develop the automatic recognition system for a more efficient and effective inspection of appearance damages. In the process, the image processing technology and the data management & analysis system for damage recognition are mainly developed and applied. This automatic recognition system enables inspectors or clients to obtain correct data that can recognize a damage, such as, crack, water leakage, efflorescence, delamination (peeling), spalling, etc. In addition, this study takes aim at the effect of secure safety, functional maintenance and extension of design lifetime according to build up continuous and systematic data management system.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.505-510
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• 2024

Since rolling contact fatigue cracks can always occur on the rail surface, which is the contact surface between wheels and rails, railway rails require thorough inspection and diagnosis to thoroughly inspect the condition of the cracks and prevent breakage. Recent detailed guidelines on the performance evaluation of track facilities present the requirements for methods and procedures for track performance evaluation. However, diagnosing and grading rail surface damage mainly relies on external inspection (visual inspection), which inevitably relies on qualitative evaluation based on the subjective judgment of the inspector. Therefore, in this study, we conducted a deep learning model study for rail surface defect detection using Fast R-CNN. After building a dataset of rail surface defect images, the model was tested. The performance evaluation results of the deep learning model showed that mAP was 94.9%. Because Fast R-CNN has a high crack detection effect, it is believed that using this model can efficiently identify rail surface defects.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.161-164
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• 2006

In this thesis we designed the vision system to inspect the defect of a back light unit of plat panel display device. The vision system is divided into hardware and inspection algorithm of defect. Hardware components consist of illumination part, robot-arm controller part and image-acquisition part. Illumination part is made of acrylic panel for light diffusion and five 36W FPL's(Fluorescent Parallel Lamp) and electronic ballast with low frequency harmonics. The CCD(Charge-Coupled Device) camera of image-acquisition part is able to acquire the bright image by the light coming from lamp. The image-acquisition part is composed of CCD camera and frame grabber. The robot-arm controller part has a role to let the CCD camera move to the desired position. To take inspections of surface images of a flat panel display it can be controlled and located every nook and comer. Images obtained by robot-arm and image-acquisition board are saved on the hard-disk through windows programming and are tested whether there are defects by using the image processing algorithms.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.429-436
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• 2014

Most mechanical systems are now operating consistently and getting faster due to the development of automation systems. Peoples' dependence on machines have increased as when problems occur within the mechanical system, personal injury and production loss may come as a result, as most of the mechanical system's malfunctions are caused by the failure of the rotational bearing. What we need now is a maintenance system that can warn us when it detects abnormal conditions before significant damage occurs to the bearing. In this study, we have developed an acoustic emissions sensor that can figure if the bearing works under the normal condition. With this acoustic emissions sensor, we can inspect the bearing for defects by using the Heterodyne technique, which converts the ultrasound signal into audio, as a signal conditioning process.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.6
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• pp.439-445
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• 2005

The stud bolt is one of crucial parts for safe operation of reactor vessels in nuclear power plants, Crack initiation and propagation were reported in stud bolts that arc used for closure of reactor vessel and head, Stud bolts are inspected by ultrasonic technique during overhaul periodically for the prevention of stud bolt failure which could induce radioactive leakage from nuclear reactor, In conventional ultrasonic testing for inspection of stud bolts, cracks are detected by using shadow effect It takes too much time to inspect stud bolts by using conventional ultrasonic technique. In addition, there were numerous spurious signals reflected from every oblique surfaces of thread, In this study, the signal processing technique for enhancing conventional ultrasonic technique was introduced for inspecting stud bolts. The signal processing technique provides removing spurious signal reflected from every oblique surfaces of thread and enhances detectability of defects. Detectability for small crack was enhanced by using this signal processing in ultrasonic inspection of stud bolts in Nuclear Power Plants.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.2
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• pp.127-132
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• 2005

The optical glass lens is required high dimensional precision such as the lack of defect. In this paper, we examined the detectable defect by using the resonant ultrasound spectroscopy(RUS). The RUS is the measurement system which is to excite the specimen and to inspect the differences of resonant frequency pattern between acceptable specimen and specimen which has some defects. In this paper, for nondestructive evaluation by using RUS, we measured the resonant frequency of each specimen which is spherical and aspherical glass lens. With the results, we knew the polishing processing degree of spherical glass lens by the measured resonant frequency and could evaluate the characteristic of aspherical glass lens about some flaws.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.67-73
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• 2008

The most common method of pipeline inspection is to use a remote-controlled-machine equipped with a CCTV, which, however, has many limitations to accurately inspect pipeline condition. In case of a typical CCTV, since the camera looks at the end point of the pipe, the locations of the defects and distance-readings are often different. In addition, the quality and accuracy of the inspection is highly dependent on the operator's skill and experience. In this research a new system is developed by use of the image processing techniques and the lens combination. The image acquisition system is developed that acquires the front and the side view of the pipe simultaneously. Side view unwrapping and stitching technology using image process techniques are developed which delivers high resolution image data.

• Journal of the Microelectronics and Packaging Society
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• v.8 no.3
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• pp.1-9
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• 2001

This paper proposes an inspection algorithm for micro ball grid array ($\mu$BGA) solder balls. This algorithm is motivated by the difficulty of finding defect balls by human visual inspection due to their small dimensions. Specifically, it is developed herein an automated vision-based inspection algorithm for $\mu$BGA's, which can inspect solder balls not only for so-called two dimensional errors, such as missings, positions and sizes, but also for height errors. The inspection algorithm uses two dimensional images of $\mu$BGA obtained through special blue illumination, and processes them with a rotation-invariant sub algorithm. It can also detect height errors when a two-camera system is available. Simulation results show that the proposed algorithm is more efficient in detecting ball defects compared with the conventional algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.384-391
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• 1998

When a device is mounted on the PCB, it is impossible to have zero defects due to many unpredictable problems. Among these problems, devices with bent corner leads due to mis-handling and which are not placed at a given point measured along the axis are principal problem in SMT(Surface Mounting Technology). It is obvious that given the complexity of the inspection task, the efficiency of a human inspection is questionable. Thus, new technologies for inspection of SMD(Surface Mounting Device) should be explored. An example of such technologies is the Automated Visual Inspection(AVI), wherein the vision system plays a key role to correct this problem. In implementing vision system, high-speed and high-precision are indispensable for practical purposes. In this paper, a new algorithm based on the Radon transform which uses a projection technique to inspect the FIC(Flat Integrated Circuit) device is proposed. The proposed algorithm is compared with other algorithms by measuring the position error(center and angle) and the processing time for the device image, characterized by line scan camera.