• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1057-1064
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• 2017

High sensitivity magnetic sensor having foreign metal detection capability is proposed utilizing giant magneto-impedance effect. Strip sensor showed the increasing output voltage when the external magnetic field was applied along with strip from strip grounding point, although the initial DC voltage varied depending on the pointing direction of strip sensor. Proposed sensor was able to eliminate more than half of background noise using active noise filter to achive high sensitivity, and it showed the capability to detect magnetized foreign metal object independent of ambient electro-magnetic noise and earth magnet. In case of ferrous sphere, the metal detection up to 0.8mm diameter was experimentally demonstrated at 5mm distance from strip sensor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.99-107
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• 2023

Recently, the rate of death and safety accidents at construction sites is the highest among all kinds of industries. In order to apply artificial intelligence technology to construction sites, it is essential to secure a dataset which can be used as a basic training data. In this paper, a number of image data were collected through actual construction site, for which major construction equipment objects mainly operated in civil engineering sites were defined. The optimal training dataset construction was completed by annotation process of about 90,000 image dataset. Reliability of the dataset was verified with the mAP of over 90 % in use of YOLO, a representative model in the field of object detection. The construction equipment training dataset built in this study has been released which is currently available on the public data portal of the Ministry of Public Administration and Security. This dataset is expected to be freely used for any application of object detection technology on construction sites especially in the field of construction safety in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.679-689
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• 2014

In this paper, an analysis of the effect of time-variant reflected impedance and its detection method on wireless power transfer(WPT) systems are presented. The reflected resistance at WPT systems is very important parameter as it indicates how well matched antenna is and will exhibit high efficiency. Proposed detection method is based on transmitter current variation analysis with respect to frequency sweep. Using the proposed design method, a wireless power transfer system operating at the frequency of 125 kHz, is design and detect reflected impedance variation. The proposed design method provides good agreements between measured and simulated results. Therefore, The proposed detecting method provides a nonintrusive method to detect harmful object in WPT system.

• Journal of Chest Surgery
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• v.40 no.5 s.274
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• pp.384-387
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• 2007

The finding of a tracheal penetrating injury that's caused by a foreign body is rare in adulthood. A 42-year-old man had experienced penetrating trauma due to a glass fragment 10 years ago. He presented with blood tinged sputum and dyspnea on exertion, and this had developed 1 year previously. Chest CT scan and bronchoscopy revealed a foreign body crossing the tracheal lumen and the object arose from outside of the trachea; this was all associated with airway edema. We removed the foreign body, which was a 5cm length of glass fragment, and we repaired the tracheal defect using a simple primary suture. The postoperative course of the patient was uneventful and he is now being followed up at the outpatient department; he has had no additional symptoms.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.43-62
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• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.300-308
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• 2021

Usually, during slaughter, the meat is divided into large chunks by part after deboning. The meat chunks are inspected for the presence of needles with an X-ray scanner. Although needles in the meat chunks are easily detectable, they can also be found in trimmings and meat offals, where meat skins, fat chunks, and pieces of meat from different parts get agglomerated. Detection of needles in trimmings and meat offals becomes challenging because of many needle-like patterns that are detected by the X-ray scanner. This problem can be solved by learning the trimmings or meat offals using deep learning. However, it is not easy to collect a large number of learning patterns in trimmings or meat offals. In this study, we demonstrate the use of deep convolutional generative adversarial network (DCGAN) to create fake images of trimmings or meat offals and train them using a convolution neural network (CNN).

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.51-52
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• 2015

동영상에서의 객체추적을 위해 주파수변환을 적용하는 연구가 발표되고 있다. 주파수영역으로의 변환 방법은 FFT와 같은 고속변환을 적용하므로 실시간 객체 추적을 위해 좋은 방법이다. 동영상에서 이동 중인 객체는 인접 프레임에서 위치의 변화가 크지 않기 때문에 주파수영역으로의 변환 방법으로 고속 객체 탐색을 실현할 수 있다. 그러나 동영상에서 이동중인 객체는 형상이 조금씩 변할 수 있으므로 탐색기법은 이 점을 고려해야한다. 본 논문에서는 추적 대상 객체가 다른 물체에 의해 가려지는 상황에 따라 필터갱신을 적응적으로 수행하고 이동경로와 주변정보를 사용하고 검출 객체에 비례대칭평균화 전처리를 적용함으로써 추적 대상객체가 가려지는 상황에서도 추적 실패를 줄일 수 있는 객체 탐색 기법을 제안한다.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.737-739
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• 1996

Abnormal conditions and disturbances in distribution system cause an immediate influence to the customers. Conventional detection schemes for the distribution abnormalities have been applied in limited extents mainly because of their low reliability. In this paper, we developed a disturbance identification system which monitors the load level after a transient, checks the harmonic behavior of the load, and finally makes decision on the cause of the disturbance. This system identifies and discriminates overcurrent faults, arcing ground faults, recloser activities, and foreign object or tree contacts. In the implementation of the identification system, we applied fuzzy logic to better represent some variables whose Quantities are expressed only in non-numerical terms.