• Title/Summary/Keyword: electric train

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A Research to Decrease Airborne Microoganism the Train (전동차내 부유 미생물 저감방안에 관한 연구)

  • Choi, Sung-Ho;Choi, Soon-Gi;Son, Young-Jin
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.2895-2901
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    • 2011
  • SeoulMetro(line number 1 to 4) for the first half of the year. Therefore air quality in the subway is very important. It is passengers, such as sneezing and respiratory vital activities, Suspended due to skin keratin microbial action, and Microbial contaminants such as viruses. Hypersensitivity disorders, an atopic dermatitis, infectious diseases, allergic diseases, and can cause respiratory diseases. Ministry of Environment and National Institute of Environmental Research is managed so the life bacteria. It is emerging as the occupational health problems. Introduction of an appropriate ventilation system for cooling and dehumidification is needed. In line number 2, commuting and normal trains are measured in-room floating microbes. Suspended bacteria and fungi suspended in 2011 for 85 ~ 385$cfu/m^3$, 67 ~ 98$cfu/m^3$ is lower than baseline. Suspended to prevent microbial contamination and air conditioning equipment performance is a substantial improvement. Suspended micro-organisms and the impact on passenger room ventilation is increased. Electric car how to improve air quality substantially investigated.

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A Study on the Improvement of Reliability of Line Conversion Monitoring System using CCTV Camera (CCTV카메라를 활용한 선로전환감시시스템의 신뢰성 향상에 관한 연구)

  • Moon, Chae-young;Kim, Se-min;Ryoo, Kwang-ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.400-402
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    • 2019
  • The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.

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Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • 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.