• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1240-1246
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• 2006

Generally, there are two types of main factors to affect output power quality of a auxiliary power supply an EMU(electric multiple unit). One is a voltage flicker by amplitude modulation of short time and air compressors. The other is repetitive motion of large capacity motor such as air compressors, HVAC unit etc. in main factors. This paper compared two kinds of fluorescent lamp, 32W (after remodeling interior) and 40W(before remodeling interior) and measured the light output varying input power(AC220V) for a flicker phenomenon related power supply of lamps in EMU. Also, we analyzed a flicker considering EMU operating time and density in order to grasp main factors of a load change to cause a voltage change. As a results of test, a 40W fluorescent lamp was more insensitive with 20.26% degree an eye recognition degree sides about changes of the input power and lower with 19.9% voltage side generating flicker compare with fluorescent lamp 32W. Also, we confirmed the fact which the fluorescent lamp flicker was generated by varying fluorescent lamp output voltage when the commercial EMU was in high driving density and at the busy time. Additionally, we confirmed the frequency band which an EMU passenger could feel sensitively blinking of a fluorescent lamp was visually $8Hz{\sim}15Hz$.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.821-831
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• 2013

Recently image velocimetries, including particle image velocimetry (PIV) and surface image velocimetry (SIV), are often used to measure flow velocities in laboratories and rivers. The most difficult point in using image velocimetries may be how to determine the sizes of the interrogation areas and the measurement uncertainties. Especially, it is a little hard for unskilled users to use these instruments, since any standardized measuring techniques or measurement uncertainties are not well evaluated. Sometimes the user's skill and understanding on the instruments may make a wide gap between velocity measurement results. The present study aims to evaluate image velocimetry's uncertainties due to the changes in the sizes of interrogation areas and searching areas with the error analyses. For the purpose, we generated 12 series of artificial images with known velocity fields and various numbers and sizes of particles. The analysis results showed that the accuracy of velocity measurements of the image velocimetry was significantly affected by the change of the size of interrogation area. Generally speaking, the error was reduced as the size of interrogation areas became small. For the same sizes of interrogation areas, the larger particle sizes and the larger number of particles resulted smaller errors. Especially, the errors of the image velocimetries were more affected by the number of particles rather than the sizes of them. As the sizes of interrogation areas were increased, the differences between the maximum and the minimum errors seemed to be reduced. For the size of the interrogation area whose average errors were less than 5%, the differences between the maximum and the minimum errors seemed a little large. For the case, in other words, the uncertainty of the velocity measurements of the image velocimetry was large. In the viewpoint of the particle density, the size of the interrogation area was small for large particle density cases. For the cases of large number of particle and small particle density, however, the minimum size of interrogation area became smaller.