• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.489-495
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• 2010

Hyperspectral imaging obtains information with a wider wavelength range a large number of bands. However, a high correlation between each band, computation cost, and noise causes inaccurate results in cases of no pre-processing. The noises of band extraction and elimination positively necessary in hyperspectral imaging. Since the previous studies have used a characteristic the whole image, a local characteristic of the image is considered for the noise band extraction. In this study, the Quadtree, which is a data structure algorithm. and the fractal dimension are adopted for noise band extraction in Hyperion images. The fractal dimensions of the segments divided by the Quadtree structure are calculated, and variation is used. We focused on the extraction of random noise bands in Hyperion images and compared them with the reference data made by visual decisions. The proposed algorithm extracts the most bands, including random noises. It is possible to eliminate more than 30 noise bands, regardless of images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.269-286
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• 2018

Signal detection in symmetric alpha-stable ($S{\alpha}S$) distributed noise is a challenging problem. This paper proposes a detector based on a decreasing exponential function (DEF). The DEF detector can effectively suppress the impulsive noise and achieve good performance in the presence of $S{\alpha}S$ noise. The analytical expressions of the detection and false alarm probabilities of the DEF detector are derived, and the parameter optimization for the detector is discussed. A performance analysis shows that the DEF detector has much lower computational complexity than the Gaussian kernelized energy detector (GKED), and it performs better than the latter in $S{\alpha}S$ noise with small characteristic exponent values. In addition, the DEF detector outperforms the fractional lower order moment (FLOM)-based detector in $S{\alpha}S$ noise for most characteristic exponent values with the same order of magnitude of computational complexity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.588-595
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• 2014

In this paper, analysis of the vibration Characteristic for the Mine Detectable Test Platform is described. The test platform system is the multi-sensor mine detectable vehicle. This multi-sensor mine detectable unit is more efficient detection performance than other conventional methods. The test platform system has five subsystems, the UWB(Ultra Wide Band) sensor scanner, the MD(Metal Detector) sensor scanner, the neutron sensor scanner, and the detectable vehicle. We perform the vibration tests for the test platform and analyze the vibration characteristic, such as the max displacement, the max deformation and the max Von-Misses Stress.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.440-445
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• 2011

Dynamic characteristic analysis is required in developing SMT mounter system with high installation speed and position precision, because of vibration source occurred by positioning head. This paper presents the method of improving dynamic characteristic of SMT(Surface Mount Technology) mounter with finite element method and modal test. The design direction is that natural frequencies of SMT mounter must be higher than the vibration source. In addition, the effect of input shaping on residual vibration reduction is investigated by simulating the response of a first-order system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.12
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• pp.927-934
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• 2014

In this paper, analysis of the vibration characteristic for the mine detectable test platform is described. The test platform system is the multi-sensor mine detectable vehicle. This multi-sensor mine detectable unit is more efficient detection performance than other conventional methods. The test platform system has five subsystems, the UWB(ultra wide band) sensor scanner, the MD(metal detector) sensor scanner, the ND(neutron detector) sensor scanner, and the detectable vehicle. We perform the vibration tests for the test platform and analyze the vibration characteristic, such as the max displacement, the max deformation and the max Von-Misses stress.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1394-1399
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• 2001

The purpose of this paper is that investigates the dynamic behavior characteristic of W.T.S(Wind Turbine System) and carries out the evaluation analysis during operating W.T.S. To investigate the dynamic behavior characteristic of W.T.S. the experiments to measure vibration of the blade from the attached accelerometer on the flap and edge section of the blade that is one of the most important elements of dynamic characteristic of W.T.S are performed. Natural frequency and mode shape are calculated with commercial program (STAR MODAL) using the measured vibration acceleration that receives the signal with F.F.T Analyzer from the accelerometer. For validation of these experiments. the finite element analysis is performed with commercial F.E.M Program (ANSYS) on the basis of the natural frequency and mode shape. The results indicate that experimental values have good agreements with the finite element analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1347-1352
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• 2001

In this study, the acoustic properties of polyester sound absorbing materials with three different bulk densities were investigated by calculating and measuring the acoustic parameters in terms of characteristic impedance, propagation constant, and absorption coefficient. For the calculations, Delany and Bazley's empirical equation was used together with the experimentally obtained specific flow resistivities under steady flow conditions. For the experimental measurements, the well-known two-thickness method was accessed. The experimentally measured values of characteristic impedance and propagation constant were generally agreed well with the corresponding calculated values. Based on the comparisons between the calculations and measurements, it was found that the magnitude of the absorption coefficient was closely related to the characteristic impedance and the real part of the propagation constant. Especially, the maximum magnitude of the absorption coefficient was depended upon the imaginary part of the propagation constant indicating the phase change of the propagation constant.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.152-160
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• 2013

In this paper, to the aim of wideband SSN(Simultaneous Switching Noise) suppression characteristic, investigation of spiral resonator are used in conjunction with bead which is commonly used for noise suppression method. Bead works effectively to suppress the power noise up to the first harmonic of fundamental frequency, 0.8 GHz, and spiral resonator suppress noise well in the frequency range of SRF(Self Resonance Frequency) which is inversely proportional to the length of spiral. Thus, when bead used in conjunction with a spiral the noise suppression characteristic is determined by the one of higher impedance element of the two in the frequency range and achieves more broadband filtering characteristic. The case for using 22 nH bead turns out 4.8, 2.0, 0, and, 0.6 dB, and the case for using 22 nH bead in conjunction with 3-turns spiral achieves more wideband characteristic of 9.5, 8.3, 6.1, and 9.9 dB power noise suppression performances at the first, second, third, and fourth harmonics, respectively. The peak-to-peak voltage levels decrease from 76 mV to 56 mV using 22 nH bead, and the level decrease rapidly to 34 mV when using in conjunction with bead and 3-turn spiral. Thus more wideband SSN suppression characteristic can be achieved using bead with spiral.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.854-855
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• 2015

Electric machines for office automation device such as printer and scanner have been required the low noise and vibration performance. Many researches about the low noise and vibration of polygon mirror scanner motor have been also progressed. The noise and vibration of polygon mirror scanner motor can be classified by aerodynamic, structural and electromagnetic. Electromagnetic noise and vibration can be occurred by high cogging torque and nonsinusoidal back EMF. To improve the cogging torque and back EMF characteristic, we apply unequal air-gap. To analyse characteristic of a polygon mirror scanner motor, two dimensional finite element method is used. To minimize the cogging torque of a polygon mirror motor, Kriging based on latin hypercube sampling (LHS) is utilized. As a result, the cogging torque and torque ripple improved while maintaining the back EMF and average torque.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.904-908
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• 2008

As the various industrial production machinery has come into being by development of industrial technology, the productivity of the basic industrial production machinery has improved and the international competitiveness of the one of Korea has strengthened. However, at the same time, noise from various industrial production machinery disturbs the quiet environment. There are 35 kinds of the noise emission machinery defined in the noise and vibration control act according to the horse power and the number of machinery. These were classified in 1992 through investigation from 1990 to 1991, and the characteristic of the noise emission machinery may be different from the past one. So we need to investigate the characteristics of the noise emitted by machinery to control it rightly. Also we need to investigate the new noise emission machinery which has come into being recently. In this survey, we measured sound intensity of 32 noise emission machinery to calculate the sound power levels of those and investigated the characteristic of the sound power level of those according to the frequency. From the survey, we found that the forging machine, concrete pipe and pile making machine, sawing machine, etc. are the noisy machinery. And the automatic packing machine, sewing machine, centrifuge, etc. are the silent machinery. Also the generator, the concrete pipe and pile making machine, the printing machine, etc. emit the low frequency noise, and the molding machine, the stone cutter, the metal cutter, etc. emit the high frequency noise. Lastly, we intented to propose the proper guide line of classifying noise emission machinery.