• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.89-99
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• 2018

Downtime and malfunction of industrial rotor machines represents a crucial cost burden and productivity loss. Fault diagnosis of this equipment has recently been carried out to detect their fault(s) and cause(s) by using fault classification methods. However, these methods are of limited use in detecting rotor faults because of their hypersensitivity to unexpected and different equipment conditions individually. These limitations tend to affect the accuracy of fault classification since fault-related features calculated from vibration signal are moved to other regions or changed. To improve the limited diagnosis accuracy of existing methods, we propose a new approach for fault diagnosis of rotor machines based on the model generated by supervised learning. Our work is based on feature residual values from vibration signals as fault indices. Our diagnostic model is a robust and flexible process that, once learned from historical data only one time, allows it to apply to different target systems without optimization of algorithms. The performance of the proposed method was evaluated by comparing its results with conventional methods for fault diagnosis of rotor machines. The experimental results show that the proposed method can be used to achieve better fault diagnosis, even when applied to systems with different normal-state signals, scales, and structures, without tuning or the use of a complementary algorithm. The effectiveness of the method was assessed by simulation using various rotor machine models.

• Journal of Digital Policy
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• v.3 no.3
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• pp.9-14
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• 2024

In this paper, proposes a method using a multi block structure composed of residual blocks with adaptive weights to improve the quality of results in single image super resolution. In the process of generating super resolution images using deep learning, the most critical factor for enhancing quality is feature extraction and application. While extracting various features is essential for restoring fine details that have been lost due to low resolution, issues such as increased network depth and complexity pose challenges in practical implementation. Therefore, the feature extraction process was structured efficiently, and the application process was improved to enhance quality. To achieve this, a multi block structure was designed after the initial feature extraction, with nested residual blocks inside each block, where adaptive weights were applied. Additionally, for final high resolution reconstruction, a multi kernel image reconstruction process was employed, further improving the quality of the results. The performance of the proposed method was evaluated by calculating PSNR and SSIM values compared to the original image, and its superiority was demonstrated through comparisons with existing algorithms.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.85-87
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• 2008

DMWs are common feature of the PWR in the welded connections between carbon steel and stainless steel piping. The nickel-based weld metal, Alloy 82/182, is used for welding the dissimilar metals and is known to be susceptible to PWSCC. A round-robin program has been implemented to benchmark the numerical simulation of the transient temperature and weld residual stresses in the DMWs. To solve the round-robin problem related to Pressurizer Safety & Relief nozzle, the thermal elasto-plastic analysis is performed in the DMW by using the FEM. The welding includes both the DMW of the nozzle to safe-end and the SMW of the safe-end and piping. Major results of the analyses are discussed: The axial and circumferential residual stresses are found to be -88MPa(225MPa) and -38MPa(293MPa) on the inner surface of the DMW; where the values in parenthesis are the residual stresses after the DMW. Thermo-mechanical interaction by the SMW has a significant effect on the residual stress fields in the DMW.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.1-7
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• 2005

We propose an effective Landsat TM image compression method using the classified bidirectional prediction (CBP), the classified KLT and the SPIHT. The SPIHT is used to exploit the spatial redundancy of feature bands selected in the visible range and the infrared range separately. Regions of the prediction bands are classified into three classes in the wavelet domain, and then the CBP is performed to exploit the spectral redundancy. Residual bands that consist of difference values between the original band and the predicted band are decorrelated by the spectral KLT Finally, the three dimensional (3-D) SPIHT is used to encode the decorrelated coefficients. Experiment results show that the proposed method reconstructs higher quality Landsat TM image than conventional methods at the same bit rate.

• Steel and Composite Structures
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• v.21 no.4
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• pp.863-882
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• 2016

This study aims to introduce a new bracing system by which even super-wide frames with large openings can be braced. The proposed system, hereafter called Cable-Pulley Brace (CPB), is a tension-only bracing system with a rectilinear configuration. In CPB, a wire rope passes through a rectilinear path around the opening(s) and connects the lower corner of the frame to its opposite upper one. CPB is a secondary load resisting system with a nonlinear-elastic hysteretic behavior due to its initial pre-tension load. As a result, the required energy dissipation would be provided by the MRF itself, and the main intention of using CPB is to contribute to the initial and post-yield stiffness of the whole system. Using a stiffness calibration technique, optimum placement of the CPBs is discussed to yield a uniform displacement demand along the height of the structure. A displacement-based design procedure is proposed by which the MRF with CPB can be designed to achieve a uniform distribution of inter-story drifts with predefined values. Obtained results indicated that CPB leads to significant reductions in maximum and residual deformations of the MRF at the expense of minor increase in the maximum base shear and developed axial force demands in the columns. In the case of a typical 5-story residential building, compared to SMRF system, CPB system reduces maximum amounts of inter-story and residual drifts by 35% and 70%, respectively. Moreover, openings of the frame are not interrupted by the CPB. This is the most appealing feature of the proposed bracing system from architectural point of view.

• Steel and Composite Structures
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• v.23 no.6
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• pp.633-646
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• 2017

The compressive behavior of special-shaped concrete filled tube (CFT) mega column coupled with multiple cavities is studied by testing six columns subjected to cyclically uniaxial compressive load. The six columns include three pentagonal specimens and three hexagonal specimens. The influence of cavity construction, arrangement of reinforcement, concrete strength on failure feature, bearing capacity, stiffness, and residual deformation is examined. Experimental results show that cavity construction and reinforcements make it possible to form a combined confinement effect to in-filled concrete, and the two groups of special-shaped CFT columns show good elastic-plastic compressive behavior. As there is no axial bearing capacity calculation method currently available in any Code of practice for special-shaped CFT columns, values predicted by normal CFT column formulas in GB50936, CECS254, ACI-318, EC4, AISCI-LRFD, CECS159, and AIJ are compared with tested values. The calculated values are lower than the tested values for most columns, thus the predicted bearing capacity is safe. A reasonable calculation method by dividing concrete into active and inactive confined regions is proposed. And high accuracy shows in estimating special-shaped CFT columns either coupled with multiple cavities or not. In addition, a finite element method (FEM) analysis is conducted and the simulated results match the test well.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.159-171
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• 1996

The aim of this study is which factors affect the commercial land values and how they act upon them through distribution of commercial land values by multiple regression analysis in Gwangju city. The major findings of this study are as follows: (1) The changes of commercial land values distribution in $1989{\sim}1996$, We see that the commercial area of higher land values extends following the main arterial road. This is related to urbanization in urban fringe while the decline of commercial land values occurs in city center with long history of commercial region. This is due to unsuitableness in rapid changes of commercial environment because of fragmented lots, old buildings. traffic congestion etc. (2) The regions where commercial land values greatly rose are the west in constructed the new planning city center of Sangmu-dong. and the south west in which is related to the extension of high density apartment and the location of big discount stores. (3) Through the changes in commercial land values distribution map. and road map, topographical map, we know that commercial land values is related to various factors; namely, distance from CBD, convenient traffic, reputation of commercial district, condition of a road, size of supplementary, a degree of commercial land use etc. (4) From the above related factor, six variables are extracted by operational definition. That is the spatial distance from the city center, the walking distance to a stopping place, the road width, the amount of bus traffic, the amount of pedestrian, the number of the shop. (5) Data of seven variables are collected on the highest values point of each Dong. We applicate multiple regression analysis with commercial land values as a dependent variable, extracted six variables as independent variables. (6) As a result of multiple regression on the determinants of commercial land values, the variables which is greatly related to commercial land values are the amount of pedestrain, the spatial distance from city center. We identify that two variables explain variance of the commercial land values by 65%. (7) In order to make clear about not explained 35%. we carry out analysis of residual. In consequence, we see small estimate in downtown area and large estimate in urban fringe. This feature is due to simple core structure of Gwangju city and limits of this regression model.

• Journal of Welding and Joining
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• v.29 no.3
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• pp.76-81
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• 2011

Recently, the structural failures due to fatigue occur frequently with the increase of size of ships and offshore structures. In this respect, the assessment of fatigue life and the residual strength are very important. Currently, the smart materials technology has demonstrated a variety of possibilities for a diagnosis of structural strength and structural health condition for large structures. The benefits and feature of the MFC sensor are more flexible, durable and reliable than conventional smart material. In this study, Micro Fiber Composite (MFC) sensor for the measurement of stress intensity factor (SIF) of two dimensional cracks induced in a structure is developed. Two MFC sensors are placed in the vicinity of the crack tip close to each other with the crack tip in between them. The SIFs of Mode I($K_I$) as well as of Mode II($K_{II}$) based on the piezoelectric constitutive law and fracture mechanics are calculated. In this study, the SIF values measured by MFC sensors are compared with the theoretical results and measured value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.185-191
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• 2022

In this study, we propose a novel super-resolution neural network based on U-Net, residual neural network, and sub-pixel convolution. To prevent the loss of detailed information due to the max pooling of U-Net, we propose down-sampling and connection using sub-pixel convolution. This uses all pixels in the filter, unlike the max pooling that creates a new feature map with only the max value in the filter. As a 2×2 size filter passes, it creates a feature map consisting only of pixels in the upper left, upper right, lower left, and lower right. This makes it half the size and quadruple the number of feature maps. And we propose two methods to reduce the computation. The first uses sub-pixel convolution, which has no computation, and has better performance, instead of up-convolution. The second uses a layer that adds two feature maps instead of the connection layer of the U-Net. Experiments with a banchmark dataset show better PSNR values on all scale and benchmark datasets except for set5 data on scale 2, and well represent local area patterns.

• Journal of the Korean Society for Nondestructive Testing
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• v.7 no.2
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• pp.42-47
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• 1988

The off-axis tensile strength of the unidirectional carbon fiber reinforced plastic and the residual strength of impact damaged CFRP were measured and compared with the stress wave factor (SWF) of the specimens. The SWF values were measured to be decreased with the strength reduction in both cases and found to be useful for the nondestructive strength evaluation of unidirectional CFRP. The failure behaviour of the unidirectional CFRP during off-axis tensile testing was also monitored by acoustic emission(AE) method. The AE energy release showed the characteristic feature depending on the off-axis angle and this result was analyzed to be caused by the difference of the expected failure mode depending on the off-axis angle. The failure mode of CFRP was found to be analyzed by investigation of the peak amplitude distribution of AE.