• Tribology and Lubricants
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• v.15 no.3
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• pp.257-264
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• 1999

Recently as electronics and semi-conductor industry develop, ultra-precision machine tools that use air-spindle with externally pressurized air bearing appear in need of ultra-precision products which demand high precision property. Effects of air compressibility absorbs the vibration of shaft, this is called averaging effect, however, the higher running accuracy is demanded by degrees, the more important factor is machining errors that affect running accuracy of shaft. Actually, it would be very important in the view points of running accuracy to understand effects of machining errors on the running accuracy of the spindle system quantitatively to design and manufacture precision spindle system in the aspect that efficiency in manufacturing spindle system and performance in operation. So fu, there are some researches on the effects that machining error affect running accuracy. However, because these researches deal with one bearing of spindle system, these results aren't enough to explain how much machining errors affect running accuracy in the typical spindle system overall. In this study, we investigate the effects of the perpendicularity error of bearing and shaft on running accuracy of spindle system that consists of journal and thrust bearing theoretically, and suggest design guideline about shape tolerances.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.65-70
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• 2002

The rotational performance off machine tool spindle has a direct influence upon the surface finish of the finished workpiece. This running accuracy of the spindle is improved by increasing preload on the bearings, while it results in higher temperature rise and larger thermal deformation. Therefore, finding the optimal preload condition for high speed spindle is very important factors in spindle motion. in spindle motion. In this study, the effect of the preload on the roundness accuracy has been examined at the different cutting conditions. Experiments were carried out to investigate the effects of the bearing preload on the running accuracy of high speed spindle which was supported by two angular contact bearings.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.107-119
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• 1991

This dissertation analyzes the running mechanism of flexible and thin tape above rotating head through the experiment. The scope of study is confined to measure the vertical deformation of running tape under hydrodynamic pressure invoking phenomena of elasto-hydrodynamic lubrication between the protruded bump on a rotating cylinder ad the running tape. Experimental system is devised to measure the vertical deflection of the running tape by opto-electronical displacement gauge, which enables to detect microscopic surface deflection of high frequency. Thorough the tests of small specimens of groove and bump, the accuracy and reliability of this experimental method is confirmed and achieved an accuracy within 5%(2.mu.m) error for the microscopic deflection with high frequency. In experimental works, the effects of bump size on flying characteristics of the tape were evaluated and examined. For the vertical deformation of the running tape. the numerical results and its trend agree qualitatively with the experimental ones.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.5 s.110
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• pp.441-451
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• 2006

It is known that ball bearings mounted in housing or on shaft are playing a key role to keep it running smoothly. The roundness of a housing bore on which bearing outer ring is mounted with interference has directly affected the running accuracy of bearing. The running accuracy of bearing, therefore, can extend the significant influence to the rotating machinery as well. In this paper, bearing's vibration and fatigue life considering raceway roundness of ball bearing before and after mounted in housing bore are theoretically estimated. To perform analysis, a simple three degrees of freedom model was proposed and then Newton-Raphson iterative method was introduced to be utilized in the analysis. The results show that the vibration magnitude of ball bearing fitted into housing unit is appeared considerably larger than the one of its pre-assembling. And theoretical $L_{10}$ life which ninety percent of the bearing population will endure decreased in about fifty percent.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.112-118
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• 2005

Ball bearings which were fitted between housing and shaft play an important role in rotating shaft system smoothly, Therefore bearing's running accuracy has significant influence on that of rotating machinery. Manufacturing accuracy of bearings as well as that of shaft and housing is main factor to affect bearing running accuracy In this paper, bearing's vibration and fatigue life considering raceway roundness of ball bearing before and after being fitted into housing are theoretically estimated. To perform analysis, a simple three degrees of freedom model was proposed and then these analysis was conducted utilizing the Newton-Raphson iterative method. The results show that vibration magnitude of ball bearing fitted into housing is considerably larger than before assembly, and bearing's theoretical L$_{10}$ fatigue life that ninety percent of the bearing population will endure decreased in about fifty percent.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.259-264
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• 2019

This paper proposes an image prediction system architecture for deep running in enterprise environment. Easily transform into an artificial intelligence platform for an enterprise environment, and allow sufficient deep-running services to be developed and modified even in Java-centric architectures to improve the shortcomings of Java-centric enterprise development because artificial intelligence platforms are concentrated in the pipeline. In addition, based on the proposed environment, we propose a more accurate prediction system in the deep running architecture environment that has been previously learned through image forecasting experiments. Experiments show 95.23% accuracy in the image example provided for deep running to be performed, and the proposed model shows 96.54% accuracy compared to other similar models.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.450-459
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• 2023

According to Korea Maritime Safety Tribunal, there have been 14,100 maritime accidents from 2017 to 2021. Among those accidents, ship collision accidents have been up to 1,275 cases. But in the accidents relating to small ships like a fishing vessel, analyzing the causes of the accidents would depend on statements of the persons related because there is often no navigational data. But those statements can be incorrect and give rise to disagreements between them so that it causes conflicts with each other during the trial. So a replay system of ship collision accident (RESCA) has been developed in order to reproduce the ship collision accident by using AIS, V-PASS or radar data. But the reproduced trajectory of ship collision accident is needed to be verified because it can be unreasonable physically. So a method to verify the reproduced trajectory and collect the physical data on ship collision accident is newly designed by using free running test. In the RESCA, the accident is reproduced using the navigational data from the trajectory for a ship and measured from free running model test for the other ship at the same time. Through free running test, the behavior of the model ship is transformed from model scale into real scale. In order to check into the accuracy of the new method, free running model tests by using RESCA are carried out on the actual ship collision accidents.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.299-303
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• 2017

By piling up hidden layers in artificial neural networks, deep learning is delivering outstanding performances for high-level abstraction problems such as object/speech recognition and natural language processing. Alternatively, deep-learning users often struggle with the tremendous amounts of time and resources that are required to train deep neural networks. To alleviate this computational challenge, many approaches have been proposed in a diversity of areas. In this work, two of the existing Apache Spark-based acceleration frameworks for deep learning (SparkNet and DeepSpark) are compared and analyzed in terms of the training accuracy and the time demands. In the authors' experiments with the CIFAR-10 and CIFAR-100 benchmark datasets, SparkNet showed a more stable convergence behavior than DeepSpark; but in terms of the training accuracy, DeepSpark delivered a higher classification accuracy of approximately 15%. For some of the cases, DeepSpark also outperformed the sequential implementation running on a single machine in terms of both the accuracy and the running time.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.353-358
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• 2010

This research introduces a new and improved design for a pneumatic cylinder driven roll feeder wherein each of the principal rotating feeder parts is configured so as to have feeding accuracy and to be low manufacturing cost. The feed pitch accuracy of the proposed roll feeder was evaluated by measuring lengths of cut offs of the strip stock with a shear attached to an air press. The air press was designed, manufactured, and mounted on the same table of the proposed roll feeder such that the strip stock maintained horizontal plane until the strip stock entered into the shear. The proposed roll feeder and the air press were designed to be operated automatically by a PLC employed controller. The feed pitch accuracy of the proposed roll feeder was analyzed by setting the pitch as 10, 12.5, and 15mm. At each predetermined feed pitch, the proposed roll feeder was tested 300 times as one test set and replicated three times. The average lengths of the cut offs of the strip stock ranged from 9.98 to 10.13mm, from 12.42 to 12.57mm, and from 14.96 to 15.06mm at the predetermined 10, 12.5, and 15mm feed pitch, respectively, among the total of 900 samples of each feed pitch. Main cause of variation of the length of the cut off of the strip stock fed by the proposed roll feeder was considered to be fluctuation of the air press during recompressing period of the air compressor to pressurize the air in the air tank. The largest difference between the maximum and the minimum length of the cut off was appeared while the air compressor recompressing the air. The air compressor used for this study restricted the air delivered to the proposed roll feeder while it was still running. Thus, this air delivery restriction problem should be improved by stabilizing the air press while the proposed roll feeder is running.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.892-904
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• 2021

An image semantic segmentation model is proposed based on improved ENet network in order to achieve the low accuracy of image semantic segmentation in complex environment. Firstly, this paper performs pruning and convolution optimization operations on the ENet network. That is, the network structure is reasonably adjusted for better results in image segmentation by reducing the convolution operation in the decoder and proposing the bottleneck convolution structure. Squeeze-and-excitation (SE) module is then integrated into the optimized ENet network. Small-scale targets see improvement in segmentation accuracy via automatic learning of the importance of each feature channel. Finally, the experiment was verified on the public dataset. This method outperforms the existing comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU) values. And in a short running time, the accuracy of the segmentation and the efficiency of the operation are guaranteed.