• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.241-248
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• 2011

In this paper we proposed and implemented a diagnosis system to control nuclear fuel handling machine. The proposed system consists of data acquisition system, diagnosis algorithm and faults simulator. Since the test on real operation of the fuel handling machine is impossible, we evaluated the proposed system by diagnosis experiments using the faults simulator, with which test signals on abnormal states of the bearing ball and the inner race of the bearing are generated. The experiments showed that resulting diagnosis analysis are consistent with the theoretical expectations.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.47-53
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• 2020

There is a need for a system that provides early warning of presence and type of failure of automobile wheel bearings through the application of predictive fault analysis technologies. In this paper, we presented a sensor module mounted on a wheel bearing and a diagnostic system that collects, stores and analyzes vehicle acceleration information and vibration information from the sensor module. The developed sensor module and predictive analysis system was tested and evaluated thorough excitation test equipment and real automotive vehicle to prove the effectiveness.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.9-18
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• 2015

Numerical analysis of PSC box bridge bearings for high speed KTX train vehicles has been carried out as a virtual simulation for Ubiquitous Technology. Improved numerical models of bridge, vehicle and interaction between bridge and train are considered, where bending and torsional modes are provided, whereas the exist UIC code is applied by the simplified HL loading. Dynamic and static analysed results are compared to get Dynamic Amplification Factors (D. A. F.) for maximum deflections and bending stresses up to running speed of 500 km/h. Equation from the regression analysis for the D. A. F. is presented. Sliding distance of the bearings for various KTX running speeds is compared with maximum and accumulated distances by the dynamic behaviors of PSC box bridge. Dynamic and static simulated sliding distances of the bearings according to the KTX running speed are proved as a major parameter in spite of the specifications of AASHTO and EN1337-2 focused on the distance by temperature variations.

• Journal of the Society of Disaster Information
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• v.8 no.2
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• pp.138-147
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• 2012

In this paper, the various parametric study of collisions between a offshore wind tower and vessels were performed to estimate the ultimate behaviors of the bucket foundation and the tower. Additionally, the stability of the foundation and the energy dissipation capacities of the tower were analyzed. The results shows that the collision energy of the vessel was mainly dissipated by the plastic deformation energy of the tower and the foundation system shown enough bearing capacity against to this severe loading condition.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.422-429
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• 2014

Proximity sensor networks are aimed at estimation kinematic state of target using estimated position of the target by each sensor node or target parameter. To analyze the kinematic state of target, traditional approaches require detections on multiple sensors, very large number of sensors to achieve acceptable performance. In this paper, we propose a novel method which can estimate predicted position of the underwater target using minimum proximity sensor with bearing information to this problem. The proposed algorithm was verified performance through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.96-101
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• 1998

다양한 통신욕구와 실시간 통신에 대한 수요가 증대하고 범세계적으로 글로벌시대가 도래함에 따라 정치, 사회, 전파, 기술에 큰 변화가 발생하고 있다 이에 따라 전파관리정책에서도 기존 주파수의 협대역화 및 재배치, 멀티플 액세스, 신규 주파수대역의 개발, 전파자원 관리방안 개선 및 투명성 확보 등 주파수 이용효율을 극대화하기 위한 정책 변화가 요구된다. 본 논문에서는 주요 선진국의 주파수 정책 중에서 성공한 사례를 분석하고, 우리나라의 주파수 이용현황 및 이용계획과 비교하여 우리나라에 맞는 주파수 정책 방향을 제시하였다.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.404-409
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• 2012

In order to detect and track target, submarine gather the target information(bearing, range, frequency and so on) with using multiple sensors. And submarine can estimate target states with target information. In this paper, we suggest the target motion analysis(TMA) filter architecture of submarine and the proposed TMA filter architecture is tested by a series of computer simulation runs and the results are analyzed and verified.

• Journal of the Korean Society for information Management
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• v.14 no.2
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• pp.47-83
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• 1997

The purpose of this study is to present scientific and technical information management policy for efficient support for technical cooperation with Russia and China. Bearing this purpose in mind, the main function, of Korea's scientific and technical information managing organizations related to Russia and China and the status of information management were examined, then the realities of, and controversial points on, technical cooperation have been investigated and analyzed. On the basis of this, this paper tried to present measures concerning the establishment of scientific and technical information managing policy, the securing of budget, the enforcement of scientific and technical information managing operations and the promotion of a comprehensive organization for scientific and technical information management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.128-139
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• 2017

Railway is one of the public transportation systems along with shipping and aviation. With the recent introduction of high speed train, its proportion is increasing rapidly, which results in the higher risk of catastrophic failures. The wheel bearing to support the train is one of the important components requiring higher reliability and safety in this aspect. Recently, many studies have been made under the name of prognostics and health management (PHM), for the purpose of fault diagnosis and failure prognosis of the bearing under operation. Among them, the most important step is to extract a feature that represents the fault status properly and is useful for accurate remaining life prediction. However, the conventional features have shown some limitations that make them less useful since they fluctuate over time even after the signal de-noising or do not show a distinct pattern of degradation which lack the monotonic trend over the cycles. In this study, a new method for feature extraction is proposed based on the observation of relative frequency energy shifting over the cycles, which is then converted into the feature using the information entropy. In order to demonstrate the method, traditional and new features are generated and compared using the bearing data named FEMTO which was provided by the FEMTO-ST institute for IEEE 2012 PHM Data Challenge competition.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.