• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.1
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• pp.103-111
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• 1999

구조물에 손상이 발생하게 되면 동적특성이 변하게 된다. 그러므로 이와 갈은 특성을 계측하여 구조물의 손상된 정도를 평가하게 되면 이를 상시감시에 활용할 수가 있다. 대표적인 손상기술들을 제작된 모형교량에 서로 다른 경계조건을 구현하여 손상도를 Simulation을 이용하여 결정하고 가장 적법한 방법과 대책을 연구했다. 모형교량은 I-DEAS의 Normal Mode Dynamic Solver를 이용하여 분석 제작되어 계측과 비교평가 되어 손상기술에 적용되었다. 24개의 가속도 감지기를 이용하여 데이터를 획득하였고, Residue법으로 모달인자를 추출하였다. 추출된 동적인자가 상시감시에 적용하도록 구조물의 손상검출기술을 제안한다

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.866-869
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• 2004

Power transformers, air-intakes and stacks in the urban combined power plant are main noisy sources. Because of Inhabitant complaint by abnormal noise transferred from the power plant. the noise was investigated at power plant and uptown area. The result of diagnosis made the acoustic resonance phenomenon by 580Hz's combustion dynamic pressure with the standing wave mode of sound fields in exhaust passageway of gas turbine into main noise source of public complain. The abnormal noise is caused by the resonance exhaust noise transferred through stacks of power plant.

• Journal of Korean Neurosurgical Society
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• v.29 no.4
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• pp.580-585
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• 2000

The atlantoaxial rotatory fixation is a uncommon disease of deformity, occuring much more frequently in children than in adults. Despite of its benign clinical course, delayed recognition or improper management may cause persistent deformity or recurrence. We report three cases of typical atlantoaxial rotatory fixation. Successful reduction was achieved with posterior atlantoaxial fusion in one case and nonoperative treatment in others. We emphasize that it is necessary to perform dynamic CT scan to obtain correct diagnosis and to plan proper treatment for this disease entity.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.456-458
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• 1997

본 논문에서는 플랜트의 계측신호들에 나타나는 현상적인 특징파형들을 감지하여 플랜트의 고장을 진단하는 기법을 제시하고, 플랜트의 고장시 나타나는 여러 특징 파형들의 전형인 oscillatory 파형을 감지하는 알고리즘을 prediction filtering 기법을 적용하여 얻는 과정을 기술하였다. 또한 이의 구체적 적용 예로 500MW급 화력발전소의 보일러 제어 시스템을 대상으로 여러 고장상황에 대한 고장감지 알고리즘을 설계하였고 제시한 기법의 유용성을 보이기 위한 시뮬레이션 적용 결과를 보였다.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.347-354
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• 1994

This paper describes a diagnostic protocol of nonlinear dynamic characteristics of biological system using chaos theory. An integrated chaos analysis system for the diagnosis of biological system was designed. We suggest a procedure of attractor reconstruction for reliable qualitative and quantitative analysis. The effect of autonomic nervous system activity on heart rate variability with power spectral analysis and its characteristics of chaotic attractors are investigated. The results show the applicability to evaluate the mental and physical conditions using nonlinear characteristics of biological signal.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.94-102
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• 2000

This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the unknown nonlinear system, which can detect and isolate process faults continuously over all ranges of operating condition. The dynamic behavior of a nonlinear process is represented by a set of local linear models. The parameters of the DFM are identified by an on-line methods. The residual vector of the FDI system is consisted of the parameter deviations from nominal model and the set of grade of membership values indicating the operating condition of the nonlinear process. The detection and isolation of faults are performed via a neural network classifier that are learned the relationship between the residual vector and fault type. We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.219-225
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• 2015

In this paper, a three-dimensional model for the dynamic analysis of a flywheel based on the finite element method is presented. The static structure analysis for the model provides stress and strain distribution cloud charts. The modal analysis provides the basis of dynamic analysis due to its ability to obtain the natural frequencies and the vibration-made vectors of the first 10 orders. The results show the main faults are attrition and cracks, while also indicating the locations and patterns of faults. The harmonic response simulation was performed to gain the vibration response of the flywheel under operation. In this paper, we present a Hilbert-Huang transform (HHT) algorithm for flywheel vibration analysis. The simulation indicated that the proposed flywheel vibration signal analysis method performs well, which means that the method can lay the foundation for the detection and diagnosis in a reactor main coolant pump.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.73-81
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• 2006

This paper describes our primary study for a new method of recognizing materials, which is need for precision work system. This is a study of dynamic characteristics of smart sensors, new method$(R_{SAI})$ has the sensing ability of distinguishing materials. Experiment and analysis are executed for finding the proper dynamic sensing condition. First, we developed advanced smart sensor. We made smart sensors for experiment. The type of smart sensor is HH type. The smart sensor was developed for recognition of material. Second, we develop new estimation methods that have a sensing ability of distinguish materials. Dynamic characteristics of sensor are evaluated through new recognition index$(R_{SAI})$ that ratio of sensing ability index. Distinguish of object is executed with $R_{SAI}$ method relatively. We can use the $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object (auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• Journal of Korean Neurosurgical Society
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• v.29 no.12
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• pp.1570-1576
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• 2000

Objective : To evaluate objectively the sites of injury in patients with posttraumatic olfactory deficits and to suggest the diagnostic procedure for evaluation of posttraumatic anosmia. Methods : Ten patients with posttraumatic olfactory dysfunction were examined by means of olfactory testing, sinoscopy, contrast filled paranasal sinus computed tomography(contrast filled PNS CT) and magnetic resonance imaging(MRI). Five normal persons without olfactory dysfunction were also evauluated. The aerodynamic patency of olfactory cleft was examined by contrast filled PNS CT. The olfactory system(oflactory bulbs, olfactory tracts, inferior frontal region, hippocampi, or temporal lobes) was investigated in detail with MRI. The difference in the size of the olfactory bulb between normal volunteers and anosmic patients was evaluated by Student's t test. Results : Contrast filled dynamic CT scan was useful method for the evaluation of dynamic patency of the olfactory cleft. Paranasal CT scan of the all anosmic patients showed dynamic reflux of contrast media in olfactory cleft on valsalva maneuver. For the largest cross-sectional area and great height, the difference in olfactory bulb size between normal volunteers and patients was statistically significant(p<0.001) in MRI study. Conclusion : Posttraumatic anosmia was completely evaluated by olfactory testing, sinoscopy, and contrast filled CT scan for differentiation between conductive type and neurogenic type. Neurogenic anosmia was confirmed by perfect localization with MRI study.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.851-876
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• 2018

Dynamic time warping (DTW) is the main algorithms for time series alignment. However, it is unsuitable for quasi-periodic time series. In the current situation, except the recently published the shape exchange algorithm (SEA) method and its derivatives, no other technique is able to handle alignment of this type of very complex time series. In this work, we propose a novel algorithm that combines the advantages of the SEA and the DTW methods. Our main contribution consists in the elevation of the DTW power of alignment from the lowest level (Class A, non-periodic time series) to the highest level (Class C, multiple-periods time series containing different number of periods each), according to the recent classification of time series alignment methods proposed by Boucheham (Int J Mach Learn Cybern, vol. 4, no. 5, pp. 537-550, 2013). The new method (quasi-periodic dynamic time warping [QP-DTW]) was compared to both SEA and DTW methods on electrocardiogram (ECG) time series, selected from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) public database and from the PTB Diagnostic ECG Database. Results show that the proposed algorithm is more effective than DTW and SEA in terms of alignment accuracy on both qualitative and quantitative levels. Therefore, QP-DTW would potentially be more suitable for many applications related to time series (e.g., data mining, pattern recognition, search/retrieval, motif discovery, classification, etc.).