• 제목/요약/키워드: bearing frequencies

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유연한 지지 구조와 유체 동압 베어링으로 지지되는 HDD의 회전 유연 디스크-스핀들 시스템에 대한 유한 요소 고유 진동 해석 (Finite Element Modal Analysis of a Spinning Flexible Disk-Spindle System Supported by Hydro Dynamic Bearings and Flexible Supporting Structures In a HDD)

  • 한재혁;장건희
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 추계학술대회논문집
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    • pp.572-578
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    • 2003
  • The free vibration of a spinning flexible disk-spindle system supported by hydro dynamic bearings in a HDD is analyzed by FEM. The spinning flexible disk is described using Kirchhoff plate theory and von Karman non-linear strain, and its rigid body motion is also considered. It is discretized by annular sector element. The rotating spindle which includes the clamp, hub, permanent magnet and yoke, is modeled by Timoshenko beam including the gyroscopic effect. The flexible supporting structure with a complex shape which includes stator core, housing, base plate, sleeve and thrust pad is modeled by using a 4-node tetrahedron element with rotational degrees of freedom to satisfy the geometric compatibility. The dynamic coefficients of HDB are calculated from the HDB analysis program, which solves the perturbed Raynolds equation using FEM. Introducing the virtual nodes and the rigid link constraints defined in the center of HDB, beam elements of the shaft are connected to the solid elements of the sleeve and thrust pad through the spring and damper element. The global matrix equation obtained by assembling the finite element equations of each substructure is transformed to the state-space matrix-vector equation, and the associated eigenvalue problem is solved by using the restarted Arnoldi iteration method. The validity of this research is verified by comparing the numerical results of the natural frequencies with the experimental ones. Also the effect of supporting structures to the natural modes of the total HDD system is rigorously analyzed.

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아스팔트 노반 설계를 위한 간이 비파괴시험에 의한 동탄성계수 취득방법 적합성 분석 (Application of a Simple Non Destructive Test Method to Obtain the Dynamic Modulus of Asphalt Mixtures used for an Asphalt Trackbed Foundation)

  • 임유진;이성혁;이진욱;이병식
    • 한국철도학회논문집
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    • 제17권2호
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    • pp.114-122
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    • 2014
  • 지지력과 주행쾌적성을 개선시키기 위하여 아스팔트노반의 도입이 고려되고 있다. 다져진 아스팔트 혼합물의 동탄성계수는 아스팔트 노반설계에 있어 매우 중요한 설계입력요소이다. 동탄성계수($E^*$)를 획득하기 위하여 사용할 수 있는 간이 시험법으로서 소형충격공진시험 및 초음파시험의 사용적합성을 분석하였다. 간이 시험법에 의한 시험결과의 신뢰도를 검토하기 위하여 혼합물의 동탄성계수 예측식으로 사용되는 AASHTO 2002 MEPDG 제안식 및 한국형 포장설계법(KPRP)에서 제시한 예측식 계산 결과와 간이 비파괴시험법에 의한 취득결과를 비교, 분석하였다. 분석한 실험결과는 추가시험과 보완을 통해 철도 아스팔트 노반설계를 위한 간이시험법으로 적용할 수 있을 것으로 판단되었다.

고압전동기용 진동 감시 시스템을 위한 특징 파라미터 추출기법 개발 (Development of the Extracting Technique of the Character Parameter for the Vibration Monitoring System in High Voltage Motor)

  • 이달호;박정철
    • 한국정보전자통신기술학회논문지
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    • 제12권4호
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    • pp.349-358
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    • 2019
  • 본 논문에서는 회전체의 특징 파라미터들을 추출하기 위한 센서의 신호들을 수집하는 방법을 연구하고자 한다. 이를 위해, 모형 시험을 수행하기 위한 진동 테스트 리그를 개발하여 정상적으로 운전하에서의 신호특성을 분석하였다. 다른 진동 요소들로부터 주기적인 충격에 의해 발생되는 진동 성분을 추출하기 위하여 포락 신호처리(Envelope FFT Analysis) 기법을 사용하였다. 회전속도에 따른 신호분석과 더불어 회전체의 저주파수 특성을 잘 나타내는 속도센서 및 진동 테스트 리그의 부하변화에 따른 신호를 분석하였다. 그 결과, 베어링 하우징에서 측정되는 가속도 신호는 진폭이 작으며 조화 성분과 모터의 회전주파수 성분만이 발생함을 확인하였다. 즉, 회전수가 높아짐에 따라 가속도의 진폭이 높아짐을 확인할 수 있었다. 회전속도가 증가하면 원 데이터의 형상의 차이가 있는 것을 확인할 수 있었고, 가속도 FFT 그래프와 비교하였을 경우 저 주파수에서 노이즈에 강하며 해당 회전 주파수 성분을 뚜렷하게 나타내었다. 또한 부하를 변화시켜도 주요 회전 주파수 성분이 증가하지 않음을 알 수 있었다.

고효율 회전형 정전 나노 발전기의 기구학적 설계 (Kinematic Design of High-Efficient Rotational Triboelectric Nanogenerator)

  • 이지현;나성민;최덕현
    • 한국전기전자재료학회논문지
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    • 제37권1호
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    • pp.106-111
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    • 2024
  • A triboelectric nanogenerator is a promising energy harvester operated by the combined mechanism of electrostatic induction and contact electrification. It has attracting attention as eco-friendly and sustainable energy generators by harvesting wasting mechanical energies. However, the power generated in the natural environment is accompanied by low frequencies, so that the output power under such input conditions is normally insufficient amount for a variety of industrial applications. In this study, we introduce a non-contact rotational triboelectric nanogenerator using pedaling and gear systems (called by P-TENG), which has a mechanism that produces high power by using rack gear and pinion gear when a large force by a pedal is given. We design the system can rotate the shaft to which the rotor is connected through the conversion of vertical motion to rotational motion between the rack gear and the pinion gear. Furthermore, the system controls the one directional rotation due to the engagement rotation of the two pinion gears and the one-way needle roller bearing. The TENG with a 2 mm gap between the rotor and the stator produces about the power of 200 ㎼ and turns on 82 LEDs under the condition of 800 rpm. We expect that P-TENG can be used in a variety of applications such as operating portable electronics or sterilizing contaminated water.

Wavelet Thresholding Techniques to Support Multi-Scale Decomposition for Financial Forecasting Systems

  • Shin, Taeksoo;Han, Ingoo
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.175-186
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    • 1999
  • Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

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Wavelet Thresholding Techniques to Support Multi-Scale Decomposition for Financial Forecasting Systems

  • Shin, Taek-Soo;Han, In-Goo
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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    • pp.175-186
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    • 1999
  • Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

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형질전환 초파리에서 Heterocyclic Amines와 Aflatoxin $B_1$에 의한 체세포 돌연변이 유발의 고감수성에 관한 연구 (Hypersensitivity of Somatic Mutations and Mitotic Recombinations Induced by Heterocyclic amines and Aflatoxin $B_1$ in Transgenic Drosophila)

  • 최영현;유미애;이원호
    • 한국응용곤충학회지
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    • 제35권4호
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    • pp.315-320
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    • 1996
  • Drosophila의 actin 5C 유전자 promoter에 쥐의 DNA polymerase $\beta$cDNA를 도입시킨 형질전환 초파리가 고감수성 환경성 변이원 검출계로 사용할 수 있는지를 조사하였다. 체세포 염색체 재조환과 체세포 염색체 돌연변이의 검출을 위해서는 geterozygous(mwh/+) 계통을 사용하였다. 염색체상의 결실이나 비분리 등에 의한 small mwh spot의 자연 발생적 빈도는 non-transgenic w 계통과 transgenic p[pol $\beta$]-130 계통에서 각각 0.351 및 0.606 정도였다. 체세포 염색체 재조환에 의한 large mwh spot의 자연 발생적 빈도의 경우는 transgenic p[pol $\beta$]-130 계통(0.063)이 non-transgenic w 계통(0.021)에 비해 약 3배 정도 높게 나타났다. IQ, Glu-P-1 및 {TEX}$AFB_{1}${/TEX} 등의 돌연변이원의 처리에 의한 경우, 두 종류의 mutant clone의 발생 빈도는 쥐의 DNA polymerase $\beta$가 도입된 transgenic p[pol $\beta$]-130 계통이 non-transgenic w 계통에 비하여 모두 약 2-3배 정도 높게 나타났다. 본 연구의 결과는 쥐의 DNA polymerase $\beta$가 최소한 체세포 염색체 돌연변이 유발이나 체세포 염색체 재조환의 생성 과정에 관여함을 의미하며, 형질전환 초파리 계통이 환경성 변이원 검출계로서 충분한 응용가능성이 있음을 보여 주었다.

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The UGT1A9*22 genotype identifies a high-risk group for irinotecan toxicity among gastric cancer patients

  • Lee, Choong-kun;Chon, Hong Jae;Kwon, Woo Sun;Ban, Hyo-Jeong;Kim, Sang Cheol;Kim, Hyunwook;Jeung, Hei-Cheul;Chung, Jimyung;Rha, Sun Young
    • Genomics & Informatics
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    • 제20권3호
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    • pp.29.1-29.12
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    • 2022
  • Several studies have shown associations between irinotecan toxicity and UGT1A genetic variations in colorectal and lung cancer, but only limited data are available for gastric cancer patients. We evaluated the frequencies of UGT1A polymorphisms and their relationship with clinicopathologic parameters in 382 Korean gastric cancer patients. Polymorphisms of UGT1A1*6, UGT1A1*27, UGT1A1*28, UGT1A1*60, UGT1A7*2, UGT1A7*3, and UGT1A9*22 were genotyped by direct sequencing. In 98 patients treated with irinotecan-containing regimens, toxicity and response were compared according to the genotype. The UGT1A1*6 and UGT1A9*22 genotypes showed a higher prevalence in Korean gastric cancer patients, while the prevalence of the UG1A1*28 polymorphism was lower than in normal Koreans, as has been found in other studies of Asian populations. The incidence of severe diarrhea after irinotecan-containing treatment was more common in patients with the UGT1A1*6, UGT1A7*3 and UGT1A9*22 polymorphisms than in controls. The presence of the UGT1A1*6 allele also showed a significant association with grade III-IV neutropenia. Upon haplotype and diplotype analyses, almost every patient bearing the UGT1A1*6 or UGT1A7*3 variant also had the UGT1A9*22 polymorphism, and all severe manifestations of UGT1A polymorphism-associated toxicity were related to the UGT1A9*22 polymorphism. By genotyping UGT1A9*22 polymorphisms, we could identify high-risk gastric cancer patients receiving irinotecan-containing chemotherapy, who would experience severe toxicity. When treating high-risk patients with the UGT1A9*22 polymorphism, clinicians should closely monitor them for signs of toxicity such as severe diarrhea or neutropenia.