• 제목/요약/키워드: Error-Parameter($d_f$)

검색결과 16건 처리시간 0.028초

열화된 증기 터빈블레이드의 피로강도에 대한 확률론적 해석 (A Stochastic Analysis in Fatigue Strength of Degraded Steam Turbine Blade Steel)

  • 김철수;정화영;김정규
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집A
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    • pp.262-267
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    • 2001
  • In this study, the Reliability of degraded steam turbine blade was evaluated using the limited fatigue data. The statistical estimation of limited fatigue data implies that some unknown uncertainties which may be involved in fatigue reliability analysis. Therefore, an appropriate distribution in the fatigue strength was determined by the characteristic distribution - linear correlation coefficient, fatigue physics, error parameter. 3-parameter Weibull distribution is the most appropriate distribution to assume for infinite region. The load applied on the blade is mainly tensile. The maximum Von-Mises stress is 219.4 MPa at the steady state service condition. The failure probability($F_p$) derived from the strength-stress interference model using Monte carlo simulation under variable service condition is 0.25% at the 99.99% confidence level.

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역전파신경회로망을 이용한 피로균열성장과 수명 모델링에 관한 연구 (A Study on Fatigue Crack Growth and Life Modeling using Backpropagation Neural Networks)

  • 조석수;주원식
    • 대한기계학회논문집A
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    • 제24권3호
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    • pp.634-644
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    • 2000
  • Fatigue crack growth and life is estimated by various fracture mechanical parameters but affected by load, material and environment. Fatigue character of component without surface notch cannot be e valuated by above-mentioned parameters due to microstructure of in-service material. Single fracture mechanical parameter or nondestructive parameter cannot predict fatigue damage in arbitrary boundary condition but multiple fracture mechanical parameters or nondestructive parameters can Fatigue crack growth modelling with three point representation scheme uses this merit but has limit on real-time monitoring. Therefore, this study shows fatigue damage model using backpropagatior. neural networks on the basis of X-ray half breadth ratio B/$B_o$ fractal dimension $D_f$ and fracture mechanical parameters can predict fatigue crack growth rate da/dN and cycle ratioN/$N_f$ at the same time within engineering estimated mean error(5%).

A Study on Fatigue Damage Modeling Using Neural Networks

  • Lee Dong-Woo;Hong Soon-Hyeok;Cho Seok-Swoo;Joo Won-Sik
    • Journal of Mechanical Science and Technology
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    • 제19권7호
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    • pp.1393-1404
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    • 2005
  • Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can't predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X -ray half breadth ratio B / $B_o$, fractal dimension $D_f$ and fracture mechanical parameters can estimate fatigue crack growth rate da/ dN and cycle ratio N / $N_f$ at the same time within engineering limit error ($5\%$).

LRCS 강우-유출 모형의 보정 및 민감도 분석(II) : 적용 (Calibration and Sensitivity Analysis of LRCS Rainfall-Runoff Model(II) : Application)

  • 오규창;이길성;이상호
    • 한국수자원학회논문집
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    • 제32권6호
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    • pp.665-674
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    • 1999
  • 본 논문은 LRCS 모형을 낙동강 수계 송리원 수위표 지점의 18개 호우사상에 대하여 보정 및 민감도 분석을 실시하여 모형의 국내 하천에 적용성을 확인하였고, 모형의 적합성 분석 결과 LAD 추정자가 LS와 WLS에 비하여 좋지 못한 결과를 얻었다. "hot" 행렬의 대각 요소(hi)와 영향성 척도(Di)를 매개변수 추정치를 분석하는데 사용할 수 있고, 매개변수 IL이 모형 출력에 가장 중요함을 알 수 있었다. 매개변수의 오차에 따른 오차 전파의 정도는 IL, TP, F1 의 순서이며, 이는 모형의 출력이 첨두유량일 경우에 민감도의 정도를 나타낸다. 민감도 계수와 hi 의 대각 요소와 Di 값의 분석과 모형의 보정 및 민감도 분석의 관련성을 확인하였다.련성을 확인하였다.

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신경회로망을 이용한 Al 2024-T3 합금의 피로손상모델에 관한 연구 (A Study of Fatigue Damage Model using Neural Networks in 2024-T3 Aluminium Alloy)

  • 홍순혁;조석수;주원식
    • 한국공작기계학회논문집
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    • 제10권4호
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    • pp.14-21
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    • 2001
  • To estimate crack growth rate and cycle ratio uniquely, many investigators have developed various kinds of mechanical parameters and theories. But, thes have produced local solution space through single parameter. Neural Networks can perform patten classification using several input and output parameters. Fatigue damage model by neural networks was used to recognize the relation between da/dN/N/N(sub)f, and half-value breadth ratio B/Bo, fractal dimension D(sub)f, and fracture mechanical parameters in 2024-T3 aluminium alloy. Learned neural networks has ability to predict both crack growth rate da/dN and cycly ratio /N/N(sub)f within engineering estimated mean error(5%).

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배기가스재순환 적용에 따른 Off-road 엔진의 연료 분사 시기 전략에 관한 연구 (A Study on the Strategy of Fuel Injection Timing according to Application of Exhaust Gas Recirculation for Off-road Engine)

  • 하형수;신재식;표수강;정학섭;강정호
    • 한국자동차공학회논문집
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    • 제24권4호
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    • pp.447-453
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    • 2016
  • The reduction technologies of exhaust gas from both the off-road engine and on-road vehicles are important. It is possible to apply various combustion technologies with engines after the application of a treatment technology to this field. In this study, main injection timing, pilot injection timing, and exhaust gas recirculation (EGR) rate were selected as the experimental parameters whose effects on the emission of exhaust gases and on the fuel consumption characteristics were to be determined. In the experiment, the emission of nitrogen oxide (NOx) and Smoke, and the Torque at the same fuel consumption level, were measured. The experimental data were analyzed using the Taguchi method with an L9 orthogonal array. Additionally, analysis of variation (ANOVA) was used to confirm the influence of each parameter. Consequently, the level of each parameter was selected based on the signal-to-noise ratio data (main injection timing, 3; pilot injection timing, 3; EGR rate, 2), and the results of the Taguchi prediction were verified experimentally (error: NOx, 10.3 %; Smoke, 6.6 %; brake-specific fuel consumption (BSFC), 0.6 %).

비선형 시스템 모델링 및 제어를 위한 퍼지 규칙기반의 진화 설계 (Evolutionary Design of Fuzzy Rule Base for Modeling and Control)

  • 이창훈
    • 대한전기학회논문지:시스템및제어부문D
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    • 제50권12호
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    • pp.566-574
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    • 2001
  • In designing fuzzy models and controllers, we encounter a major difficulty in the identification f an optimized fuzzy rule base, which is traditionally achieved by a tedious trial-and-error process. This paper presents an approach to the evolutionary design of an optimal fuzzy rule base for modeling and control. Evolutionary programming is used to simultaneously evolve the structure and the parameter of fuzzy rule base for a given task. To check the effectiveness of the suggested approach, four numerical examples are examined. The performance of the identified fuzzy rule bases is demonstrated.

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Simple Neuro-Controllers for Field-Oriented Induction Motor Servo Drives

  • Fayez F. M.;Sousy, E-I;M. M. Salem
    • Journal of Power Electronics
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    • 제4권1호
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    • pp.28-38
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    • 2004
  • In this paper, the position control of a detuned indirect field oriented control (IFOC) induction motor drive is studied. A proposed Simple-Neuro-Controllers (SNCs) are designed and analyzed to achieve high-dynamic performance both in the position command tracking and load regulation characteristics for robotic applications. The proposed SNCs are trained on-line based on the back propagation algorithm with a modified error function. Four SNCs are developed for position, speed and d-q axes stator currents respectively. Also, a synchronous proportional plus integral-derivative (PI-D) two-degree-of-freedom (2DOF) position controller and PI-D speed controller are designed for an ideal IFOC induction motor drive with the desired dynamic response. The performance of the proposed SNCs and synchronous PI-D 2DOF position controllers for detuned field oriented induction motor servo drive is investigated. Simulation results show that the proposed SNCs controllers provide high-performance dynamic characteristics which are robust with regard to motor parameter variations and external load disturbance. Furthermore, comparing the SNC position controller with the synchronous PI-D 2DOF position controller demonstrates the superiority of the proposed SNCs controllers due to attain a robust control performance for IFOC induction motor servo drive system.

A Vector-Controlled PMSM Drive with a Continually On-Line Learning Hybrid Neural-Network Model-Following Speed Controller

  • EI-Sousy Fayez F. M.
    • Journal of Power Electronics
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    • 제5권2호
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    • pp.129-141
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    • 2005
  • A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

A novel reference model for dental scanning system evaluation: analysis of five intraoral scanners

  • Karakas-Stupar, Irina;Zitzmann, Nicola Ursula;Joda, Tim
    • The Journal of Advanced Prosthodontics
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    • 제14권2호
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    • pp.63-69
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    • 2022
  • PURPOSE. The aim of this in vitro study was to investigate the accuracy (trueness and precision) of five intraoral scanners (IOS) using a novel reference model for standardized performance evaluation. MATERIALS AND METHODS. Five IOSs (Medit i500, Omnicam, Primescan, Trios 3, Trios 4) were used to digitize the reference model, which represented a simplified full-arch situation with four abutment teeth. Each IOS was used five times by an experienced operator, resulting in 25 STL (Standard Tessellation Language) files. STL data were imported into 3D software (Final Surface®) and examined for inter- and intra-group analyses. Deviations in the parameter matching error were calculated. ANOVA F-test and Kruskal-Wallis test were applied for inter-group comparisons (α = .05); and the coefficient of variation (CV) was calculated for intra-group comparisons (in % ± SD). RESULTS. Primescan (matching error value: 0.015), Trios 3 (0.016), and Trios 4 (0.018) revealed comparable results with significantly higher accuracy compared to Medit i500 (0.035) and Omnicam (0.028) (P < .001). For intra-group comparison, Trios 4 demonstrated the most homogenous results (CV 15.8%). CONCLUSION. The novel reference model investigated in this study can be used to assess the performance of dental scanning technologies in the daily routine setting and in research settings.