• Title/Summary/Keyword: Uncertainty estimation

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Modeling and Uncertainty Analysis of Ballscrew Nut Stiffness (볼스크류 너트부의 강성 모델링과 불확도 해석)

  • Min, Bog-Ki;Cao, Lei;Khim, Gyungho;Park, Chun-Hong;Chung, Sung-Chong
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.5
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    • pp.415-422
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    • 2015
  • Ballscrews are important motion transfer and positioning units of industrial machinery and precision machines. Positioning accuracy of the feed drive system depends upon axial stiffness of ballscrew systems. As the nut stiffness depends upon preload and operating conditions, analytical modeling of the stiffness is performed through the contact and body deformation analysis. For accurate contact analysis, the contact angle variation between balls and grooves is incorporated in the developed model. To verify the developed mathematical stiffness model, experiments are conducted on the test-rig. Through the uncertainty analysis according to GUM (Guide to the expression of Uncertainty in Measurement), it is confirmed that the formulated stiffness model has over 85% estimation accuracy. After constructing the ballscrew DB, a quick turnaround system for the nut stiffness estimation has been developed in this research.

Reliability Design of the Natural frequency of a System based on the Samples of Uncertain Parameters (불확실한 인자 표본을 이용한 시스템 고유진동수의 신뢰성 설계)

  • Choi, Chan Kyu;Yoo, Hong Hee
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.10a
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    • pp.467-471
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    • 2014
  • The natural frequencies of a mechanical system are determined by the system parameters such as masses and stiffness of the system. Since material irregularities and manufacturing tolerances always exist in most of practical engineering situations, the system parameters always have uncertainties. As the uncertainties of the parameters increase, the uncertainties of the system natural frequencies also increases. Then, the reliability of the system deteriorates. So, the uncertainty of the system natural frequencies should be analyzed accurately and considered in the design of the system. In order to analyze the uncertainty of the system natural frequencies employing most of existing uncertainty analysis methods, the probability distributions of the uncertain system parameters should be identified. In most practical situations, however, identification of the probability distributions is almost impossible because of limited time and cost. For that case, the reliability should be estimated based on finite samples of the system parameters. In this paper, sample based reliability estimation method employing extreme value theory was proposed. Using the proposed estimation method, sample based reliability design of the system natural frequencies was conducted.

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Incorporation of IMM-based Feature Compensation and Uncertainty Decoding (IMM 기반 특징 보상 기법과 불확실성 디코딩의 결합)

  • Kang, Shin-Jae;Han, Chang-Woo;Kwon, Ki-Soo;Kim, Nam-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.6C
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    • pp.492-496
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    • 2012
  • This paper presents a decoding technique for speech recognition using uncertainty information from feature compensation method to improve the speech recognition performance in the low SNR condition. Traditional feature compensation algorithms have difficulty in estimating clean feature parameters in adverse environment. Those algorithms focus on the point estimation of desired features. The point estimation of feature compensation method degrades speech recognition performance when incorrectly estimated features enter into the decoder of speech recognition. In this paper, we apply the uncertainty information from well-known feature compensation method, such as IMM, to the recognition engine. Applied technique shows better performance in the Aurora-2 DB.

Uncertainty analysis of containment dose rate for core damage assessment in nuclear power plants

  • Wu, Guohua;Tong, Jiejuan;Gao, Yan;Zhang, Liguo;Zhao, Yunfei
    • Nuclear Engineering and Technology
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    • v.50 no.5
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    • pp.673-682
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    • 2018
  • One of the most widely used methods to estimate core damage during a nuclear power plant accident is containment radiation measurement. The evolution of severe accidents is extremely complex, leading to uncertainty in the containment dose rate (CDR). Therefore, it is difficult to accurately determine core damage. This study proposes to conduct uncertainty analysis of CDR for core damage assessment. First, based on source term estimation, the Monte Carlo (MC) and point-kernel integration methods were used to estimate the probability density function of the CDR under different extents of core damage in accident scenarios with late containment failure. Second, the results were verified by comparing the results of both methods. The point-kernel integration method results were more dispersed than the MC results, and the MC method was used for both quantitative and qualitative analyses. Quantitative analysis indicated a linear relationship, rather than the expected proportional relationship, between the CDR and core damage fraction. The CDR distribution obeyed a logarithmic normal distribution in accidents with a small break in containment, but not in accidents with a large break in containment. A possible application of our analysis is a real-time core damage estimation program based on the CDR.

Calibration and uncertainty analysis of integrated surface-subsurface model using iterative ensemble smoother for regional scale surface water-groundwater interaction modeling

  • Bisrat Ayalew Yifru;Seoro Lee;Woon Ji Park;Kyoung Jae Lim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.287-287
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    • 2023
  • Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.

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A Study on the Uncertainty Estimation of Flowmeter Calibrator with Two Master Flowmeters (2개의 기준유량계를 이용한 유량계 교정장치의 측정불확도 평가에 관한 연구)

  • Choi Jong Oh;Lee Woan Kyu;Lim Ki Won
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.28 no.10
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    • pp.1219-1230
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    • 2004
  • Comparing to the gravimetric and volumetric method, the flowmeter calibration based on the master meter method is relatively economical and convenient, especially for high flowrate. The uncertainty of flow quantity and flowrate using the master meter method was evaluated according to the GUM (Guide to the Expression of Uncertainty in Measurement). In order to apply for the wider flow range, two master meters (electromagnetic flow meter) were employed as reference flowmeters. The uncertainty of the master meter was obtained by combining the statistical variation of the repeated measurements and the variation of fluid density and pipe material due to temperature and pressure changes were scrutinized. for a practical application, the uncertainty of calibrator, whose measuring capacity of 1000 ㎥/h obtained by employing two 500 ㎥/h electromagnetic How meters, was evaluated. The uncertainty budget shows the quantitative contribution of each uncertainty component to the overall uncertainty of the calibrator. As a result, it was found that the dominant uncertainties were from the master meter, which was evaluated statistically, and from the process of least squares fitting. On the contrary, the uncertainties arising from the variation of the fluid density and the pipe volume due to the temperature and pressure were negligible.

Expected Annual Damage Estimation with Uncertainty (불확실성을 고려한 연피해 기대치 산정)

  • Kim, Hung Soo;Kim, Yoo Jin;Lee, Ji-Won
    • Journal of Wetlands Research
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    • v.5 no.1
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    • pp.41-52
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    • 2003
  • The flood damage reduction studies have been performed by the channel improvement plan and the levee has mainly constructed with the freeboard concept. However, the freeboard concept might be an inappropriate choice as a safety factor of the levee because many uncertainties are involved in the procedure of the channel improvement plan studies. So, we considered the uncertainties In the discharge-probability, stage-discharge, and stage-damage functions and estimate the expected annual damage. The Monte Carlo technique for uncertainty analysis is used. As our results, the expected annual damage with uncertainty shows the larger value than without uncertainty. Since the expected annual damage with uncertainty already considers the safety factor it is the proper result. However, the expected annual damage without uncertainty does not consider the safety factor yet. Thus, if the expected annual damage without uncertainty considers the freeboard concept, it could be compared with the expected annual damage with uncertainty for the evaluation of the overestimation or underestimation of the levee construction.

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Important measure analysis of uncertainty parameters in bridge probabilistic seismic demands

  • Song, Shuai;Wu, Yuan H.;Wang, Shuai;Lei, Hong G.
    • Earthquakes and Structures
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    • v.22 no.2
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    • pp.157-168
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    • 2022
  • A moment-independent importance measure analysis approach was introduced to quantify the effects of structural uncertainty parameters on probabilistic seismic demands of simply supported girder bridges. Based on the probability distributions of main uncertainty parameters in bridges, conditional and unconditional bridge samples were constructed with Monte-Carlo sampling and analyzed in the OpenSees platform with a series of real seismic ground motion records. Conditional and unconditional probability density functions were developed using kernel density estimation with the results of nonlinear time history analysis of the bridge samples. Moment-independent importance measures of these uncertainty parameters were derived by numerical integrations with the conditional and unconditional probability density functions, and the uncertainty parameters were ranked in descending order of their importance. Different from Tornado diagram approach, the impacts of uncertainty parameters on the whole probability distributions of bridge seismic demands and the interactions of uncertainty parameters were considered simultaneously in the importance measure analysis approach. Results show that the interaction of uncertainty parameters had significant impacts on the seismic demand of components, and in some cases, it changed the most significant parameters for piers, bearings and abutments.

A Covariance Matrix Estimation Method for Position Uncertainty of the Wheeled Mobile Robot

  • Doh, Nakju Lett;Chung, Wan-Kyun;Youm, Young-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1933-1938
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    • 2003
  • A covariance matrix is a tool that expresses odometry uncertainty of the wheeled mobile robot. The covariance matrix is a key factor in various localization algorithms such as Kalman filter, topological matching and so on. However it is not easy to acquire an accurate covariance matrix because we do not know the real states of the robot. Up to the authors knowledge, there seems to be no established result on the covariance matrix estimation for the odometry. In this paper, we propose a new method which can estimate the covariance matrix from empirical data. It is based on the PC-method and shows a good estimation ability. The experimental results validate the performance of the proposed method.

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Sensorless Control of Permanent Magnet Synchronous Motors with Compensation for Parameter Uncertainty

  • Yang, Jiaqiang;Mao, Yongle;Chen, Yangsheng
    • Journal of Electrical Engineering and Technology
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    • v.12 no.3
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    • pp.1166-1176
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    • 2017
  • Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.