• Title/Summary/Keyword: Estimation method

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A Study on the Development of New State Estimation Algorithm by the Decomposition Method of Linear Transformation (선형변환분할 기법에 의한 새로운 상태추정 앨고리즘 개발에 관한 연구)

  • 송길영;김영한;최상규
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.35 no.4
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    • pp.148-155
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    • 1986
  • This paper presents a new decoupled power system state estimation method. The decoupling is achieved via simple linear transformation on power measurements in contrast with the modified fast decoupled state estimation method which assumes decoupling by direct negligence of the off-diagonal blocks of the observation functions. The new estimation method is compared with the modified decoupled state estimation method against IEEE-14 bus model power system and 25 bus model power system in several system conditions. It is observed that the proposed method shows better convergence performance and filtering performance than a modified fast decoupled state estimation.

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A Power Estimation Method for ASIPs Considering Data Types of Variables in Application Programs

  • Kim, Tsutomu ura;Shibahara, Shin-ichi;Yoshinori Takeuchi;Masaharu Imai;Akira Kitajima;Michiaki Muraoka
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.387-390
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    • 2000
  • This paper proposes an efficient and accurate power estimation method for Application Specific Instruction set Processors (ASIPs). Proposed method takes advantage of the data types of variables in application program to be executed on the ASIP. According to the experimental results, the efficiency of proposed method was more than 1000 times as high as that of conventional RTL based power estimation method, and the estimation error was within 10% compared to a conventional gate-level accurate power estimation method

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Battery State-of-Health Estimation Method based on Deep-learning and Feature Engineering (딥러닝과 특징 추출 기반 배터리 노화 상태 추정 방법)

  • Chang, Moon-Seok;Lee, Gang-Seok;Bae, Sungwoo
    • The Transactions of the Korean Institute of Power Electronics
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    • v.27 no.4
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    • pp.332-338
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    • 2022
  • This study proposes a battery state-of-health estimation method by applying a feature extraction technique. The technique that can improve estimation performance is the process of identifying and extracting meaningful data. To apply a data-driven-based aging state estimation method to batteries, health indicators are used as training data. However, limitations occur in extracting health indicators from charge/discharge cycles. This study proposes a deep-learning-based battery state-of-health estimation method that applies feature extraction techniques to compensate for this problem. According to the performance evaluation result of the proposed method, it has a low estimation error of 0.3887% based on an absolute error evaluation method.

Pose-graph optimized displacement estimation for structural displacement monitoring

  • Lee, Donghwa;Jeon, Haemin;Myung, Hyun
    • Smart Structures and Systems
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    • v.14 no.5
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    • pp.943-960
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    • 2014
  • A visually servoed paired structured light system (ViSP) was recently proposed as a novel estimation method of the 6-DOF (Degree-Of-Freedom) relative displacement in civil structures. In order to apply the ViSP to massive structures, multiple ViSP modules should be installed in a cascaded manner. In this configuration, the estimation errors are propagated through the ViSP modules. In order to resolve this problem, a displacement estimation error back-propagation (DEEP) method was proposed. However, the DEEP method has some disadvantages: the displacement range of each ViSP module must be constrained and displacement errors are corrected sequentially, and thus the entire estimation errors are not considered concurrently. To address this problem, a pose-graph optimized displacement estimation (PODE) method is proposed in this paper. The PODE method is based on a graph-based optimization technique that considers entire errors at the same time. Moreover, this method does not require any constraints on the movement of the ViSP modules. Simulations and experiments are conducted to validate the performance of the proposed method. The results show that the PODE method reduces the propagation errors in comparison with a previous work.

Factors for Speech Signal Time Delay Estimation (음성 신호를 이용한 시간지연 추정에 미치는 영향들에 관한 연구)

  • Kwon, Byoung-Ho;Park, Young-Jin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.8
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    • pp.823-831
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    • 2008
  • Since it needs the light computational load and small database, sound source localization method using time delay of arrival(TDOA method) is applied at many research fields such as a robot auditory system, teleconferencing and so on. Researches for time delay estimation, which is the most important thing of TDOA method, had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Silverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time. Also, we define the performance index(PI) to show a similar tendency to R/D ratio, and propose the method to improve the performance of time delay estimation with PI.

Comparison Study of Parameter Estimation Methods for Some Extreme Value Distributions (Focused on the Regression Method) (극단치 분포의 모수 추정방법 비교 연구(회귀 분석법을 기준으로))

  • Woo, Ji-Yong;Kim, Myung-Suk
    • Communications for Statistical Applications and Methods
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    • v.16 no.3
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    • pp.463-477
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    • 2009
  • Parameter estimation methods such as maximum likelihood estimation method, probability weighted moments method, regression method have been popularly applied to various extreme value models in numerous literature. Among three methods above, the performance of regression method has not been rigorously investigated yet. In this paper the regression method is compared with the other methods via Monte Carlo simulation studies for estimation of parameters of the Generalized Extreme Value(GEV) distribution and the Generalized Pareto(GP) distribution. Our simulation results indicate that the regression method tends to outperform other methods under small samples by providing smaller biases and root mean square errors for estimation of location parameter of the GEV model. For the scale parameter estimation of the GP model under small samples, the regression method tends to report smaller biases than the other methods. The regression method tends to be superior to other methods for the shape parameter estimation of the GEV model and GP model when the shape parameter is -0.4 under small and moderately large samples.

Robust 2D human upper-body pose estimation with fully convolutional network

  • Lee, Seunghee;Koo, Jungmo;Kim, Jinki;Myung, Hyun
    • Advances in robotics research
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    • v.2 no.2
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    • pp.129-140
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    • 2018
  • With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

A dynamic finite element method for the estimation of cable tension

  • Huang, Yonghui;Gan, Quan;Huang, Shiping;Wang, Ronghui
    • Structural Engineering and Mechanics
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    • v.68 no.4
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    • pp.399-408
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    • 2018
  • Cable supported structures have been widely used in civil engineering. Cable tension estimation has great importance in cable supported structures' analysis, ranging from design to construction and from inspection to maintenance. Even though the Bernoulli-Euler beam element is commonly used in the traditional finite element method for calculation of frequency and cable tension estimation, many elements must be meshed to achieve accurate results, leading to expensive computation. To improve the accuracy and efficiency, a dynamic finite element method for estimation of cable tension is proposed. In this method, following the dynamic stiffness matrix method, frequency-dependent shape functions are adopted to derive the stiffness and mass matrices of an exact beam element that can be used for natural frequency calculation and cable tension estimation. An iterative algorithm is used for the exact beam element to determine both the exact natural frequencies and the cable tension. Illustrative examples show that, compared with the cable tension estimation method using the conventional beam element, the proposed method has a distinct advantage regarding the accuracy and the computational time.

An Improved Grid Impedance Estimation using PQ Variations (PQ변동을 이용한 개선된 계통 임피던스 추정기법)

  • Cho, Je-Hee;Kim, Yong-Wook;Kim, Rae-Young
    • The Transactions of the Korean Institute of Power Electronics
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    • v.20 no.2
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    • pp.152-159
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    • 2015
  • In a weak grid condition, the precise grid impedance estimation is essential to guaranteeing the high performance current control and power transfer for a grid-connected inverter. This study proposes a precise estimation method for grid impedance by PQ variations by employing the variation method of reference currents. The operation principle of grid impedance estimation is fully presented, and the negative impact of the phase locked loop is analyzed. Estimation error by a synchronization angle in the park's transformation using the phase locked loop is derived. As a result, the variation method of reference currents for accurate estimation is introduced. The validation of the proposed method is verified through several simulation results and experiments based on a 2-kW voltage source inverter prototype.

A Comparison of the Reliability Estimation Accuracy between Bayesian Methods and Classical Methods Based on Weibull Distribution (와이블분포 하에서 베이지안 기법과 전통적 기법 간의 신뢰도 추정 정확도 비교)

  • Cho, HyungJun;Lim, JunHyoung;Kim, YongSoo
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.4
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    • pp.256-262
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    • 2016
  • The Weibull is widely used in reliability analysis, and several studies have attempted to improve estimation of the distribution's parameters. least squares estimation (LSE) or Maximum likelihood estimation (MLE) are often used to estimate distribution parameters. However, it has been proven that Bayesian methods are more suitable for small sample sizes than LSE and MLE. In this work, the Weibull parameter estimation accuracy of LSE, MLE, and Bayesian method are compared for sample sets with 3 to 30 data points. The Bayesian method was most accurate for sample sizes under 25, and the accuracy of the Bayesian method was similar to LSE and MLE as the sample size increased.