• Title/Summary/Keyword: Online estimation

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Stochastic Model based Fault Diagnosis System of Induction Motors using Online Probability Density Estimation (온라인 확률분포 추정기법을 이용한 확률모델 기반 유도전동기의 고장진단 시스템)

  • Cho, Hyun-Cheol;Kim, Kwang-Soo;Lee, Kwon-Soon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.10
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    • pp.1847-1853
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    • 2008
  • This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

Online Probability Density Estimation of Nonstationary Random Signal using Dynamic Bayesian Networks

  • Cho, Hyun-Cheol;Fadali, M. Sami;Lee, Kwon-Soon
    • International Journal of Control, Automation, and Systems
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    • v.6 no.1
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    • pp.109-118
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    • 2008
  • We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

High accuracy online 3D-reconstruction by multiple cameras

  • Oota, Yoshikazu;Pan, Yaodong;Furuta, Katuhisa
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1749-1752
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    • 2005
  • For online high accurate reconstruction of an object from an visual information, a linear reconstruction method for multiple images is popular. Basically this method needs many cameras or many different screen shots from different view points. This method, however, has the benefit of less calculation and is adequate for a real time application by comparing other popular method. In this paper, online reconstruction system using more than three cameras is treated. An evaluation method of cameras' position, and of the number is derived for the linear reconstruction method. To decrease errors that are caused from skew of lens, positional error between corresponding points is taken into consideration on the evaluation. The proposed evaluation method enables estimation of the adequate number of cameras and then of feasible view locations. Additionally, repeating search of epipolar lines enables estimation of the hidden point. Comparing with result of an average error analysis, it was confirmed that the proposed methods works effectively.

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Online DCIR Estimation for Series-connected Battery Cells using Matrix-Switched Capacitor Converter

  • La, Phuong-Ha;Choi, Sung-Jin
    • Proceedings of the KIPE Conference
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    • 2020.08a
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    • pp.381-382
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    • 2020
  • In the battery energy storage system, battery cells are connected in series to increase the operating voltage. Due to the difference in characteristics, the performance degradation of cells is dissimilar. This paper proposes an online DC internal impedance estimation for battery cells in the series string using a matrix-switched capacitor converter, which is already verified as useful for the series balancing of the cells. The simulation in the hardware in the loop test rig shows good accuracy and the feasibility of the proposed method.

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Fault Detection and Diagnosis Systems of Induction Machines using Real-Time Stochastic Modeling Approach (실시간 확률 모델링 기법을 이용한 유도기기의 고장검출 및 진단시스템)

  • Lee, Jin-Woo;Kim, Kwang-Soo;Cho, Hyun-Cheol;Lee, Young-Jin;Lee, Kwon-Soon
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.3
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    • pp.241-248
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    • 2009
  • This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

A Coupled Recursive Total Least Squares-Based Online Parameter Estimation for PMSM

  • Wang, Yangding;Xu, Shen;Huang, Hai;Guo, Yiping;Jin, Hai
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2344-2353
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    • 2018
  • A coupled recursive total least squares (CRTLS) algorithm is proposed for parameter estimation of permanent magnet synchronous machines (PMSMs). TLS considers the errors of both input variables and output ones, and thus achieves more accurate estimates than standard least squares method does. The proposed algorithm consists of two recursive total least squares (RTLS) algorithms for the d-axis subsystem and q-axis subsystem respectively. The incremental singular value decomposition (SVD) for the RTLS obtained by an approximate calculation with less computation. The performance of the CRTLS is demonstrated by simulation and experimental results.

Online SNR Estimation for Turbo Coded Multicode DS/SS Systems

  • Takizawa, Ken-ichi;Shigenobu Sasaki;Jie Zhou;Shogo Muramatsu;Hisakazu Kikuchi
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1316-1319
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    • 2002
  • In this paper, an online SNR estimator is derived for turbo coded multicode DS/SS systems in Nakagami fading channels. The multicode DS/SS approach is one of promising solutions to obtain higher-rate data transmission in DS/SS technologies. Turbo coding has paid much attention because of the significant improvements on error rate performances in various communication systems including multicode DS/SS systems. However, in the turbo decoding, channel state information, especially signal-to-noise ratio (SNR) at the correlator outputs, is desired in order to obtain such improvements. We evaluate the accuracy of the derived SNR estimation. It is shown that the bit error rate performance using our SNR estimation is close to the performance with perfect knowledge of channel state information.

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Online Capacitance Estimation of DC-Link Capacitors using AC Voltage Injection in AC/DC/AC PWM Converters

  • Abo-Khalil Ahmed G.;Lee Dong-Choon
    • Proceedings of the KIPE Conference
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    • 2006.06a
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    • pp.381-383
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    • 2006
  • A novel online capacitance estimation method for a DC-link capacitor in a three-phase AC/DC/AC PWM converter is proposed. A controlled AC voltage with a lower frequency than the line frequency is Injected into the DC-link voltage, which then causes AC power ripples at the DC output side. By extracting the AC voltage and power components on the DC output side using digital filters, the capacitance can then be calculated using the recursive least squares method. The proposed method can be simply implemented with only software and no additional hardware. Experimental results confirm that the estimation error is less than 0.2%.

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An Exploratory Study on the New Product Demand Curve Estimation Using Online Auction Data

  • Shim Seon-Young;Lee Byung-Tae
    • Management Science and Financial Engineering
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    • v.11 no.3
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    • pp.125-136
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    • 2005
  • As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

Throughput-efficient Online Relay Selection for Dual-hop Cooperative Networks

  • Lin, Yuan;Li, Bowen;Yin, Hao;He, Yuanzhi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.6
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    • pp.2095-2110
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    • 2015
  • This paper presents a design for a throughput-efficient online relay selection scheme for dual-hop multi-relay cooperative networks. Problems arise with these networks due to unpredictability of the relaying link quality and high time-consumption to probe the dual-hop link. In this paper, we firstly propose a novel probing and relaying protocol, which greatly reduces the overhead of the dual-hop link estimation by leveraging the wireless broadcasting nature of the network. We then formulate an opportunistic relay selection process for the online decision-making, which uses a tradeoff between obtaining more link information to establish better cooperative relaying and minimizing the time cost for dual-hop link estimation to achieve higher throughput. Dynamic programming is used to construct the throughput-optimal control policy for a typically heterogeneous Rayleigh fading environment, and determines which relay to probe and when to transmit the data. Additionally, we extend the main results to mixed Rayleigh/Rician link scenarios, i.e., where one side of the relaying link experiences Rayleigh fading while the other has Rician distribution. Numerical results validate the effectiveness and superiority of our proposed relaying scheme, e.g., it achieves at least 107% throughput gain compared with the state of the art solution.