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    Estimating an optimal setpoint to lessen errors in filling weighing system based on Kalman filtering
    (2014-01-01)
    Sinchai, Sakkarin
    ;
    Saechia, Sukkharak
    ;
    Limpiti, Tulaya
    ;
    Koseeyaporn, Jeerasuda
    ;
    Wardkein, Paramote
    A weighing system in which a sensor is not mounted to a discharger especially in vertical filling gives rise to an excess of weight added to the given target of weight. In addition, the excess is not constant on account of some factors, such as vibration of the machine, flow of the substance, and cycle time of the system. These factors cause the surplus to oscillate. To overcome this problem, Kalman filtering is performed to predict the optimal setpoint to meet the defined target. To illustrate the performance of the proposed technique, the resulting outcome is compared with that of using the conventional statistical method. The results have shown that the proposed approach has significantly increased the speed and lowered the error. It is pointed out that the proposed algorithm may be preferable to the traditional statistical technique due to its effectiveness and its simple implementation. © 2014 IEEE.
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    Air-gap power and rotor loss estimation for induction motor efficiency monitoring based on Kalman filtering
    (2013-01-01)
    Jirasuwankul, N.
    ;
    Manop, C.
    This paper presents a technique of induction motor's efficiency monitoring based on air-gap power and rotor loss estimation by Kalman filtering. A simplified model of three phase induction motor, with equivalent circuit of five elements, has been tested by the proposed technique with varying load torque and power to represent practical operations. Good agreement between the simulation and experimental results are found in a normal operating range of load torque and power. © 2013 IEEE.
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    Evaporative estimation using data fusion
    (2008-12-01)
    Roengruen, P.
    ;
    Tipsuwannaporn, V.
    ;
    Numsomran, A.
    ;
    Harnnarong, Sh
    This paper present evaporative estimation of water using data fusion technique. There are many factors in evaporative locating process that provided for consideration together. So this paper will be study about factors with concerning in meteorology that influential to evaporation and explained about relation of these factors by statistical method. The used data obtained from Thai Meteorological Department which collects daily data for the environment with various sensors. The results of data fusion process will be shown value of daily evaporation that provided to comparing between the evaporative value of pan evaporation and calculated by hydrology formula. © 2008 SICE.
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    Speckle noise estimation with generalized gamma distribution
    (2006-12-01)
    Intajag, Sathit
    ;
    Chitwong, Sakreya
    Speckle noise is an inherent property of a synthetic aperture radar (SAR) image, and it generally tends to reduce the image resolution and contrast. The speckle noise estimation is an important prerequisite, whenever SAR image is used for object segmentation. Among the many methods in statistical description that have been proposed to perform the estimation, there exists a class of approaches that use a multiplicative model of speckled image formation, such as Rayleigh distribution, K-distribution, Weibull distribution etc. In this paper, generalized gamma (GG) distribution is used to estimate the noise characteristics. GG distribution is especially attractive because it contains several distributions as special cases, viz. Rayleigh, exponential, Weibull, and log-normal. The major parameter of the GG distribution is estimated according to maximum likelihood (ML) principle. The proposed method works successfully when the solution is located in the parameter space. For verifying the performance of the proposed scheme compared to the other methods, we use a χ<sup>2</sup> goodness-of-fit (GOF) test. © 2006 ICASE.